The yield of SNP microarray analysis for fetal ultrasound cardiac abnormalities

The yield of SNP microarray analysis for fetal ultrasound cardiac abnormalities | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The yield of SNP microarray analysis for fetal ultrasound cardiac abnormalities Fenlei Ye, Xiayuan Xu, Yi Wang, Lifang Chen, Qunda Shan, Fan Jin, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3325051/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Apr, 2024 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted 13 You are reading this latest preprint version Abstract Objective This study aimed to evaluate the effectiveness of single nucleotide polymorphism microarray (SNP-Array) in the etiological diagnosis of fetal cardiac ultrasound abnormalities. Methods A total of 2092 pregnant women who underwent prenatal diagnosis from 2017 to 2022 were included in the study and divided into four groups based on the presence of ultrasound structural abnormalities and the type of abnormality. The results of the SNP-Array test in amniotic fluids in different groups were analyzed. Results The non-CHD had the highest incidence of aneuploidy, overall chromosomal abnormalities, and trisomy 18, showing significant statistical differences compared to the other groups(p＜0.001). In terms of CNV segment size distribution frequency, there was no statistical difference between the isolated congenital heart defect group and the non-isolated congenital heart defect group (p＞0.05). The occurrence rates of 22q11.2 and 15q11.2 were also not statistically different between the isolated congenital heart defect group and the non-isolated congenital heart defect group (p＞0.05). Conclusion SNP-Array improves the ability to detect of abnormal CNVs in CHD fetuses, providing valuable assistance in diagnosing chromosomal etiology and genetic counseling. single nucleotide polymorphism microarray congenital heart disease copy number variation prenatal diagnosis Figures Figure 1 Introduction Congenital heart disease (CHD) is the most common congenital birth defect, affecting approximately 1% of all births 1 . The prevalence of CHD has continued to increase globally since 2009 2 . CHD is defined as abnormal development of the cardiovascular system and is characterized by one or more structural heart defects at birth. Although the survival rates of CHD patients have improved due to pediatric cardiovascular surgery and cardiac interventional catheterization, CHD remains the leading cause of death from a congenital anomaly within the first 4 years of life 3 . Consequently, preconception counseling regarding prenatal screening and the risk of recurrence is urgently needed for CHD patients of reproductive age and women who have previously conceived CHD fetuses. CHD pathogenesis is known to be multifactorial, with genetic factors playing a significant role in its etiology. A recent study has found that approximately 40% of CHD cases are caused by genetic factors, 5% by environmental variables, and the remaining 55% by unknown factors 4 . Chromosomal abnormalities, copy number variants (CNVs), and single gene disorders comprise the majority of genetic contributions to CHD. Initial studies have shown that trisomy 21, trisomy 18, trisomy 13, and monosomy X are the most common chromosomal aneuploidies in infants with CHD 5 . With the evolution of detection platforms in recent years, there is evidence that genome-wide rare CNVs represent a significant contributor to CHD susceptibility. CNVs are defined as the gain or loss of genomic material that is 1 kb or larger between individuals of the same species. CNVs can present deletions, duplications, segmental duplications, insertions, inversions, and translocations. Robust studies have shown that 22q11.2 deletion syndrome (Del22q11) is estimated to exhibit a prevalence of 50% in interrupted aortic arch type B, 33% in truncus arteriosus, 15% in tetralogy of Fallot (TOF), and 5–10% in ventricular septal defect (VSD) 6 , 7 . The deletion or haploinsufficiency of the T-Box transcription factor TBX1 within the 22q11.2 region is closely associated with the cardio-pharyngeal phenotype. Recently, emerging genomic hotspots including 1q21.1, 2q13, 8p23.1, 11q24, 15q11.2, 16p11.2, and 22q11.2 are enriched in CHD cohorts 8 . However, the reduced penetrance and variable phenotype expressivity of some likely pathogenic CNVs have made the prenatal diagnosis of CHD challenging. Single nucleotide polymorphism array (SNP-Array) is an effective method for detecting CNVs in the genome with high sensitivity for submicroscopic abnormalities. In previous studies, SNP arrays have been conducted to investigate the etiology of CHD 9 , 10 . However, due to the varied cohorts and control settings in previous studies, the correlation of the detected pathogenic CNVs for CHD differed slightly. Therefore, additional studies are required to emphasize the value of CNV screening as a tool for prenatal CHD diagnosis. In this study, we analyzed a total of 1056 fetuses, including 90 fetuses with isolated heart defects, 36 fetuses with non-isolated heart defects, 319 fetuses with other congenital defects excluding CHD, and 611 fetuses with normal sonographic findings. The objective of this study was to demonstrate the significance of SNP-based chromosomal microarray analysis in investigating the etiology of CHD fetuses. Materials and Methods Participants A total of 2092 pregnant women who underwent prenatal diagnosis at the prenatal diagnosis center of Lishui Maternal and Child Health Hospital and Jinhua Maternal and Child Health Hospital from January 2017 to December 2022 were included in the study. According to ultrasound examination results and the presence of fetal structural abnormalities and types of abnormalities, the participants were categorized into four groups: isolated CHD group(170 cases with only fetal heart abnormalities), non-isolated CHD group(68 cases with both fetal heart abnormalities and extracardiac abnormalities, including soft markers), non-CHD group (538 cases with other fetal structural abnormalities, including soft markers, but without fetal heart abnormalities), and control group (1316 cases with no fetal structural abnormalities detected by ultrasound)(Figure 1 ). The amniotic fluid from the fetuses in each group was analyzed through chromosomal karyotyping and SNP-Array testing, followed by retrospective analysis. The inclusion criteria for the control group were as follows: singleton pregnancy that is naturally conceived, and the presence of any one or more of the following conditions: 1) high-risk chromosomal abnormality detected through maternal serum biochemical or high-throughput non-invasive prenatal screening; 2) previous history of fetal birth defects; 3) maternal age of 35 years or older. Exclusion criteria include consanguineous marriage, family history of hereditary disease, and pregnant women who received allogeneic blood transfusion, transplantation surgery, or immunotherapy within one year. All pregnant women signed an informed consent form, and this study was approved by the ethics committee of Lishui Maternal and Child Health Hospital and Jinhua Maternal and Child Health Hospital. Methods Ultrasound Examination Diagnostic criteria: Diagnosis was performed using the International Society of Ultrasound in Obstetrics and Gynecology guidelines 11 , 12 in various planes. The types of fetal heart defects were classified based on the International Pediatric and Congenital Heart Disease Code (IPCCC) and International Classification of Diseases 11th Revision (ICD-11) 13 . At least two ultrasound physicians with prenatal diagnosis qualifications made the diagnoses. Amniocentesis and SNP-Array Testing Chromosome analysis and microarray analysis were performed on amniotic fluid samples from all fetuses. Under real-time ultrasound guidance, 30ml of amniotic fluid was extracted, and 20ml of amniotic fluid was used for chromosome sample preparation for karyotyping analysis. Meanwhile, 10ml of amniotic fluid was used for SNP-Array testing, which was performed using the AffymetrixCytoScan 750K chip provided by Affymetrix, USA. SNP-array result interpretation The ChAs software (Thermo Fisher, Affymetrix, USA) was utilized to interpret the detection results based on multiple databases, including the Database of Genomic Variants ( http://projects.tcag.ca/variation/ ), DECIPHER ( http://decipher.sanger.ac.uk/ ); ClinVar ( https://www.ncbi.nlm.nih.gov/clinvar/ ); and Online Mendelian Inheritance in Man ( http://www.ncbi.nlm.nih.gov/omim ). Cases with copy number gains or losses involving the entire chromosome were defined as aneuploid, while deletions greater than 100kb and duplications greater than 200kb were considered CNV. The qualitative assessment of CNV was classified according to the American College of Medical Genetics and Genomics (ACMG) guidelines, including pathogenic, likely pathogenic, and variants of uncertain significance 14 . The occurrence rates and distribution segments of aneuploid, pathogenic, likely pathogenic, and variants of uncertain significance CNVs among the four groups were compared to provide information for the SNP-array detection technology in the etiology of fetal CHD. Statistical analysis The data processing was conducted using SPSS version 25.0 (IBM Corporation, Armonk, NY, USA). For normally distributed continuous variables, one-way analysis of variance (ANOVA) followed by post hoc pairwise comparisons were performed. For non-normally distributed variables or variables with unequal variances, nonparametric multiple sample tests, such as the Kruskal-Wallis test followed by post hoc pairwise comparisons, were used. The chi-square test was used for the comparison of categorical variables among multiple groups, and p < 0.05 was considered statistically significant. Results Demographical characteristic The age and gestational weeks of the four groups of pregnant women showed non-normal distribution. For the isolated CHD group, the maternal ages ranged from 17 to 44 years, and the gestational weeks ranged from 16 to 28 weeks. For the non-isolated congenital heart group, the maternal ages ranged from 18 to 42 years, and the gestational weeks ranged from 16 to 31 weeks. For the non-CHD group, the maternal ages ranged from 19 to 46 years, and the gestational weeks ranged from 16 to 32 weeks. For the control group, the maternal ages ranged from 18 to 46 years, and the gestational weeks ranged from 17 to 32 weeks. Table 1 displays the demographic and diagnostic information of the four groups. There were no statistically significant differences observed in age and ultrasound-diagnosed gestational weeks among the four groups ( p = 0.610, 0.151). Table 1 Maternal age and gestational weeks of four groups(Mean ± SD ) Total Age Diagnosis of gestational week Isolated CHD group 170 31.12 ± 5.01 21.69 ± 2.81 Non-isolated CHD group 68 31.09 ± 5.66 21.94 ± 3.48 Non-CHD group 538 31.03 ± 5.51 21.47 ± 3.29 Control group 1316 31.60 ± 6.91 21.24 ± 2.44 P -value 0.610 0.151 Incidence of aneuploidy and CNV segments with various properties The incidence of aneuploidy, pathogenic CNVs, likely pathogenic CNVs, and variants of uncertain significance CNVs in the four groups are shown in Table 2 . Concerning the incidence of aneuploidy, the non-isolated CHD group displays the highest rate, with significant statistical differences observed when compared to the isolated CHD group (27.9% vs. 3.5%, p < 0.001), the non-CHD group (27.9% vs. 8.6%, p < 0.001), and the control group (27.9% vs. 5.9%, p < 0.001). In terms of the incidence of pathogenic CNVs and 22q11.2, no statistically significant differences were found between the isolated CHD group and the non-isolated CHD group (8.2% vs. 14.7%, p = 0.134), (2.9% vs. 4.4%, p = 0.865), respectively. The incidence of overall chromosomal abnormalities in the non-isolated CHD group was highest, with significant statistical distinctions compared to the isolated CHD group (42.6% vs. 14.1%, p < 0.001), the non-CHD group (42.6% vs. 14.9%, p < 0.001), and the control group (42.6% vs. 9.4%, p < 0.001). Regarding the incidence of variants of uncertain significance CNVs, there were no statistically significant differences between the isolated CHD group and the non-isolated CHD group (8.2% vs. 8.8%, p = 0.883). Table 2 The incidence of aneuploidy, pathogenic, likely pathogenic, and variants of uncertain significance CNVs in four groups of pregnant women (%) n aneuploidy Pathogenic CNVs Likely pathogenic CNVs Total known pathogenic and likely pathogenic findings variants of uncertain significance CNVs 22q11.2 Other Total Isolated CHD group 170 6(3.5) 5(2.9) 9(5.3) 14(8.2) 0(0) 20(11.8) 14(8.2) Non-isolated CHD group 68 19(27.9) 3(4.4) 7(10.3) 10(14.7) 0(0) 29(42.6) 6(8.8) Non-CHD group 538 46(8.6) 2(0.4) 28(5.2) 30(5.6) 2(0.4) 78(14.5) 28(5.2) Control group 1316 78(5.9) 5(0.4) 37(2.8) 42(3.2) 3(0.4) 123(9.3) 41(3.1) P -value ＜0.001 ＜0.001 0.005 ＜0.001 ＜0.001 0.031 Distribution of aneuploidy The distribution of aneuploidy is listed in Table 3 . Regarding the incidence of trisomy 21, statistically significant differences were observed only between the non-CHD group and the control group ( p = 0.003), with no significant differences noted among the other groups. For trisomy 18, the non-isolated CHD group exhibited the highest incidence rate, showing significant statistical significance when compared to the isolated CHD group (16.2% vs. 1.2%, p < 0.001), the non-CHD group (16.2% vs. 1.5%, p < 0.001), and the control group (16.2% vs. 0.5%, p < 0.001). No statistical differences were found between the isolated CHD group and the non-CHD group or the control group. In terms of trisomy 13, a statistically significant difference was observed between the non-isolated CHD group and the non-CHD group (4.4% vs. 0.4%, p = 0.008). Table 3 The distribution of aneuploidy in four groups of pregnant women (%) n Trisomy 21 Trisomy 18 Trisomy 13 Other aneuploidies Isolated CHD group 170 4(2.4) 2(1.2) 0 0 Non-isolated CHD group 68 4(5.9) 11(16.2) 3(4.4) 1(1.5) Non-CHD group 538 28(5.2) 8(1.5) 2(0.4) 8(1.5) Control group 1316 33(2.5) 6(0.5) 0 39(3.0) P -value 0.021 < 0.001 Distribution frequency of CNV fragment sizes The frequency of CNV fragment sizes was compared among four groups, including pathogenic CNVs, likely pathogenic CNVs, and variants of uncertain significance CNVs, as shown in Table 4 . Regarding the distribution frequency of CNVs < 1Mb, statistically significant differences were observed only between the non-heart group and the control group ( p = 0.002). There was no statistically significant difference between the isolated CHD group and the non-isolated CHD group (4.7% vs. 5.9%, p = 0.963). For CNVs with a distribution frequency of 1-4Mb, statistically significant differences were found between the isolated CHD group, the non-isolated CHD, and the control group (7.1% vs. 3.3%, p = 0.014; 9.1% vs. 3.3%, p = 0.031). However, there was no statistically significant difference between the isolated CHD group and the non-isolated CHD group (7.1% vs. 9.1, p = 0.598). In terms of CNVs with a distribution frequency ≥ 5Mb, the non-isolated CHD group exhibited the highest frequency, but there was no statistically significant difference between the non-isolated CHD group and the isolated CHD group (8.8% vs. 4.7%, p = 0.360). However, statistically significant differences were observed between the non-isolated CHD group and the non-CHD group ( p = 0.003), as well as the control group ( p < 0.001). Table 4 Compares the distribution frequencies of CNV fragment sizes among four groups of pregnant women(%) n ＜1Mb 1-4Mb ≥ 5Mb Isolated CHD group 170 8(4.7) 12(7.1) 8(4.7) Non-isolated CHD group 68 4(5.9) 6(8.8) 6(8.8) Non-CHD group 538 25(4.6) 25(4.6) 10(1.9) Control group 1316 27(2.1) 43(3.3) 16(1.2) P -value 0.008 0.030 < 0.001 The distribution profiles of pathogenic CNVs in the four groups As seen in Table 5 , the isolated CHD group comprised two large segmental duplications: partial trisomy and Xq28 duplication syndrome, four cases of large segmental deletions (7.2 ~ 12.3Mb), one case of < 4Mb duplication (Cat eye syndrome), and seven cases of < 4Mb deletion, of which four 22q11.2 microdeletion syndrome, one 12q14 microdeletion syndrome, Del(19p13.2), and 15q11.2 BP1-BP2 microdeletion. The non-isolated CHD group comprised three cases of large segment duplications(13.37 ~ 47.7Mb), two cases of large segment deletions(10.1 ~ 14.9Mb), and five cases of deletions ＜4Mb. Among these, one 15q11.2 microdeletion, and three 22q11.2 microdeletion syndrome. The non-CHD group had three cases of large segment duplications(12.7 ~ 22.6Mb), six cases of large segment deletions (6.3 ~ 19.1Mb), sixteen cases of deletions, and five cases of duplication＜4Mb. Among these, known microduplications/microdeletions as 15q11.2 BP1-BP2 microdeletion, 16p11.2 microdeletion/microduplication syndrome, Potocki-Lupski syndrome, 22q11.2 deletion/duplication syndrome, and Leri-Weill dyschondrostosis (LWD)-SHOX deletion. The control group included three cases of large segment duplications(8.1 ~ 22.5Mb), twelve cases of large segment deletions(5.4 ~ 25.7Mb), and twenty-seven cases of microdeletions/microduplications. Among these, known CNVs included 1q21.1 recurrent microduplication, 7q11.23 duplication syndrome, 15q11.2 BP1-BP2 microdeletion, 16p11.2 microduplication syndrome, 22q11.2 deletion/duplication syndrome, Cat eye syndrome, and others. Table 5 Distribution of pathogenic CNV in the four groups Isolated CHD group Non-isolated CHD group Non-CHD group Control group Correspondence syndrome Del(1q43q44) (9.8Mb) 1q43q44 deletion syndrome Del(1q21.1q21.2)(5.4Mb) 1q21.1 recurrent microdeletion Dup(1q21.1q21.2)(1.8Mb) 1q21.1 recurrent microduplication Dup(1q21.1q21.2)(2.1Mb) 1q21.1 recurrent microduplication Del(2q14.2q22.3)(25.0Mb) Del(2p25.3)(2.6Mb) Del(2p25.1p24.2)(5.8Mb) Dup(2p25.3p21)(41.1Mb) Del(2q37.1q37.3)(9.3Mb) Del(3p26.3p25.3)(11.5Mb) Dup(4p16.3p14)(39.7Mb) Partial 4p trisomy Del(4p16.3p15.31)(19.1Mb) Del(4p16.3p15.32)(16.3Mb) Wolf-Hirschhorn syndrome Del(4p16.3p15.33)(13.5Mb) Wolf-Hirschhorn syndrome Del(5p15.33p14.1)(25.7Mb) Dup(5q35.2q35.3)(1.9Mb) Del(5q35.3)(3.1Mb) Del(5q35.2q35.3)(2.1Mb) Del(6q26q27)(8.4Mb) Del(6p24.3)(526.6Kb) Dup(7q11.23)(1.4Mb) 7q11.23 duplication syndrome Del(7q11.23)(1.5Mb) Dup(8q22.1q24.3)(47.7Mb) Del(8p23.3p23.1)(10.2Mb) Del(8p23.3p23.1)(8.2Mb) Dup(9p24.3p21.3)(22.5Mb) Del(10p15.3p14)(10.1Mb) Del(10q23.31)(1.0Mb) Dup(10q25.3q26.3)(19.0Mb) Del(10q26.13q26.3)(10.8Mb) 10q26 deletion syndrome Dup(11p12p11.12)(12.7Mb) Del(11p14.3p13)(10.4Mb) Del(11q24.2q25)(7.2Mb) Del(11q24.1q25)(12.3Mb) Del(12q14.3q15)(3.14Mb) 12q14 microdeletion syndrome Dup(12p13.33p12.1)(22.6Mb) Del(13q13.3q14.3)(14.5Mb) Dup(14q22.1q23.3)(13.37Mb) Del(15q11.2)(512.3Kb) Del15q11.2)(507.0Kb) Del(15q11.2)(855.3Kb) Del(15q11.2)(855.4Kb) 15q11.2 BP1-BP2 microdeletion Del(15q11.2)(855.3Kb) 15q11.2 BP1-BP2 microdeletion Del(15q11.2)(512.4Kb) 15q11.2 BP1-BP2 microdeletion Del(15q11.2)(311.8Kb) 15q11.2 BP1-BP2 microdeletion Del(15q11.2)(855.3Kb) 15q11.2 BP1-BP2 microdeletion Del(15q11.2)(507.0Kb) 15q11.2 BP1-BP2 microdeletion Del(16p11.2)(749.9Kb) 16p11.2 microdeletion syndrome Del(16p11.2)(309.5Kb) 16p11.2 microdeletion syndrome Del(16p11.2)(622.7Kb) 16p11.2 microdeletion syndrome Del(16p11.2)(301.9Kb) 16p11.2 microdeletion syndrome Dup(16P11.2)(226.7Kb) Dup(16p11.2)(585.1Kb) 16p11.2 microduplication syndrome Dup(16P11.2)(598.7Kb) Dup(16p11.2)(585.2Kb) 16p11.2 microduplication syndrome Del(16p13.12p12.3)(2.1Mb) Dup(17p11.2)(3.7Mb) Potocki-Lupski syndrome Del(18p11.32p11.21)(14.9Mb) Del(18p11.32p11.21)(14.9Mb) Partial 18p monosomy Del(18q21.31q23)(22.2Mb) Del(19p13.2)(2.1M) Dup(21q21.2q22.13)(14.8Mb) Dup(21q22.2q22.3)(8.1Mb) Del(21q22.3)(1.6Mb) Del(22q11.21)(3.1Mb) Del(22q11.21)(2.8Mb) Del(22q11.1q11.21)(3.8Mb) Del(22q11.21)(744.1Kb) 22q11.2 deletion syndrome Del(22q11.21)(3.1Mb) Del(22q11.21)(3.1Mb) Del(22q11.21)(2.8Mb) 22q11.2 deletion syndrome Del(22q11.21q11.22)(1.1Mb) Del(22q11.21)(2.9Mb) Del(22q11.21)(3.2Mb) 22q11.2 deletion syndrome Del(22q11.21)(3.2Mb) 22q11.2 deletion syndrome Dup(22q11.21)(2.8Mb) Dup(22q11.21)(2.8Mb) 22q11.2 duplication syndrome Dup(22q11.1q11.21)(1.6Mb) Dup(22q11.1q11.21)(2.1Mb) Cat eye syndrome Del(22q12.1)(213.4Kb) Del(22q13.32q13.33)(2.5Mb) Del(Yq11.221q11.23)(10.5Mb) AZFb + AZFc deletion Del(Yq11.223q11.23)(3.5Mb) AZFc deletion Del(Xp21.1)(272.1Kb) Del(Xp21.1)(271.3Kb) Del(Xp22.31)(1.2Mb) Steroid sulphatase deficiency(STS) Del(Xp22.31)(1.6Mb) Steroid sulphatase deficiency(STS) Del(Xp22.31)(1.6Mb) Steroid sulphatase deficiency(STS) Del(Xp22.31)(1.6Mb) Steroid sulphatase deficiency(STS) Del(Xp22.31)(1.7Mb) Steroid sulphatase deficiency(STS) Del(Xp22.31)(1.7Mb) Steroid sulphatase deficiency(STS) Del(Xp22.31)(1.7Mb) Steroid sulphatase deficiency(STS) Del(XP22.33)(3.9Mb) Del(Xp22.33)(742.6Kb) Leri-Weill dyschondrostosis (LWD) - SHOX deletion Del(Xp22.33p22.31)(6.3Mb) Leri-Weill dyschondrostosis (LWD) - SHOX deletion Dup(Xq27.2q28)(13.1Mb) Xq28 duplication syndrome Distribution profile of likely pathogenic CNVs in the four groups From Table 6 , it can be observed that in the non-CHD group, there was one case each of duplication and deletion CNV. In the control group, there was one case of a large segment duplication and two cases of microdeletions. Table 6 Distribution of likely pathogenic CNV in the four groups Isolated CHD group Non-isolated CHD group Non-CHD group Control group Dup(4p16.3p16.1)(10.7Mb) Dup(11p15.5p15.4)(5.1Mb) Del(16p12.2)(600.7Kb) Del(16p12.2)(600.6Kb) Del(20p13)(981.6Kb) Distribution variants of uncertain significance CNVs in four groups As seen in Table 7 , it is evident that in the isolated CHD group, there were six cases of microdeletions and eight cases of microduplications. In the non-isolated CHD group, all six cases were duplications, with one case being a large segment duplication. In the non-CHD group, there are twenty-one cases of microduplications and seven cases of microdeletions. In the control group, there were 23 cases of microduplications and eighteen cases of microdeletions. Table 7 Distribution variants of uncertain significance CNVs in the four groups Isolated CHD group Non-isolated CHD group Non-CHD group Control group Dup(1q21.1)(576.0Kb) Dup(1q21.1)(385.9Kb) Del(1q24.3q25.1)(2.3Mb) Dup(2p12)(1.4Mb) Dup(2p16.1p15)(1.6Mb) Del(2p21)(151.7Kb) Dup(2p25.3)(1.0Mb) Del(2q13)(106.4Kb) Del(2q13)(103.5Kb) Del(2q13)(871.1Kb) Del(2q13)(482.1Kb) Del(2q13)(482.1Kb) Del(2q13)(103.5Kb) Del(2q13)(1.7Mb) Del(2q13)(1.7Mb) Dup(2q12.3q13)(2.4Mb) Dup(3p14.2)(1.6Mb) Dup(3p24.1p23)(4.0Mb) Del(3p25.3)(128.7Kb) Dup(3q23q24)(5.18Mb) Dup(3q25.32)(568.0Kb) Dup(4p16.1)(1.9Mb) Del(4p16.2)(1.0Mb) Del(4q34.3)(3.3Mb) Del(4q35.2)(1.3Mb) Dup(5q23.1q23.2)(4.4Mb) Dup(5q35.3)(1.6Mb) Del(6p21.31)(1.8Mb) Dup(6q14.1)(823.2Kb) Del(6q26)(188.7Kb) Dup(6q15)(627.8Kb) Del(6q26)(241.4Kb) Dup(6q25.3q26)(1.2Mb) Dup(7p14.1)(1.3Mb) Dup(7p21.1)(613.9Kb) Dup(7p21.3)(1.1Mb) Dup(7p22.3)(789.6Kb) Del(7q32.1)(294.0Kb) Dup(8p21.3)(2.1Mb) Del(8p23.1)(143.8Kb) Dup(8p23.2)(1.3Mb) Dup(8p23.3p23.2)(2.7Mb) Dup(8p23.2)(2.2Mb) Del(8p23.2)(1.1Mb) Del(8q11.21)(1.7Mb) Del(9p24.1)(197.9Kb) Dup(9p24.3p24.1)(5.3Mb) Dup(9p24.3)(686.3Kb) Dup(9q31.1)(1.2Mb) Del(10q21.3)(312.3Kb) Del(10q21.3)(1.3Mb) Dup(11p14.3p14.1)(4.4Mb) Del(12q21.32)(1.2Mb) Dup(13q12.12)(1.4Mb) Del(13q33.1q33.2)(1.8Mb) Del(14q22.1q22.2)(3.1Mb) Dup(15q13.3)(422.4Kb) Dup(15q13.1q13.2)(1.5Mb) Dup(16p13.11)(1.6Mb) Dup(16p13.11) (926.6Kb) Dup(16p13.11)(827.3Kb) Dup(16p13.11) (796.4Kb) Dup(16p13.11) (1.2Mb) Dup(16p13.11) (1.6Mb) Dup(16p13.11) (796.4Kb) Dup(16p13.2p13.13)(486.1Kb) Dup(16p13.3)(1.0Mb) Dup(16q11.2q12.1)(640.9Kb) Dup(16q12.1)(480.0Kb) Dup(16q22.2)(607.2Kb) Del(16q23.1)(260.2Kb) Dup(17p11.2q11.1)(3.7Mb) Dup(17p13.3)(836.1Kb) Del(17p13.3)(624.6Kb) Dup(17q22)(1.0Mb) Dup(18p11.32p11.23)(7.8Mb) Dup(18p11.32)(1.6Mb) Dup(20q12)(1.4Mb) Dup(21q11.3)(731.9Kb) Del(21q21.1)(1.9Mb) Dup(21q21.1)(1.2Mb) Dup(22q11.23)(1.3Mb) Dup(22q11.23)(1.3Mb) Dup(22q11.23)(1.3Mb) Dup(Xp22.31)(125.8Kb) Dup(Xp22.31)(1.6Mb) Dup(Xp22.31)(543.7Kb) Dup(Xp22.33)(392.7Kb) Dup(Xq22.1)(599.2Kb) Discussion In recent years, chromosomal imbalances observed under the microscope have been considered a significant contributor to CHD 7 . This study used fetal ultrasound imaging to establish isolated CHD, non-isolated CHD, non-CHD, and control groups and described the distribution and frequency of CNVs in each group to evaluate the feasibility of SNP array in identifying the etiology of CHD fetuses. The overall detection rate of abnormal CNVs in isolated CHD and non-isolated CHD groups was 8.2% (14/170) and 14.7% (10/68), respectively, while in the non-CHD and control groups, the rates were 5.6% (30/538) and 3.2% (42/1316). Previous studies have shown that the detection rate of chromosomal microarrays for congenital heart disease ranges from 4–20% 15 , while another study reported detection rates of 6% for ultrasound abnormalities and approximately 1.7% for non-ultrasound structural abnormalities in older women and those with positive results in chromosomal screening 16 . Compared to previous studies, this research exhibits a similar detection rate for fetal congenital heart defects and other ultrasound structural abnormalities. However, the detection rate for cases without ultrasound structural abnormalities is slightly higher. This difference may be attributed to variations in the array platform used, the resolution of the array, and the reporting practices of individual clinical laboratories. Additionally, as new literature and public data sharing contribute to an expanding understanding of genomic regions associated with specific diseases, annual reviews of the same dataset have led to an increase in disease-associated cases to 1.8% while reducing the number of cases classified as variants of uncertain significance to 0.9% 17 . A recent meta-analysis of 45 studies revealed that the overall prevalence of chromosomal abnormalities in isolated congenital heart defects (CHD) and non-isolated CHD was 16% and 37%, respectively. Among non-isolated CHD cases, the prevalence of aneuploidy (19%), other CNVs (excluding 22q11) (4%), and trisomy 18 were higher than in isolated CHD cases 18 . Our study demonstrated that the overall prevalence of chromosomal abnormalities in the isolated CHD group and non-isolated CHD group is 11.8% and 42.6%, respectively. Comparative analysis showed that the non-isolated CHD group has the highest prevalence of aneuploidy and overall chromosomal abnormalities, with statistically significant differences compared to the isolated CHD group, non-CHD group, and control group. The non-isolated CHD group had the highest prevalence of T18, and there was no statistically significant difference in the prevalence of T21 compared to the isolated CHD group, consistent with the meta-analysis. However, there was no statistically significant difference between the non-isolated CHD group and isolated CHD group (14.7% vs. 8.2%, p = 0.134) in prevalence of pathogenic CNV, and even after excluding 22q11, the non-isolated CHD group still showed no statistically significant difference in pathogenic CNV prevalence compared to the isolated CHD group (10.3% vs. 5.3%, p = 0.269), which differs from the meta-analysis. Furthermore, our study found that the prevalence of aneuploidy cases and pathogenic CNVs was slightly higher than in the meta-analysis, possibly due to differences in the number of subjects included in each group. The traditional chromosomal karyotype resolution is typically in the range of 5-10Mb. Our research indicates that there was no statistically significant difference in the distribution frequency of pathogenic CNVs and variants of uncertain significance CNVs between isolated and non-isolated CHD groups. The significance of CNV segment size typically depends on their location in the genome and the genes or non-coding regions they contain. Smaller CNV segments may have localized effects on gene expression, which could impact an individual's phenotype and disease risk. Larger CNV segments may affect multiple genes, thus influencing various phenotypes and disease risks 19 . Some studies suggest that the etiology of isolated CHD is multifactorial, with some cases being attributed to single genes. Non-isolated CHD is associated with various causes, including chromosomal and sub-chromosomal abnormalities, single-gene syndromes, epigenetic factors, and environmental influences 15 . The results of our study show that in the non-CHD group, pathogenic CNVs larger than 10Mb account for 50% of the cases. These larger segments may be considered partial aneuploidy, and non-CHD with multiple systemic developmental abnormalities are more likely to manifest as chromosomal abnormality syndromes. In contrast, isolated CHD identified by ultrasound is more likely to be caused by smaller chromosomal segments or gene variations. In the four groups of pathogenic CNVs, we identified a total of 15 cases involving the 22q11.2 region, including 11 deletions and 4 duplications. The 22q11.2 microdeletion is currently recognized as a syndrome associated with congenital heart defects, with severity ranging from non-survivable to subclinical, or even without a CHD phenotype. The main known causative gene for this syndrome is TBX1. The 22q11.2 microduplication syndrome complements the 22q11.2 microdeletion syndrome, sharing common features but exhibiting considerable phenotypic variation, with a CHD occurrence rate of approximately 25% 20, 21 . Furthermore, we observed one case each of 22q11.1q11.21 microduplication in the isolated congenital heart defect group and the control group. This region encompasses a critical area within the 22q11.21 recurrent region (Cat Eye Syndrome, CES). However, it does not involve the 22q11.2 region associated with DiGeorge syndrome/Velocardiofacial syndrome (DGS/VCFS) 22 . Upon pairwise comparison, we found that the occurrence rate of 22q11.2 abnormalities in the isolated CHD group and the non-isolated CHD group did not exhibit statistically significant differences (2.9% vs. 4.4%, p = 0.865), consistent with some previous reports 18 , 23 . However, both the isolated and non-isolated CHD groups had higher occurrence rates than the non-CHD group ( p = 0.012, p = 0.008) and the control group ( p = 0.001, p = 0.001). This study identified 3 cases of 22q11.2 microdeletion and 2 cases of microduplication in the control group without ultrasound structural abnormalities. This may be related to the lack of obvious neurological and psychiatric characteristics in the prenatal stage and the absence of typical facial features. Additionally, among the four groups, a total of 9 cases involved the 15q11.2. The occurrence rates were as follows: isolated CHD group 0.6% (1/170), non-isolated CHD group 1.5% (1/68), non-CHD group 1.1% (6/538), and control group 0.1% (1/1316). After pairwise comparisons, there were no statistically significant differences between the isolated CHD group and the non-isolated CHD group (p = 0.522). The nature of the 15q11.2 BP1-BP2 microdeletion has been a subject of controversy. Its prevalence in CMA-tested populations is approximately 0.57%-1.27% 24 . Clinical phenotypes are mainly associated with neurodevelopmental disorders, developmental and language delays, and autism spectrum disorders, with a relatively low penetrance of 10–12% 25 . The 15q11.2 BP1-BP2 microdeletion encompasses four highly conserved non-imprinted genes, NIPA1, NIPA2, CYFIP1, and TUBGCP5. Currently, there is no established independent connection between this microdeletion and heart morphology. Some studies suggested that the 15q11.2 BP1-BP2 microdeletion has a relative frequency of 3.4% in intellectual disability, 2% in schizophrenia, and 2.1% in epilepsy, with no increased risk of cardiac malformation or autism, making it of limited clinical significance, and it has been suggested to be classified as a "mildly pathogenic factor." 26 . In 2015, the UK Genomic Medicine Committee even proposed not to report the 15q11.2 BP1-BP2 microdeletion in prenatal diagnosis 27 . However, a recent study by the Williams team indicated an increased risk of cardiovascular malformation associated with the 15q11.2 BP1-BP2 microdeletion, with cardiovascular malformation being more common but not necessarily severe 25 . In our study, both isolated and non-isolated CHD groups had 15q11.2 microdeletion, and both exhibited ventricular septal defects, which aligns with the findings by Williams et al. In the non-CHD group, four cases of 15q11.2 microdeletion only showed increased nuchal translucency on ultrasound. In variants of uncertain significance CNVs, small segmental duplications were predominant across the four groups. It was observed that 2q13 was involved in all four groups, with eight cases of microdeletions and one case of microduplication in total. The pathogenic nature of 2q13 is not well understood. Several studies have indicated that duplications and deletions of 2q13 are risk factors for developmental delay and anomalies. Wolfe’s research found an increased prevalence of attention deficit hyperactivity disorder (ADHD) in individuals with defects associated with the 2q13 locus, with 30% of defect carriers having heart defects, whereas no defects were observed in carriers of duplications 28 . Other researchers have noted that with chromosome 2q13 phenotypes, deletions are more enriched in cardiovascular disease, while duplications are associated with craniofacial features 29 . In our study, two cases of 2q13 deletion were found in individuals with CHD, and both were isolated cases. Their phenotypes were complete transposition of the great arteries with pulmonary artery stenosis and anomalous origin of the right pulmonary artery with pulmonary artery stenosis, which aligns with the above results. Since 2q13 can also be present in the normal population and given the current lack of large-sample data, further research may be needed to explore the pathogenic genes and phenotypes associated with heart defects. Additionally, we also observed that the isolated CHD group had a Dup(9p24.3p24.1), the control group had a Dup(9p24.3), the non-isolated CHD group had a Dup(16q11.2q12.1), and the non-CHD group had a Dup(16q12.1), all of which involved partially overlapping regions. The 9p24.3 duplication segment contains genes like DOCK8 and may be associated with autism spectrum disorders, intellectual disabilities/developmental delay, and other conditions. However, whether the 9p24.3p24.1 segment is related to congenital heart disease phenotypes has not been reported in the literature 30 . All four groups of CNVs involved chromosome 16, but the specific segments affected were different. Chromosome 16 is one of the most enriched chromosomes for segmental duplications, and 16p is one of the more unstable regions in the genome, with over 10% of the 16p euchromatic regions consisting of highly complex low-copy repeats 31 , 32 . The shared regions affected by CNVs in the non-isolated CHD group and the non-CHD group have rare clinical phenotypes reported in the literature. This suggests that, apart from genetic factors, other factors such as environmental influences may also play a role. Study limitation The study has a large overall sample size, but it still had limitations. The number of samples involving CHD is relatively small, especially for non-CHD. Ultrasound has certain limitations, and some cases with mild neurodevelopmental or craniofacial abnormalities may be challenging to classify into specific groups. Fetal and other associated symptoms may become more apparent as gestational weeks progress. Additionally, the study lacked parental validation and follow-up data. Conclusion In summary, SNP microarrays can effectively improve the diagnostic rate of abnormal CNVs in fetal congenital heart defects (CHD). This not only highlights CNVs as important pathogenic factors in CHD but also aids in the chromosome-based diagnosis of such children and provides guidance for their family planning. Both isolated and non-isolated CHD exhibit a variety of genetic variations, including common microdeletion/microduplication syndromes, chromosomal syndromes, and more. These variations represent differences in the phenotypic expression of various chromosomal abnormality syndromes and also reflect the limitations of prenatal ultrasound diagnosis in distinguishing between isolated and non-isolated cases. Further research into the mechanisms underlying congenital heart defects will require more in-depth phenotypic observations combined with detailed molecular genetics, metabolic studies, epigenetics, and other analyses. Declarations Author Contributions : Data curation, Fenglei Ye; Funding acquisition, Qijing Wang; Investigation, Fenglei Ye; Project administration, Xiayuan Xu; Resources, Xiayuan Xu, Yi Wang, Lifang Chen, and Qunda Shan; Supervision, Xiayuan Xu and Yi Wang; Writing – original draft, Fenglei Ye; Writing – review & editing, Qijing Wang and Fan Jin. All authors read and approved the final manuscript. Funding: This study was supported by the National Natural Science Foundation of China (no. 82201843), and the Jinhua City Science and Technology Research Program Project (no.2020-4-068). Institutional Review Board Statement: The study was approved by the Institutional Ethics Committee of the Lishui Maternal and Child Health Hospital and Jinhua Maternal and Child Health Hospital (approval no. 2020-KY-003). All participants understood the content and purpose of this study and signed an informed consent form before enrollment. Informed Consent Statement: All participants understood the content and purpose of this study and signed an informed consent form before enrollment. Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflicts of interest. Availability of Data and Materials: The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. References Global Burden of Disease, Study C. 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Cite Share Download PDF Status: Published Journal Publication published 05 Apr, 2024 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted Editorial decision: Revision requested 19 Dec, 2023 Reviews received at journal 28 Nov, 2023 Reviews received at journal 21 Nov, 2023 Reviewers agreed at journal 13 Nov, 2023 Reviewers agreed at journal 13 Nov, 2023 Reviews received at journal 10 Nov, 2023 Reviewers agreed at journal 30 Oct, 2023 Reviewers agreed at journal 29 Oct, 2023 Reviewers invited by journal 19 Oct, 2023 Editor assigned by journal 19 Oct, 2023 Editor invited by journal 26 Sep, 2023 Submission checks completed at journal 26 Sep, 2023 First submitted to journal 04 Sep, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3325051","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":236029174,"identity":"d01dc0c8-0335-4e52-aaca-0b47b5bb3119","order_by":0,"name":"Fenlei Ye","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fenlei","middleName":"","lastName":"Ye","suffix":""},{"id":236029175,"identity":"9700e691-1d82-4e00-b233-bdfb59a2bf76","order_by":1,"name":"Xiayuan Xu","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiayuan","middleName":"","lastName":"Xu","suffix":""},{"id":236029176,"identity":"2973a774-a3a4-4862-87fb-5fedd6b6bb92","order_by":2,"name":"Yi Wang","email":"","orcid":"","institution":"Lishui Maternal and Child Health Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Wang","suffix":""},{"id":236029177,"identity":"85f7c8fa-9c02-47d9-ba41-8f6254cc9531","order_by":3,"name":"Lifang Chen","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lifang","middleName":"","lastName":"Chen","suffix":""},{"id":236029178,"identity":"54db55d9-da51-4bee-b43f-6273c57f93d4","order_by":4,"name":"Qunda Shan","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qunda","middleName":"","lastName":"Shan","suffix":""},{"id":236029179,"identity":"229a2164-8032-45bc-a7b5-5225249186a2","order_by":5,"name":"Fan Jin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYBACxmYGhg8MDDYMjA1AHg+RWhhnMDCkkaAFpAuo5TCESZQW5nbegw0/d5y3Z56RwPjgbRuDvDlhh/ElNvaeuc3MOCOB2XBuG4PhzgaCWnjMH/C23WYDamGT5m1jSDA4QFiLYePftnM8QC3sv4nW0szbdkACZAsz8Vpk25INGHseNkvOOSdhuIGQFsP+M4aNb9vs7A3bkw9+eFNmI0/QFsMGOAMcmRIE1AOBPAZjFIyCUTAKRgE6AABdLzwHdO9E4gAAAABJRU5ErkJggg==","orcid":"","institution":"Zhejiang University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Fan","middleName":"","lastName":"Jin","suffix":""},{"id":236029180,"identity":"c77c7b41-59e2-4612-a7d0-dc18f6b1c145","order_by":6,"name":"Qijing Wang","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qijing","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2023-09-04 15:44:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3325051/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3325051/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12884-024-06428-9","type":"published","date":"2024-04-05T15:01:34+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":44037211,"identity":"c3450e93-a76d-4f36-bf75-c1dbf62d8d75","added_by":"auto","created_at":"2023-10-03 18:07:15","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":43535,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart for study inclusion describing how the patient cohort was derived.\u003c/p\u003e","description":"","filename":"chartflow.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3325051/v1/ec908eeebdc5bedef6ae4813.jpg"},{"id":54303880,"identity":"e6155579-d2e1-4680-9b6b-75da6d620392","added_by":"auto","created_at":"2024-04-08 15:12:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":608602,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3325051/v1/9b07a223-7587-4226-81a9-d34f9db0d506.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The yield of SNP microarray analysis for fetal ultrasound cardiac abnormalities","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCongenital heart disease (CHD) is the most common congenital birth defect, affecting approximately 1% of all births\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The prevalence of CHD has continued to increase globally since 2009\u003csup\u003e2\u003c/sup\u003e. CHD is defined as abnormal development of the cardiovascular system and is characterized by one or more structural heart defects at birth. Although the survival rates of CHD patients have improved due to pediatric cardiovascular surgery and cardiac interventional catheterization, CHD remains the leading cause of death from a congenital anomaly within the first 4 years of life\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Consequently, preconception counseling regarding prenatal screening and the risk of recurrence is urgently needed for CHD patients of reproductive age and women who have previously conceived CHD fetuses.\u003c/p\u003e \u003cp\u003eCHD pathogenesis is known to be multifactorial, with genetic factors playing a significant role in its etiology. A recent study has found that approximately 40% of CHD cases are caused by genetic factors, 5% by environmental variables, and the remaining 55% by unknown factors\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Chromosomal abnormalities, copy number variants (CNVs), and single gene disorders comprise the majority of genetic contributions to CHD. Initial studies have shown that trisomy 21, trisomy 18, trisomy 13, and monosomy X are the most common chromosomal aneuploidies in infants with CHD\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. With the evolution of detection platforms in recent years, there is evidence that genome-wide rare CNVs represent a significant contributor to CHD susceptibility. CNVs are defined as the gain or loss of genomic material that is 1 kb or larger between individuals of the same species. CNVs can present deletions, duplications, segmental duplications, insertions, inversions, and translocations. Robust studies have shown that 22q11.2 deletion syndrome (Del22q11) is estimated to exhibit a prevalence of 50% in interrupted aortic arch type B, 33% in truncus arteriosus, 15% in tetralogy of Fallot (TOF), and 5\u0026ndash;10% in ventricular septal defect (VSD)\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. The deletion or haploinsufficiency of the T-Box transcription factor TBX1 within the 22q11.2 region is closely associated with the cardio-pharyngeal phenotype. Recently, emerging genomic hotspots including 1q21.1, 2q13, 8p23.1, 11q24, 15q11.2, 16p11.2, and 22q11.2 are enriched in CHD cohorts\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. However, the reduced penetrance and variable phenotype expressivity of some likely pathogenic CNVs have made the prenatal diagnosis of CHD challenging.\u003c/p\u003e \u003cp\u003eSingle nucleotide polymorphism array (SNP-Array) is an effective method for detecting CNVs in the genome with high sensitivity for submicroscopic abnormalities. In previous studies, SNP arrays have been conducted to investigate the etiology of CHD\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. However, due to the varied cohorts and control settings in previous studies, the correlation of the detected pathogenic CNVs for CHD differed slightly. Therefore, additional studies are required to emphasize the value of CNV screening as a tool for prenatal CHD diagnosis. In this study, we analyzed a total of 1056 fetuses, including 90 fetuses with isolated heart defects, 36 fetuses with non-isolated heart defects, 319 fetuses with other congenital defects excluding CHD, and 611 fetuses with normal sonographic findings. The objective of this study was to demonstrate the significance of SNP-based chromosomal microarray analysis in investigating the etiology of CHD fetuses.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eA total of 2092 pregnant women who underwent prenatal diagnosis at the prenatal diagnosis center of Lishui Maternal and Child Health Hospital and Jinhua Maternal and Child Health Hospital from January 2017 to December 2022 were included in the study. According to ultrasound examination results and the presence of fetal structural abnormalities and types of abnormalities, the participants were categorized into four groups: isolated CHD group(170 cases with only fetal heart abnormalities), non-isolated CHD group(68 cases with both fetal heart abnormalities and extracardiac abnormalities, including soft markers), non-CHD group (538 cases with other fetal structural abnormalities, including soft markers, but without fetal heart abnormalities), and control group (1316 cases with no fetal structural abnormalities detected by ultrasound)(Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The amniotic fluid from the fetuses in each group was analyzed through chromosomal karyotyping and SNP-Array testing, followed by retrospective analysis.\u003c/p\u003e \u003cp\u003eThe inclusion criteria for the control group were as follows: singleton pregnancy that is naturally conceived, and the presence of any one or more of the following conditions: 1) high-risk chromosomal abnormality detected through maternal serum biochemical or high-throughput non-invasive prenatal screening; 2) previous history of fetal birth defects; 3) maternal age of 35 years or older. Exclusion criteria include consanguineous marriage, family history of hereditary disease, and pregnant women who received allogeneic blood transfusion, transplantation surgery, or immunotherapy within one year. All pregnant women signed an informed consent form, and this study was approved by the ethics committee of Lishui Maternal and Child Health Hospital and Jinhua Maternal and Child Health Hospital.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMethods\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eUltrasound Examination\u003c/h2\u003e \u003cp\u003eDiagnostic criteria: Diagnosis was performed using the International Society of Ultrasound in Obstetrics and Gynecology guidelines\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e in various planes. The types of fetal heart defects were classified based on the International Pediatric and Congenital Heart Disease Code (IPCCC) and International Classification of Diseases 11th Revision (ICD-11)\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. At least two ultrasound physicians with prenatal diagnosis qualifications made the diagnoses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eAmniocentesis and SNP-Array Testing\u003c/h2\u003e \u003cp\u003eChromosome analysis and microarray analysis were performed on amniotic fluid samples from all fetuses. Under real-time ultrasound guidance, 30ml of amniotic fluid was extracted, and 20ml of amniotic fluid was used for chromosome sample preparation for karyotyping analysis. Meanwhile, 10ml of amniotic fluid was used for SNP-Array testing, which was performed using the AffymetrixCytoScan 750K chip provided by Affymetrix, USA.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSNP-array result interpretation\u003c/h2\u003e \u003cp\u003eThe ChAs software (Thermo Fisher, Affymetrix, USA) was utilized to interpret the detection results based on multiple databases, including the Database of Genomic Variants (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://projects.tcag.ca/variation/\u003c/span\u003e\u003cspan address=\"http://projects.tcag.ca/variation/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), DECIPHER (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://decipher.sanger.ac.uk/\u003c/span\u003e\u003cspan address=\"http://decipher.sanger.ac.uk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); ClinVar (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/clinvar/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/clinvar/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); and Online Mendelian Inheritance in Man (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ncbi.nlm.nih.gov/omim\u003c/span\u003e\u003cspan address=\"http://www.ncbi.nlm.nih.gov/omim\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Cases with copy number gains or losses involving the entire chromosome were defined as aneuploid, while deletions greater than 100kb and duplications greater than 200kb were considered CNV. The qualitative assessment of CNV was classified according to the American College of Medical Genetics and Genomics (ACMG) guidelines, including pathogenic, likely pathogenic, and variants of uncertain significance\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The occurrence rates and distribution segments of aneuploid, pathogenic, likely pathogenic, and variants of uncertain significance CNVs among the four groups were compared to provide information for the SNP-array detection technology in the etiology of fetal CHD.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe data processing was conducted using SPSS version 25.0 (IBM Corporation, Armonk, NY, USA). For normally distributed continuous variables, one-way analysis of variance (ANOVA) followed by post hoc pairwise comparisons were performed. For non-normally distributed variables or variables with unequal variances, nonparametric multiple sample tests, such as the Kruskal-Wallis test followed by post hoc pairwise comparisons, were used. The chi-square test was used for the comparison of categorical variables among multiple groups, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eDemographical characteristic\u003c/h2\u003e \u003cp\u003eThe age and gestational weeks of the four groups of pregnant women showed non-normal distribution. For the isolated CHD group, the maternal ages ranged from 17 to 44 years, and the gestational weeks ranged from 16 to 28 weeks. For the non-isolated congenital heart group, the maternal ages ranged from 18 to 42 years, and the gestational weeks ranged from 16 to 31 weeks. For the non-CHD group, the maternal ages ranged from 19 to 46 years, and the gestational weeks ranged from 16 to 32 weeks. For the control group, the maternal ages ranged from 18 to 46 years, and the gestational weeks ranged from 17 to 32 weeks. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e displays the demographic and diagnostic information of the four groups. There were no statistically significant differences observed in age and ultrasound-diagnosed gestational weeks among the four groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.610, 0.151).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMaternal age and gestational weeks of four groups(Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD )\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDiagnosis of gestational week\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsolated CHD group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.12\u0026thinsp;\u0026plusmn;\u0026thinsp;5.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.69\u0026thinsp;\u0026plusmn;\u0026thinsp;2.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-isolated CHD group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.09\u0026thinsp;\u0026plusmn;\u0026thinsp;5.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.94\u0026thinsp;\u0026plusmn;\u0026thinsp;3.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-CHD group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.03\u0026thinsp;\u0026plusmn;\u0026thinsp;5.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.47\u0026thinsp;\u0026plusmn;\u0026thinsp;3.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.60\u0026thinsp;\u0026plusmn;\u0026thinsp;6.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.24\u0026thinsp;\u0026plusmn;\u0026thinsp;2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eIncidence of aneuploidy and CNV segments with various properties\u003c/h2\u003e \u003cp\u003eThe incidence of aneuploidy, pathogenic CNVs, likely pathogenic CNVs, and variants of uncertain significance CNVs in the four groups are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Concerning the incidence of aneuploidy, the non-isolated CHD group displays the highest rate, with significant statistical differences observed when compared to the isolated CHD group (27.9% vs. 3.5%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the non-CHD group (27.9% vs. 8.6%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the control group (27.9% vs. 5.9%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In terms of the incidence of pathogenic CNVs and 22q11.2, no statistically significant differences were found between the isolated CHD group and the non-isolated CHD group (8.2% vs. 14.7%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.134), (2.9% vs. 4.4%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.865), respectively. The incidence of overall chromosomal abnormalities in the non-isolated CHD group was highest, with significant statistical distinctions compared to the isolated CHD group (42.6% vs. 14.1%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the non-CHD group (42.6% vs. 14.9%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the control group (42.6% vs. 9.4%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Regarding the incidence of variants of uncertain significance CNVs, there were no statistically significant differences between the isolated CHD group and the non-isolated CHD group (8.2% vs. 8.8%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.883).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe incidence of aneuploidy, pathogenic, likely pathogenic, and variants of uncertain significance CNVs in four groups of pregnant women (%)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eaneuploidy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003ePathogenic CNVs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLikely pathogenic\u003c/p\u003e \u003cp\u003eCNVs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal known pathogenic\u003c/p\u003e \u003cp\u003eand likely pathogenic\u003c/p\u003e \u003cp\u003efindings\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003evariants of uncertain significance CNVs\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22q11.2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsolated CHD group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6(3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5(2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9(5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14(8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e20(11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e14(8.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-isolated CHD group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19(27.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3(4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7(10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10(14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e29(42.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e6(8.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-CHD group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46(8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28(5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30(5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e78(14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e28(5.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78(5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37(2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e42(3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e123(9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e41(3.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e＜0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e＜0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e＜0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e＜0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of aneuploidy\u003c/h2\u003e \u003cp\u003eThe distribution of aneuploidy is listed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Regarding the incidence of trisomy 21, statistically significant differences were observed only between the non-CHD group and the control group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), with no significant differences noted among the other groups. For trisomy 18, the non-isolated CHD group exhibited the highest incidence rate, showing significant statistical significance when compared to the isolated CHD group (16.2% vs. 1.2%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the non-CHD group (16.2% vs. 1.5%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the control group (16.2% vs. 0.5%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No statistical differences were found between the isolated CHD group and the non-CHD group or the control group. In terms of trisomy 13, a statistically significant difference was observed between the non-isolated CHD group and the non-CHD group (4.4% vs. 0.4%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe distribution of aneuploidy in four groups of pregnant women (%)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTrisomy 21\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTrisomy 18\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTrisomy 13\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOther aneuploidies\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsolated CHD group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4(2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2(1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-isolated CHD group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4(5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11(16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-CHD group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28(5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8(1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8(1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33(2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6(0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39(3.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDistribution frequency of CNV fragment sizes\u003c/h2\u003e \u003cp\u003eThe frequency of CNV fragment sizes was compared among four groups, including pathogenic CNVs, likely pathogenic CNVs, and variants of uncertain significance CNVs, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Regarding the distribution frequency of CNVs\u0026thinsp;\u0026lt;\u0026thinsp;1Mb, statistically significant differences were observed only between the non-heart group and the control group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002). There was no statistically significant difference between the isolated CHD group and the non-isolated CHD group (4.7% vs. 5.9%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.963). For CNVs with a distribution frequency of 1-4Mb, statistically significant differences were found between the isolated CHD group, the non-isolated CHD, and the control group (7.1% vs. 3.3%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014; 9.1% vs. 3.3%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031). However, there was no statistically significant difference between the isolated CHD group and the non-isolated CHD group (7.1% vs. 9.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.598). In terms of CNVs with a distribution frequency\u0026thinsp;\u0026ge;\u0026thinsp;5Mb, the non-isolated CHD group exhibited the highest frequency, but there was no statistically significant difference between the non-isolated CHD group and the isolated CHD group (8.8% vs. 4.7%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.360). However, statistically significant differences were observed between the non-isolated CHD group and the non-CHD group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), as well as the control group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCompares the distribution frequencies of CNV fragment sizes among four groups of pregnant women(%)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e＜1Mb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1-4Mb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5Mb\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsolated CHD group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8(4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12(7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8(4.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-isolated CHD group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4(5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6(8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6(8.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-CHD group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25(4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25(4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10(1.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27(2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43(3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16(1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eThe distribution profiles of pathogenic CNVs in the four groups\u003c/h2\u003e \u003cp\u003eAs seen in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, the isolated CHD group comprised two large segmental duplications: partial trisomy and Xq28 duplication syndrome, four cases of large segmental deletions (7.2\u0026thinsp;~\u0026thinsp;12.3Mb), one case of \u0026lt;\u0026thinsp;4Mb duplication (Cat eye syndrome), and seven cases of \u0026lt;\u0026thinsp;4Mb deletion, of which four 22q11.2 microdeletion syndrome, one 12q14 microdeletion syndrome, Del(19p13.2), and 15q11.2 BP1-BP2 microdeletion. The non-isolated CHD group comprised three cases of large segment duplications(13.37\u0026thinsp;~\u0026thinsp;47.7Mb), two cases of large segment deletions(10.1\u0026thinsp;~\u0026thinsp;14.9Mb), and five cases of deletions ＜4Mb. Among these, one 15q11.2 microdeletion, and three 22q11.2 microdeletion syndrome. The non-CHD group had three cases of large segment duplications(12.7\u0026thinsp;~\u0026thinsp;22.6Mb), six cases of large segment deletions (6.3\u0026thinsp;~\u0026thinsp;19.1Mb), sixteen cases of deletions, and five cases of duplication＜4Mb. Among these, known microduplications/microdeletions as 15q11.2 BP1-BP2 microdeletion, 16p11.2 microdeletion/microduplication syndrome, Potocki-Lupski syndrome, 22q11.2 deletion/duplication syndrome, and Leri-Weill dyschondrostosis (LWD)-SHOX deletion. The control group included three cases of large segment duplications(8.1\u0026thinsp;~\u0026thinsp;22.5Mb), twelve cases of large segment deletions(5.4\u0026thinsp;~\u0026thinsp;25.7Mb), and twenty-seven cases of microdeletions/microduplications. Among these, known CNVs included 1q21.1 recurrent microduplication, 7q11.23 duplication syndrome, 15q11.2 BP1-BP2 microdeletion, 16p11.2 microduplication syndrome, 22q11.2 deletion/duplication syndrome, Cat eye syndrome, and others.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of pathogenic CNV in the four groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsolated CHD group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-isolated CHD group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-CHD group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCorrespondence syndrome\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(1q43q44) (9.8Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1q43q44 deletion syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(1q21.1q21.2)(5.4Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1q21.1 recurrent microdeletion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(1q21.1q21.2)(1.8Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1q21.1 recurrent microduplication\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(1q21.1q21.2)(2.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1q21.1 recurrent microduplication\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(2q14.2q22.3)(25.0Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDel(2p25.3)(2.6Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(2p25.1p24.2)(5.8Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDup(2p25.3p21)(41.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(2q37.1q37.3)(9.3Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(3p26.3p25.3)(11.5Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDup(4p16.3p14)(39.7Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePartial 4p trisomy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(4p16.3p15.31)(19.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(4p16.3p15.32)(16.3Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWolf-Hirschhorn syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(4p16.3p15.33)(13.5Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWolf-Hirschhorn syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(5p15.33p14.1)(25.7Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(5q35.2q35.3)(1.9Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(5q35.3)(3.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(5q35.2q35.3)(2.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(6q26q27)(8.4Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(6p24.3)(526.6Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(7q11.23)(1.4Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7q11.23 duplication syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(7q11.23)(1.5Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDup(8q22.1q24.3)(47.7Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(8p23.3p23.1)(10.2Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(8p23.3p23.1)(8.2Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(9p24.3p21.3)(22.5Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDel(10p15.3p14)(10.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(10q23.31)(1.0Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(10q25.3q26.3)(19.0Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(10q26.13q26.3)(10.8Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10q26 deletion syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(11p12p11.12)(12.7Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(11p14.3p13)(10.4Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(11q24.2q25)(7.2Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(11q24.1q25)(12.3Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(12q14.3q15)(3.14Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12q14 microdeletion syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(12p13.33p12.1)(22.6Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(13q13.3q14.3)(14.5Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDup(14q22.1q23.3)(13.37Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(15q11.2)(512.3Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDel15q11.2)(507.0Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(15q11.2)(855.3Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(15q11.2)(855.4Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15q11.2 BP1-BP2 microdeletion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(15q11.2)(855.3Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15q11.2 BP1-BP2 microdeletion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(15q11.2)(512.4Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15q11.2 BP1-BP2 microdeletion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(15q11.2)(311.8Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15q11.2 BP1-BP2 microdeletion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(15q11.2)(855.3Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15q11.2 BP1-BP2 microdeletion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(15q11.2)(507.0Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15q11.2 BP1-BP2 microdeletion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(16p11.2)(749.9Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16p11.2 microdeletion syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(16p11.2)(309.5Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16p11.2 microdeletion syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(16p11.2)(622.7Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16p11.2 microdeletion syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(16p11.2)(301.9Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16p11.2 microdeletion syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(16P11.2)(226.7Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(16p11.2)(585.1Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16p11.2 microduplication syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(16P11.2)(598.7Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(16p11.2)(585.2Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16p11.2 microduplication syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(16p13.12p12.3)(2.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(17p11.2)(3.7Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePotocki-Lupski syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDel(18p11.32p11.21)(14.9Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(18p11.32p11.21)(14.9Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePartial 18p monosomy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(18q21.31q23)(22.2Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(19p13.2)(2.1M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(21q21.2q22.13)(14.8Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(21q22.2q22.3)(8.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(21q22.3)(1.6Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(22q11.21)(3.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDel(22q11.21)(2.8Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(22q11.1q11.21)(3.8Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(22q11.21)(744.1Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22q11.2 deletion syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(22q11.21)(3.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDel(22q11.21)(3.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(22q11.21)(2.8Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22q11.2 deletion syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(22q11.21q11.22)(1.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDel(22q11.21)(2.9Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(22q11.21)(3.2Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22q11.2 deletion syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(22q11.21)(3.2Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22q11.2 deletion syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(22q11.21)(2.8Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(22q11.21)(2.8Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22q11.2 duplication syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDup(22q11.1q11.21)(1.6Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(22q11.1q11.21)(2.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCat eye syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(22q12.1)(213.4Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(22q13.32q13.33)(2.5Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(Yq11.221q11.23)(10.5Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAZFb\u0026thinsp;+\u0026thinsp;AZFc deletion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(Yq11.223q11.23)(3.5Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAZFc deletion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(Xp21.1)(272.1Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(Xp21.1)(271.3Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(Xp22.31)(1.2Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSteroid sulphatase deficiency(STS)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(Xp22.31)(1.6Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSteroid sulphatase deficiency(STS)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(Xp22.31)(1.6Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSteroid sulphatase deficiency(STS)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(Xp22.31)(1.6Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSteroid sulphatase deficiency(STS)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(Xp22.31)(1.7Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSteroid sulphatase deficiency(STS)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(Xp22.31)(1.7Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSteroid sulphatase deficiency(STS)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(Xp22.31)(1.7Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSteroid sulphatase deficiency(STS)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(XP22.33)(3.9Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(Xp22.33)(742.6Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLeri-Weill dyschondrostosis (LWD) - SHOX deletion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(Xp22.33p22.31)(6.3Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLeri-Weill dyschondrostosis (LWD) - SHOX deletion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDup(Xq27.2q28)(13.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eXq28 duplication syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eDistribution profile of likely pathogenic CNVs in the four groups\u003c/h2\u003e \u003cp\u003eFrom Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, it can be observed that in the non-CHD group, there was one case each of duplication and deletion CNV. In the control group, there was one case of a large segment duplication and two cases of microdeletions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of likely pathogenic CNV in the four groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsolated CHD group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-isolated CHD group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-CHD group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(4p16.3p16.1)(10.7Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(11p15.5p15.4)(5.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(16p12.2)(600.7Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(16p12.2)(600.6Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(20p13)(981.6Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eDistribution variants of uncertain significance CNVs in four groups\u003c/h2\u003e \u003cp\u003eAs seen in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, it is evident that in the isolated CHD group, there were six cases of microdeletions and eight cases of microduplications. In the non-isolated CHD group, all six cases were duplications, with one case being a large segment duplication. In the non-CHD group, there are twenty-one cases of microduplications and seven cases of microdeletions. In the control group, there were 23 cases of microduplications and eighteen cases of microdeletions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution variants of uncertain significance CNVs in the four groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsolated CHD group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-isolated CHD group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-CHD group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDup(1q21.1)(576.0Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(1q21.1)(385.9Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(1q24.3q25.1)(2.3Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(2p12)(1.4Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(2p16.1p15)(1.6Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(2p21)(151.7Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(2p25.3)(1.0Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(2q13)(106.4Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(2q13)(103.5Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(2q13)(871.1Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(2q13)(482.1Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(2q13)(482.1Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(2q13)(103.5Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(2q13)(1.7Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(2q13)(1.7Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(2q12.3q13)(2.4Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDup(3p14.2)(1.6Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(3p24.1p23)(4.0Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(3p25.3)(128.7Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDup(3q23q24)(5.18Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(3q25.32)(568.0Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(4p16.1)(1.9Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(4p16.2)(1.0Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(4q34.3)(3.3Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(4q35.2)(1.3Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(5q23.1q23.2)(4.4Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDup(5q35.3)(1.6Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(6p21.31)(1.8Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(6q14.1)(823.2Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(6q26)(188.7Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(6q15)(627.8Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(6q26)(241.4Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDup(6q25.3q26)(1.2Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(7p14.1)(1.3Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(7p21.1)(613.9Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(7p21.3)(1.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(7p22.3)(789.6Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(7q32.1)(294.0Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(8p21.3)(2.1Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(8p23.1)(143.8Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(8p23.2)(1.3Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(8p23.3p23.2)(2.7Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(8p23.2)(2.2Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(8p23.2)(1.1Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(8q11.21)(1.7Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(9p24.1)(197.9Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDup(9p24.3p24.1)(5.3Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(9p24.3)(686.3Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(9q31.1)(1.2Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(10q21.3)(312.3Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(10q21.3)(1.3Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDup(11p14.3p14.1)(4.4Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(12q21.32)(1.2Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(13q12.12)(1.4Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(13q33.1q33.2)(1.8Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(14q22.1q22.2)(3.1Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDup(15q13.3)(422.4Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(15q13.1q13.2)(1.5Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(16p13.11)(1.6Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(16p13.11) (926.6Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(16p13.11)(827.3Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(16p13.11) (796.4Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(16p13.11) (1.2Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(16p13.11) (1.6Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(16p13.11) (796.4Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDup(16p13.2p13.13)(486.1Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDup(16p13.3)(1.0Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDup(16q11.2q12.1)(640.9Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(16q12.1)(480.0Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDup(16q22.2)(607.2Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDel(16q23.1)(260.2Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(17p11.2q11.1)(3.7Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(17p13.3)(836.1Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDel(17p13.3)(624.6Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(17q22)(1.0Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDup(18p11.32p11.23)(7.8Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(18p11.32)(1.6Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(20q12)(1.4Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDup(21q11.3)(731.9Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDel(21q21.1)(1.9Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(21q21.1)(1.2Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDup(22q11.23)(1.3Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(22q11.23)(1.3Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(22q11.23)(1.3Mb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(Xp22.31)(125.8Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(Xp22.31)(1.6Mb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(Xp22.31)(543.7Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDup(Xp22.33)(392.7Kb)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDup(Xq22.1)(599.2Kb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn recent years, chromosomal imbalances observed under the microscope have been considered a significant contributor to CHD\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. This study used fetal ultrasound imaging to establish isolated CHD, non-isolated CHD, non-CHD, and control groups and described the distribution and frequency of CNVs in each group to evaluate the feasibility of SNP array in identifying the etiology of CHD fetuses. The overall detection rate of abnormal CNVs in isolated CHD and non-isolated CHD groups was 8.2% (14/170) and 14.7% (10/68), respectively, while in the non-CHD and control groups, the rates were 5.6% (30/538) and 3.2% (42/1316). Previous studies have shown that the detection rate of chromosomal microarrays for congenital heart disease ranges from 4\u0026ndash;20%\u003csup\u003e15\u003c/sup\u003e, while another study reported detection rates of 6% for ultrasound abnormalities and approximately 1.7% for non-ultrasound structural abnormalities in older women and those with positive results in chromosomal screening\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Compared to previous studies, this research exhibits a similar detection rate for fetal congenital heart defects and other ultrasound structural abnormalities. However, the detection rate for cases without ultrasound structural abnormalities is slightly higher. This difference may be attributed to variations in the array platform used, the resolution of the array, and the reporting practices of individual clinical laboratories. Additionally, as new literature and public data sharing contribute to an expanding understanding of genomic regions associated with specific diseases, annual reviews of the same dataset have led to an increase in disease-associated cases to 1.8% while reducing the number of cases classified as variants of uncertain significance to 0.9%\u003csup\u003e17\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA recent meta-analysis of 45 studies revealed that the overall prevalence of chromosomal abnormalities in isolated congenital heart defects (CHD) and non-isolated CHD was 16% and 37%, respectively. Among non-isolated CHD cases, the prevalence of aneuploidy (19%), other CNVs (excluding 22q11) (4%), and trisomy 18 were higher than in isolated CHD cases\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Our study demonstrated that the overall prevalence of chromosomal abnormalities in the isolated CHD group and non-isolated CHD group is 11.8% and 42.6%, respectively. Comparative analysis showed that the non-isolated CHD group has the highest prevalence of aneuploidy and overall chromosomal abnormalities, with statistically significant differences compared to the isolated CHD group, non-CHD group, and control group. The non-isolated CHD group had the highest prevalence of T18, and there was no statistically significant difference in the prevalence of T21 compared to the isolated CHD group, consistent with the meta-analysis. However, there was no statistically significant difference between the non-isolated CHD group and isolated CHD group (14.7% vs. 8.2%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.134) in prevalence of pathogenic CNV, and even after excluding 22q11, the non-isolated CHD group still showed no statistically significant difference in pathogenic CNV prevalence compared to the isolated CHD group (10.3% vs. 5.3%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.269), which differs from the meta-analysis. Furthermore, our study found that the prevalence of aneuploidy cases and pathogenic CNVs was slightly higher than in the meta-analysis, possibly due to differences in the number of subjects included in each group.\u003c/p\u003e \u003cp\u003eThe traditional chromosomal karyotype resolution is typically in the range of 5-10Mb. Our research indicates that there was no statistically significant difference in the distribution frequency of pathogenic CNVs and variants of uncertain significance CNVs between isolated and non-isolated CHD groups. The significance of CNV segment size typically depends on their location in the genome and the genes or non-coding regions they contain. Smaller CNV segments may have localized effects on gene expression, which could impact an individual's phenotype and disease risk. Larger CNV segments may affect multiple genes, thus influencing various phenotypes and disease risks\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Some studies suggest that the etiology of isolated CHD is multifactorial, with some cases being attributed to single genes. Non-isolated CHD is associated with various causes, including chromosomal and sub-chromosomal abnormalities, single-gene syndromes, epigenetic factors, and environmental influences\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. The results of our study show that in the non-CHD group, pathogenic CNVs larger than 10Mb account for 50% of the cases. These larger segments may be considered partial aneuploidy, and non-CHD with multiple systemic developmental abnormalities are more likely to manifest as chromosomal abnormality syndromes. In contrast, isolated CHD identified by ultrasound is more likely to be caused by smaller chromosomal segments or gene variations.\u003c/p\u003e \u003cp\u003eIn the four groups of pathogenic CNVs, we identified a total of 15 cases involving the 22q11.2 region, including 11 deletions and 4 duplications. The 22q11.2 microdeletion is currently recognized as a syndrome associated with congenital heart defects, with severity ranging from non-survivable to subclinical, or even without a CHD phenotype. The main known causative gene for this syndrome is TBX1. The 22q11.2 microduplication syndrome complements the 22q11.2 microdeletion syndrome, sharing common features but exhibiting considerable phenotypic variation, with a CHD occurrence rate of approximately 25%\u003csup\u003e20, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Furthermore, we observed one case each of 22q11.1q11.21 microduplication in the isolated congenital heart defect group and the control group. This region encompasses a critical area within the 22q11.21 recurrent region (Cat Eye Syndrome, CES). However, it does not involve the 22q11.2 region associated with DiGeorge syndrome/Velocardiofacial syndrome (DGS/VCFS)\u003csup\u003e22\u003c/sup\u003e. Upon pairwise comparison, we found that the occurrence rate of 22q11.2 abnormalities in the isolated CHD group and the non-isolated CHD group did not exhibit statistically significant differences (2.9% vs. 4.4%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.865), consistent with some previous reports\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. However, both the isolated and non-isolated CHD groups had higher occurrence rates than the non-CHD group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008) and the control group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). This study identified 3 cases of 22q11.2 microdeletion and 2 cases of microduplication in the control group without ultrasound structural abnormalities. This may be related to the lack of obvious neurological and psychiatric characteristics in the prenatal stage and the absence of typical facial features.\u003c/p\u003e \u003cp\u003eAdditionally, among the four groups, a total of 9 cases involved the 15q11.2. The occurrence rates were as follows: isolated CHD group 0.6% (1/170), non-isolated CHD group 1.5% (1/68), non-CHD group 1.1% (6/538), and control group 0.1% (1/1316). After pairwise comparisons, there were no statistically significant differences between the isolated CHD group and the non-isolated CHD group (p\u0026thinsp;=\u0026thinsp;0.522). The nature of the 15q11.2 BP1-BP2 microdeletion has been a subject of controversy. Its prevalence in CMA-tested populations is approximately 0.57%-1.27% \u003csup\u003e24\u003c/sup\u003e. Clinical phenotypes are mainly associated with neurodevelopmental disorders, developmental and language delays, and autism spectrum disorders, with a relatively low penetrance of 10\u0026ndash;12%\u003csup\u003e25\u003c/sup\u003e. The 15q11.2 BP1-BP2 microdeletion encompasses four highly conserved non-imprinted genes, NIPA1, NIPA2, CYFIP1, and TUBGCP5. Currently, there is no established independent connection between this microdeletion and heart morphology. Some studies suggested that the 15q11.2 BP1-BP2 microdeletion has a relative frequency of 3.4% in intellectual disability, 2% in schizophrenia, and 2.1% in epilepsy, with no increased risk of cardiac malformation or autism, making it of limited clinical significance, and it has been suggested to be classified as a \"mildly pathogenic factor.\" \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. In 2015, the UK Genomic Medicine Committee even proposed not to report the 15q11.2 BP1-BP2 microdeletion in prenatal diagnosis\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. However, a recent study by the Williams team indicated an increased risk of cardiovascular malformation associated with the 15q11.2 BP1-BP2 microdeletion, with cardiovascular malformation being more common but not necessarily severe\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. In our study, both isolated and non-isolated CHD groups had 15q11.2 microdeletion, and both exhibited ventricular septal defects, which aligns with the findings by Williams et al. In the non-CHD group, four cases of 15q11.2 microdeletion only showed increased nuchal translucency on ultrasound.\u003c/p\u003e \u003cp\u003eIn variants of uncertain significance CNVs, small segmental duplications were predominant across the four groups. It was observed that 2q13 was involved in all four groups, with eight cases of microdeletions and one case of microduplication in total. The pathogenic nature of 2q13 is not well understood. Several studies have indicated that duplications and deletions of 2q13 are risk factors for developmental delay and anomalies. Wolfe\u0026rsquo;s research found an increased prevalence of attention deficit hyperactivity disorder (ADHD) in individuals with defects associated with the 2q13 locus, with 30% of defect carriers having heart defects, whereas no defects were observed in carriers of duplications\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Other researchers have noted that with chromosome 2q13 phenotypes, deletions are more enriched in cardiovascular disease, while duplications are associated with craniofacial features\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. In our study, two cases of 2q13 deletion were found in individuals with CHD, and both were isolated cases. Their phenotypes were complete transposition of the great arteries with pulmonary artery stenosis and anomalous origin of the right pulmonary artery with pulmonary artery stenosis, which aligns with the above results. Since 2q13 can also be present in the normal population and given the current lack of large-sample data, further research may be needed to explore the pathogenic genes and phenotypes associated with heart defects.\u003c/p\u003e \u003cp\u003eAdditionally, we also observed that the isolated CHD group had a Dup(9p24.3p24.1), the control group had a Dup(9p24.3), the non-isolated CHD group had a Dup(16q11.2q12.1), and the non-CHD group had a Dup(16q12.1), all of which involved partially overlapping regions. The 9p24.3 duplication segment contains genes like DOCK8 and may be associated with autism spectrum disorders, intellectual disabilities/developmental delay, and other conditions. However, whether the 9p24.3p24.1 segment is related to congenital heart disease phenotypes has not been reported in the literature\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. All four groups of CNVs involved chromosome 16, but the specific segments affected were different. Chromosome 16 is one of the most enriched chromosomes for segmental duplications, and 16p is one of the more unstable regions in the genome, with over 10% of the 16p euchromatic regions consisting of highly complex low-copy repeats\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. The shared regions affected by CNVs in the non-isolated CHD group and the non-CHD group have rare clinical phenotypes reported in the literature. This suggests that, apart from genetic factors, other factors such as environmental influences may also play a role.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStudy limitation\u003c/h2\u003e \u003cp\u003eThe study has a large overall sample size, but it still had limitations. The number of samples involving CHD is relatively small, especially for non-CHD. Ultrasound has certain limitations, and some cases with mild neurodevelopmental or craniofacial abnormalities may be challenging to classify into specific groups. Fetal and other associated symptoms may become more apparent as gestational weeks progress. Additionally, the study lacked parental validation and follow-up data.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, SNP microarrays can effectively improve the diagnostic rate of abnormal CNVs in fetal congenital heart defects (CHD). This not only highlights CNVs as important pathogenic factors in CHD but also aids in the chromosome-based diagnosis of such children and provides guidance for their family planning. Both isolated and non-isolated CHD exhibit a variety of genetic variations, including common microdeletion/microduplication syndromes, chromosomal syndromes, and more. These variations represent differences in the phenotypic expression of various chromosomal abnormality syndromes and also reflect the limitations of prenatal ultrasound diagnosis in distinguishing between isolated and non-isolated cases. Further research into the mechanisms underlying congenital heart defects will require more in-depth phenotypic observations combined with detailed molecular genetics, metabolic studies, epigenetics, and other analyses.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e: Data curation, Fenglei Ye; Funding acquisition, Qijing Wang; Investigation, Fenglei Ye; Project administration, Xiayuan Xu; Resources, Xiayuan Xu, Yi Wang, Lifang Chen, and Qunda Shan; Supervision, Xiayuan Xu and Yi Wang; Writing \u0026ndash; original draft, Fenglei Ye; Writing \u0026ndash; review \u0026amp; editing, Qijing Wang and Fan Jin. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This study was supported by the National Natural Science Foundation of China (no. 82201843), and the Jinhua City Science and Technology Research Program Project (no.2020-4-068).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u003c/strong\u003e The study was approved by the Institutional Ethics Committee of the Lishui Maternal and Child Health Hospital and Jinhua Maternal and Child Health Hospital (approval no. 2020-KY-003). All participants understood the content and purpose of this study and signed an informed consent form before enrollment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u0026nbsp;\u003c/strong\u003eAll participants understood the content and purpose of this study and signed an informed consent form before enrollment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials:\u003c/strong\u003e The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGlobal Burden of Disease, Study C. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990\u0026ndash;2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;386(9995):743\u0026ndash;800.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang H, Lin X, Lyu G, He S, Dong B, Yang Y. Chromosomal abnormalities in fetuses with congenital heart disease: a meta-analysis. Arch Gynecol Obstet 2023, 1\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMandalenakis Z, Giang KW, Eriksson P, Liden H, Synnergren M, W\u0026aring;hlander H, Fedchenko M, Rosengren A, Dellborg M. Survival in children with congenital heart disease: have we reached a peak at 97%? J Am Heart Association 2020, 9 (22), e017704.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRachamadugu SI, Miller KA, Lee IH, Zou YS. Genetic detection of congenital heart disease. Gynecol Obstet Clin Med 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNees SN, Chung WK. Genetic Basis of Human Congenital Heart Disease. Cold Spring Harb Perspect Biol 2020, \u003cem\u003e12\u003c/em\u003e (9).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcDonald-McGinn DM, Sullivan KE, Marino B, Philip N, Swillen A, Vorstman JA, Zackai EH, Emanuel BS, Vermeesch JR, Morrow BE. 22q11. 2 deletion syndrome. Nat reviews Disease primers. 2015;1(1):1\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCostain G, Silversides CK, Bassett AS. The importance of copy number variation in congenital heart disease. NPJ genomic medicine. 2016;1(1):1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEhrlich L, Prakash SK. Copy-number variation in congenital heart disease. Curr Opin Genet Dev. 2022;77:101986.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevy B, Wapner R. Prenatal diagnosis by chromosomal microarray analysis. Fertil Steril. 2018;109(2):201\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXia Y, Yang Y, Huang S, Wu Y, Li P, Zhuang J. Clinical application of chromosomal microarray analysis for the prenatal diagnosis of chromosomal abnormalities and copy number variations in fetuses with congenital heart disease. Prenat Diagn. 2018;38(6):406\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalomon LJ, Alfirevic Z, Berghella V, Bilardo C, Hernandez-Andrade E, Johnsen SL, Kalache K, Leung KY, Malinger G, Munoz H, Prefumo F, Toi A, Lee W, Committee ICS. Practice guidelines for performance of the routine mid-trimester fetal ultrasound scan. Ultrasound Obstet Gynecol. 2011;37(1):116\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInternational Society of Ultrasound in, Gynecology O, Carvalho JS, Allan LD, Chaoui R, Copel JA, DeVore GR, Hecher K, Lee W, Munoz H, Paladini D, Tutschek B, Yagel S. ISUOG Practice Guidelines (updated): sonographic screening examination of the fetal heart. Ultrasound Obstet Gynecol. 2013;41(3):348\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFranklin RC, B\u0026eacute;land MJ, Colan SD, Walters HL, Aiello VD, Anderson RH, Bailliard F, Boris JR, Cohen MS, Gaynor JW. Nomenclature for congenital and paediatric cardiac disease: the International Paediatric and Congenital Cardiac Code (IPCCC) and the Eleventh Iteration of the International Classification of Diseases (ICD-11). 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Arch Gynecol Obstet 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eItsara A, Cooper GM, Baker C, Girirajan S, Li J, Absher D, Krauss RM, Myers RM, Ridker PM, Chasman DI, Mefford H, Ying P, Nickerson DA, Eichler EE. Population analysis of large copy number variants and hotspots of human genetic disease. Am J Hum Genet. 2009;84(2):148\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHasten E, McDonald-McGinn DM, Crowley TB, Zackai E, Emanuel BS, Morrow BE, Racedo SE. Dysregulation of TBX1 dosage in the anterior heart field results in congenital heart disease resembling the 22q11.2 duplication syndrome. Hum Mol Genet. 2018;27(11):1847\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePortnoi MF. Microduplication 22q11.2: a new chromosomal syndrome. 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E. E.; Gilna, P.; Lucas, S. M.; Myers, R. M.; Rubin, E. M.; Pennacchio, L. A., The sequence and analysis of duplication-rich human chromosome 16. \u003cem\u003eNature\u003c/em\u003e 2004, \u003cem\u003e432\u003c/em\u003e (7020), 988 \u0026ndash; 94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCiaccio C, Tucci A, Scuvera G, Estienne M, Esposito S, Milani D. 16p13 microduplication without CREBBP involvement: Moving toward a phenotype delineation. Eur J Med Genet. 2017;60(3):159\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"single nucleotide polymorphism microarray, congenital heart disease, copy number variation, prenatal diagnosis","lastPublishedDoi":"10.21203/rs.3.rs-3325051/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3325051/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to evaluate the effectiveness of single nucleotide polymorphism microarray (SNP-Array) in the etiological diagnosis of fetal cardiac ultrasound abnormalities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 2092 pregnant women who underwent prenatal diagnosis from 2017 to 2022 were included in the study and divided into four groups based on the presence of ultrasound structural abnormalities and the type of abnormality. The results of the SNP-Array test in amniotic fluids in different groups were analyzed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe non-CHD had the highest incidence of aneuploidy, overall chromosomal abnormalities, and trisomy 18, showing significant statistical differences compared to the other groups(p＜0.001). In terms of CNV segment size distribution frequency, there was no statistical difference between the isolated congenital heart defect group and the non-isolated congenital heart defect group (p＞0.05). The occurrence rates of 22q11.2 and 15q11.2 were also not statistically different between the isolated congenital heart defect group and the non-isolated congenital heart defect group (p＞0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSNP-Array improves the ability to detect of abnormal CNVs in CHD fetuses, providing valuable assistance in diagnosing chromosomal etiology and genetic counseling.\u003c/p\u003e","manuscriptTitle":"The yield of SNP microarray analysis for fetal ultrasound cardiac abnormalities","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-10-03 18:07:10","doi":"10.21203/rs.3.rs-3325051/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2023-12-19T08:10:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-11-28T19:57:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-11-21T20:54:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"d26ccebf-b98a-4542-9b70-333e35468acb","date":"2023-11-13T08:03:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"b67cd889-89ed-47b3-bc5e-83707e32b919","date":"2023-11-13T06:32:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-11-10T13:36:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"364aadae-0dc9-4b62-9cd8-22b4006d5d89","date":"2023-10-30T06:26:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6f7b1272-a161-4a72-abb7-06a9dd58f11f","date":"2023-10-29T19:14:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-10-19T17:46:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-10-19T17:01:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2023-09-26T04:54:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-09-26T04:43:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2023-09-04T15:32:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bd51b538-adc8-4739-a13c-d348aa59ec8d","owner":[],"postedDate":"October 3rd, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-04-08T15:06:00+00:00","versionOfRecord":{"articleIdentity":"rs-3325051","link":"https://doi.org/10.1186/s12884-024-06428-9","journal":{"identity":"bmc-pregnancy-and-childbirth","isVorOnly":false,"title":"BMC Pregnancy and Childbirth"},"publishedOn":"2024-04-05 15:01:34","publishedOnDateReadable":"April 5th, 2024"},"versionCreatedAt":"2023-10-03 18:07:10","video":"","vorDoi":"10.1186/s12884-024-06428-9","vorDoiUrl":"https://doi.org/10.1186/s12884-024-06428-9","workflowStages":[]},"version":"v1","identity":"rs-3325051","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3325051","identity":"rs-3325051","version":["v1"]},"buildId":"oE6Zbj460LM0Up2FdVbMZ","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}