Whole-exome Sequencing in deceased fetuses with ultrasound anomalies: A Retrospective Analysis

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To investigate the diagnostic value of WES in fetuses with ultrasound abnormalities that resulted in fetal demise or pregnancy termination. Methods: 61 deceased fetuses with ultrasound abnormalities and normal copy number variation Sequencing (CNV-seq) were retrospectively collected. Proband-only or trio-WES were performed on the products of conception. Result: Collectively, 28 cases were positive with 39 variants (10 pathogenic, 22 likely pathogenic and 7 variants of uncertain significance) of 18 genes, and the overall diagnostic rate was 45.9% (28/61), of which 39.2% (11/28) were de novo variants. In addition, 21 variants in 11 genes among the positive cases had not been previously reported. The diagnostic yield for definitive findings for trio analysis was 55.9% (19/34) compared to 33.3% (9/27) for singletons. The most common ultrasound abnormalities were skeletal system abnormalities 39.2% (11/28), followed by multiple system abnormalities (17.9%, 5/28) and genitourinary abnormalities (17.9%, 5/28). Conclusion: Our results support the use of WES to identify genetic etiologies of ultrasound abnormalities and improve understanding of pathogenic variants. The identification of disease-related variants provided information for subsequent genetic counseling of recurrence risk and management of subsequent pregnancies. Whole-exome sequencing deceased fetuses products of conception genetic diagnosis Figures Figure 1 Background Congenital structural abnormalities are identified in approximately 3% of fetuses, accounting for 25% of perinatal deaths[ 1 , 2 ]. Fetal structural abnormalities can vary from isolated minor anomalies to severe multi-system abnormalities, which can be effectively identified by prenatal ultrasound[ 3 ]. The identification of fetal ultrasound anomalies prompts additional prenatal evaluations. Most of the structural abnormalities indicated by prenatal ultrasound occur in fetuses with no family history of congenital malformation, making accurate prenatal genetic counseling difficult. Therefore, it is necessary to clarify the genetic etiology of fetal structural abnormalities. Chromosomal abnormalities and monogenic disorders have been considered as major causes of birth defects, although the etiology of many congenital malformations is unknown. G-banded karyotyping identified numerical and structural chromosomal abnormalities in 50% of fetuses with ultrasound abnormalities, low-coverage genome sequencing (eg. CNV-seq) increases the detection rate in this group of fetuses by up to 5%[ 4 , 5 ]. However, identifiable genetic cause is still undetected in over 60% of cases. Whole-exome sequencing (WES), can identify the genetic etiology by identifying the single gene pathogenic variation of fetal structural abnormalities. According to previous studies, WES can be used to discover the genetic causes of fetal structural abnormalities, identify pathogenic variations, and establish genotype-phenotypic associations[ 6 ]. Therefore, the method of WES was used in this study to analyze the 61 causes of fetal specimens terminated due to structural abnormalities indicated by ultrasound. Methods Subjects Fetal WES cases were retrospectively collected from pregnancies with ultrasound anomalies that were terminated or resulted in fetal demise between October 2020 and May 2022. All cases had previously undergone CNV-seq and no clinically significant variants were detected. Fetal phenotype information was obtained from prenatal ultrasound and fetal magnetic resonance imaging reports. All the couples were not consanguineous. Pregnant women with known teratogen, uterine malformation, hypertension, diabetes, and other basic diseases were also excluded. Ethics approval to undertake the research was granted by the First Affiliated Hospital of Zhengzhou University Committee. Sequencing analysis and variant annotation of WES Fetal genomic DNA was obtained from products of conception (POC) including chorionic villi and fetal skin tissues. Parental DNA was extracted from peripheral blood samples. The genomic DNA of deceased fetuses and their parents were extracted using the QIAamp DNA extraction kit (Qiagen, Germany), then quantified by using Qubit 4.0 (Thermo Fisher Scientific Inc. USA). DNA libraries were established by using Ada & Index Kit (UDI for LIM) and Enzyme Plus Library Prep Kit (iGeneTech Co., Ltd, Beijing, China), and exome coding and splicing regions were captured using AIExome Human Exome Panel V2 Plus with TargetSeq One Hyb & Wash Kit (iGeneTech Co., Ltd, Beijing, China), according to the manufacturer’s instructions. Subsequently, the captured libraries were sequenced on the NovaSeq6000 platform (Illumina, San Diego, CA, USA) with the average sequencing depth > 100X and 20X sequencing coverage > 98%. Sentieon(release 201808.05) was used to align paired-end reads with the human reference genome GRCh37/hg19 under the Genome Analysis Toolkit(GATK) best practice guidelines, and the duplicate reads were removed using Picard version 2.9.0. Candidate variants were assessed with latest reports in the online databases, such as ClinVar, Human exons database (ExAC), Human Gene Mutation Database (HGMD) and Online Mendelian Inheritance in Man (OMIM) databases. Variant interpretation and classification Variants were classified into pathogenic variants, likely pathogenic variants, variants of uncertain significance (VUS), likely benign variants, and benign variants according to the guidelines of the American College of Medical Genetics and Genomics(ACMG)[ 7 ]. The pathogenic and likely pathogenic variants were further analyzed in conjunction with prenatal imaging to determine whether they fully and partially explain the observed phenotype. Polymerase chain reaction (PCR) combined with Sanger sequencing were used to validate the candidate P/LP variants in specimens of deceased fetuses and peripheral blood of parents. Clinical reports including P and LP variants associated with the ultrasound phenotype and VUS variants highly consistent with the prenatal ultrasound phenotype were provided to the families. Results Demographic characteristics We analyzed WES results from 61 deceased fetuses, with 44.3% (27/61) submitted as singleton-only, 55.7 (34/61) as proband-parent trios. All cases terminated the pregnancies due to severe ultrasound abnormalities. The maternal age was from 22 to 38 years old (median 30 years); the mean gestational age was 21 weeks, with a range from 12 to 33 weeks and 1 day. A total of 15 women (25%) had previous pregnancy history of fetus with similar congenital malformations. There were 47.5% (N = 29) males and 52.5% (N =32) females based on fetal sex determined by WES data. The 61 cases were categorized into 10 classes according to the anatomical system affected, including skeletal system (14, 23.0%), multisystem (10, 16.4%), genitourinary (8, 13.1%), nervous system (6, 9.9%), facial region (6, 9.9%), cardiovascular (6, 9.9%), hydrops (4, 6.5%), stillbirth (4, 6.5%), growth abnormality (2, 3.3%), and abdominal (1, 1.6%). [Figure.1(A)]. Potential diagnostic variants and detection rate of WES in deceased fetuses Among the 61 cases included, 28 cases yielded a definitive diagnosis by WES with a detection rate of 45.9% (28/61), involving 39 variants in 18 genes (10 pathogenic variants, 22 likely pathogenic variants, and 7 VUS). Detailed phenotypic and variant information of the diagnostic cases were summarized in Table 1. Skeletal system abnormalities yielded the highest detected rate of 39.2% (11/28), followed by 17.9% (5/28) in multi-system, 17.9% (5/28) in genitourinary abnormalities, 7.1% (2/28) in facial abnormalities, 7.1% (2/28) in nervous system, and 3.6% (1/28) in fetal hydrops, cardiovascular system abnormalities, and stillbirth, respectively [Figure 1(B)].The diagnostic rate was 48.3% (14/29) for male fetuses and 43.8% (14/32) for female fetuses, the difference was not statistically significant (p=0.723) . The diagnostic rate of single system abnormalities was 45.1% (23/51), and that of two or more systems abnormalities was 50% (5/10). The diagnostic rate of two or more systems fetal abnormalities was slightly higher than that of single-system, but the difference was not statistically significant (p=0.776). Inheritance mode in the diagnosed cases Among the 28 cases with diagnostic results, 46.45% (13/28) were associated with autosomal dominant (AD) diseases, 46.45% (13/28) with autosomal recessive (AR) conditions, and 7.1% (2/28) with X-linked recessive diseases. A total of 11 variants had arisen de novo (3 cases with missense variant in FGFR3 , 2 cases with missense variant in COL1A1 , 4 cases with frameshift variant in SALL4 , KAT6B , ARIDA1 and COL1A1 , 1 case with nonsense variant in NOTCH 2, 1 cases with missense variant in GNAI3 ), all of them were associated with AD conditions. In remaining 15 cases with recessive pathogenic variants, 12 cases (80%) had biparentally inherited compound heterozygous variants, 1 case had homozygous variant (missense variant in ACE ) and 2 fetuses inherited the variant in chromosome X from the mother. Specially, in Case No.9, supratententate hydrocephalus with narrow transparent compartments was detected by ultrasound. A heterozygous variant of L1CAM was found in this female fetus by WES, which was inherited from the mother. The phenotype was consistent with X-linked cerebral edema (HSAS) caused by this gene. Although the condition was X-linked recessive inheritance, considering that similar fetal malformations were found in two previous pregnancies, the phenotypes in the current fetus maybe caused by skewed X-inactivation. In addition, 21 novel variants in 11 gene were found. The inheritance mode of 28 cases was listed in Table2. Disease categories involved in the diagnosed cases The most prevalent disease was skeletal disorders involving six genes ( FGFR3 , DYNC2H1 , COL1A1 , NEB , SALL4 , ECEL1 ) in 11 cases. FGFR3 associated with achondroplasia (100800) were identified in 3 cases, 4 cases of Asphyxiating Thoracic Dystrophy 3 (613091) were caused by DYNC2H1 . In the remaining 4 cases, each was found with pathogenic/likely pathogenic variants in COL1A1 associated with Osteogenesis Imperfecta, Type I (166200), NEB gene associated with Arthrogryposis Multiplex Congenital 6 (619334), SALL4 associated with Duane-radial Ray Syndrome (607323), ECEL1 associated with Arthrogryposis, Distal, Type 5d (615065), respectively. The second most common category was multi-system involving 5 genes- COL1A1 , FGFR3 , CAD , NOTCH2 , KAT6B -in 5 cases. For genitourinary system, variants in 3 genes- PKHD1 , JAG1 , ACE - were identified in 5 cases, among which 3 cases were Polycystic Kidney Disease 4 With Or Without Polycystic Liver Disease (263200) caused by PKHD1. In the remaining 2 cases, each was found with pathogenic/likely pathogenic variants in JAG1 gene associated with Alagille Syndrome 1 (118450), ACE gene associated with Renal Tubular Dysgenesis (267430). Variants in 2 genes- GNAI3 , TFAP2A- associated with facial region were identified in two cases. GNAI3 gene associated with Auriculocondylar Syndrome 1 (602483), TFAP2A gene associated with Branchiooculofacial Syndrome (113620). In addition, variants were identified in the other 4 phenotype categories involving 4 genes, including 2 cases of L1CAM associated with Hydrocephalus Due To Congenital Stenosis Of Aqueduct Of Sylvius (307000), PLAA associated with Neurodevelopmental Disorder With Progressive Microcephaly, Spasticity, and Brain Anomalies (617527), PIEZO1 associated with Lymphedema, Hereditary, Iii (616843), and ARID1A associated with Coffin-siris Syndrome 2 (614607). In case NO.2, we received a definitive diagnosis with the Alagille syndrome type 1 caused by heterozygous variation of JAG1 gene, which was an autosomal dominant inheritance, and the variation came from the mother. Of the remaining 33 cases without definitive diagnosis, there was one case with VUS. Abnormal development of both kidneys was found in prenatal imaging of one case, and heterozygous variant with uncertain significance of JAG1 was identified by singleton WES. Sanger sequencing indicated that the variant was inherited from the mother who did not show any clinical phenotype. Discussion WES can be used to explain the impact of monogenic disorders on pregnancy loss, elucidate the underlying genetic basis of structural developmental abnormality, establish a cause-effect relationship for fetal death, enable more accurate diagnosis of the disease Currently, it is an effective method in the prenatal setting for identification of the underlying genetic etiology of fetal ultrasound abnormalities [ 8 ]. By using G-banded karyotyping, microarray analysis and WES, previous studies showed that the diagnostic rates of chromosomal abnormalities, pathogenic CNVs and monogenic variations in cases of fetal structural anomalies were 50%, 4%, and 22–36%, respectively [ 9 ]. These results suggest that with the addition of WES, current genetic testing can identify specific genetic etiology in about three quarters of deceased fetuses. In 61 fetal WES cases with ultrasound structural abnormalities, 39 mutations of 18 genes were detected, and 28 cases received positive WES results, with a definite diagnosis rate of 45.9% (28/61) . Fu M et al [ 10 ]. conducted WES of 19 aborted tissues and detected a total of 36 variation sequences, among which 12 were pathogenicity variations, with a diagnosis rate as high as 33%. Elizabeth Quinlan-Jones et al [ 11 ]. performed ES in 27 deceased fetuses from induced labor or stillbirth due to ultrasound abnormalities, with a diagnostic rate of 37%. In another small study, Alamillo et al [ 12 ]. reported seven fetal specimens from pregnancies with ultrasound anomalies in which three had “positive” results and one had a “likely positive” result, for a detection rate of 43% (3/7) to 57% (4/7). In the study of Drury et al [ 13 ]. 14% of singleton cases had a positive result and this number increased to 30% when trios were analyzed. Yates et al [ 6 ]. performed WES in 84 deceased fetuses with structural anomalies with a diagnostic rate of 20%. In the Yates study, 52 performed parental/fetus trios with a diagnostic rate yield of 24%. In those probands with only fetal DNA tested, there was a lower diagnostic rate of 14%. This elevation of sensitivity is mostly due to the ability of performed parental/fetus trios to identify de novo variants and determine phase for variants identified in recessive genes. In our study, we reported WES data in 61 cases with structural anomalies, singleton cases obtained a diagnostic yield of 33.3% and this number increased to 55.9% when trios were analyzed. The disease categories classified in this study overlap considerably with those identified in previous studies of deceased fetuses, including multisystem diseases, urinary abnormalities, skeletal dysplasia, and central nervous system abnormalities. In our study, the diagnosis rate was higher than that of previous large-scale studies (22%-36%) [ 9 ]. This may be because the cases in this cohort had serious structural malformations, showing characteristic ultrasonic phenotypes. The most frequent ultrasound anomalies in the positive cases included skeletal systems, multi-system, nervous system and Genitourinary system anomalies. The most common diagnosis in this study was short-rib thoracic dysplasia type 3(SRTD3) with or without polydactyly caused by DYNC2H1 in 5 cases. All these cases had similar prenatal ultrasound finding of hypoplasia of the extremities, with compound heterozygous variants identified in DYNC2H1 . SRTD3 is a serious autosomal recessive fetal osteochondroplasia [ 14 ]. DYNC2H1 gene located at 11q22.3 encodes a large cytoplasmic dynamin involved in the structure and function of cilia, which is involved in the retrograde transport of cilia and affects the formation of chondrocytes [ 15 , 16 ]. Meanwhile, DYNC2H1 gene defect leads to the disruption of the Hedgehog signaling pathway, which affects the proliferation and differentiation of osteoblasts and chondrocytes, leading to chondroplasia [ 17 , 18 ]. This gene mutation often leads to severe fetal malformation, and it is a serious fatal condition that dies after birth due to severe respiratory failure. Case NO.2 was found to have renal cystic dysplasia on prenatal ultrasonography and also demonstrated Oligohydramnios. WES analysis revealed a JAG1 heterozygous splice variant consistent with a diagnosis of Alagille syndrome. JAG1 gene can encode protein jagged-1 (JAG1) [ 19 ], a surface ligand in the highly conserved Notch signaling pathway, which can interact with the Notch receptor to regulate gene transcription [ 20 ]. The disease does not often lead to intrauterine death, it has well-defined postnatal phenotypes. More than 95 percent of ALGS patients develop heart defects. Butterfly vertebrae and special facial features (triangular face, pointed chin) are also characteristic of Alagille syndrome [ 21 , 22 ]. In addition to these features, most patients also have renal and vascular abnormalities. The current fetus showed renal abnormalities, and the variant was inherited from the mother, an imaging examination of the mother found that both kidneys were small accompanied by multiple cystic echoes. This suggests the effect of JAG1 gene variant on renal development. However,abnormal development of both kidneys was found in prenatal imaging of one negative case and heterozygous variant with unknown significance of JAG1 was identified by WES. This variation was derived from the mother, but the mother did not have similar clinical phenotype, which may be caused by the heterogeneity of JAG1 gene or the phenotypic diversity related to JAG1 gene. Of the 11 de novo mutations, variants in FGFR3 genes associated with achondroplasia were identified in three cases. Prenatal ultrasound in all of these fetuses revealed severe long bone shortness and constriction of the thorax. This missense mutation resulted in a fatal prenatal phenotype of bone dysplasia. The variant identified in the FGFR3 gene, p.Arg248Cys is identical to the previously reported FGFR3 gene variant, which has been reported in cases of fetal death [ 23 ]. By analyzing the entire exome cohort of fetus with ultrasound abnormalities, the trio allows for a broader search of disease-causing genes, including some de novo mutations and some recessive genes. For families with de novo mutations, they can be directly informed of the low risk of recurrence in the second pregnancy, despite the possibility of parental low-level mosaicism which is very rare. These with definitive diagnosed recessive inheritance patterns have high recurrence risks then had the option for invasive prenatal diagnosis in the subsequent pregnancy to ascertain if the fetus was affected with the same condition. The relationship between fetal phenotype and genotype was established to clarify that the genetic causes of fetal abnormalities were dependent on gestational age of the fetus, the experience of geneticists and the type of imaging utilized. For a fetus with ultrasound abnormalities, it is difficult to identify accurate fetal phenotype due to the difference in gestational age corresponding to the stage of fetal development. Fetal different developmental stage show different phenotype and fetal position change under examination, at the same time, due to differences in the levels of clinical experience, prenatal imaging examination sometimes cannot accurately identified the clinical phenotype of fetus, thus genetic physicians cannot be accurately established the relationship of genotype and phenotype. It brought challenge to WES diagnosis and analysis. Conclusions In conclusion, ultrasound imaging does not provide an accurate diagnosis due to the lack of adequate phenotypic information in this early stage of fetal development. The application of WES technology has improved the diagnostic rate of fetus with ultrasound abnormalities and identified the pathogenic effect of monogenic disease. In our cohort, we identified variants in genes known to manifest prenatally and the molecular diagnosis was consistent with the ultrasound findings. By combining this strategy with prenatal imaging, clinicians can help more couples with fetal malformations to identify the underlying genetic etiology and evaluate the recurrence risk. For families with a high risk of recurrence, more accurate counseling and planning can be provided in terms of risk assessment and clinical management. Abbreviations WES: Whole-exome sequencing; CNV-seq: Copy Number Variation Sequencing; P:Pathogenic; LP: Likely pathogenic; VUS: Variants of uncertain significance; POC: Product of concepts; GATK: Genome Analysis Tool kit; ExAC: Human exons database; HGMD: Human Gene Mutation Database; OMIM: Online Mendelian Inheritance in Man; ACMG: American College of Medical Genetics and Genomics; AD: Autosomal dominant; AR: Autosomal recessive; XLR: X-linked recessive. Declarations Acknowledgements We would like to thank all the patients and their family members who contributed their samples and information for this study Funding This study was supported by Key Scientific Research Projects in Colleges and Universities of Henan Province (22A320075) and Henan Province Medical Science and Technique Foundation (SBGJ202102097). Authors’ contributions Huang Wei: writing-original draft preparation, acquisition of data. Sun Gege, Zhu Xiaofan: to conduct the molecular genetic studies and participated in the sequence alignment. Huang Wei, Sun Gege, Zhu Xiaofan, Gao Zhi: analysis and interpretation of data. Huang Wei, Kong Xiangdong conceived of the study, participated in the design research. All authors have read and agreed to the published version of the manuscript. Availability of data and materials Data generated or analyzed during this study are included in this published article. Data supporting the manuscript can be requested from the corresponding author. The web links of the relevant datasets were as follows: hg19 (http://genome.ucsc.edu), Clinvar (http://www.ncbi.nlm.nih.gov/clinvar/), ExAC (http://exac.broad.institute.org/), HGMD (http://www.hgmd.cf.ac.uk/) and OMIM (http://www.omim.org). Ethics approval and consent to participate The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the First Affiliated Hospital of Zhengzhou University Committee, Zhengzhou, China (2020-KY-0393-002). Informed consent was obtained from patients at the time of genetic sample collection.. Consent for publication Informed consent was obtained from all subjects involved in the study. Competing interests The authors declare that they have no competing interests Author details 1 Genetics and Prenatal Diagnosis Center, Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China 450052 References He M, Du L, Xie H, Zhang L, Gu Y, Lei T, Zheng J, Chen D: The Added Value of Whole-Exome Sequencing for Anomalous Fetuses With Detailed Prenatal Ultrasound and Postnatal Phenotype. Front Genet 2021, 12:627204. Zhu X, Gao Z, Wang Y, Huang W, Li Q, Jiao Z, Liu N, Kong X: Implementation of trio-based prenatal exome sequencing incorporating splice-site and mitochondrial genome assessment in pregnancies with fetal structural anomalies: prospective cohort study. Ultrasound Obstet Gynecol 2022. Persson M, Cnattingius S, Villamor E, Soderling J, Pasternak B, Stephansson O, Neovius M: Risk of major congenital malformations in relation to maternal overweight and obesity severity: cohort study of 1.2 million singletons. BMJ 2017, 357:j2563. Zhou Q, Wu SY, Amato K, DiAdamo A, Li P: Spectrum of Cytogenomic Abnormalities Revealed by Array Comparative Genomic Hybridization on Products of Conception Culture Failure and Normal Karyotype Samples. J Genet Genomics 2016, 43(3):121-131. van den Veyver IB, Eng CM: Genome-Wide Sequencing for Prenatal Detection of Fetal Single-Gene Disorders. Cold Spring Harb Perspect Med 2015, 5(10). Yates CL, Monaghan KG, Copenheaver D, Retterer K, Scuffins J, Kucera CR, Friedman B, Richard G, Juusola J: Whole-exome sequencing on deceased fetuses with ultrasound anomalies: expanding our knowledge of genetic disease during fetal development. Genet Med 2017, 19(10):1171-1178. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, Grody WW, Hegde M, Lyon E, Spector E et al : Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 2015, 17(5):405-424. Stark Z, Tan TY, Chong B, Brett GR, Yap P, Walsh M, Yeung A, Peters H, Mordaunt D, Cowie S et al : A prospective evaluation of whole-exome sequencing as a first-tier molecular test in infants with suspected monogenic disorders. Genet Med 2016, 18(11):1090-1096. Zhao C, Chai H, Zhou Q, Wen J, Reddy UM, Kastury R, Jiang Y, Mak W, Bale AE, Zhang H et al : Exome sequencing analysis on products of conception: a cohort study to evaluate clinical utility and genetic etiology for pregnancy loss. Genet Med 2021, 23(3):435-442. Fu M, Mu S, Wen C, Jiang S, Li L, Meng Y, Peng H: Wholeexome sequencing analysis of products of conception identifies novel mutations associated with missed abortion. Mol Med Rep 2018, 18(2):2027-2032. Quinlan-Jones E, Lord J, Williams D, Hamilton S, Marton T, Eberhardt RY, Rinck G, Prigmore E, Keelagher R, McMullan DJ et al : Molecular autopsy by trio exome sequencing (ES) and postmortem examination in fetuses and neonates with prenatally identified structural anomalies. Genet Med 2019, 21(5):1065-1073. Alamillo CL, Powis Z, Farwell K, Shahmirzadi L, Weltmer EC, Turocy J, Lowe T, Kobelka C, Chen E, Basel D et al : Exome sequencing positively identified relevant alterations in more than half of cases with an indication of prenatal ultrasound anomalies. Prenat Diagn 2015, 35(11):1073-1078. Drury S, Williams H, Trump N, Boustred C, Gosgene, Lench N, Scott RH, Chitty LS: Exome sequencing for prenatal diagnosis of fetuses with sonographic abnormalities. Prenat Diagn 2015, 35(10):1010-1017. Mei L, Huang Y, Pan Q, Su W, Quan Y, Liang D, Wu L: Targeted next-generation sequencing identifies novel compound heterozygous mutations of DYNC2H1 in a fetus with short rib-polydactyly syndrome, type III. Clin Chim Acta 2015, 447:47-51. Dagoneau N, Goulet M, Genevieve D, Sznajer Y, Martinovic J, Smithson S, Huber C, Baujat G, Flori E, Tecco L et al : DYNC2H1 mutations cause asphyxiating thoracic dystrophy and short rib-polydactyly syndrome, type III. Am J Hum Genet 2009, 84(5):706-711. Schmidts M, Arts HH, Bongers EM, Yap Z, Oud MM, Antony D, Duijkers L, Emes RD, Stalker J, Yntema JB et al : Exome sequencing identifies DYNC2H1 mutations as a common cause of asphyxiating thoracic dystrophy (Jeune syndrome) without major polydactyly, renal or retinal involvement. J Med Genet 2013, 50(5):309-323. Rix S, Calmont A, Scambler PJ, Beales PL: An Ift80 mouse model of short rib polydactyly syndromes shows defects in hedgehog signalling without loss or malformation of cilia. Hum Mol Genet 2011, 20(7):1306-1314. Ocbina PJ, Eggenschwiler JT, Moskowitz I, Anderson KV: Complex interactions between genes controlling trafficking in primary cilia. Nat Genet 2011, 43(6):547-553. Grochowski CM, Loomes KM, Spinner NB: Jagged1 (JAG1): Structure, expression, and disease associations. Gene 2016, 576(1 Pt 3):381-384. Bray SJ: Notch signalling in context. Nat Rev Mol Cell Biol 2016, 17(11):722-735. Turnpenny PD, Ellard S: Alagille syndrome: pathogenesis, diagnosis and management. Eur J Hum Genet 2012, 20(3):251-257. Mitchell E, Gilbert M, Loomes KM: Alagille Syndrome. Clin Liver Dis 2018, 22(4):625-641. Lord J, McMullan DJ, Eberhardt RY, Rinck G, Hamilton SJ, Quinlan-Jones E, Prigmore E, Keelagher R, Best SK, Carey GK et al : Prenatal exome sequencing analysis in fetal structural anomalies detected by ultrasonography (PAGE): a cohort study. Lancet 2019, 393(10173):747-757. Tables Table 1 is available in the Supplementary Files section Table 2 Models of inheritance observed across 2 8 molecular diagnoses in 61 cases Mode of Inheritance Number of Diagnoses Percent of Diagnoses Number of novel variants Autosomal dominant 13 46.45% 4 De novo 11 2 Inherited maternal 1 Inherited,paternal 1 2 Autosomal recessive 13 46.45% 17 Homozygous 1 Compound heterozygous 12 17 X-linked 2 7.1% Inherited maternal 2 Additional Declarations No competing interests reported. Supplementary Files Table1.docx Cite Share Download PDF Status: Published Journal Publication published 16 Feb, 2023 Read the published version in BMC Medical Genomics → Version 1 posted Editorial decision: Major revision 15 Nov, 2022 Reviews received at journal 11 Nov, 2022 Reviewers agreed at journal 03 Nov, 2022 Reviews received at journal 01 Nov, 2022 Reviewers agreed at journal 26 Oct, 2022 Reviewers invited by journal 06 Oct, 2022 Editor assigned by journal 06 Oct, 2022 Editor invited by journal 06 Oct, 2022 Submission checks completed at journal 06 Oct, 2022 First submitted to journal 30 Sep, 2022 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-2118883","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":142184816,"identity":"d4315e1f-9aa3-494a-8914-945c7d42a10d","order_by":0,"name":"Wei Huang","email":"","orcid":"","institution":"First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Huang","suffix":""},{"id":142184818,"identity":"2bfcb673-4f1b-4c85-ba6a-e0a75d1300a3","order_by":1,"name":"Xiaofan Zhu","email":"","orcid":"","institution":"First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaofan","middleName":"","lastName":"Zhu","suffix":""},{"id":142184819,"identity":"682efcba-b009-4b25-84c0-a52ec8f62f45","order_by":2,"name":"Gege Sun","email":"","orcid":"","institution":"First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Gege","middleName":"","lastName":"Sun","suffix":""},{"id":142184820,"identity":"6775dea6-ba0b-4dc9-98ce-bb2ab43c93cf","order_by":3,"name":"Zhi Gao","email":"","orcid":"","institution":"First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhi","middleName":"","lastName":"Gao","suffix":""},{"id":142184821,"identity":"6ead0636-5cf5-40a8-863c-e3023e9039d7","order_by":4,"name":"Xiangdong Kong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYBACCTDJZiPHz99AmpY0Y8kZB4CMBOK1HE7c0JBApBbJ9t7Dr3nKzjNuYDjA9uDjDyK0SPOcS7Occe42szlzA7vhDGJskZPIMTP42HabzbLhAJs0D9FaEtvO8RgcSGCT/kOMFmmJHOMHH9sOSIC1EOf9njNmjDPOJRtIzjjYJtmTRoQWieM9xp95yuzq+/mbj0n8sCFCCxCwQeKGgbGBOPVAwPyBaKWjYBSMglEwMgEA1lc1Bsnz0CgAAAAASUVORK5CYII=","orcid":"","institution":"First Affiliated Hospital of Zhengzhou University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Xiangdong","middleName":"","lastName":"Kong","suffix":""}],"badges":[],"createdAt":"2022-09-30 05:59:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2118883/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2118883/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12920-022-01427-1","type":"published","date":"2023-02-16T18:57:20+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":27633217,"identity":"f857984d-232b-4d6f-915e-80b7799d60d0","added_by":"auto","created_at":"2022-10-11 17:45:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":173281,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhenotypic spectrum of fetuses with ultrasound anomalies undergoing ES\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003e Scaled representation of relative frequency of each phenotype class within this series.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(B)\u003c/strong\u003e Diagnostic rate for each phenotype class in positive case\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2118883/v1/cbd8ff12fca39b1cac34fc01.png"},{"id":44719818,"identity":"f0bb992c-a9f6-4901-bd44-718f9c9413bd","added_by":"auto","created_at":"2023-10-16 19:02:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":538936,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2118883/v1/ced5d301-4993-4a38-87a1-114dd314bfb6.pdf"},{"id":27633218,"identity":"8f60bb06-04d8-46e1-8c94-a9b6835ff6b9","added_by":"auto","created_at":"2022-10-11 17:45:08","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":23681,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-2118883/v1/d7126ba42527a6fe1ec59fb9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Whole-exome Sequencing in deceased fetuses with ultrasound anomalies: A Retrospective Analysis","fulltext":[{"header":"Background","content":"\u003cp\u003eCongenital structural abnormalities are identified in approximately 3% of fetuses, accounting for 25% of perinatal deaths[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Fetal structural abnormalities can vary from isolated minor anomalies to severe multi-system abnormalities, which can be effectively identified by prenatal ultrasound[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The identification of fetal ultrasound anomalies prompts additional prenatal evaluations. Most of the structural abnormalities indicated by prenatal ultrasound occur in fetuses with no family history of congenital malformation, making accurate prenatal genetic counseling difficult. Therefore, it is necessary to clarify the genetic etiology of fetal structural abnormalities. Chromosomal abnormalities and monogenic disorders have been considered as major causes of birth defects, although the etiology of many congenital malformations is unknown. G-banded karyotyping identified numerical and structural chromosomal abnormalities in 50% of fetuses with ultrasound abnormalities, low-coverage genome sequencing (eg. CNV-seq) increases the detection rate in this group of fetuses by up to 5%[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, identifiable genetic cause is still undetected in over 60% of cases. Whole-exome sequencing (WES), can identify the genetic etiology by identifying the single gene pathogenic variation of fetal structural abnormalities. According to previous studies, WES can be used to discover the genetic causes of fetal structural abnormalities, identify pathogenic variations, and establish genotype-phenotypic associations[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, the method of WES was used in this study to analyze the 61 causes of fetal specimens terminated due to structural abnormalities indicated by ultrasound.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSubjects\u003c/h2\u003e \u003cp\u003eFetal WES cases were retrospectively collected from pregnancies with ultrasound anomalies that were terminated or resulted in fetal demise between October 2020 and May 2022. All cases had previously undergone CNV-seq and no clinically significant variants were detected. Fetal phenotype information was obtained from prenatal ultrasound and fetal magnetic resonance imaging reports. All the couples were not consanguineous. Pregnant women with known teratogen, uterine malformation, hypertension, diabetes, and other basic diseases were also excluded. Ethics approval to undertake the research was granted by the First Affiliated Hospital of Zhengzhou University Committee.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSequencing analysis and variant annotation of WES\u003c/h2\u003e \u003cp\u003eFetal genomic DNA was obtained from products of conception (POC) including chorionic villi and fetal skin tissues. Parental DNA was extracted from peripheral blood samples. The genomic DNA of deceased fetuses and their parents were extracted using the QIAamp DNA extraction kit (Qiagen, Germany), then quantified by using Qubit 4.0 (Thermo Fisher Scientific Inc. USA). DNA libraries were established by using Ada \u0026amp; Index Kit (UDI for LIM) and Enzyme Plus Library Prep Kit (iGeneTech Co., Ltd, Beijing, China), and exome coding and splicing regions were captured using AIExome Human Exome Panel V2 Plus with TargetSeq One Hyb \u0026amp; Wash Kit (iGeneTech Co., Ltd, Beijing, China), according to the manufacturer\u0026rsquo;s instructions. Subsequently, the captured libraries were sequenced on the NovaSeq6000 platform (Illumina, San Diego, CA, USA) with the average sequencing depth\u0026thinsp;\u0026gt;\u0026thinsp;100X and 20X sequencing coverage\u0026thinsp;\u0026gt;\u0026thinsp;98%. Sentieon(release 201808.05) was used to align paired-end reads with the human reference genome GRCh37/hg19 under the Genome Analysis Toolkit(GATK) best practice guidelines, and the duplicate reads were removed using Picard version 2.9.0. Candidate variants were assessed with latest reports in the online databases, such as ClinVar, Human exons database (ExAC), Human Gene Mutation Database (HGMD) and Online Mendelian Inheritance in Man (OMIM) databases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eVariant interpretation and classification\u003c/h2\u003e \u003cp\u003eVariants were classified into pathogenic variants, likely pathogenic variants, variants of uncertain significance (VUS), likely benign variants, and benign variants according to the guidelines of the American College of Medical Genetics and Genomics(ACMG)[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The pathogenic and likely pathogenic variants were further analyzed in conjunction with prenatal imaging to determine whether they fully and partially explain the observed phenotype. Polymerase chain reaction (PCR) combined with Sanger sequencing were used to validate the candidate P/LP variants in specimens of deceased fetuses and peripheral blood of parents. Clinical reports including P and LP variants associated with the ultrasound phenotype and VUS variants highly consistent with the prenatal ultrasound phenotype were provided to the families.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDemographic characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe analyzed WES results from 61 deceased fetuses, with 44.3% (27/61) submitted as singleton-only, 55.7 (34/61) as proband-parent trios. All cases terminated the pregnancies due to severe ultrasound abnormalities. The maternal age was from 22 to 38 years old (median 30 years); the mean gestational age was 21 weeks, with a range from 12 to 33 weeks and 1 day. A total of 15 women (25%) had previous pregnancy history of fetus with similar congenital malformations. There were 47.5% (N = 29) males and 52.5% (N =32) females based on fetal sex determined by WES data. The 61 cases were categorized into 10 classes according to the anatomical system affected, including skeletal system (14, 23.0%), multisystem (10, 16.4%), genitourinary (8, 13.1%), nervous system (6, 9.9%), facial region (6, 9.9%), cardiovascular (6, 9.9%), hydrops (4, 6.5%), stillbirth (4, 6.5%), growth abnormality (2, 3.3%), and abdominal (1, 1.6%). [Figure.1(A)].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePotential diagnostic variants and detection rate of WES in deceased fetuses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the 61 cases included, 28 cases yielded a definitive diagnosis by WES with a detection rate of 45.9% (28/61), involving 39 variants in 18 genes (10 pathogenic variants, 22 likely pathogenic variants, and 7 VUS). Detailed phenotypic and variant information of the diagnostic cases were summarized in Table 1. Skeletal system abnormalities yielded the highest detected rate of 39.2% (11/28), followed by 17.9% (5/28) in multi-system, 17.9% (5/28) in genitourinary abnormalities, 7.1% (2/28) in facial abnormalities, 7.1% (2/28) in nervous system, and 3.6% (1/28) in fetal hydrops, cardiovascular system abnormalities, and stillbirth, respectively [Figure 1(B)].The diagnostic rate was 48.3% (14/29) for male fetuses and 43.8% (14/32) for female fetuses, the difference was not statistically significant (p=0.723) . The diagnostic rate of single system abnormalities was 45.1% (23/51), and that of two or more systems abnormalities was 50% (5/10). The diagnostic rate of two or more systems fetal abnormalities was slightly higher than that of single-system, but the difference was not statistically significant (p=0.776).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInheritance mode in the diagnosed cases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the 28 cases with diagnostic results, 46.45% (13/28) were associated with autosomal dominant (AD) diseases, 46.45% (13/28) with autosomal recessive (AR) conditions, and 7.1% (2/28) with X-linked recessive diseases. A total of\u0026nbsp;11 variants had arisen \u003cem\u003ede novo\u003c/em\u003e (3 cases with missense variant in\u003cem\u003e\u0026nbsp;FGFR3\u003c/em\u003e, 2 cases with missense variant in \u003cem\u003eCOL1A1\u003c/em\u003e, 4 cases with frameshift variant in \u003cem\u003eSALL4\u003c/em\u003e, \u003cem\u003eKAT6B\u003c/em\u003e, \u003cem\u003eARIDA1\u003c/em\u003e and \u003cem\u003eCOL1A1\u003c/em\u003e, 1 case with nonsense variant in\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eNOTCH\u003c/em\u003e2, 1 cases with missense variant in \u003cem\u003eGNAI3\u003c/em\u003e), all of them were associated with AD conditions. In remaining 15 cases with recessive pathogenic variants, 12 cases (80%) had biparentally inherited compound heterozygous variants, 1 case had homozygous variant (missense variant in \u003cem\u003eACE\u003c/em\u003e) and 2 fetuses inherited the variant in chromosome X from the mother. Specially, in Case\u0026nbsp;No.9, supratententate hydrocephalus with narrow transparent compartments was detected by ultrasound. A heterozygous variant of \u003cem\u003eL1CAM\u003c/em\u003e was found in this female fetus by WES, which was inherited from the mother. The phenotype was consistent with X-linked cerebral edema (HSAS) caused by this gene. Although the condition was X-linked recessive inheritance, considering that similar fetal malformations were found in two previous pregnancies, the phenotypes in the current fetus maybe caused by skewed X-inactivation.\u0026nbsp;In addition, 21 novel variants in 11 gene were found.\u0026nbsp;The inheritance mode of 28 cases was listed in Table2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisease categories involved in the diagnosed cases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe most prevalent disease was skeletal disorders involving six genes (\u003cem\u003eFGFR3\u003c/em\u003e, \u003cem\u003eDYNC2H1\u003c/em\u003e, \u003cem\u003eCOL1A1\u003c/em\u003e, \u003cem\u003eNEB\u003c/em\u003e, \u003cem\u003eSALL4\u003c/em\u003e, \u003cem\u003eECEL1\u003c/em\u003e) in 11 cases. \u003cem\u003eFGFR3\u0026nbsp;\u003c/em\u003eassociated with achondroplasia (100800) were identified in 3 cases, 4 cases of Asphyxiating Thoracic Dystrophy 3 (613091) were caused by \u003cem\u003eDYNC2H1\u003c/em\u003e. In the remaining 4 cases, each was found with pathogenic/likely pathogenic variants in \u003cem\u003eCOL1A1\u003c/em\u003e associated with Osteogenesis Imperfecta, Type I (166200), \u003cem\u003eNEB\u003c/em\u003e gene associated with Arthrogryposis Multiplex Congenital 6 (619334), \u003cem\u003eSALL4\u003c/em\u003e associated with Duane-radial Ray Syndrome (607323), \u003cem\u003eECEL1\u003c/em\u003e associated with Arthrogryposis, Distal, Type 5d (615065), respectively. The second most common category was multi-system involving 5 genes-\u003cem\u003eCOL1A1\u003c/em\u003e, \u003cem\u003eFGFR3\u003c/em\u003e, \u003cem\u003eCAD\u003c/em\u003e, \u003cem\u003eNOTCH2\u003c/em\u003e, \u003cem\u003eKAT6B\u003c/em\u003e-in 5 cases. For genitourinary system, variants in 3 genes-\u003cem\u003ePKHD1\u003c/em\u003e, \u003cem\u003eJAG1\u003c/em\u003e, \u003cem\u003eACE\u003c/em\u003e- were identified in 5 cases, among which 3 cases were Polycystic Kidney Disease 4 With Or Without Polycystic Liver Disease (263200) caused by \u003cem\u003ePKHD1.\u003c/em\u003e In the remaining 2 cases, each was found with pathogenic/likely pathogenic variants in \u003cem\u003eJAG1\u003c/em\u003e gene associated with Alagille Syndrome 1 (118450), \u003cem\u003eACE\u003c/em\u003e gene associated with Renal Tubular Dysgenesis (267430). Variants in 2 genes-\u003cem\u003eGNAI3\u003c/em\u003e, \u003cem\u003eTFAP2A-\u003c/em\u003eassociated with facial region were identified in two cases. \u003cem\u003eGNAI3\u003c/em\u003e gene associated with\u003cem\u003e\u0026nbsp;\u003c/em\u003eAuriculocondylar Syndrome 1 (602483), \u003cem\u003eTFAP2A\u003c/em\u003e gene associated with\u003cem\u003e\u0026nbsp;\u003c/em\u003eBranchiooculofacial Syndrome (113620). In addition, variants were identified in the other 4 phenotype categories involving 4 genes, including 2 cases of \u003cem\u003eL1CAM\u0026nbsp;\u003c/em\u003eassociated with Hydrocephalus Due To Congenital Stenosis Of Aqueduct Of Sylvius (307000), \u003cem\u003ePLAA\u0026nbsp;\u003c/em\u003eassociated with Neurodevelopmental Disorder With Progressive Microcephaly, Spasticity, and Brain Anomalies (617527), \u003cem\u003ePIEZO1\u003c/em\u003e associated with Lymphedema, Hereditary, Iii (616843), and \u003cem\u003eARID1A\u003c/em\u003e associated with Coffin-siris Syndrome 2 (614607).\u003c/p\u003e\n\u003cp\u003eIn case NO.2, we received a definitive diagnosis with the Alagille syndrome type 1 caused by heterozygous variation of \u003cem\u003eJAG1\u0026nbsp;\u003c/em\u003egene, which was an autosomal dominant inheritance, and the variation came from the mother. Of the remaining 33 cases without definitive diagnosis, there was one case with VUS. Abnormal development of both kidneys was found in prenatal imaging of \u0026nbsp;one case, and heterozygous variant with uncertain significance of \u003cem\u003eJAG1\u003c/em\u003e was identified by singleton WES. Sanger sequencing indicated that the variant was inherited from the mother who did not show any clinical phenotype.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWES can be used to explain the impact of monogenic disorders on pregnancy loss, elucidate the underlying genetic basis of structural developmental abnormality, establish a cause-effect relationship for fetal death, enable more accurate diagnosis of the disease Currently, it is an effective method in the prenatal setting for identification of the underlying genetic etiology of fetal ultrasound abnormalities [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. By using G-banded karyotyping, microarray analysis and WES, previous studies showed that the diagnostic rates of chromosomal abnormalities, pathogenic CNVs and monogenic variations in cases of fetal structural anomalies were 50%, 4%, and 22\u0026ndash;36%, respectively [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. These results suggest that with the addition of WES, current genetic testing can identify specific genetic etiology in about three quarters of deceased fetuses. In 61 fetal WES cases with ultrasound structural abnormalities, 39 mutations of 18 genes were detected, and 28 cases received positive WES results, with a definite diagnosis rate of 45.9% (28/61) .\u003c/p\u003e \u003cp\u003eFu M et al [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. conducted WES of 19 aborted tissues and detected a total of 36 variation sequences, among which 12 were pathogenicity variations, with a diagnosis rate as high as 33%. Elizabeth Quinlan-Jones et al [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. performed ES in 27 deceased fetuses from induced labor or stillbirth due to ultrasound abnormalities, with a diagnostic rate of 37%. In another small study, Alamillo et al [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. reported seven fetal specimens from pregnancies with ultrasound anomalies in which three had \u0026ldquo;positive\u0026rdquo; results and one had a \u0026ldquo;likely positive\u0026rdquo; result, for a detection rate of 43% (3/7) to 57% (4/7). In the study of Drury et al [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. 14% of singleton cases had a positive result and this number increased to 30% when trios were analyzed. Yates et al [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. performed WES in 84 deceased fetuses with structural anomalies with a diagnostic rate of 20%. In the Yates study, 52 performed parental/fetus trios with a diagnostic rate yield of 24%. In those probands with only fetal DNA tested, there was a lower diagnostic rate of 14%. This elevation of sensitivity is mostly due to the ability of performed parental/fetus trios to identify \u003cem\u003ede novo\u003c/em\u003e variants and determine phase for variants identified in recessive genes. In our study, we reported WES data in 61 cases with structural anomalies, singleton cases obtained a diagnostic yield of 33.3% and this number increased to 55.9% when trios were analyzed. The disease categories classified in this study overlap considerably with those identified in previous studies of deceased fetuses, including multisystem diseases, urinary abnormalities, skeletal dysplasia, and central nervous system abnormalities. In our study, the diagnosis rate was higher than that of previous large-scale studies (22%-36%) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This may be because the cases in this cohort had serious structural malformations, showing characteristic ultrasonic phenotypes.\u003c/p\u003e \u003cp\u003eThe most frequent ultrasound anomalies in the positive cases included skeletal systems, multi-system, nervous system and Genitourinary system anomalies. The most common diagnosis in this study was short-rib thoracic dysplasia type 3(SRTD3) with or without polydactyly caused by \u003cem\u003eDYNC2H1\u003c/em\u003e in 5 cases. All these cases had similar prenatal ultrasound finding of hypoplasia of the extremities, with compound heterozygous variants identified in \u003cem\u003eDYNC2H1\u003c/em\u003e. SRTD3 is a serious autosomal recessive fetal osteochondroplasia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. \u003cem\u003eDYNC2H1\u003c/em\u003e gene located at 11q22.3 encodes a large cytoplasmic dynamin involved in the structure and function of cilia, which is involved in the retrograde transport of cilia and affects the formation of chondrocytes [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Meanwhile, \u003cem\u003eDYNC2H1\u003c/em\u003e gene defect leads to the disruption of the Hedgehog signaling pathway, which affects the proliferation and differentiation of osteoblasts and chondrocytes, leading to chondroplasia [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This gene mutation often leads to severe fetal malformation, and it is a serious fatal condition that dies after birth due to severe respiratory failure. Case NO.2 was found to have renal cystic dysplasia on prenatal ultrasonography and also demonstrated Oligohydramnios. WES analysis revealed a \u003cem\u003eJAG1\u003c/em\u003e heterozygous splice variant consistent with a diagnosis of Alagille syndrome. \u003cem\u003eJAG1\u003c/em\u003e gene can encode protein jagged-1 (JAG1) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], a surface ligand in the highly conserved Notch signaling pathway, which can interact with the Notch receptor to regulate gene transcription [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The disease does not often lead to intrauterine death, it has well-defined postnatal phenotypes. More than 95 percent of ALGS patients develop heart defects. Butterfly vertebrae and special facial features (triangular face, pointed chin) are also characteristic of Alagille syndrome [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In addition to these features, most patients also have renal and vascular abnormalities. The current fetus showed renal abnormalities, and the variant was inherited from the mother, an imaging examination of the mother found that both kidneys were small accompanied by multiple cystic echoes. This suggests the effect of \u003cem\u003eJAG1\u003c/em\u003e gene variant on renal development. However,abnormal development of both kidneys was found in prenatal imaging of one negative case and heterozygous variant with unknown significance of \u003cem\u003eJAG1\u003c/em\u003e was identified by WES. This variation was derived from the mother, but the mother did not have similar clinical phenotype, which may be caused by the heterogeneity of \u003cem\u003eJAG1\u003c/em\u003e gene or the phenotypic diversity related to \u003cem\u003eJAG1\u003c/em\u003e gene.\u003c/p\u003e \u003cp\u003eOf the 11 \u003cem\u003ede novo\u003c/em\u003e mutations, variants in \u003cem\u003eFGFR3\u003c/em\u003e genes associated with achondroplasia were identified in three cases. Prenatal ultrasound in all of these fetuses revealed severe long bone shortness and constriction of the thorax. This missense mutation resulted in a fatal prenatal phenotype of bone dysplasia. The variant identified in the \u003cem\u003eFGFR3\u003c/em\u003e gene, p.Arg248Cys is identical to the previously reported \u003cem\u003eFGFR3\u003c/em\u003e gene variant, which has been reported in cases of fetal death [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. By analyzing the entire exome cohort of fetus with ultrasound abnormalities, the trio allows for a broader search of disease-causing genes, including some \u003cem\u003ede novo\u003c/em\u003e mutations and some recessive genes. For families with \u003cem\u003ede novo\u003c/em\u003e mutations, they can be directly informed of the low risk of recurrence in the second pregnancy, despite the possibility of parental low-level mosaicism which is very rare. These with definitive diagnosed recessive inheritance patterns have high recurrence risks then had the option for invasive prenatal diagnosis in the subsequent pregnancy to ascertain if the fetus was affected with the same condition.\u003c/p\u003e \u003cp\u003eThe relationship between fetal phenotype and genotype was established to clarify that the genetic causes of fetal abnormalities were dependent on gestational age of the fetus, the experience of geneticists and the type of imaging utilized. For a fetus with ultrasound abnormalities, it is difficult to identify accurate fetal phenotype due to the difference in gestational age corresponding to the stage of fetal development. Fetal different developmental stage show different phenotype and fetal position change under examination, at the same time, due to differences in the levels of clinical experience, prenatal imaging examination sometimes cannot accurately identified the clinical phenotype of fetus, thus genetic physicians cannot be accurately established the relationship of genotype and phenotype. It brought challenge to WES diagnosis and analysis.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, ultrasound imaging does not provide an accurate diagnosis due to the lack of adequate phenotypic information in this early stage of fetal development. The application of WES technology has improved the diagnostic rate of fetus with ultrasound abnormalities and identified the pathogenic effect of monogenic disease. In our cohort, we identified variants in genes known to manifest prenatally and the molecular diagnosis was consistent with the ultrasound findings. By combining this strategy with prenatal imaging, clinicians can help more couples with fetal malformations to identify the underlying genetic etiology and evaluate the recurrence risk. For families with a high risk of recurrence, more accurate counseling and planning can be provided in terms of risk assessment and clinical management.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eWES: Whole-exome sequencing; CNV-seq: Copy Number Variation Sequencing; P:Pathogenic; LP: Likely pathogenic; VUS: Variants of uncertain significance; POC: Product of concepts; GATK: Genome Analysis Tool kit; ExAC: Human exons database; HGMD: Human Gene Mutation Database; OMIM: Online Mendelian Inheritance in Man; ACMG: American College of Medical Genetics and Genomics; AD: Autosomal dominant; AR: Autosomal recessive; XLR: X-linked recessive.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all the patients and their family members who contributed their samples and information for this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Key Scientific Research Projects in Colleges and Universities of Henan Province (22A320075) and Henan Province Medical Science and Technique Foundation (SBGJ202102097).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuang Wei: writing-original draft preparation, acquisition of data. Sun Gege, Zhu Xiaofan: to conduct the molecular genetic studies and participated in the sequence alignment. Huang Wei, Sun Gege, Zhu Xiaofan, Gao Zhi: analysis and interpretation of data. Huang Wei, Kong Xiangdong conceived of the study, participated in the design research. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData generated or analyzed during this study are included in this published article. Data supporting the manuscript can be requested from the corresponding author. The web links of the relevant datasets were as follows: hg19 (http://genome.ucsc.edu), Clinvar (http://www.ncbi.nlm.nih.gov/clinvar/), ExAC (http://exac.broad.institute.org/), HGMD (http://www.hgmd.cf.ac.uk/) and OMIM (http://www.omim.org).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted according to the guidelines of the Declaration of Helsinki and approved by the First Affiliated Hospital of Zhengzhou University Committee, Zhengzhou, China (2020-KY-0393-002). Informed consent was obtained from patients at the time of genetic sample collection..\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all subjects involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eGenetics and Prenatal Diagnosis Center, Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China 450052\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHe M, Du L, Xie H, Zhang L, Gu Y, Lei T, Zheng J, Chen D: The Added Value of Whole-Exome Sequencing for Anomalous Fetuses With Detailed Prenatal Ultrasound and Postnatal Phenotype. \u003cem\u003eFront Genet \u003c/em\u003e2021, 12:627204.\u003c/li\u003e\n\u003cli\u003eZhu X, Gao Z, Wang Y, Huang W, Li Q, Jiao Z, Liu N, Kong X: Implementation of trio-based prenatal exome sequencing incorporating splice-site and mitochondrial genome assessment in pregnancies with fetal structural anomalies: prospective cohort study. \u003cem\u003eUltrasound Obstet Gynecol \u003c/em\u003e2022.\u003c/li\u003e\n\u003cli\u003ePersson M, Cnattingius S, Villamor E, Soderling J, Pasternak B, Stephansson O, Neovius M: Risk of major congenital malformations in relation to maternal overweight and obesity severity: cohort study of 1.2 million singletons. \u003cem\u003eBMJ \u003c/em\u003e2017, 357:j2563.\u003c/li\u003e\n\u003cli\u003eZhou Q, Wu SY, Amato K, DiAdamo A, Li P: Spectrum of Cytogenomic Abnormalities Revealed by Array Comparative Genomic Hybridization on Products of Conception Culture Failure and Normal Karyotype Samples. \u003cem\u003eJ Genet Genomics \u003c/em\u003e2016, 43(3):121-131.\u003c/li\u003e\n\u003cli\u003evan den Veyver IB, Eng CM: Genome-Wide Sequencing for Prenatal Detection of Fetal Single-Gene Disorders. \u003cem\u003eCold Spring Harb Perspect Med \u003c/em\u003e2015, 5(10).\u003c/li\u003e\n\u003cli\u003eYates CL, Monaghan KG, Copenheaver D, Retterer K, Scuffins J, Kucera CR, Friedman B, Richard G, Juusola J: Whole-exome sequencing on deceased fetuses with ultrasound anomalies: expanding our knowledge of genetic disease during fetal development. \u003cem\u003eGenet Med \u003c/em\u003e2017, 19(10):1171-1178.\u003c/li\u003e\n\u003cli\u003eRichards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, Grody WW, Hegde M, Lyon E, Spector E\u003cem\u003e et al\u003c/em\u003e: Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. \u003cem\u003eGenet Med \u003c/em\u003e2015, 17(5):405-424.\u003c/li\u003e\n\u003cli\u003eStark Z, Tan TY, Chong B, Brett GR, Yap P, Walsh M, Yeung A, Peters H, Mordaunt D, Cowie S\u003cem\u003e et al\u003c/em\u003e: A prospective evaluation of whole-exome sequencing as a first-tier molecular test in infants with suspected monogenic disorders. \u003cem\u003eGenet Med \u003c/em\u003e2016, 18(11):1090-1096.\u003c/li\u003e\n\u003cli\u003eZhao C, Chai H, Zhou Q, Wen J, Reddy UM, Kastury R, Jiang Y, Mak W, Bale AE, Zhang H\u003cem\u003e et al\u003c/em\u003e: Exome sequencing analysis on products of conception: a cohort study to evaluate clinical utility and genetic etiology for pregnancy loss. \u003cem\u003eGenet Med \u003c/em\u003e2021, 23(3):435-442.\u003c/li\u003e\n\u003cli\u003eFu M, Mu S, Wen C, Jiang S, Li L, Meng Y, Peng H: Wholeexome sequencing analysis of products of conception identifies novel mutations associated with missed abortion. \u003cem\u003eMol Med Rep \u003c/em\u003e2018, 18(2):2027-2032.\u003c/li\u003e\n\u003cli\u003eQuinlan-Jones E, Lord J, Williams D, Hamilton S, Marton T, Eberhardt RY, Rinck G, Prigmore E, Keelagher R, McMullan DJ\u003cem\u003e et al\u003c/em\u003e: Molecular autopsy by trio exome sequencing (ES) and postmortem examination in fetuses and neonates with prenatally identified structural anomalies. \u003cem\u003eGenet Med \u003c/em\u003e2019, 21(5):1065-1073.\u003c/li\u003e\n\u003cli\u003eAlamillo CL, Powis Z, Farwell K, Shahmirzadi L, Weltmer EC, Turocy J, Lowe T, Kobelka C, Chen E, Basel D\u003cem\u003e et al\u003c/em\u003e: Exome sequencing positively identified relevant alterations in more than half of cases with an indication of prenatal ultrasound anomalies. \u003cem\u003ePrenat Diagn \u003c/em\u003e2015, 35(11):1073-1078.\u003c/li\u003e\n\u003cli\u003eDrury S, Williams H, Trump N, Boustred C, Gosgene, Lench N, Scott RH, Chitty LS: Exome sequencing for prenatal diagnosis of fetuses with sonographic abnormalities. \u003cem\u003ePrenat Diagn \u003c/em\u003e2015, 35(10):1010-1017.\u003c/li\u003e\n\u003cli\u003eMei L, Huang Y, Pan Q, Su W, Quan Y, Liang D, Wu L: Targeted next-generation sequencing identifies novel compound heterozygous mutations of DYNC2H1 in a fetus with short rib-polydactyly syndrome, type III. \u003cem\u003eClin Chim Acta \u003c/em\u003e2015, 447:47-51.\u003c/li\u003e\n\u003cli\u003eDagoneau N, Goulet M, Genevieve D, Sznajer Y, Martinovic J, Smithson S, Huber C, Baujat G, Flori E, Tecco L\u003cem\u003e et al\u003c/em\u003e: DYNC2H1 mutations cause asphyxiating thoracic dystrophy and short rib-polydactyly syndrome, type III. \u003cem\u003eAm J Hum Genet \u003c/em\u003e2009, 84(5):706-711.\u003c/li\u003e\n\u003cli\u003eSchmidts M, Arts HH, Bongers EM, Yap Z, Oud MM, Antony D, Duijkers L, Emes RD, Stalker J, Yntema JB\u003cem\u003e et al\u003c/em\u003e: Exome sequencing identifies DYNC2H1 mutations as a common cause of asphyxiating thoracic dystrophy (Jeune syndrome) without major polydactyly, renal or retinal involvement. \u003cem\u003eJ Med Genet \u003c/em\u003e2013, 50(5):309-323.\u003c/li\u003e\n\u003cli\u003eRix S, Calmont A, Scambler PJ, Beales PL: An Ift80 mouse model of short rib polydactyly syndromes shows defects in hedgehog signalling without loss or malformation of cilia. \u003cem\u003eHum Mol Genet \u003c/em\u003e2011, 20(7):1306-1314.\u003c/li\u003e\n\u003cli\u003eOcbina PJ, Eggenschwiler JT, Moskowitz I, Anderson KV: Complex interactions between genes controlling trafficking in primary cilia. \u003cem\u003eNat Genet \u003c/em\u003e2011, 43(6):547-553.\u003c/li\u003e\n\u003cli\u003eGrochowski CM, Loomes KM, Spinner NB: Jagged1 (JAG1): Structure, expression, and disease associations. \u003cem\u003eGene \u003c/em\u003e2016, 576(1 Pt 3):381-384.\u003c/li\u003e\n\u003cli\u003eBray SJ: Notch signalling in context. \u003cem\u003eNat Rev Mol Cell Biol \u003c/em\u003e2016, 17(11):722-735.\u003c/li\u003e\n\u003cli\u003eTurnpenny PD, Ellard S: Alagille syndrome: pathogenesis, diagnosis and management. \u003cem\u003eEur J Hum Genet \u003c/em\u003e2012, 20(3):251-257.\u003c/li\u003e\n\u003cli\u003eMitchell E, Gilbert M, Loomes KM: Alagille Syndrome. \u003cem\u003eClin Liver Dis \u003c/em\u003e2018, 22(4):625-641.\u003c/li\u003e\n\u003cli\u003eLord J, McMullan DJ, Eberhardt RY, Rinck G, Hamilton SJ, Quinlan-Jones E, Prigmore E, Keelagher R, Best SK, Carey GK\u003cem\u003e et al\u003c/em\u003e: Prenatal exome sequencing analysis in fetal structural anomalies detected by ultrasonography (PAGE): a cohort study. \u003cem\u003eLancet \u003c/em\u003e2019, 393(10173):747-757.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eTable 1 is available in the Supplementary Files section\u003c/strong\u003e\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eModels of inheritance observed across 2\u003c/strong\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;molecular diagnoses in 61 cases\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMode of Inheritance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.056338028169016%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Diagnoses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.345070422535212%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent of Diagnoses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.598591549295776%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of novel variants\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAutosomal dominant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.056338028169016%\"\u003e\n \u003cp\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.345070422535212%\"\u003e\n \u003cp\u003e\u003cstrong\u003e46.45%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.598591549295776%\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cem\u003eDe novo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.056338028169016%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.345070422535212%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.598591549295776%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003eInherited maternal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.056338028169016%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.345070422535212%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.598591549295776%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003eInherited,paternal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.056338028169016%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.345070422535212%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.598591549295776%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAutosomal recessive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.056338028169016%\"\u003e\n \u003cp\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.345070422535212%\"\u003e\n \u003cp\u003e\u003cstrong\u003e46.45%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.598591549295776%\"\u003e\n \u003cp\u003e\u003cstrong\u003e17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003eHomozygous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.056338028169016%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.345070422535212%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.598591549295776%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003eCompound heterozygous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.056338028169016%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.345070422535212%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.598591549295776%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eX-linked\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.056338028169016%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.345070422535212%\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.1%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.598591549295776%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003eInherited maternal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.056338028169016%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.345070422535212%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.598591549295776%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\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-medical-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mgnm","sideBox":"Learn more about [BMC Medical Genomics](http://bmcmedgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mgnm/default.aspx","title":"BMC Medical Genomics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Whole-exome sequencing, deceased fetuses, products of conception, genetic diagnosis","lastPublishedDoi":"10.21203/rs.3.rs-2118883/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2118883/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Whole-exome sequencing (WES) is an effective method in the prenatal setting for identification of the underlying genetic etiology of fetal ultrasound abnormalities. To investigate the diagnostic value of WES in fetuses with ultrasound abnormalities that resulted in fetal demise or pregnancy termination.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e 61 deceased fetuses with ultrasound abnormalities and normal copy number variation Sequencing (CNV-seq) were retrospectively collected. Proband-only or trio-WES were performed on the products of conception.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResult: \u003c/strong\u003eCollectively, 28 cases were positive with 39 variants (10 pathogenic, 22 likely pathogenic and 7 variants of uncertain significance) of 18 genes, and the overall diagnostic rate was 45.9% (28/61), of which 39.2% (11/28) were \u003cem\u003ede novo\u003c/em\u003e variants. In addition, 21 variants in 11 genes among the positive cases had not been previously reported. The diagnostic yield for definitive findings for trio analysis was 55.9% (19/34) compared to 33.3% (9/27) for singletons. The most common ultrasound abnormalities were skeletal system abnormalities 39.2% (11/28), followed by multiple system abnormalities (17.9%, 5/28) and genitourinary abnormalities (17.9%, 5/28).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eOur results support the use of WES to identify genetic etiologies of ultrasound abnormalities and improve understanding of pathogenic variants. The identification of disease-related variants provided information for subsequent genetic counseling of recurrence risk and management of subsequent pregnancies.\u003c/p\u003e","manuscriptTitle":"Whole-exome Sequencing in deceased fetuses with ultrasound anomalies: A Retrospective Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-10-11 17:45:06","doi":"10.21203/rs.3.rs-2118883/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-11-15T17:42:11+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-11-11T16:00:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"36321e26-f4cd-41e9-a71a-68c28d9c994b","date":"2022-11-03T12:15:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-11-01T16:19:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"a525d6a9-04ce-4449-84ac-de00d41cdc9a","date":"2022-10-26T14:33:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-10-06T09:06:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-10-06T08:31:03+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2022-10-06T07:50:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-10-06T07:41:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Genomics","date":"2022-09-30T05:46:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mgnm","sideBox":"Learn more about [BMC Medical Genomics](http://bmcmedgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mgnm/default.aspx","title":"BMC Medical Genomics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6550ddf1-2a11-4ca7-ba7d-a618117c493d","owner":[],"postedDate":"October 11th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T18:59:39+00:00","versionOfRecord":{"articleIdentity":"rs-2118883","link":"https://doi.org/10.1186/s12920-022-01427-1","journal":{"identity":"bmc-medical-genomics","isVorOnly":false,"title":"BMC Medical Genomics"},"publishedOn":"2023-02-16 18:57:20","publishedOnDateReadable":"February 16th, 2023"},"versionCreatedAt":"2022-10-11 17:45:06","video":"","vorDoi":"10.1186/s12920-022-01427-1","vorDoiUrl":"https://doi.org/10.1186/s12920-022-01427-1","workflowStages":[]},"version":"v1","identity":"rs-2118883","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2118883","identity":"rs-2118883","version":["v1"]},"buildId":"omnImTCwR2MFx8CMYfrG7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}