The relationship between fetal tissue chromosomal karyotype and clinical characteristics in patients with spontaneous abortion: a retrospective study

The relationship between fetal tissue chromosomal karyotype and clinical characteristics in patients with spontaneous abortion: a retrospective study | 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 Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The relationship between fetal tissue chromosomal karyotype and clinical characteristics in patients with spontaneous abortion: a retrospective study Lin Liu, Yanting Yang, Huyan Huo, Ning Hu, Fang Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4190327/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Background Abnormal fetal tissue chromosome karyotypes are one of the important pathogenic factors for spontaneous abortion (SA). To analyze the characteristics of fetal tissue chromosomal karyotype in 778 women with a history of SA and its relationship with clinical features. Methods A retrospective study collected maternal age, body mass index (BMI), gestational weeks at miscarriage, the number of previous pregnancy losses and fetal tissue karyotypes CNV-seq data of 778 SA couples from Lanzhou University Second Hospital from October 2019 to December 2023, and described the characteristics of fetal tissue chromosomal karyotype and its relationship with clinical features. Results In our study, 432 patients (55.53% of total) had abnormal fetal tissue chromosomal karyotypes, with the highest incidence being trisomy syndrome (46.99%,203/432). Advanced maternal age(>35 years), early pregnancy(<12 weeks), and a history of less than four previous pregnancy losses were all identified as risk factors for fetal tissue chromosomal abnormalities. Conclusion The results of this study indicate that fetal tissue chromosomal abnormalities are the primary factor leading to SA. Additionally, advanced maternal age(>35years), early pregnancy(<12 weeks=, and the fewer number of previous pregnancy losses(≤ 4 times) are associated with a higher risk of fetal tissue chromosomal abnormalities following miscarriage. Fetal chromosome karyotypes Spontaneous abortion advanced maternal age CNV-seq Figures Figure 1 Figure 2 Introduction Spontaneous abortion（SA）is one of the most common complications during pregnancy. According to the gestational age at the time of abortion, it can be divided into early SA, which is defined as pregnancy failure before 12 weeks of pregnancy, and middle-late SA [1, 2] . Most previous studies have shown that the incidence of SA in women of childbearing age is approximately 15%，and 3%-5% of these couples experience recurrent pregnancy loss（RPL） [3, 4] . Currently, it is known that chromosomal abnormalities, anatomical abnormalities, immune abnormalities, and endocrine abnormalities are common causes of SA [1] . Among them, fetal chromosomal abnormalities are the most common cause of early SA, accounting for 50% of cases or more [5, 6] . Compared with traditional analytical methods, copy number variation sequencing (CNV-seq) has the advantages of high resolution, high accuracy and sensitivity, not being limited by specific genomic regions, as well as a faster experimental cycle [7, 8] . It is increasingly being used in the analysis of miscarriage material [9, 10] , and its combination with quantitative fluorescence polymerase chain reaction（QF-PCR）can identify chromosomal aneuploidy, polyploidy, and copy number variants(CNVs) [11] . In this study, we analyzed the characteristics of chromosomal abnormalities in miscarriage tissue and their relationship with clinical features, aiming to contribute to the treatment and prevention of miscarriages in clinical practice. Materials and methods Patients From October 2019 to December 2023, 778 patients with SA were treated at Lanzhou University Second Hospital were enrolled as research subjects. And all these patients performed uterine cavity cleaning operations, meanwhile, obtained abortion tissue for CNV-seq and provided examination report data for scientific research voluntarily. This study was approved by the Ethics Committee of Lanzhou University Second Hospital(2023A-739) and complied with the Declaration of Helsinki. In line with our previous research, this study will also focus on triploid, trisomy, mosaicism, 45, X, microduplication, microdeletion, and monosomy as the main research indicators [ 12 ] . Furthermore, maternal age, body mass index (BMI), gestational weeks at miscarriage, and the number of previous pregnancy losses were also included as study indicators. Detection of chromosomal abnormalities This test utilized the BioelectronSeq4000 high-throughput genetic sequencer for CNV-seq. The sequencing reads were aligned to the UCSC hg19 reference genome, and ultimately, bioinformatics was employed to determine whether the sample exhibited chromosomal abnormalities. Database of PubMed ( https://www.ncbi.nlm.nih.gov/pubmed/),UCS C Genome Browser ( http://genome.ucsc.edu/),Onlin e Mendelian Inheritance in Man (OMIM) ( https://omim.org ) ere explored for CNVs mapping and identification. Statistical analysis The SPSS software (IBM, Version 27.0) was used to analyze the data. All data were summarized by mean ± SD and proportions, and the data were compared across whole groups using student-T test, chi-squared and Fisher exact test. A difference was deemed statistically significant if the P -value was < 0.05. Results Patient characteristics From October 2019 to December 2023, a total of 778 women with a history of SA who were treated at the Second Hospital of Lanzhou University were included in the study. Chromosome analysis was performed on all miscarriage specimens from these women, and all chromosomes were detected. Demographic and fetal tissue chromosome karyotype conditions were presented in Table 1 and Table 2 . Of these, a larger proportion (55.53%, 432/778) was patients with abnormal foetal tissue chromosomal karyotypes. The mean age and body mass index (BMI) of all patients were 30.98 ± 3.97 years and 22.52 ± 2.81 kg/m 2 , respectively. 730 cases of patients experienced SA before 12 weeks of pregnancy. The number of previous pregnancy losses was as follows: once in 147 cases, twice in 320 cases, three times in 221 cases, and ≥ 4 times in 108 cases. Table 1 Number of people in all fetal tissue chromosome karyotypes. Characteristics Number Percentage (%) ALL 778 100.00 Normal 346 44.47 Trisomy 203 26.09 Others 63 8.10 45, X 51 6.56 Microduplication 38 4.88 Triploid 34 4.37 Microdeletion 26 3.34 Mosaicism 15 1.93 Monosomy 2 0.26 Table 2 The correlations between clinical characteristics and chromosomal variants. Characteristics All Patients(n = 778) Normal (n = 346) Abnormal (n = 432) Test value P value Age(years) 30.98 ± 3.97 30.64 ± 3.72 31.26 ± 4.14 2.183 0.029 ≤ 35 662(85.09) 307(46.37) 355(53.63) 6.502 0.011 >35 116(14.91) 39(33.62) 77(66.38) BMI(kg/m 2 ) 22.52 ± 2.81 22.64 ± 2.76 22.42 ± 2.85 1.110 0.267 <18.5 38(4.88) 14(36.84) 24(63.16) 1.448 0.485 ≥ 18.5, <24.0 540(69.41) 238(44.07) 302(55.93) ≥ 24.0 200(25.71) 94(47.00) 106(53.00) Gestational age(weeks) <12 730(93.83) 317(43.42) 413(56.58) 5.266 0.022 ≥ 12 48(6.17) 29(60.42) 19(39.58) The number of previous miscarriages(times) 1 147(18.89) 63(42.86) 84(57.14) 9.482 0.024 2 302(38.82) 126(41.72) 176(58.28) 3 221(28.41) 95(42.99) 126(57.01) ≥ 4 108(13.88) 62(57.41) 46(42.59) The association between clinical characteristics and chromosomal abnormalities The relationship between chromosomal abnormalities and different clinical features is presented in Table 1 .Among them, patients with abnormal fetal tissue chromosomal karyotypes had a significantly higher average age than those with normal karyotypes(31.26 ± 4.14 vs. 30.64 ± 3.72, P = 0.029), but there was no significant difference in BMI between the two groups(22.42 ± 2.85 vs. 22.64 ± 2.76, P = 0.267). Moreover, the rate of chromosomal abnormalities was significantly higher in patients with maternal age >35 years than those patients in ≤ 35years(66.38% vs. 53.63%, P = 0.011). Additionally, the rate of fetal chromosomal abnormalities in pregnant women with gestational age < 12 weeks is significantly higher than those with gestational age ≥ 12 weeks (56.58% vs.39.68%, P = 0.022). When comparing the number of previous pregnancy losses, we found that among patients with recurrent pregnancy loss (RPL) who have had ≥ 4 miscarriages (42.59%), as the number of prior miscarriages decreases, the proportion of fetal chromosomal abnormalities increases (once:57.14%; twice:58.28%;3 times:57.01%; P = 0.024). Table 3 showed the results from multiple logistic analyses. Compared with the corresponding comparison groups, the risk of chromosomal abnormalities was increased in women with advanced age(＞35 years,OR,1.841;95%CI,1.205-2.812),an earlier gestational age(＜12weeks,OR,2.041;95%CI,1.116-3.732)，less number of previous pregnancy loss(once: OR,2.007;95%CI,1.202-3.351;twice:OR,2.039;95%CI,1.296-3.206;3times:OR,1.957;95%CI,1.219-3.143). The risk of SA patients with normal and abnormal fetal tissue chromosome karyotypes by different clinical characteristics was shown in Table4.The relative risk rate (RR) of ≥ 35 years patients was a significant 1.4-fold higher than < 35 years (RR, 1.4, 95%CI, 1.1–1.8).Meanwhile, the RR of gestational age ＜12 weeks patients was a significant 1.4-fold higher than those ≥12 weeks(RR,1.4,95%CI,1.1-1.8). Based on the reference group's criteria, individuals who have experienced 1(RR,1.3,95%CI,1.0-1.7), 2(RR,1.4,95%CI,1.1-1.7), and 3(RR,1.3,95%CI,1.1-1.7) pregnancy losses all show significantly higher RR compared to the reference group(≥4 previous pregnancy losses). Table 3 Multiple logistic regression analyses of clinical risk characteristics for chromosomal variants. Characteristics Abnormal n Rate(%) 95%CI RR 95%CI Age(years) ≤ 35 355 662 53.6 (48.8–57.4) Ref >35 77 116 66.4 (57.7–75.1) 1.4 (1.1–1.8) BMI(kg/m 2 ) <18.5 24 38 63.2 (47.1–79.2) 1.2 (0.8–1.8) ≥ 18.5, <24.0 302 540 55.9 (51.7–60.1) Ref ≥ 24.0 106 200 53.0 (46.0–60.0) 1.0 (0.8–1.1) Gestational age(weeks) <12 413 730 56.6 (53.0-60.2) 1.4 (1.1–1.8) ≥ 12 19 48 39.6 (25.2–53.9) Ref The number of previous miscarriages(times) 1 84 147 57.1 (49.0-65.2) 1.3 (1.0-1.7) 2 176 302 58.3 (52.7–63.9) 1.4 (1.1–1.7) 3 126 221 57.0 (50.4–63.6) 1.3 (1.1–1.7) ≥ 4 46 108 42.6 (33.1–52.1) Ref Table 4 The risk of SA patients with normal and abnormal fetal tissue chromosome karyotypes by different clinical characteristics. Characteristics Abnormal n Rate(%) 95%CI RR 95%CI Age(years) ≤ 35 355 662 53.6 (48.8–57.4) Ref >35 77 116 66.4 (57.7–75.1) 1.4 (1.1–1.8) BMI(kg/m 2 ) <18.5 24 38 63.2 (47.1–79.2) 1.2 (0.8–1.8) ≥ 18.5, <24.0 302 540 55.9 (51.7–60.1) Ref ≥ 24.0 106 200 53.0 (46.0–60.0) 1.0 (0.8–1.1) Gestational age(weeks) <12 413 730 56.6 (53.0-60.2) 1.4 (1.1–1.8) ≥ 12 19 48 39.6 (25.2–53.9) Ref The number of previous miscarriages(times) 1 84 147 57.1 (49.0-65.2) 1.3 (1.0-1.7) 2 176 302 58.3 (52.7–63.9) 1.4 (1.1–1.7) 3 126 221 57.0 (50.4–63.6) 1.3 (1.1–1.7) ≥ 4 46 108 42.6 (33.1–52.1) Ref Fetal tissue chromosomal characteristics and the distribution of abnormal chromosome karyotypes in 23 pairs of chromosomes Figure 1 and Table 1 provide a detailed description of the types and distribution percentages of all embryo chromosomes. Among all fetal tissue chromosomes, the proportion of abnormal chromosomes is slightly higher than that of normal chromosomes (55.53%,432/778 vs. 44.47%,346/778). Categories of abnormal fetal tissue chromosome karyotypes were trisomy (26.09%,203/778),45,X(6.56%,51/778),microduplication(4.88%,38/778),triploid(4.37%,34/778),microdeletion(3.34%,26/778),mosaicism(1.93%,15/778),monosomy(0.26%,2/778)and others[8.10%,63/778,among them, multiple-chr(number of abnormal chromosomes ≥ 2, 7.46%,58/778), uniparental disomy(UPD,0.26%,2/778)and tetraploid(0.26%,2/778)]. Figure 1 The number of patients with all fetal tissue chromosome karyotypes. The distribution of the 23 pairs of chromosomes was in Fig.2. The distribution of abnormal fetal tissue chromosome karyotypes was concentrated on the sex chromosomes (20.30%,68/335), chromosome 16(19.40%,65/335), and chromosome 22(10.15%,34/335), and fewest on chromosome 12(0.60%,2/335). Trisomy is the most common type of abnormality among chromosomes, and it is predominantly found in chromosome 16(25.25%,51/202), followed by chromosomes 22(14.36%,29/202), 21(8.91%,18/202), 13(8.42%,17/202), and 2(6.93%,14/202), and showed no signs on chromosome 12(0%,0/202). The distribution of mosaicism was also enrichment on chromosome 16(26.67%,4/15), and showed no signs on chromosomes 1,6,7,8,10,13,14,15,17,18,20,21and X/Y (all 0%,0/15). The distribution of microduplication was enrichment on chromosome 16(17.95%,7/39), followed by chromosome 10(12.82%,5/39), but chromosomes 3,4,7,9,14 and 18 did not show this kind of abnormality (all 0%,0/39). The distribution of microdeletion was enrichment on chromosome X/Y(16.67%，4/24)，and fewest on chromosomes 2,3,6,7,8,10,12,13,20 and 21(all 0%,0/24). Discussion Chromosomal abnormalities in the embryo have long been considered the most common cause of early SA, with most early studies indicating that it can lead to approximately half of all SAs [ 13 , 14 ] . Our study analyzed a total of 778 cases of miscarried products of conception (POCs), with a detection rate of abnormal chromosomes at 55.53%, which is like most previous studies [ 15 , 16 ] . The previous research indicated that most SA occur in the first 12 weeks of gestation, and the main cause of early pregnancy miscarriage was primarily due to chromosomal numerical abnormality [ 17 – 19 ] . Aneuploidy, a type of chromosomal numerical abnormality, is the most common embryonic chromosomal abnormality leading to SA, with trisomy being the most common [ 20 , 21 ] . Our research indicated that chromosome 16 was the most common numerical abnormality, followed by chromosome 22. Additionally, the incidence rate of 45, X was highest among monoploids, which was consistent with previous studies [ 12 , 16 , 21 – 23 ] . It was generally believed that advanced maternal age was a well-recognized risk factor for increased chromosomal abnormalities and the risk of SA [ 24 ] . Furthermore, studies had indicated that the incidence of fetal chromosomal aneuploidy was higher in women over 35 years of age [ 5 , 21 , 25 ] . Most researchers believed that it was mainly due to the occurrence of premature separation of sister chromatids, non-disjunction in meiosis II, and reverse segregation during the development of oocytes in older women, which can significantly increase the incidence of trisomy in fetal tissue chromosome [ 26 , 27 ] . In our study, the rate of fetal tissue chromosomal abnormalities in older women was significantly higher than that in younger women. However, due to the large difference in sample sizes between the two groups, no significant difference in the incidence of fetal tissue trisomy syndrome was found between the two groups. However, it is important to note that not all cases of trisomy syndrome will result in SA. Some trisomy anomalies may lead to children being born with a range of genetic disorders and developmental challenges, rather than miscarriage during pregnancy [ 12 ] . Therefore, we still need to expand the sample size and conduct further research to improve the accuracy and representativeness of our results. In addition to maternal age, this study also analyzed the relationship between gestational weeks, maternal BMI, and the number of previous miscarriages with fetal tissue chromosomal karyotypes. The study by Zhu et al. indicated that early pregnancy(≤ 12weeks) and fewer previous pregnancy losses were significant risk factors for fetal tissue chromosomal numerical abnormalities [ 17 ] . Similarly, Gu et al. pointed out that early pregnancy(≤ 11weeks) was a risk factor for fetal tissue aneuploidy and demonstrated that a history of recurrent miscarriages was a significant risk factor for sex chromosome abnormalities [ 21 ] . The study by Nobuaki Ozawa et al. found that the rate of chromosomal abnormalities from women with a history of fewer than 2 pregnancy losses was significantly higher than those with 2 or more losses, and the types of chromosomal abnormalities in early pregnancy varied with gestational weeks [ 5 ] . However, in this study, using a history of ≥ 4 previous pregnancy losses as a reference, it was found that the rate of chromosomal abnormalities was higher in patients with a history of < 4 previous pregnancy losses, and as the number of losses decreased, the abnormality rate gradually increased. Additionally, the rate of abnormal chromosomes in early miscarriage(<12weeks) patients was significantly higher than in mid-to-late pregnancy. However, the sample size was small in this study, which may introduce some bias, therefore requiring an expansion of the sample size for further research. BMI is a measure of body fat based on a person's weight and height. It is used to assess whether a person is underweight, normal weight, overweight, or obese, and is commonly used as one of the indicators of health risks. This study analyzed the relationship between different BMIs and the rate of chromosomal abnormalities in fetal tissue but did not find a significant association between the two. However, a previous study indicated a potential link between higher BMI and chromosomal abnormalities leading to recurrent miscarriages, while there was no significant association between BMI and patients with normal karyotypes and no history of miscarriage [ 23 ] . This study also has certain limitations. Firstly, it is a single-center study with a relatively small sample size, and therefore, it cannot exclude the influence of factors such as geographical location, ethnicity, and lifestyle habits on miscarriage outcomes and fetal tissue chromosomal abnormalities. Secondly, although previous studies have indicated that fetal sex, crown-rump length, and mode of conception are important factors affecting the normalcy of embryo tissue chromosomal karyotypes [ 16 , 17 , 21 , 28 ] , this study did not take into account the condition of the gestational sac at the time of miscarriage (size, appearance, presence of fluid/hemorrhage around the sac), fetal conditions (crown-rump length and sex), and mode of conception (natural conception, ovulation induction, and assisted reproductive technology), which could potentially affect the study results. Thirdly, as the fertilized egg is a product of the combination of sperm and egg, abnormalities in fetal tissue chromosomal composition may result from factors related to either the male or female partner [ 29 – 31 ] . However, this study did not incorporate these male-related factors into the analysis, such as male age, semen quality, and DNA fragmentation index (DFi), therefore, the potential impact of male factors on the experimental results cannot be ruled out. Finally, this study utilized CNV-Seq to detect fetal tissue chromosomal abnormalities. Due to inherent limitations of the detection technique [ 32 , 33 ] , such as maternal cell contamination, inability to detect polyploidy, or identification errors, the fetal tissue chromosomal results obtained in this study may have some minor inaccuracies. Therefore, in summary, we still need to conduct large-scale, multi-center studies, ideally incorporating as many relevant factors as possible, and employ a combination of various detection methods may lead to more accurate, universal, and representative conclusions. Conclusion In conclusion, fetal tissue chromosomal abnormalities, especially numerical abnormalities, are the primary factors leading to SA. Maternal age, gestational age at the time of miscarriage, and the number of previous pregnancy losses are all important risk factors for fetal tissue chromosomal abnormalities. Further detailed research is needed to elucidate the specific mechanisms and explore additional risk factors, aiming to provide assistance and reference value for clinical treatment and improvement of prognosis for women with a history of SA. Declarations Ethics approval and consent of participat e The informed consent was signed by all patients in Lanzhou University Second Hospital. The study used non-identifiable patient data and was approved by the ethics review committee of the Lanzhou University Second Hospital(2023A-739). The research complies with the Declaration of Helsinki. Consent of publication All authors have agreed to publish this article. Availability of data and materials The data that support the findings of this study are available on request from the corresponding author. Researchers who are interested in working together on our study are more than welcome to collaborate. Contact the paper’s corresponding author, Fang Wang, [ [email protected] ]. Competing interests The authors declare no competing interests. Funding This work was funded by the Science Foundation of Lanzhou University (Grant No. 071100132 and 071100186), the Medical Innovation and Development Project of Lanzhou University (Grant No. lzuyxcx-2022-137), and the Science Foundation of Lanzhou University Second Hospital (Grant No. YJS-BD-19). Authors’ contributions The study conception and design were performed by L.L and F.W. Material preparation, data collection, and analysis were performed by L.L,YT.Y,N.H and HY.H. F.W provided raw data. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. References BENDER ATIK R, CHRISTIANSEN O B, ELSON J, et al. ESHRE guideline: recurrent pregnancy loss [J]. Hum Reprod Open, 2018, 2018(2): hoy004. Evaluation and treatment of recurrent pregnancy loss: a committee opinion [J]. Fertil Steril, 2012, 98(5): 1103-11. GONG C, YANG W, LIU X, et al. Low follistatin level is a causal risk factor for spontaneous abortion: a two-sample mendelian randomization study [J]. Front Endocrinol (Lausanne), 2023, 14: 1255591. QUENBY S, GALLOS I D, DHILLON-SMITH R K, et al. Miscarriage matters: the epidemiological, physical, psychological, and economic costs of early pregnancy loss [J]. Lancet, 2021, 397(10285): 1658-67. OZAWA N, OGAWA K, SASAKI A, et al. Maternal age, history of miscarriage, and embryonic/fetal size are associated with cytogenetic results of spontaneous early miscarriages [J]. J Assist Reprod Genet, 2019, 36(4): 749-57. D'IPPOLITO S, LONGO G, ORTESCHI D, et al. Investigating the "Fetal Side" in Recurrent Pregnancy Loss: Reliability of Cell-Free DNA Testing in Detecting Chromosomal Abnormalities of Miscarriage Tissue [J]. J Clin Med, 2023, 12(12). DOLANC MERC M, PETERLIN B, LOVRECIC L. The genetic approach to stillbirth: A »systematic review« [J]. Prenat Diagn, 2023, 43(9): 1220-8. MCQUEEN D B, LATHI R B. Miscarriage chromosome testing: Indications, benefits and methodologies [J]. Semin Perinatol, 2019, 43(2): 101-4. PAUTA M, GRANDE M, RODRIGUEZ-REVENGA L, et al. Added value of chromosomal microarray analysis over karyotyping in early pregnancy loss: systematic review and meta-analysis [J]. Ultrasound Obstet Gynecol, 2018, 51(4): 453-62. SHAO Y, YANG S, CHENG L, et al. Identification of chromosomal abnormalities in miscarriages by CNV-Seq [J]. Mol Cytogenet, 2024, 17(1): 4. LI F-X, XIE M-J, QU S-F, et al. Detection of chromosomal abnormalities in spontaneous miscarriage by low‑coverage next‑generation sequencing [J]. Mol Med Rep, 2020, 22(2): 1269-76. ZHANG J, MU F, GUO Z, et al. Chromosome analysis of foetal tissue from 1903 spontaneous abortion patients in 5 regions of China: a retrospective multicentre study [J]. BMC Pregnancy Childbirth, 2023, 23(1): 818. ROSENFELD J A, TUCKER M E, ESCOBAR L F, et al. Diagnostic utility of microarray testing in pregnancy loss [J]. Ultrasound Obstet Gynecol, 2015, 46(4): 478-86. CHEN Q, ZHANG H, LI X, et al. Sequential application of copy number variation sequencing and quantitative fluorescence polymerase chain reaction in genetic analysis of miscarriage and stillbirth [J]. Mol Genet Genomic Med, 2023, 11(8): e2187. DU Y, CHEN L, LIN J, et al. Chromosomal karyotype in chorionic villi of recurrent spontaneous abortion patients [J]. Biosci Trends, 2018, 12(1): 32-9. GUI J, DING J, YIN T, et al. Chromosomal analysis of 262 miscarried conceptuses: a retrospective study [J]. BMC Pregnancy Childbirth, 2022, 22(1): 906. ZHU D, WEI X, ZHOU X-Y, et al. Chromosomal abnormalities in recurrent pregnancy loss and its association with clinical characteristics [J]. J Assist Reprod Genet, 2023, 40(7): 1713-20. DAI Y-F, WU X-Q, HUANG H-L, et al. Experience of copy number variation sequencing applied in spontaneous abortion [J]. BMC Med Genomics, 2024, 17(1): 15. KORKIDAKIS A, ALBERT A Y, JIANG I, et al. The Clinical Significance of Embryonic Chromosomal Errors in Recurrent Pregnancy Loss: an Analysis of 1107 Miscarriages [J]. Reprod Sci, 2023, 30(10): 3019-26. ZHANG L, YANG Y, WANG W, et al. Predicting risk of blastocyst aneuploidy among women with previous aneuploid pregnancy loss: a multicenter-data-based multivariable model [J]. Hum Reprod, 2023, 38(12): 2382-90. GU C, LI K, LI R, et al. Chromosomal Aneuploidy Associated With Clinical Characteristics of Pregnancy Loss [J]. Front Genet, 2021, 12: 667697. ZENG W, QI H, DU Y, et al. Analysis of potential copy-number variations and genes associated with first-trimester missed abortion [J]. Heliyon, 2023, 9(8): e18868. BAI W, ZHANG Q, LIN Z, et al. Analysis of copy number variations and possible candidate genes in spontaneous abortion by copy number variation sequencing [J]. Front Endocrinol (Lausanne), 2023, 14: 1218793. MELO P, DHILLON-SMITH R, ISLAM M A, et al. Genetic causes of sporadic and recurrent miscarriage [J]. Fertil Steril, 2023, 120(5): 940-4. ELMERDAHL FREDERIKSEN L, ØLGAARD S M, ROOS L, et al. Maternal age and the risk of fetal aneuploidy: A nationwide cohort study of more than 500 000 singleton pregnancies in Denmark from 2008 to 2017 [J]. Acta Obstet Gynecol Scand, 2024, 103(2): 351-9. VERDYCK P, ALTARESCU G, SANTOS-RIBEIRO S, et al. Aneuploidy in oocytes from women of advanced maternal age: analysis of the causal meiotic errors and impact on embryo development [J]. Hum Reprod, 2023, 38(12): 2526-35. CIMADOMO D, FABOZZI G, VAIARELLI A, et al. Impact of Maternal Age on Oocyte and Embryo Competence [J]. Front Endocrinol (Lausanne), 2018, 9: 327. BALAGUER N, RODRIGO L, MATEU-BRULL E, et al. Non-invasive cell-free DNA-based approach for the diagnosis of clinical miscarriage: A retrospective study [J]. BJOG, 2024, 131(2): 213-21. AL-OUQAILI M T S, MURSHID R M, ABD AL-KARIEM B Y, et al. Molecular cytogenetic analysis of multi-miscarriage products of conception in clinical cases from Al-Anbar Governorate, west of Iraq [J]. Saudi J Biol Sci, 2024, 31(3): 103932. SCHLIEP K C, FELDKAMP M L, HANSON H A, et al. Are paternal or grandmaternal age associated with higher probability of trisomy 21 in offspring? A population-based, matched case-control study, 1995-2015 [J]. Paediatr Perinat Epidemiol, 2021, 35(3): 281-91. WANG Z, LIU X, XU J, et al. Paternal age, body mass index, and semen volume are associated with chromosomal aberrations-related miscarriages in couples that underwent treatment by assisted reproductive technology [J]. Aging (Albany NY), 2020, 12(9): 8459-72. LUO H, WANG Q, FU D, et al. Additional diagnostic value of CNV-seq over conventional karyotyping in prenatal diagnosis: A systematic review and meta-analysis [J]. J Obstet Gynaecol Res, 2023, 49(7): 1641-50. ZHANG J, TANG X, HU J, et al. Investigation on combined copy number variation sequencing and cytogenetic karyotyping for prenatal diagnosis [J]. BMC Pregnancy Childbirth, 2021, 21(1): 496. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Submission checks completed at journal 30 Mar, 2024 Editor assigned by journal 30 Mar, 2024 First submitted to journal 29 Mar, 2024 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board 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-4190327","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":285688289,"identity":"d737e21c-8291-46e7-8bef-0b20c672c178","order_by":0,"name":"Lin Liu","email":"","orcid":"","institution":"Lanzhou University","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Liu","suffix":""},{"id":285688292,"identity":"18f9152b-7d00-45ad-81e4-be688dbc2317","order_by":1,"name":"Yanting Yang","email":"","orcid":"","institution":"Lanzhou University","correspondingAuthor":false,"prefix":"","firstName":"Yanting","middleName":"","lastName":"Yang","suffix":""},{"id":285688295,"identity":"aa10d4f8-82eb-44df-9ad2-d3557e1ecb19","order_by":2,"name":"Huyan Huo","email":"","orcid":"","institution":"Lanzhou University","correspondingAuthor":false,"prefix":"","firstName":"Huyan","middleName":"","lastName":"Huo","suffix":""},{"id":285688297,"identity":"1c55e9c0-8d44-4d6d-baff-efcaa6fb5bcb","order_by":3,"name":"Ning Hu","email":"","orcid":"","institution":"Lanzhou University","correspondingAuthor":false,"prefix":"","firstName":"Ning","middleName":"","lastName":"Hu","suffix":""},{"id":285688298,"identity":"5629a7ac-28f6-448d-80dd-514f0fb9d554","order_by":4,"name":"Fang Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYLCCChDB3twAohgbiNJyBkTwHCRZi0QikVr4pc8YMBxss8uTj3zY/JmHwUZ2wwHmZw/waZHsywFpSS42vJ3YYMzDkGa84QCbuQE+LQZneAyYP25jTtw4O7EhmYfhcOKGAzxsEvi02AO1MBzcVp+4cebBhsM8DP8JazHgAWs5nDhfgrGxmYfhAGEtEmfYChgO/jueuIEnsZlxjkGy8czDbGZ4tfD3MG9gOHCmOnF+++HDH95U2Mn2HW9+hlcLAwOH+Q+wCw+ASSBmxq8eCNgfgCn5BoIqR8EoGAWjYKQCAEL5S08MhUsPAAAAAElFTkSuQmCC","orcid":"","institution":"Lanzhou University Second Hospital","correspondingAuthor":true,"prefix":"","firstName":"Fang","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-03-30 02:59:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4190327/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4190327/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54037953,"identity":"435ff336-6185-4511-9624-2f7e321442e3","added_by":"auto","created_at":"2024-04-03 17:13:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":15618,"visible":true,"origin":"","legend":"\u003cp\u003eThe number of patients with all fetal tissue chromosome karyotypes.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4190327/v1/12ae713ef92ac8e7d785a48f.png"},{"id":54037952,"identity":"a0d5d06e-4ac0-4cc2-ab20-0635d9fdc4b0","added_by":"auto","created_at":"2024-04-03 17:13:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":62922,"visible":true,"origin":"","legend":"\u003cp\u003eThe stacked histogram of the distribution of the 23 pairs of chromosomes in abnormal fetal tissue chromosome karyotypes and their distribution by type.\u003cstrong\u003e A \u003c/strong\u003eThe number of distribution for the 23 pairs chromosomes in abnormal fetal tissue chromosome karyotypes.\u003cstrong\u003e B\u003c/strong\u003e The distribution\u003c/p\u003e\n\u003cp\u003efor the 23 pairs chromosomes in trisomy, mosaicism, microduplication and microdeletion.\u003cstrong\u003eC \u003c/strong\u003eThe percentage of distribution for the 23 pairs chromosomes in trisomy, mosaicism, microduplication and microdeletion.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4190327/v1/bbdf98aa21f45988c18e8d27.png"},{"id":54039498,"identity":"144c8e1f-cc4c-4086-b226-41d1eb88dcf2","added_by":"auto","created_at":"2024-04-03 17:22:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":502447,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4190327/v1/fcc68b18-465a-444a-afe2-4f0dbca6af8b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The relationship between fetal tissue chromosomal karyotype and clinical characteristics in patients with spontaneous abortion: a retrospective study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSpontaneous abortion（SA）is one of the most common complications during pregnancy. According to the gestational age at the time of abortion, it can be divided into early SA, which is defined as pregnancy failure before 12 weeks of pregnancy, and middle-late SA\u003csup\u003e[1, 2]\u003c/sup\u003e. Most previous studies have shown that the incidence of SA in women of childbearing age is approximately 15%，and 3%-5% of these couples experience recurrent pregnancy loss（RPL）\u003csup\u003e[3, 4]\u003c/sup\u003e. Currently, it is known that chromosomal abnormalities, anatomical abnormalities, immune abnormalities, and endocrine abnormalities are common causes of SA\u003csup\u003e[1]\u003c/sup\u003e. Among them, fetal chromosomal abnormalities are the most common cause of early SA, accounting for 50% of cases or more \u003csup\u003e[5, 6]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eCompared with traditional analytical methods, copy number variation sequencing (CNV-seq) has the advantages of high resolution, high accuracy and sensitivity, not being limited by specific genomic regions, as well as a faster experimental cycle\u003csup\u003e[7, 8]\u003c/sup\u003e. It is increasingly being used in the analysis of miscarriage material\u003csup\u003e[9, 10]\u003c/sup\u003e, and its combination with quantitative fluorescence polymerase chain reaction（QF-PCR）can identify chromosomal aneuploidy, polyploidy, and copy number variants(CNVs)\u003csup\u003e[11]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn this study, we analyzed the characteristics of chromosomal abnormalities in miscarriage tissue and their relationship with clinical features, aiming to contribute to the treatment and prevention of miscarriages in clinical practice.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eFrom October 2019 to December 2023, 778 patients with SA were treated at Lanzhou University Second Hospital were enrolled as research subjects. And all these patients performed uterine cavity cleaning operations, meanwhile, obtained abortion tissue for CNV-seq and provided examination report data for scientific research voluntarily. This study was approved by the Ethics Committee of Lanzhou University Second Hospital(2023A-739) and complied with the Declaration of Helsinki.\u003c/p\u003e \u003cp\u003eIn line with our previous research, this study will also focus on triploid, trisomy, mosaicism, 45, X, microduplication, microdeletion, and monosomy as the main research indicators\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Furthermore, maternal age, body mass index (BMI), gestational weeks at miscarriage, and the number of previous pregnancy losses were also included as study indicators.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDetection of chromosomal abnormalities\u003c/h2\u003e \u003cp\u003eThis test utilized the BioelectronSeq4000 high-throughput genetic sequencer for CNV-seq.\u0026nbsp;The sequencing reads were aligned to the UCSC hg19 reference genome, and ultimately, bioinformatics was employed to determine whether the sample exhibited chromosomal abnormalities. Database of PubMed (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/pubmed/),UCS\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/pubmed/),UCS\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003eC Genome Browser (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://genome.ucsc.edu/),Onlin\u003c/span\u003e\u003cspan address=\"http://genome.ucsc.edu/),Onlin\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003ee Mendelian Inheritance in Man (OMIM) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://omim.org\u003c/span\u003e\u003cspan address=\"https://omim.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) ere explored for CNVs mapping and identification.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe SPSS software (IBM, Version 27.0) was used to analyze the data. All data were summarized by mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD and proportions, and the data were compared across whole groups using student-T test, chi-squared and Fisher exact test. A difference was deemed statistically significant if the \u003cem\u003eP\u003c/em\u003e-value was \u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec6\"\u003e\n \u003ch2\u003ePatient characteristics\u003c/h2\u003e\n \u003cp\u003eFrom October 2019 to December 2023, a total of 778 women with a history of SA who were treated at the Second Hospital of Lanzhou University were included in the study. Chromosome analysis was performed on all miscarriage specimens from these women, and all chromosomes were detected. Demographic and fetal tissue chromosome karyotype conditions were presented in Table \u003cspan\u003e1\u003c/span\u003e and Table \u003cspan\u003e2\u003c/span\u003e. Of these, a larger proportion (55.53%, 432/778) was patients with abnormal foetal tissue chromosomal karyotypes. The mean age and body mass index (BMI) of all patients were 30.98\u0026thinsp;\u0026plusmn;\u0026thinsp;3.97 years and 22.52\u0026thinsp;\u0026plusmn;\u0026thinsp;2.81 kg/m\u003csup\u003e2\u003c/sup\u003e, respectively. 730 cases of patients experienced SA before 12 weeks of pregnancy. The number of previous pregnancy losses was as follows: once in 147 cases, twice in 320 cases, three times in 221 cases, and \u0026ge;\u0026thinsp;4 times in 108 cases.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eNumber of people in all fetal tissue chromosome karyotypes.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eALL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTrisomy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45, X\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMicroduplication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTriploid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMicrodeletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMosaicism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonosomy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe correlations between clinical characteristics and chromosomal variants.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAll Patients(n\u0026thinsp;=\u0026thinsp;778)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;346)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAbnormal\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;432)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTest value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.98\u0026thinsp;\u0026plusmn;\u0026thinsp;3.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.64\u0026thinsp;\u0026plusmn;\u0026thinsp;3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.26\u0026thinsp;\u0026plusmn;\u0026thinsp;4.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e662(85.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e307(46.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e355(53.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.502\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e116(14.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39(33.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77(66.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI(kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.52\u0026thinsp;\u0026plusmn;\u0026thinsp;2.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.64\u0026thinsp;\u0026plusmn;\u0026thinsp;2.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.267\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;18.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38(4.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14(36.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24(63.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.485\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;18.5, \u0026lt;24.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e540(69.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e238(44.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e302(55.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;24.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200(25.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94(47.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e106(53.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGestational age(weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e730(93.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e317(43.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e413(56.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48(6.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29(60.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19(39.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe number of previous miscarriages(times)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e147(18.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63(42.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84(57.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.482\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e302(38.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126(41.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e176(58.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e221(28.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95(42.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126(57.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e108(13.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62(57.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46(42.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\"\u003e\n \u003ch2\u003eThe association between clinical characteristics and chromosomal abnormalities\u003c/h2\u003e\n \u003cp\u003eThe relationship between chromosomal abnormalities and different clinical features is presented in Table \u003cspan\u003e1\u003c/span\u003e.Among them, patients with abnormal fetal tissue chromosomal karyotypes had a significantly higher average age than those with normal karyotypes(31.26\u0026thinsp;\u0026plusmn;\u0026thinsp;4.14 vs. 30.64\u0026thinsp;\u0026plusmn;\u0026thinsp;3.72,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029), but there was no significant difference in BMI between the two groups(22.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.85 vs. 22.64\u0026thinsp;\u0026plusmn;\u0026thinsp;2.76,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.267). Moreover, the rate of chromosomal abnormalities was significantly higher in patients with maternal age \u0026gt;35 years than those patients in \u0026le;\u0026thinsp;35years(66.38% vs. 53.63%,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011). Additionally, the rate of fetal chromosomal abnormalities in pregnant women with gestational age\u0026thinsp;\u0026lt;\u0026thinsp;12 weeks is significantly higher than those with gestational age\u0026thinsp;\u0026ge;\u0026thinsp;12 weeks (56.58% vs.39.68%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022). When comparing the number of previous pregnancy losses, we found that among patients with recurrent pregnancy loss (RPL) who have had\u0026thinsp;\u0026ge;\u0026thinsp;4 miscarriages (42.59%), as the number of prior miscarriages decreases, the proportion of fetal chromosomal abnormalities increases (once:57.14%; twice:58.28%;3 times:57.01%; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024).\u003c/p\u003e\n \u003cdiv\u003e\n \u003cdiv align=\"left\"\u003eTable 3 showed the results from multiple logistic analyses. Compared with the corresponding comparison groups, the risk of chromosomal abnormalities was increased in women with advanced age(＞35 years,OR,1.841;95%CI,1.205-2.812),an earlier gestational age(＜12weeks,OR,2.041;95%CI,1.116-3.732)，less number of previous pregnancy loss(once: OR,2.007;95%CI,1.202-3.351;twice:OR,2.039;95%CI,1.296-3.206;3times:OR,1.957;95%CI,1.219-3.143).\u003c/div\u003e\n \u003cdiv align=\"char\"\u003eThe risk of SA patients with normal and abnormal fetal tissue chromosome karyotypes by different clinical characteristics was shown in Table4.The relative risk rate (RR) of \u0026ge; 35 years patients was a significant 1.4-fold higher than \u0026lt; 35 years (RR, 1.4, 95%CI, 1.1\u0026ndash;1.8).Meanwhile, the RR of gestational age ＜12 weeks patients was a significant 1.4-fold higher than those \u0026ge;12 weeks(RR,1.4,95%CI,1.1-1.8). Based on the reference group\u0026apos;s criteria, individuals who have experienced 1(RR,1.3,95%CI,1.0-1.7), 2(RR,1.4,95%CI,1.1-1.7), and 3(RR,1.3,95%CI,1.1-1.7) pregnancy losses all show significantly higher RR compared to the reference group(\u0026ge;4 previous pregnancy losses).\u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eMultiple logistic regression analyses of clinical risk characteristics for chromosomal variants.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAbnormal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRate(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(48.8\u0026ndash;57.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e66.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(57.7\u0026ndash;75.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(1.1\u0026ndash;1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI(kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;18.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(47.1\u0026ndash;79.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(0.8\u0026ndash;1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;18.5, \u0026lt;24.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(51.7\u0026ndash;60.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;24.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(46.0\u0026ndash;60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(0.8\u0026ndash;1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGestational age(weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e730\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(53.0-60.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(1.1\u0026ndash;1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(25.2\u0026ndash;53.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe number of previous miscarriages(times)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(49.0-65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(1.0-1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(52.7\u0026ndash;63.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(1.1\u0026ndash;1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(50.4\u0026ndash;63.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(1.1\u0026ndash;1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(33.1\u0026ndash;52.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe risk of SA patients with normal and abnormal fetal tissue chromosome karyotypes by different clinical characteristics.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAbnormal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRate(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(48.8\u0026ndash;57.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e66.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(57.7\u0026ndash;75.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(1.1\u0026ndash;1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI(kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;18.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(47.1\u0026ndash;79.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(0.8\u0026ndash;1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;18.5, \u0026lt;24.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(51.7\u0026ndash;60.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;24.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(46.0\u0026ndash;60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(0.8\u0026ndash;1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGestational age(weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e730\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(53.0-60.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(1.1\u0026ndash;1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(25.2\u0026ndash;53.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe number of previous miscarriages(times)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(49.0-65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(1.0-1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(52.7\u0026ndash;63.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(1.1\u0026ndash;1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(50.4\u0026ndash;63.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(1.1\u0026ndash;1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(33.1\u0026ndash;52.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eFetal tissue chromosomal characteristics and the distribution of abnormal chromosome karyotypes in 23 pairs of chromosomes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan\u003e1\u003c/span\u003e and Table \u003cspan\u003e1\u003c/span\u003e provide a detailed description of the types and distribution percentages of all embryo chromosomes. Among all fetal tissue chromosomes, the proportion of abnormal chromosomes is slightly higher than that of normal chromosomes (55.53%,432/778 vs. 44.47%,346/778). Categories of abnormal fetal tissue chromosome karyotypes were trisomy (26.09%,203/778),45,X(6.56%,51/778),microduplication(4.88%,38/778),triploid(4.37%,34/778),microdeletion(3.34%,26/778),mosaicism(1.93%,15/778),monosomy(0.26%,2/778)and others[8.10%,63/778,among them, multiple-chr(number of abnormal chromosomes\u0026thinsp;\u0026ge;\u0026thinsp;2, 7.46%,58/778), uniparental disomy(UPD,0.26%,2/778)and tetraploid(0.26%,2/778)].\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFigure 1\u003c/strong\u003eThe number of patients with all fetal tissue chromosome karyotypes.\u003c/p\u003e\n \u003cp\u003eThe distribution of the 23 pairs of chromosomes was in Fig.2. The distribution of abnormal fetal tissue chromosome karyotypes was concentrated on the sex chromosomes (20.30%,68/335), chromosome 16(19.40%,65/335), and chromosome 22(10.15%,34/335), and fewest on chromosome 12(0.60%,2/335). Trisomy is the most common type of abnormality among chromosomes, and it is predominantly found in chromosome 16(25.25%,51/202), followed by chromosomes 22(14.36%,29/202), 21(8.91%,18/202), 13(8.42%,17/202), and 2(6.93%,14/202), and showed no signs on chromosome 12(0%,0/202). The distribution of mosaicism was also enrichment on chromosome 16(26.67%,4/15), and showed no signs on chromosomes 1,6,7,8,10,13,14,15,17,18,20,21and X/Y (all 0%,0/15). The distribution of microduplication was enrichment on chromosome 16(17.95%,7/39), followed by chromosome 10(12.82%,5/39), but chromosomes 3,4,7,9,14 and 18 did not show this kind of abnormality (all 0%,0/39). The distribution of microdeletion was enrichment on chromosome X/Y(16.67%，4/24)，and fewest on chromosomes 2,3,6,7,8,10,12,13,20 and 21(all 0%,0/24).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eChromosomal abnormalities in the embryo have long been considered the most common cause of early SA, with most early studies indicating that it can lead to approximately half of all SAs\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Our study analyzed a total of 778 cases of miscarried products of conception (POCs), with a detection rate of abnormal chromosomes at 55.53%, which is like most previous studies\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe previous research indicated that most SA occur in the first 12 weeks of gestation, and the main cause of early pregnancy miscarriage was primarily due to chromosomal numerical abnormality\u003csup\u003e[\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Aneuploidy, a type of chromosomal numerical abnormality, is the most common embryonic chromosomal abnormality leading to SA, with trisomy being the most common\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. Our research indicated that chromosome 16 was the most common numerical abnormality, followed by chromosome 22. Additionally, the incidence rate of 45, X was highest among monoploids, which was consistent with previous studies\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIt was generally believed that advanced maternal age was a well-recognized risk factor for increased chromosomal abnormalities and the risk of SA\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Furthermore, studies had indicated that the incidence of fetal chromosomal aneuploidy was higher in women over 35 years of age\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. Most researchers believed that it was mainly due to the occurrence of premature separation of sister chromatids, non-disjunction in meiosis II, and reverse segregation during the development of oocytes in older women, which can significantly increase the incidence of trisomy in fetal tissue chromosome\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. In our study, the rate of fetal tissue chromosomal abnormalities in older women was significantly higher than that in younger women. However, due to the large difference in sample sizes between the two groups, no significant difference in the incidence of fetal tissue trisomy syndrome was found between the two groups. However, it is important to note that not all cases of trisomy syndrome will result in SA. Some trisomy anomalies may lead to children being born with a range of genetic disorders and developmental challenges, rather than miscarriage during pregnancy\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Therefore, we still need to expand the sample size and conduct further research to improve the accuracy and representativeness of our results.\u003c/p\u003e \u003cp\u003eIn addition to maternal age, this study also analyzed the relationship between gestational weeks, maternal BMI, and the number of previous miscarriages with fetal tissue chromosomal karyotypes. The study by Zhu et al. indicated that early pregnancy(\u0026le;\u0026thinsp;12weeks) and fewer previous pregnancy losses were significant risk factors for fetal tissue chromosomal numerical abnormalities\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Similarly, Gu et al. pointed out that early pregnancy(\u0026le;\u0026thinsp;11weeks) was a risk factor for fetal tissue aneuploidy and demonstrated that a history of recurrent miscarriages was a significant risk factor for sex chromosome abnormalities\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. The study by Nobuaki Ozawa et al. found that the rate of chromosomal abnormalities from women with a history of fewer than 2 pregnancy losses was significantly higher than those with 2 or more losses, and the types of chromosomal abnormalities in early pregnancy varied with gestational weeks\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. However, in this study, using a history of \u0026ge;\u0026thinsp;4 previous pregnancy losses as a reference, it was found that the rate of chromosomal abnormalities was higher in patients with a history of \u0026lt;\u0026thinsp;4 previous pregnancy losses, and as the number of losses decreased, the abnormality rate gradually increased. Additionally, the rate of abnormal chromosomes in early miscarriage(\u0026lt;12weeks) patients was significantly higher than in mid-to-late pregnancy. However, the sample size was small in this study, which may introduce some bias, therefore requiring an expansion of the sample size for further research.\u003c/p\u003e \u003cp\u003eBMI is a measure of body fat based on a person's weight and height. It is used to assess whether a person is underweight, normal weight, overweight, or obese, and is commonly used as one of the indicators of health risks. This study analyzed the relationship between different BMIs and the rate of chromosomal abnormalities in fetal tissue but did not find a significant association between the two. However, a previous study indicated a potential link between higher BMI and chromosomal abnormalities leading to recurrent miscarriages, while there was no significant association between BMI and patients with normal karyotypes and no history of miscarriage\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study also has certain limitations. Firstly, it is a single-center study with a relatively small sample size, and therefore, it cannot exclude the influence of factors such as geographical location, ethnicity, and lifestyle habits on miscarriage outcomes and fetal tissue chromosomal abnormalities. Secondly, although previous studies have indicated that fetal sex, crown-rump length, and mode of conception are important factors affecting the normalcy of embryo tissue chromosomal karyotypes\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e, this study did not take into account the condition of the gestational sac at the time of miscarriage (size, appearance, presence of fluid/hemorrhage around the sac), fetal conditions (crown-rump length and sex), and mode of conception (natural conception, ovulation induction, and assisted reproductive technology), which could potentially affect the study results. Thirdly, as the fertilized egg is a product of the combination of sperm and egg, abnormalities in fetal tissue chromosomal composition may result from factors related to either the male or female partner\u003csup\u003e[\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. However, this study did not incorporate these male-related factors into the analysis, such as male age, semen quality, and DNA fragmentation index (DFi), therefore, the potential impact of male factors on the experimental results cannot be ruled out. Finally, this study utilized CNV-Seq to detect fetal tissue chromosomal abnormalities. Due to inherent limitations of the detection technique\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e, such as maternal cell contamination, inability to detect polyploidy, or identification errors, the fetal tissue chromosomal results obtained in this study may have some minor inaccuracies.\u003c/p\u003e \u003cp\u003eTherefore, in summary, we still need to conduct large-scale, multi-center studies, ideally incorporating as many relevant factors as possible, and employ a combination of various detection methods may lead to more accurate, universal, and representative conclusions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, fetal tissue chromosomal abnormalities, especially numerical abnormalities, are the primary factors leading to SA. Maternal age, gestational age at the time of miscarriage, and the number of previous pregnancy losses are all important risk factors for fetal tissue chromosomal abnormalities. Further detailed research is needed to elucidate the specific mechanisms and explore additional risk factors, aiming to provide assistance and reference value for clinical treatment and improvement of prognosis for women with a history of SA.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent of participat\u003c/strong\u003ee\u003c/p\u003e\n\u003cp\u003eThe informed consent was signed by all patients in Lanzhou University Second Hospital. The study used non-identifiable patient data and was approved by the ethics review committee of the Lanzhou University Second Hospital(2023A-739). The research complies with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent of publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have agreed to publish this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available on request from the corresponding author. Researchers who are interested in working together on our study are more than welcome to collaborate. Contact the paper\u0026rsquo;s corresponding author, Fang Wang, [[email protected]].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the Science Foundation of Lanzhou University (Grant No. 071100132 and 071100186), the Medical Innovation and Development Project of Lanzhou University (Grant No. lzuyxcx-2022-137), and the Science Foundation of Lanzhou University Second Hospital (Grant No. YJS-BD-19).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The study conception and design were performed by L.L and F.W. Material preparation, data collection, and analysis were performed by L.L,YT.Y,N.H and HY.H. F.W provided raw data. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBENDER ATIK R, CHRISTIANSEN O B, ELSON J, et al. ESHRE guideline: recurrent pregnancy loss [J]. Hum Reprod Open, 2018, 2018(2): hoy004.\u003c/li\u003e\n\u003cli\u003eEvaluation and treatment of recurrent pregnancy loss: a committee opinion [J]. Fertil Steril, 2012, 98(5): 1103-11.\u003c/li\u003e\n\u003cli\u003eGONG C, YANG W, LIU X, et al. Low follistatin level is a causal risk factor for spontaneous abortion: a two-sample mendelian randomization study [J]. Front Endocrinol (Lausanne), 2023, 14: 1255591.\u003c/li\u003e\n\u003cli\u003eQUENBY S, GALLOS I D, DHILLON-SMITH R K, et al. Miscarriage matters: the epidemiological, physical, psychological, and economic costs of early pregnancy loss [J]. Lancet, 2021, 397(10285): 1658-67.\u003c/li\u003e\n\u003cli\u003eOZAWA N, OGAWA K, SASAKI A, et al. Maternal age, history of miscarriage, and embryonic/fetal size are associated with cytogenetic results of spontaneous early miscarriages [J]. J Assist Reprod Genet, 2019, 36(4): 749-57.\u003c/li\u003e\n\u003cli\u003eD\u0026apos;IPPOLITO S, LONGO G, ORTESCHI D, et al. Investigating the \u0026quot;Fetal Side\u0026quot; in Recurrent Pregnancy Loss: Reliability of Cell-Free DNA Testing in Detecting Chromosomal Abnormalities of Miscarriage Tissue [J]. J Clin Med, 2023, 12(12).\u003c/li\u003e\n\u003cli\u003eDOLANC MERC M, PETERLIN B, LOVRECIC L. The genetic approach to stillbirth: A \u0026raquo;systematic review\u0026laquo; [J]. Prenat Diagn, 2023, 43(9): 1220-8.\u003c/li\u003e\n\u003cli\u003eMCQUEEN D B, LATHI R B. Miscarriage chromosome testing: Indications, benefits and methodologies [J]. Semin Perinatol, 2019, 43(2): 101-4.\u003c/li\u003e\n\u003cli\u003ePAUTA M, GRANDE M, RODRIGUEZ-REVENGA L, et al. Added value of chromosomal microarray analysis over karyotyping in early pregnancy loss: systematic review and meta-analysis [J]. Ultrasound Obstet Gynecol, 2018, 51(4): 453-62.\u003c/li\u003e\n\u003cli\u003eSHAO Y, YANG S, CHENG L, et al. Identification of chromosomal abnormalities in miscarriages by CNV-Seq [J]. Mol Cytogenet, 2024, 17(1): 4.\u003c/li\u003e\n\u003cli\u003eLI F-X, XIE M-J, QU S-F, et al. Detection of chromosomal abnormalities in spontaneous miscarriage by low‑coverage next‑generation sequencing [J]. Mol Med Rep, 2020, 22(2): 1269-76.\u003c/li\u003e\n\u003cli\u003eZHANG J, MU F, GUO Z, et al. Chromosome analysis of foetal tissue from 1903 spontaneous abortion patients in 5 regions of China: a retrospective multicentre study [J]. BMC Pregnancy Childbirth, 2023, 23(1): 818.\u003c/li\u003e\n\u003cli\u003eROSENFELD J A, TUCKER M E, ESCOBAR L F, et al. Diagnostic utility of microarray testing in pregnancy loss [J]. Ultrasound Obstet Gynecol, 2015, 46(4): 478-86.\u003c/li\u003e\n\u003cli\u003eCHEN Q, ZHANG H, LI X, et al. Sequential application of copy number variation sequencing and quantitative fluorescence polymerase chain reaction in genetic analysis of miscarriage and stillbirth [J]. Mol Genet Genomic Med, 2023, 11(8): e2187.\u003c/li\u003e\n\u003cli\u003eDU Y, CHEN L, LIN J, et al. Chromosomal karyotype in chorionic villi of recurrent spontaneous abortion patients [J]. Biosci Trends, 2018, 12(1): 32-9.\u003c/li\u003e\n\u003cli\u003eGUI J, DING J, YIN T, et al. Chromosomal analysis of 262 miscarried conceptuses: a retrospective study [J]. BMC Pregnancy Childbirth, 2022, 22(1): 906.\u003c/li\u003e\n\u003cli\u003eZHU D, WEI X, ZHOU X-Y, et al. Chromosomal abnormalities in recurrent pregnancy loss and its association with clinical characteristics [J]. J Assist Reprod Genet, 2023, 40(7): 1713-20.\u003c/li\u003e\n\u003cli\u003eDAI Y-F, WU X-Q, HUANG H-L, et al. Experience of copy number variation sequencing applied in spontaneous abortion [J]. BMC Med Genomics, 2024, 17(1): 15.\u003c/li\u003e\n\u003cli\u003eKORKIDAKIS A, ALBERT A Y, JIANG I, et al. The Clinical Significance of Embryonic Chromosomal Errors in Recurrent Pregnancy Loss: an Analysis of 1107 Miscarriages [J]. Reprod Sci, 2023, 30(10): 3019-26.\u003c/li\u003e\n\u003cli\u003eZHANG L, YANG Y, WANG W, et al. Predicting risk of blastocyst aneuploidy among women with previous aneuploid pregnancy loss: a multicenter-data-based multivariable model [J]. Hum Reprod, 2023, 38(12): 2382-90.\u003c/li\u003e\n\u003cli\u003eGU C, LI K, LI R, et al. Chromosomal Aneuploidy Associated With Clinical Characteristics of Pregnancy Loss [J]. Front Genet, 2021, 12: 667697.\u003c/li\u003e\n\u003cli\u003eZENG W, QI H, DU Y, et al. Analysis of potential copy-number variations and genes associated with first-trimester missed abortion [J]. Heliyon, 2023, 9(8): e18868.\u003c/li\u003e\n\u003cli\u003eBAI W, ZHANG Q, LIN Z, et al. Analysis of copy number variations and possible candidate genes in spontaneous abortion by copy number variation sequencing [J]. Front Endocrinol (Lausanne), 2023, 14: 1218793.\u003c/li\u003e\n\u003cli\u003eMELO P, DHILLON-SMITH R, ISLAM M A, et al. Genetic causes of sporadic and recurrent miscarriage [J]. Fertil Steril, 2023, 120(5): 940-4.\u003c/li\u003e\n\u003cli\u003eELMERDAHL FREDERIKSEN L, \u0026Oslash;LGAARD S M, ROOS L, et al. Maternal age and the risk of fetal aneuploidy: A nationwide cohort study of more than 500\u0026thinsp;000 singleton pregnancies in Denmark from 2008 to 2017 [J]. Acta Obstet Gynecol Scand, 2024, 103(2): 351-9.\u003c/li\u003e\n\u003cli\u003eVERDYCK P, ALTARESCU G, SANTOS-RIBEIRO S, et al. Aneuploidy in oocytes from women of advanced maternal age: analysis of the causal meiotic errors and impact on embryo development [J]. Hum Reprod, 2023, 38(12): 2526-35.\u003c/li\u003e\n\u003cli\u003eCIMADOMO D, FABOZZI G, VAIARELLI A, et al. Impact of Maternal Age on Oocyte and Embryo Competence [J]. Front Endocrinol (Lausanne), 2018, 9: 327.\u003c/li\u003e\n\u003cli\u003eBALAGUER N, RODRIGO L, MATEU-BRULL E, et al. Non-invasive cell-free DNA-based approach for the diagnosis of clinical miscarriage: A retrospective study [J]. BJOG, 2024, 131(2): 213-21.\u003c/li\u003e\n\u003cli\u003eAL-OUQAILI M T S, MURSHID R M, ABD AL-KARIEM B Y, et al. Molecular cytogenetic analysis of multi-miscarriage products of conception in clinical cases from Al-Anbar Governorate, west of Iraq [J]. Saudi J Biol Sci, 2024, 31(3): 103932.\u003c/li\u003e\n\u003cli\u003eSCHLIEP K C, FELDKAMP M L, HANSON H A, et al. Are paternal or grandmaternal age associated with higher probability of trisomy 21 in offspring? A population-based, matched case-control study, 1995-2015 [J]. Paediatr Perinat Epidemiol, 2021, 35(3): 281-91.\u003c/li\u003e\n\u003cli\u003eWANG Z, LIU X, XU J, et al. Paternal age, body mass index, and semen volume are associated with chromosomal aberrations-related miscarriages in couples that underwent treatment by assisted reproductive technology [J]. Aging (Albany NY), 2020, 12(9): 8459-72.\u003c/li\u003e\n\u003cli\u003eLUO H, WANG Q, FU D, et al. Additional diagnostic value of CNV-seq over conventional karyotyping in prenatal diagnosis: A systematic review and meta-analysis [J]. J Obstet Gynaecol Res, 2023, 49(7): 1641-50.\u003c/li\u003e\n\u003cli\u003eZHANG J, TANG X, HU J, et al. Investigation on combined copy number variation sequencing and cytogenetic karyotyping for prenatal diagnosis [J]. BMC Pregnancy Childbirth, 2021, 21(1): 496.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"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":"Fetal chromosome karyotypes, Spontaneous abortion, advanced maternal age, CNV-seq","lastPublishedDoi":"10.21203/rs.3.rs-4190327/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4190327/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAbnormal fetal tissue chromosome karyotypes are one of the important pathogenic factors for spontaneous abortion (SA). To analyze the characteristics of fetal tissue chromosomal karyotype in 778 women with a history of SA and its relationship with clinical features.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective study collected maternal age, body mass index (BMI), gestational weeks at miscarriage, the number of previous pregnancy losses and fetal tissue karyotypes CNV-seq data of 778 SA couples from Lanzhou University Second Hospital from October 2019 to December 2023, and described the characteristics of fetal tissue chromosomal karyotype and its relationship with clinical features.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn our study, 432 patients (55.53% of total) had abnormal fetal tissue chromosomal karyotypes, with the highest incidence being trisomy syndrome (46.99%,203/432). Advanced maternal age(\u0026gt;35 years), early pregnancy(\u0026lt;12 weeks), and a history of less than four previous pregnancy losses were all identified as risk factors for fetal tissue chromosomal abnormalities.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe results of this study indicate that fetal tissue chromosomal abnormalities are the primary factor leading to SA. Additionally, advanced maternal age(\u0026gt;35years), early pregnancy(\u0026lt;12 weeks=, and the fewer number of previous pregnancy losses(\u0026le;\u0026thinsp;4 times) are associated with a higher risk of fetal tissue chromosomal abnormalities following miscarriage.\u003c/p\u003e","manuscriptTitle":"The relationship between fetal tissue chromosomal karyotype and clinical characteristics in patients with spontaneous abortion: a retrospective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-03 17:13:54","doi":"10.21203/rs.3.rs-4190327/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"checksComplete","content":"","date":"2024-03-30T08:54:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-30T08:54:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2024-03-30T02:54:02+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":"fe684dc3-094d-4237-a429-0ed0ca2b6d5f","owner":[],"postedDate":"April 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-04-03T17:13:54+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-03 17:13:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4190327","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4190327","identity":"rs-4190327","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}