The genetic diagnostic value of invasive testing in recurrent spontaneous abortion: A retrospective cohort study.

The genetic diagnostic value of invasive testing in recurrent spontaneous abortion: A retrospective cohort study. | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 25 January 2026 V1 Latest version Share on The genetic diagnostic value of invasive testing in recurrent spontaneous abortion: A retrospective cohort study. Authors : Siyao Ha , Qi Xu 0000-0001-9437-3956 , Shuai Fu , Liqiong Zhu , Shangya Yuan , Xiaohui Ji , Na Di , Liyang Liang , Tao Du , and Hui Chen 0000-0002-3709-6494 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.176931556.63962356/v1 203 views 95 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Objective: To characterize the spectrum of genetic abnormalities and identify predictive factors for pathogenic findings in mid-trimester viable pregnancies among women with a history of recurrent spontaneous abortion (RSA). Design: Retrospective cohort study. Setting: a national study conducted at a tertiary hospital in China Sample: 473 Chinese women with a history of RSA who underwent invasive prenatal diagnosis (IPD) between 2018 and 2025. Methods: Women were stratified by fetal ultrasound findings. We assessed the diagnostic yield of karyotyping and the incremental yield of chromosomal microarray analysis (CMA) and whole-exome sequencing (WES). Multivariable logistic regression identified independent risk factors for pathogenic findings. Main outcome measures: Diagnostic yield of pathogenic findings for each testing method and adjusted odds ratios (aOR) with 95% confidence intervals (CI) for identified risk factors. Results: The karyotype yield increased from 1.77% in isolated RSA to 4.35% and 13.11% in cases with soft markers and structural anomalies, respectively (none in FGR/abnormal appendages group). CMA/WES provided significant incremental diagnostic yield alongside inconclusive results. Multivariable analysis established fetal structural anomalies (aOR, 4.47; 95% CI, 1.13 – 16.47; P = 0.033) and soft markers (aOR, 3.71; 95% CI, 1.04 – 12.51; P = 0.044) as independent risk factors, whereas advanced age, prior fetal aneuploidy/structural anomalies, and abnormal serum screening showed no independent associations. Conclusions: Real-time fetal phenotype is the dominant factor, overriding traditional risk factors in predicting outcome. A tiered strategy with karyotyping/CMA first-line and WES reserved for selected cases is proposed. makecell, tabularx makecell, tabularx Article Title : The genetic diagnostic value of invasive testing in recurrent spontaneous abortion: A retrospective cohort study. Running Title: Recurrent spontaneous abortion and invasive prenatal diagnosis Manuscript word 3041, table and figure count 6 Siyao Ha, M.D., 1# Qi Xu, M.D., 1# Shuai Fu, M.D., 2# Liqiong Zhu, M.D., 13 Shangya Yuan, M.D., 1 Xiaohui Ji, M.D., 1 Na Di, M.D., 4 Liyang Liang, M.D., 5 Tao Du, M.D., 36 and Hui Chen, M.D., 13 1 Department of Obstetrics and Gynecology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China. 2 Prenatal Diagnosis and Medical Genetics Center, Shenshan Medical Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University , Shanwei, China. 3 Guangdong Provincial Clinical Research Center for Obstetrical and Gynecological Diseases, Guangzhou, China. 4 Department of Ultrasound, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China. 5 Department of Pediatrics, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China. 6 Prenatal Diagnosis and Medical Genetics Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China. # Siyao Ha, Qi Xu, and Shuai Fu contributed equally to this study. Corresponding author Hui Chen: Department of Obstetrics and Gynecology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China. https://orcid.org/0000-0002-3709-6494, 13826445092, [email protected] . Abstract Objective: To characterize the spectrum of genetic abnormalities and identify predictive factors for pathogenic findings in mid-trimester viable pregnancies among women with a history of recurrent spontaneous abortion (RSA). Design: Retrospective cohort study. Setting: a national study conducted at a tertiary hospital in China Sample: 473 Chinese women with a history of RSA who underwent invasive prenatal diagnosis (IPD) between 2018 and 2025. Methods: Women were stratified by fetal ultrasound findings. We assessed the diagnostic yield of karyotyping and the incremental yield of chromosomal microarray analysis (CMA) and whole-exome sequencing (WES). Multivariable logistic regression identified independent risk factors for pathogenic findings. Main outcome measures: Diagnostic yield of pathogenic findings for each testing method and adjusted odds ratios (aOR) with 95% confidence intervals (CI) for identified risk factors. Results: The karyotype yield increased from 1.77% in isolated RSA to 4.35% and 13.11% in cases with soft markers and structural anomalies, respectively (none in FGR/abnormal appendages group). CMA/WES provided significant incremental diagnostic yield alongside inconclusive results. Multivariable analysis established fetal structural anomalies (aOR, 4.47; 95% CI, 1.13 – 16.47; P = 0.033) and soft markers (aOR, 3.71; 95% CI, 1.04 – 12.51; P = 0.044) as independent risk factors, whereas advanced age, prior fetal aneuploidy/structural anomalies, and abnormal serum screening showed no independent associations. Conclusions: Real-time fetal phenotype is the dominant factor, overriding traditional risk factors in predicting outcome. A tiered strategy with karyotyping/CMA first-line and WES reserved for selected cases is proposed. Funding: the Key Program of Joint Funds of the National Natural Science Foundation of China (Grant No. U24A20781), the Natural Science Foundation of Guangdong Province (Grant No. 2024A1515013264), Sun Yat-Sen Clinical Research (Grant No. SYS-5010-202410), and Guangzhou Basic and Applied Basic Research Foundation (Grant No. 2023A04J2081). Keywords: Abortion, Spontaneous; Prenatal Diagnosis; Karyotyping; Chromosomal Microarray Analysis; Exome Sequencing; Ultrasonography, Prenatal 1 Introduction Recurrent spontaneous abortion (RSA), affecting 2 – 5% of pregnancies, imposes significant physical and psychological burdens. 1-3 The etiology of RSA is multifactorial, involving genetic, immunological, endocrine, anatomical, and thrombophilia factors. 4-5 Indeed, genetic abnormalities constitute a major contributor, with chromosomal anomalies identified in 50% – 60% of miscarried embryos. 6 Current guidelines, including the American College of Obstetricians and Gynecologists (ACOG, 2016), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG, 2016), and the European Society of Human Reproduction and Embryology (ESHRE, 2022), recognize RSA as a risk factor for fetal chromosomal anomalies and recommend genetic counseling. 2,7-8 However, a significant clinical challenge remains in defining the precise additional indication for invasive prenatal diagnosis (IPD) attributable to the RSA history itself in these women: specifically, on what basis for those with isolated RSA, and to what extent the RSA history adds to the genetic risk already identified by ultrasound anomalies. Current robust evidence on genetic etiology in RSA primarily originates from studies on early pregnancy losses, 9-13 creating a fundamental knowledge gap regarding the genetic risk of surviving fetuses in women with RSA history who progress successfully into the mid-trimester. Consequently, the clinical justification for IPD in women with isolated RSA, where no ultrasonographic abnormalities are detected, remains uncertain. Conversely, for RSA pregnancies with abnormal ultrasound findings, a well-established IPD indication, it is unknown whether the RSA history confers additional genetic risk beyond the observed structural anomalies. Although chromosomal microarray analysis (CMA) improves detection of submicroscopic abnormalities and whole-exome sequencing (WES) shows diagnostic promise, their utility within a risk-stratified RSA cohort has not been systematically evaluated. 14-16 To address these gaps, we conducted a retrospective cohort study to assess the distribution of genetic abnormalities and identify predictive factors within a cohort of women with a history of RSA who had achieved viable pregnancies. By comparing detection rates across subgroups defined by ultrasound findings and evaluating traditional risk factors, this study aims to inform risk stratification and decision-making for IPD in this population. 2.1 Study design and population This single-center retrospective cohort study was conducted at the Prenatal Diagnosis Center of Sun Yat-Sen Memorial Hospital, Guangdong, China, between January 2018 and March 2025. The study was approved by the hospital’s Institutional Review Board (No.: SYSKY-2025-510-01). Informed consent was obtained from all patients on admission, prior to IPD, to use their anonymized clinical data for research purposes. The women in this study were not participating concurrently in any other clinical trials, and all included data were unpublished prior to this study. The study included Chinese women aged between 20 and 48 years who met the following criteria: (1) a documented history of two or more spontaneous pregnancy losses with the same partner; (2) a current singleton pregnancy achieved through natural conception; and (3) completion of invasive prenatal diagnostic procedures (chorionic villus sampling, amniocentesis, or cordocentesis). Exclusion criteria were applied to mitigate potential confounding factors, including: (1) non-genetic maternal factors associated with RSA (uterine anatomical anomalies, untreated cervical insufficiency, active genital tract infections); (2) pregnancies involving multiple gestations; (3) conceptions achieved through assisted reproductive technology; (4) cases with definitive indications for invasive prenatal genetic testing (high-risk non-invasive prenatal testing results, parental carrier of chromosome rearrangement, parental known carrier status of pathogenic/likely pathogenic variants, current fetal demise); and (5) instances where genetic analysis results were unavailable. Participants were stratified into mutually exclusive groups of increasing clinical severity based on pre-procedural ultrasonographic findings (for detailed definitions, see the ’Data Collection and Variable Definitions’ section). For a detailed overview of the participant selection process, see Figure 1 . 2.2 Data collection and variable definitions Data on demographic characteristics, obstetric history, and clinical details of the current pregnancy were systematically extracted from electronic medical records. RSA: Defined as two or more pregnancy losses occurring before 28 weeks of gestation with the same partner, regardless of sequence, and including biochemical pregnancies. Demographics: Included maternal age at the expected date of delivery (<35 vs. ≥35 years for advanced maternal age, AMA) ; paternal age (<40 vs. ≥40 years for advanced paternal age, APA); 17 maternal pre-pregnancy body mass index (BMI, kg/m²); and gestational age at the invasive procedure (stratified as 11 +0 ~13 +6 , 14 +0 ~24 +6 , and 25 +0 ~34 +6 weeks). Obstetric history: Included gravidity, number of prior miscarriages, history of prior fetal aneuploidy or structural anomalies, presence of maternal immune disorders (e.g., anti-phospholipid syndrome, systemic lupus erythematosus, Sjögren’s syndrome, or undifferentiated connective tissue disease), and results from serum screening (PAPP-A/β-hCG). Ultrasonographic stratification groups: Participants were categorized into the following mutually exclusive groups based on pre-procedural ultrasound examinations: 1. Isolated RSA: no ultrasound anomaly; non-imaging risks (e.g., suspicious family history) could prompt further tests but did not change classification. 2. Soft markers (e.g., nuchal translucency [NT] ≥2.5mm, nuchal Fold≥6.0mm, mild ventriculomegaly, echogenic bowel, aplastic nasal bone, hydronephrosis, and single umbilical artery，etc). 18 3. Fetal growth restriction (FGR)/Abnormal fetal appendages: Encompassing disorders such as abnormal amniotic fluid volume, placental anomalies, abnormal umbilical artery Doppler waveforms, or FGR (estimated fetal weight or abdomen circumference < 10rd percentile). 4. Fetal structural anomalies: any major structural malformation. Pregnancy outcomes were categorized based on live birth without any congenital anomalies. All other outcomes, including induced abortion, miscarriage, and live birth with congenital anomalies, were grouped accordingly. makecell, tabularx makecell, tabularx 2.3 Genetic testing analysis All genetic analyses were performed in the hospital’s accredited central laboratory. No procedure-related complications occurred within 2 weeks post-procedure in this cohort. Karyotyping with G‑banding (resolution 320 – 400 bands) was conducted according to standard cytogenetic protocols, with independent review by two certified cytogeneticists. Chromosomal microarray analysis was performed using high‑density platforms (Affymetrix CytoScan HD or Illumina GSA), delivering genome-wide resolution >50 kb and enhanced resolution (10 – 20 kb) in clinically significant regions. WES was restricted to clinician-flagged high-risk cases: major fetal structural anomaly, ≥2 soft markers, prior pregnancy with suspected monogenic disease, or unexplained family history, or multidisciplinary consensus; because selection was indication-driven, yield applies only to this enriched subset and not to the wider RSA population. Trio-whole exome sequencing was conducted on Illumina platforms using Illumina capture systems, with mean coverages of >100× for fetal samples and >80× for parental samples. Variant classification adhered to the standards of the American College of Medical Genetics and Genomics (ACMG) guidelines. 2.4 Outcome definitions Diagnostic findings were categorized according to a three-tier system: 1. Positive: Included numerical or structural chromosomal abnormalities (karyotype); pathogenic/likely pathogenic copy number variants (CNVs) and pathogenic/likely pathogenic absence of heterozygosity (AOH, CMA); and pathogenic/likely pathogenic sequence variants (WES) clearly associated with fetal phenotype, specifically including compound heterozygous or homozygous variants in autosomal recessive disorders, heterozygous variants in autosomal dominant or X-linked dominant disorders, and hemizygous variants in X-linked recessive disorders (in males). 2. Inconclusive: Comprised variants of uncertain significance (VUS), and AOH of uncertain significance (CMA); along with variants of uncertain significance detected through WES, and pathogenic/likely pathogenic sequence variants (WES) with uncertain phenotype association. 3. Negative: Defined as a normal karyotype or the presence of only benign polymorphic variants, with no pathogenic, likely pathogenic, or uncertain significance variants (CMA or WES). This classification also included carrier status for autosomal recessive, or X-linked recessive disorders (in females), although these carrier findings were returned to parents as secondary findings per laboratory policy. 2.5 Diagnostic yield and incremental detection rate Baseline yield was defined by karyotyping in the full cohort (n = 473). Among the 381 patients who proceeded to both karyotyping and CMA, incremental yield was calculated as new pathogenic or inconclusive findings detected only when the preceding karyotype was normal, divided by all patients who received both tiers. Likewise, WES increment was assessed in the 53 individuals who completed all three tests (three with missing CMA data were excluded). Positive and inconclusive rates were computed separately. 2.6 Risk analysis The primary analysis was restricted to positive results, while a sensitivity analysis incorporated both positive and inconclusive variants, with negative results serving as the reference group in all comparisons. To isolate the effect of RSA history and ultrasound phenotypes, variables including AMA, APA, history of prior fetal aneuploidy/structural anomalies, and abnormal serum screening were included in regression models as potential confounders. 7-8 These outcome definitions were consistently applied across two testing paradigms: the comprehensive approach (karyotype with optional CMA and WES) for primary analysis, and the standard approach (karyotype with optional CMA) for sensitivity analysis. 2.7 Statistical analysis Analyses were performed using R (v4.5.1). Continuous variables were compared using one-way ANOVA or the Kruskal-Wallis test, as appropriate; categorical variables using chi-square or Fisher’s exact tests. Diagnostic yield was reported with 95% Clopper-Pearson confidence interval (CI). Firth’s penalized-likelihood logistic regression was employed to reduce small-sample bias. Variables with P < 0.20 in univariate analyses or clinical relevance were included in multivariable models. Model performance was evaluated using area under the curve (AUC) with DeLong’s 95% CI. A two-sided significance level of 0.05 was used for all tests. The final model was visualized using a forest plot. 3 Results makecell, tabularx makecell, tabularx 3.1 Baseline characteristics A total of 561 women with RSA history who underwent IPD between January 2018 and March 2025 were initially assessed. After applying the exclusion criteria, 473 pregnancies constituted the final study cohort ( Table 1 ). Demographic analysis revealed significant differences: the isolated RSA group had the highest rates of advanced parental age (59.7% maternal, 30.7% paternal), with both parameters decreasing as ultrasound abnormality severity increased ( P < 0.001 ). Maternal immune disorders increased from 10.1% to 31.2% across the severity spectrum ( P = 0.009). Most IPDs were performed at 14 +0 ~24 +6 weeks, except in the FGR/abnormal fetal appendages group (56.7% at 25 +0 ~34 +6 weeks). WES utilization increased significantly from 1.8% in isolated RSA to 41.0% in structural anomalies ( P < 0.001). Pregnancy outcomes progressively worsened with abnormality severity, as live birth rates without anomalies declined from 96.8% to 8.2% ( P < 0.001). Additionally, no significant differences were observed in maternal BMI, number of miscarriages, or abnormal serum screening results across the groups. 3.2 Diagnostic yield and incremental detection rate In the entire cohort (n = 473), the diagnostic yield of karyotyping was 1.77% (95% CI 0.58 – 4.07) for isolated RSA. This yield was higher in cases with soft markers ( P = 0. 192) and highest in those with fetal structural anomalies ( P < 0. 001). No abnormal karyotypes were identified in the FGR/abnormal fetal appendages group ( Figure. 2A, Supporting Information Table S1 ). It is noteworthy that pathogenic findings in this group were exclusively identified through CMA (as detailed below) and presented at advanced gestational ages. CMA testing demonstrated incremental diagnostic yields across all groups. The isolated RSA group showed a positive incremental yield of 1.42%, compared to 3.55% in the combined abnormal ultrasound findings group, while the inconclusive incremental detection rates were 3.77% and 6.51%, respectively ( Figure. 2B, Supporting Information Table S1 ). In the WES subgroup, no additional positive or inconclusive findings were detected among isolated RSA cases. In contrast, the abnormal ultrasound group exhibited additional pathogenic findings in 4.17% (2/48) and inconclusive findings in 20.83% (10/48) of cases ( Figure. 2C, Supporting Information Table S1 ). makecell, tabularx makecell, tabularx 3.3 Risk factors for abnormal genetic findings To identify risk factors for positive genetic findings, we performed Firth penalized-likelihood logistic regression analyses, which is robust for analyses with a limited number of events. This analysis was restricted to the 362 patients undergoing procedures in mid-trimester between 14 +0 ~24 +6 weeks’ gestation to mitigate confounding by gestational age ( Figure 3 ). In univariate analysis, only fetal structural anomalies were significantly associated with positive genetic findings (odds ratio [OR] 9.31, 95% CI 3.26 – 25.44, P < 0. 001), with soft markers showing borderline association (OR 2.79, 95% CI 0.91 – 7.53, P = 0. 071). On adjusted odds ratio (aOR) analysis , both remained independently associated: fetal structural anomalies (aOR 4.47, 95% CI 1.13 – 16.47, P = 0. 033) and soft markers (aOR 3.71, 95% CI 1.04 – 12.51, P = 0.0 44). No other covariates (AMA, APA, prior fetal aneuploidy/structural anomalies, maternal immune disorders, abnormal serum screening results) reached significance. The FGR/abnormal fetal appendages group was excluded from this model because all positive cases in this category were identified by CMA or WES and presented later in gestation (after 24 +6 weeks), which was outside the gestational window selected for this primary analysis . The multivariable model demonstrated good discriminative ability, with AUC of 0.85 (95% CI: 0.79 – makecell, tabularx makecell, tabularx 0.92, Supporting Information Figure S1). 3.4 Sensitivity Analyses Sensitivity analyses confirmed the robustness of primary findings (Supporting Information Table S2). The association for structural anomalies remained significant across all models. The association for soft markers was significant in primary and core models but attenuated when excluding WES ( P = 0.1 10), suggesting its predictive value depends on comprehensive genomic testing. Null associations for other clinical factors were stable. 4 Discussion 4.1 Main Findings This study proposes an ultrasound-guided stratified genetic risk assessment model for women with RSA, identifying fetal structural anomalies and soft markers as independent risk factors for pathogenic findings. CMA and WES provided substantial incremental diagnostic value over karyotyping, albeit accompanied by a proportion of inconclusive findings. These results refine and add complexity to pre-test genetic counseling for IPD in this population. 4.2 Strengths and Limitations Strengths include a large, rigorously selected RSA cohort from Sun Yat-Sen Memorial Hospital, a comprehensive tertiary center with a National Key Clinical Specialty in Obstetrics and Gynecology. By focusing specifically on RSA patients with viable pregnancies, this research addresses an important evidence gap in prenatal genetic risk assessment. Limitations include the single-center, retrospective design, potentially affecting generalizability. The number of positive events in key subgroups remained limited. W ES was restricted to high-risk cases; thus, its yield applies only to this enriched subset . 4.3 Interpretation This baseline rate (1.77%) remained stable in the 14 +0 ~24 +6 weeks’ subgroup (1.83%). This rate is roughly twice the 0.5 – 1 % background rate, which may suggest an association worth further investigation but does not in itself establish RSA as an independent risk factor for IPD. 7-8 While early miscarriage is dominated by numerical chromosomal anomalies, the contribution of submicroscopic abnormalities in ongoing RSA pregnancies should not be overlooked. 13,19 CMA provided an incremental diagnostic yield of 1.42%, supporting its use as a more sensitive test in the RSA population, in line with ACOG recommendations. 7,20 Multivariable regression suggested that this risk was intrinsic to the condition itself, as several established factors showed no significant independent association with positive genetic findings. The diminished role of traditional risk factors here contrasts with general obstetrics. Specifically, the relationship between a history of prior fetal aneuploidy and AMA is often interdependent in the general population. 21-22 However, obstetric history was not an independent predictor in our cohort, likely due to the frequent lack of prior genetic confirmation. Similarly, while guidelines note APA as an indication, our findings support a restrained approach to its application in RSA management. 23-24 Additionally, the lack of association for abnormal serum screening, meanwhile, may reflect its primary role as a marker of placental function rather than a direct predictor of fetal genetic anomalies. 25-26 Furthermore, the number of prior miscarriages did not predict genetic abnormalities in the ongoing pregnancy, contrasting with first-trimester POC studies which link more losses to a lower rate of euploid miscarriage, 27-29 a discrepancy likely because our cohort had already survived the high-risk period for major aneuploidies. Collectively, these findings indicate that within this cohort, the presence of a viable pregnancy and its real-time ultrasound findings are the primary determinants of genetic risk, whereas the incremental contributions of traditional factors appear attenuated. Our data establish a clear risk hierarchy driven by ultrasound findings. Fetal structural anomalies constituted the strongest independent predictor of pathogenic genetic findings, with a diagnostic yield of 13.11% by karyotyping and an additional 5.26% by CMA. In multivariable analysis, the fetal structural anomalies remained a powerful risk factor (aOR 4.47, 95% CI: 1.13 – 16.47, P = 0. 033), consistent with the meta-analyses of WES. 30 Notably, ultrasonographic soft markers, often dismissed in the general population as isolated findings, 31-32 emerged as an independent risk factor in our RSA cohort (aOR 3.71, 95% CI: 1.04 – 12.51, P = 0. 044). The baseline karyotypic yield of 4.35% in this group, coupled with an incremental CMA yield of 3.23%, underscores that soft markers in RSA patients convey a meaningful genetic risk. This contrasts with general population guidelines, which typically discourage IPD for isolated soft markers . 18 Regarding FGR and abnormal fetal appendages, our findings align with evidence of a measurable CMA yield in FGR and a modest WES yield. 33-25 The sole pathogenic finding in this subgroup was detected by CMA in a FGR case at 26 weeks’ gestation; however, the small sample size at advanced gestational ages precluded stable risk estimation. Among the 53 patients who underwent all three testing modalities, WES identified no incremental findings in the 5 isolated RSA cases ( Supporting Information Table S3 ). This very limited yield, even in a selected cohort with potential genetic clues, suggests that the value of WES in isolated RSA is minimal, though larger prospective studies are needed to confirm this. This conclusion is consistent with prospective studies reporting low WES diagnostic yields in fetuses without structural anomalies. 31-32 In contrast, among the 48 patients in the abnormal ultrasound group, WES identified pathogenic variants in two cases (4.17%): one with soft markers (increased NT/hydronephrosis) harboring a de novo heterozygous variant in KAT6B , and one with multisystem structural anomalies carrying compound heterozygous variants in NEK8 ( Supporting Information Table S4 ) . This incremental diagnostic yield beyond CMA is consistent with that reported in large prospective cohorts. 32,36 These results underscore that the identification of a structural anomaly, and in selected cases of soft markers, constitutes a compelling indication for WES to elucidate the underlying genetic etiology. Critically, the pursuit of a definitive diagnosis should not be foregone solely because the pregnancy is considered precious. A clear genetic diagnosis provides invaluable information for managing the current pregnancy, predicting recurrence risk, and guiding reproductive decisions in the future. However, alongside the clear diagnostic benefits, WES also demonstrated a considerable incremental rate of inconclusive findings in the abnormal ultrasound group (20.83%; comprising 4.17% [2/48] variants with uncertain phenotype association and 6.25% [3/48] VUS). The management of such inconclusive results is a well-recognized challenge in prenatal genomics and may increase patient anxiety, underscoring the critical need for expert multidisciplinary review and tailored post-test genetic counseling to fully realize the potential of these advanced technologies. 37-39 Conclusion In summary, this study supports a stratified genetic diagnostic approach for ongoing pregnancies in women with RSA history, where real-time ultrasound findings guide decision-making. A tiered diagnostic approach utilizes karyotyping and CMA as the basis for all patients, while reserving WES for those with structural anomalies or selected soft markers. Integrating this phenotype-driven strategy with expert multidisciplinary counseling is essential for navigating genomic complexity, optimizing pregnancy management, and empowering patients with information critical for their reproductive future. Acknowledgements This work was supported by the Key Program of Joint Funds of the National Natural Science Foundation of China ( Grant No. U24A20781), the Natural Science Foundation of Guangdong Province ( Grant No. 2024A1515013264), Sun Yat-Sen Clinical Research ( Grant No. SYS-5010-202410), and Guangzhou Basic and Applied Basic Research Foundation ( Grant No. 2023A04J2081). Conflict of interest The authors declare no conflicts of interest. Author contributions Siyao Ha, Qi Xu and Shuai Fu contributed equally to this work. Siyao Ha: Investigation, Data curation, Methodology, Validation, Software, Formal analysis, Visualization and Writing – original draft. Qi Xu: Investigation, Methodology, Validation, and Writing – original draft. Shuai Fu: Investigation, Methodology, Validation, and Writing – original draft. Liqiong Zhu: Writing – review & editing Shangya Yuan: Data curation Xiaohui Ji: Formal analysis Na Di: Methodology, Validation Liyang Liang: Methodology, Validation Tao Du: Resources, Supervision, Writing – review & editing Hui Chen: Conceptualization, Project administration, Funding acquisition, Writing – review & editing Ethnics statement This national historical cohort study was conducted at the Prenatal Diagnosis Center of Sun Yat-Sen Memorial Hospital, Guangdong, China, between January 2018 and March 2025. The study was approved by the hospital’s Institutional Review Board ( No.: SYSKY-2025-510-01). Informed consent was obtained from all patients on admission, prior to procedure, to use their anonymized clinical data for research purposes. makecell, tabularx makecell, tabularx Data availability statement The data that support the findings of this study are available from the corresponding author upon reasonable request. References 1. Royal College of Obstetricians and Gynaecologists. Recurrent miscarriage green-top guideline no. 17. BJOG . 2023;130(1):e9-e39. 2. ESHRE Guideline Group on RPL. ESHRE guideline: recurrent pregnancy loss: an update in 2022. Hum Reprod Open . 2023;2023(1):hoad002. 3. Practice Committee of the American Society for Reproductive Medicine. Evaluation and treatment of recurrent pregnancy loss: a committee opinion. Fertil Steril . 2012;98(5):1103-1111. 4. Quenby S, Gallos ID, Dhillon-Smith RK, Podesek M, Stephenson MD, Fisher J. Miscarriage matters: the epidemiological, physical, psychological, and economic costs of early pregnancy loss. Lancet . 2021;397(21):1658-1667. 5. Dimitriadis E, Menkhorst E, Saito S, Kutteh WH, Brosens JJ. Recurrent pregnancy loss. Nat Rev Dis Primers . 2020;6(1):98. 6. Simpson JL. Genes, chromosomes, and reproductive failure. Fertil Steril . 1980;33(2):107-116. 7. American College of Obstetricians and Gynecologists. Practice Bulletin No. 162: Prenatal diagnostic testing for genetic disorders. Obstet Gynecol . 2016;127(5):e108-e122. 8. International Society of Ultrasound in Obstetrics and Gynecology (ISUOG). ISUOG Practice Guidelines: invasive procedures for prenatal diagnosis. Ultrasound Obstet Gynecol . 2016;48(2):256-268. 9. Wang Y, Li Y, Chen Y, Sang Z, Meng L. Systematic analysis of copy-number variations associated with early pregnancy loss. Ultrasound Obstet Gynecol . 2020;55(1):96-104. 10. Chen Y, Bartanus J, Liang D, Zhu H, Breman AM, Smith JL. Characterization of chromosomal abnormalities in pregnancy losses reveals critical genes and loci for human early development. Hum Mutat . 2017;38(6):669-677. 11. Liu S, Long S, Cram DS, Xiong L, Wang K, Wu R. Traditional karyotyping vs copy number variation sequencing for detection of chromosomal abnormalities associated with spontaneous miscarriage. Ultrasound Obstet Gynecol . 2015;46(4):472-477. 12. Li Y, Chau MHK, Zhang YX, Zhao Y, Xue S, Li TH. A pilot investigation of low-pass genome sequencing identifying site-specific variation in chromosomal mosaicisms by a multiple site sampling approach in first-trimester miscarriages. Hum Reprod . 2023;38(8):1628-1642. 13. Grande M, Borrell A, Garcia-Posada R, Borobio V, Muñoz M, Creus M. The effect of maternal age on chromosomal anomaly rate and spectrum in recurrent miscarriage. Hum Reprod . 2012;27(10):3109-3117. 14. Xiang J, Ding Y, Song X, Mao J, Liu M, Liu Y. Clinical utility of SNP array analysis in prenatal diagnosis: a cohort study of 5000 pregnancies. Front Genet . 2020;11:571219. 15.Reddy UM, Page GP, Saade GR, Silver RM, Thorsten VR, Parker CB. Karyotype versus microarray testing for genetic abnormalities after stillbirth. N Engl J Med . 2012;367(23):2185-2193. 16. Wang X, Shi W, Zhao S, Gong D, Li S, Hu C. Whole exome sequencing in unexplained recurrent miscarriage families identified novel pathogenic genetic causes of euploid miscarriage. Hum Reprod . 2023;38(5):1003-1018. 17. du Fossé NA, van der Hoorn ML, van Lith JMM, le Cessie S, Lashley E. Advanced paternal age is associated with an increased risk of spontaneous miscarriage: a systematic review and meta-analysis. Hum Reprod Update . 2020;26(5):650-669. Society for Maternal-Fetal Medicine (SMFM). Society for Maternal-Fetal Medicine Consult Series #57: Evaluation and management of isolated soft ultrasound markers for aneuploidy in the second trimester. Am J Obstet Gynecol . 2021;225(1):B2-B15. 19. Sánchez JM, Franzi L, Collia F, De Díaz SL, Panal M, Dubner M. Cytogenetic study of spontaneous abortions by transabdominal villus sampling and direct analysis of villi. Prenat Diagn . 1999;19(7):601-603. 20. Wapner RJ, Martin CL, Levy B, Ballif BC, Eng CM, Zachary JM. Chromosomal microarray versus karyotyping for prenatal diagnosis. N Engl J Med . 2012;367(23):2175-2184. 21. Grande M, Stergiotou I, Borobio V, Sabrià J, Soler A, Borrell A. Heterotrisomy recurrence risk: a practical maternal age-dependent approach for excess trisomy 21 risk calculation after a previous autosomal trisomy. J Matern Fetal Neonatal Med . 2017;30(13):1613-1615. 22. Warburton D, Dallaire L, Thangavelu M, Ross L, Levin B, Kline J. Trisomy recurrence: a reconsideration based on North American data. Am J Hum Genet . 2004;75(3):376-385. 23. Andersen AM, Urhoj SK. Is advanced paternal age a health risk for the offspring? Fertil Steril . 2017;107(2):312-318. 24. Ramasamy R, Chiba K, Butler P, Lamb DJ. Male biological clock: a critical analysis of advanced paternal age. Fertil Steril . 2015;103(6):1402-1406. 25. Gadsbøll K, Vogel I, Pedersen LH, Kristensen SE, Steffensen EH, Wright A. Danish Cytogenetic Central Registry study group. Decoding 22q11.2: prenatal profiling and first-trimester risk assessment in Danish nationwide cohort. Ultrasound Obstet Gynecol . 2024;63(1):34-43. 26. Syngelaki A, Kotecha R, Pastides A, Wright A, Nicolaides KH. First-trimester biochemical markers of placentation in screening for gestational diabetes mellitus. Metabolism . 2015;64(11):1485-1489. 27. Gomez R, Hafez N, Amrani M, Schweiger S, Dewenter MK, Thomas P. Genetic findings in miscarriages and their relation to the number of previous miscarriages. Arch Gynecol Obstet . 2021;303(6):1425-1432. 28. Ozawa N, Ogawa K, Sasaki A, Mitsui M, Wada S, Sago H. Maternal age, history of miscarriage, and embryonic/fetal size are associated with cytogenetic results of spontaneous early miscarriages. J Assist Reprod Genet . 2019;36(4):749-757. 29. Ogasawara M, Aoki K, Okada S, Suzumori K. Embryonic karyotype of abortuses in relation to the number of previous miscarriages. Fertil Steril . 2000;73(2):300-304. 30. Pauta M, Martinez-Portilla RJ, Borrell A. Diagnostic yield of exome sequencing in fetuses with multisystem malformations: systematic review and meta-analysis. Ultrasound Obstet Gynecol . 2022;59(6):715-722. 31. Lord J, McMullan DJ, Eberhardt RY, Rinck G, Hamilton SJ, Quinlan-Jones E. Prenatal Assessment of Genomes and Exomes Consortium. Prenatal exome sequencing analysis in fetal structural anomalies detected by ultrasonography (PAGE): a cohort study. Lancet . 2019;393(10173):747-757. 32. Petrovski S, Aggarwal V, Giordano JL, Stosic M, Wou K, Bier L. Whole-exome sequencing in the evaluation of fetal structural anomalies: a prospective cohort study. Lancet . 2019;393(10173):758-767. 33. Dap M, Gicquel F, Lambert L, Perdriolle-Galet E, Bonnet C, Morel O. Utility of chromosomal microarray analysis for the exploration of isolated and severe fetal growth restriction diagnosed before 24 weeks’ gestation. Prenat Diagn . 2022;42(10):1281-1287. 34. Monier I, Receveur A, Houfflin-Debarge V, Goua V, Castagne V, Jouannic J-M. French Federation of Fetal Medicine Centers. Should prenatal chromosomal microarray analysis be offered for isolated fetal growth restriction? A French multicenter study. Am J Obstet Gynecol . 2021;225(6):676.e1-676.e15. 35. Mone F, Mellis R, Gabriel H, Baptiste C, Giordano J, Wapner R. Should we offer prenatal exome sequencing for intrauterine growth restriction or short long bones? A systematic review and meta-analysis. Am J Obstet Gynecol . 2023;228(4):409-417. 36. Fu F, Li R, Yu Q, Wang D, Deng Q, Li L. Application of exome sequencing for prenatal diagnosis of fetal structural anomalies: clinical experience and lessons learned from a cohort of 1618 fetuses. Genome Med . 2022;14(1):123. 37. Talati AN, Gilmore KL, Hardisty EE, Lyerly AD, Rini C, Vora NL. Impact of prenatal exome sequencing for fetal genetic diagnosis on maternal psychological outcomes and decisional conflict in a prospective cohort. Genet Med . 2021;23(4):713-719. 38. Zhu X, Gao Z, Wang Y, Huang W, Li Q, Jiao Z. Utility of trio-based prenatal exome sequencing incorporating splice-site and mitochondrial genome assessment in pregnancies with fetal ultrasound anomalies: prospective cohort study. Ultrasound Obstet Gynecol . 2022;60(6):780-792. 39. Vora NL, Gilmore K, Brandt A, Gustafson C, Strande N, Ramkisson L. An approach to integrating exome sequencing for fetal structural anomalies into clinical practice. Genet Med . 2020;22(5):954-961. Figure 1. Flowchart depicting participants’ inclusion. FGR, fetal growth restriction; IPD, invasive prenatal diagnosis; NIPT, ‌non-invasive prenatal testing; RSA, recurrent spontaneous abortion. Figure 2. Diagnostic yield and incremental detection rate. A. Karyotype yield. B. CMA incremental yield over karyotype. C. WES incremental yield over karyotype/CMA. CMA, chromosomal microarray analysis; FGR, fetal growth restriction; RSA, recurrent spontaneous abortion; WES, whole-exome sequencing. makecell, tabularx makecell, tabularx Figure 3. Factors associated with abnormal prenatal genetic results in recurrent spontaneous abortion: a Firth regression analysis. Analysis restricted to 14 +0 ~24 +6 weeks. Covariates and CMA/WES use were adjusted. * P < 0.05. FGR/abnormal fetal appendage subgroup excluded: all positives detected at ≥25 weeks; small, late sample precluded stable estimation. aOR, adjusted odds ratio; CMA, chromosomal microarray analysis; FGR, fetal growth restriction; RSA, recurrent spontaneous abortion; WES, whole-exome sequencing. Supporting information Figure S1. Receiver operating characteristic curve ‌AUC, area under the curve; CI, confidence interval; ROC , receiver operating characteristic. Supplementary Material File (table 1.docx) Download 20.21 KB Information & Authors Information Version history V1 Version 1 25 January 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords general obstetrics genetics risk management Authors Affiliations Siyao Ha Sun Yat-Sen Memorial Hospital Department of Obstetrics and Gynecology View all articles by this author Qi Xu 0000-0001-9437-3956 Sun Yat-Sen Memorial Hospital Department of Obstetrics and Gynecology View all articles by this author Shuai Fu Sun Yat-Sen Memorial Hospital View all articles by this author Liqiong Zhu Sun Yat-Sen Memorial Hospital Department of Obstetrics and Gynecology View all articles by this author Shangya Yuan Sun Yat-Sen Memorial Hospital Department of Obstetrics and Gynecology View all articles by this author Xiaohui Ji Sun Yat-Sen Memorial Hospital Department of Obstetrics and Gynecology View all articles by this author Na Di Sun Yat-Sen Memorial Hospital View all articles by this author Liyang Liang Sun Yat-Sen Memorial Hospital Department of Pediatrics View all articles by this author Tao Du Sun Yat-Sen Memorial Hospital View all articles by this author Hui Chen 0000-0002-3709-6494 [email protected] Sun Yat-Sen Memorial Hospital Department of Obstetrics and Gynecology View all articles by this author Metrics & Citations Metrics Article Usage 203 views 95 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Siyao Ha, Qi Xu, Shuai Fu, et al. 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