The genomic basis of sporadic and recurrent pregnancy loss: a comprehensive in-depth analysis of 24,900 miscarriages.

RESEARCH QUESTION: What is the genetic cause of sporadic and recurrent pregnancy loss and does the frequency and nature of chromosomal abnormalities play a role? Types and frequency of all identifiable chromosomal abnormalities were determined to inform our understanding, medical management and recurrence risk for patients experiencing pregnancy loss. DESIGN: Genome-wide single-nucleotide polymorphism-based chromosomal microarray (SNP-CMA) were used to evaluate 24,900 products of conception samples from various forms of pregnancy losses. RESULTS: Sporadic miscarriage (64.7%) or recurrent pregnancy loss (RPL) (22%) were the most common referrals. Clinically significant abnormalities were observed in 55.8% (13,910) of samples, variants of uncertain significance in 1.8%, and normal results in 42.4%. In addition to autosomal trisomies (in 36% of samples), polyploidy and large segmental imbalances were identified in 7.8% and 2.8% of samples, respectively. Analysis of sequential samples from 1103 patients who had experienced RPL provided important insight into possible predispositions to RPL. CONCLUSIONS: This expansive chromosomal microarray analyses of pregnancy loss samples illuminates our understanding of the full spectrum, relative frequencies and the role of genomic abnormalities in pregnancy loss. The empiric observations described here provide useful insight for clinicians and highlight the importance of high-resolution genomic testing for comprehensive evaluation and risk assessment of individuals experiencing pregnancy loss.

Copy-number variants in clinical genome sequencing: deployment and interpretation for rare and undiagnosed disease.

PURPOSE: Current diagnostic testing for genetic disorders involves serial use of specialized assays spanning multiple technologies. In principle, genome sequencing (GS) can detect all genomic pathogenic variant types on a single platform. Here we evaluate copy-number variant (CNV) calling as part of a clinically accredited GS test. METHODS: We performed analytical validation of CNV calling on 17 reference samples, compared the sensitivity of GS-based variants with those from a clinical microarray, and set a bound on precision using orthogonal technologies. We developed a protocol for family-based analysis of GS-based CNV calls, and deployed this across a clinical cohort of 79 rare and undiagnosed cases. RESULTS: We found that CNV calls from GS are at least as sensitive as those from microarrays, while only creating a modest increase in the number of variants interpreted (~10 CNVs per case). We identified clinically significant CNVs in 15% of the first 79 cases analyzed, all of which were confirmed by an orthogonal approach. The pipeline also enabled discovery of a uniparental disomy (UPD) and a 50% mosaic trisomy 14. Directed analysis of select CNVs enabled breakpoint level resolution of genomic rearrangements and phasing of de novo CNVs. CONCLUSION: Robust identification of CNVs by GS is possible within a clinical testing environment.

ACOG and SMFM guidelines for prenatal diagnosis: Is karyotyping really sufficient?

OBJECTIVE: The American College of Obstetricians and Gynecologists (ACOG) and Society for Maternal-Fetal Medicine (SMFM) recommend chromosomal microarray analysis (CMA) for prenatal diagnosis in cases with 1 or more fetal structural abnormalities. For patients who elect prenatal diagnosis and have a structurally normal fetus, either microarray or karyotype is recommended. This study evaluates the frequency of clinically significant chromosomal abnormalities (CSCA) that would have been missed if all patients offered the choice between CMA and karyotyping chose karyotyping. METHODS: A total of 3223 prenatal samples undergoing CMA were evaluated. Cases were categorized into 2 groups: those that met ACOG guidelines for CMA versus those that met ACOG guidelines for either CMA or karyotype. RESULTS: Of the 3223 cases, 1475 (45.8%) met ACOG recommendations for CMA, and 1748 (54.2%) met recommendations for either CMA or karyotype. In patients who could have elected either CMA or karyotype, 2.5% had CSCA that would have been missed if the patient had elected to pursue karyotype. CONCLUSION: This study suggests that 2.5% of patients will have a CSCA that may be missed if the guidelines continue to suggest that CMA and karyotyping have equivalent diagnostic value for patients without a fetal structural abnormality.

Comprehensive genetic analysis of pregnancy loss by chromosomal microarrays: outcomes, benefits, and challenges.

PURPOSE: Chromosomal microarray analysis (CMA) is currently considered first-tier testing in pediatric care and prenatal diagnosis owing to its high diagnostic sensitivity for chromosomal imbalances. The aim of this study was to determine the efficacy and diagnostic power of CMA in both fresh and formalin-fixed paraffin-embedded (FFPE) samples of products of conception (POCs). METHODS: Over a 44-month period, 8,118 consecutive samples were received by our laboratory for CMA analysis. This included both fresh (76.4%) and FFPE samples (22.4%), most of which were ascertained for recurrent pregnancy loss and/or spontaneous abortion (83%). The majority of samples were evaluated by a whole-genome single-nucleotide polymorphism (SNP)-based array (81.6%); the remaining samples were evaluated by array-comparative genomic hybridization (CGH). RESULTS: A successful result was obtained in 7,396 of 8,118 (91.1%), with 92.4% of fresh tissue samples and 86.4% of FFPE samples successfully analyzed. Clinically significant abnormalities were identified in 53.7% of specimens (3,975 of 7,396), 94% of which were considered causative. CONCLUSION: Analysis of POC specimens by karyotyping fails in 20-40% of cases. SNP-based CMA is a robust platform, with successful results obtained in >90% of cases. SNP-based CMA can identify aneuploidy, polyploidy, whole-genome homozygosity, segmental genomic imbalances, and maternal cell contamination, thus maximizing sensitivity and decreasing false-negative results. Understanding the etiology of fetal loss enables clarification of recurrence risk and assists in determining appropriate management for future family planning.Genet Med 19 1, 83-89.