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

Autor: Natasa Dzidic, Craig A. Dise, Mary K. Travis, Trilochan Sahoo, Charles Doherty, Sara Commander, Carlos W. Benito, Michelle N. Strecker, Karine Hovanes, R. Weslie Tyson, Mandolin S. Ziadie, Arturo E. Mendoza, Mary D. Stephenson
Rok vydání: 2015
Předmět:
Zdroj: Genetics in medicine : official journal of the American College of Medical Genetics. 19(1)
ISSN: 1530-0366
Popis: 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). 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). 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. 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.
Databáze: OpenAIRE