Karyotype versus Microarray Testing for Genetic Abnormalities after Stillbirth

University of Texas Medical Branch at Galveston, Galveston (G.R.S., R.B.)
New England Journal of Medicine (Impact Factor: 55.87). 12/2012; 367(23):2185-2193. DOI: 10.1056/NEJMoa1201569
Source: PubMed


Genetic abnormalities have been associated with 6 to 13% of stillbirths, but the true prevalence may be higher. Unlike karyotype analysis, microarray analysis does not require live cells, and it detects small deletions and duplications called copy-number variants.

The Stillbirth Collaborative Research Network conducted a population-based study of stillbirth in five geographic catchment areas. Standardized postmortem examinations and karyotype analyses were performed. A single-nucleotide polymorphism array was used to detect copy-number variants of at least 500 kb in placental or fetal tissue. Variants that were not identified in any of three databases of apparently unaffected persons were then classified into three groups: probably benign, clinical significance unknown, or pathogenic. We compared the results of karyotype and microarray analyses of samples obtained after delivery.

In our analysis of samples from 532 stillbirths, microarray analysis yielded results more often than did karyotype analysis (87.4% vs. 70.5%, P<0.001) and provided better detection of genetic abnormalities (aneuploidy or pathogenic copy-number variants, 8.3% vs. 5.8%; P=0.007). Microarray analysis also identified more genetic abnormalities among 443 antepartum stillbirths (8.8% vs. 6.5%, P=0.02) and 67 stillbirths with congenital anomalies (29.9% vs. 19.4%, P=0.008). As compared with karyotype analysis, microarray analysis provided a relative increase in the diagnosis of genetic abnormalities of 41.9% in all stillbirths, 34.5% in antepartum stillbirths, and 53.8% in stillbirths with anomalies.

Microarray analysis is more likely than karyotype analysis to provide a genetic diagnosis, primarily because of its success with nonviable tissue, and is especially valuable in analyses of stillbirths with congenital anomalies or in cases in which karyotype results cannot be obtained. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development.).

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Available from: Ronald Wapner, Dec 27, 2013
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    • "Therefore, facile and accurate identification of such breakpoints is urgently required for clinicians and researchers so that more informed treatment strategies can be formulated. Conventional karyotyping, the gold standard for BCA detection, has limitations for detecting BCA accurately owing to: (1) insufficient resolution (range: 3–10 Mb) to unequivocally identify the disrupted gene, and (2) the stringent requirements for sampling cell cultures and the time-consuming nature of this technique [Lathi and Milki, 2002; Manning and Hudgins, 2010; Harris et al., 2011; Reddy et al., 2012; Wapner et al., 2012; Evangelidou et al., 2013]. Although new methods such as fluorescence in situ hybridization (FISH) and array-based comparative genomic hybridization have been used to detect BCA-associated breakpoints in conjunction with karyotyping and other cytogenetic techniques (i.e., chromosome sorting), they are laborious and also unable to achieve single base pair resolution [Veltman et al., 2003; Chen et al., 2010]. "
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    ABSTRACT: Balanced chromosomal rearrangement (or balanced chromosome abnormality, BCA) is a common chromosomal structural variation. Next-generation sequencing has been reported to detect BCA-associated breakpoints with the aid of karyotyping. However, the complications associated with this approach and the requirement for cytogenetics information has limited its application. Here, we provide a whole-genome low-coverage sequencing approach to detect BCA events independent of knowing the affected regions and with low false positives. First, six samples containing BCAs were used to establish a detection protocol and assess the efficacy of different library construction approaches. By clustering anomalous read pairs and filtering out the false-positive results with a control cohort and the concomitant mapping information, we could directly detect BCA events for each sample. Through optimizing the read depth, BCAs in all samples could be blindly detected with only 120 million read pairs per sample for data from a small-insert library and 30 million per sample for data from non-size-selected mate-pair library. This approach was further validated using another 13 samples that contained BCAs. Our approach advances the application of high-throughput whole-genome low-coverage analysis for robust BCA detection—especially for clinical samples—without the need for karyotyping. This article is protected by copyright. All rights reserved
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    • "Statistical evaluation was performed using STATA v12.1 (College Station, TX). It was determined a priori that to detect a 60% success rate in rescue karyotyping in our sample compared to the reported values of 85% or greater in the largest studies [24,25], with α = 0.05 and 80% power, at least 20 specimens were needed. Descriptive statistics were computed, and are presented as mean ± SD for normally-distributed and median [inter-quartile range (IQR)] for non-normally-distributed continuous data; categorical data are presented as n (%). "
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    • "Implementation of microarrays in clinical practice enabled to improve the diagnostic yield up to 10– 25% in this patient group compared with 5–6% detected previously by karyotyping and subtelomeric FISH. In the context of prenatal diagnostic testing, CMA provided better detection of genetic abnormalities and identified additional , clinically significant cytogenetic information as compared with karyotyping and was equally efficacious in identifying aneuploidies and unbalanced rearrangements, but did not identify balanced translocations and triploidies (Reddy et al. 2012; Wapner et al. 2012). Therefore, currently CMA is recommended as the first-tier diagnostic test for patients with DD/ID, ASD, and/or MCA (Miller et al. 2010). "
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