14
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

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

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          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).

          Related collections

          Most cited references28

          • Record: found
          • Abstract: found
          • Article: not found

          Genetics of early miscarriage.

          A miscarriage is the most frequent complication of a pregnancy. Poor chromosome preparations, culture failure, or maternal cell contamination may hamper conventional karyotyping. Techniques such as chromosomal comparative genomic hybridization (chromosomal-CGH), array-comparative genomic hybridization (array-CGH), fluorescence in situ hybridization (FISH), multiplex ligation-dependent probe amplification (MLPA) and quantitative fluorescent polymerase chain reaction (QF-PCR) enable us to trace submicroscopic abnormalities. We found the prevalence of chromosome abnormalities in women facing a single sporadic miscarriage to be 45% (95% CI: 38-52; 13 studies, 7012 samples). The prevalence of chromosome abnormalities in women experiencing a subsequent miscarriage after preceding recurrent miscarriage proved to be comparable: 39% (95% CI: 29-50; 6 studies 1359 samples). More chromosome abnormalities are detected by conventional karyotyping compared to FISH or MLPA only (chromosome region specific techniques), and the same amount of abnormalities compared to QF-PCR (chromosome region specific techniques) and chromosomal-CGH and array-CGH (whole genome techniques) only. Molecular techniques could play a role as an additional technique when culture failure or maternal contamination occurs: recent studies show that by using array-CGH, an additional 5% of submicroscopic chromosome variants can be detected. Because of the small sample size as well as the unknown clinical relevance of these molecular aberrations, more and larger studies should be performed of submicroscopic chromosome abnormalities among sporadic miscarriage samples. For recurrent miscarriage samples molecular technique studies are relatively new. It has often been suggested that miscarriages are due to chromosomal abnormalities in more than 50%, but the present review has determined that chromosomal and submicroscopic genetic abnormalities on average are prevalent in maximally half of the miscarriage samples. This article is part of a Special Issue entitled: Molecular Genetics of Human Reproductive Failure. Copyright © 2012 Elsevier B.V. All rights reserved.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Genomic imbalance in products of conception: single-nucleotide polymorphism chromosomal microarray analysis.

            To report the full cohort of identifiable anomalies, regardless of known clinical significance, in a large-scale cohort of postmiscarriage products-of-conception samples analyzed using a high-resolution single-nucleotide polymorphism (SNP)-based microarray platform. High-resolution chromosomal microarray analysis allows for the identification of visible and submicroscopic cytogenomic imbalances; the specific use of SNPs permits detection of maternal cell contamination, triploidy, and uniparental disomy. Miscarriage specimens were sent to a single laboratory for cytogenomic analysis. Chromosomal microarray analysis was performed using a SNP-based genotyping microarray platform. Results were evaluated at the cytogenetic and microscopic (greater than 10 Mb) and submicroscopic (less than 10 Mb) levels. Maternal cell contamination was assessed using information derived from fetal and maternal SNPs. Results were obtained on 2,389 of 2,392 specimens (99.9%) that were less than 20 weeks of gestation. Maternal cell contamination was identified in 528 (22.0%) specimens. The remaining 1,861 specimens were considered to be of true fetal origin. Of these, 1,106 (59.4%) showed classical cytogenetic abnormalities: aneuploidy accounted for 945 (85.4%), triploidy for 114 (10.3%), and structural anomalies or tetraploidy for the remaining 47 (4.2%). Of the 755 (40.6%) cases considered normal at the cytogenetic level, SNP chromosomal microarray analysis revealed a clinically significant copy number change or whole-genome uniparental disomy in 12 (1.6%) and three (0.4%) cases, respectively. Chromosomal microarray analysis of products-of-conception specimens yields a high diagnostic return. Using SNPs extends the scope of detectable genomic abnormalities and facilitates reporting "true" fetal results. This supports the use of SNP chromosomal microarray analysis for cytogenomic evaluation of miscarriage specimens when clinically indicated. III.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Karyotype versus microarray testing for genetic abnormalities after stillbirth.

              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.).
                Bookmark

                Author and article information

                Journal
                Genetics in Medicine
                Genet Med
                Springer Science and Business Media LLC
                1098-3600
                1530-0366
                January 2017
                June 23 2016
                January 2017
                : 19
                : 1
                : 83-89
                Article
                10.1038/gim.2016.69
                27337029
                e09d306b-e921-4dd9-9568-d1b39e2c1933
                © 2017

                http://www.springer.com/tdm

                History

                Comments

                Comment on this article