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Defining the impact of maternal cell contamination on the interpretation of prenatal microarray analysis.
MedLine Citation:
PMID:  22766610     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Purpose:To understand the ability of microarray-based comparative genomic hybridization to detect copy-number variation in the presence of maternal cell contamination.Methods:To simulate maternal cell contamination, normal female DNA was mixed at various levels with DNA carrying known copy-number variations. Mixtures were run on a whole-genome 135K oligonucleotide-based array. Data were analyzed with custom analysis software.Results:The array and software design allowed detection of larger copy-number variations at higher levels of maternal cell contamination than smaller copy-number variations. The smallest duplications and deletions were obscured at 22-31% and 55-58% maternal cell contamination, respectively. With male fetal samples, the sex chromosome ratios started showing observable shifts at ~10% maternal cell contamination.Conclusion:As knowledge of the maternal cell contamination level aids in interpretation of array results, we recommend concurrent, independent maternal cell contamination studies for all fetal samples for accurate and timely results. With male fetal samples in our laboratory, interfering levels of maternal cell contamination can be excluded when the sex chromosome plots appear normal. Thus, reportable male microarray-based comparative genomic hybridization results may be occasionally achieved without maternal cell contamination studies. Because the effects of maternal cell contamination on microarray results are dependent on array platforms, experimental techniques, and software algorithms, each laboratory should perform its own analysis to determine acceptable levels of maternal cell contamination for its assays.Genet Med advance online publication 5 July 2012.
Authors:
Allen N Lamb; Jill A Rosenfeld; Justine Coppinger; Erin T Dodge; Mindy Preston Dabell; Beth S Torchia; J Britt Ravnan; Lisa G Shaffer; Blake C Ballif
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-7-05
Journal Detail:
Title:  Genetics in medicine : official journal of the American College of Medical Genetics     Volume:  -     ISSN:  1530-0366     ISO Abbreviation:  -     Publication Date:  2012 Jul 
Date Detail:
Created Date:  2012-7-6     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9815831     Medline TA:  Genet Med     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
1] Signature Genomic Laboratories, PerkinElmer, Inc., Spokane, Washington, USA [2] Present address: ARUP Laboratories, University of Utah, Salt Lake City, Utah, USA.
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