» Articles » PMID: 28770015

Maternal Blood Contamination of Collected Cord Blood Can Be Identified Using DNA Methylation at Three CpGs

Overview
Publisher Biomed Central
Specialty Genetics
Date 2017 Aug 4
PMID 28770015
Citations 29
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Cord blood is a commonly used tissue in environmental, genetic, and epigenetic population studies due to its ready availability and potential to inform on a sensitive period of human development. However, the introduction of maternal blood during labor or cross-contamination during sample collection may complicate downstream analyses. After discovering maternal contamination of cord blood in a cohort study of 150 neonates using Illumina 450K DNA methylation (DNAm) data, we used a combination of linear regression and random forest machine learning to create a DNAm-based screening method. We identified a panel of DNAm sites that could discriminate between contaminated and non-contaminated samples, then designed pyrosequencing assays to pre-screen DNA prior to being assayed on an array.

Results: Maternal contamination of cord blood was initially identified by unusual X chromosome DNA methylation patterns in 17 males. We utilized our DNAm panel to detect contaminated male samples and a proportional amount of female samples in the same cohort. We validated our DNAm screening method on an additional 189 sample cohort using both pyrosequencing and DNAm arrays, as well as 9 publically available cord blood 450K data sets. The rate of contamination varied from 0 to 10% within these studies, likely related to collection specific methods.

Conclusions: Maternal blood can contaminate cord blood during sample collection at appreciable levels across multiple studies. We have identified a panel of markers that can be used to identify this contamination, either post hoc after DNAm arrays have been completed, or in advance using a targeted technique like pyrosequencing.

Citing Articles

Cesarean delivery and blood DNA methylation at birth and childhood: Meta-analysis in the Pregnancy and Childhood Epigenetics Consortium.

Wang S, Casey E, Sordillo J, Aguilar-Lacasana S, Morales Berstein F, Biedrzycki R Sci Adv. 2024; 10(48):eadr2084.

PMID: 39602535 PMC: 11601205. DOI: 10.1126/sciadv.adr2084.


Cord blood lipid correlation network profiles are associated with subsequent attention-deficit/hyperactivity disorder and autism spectrum disorder symptoms at 2 years: a prospective birth cohort study.

Vacy K, Thomson S, Moore A, Eisner A, Tanner S, Pham C EBioMedicine. 2024; 100:104949.

PMID: 38199043 PMC: 10825361. DOI: 10.1016/j.ebiom.2023.104949.


The Application Value of Combined Detection of Serum IL-6, LDH, S100, NSE, and GFAP in the Early Diagnosis of Brain Damage Caused by Neonatal Asphyxia.

Liu B, Lan H, Gao N, Hu G Iran J Public Health. 2023; 52(11):2363-2371.

PMID: 38106843 PMC: 10719696. DOI: 10.18502/ijph.v52i11.14036.


Examination of newborn DNA methylation among women with polycystic ovary syndrome/hirsutism.

Polinski K, Robinson S, Putnick D, Sundaram R, Bell E, Joseph P Epigenetics. 2023; 18(1):2282319.

PMID: 37992405 PMC: 10732621. DOI: 10.1080/15592294.2023.2282319.


DNA Methylation Biomarkers for Young Children with Idiopathic Autism Spectrum Disorder: A Systematic Review.

Stoccoro A, Conti E, Scaffei E, Calderoni S, Coppede F, Migliore L Int J Mol Sci. 2023; 24(11).

PMID: 37298088 PMC: 10252672. DOI: 10.3390/ijms24119138.


References
1.
Girchenko P, Lahti M, Tuovinen S, Savolainen K, Lahti J, Binder E . Cohort Profile: Prediction and prevention of preeclampsia and intrauterine growth restriction (PREDO) study. Int J Epidemiol. 2016; 46(5):1380-1381g. DOI: 10.1093/ije/dyw154. View

2.
Kupers L, Xu X, Jankipersadsing S, Vaez A, la Bastide-van Gemert S, Scholtens S . DNA methylation mediates the effect of maternal smoking during pregnancy on birthweight of the offspring. Int J Epidemiol. 2015; 44(4):1224-37. PMC: 4588868. DOI: 10.1093/ije/dyv048. View

3.
Clifford R, Jones M, MacIsaac J, McEwen L, Goodman S, Mostafavi S . Inhalation of diesel exhaust and allergen alters human bronchial epithelium DNA methylation. J Allergy Clin Immunol. 2016; 139(1):112-121. DOI: 10.1016/j.jaci.2016.03.046. View

4.
Teschendorff A, Zhuang J, Widschwendter M . Independent surrogate variable analysis to deconvolve confounding factors in large-scale microarray profiling studies. Bioinformatics. 2011; 27(11):1496-505. DOI: 10.1093/bioinformatics/btr171. View

5.
Maksimovic J, Gordon L, Oshlack A . SWAN: Subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips. Genome Biol. 2012; 13(6):R44. PMC: 3446316. DOI: 10.1186/gb-2012-13-6-r44. View