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Genetic estimators of DNA methylation provide insights into the molecular basis of polygenic traits.

ABSTRACT: The large biological distance between genetic risk loci and their mechanistic consequences in the tissue of interest limits the ability to establish functionality of susceptibility variants for genetically complex traits. Such a biological gap may be reduced through the systematic study of molecular mediators of genomic action, such as epigenetic modification. Here, we report the identification of robust genetic estimators of whole-blood CpG methylation, which can serve as intermediate molecular traits amenable to association testing with other genetically complex traits. We describe the relationship between these estimators and gene expression, demonstrate their genome-wide applicability to association testing even in the absence of individual genotypic data, and show that these estimators powerfully identify methylation-related genomic loci associated with polygenic traits and common diseases, such as schizophrenia. The use of genetic estimators for blood DNA methylation, which are made publically available, can serve as a valuable tool for the identification of epigenetic underpinnings of complex traits.

SUBMITTER: Freytag V

PROVIDER: S-EPMC5802460 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Genetic estimators of DNA methylation provide insights into the molecular basis of polygenic traits.

Freytag Virginie V Vukojevic Vanja V Wagner-Thelen Holger H Milnik Annette A Vogler Christian C Leber Markus M Weinhold Leonie L Böhmer Anne C AC Riedel-Heller Steffi S Maier Wolfgang W de Quervain Dominique J-F DJ Ramirez Alfredo A Papassotiropoulos Andreas A

Translational psychiatry 20180131 1

The large biological distance between genetic risk loci and their mechanistic consequences in the tissue of interest limits the ability to establish functionality of susceptibility variants for genetically complex traits. Such a biological gap may be reduced through the systematic study of molecular mediators of genomic action, such as epigenetic modification. Here, we report the identification of robust genetic estimators of whole-blood CpG methylation, which can serve as intermediate molecular ...[more]

PMID: 29382824

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Project description:We examined the performance of methylation scores (MS) and polygenic scores (PGS) for birth weight, BMI, prenatal maternal smoking exposure, and smoking status to assess the extent to which MS could predict these traits and exposures over and above the PGS in a multi-omics prediction model. MS may be seen as the epigenetic equivalent of PGS, but because of their dynamic nature and sensitivity of non-genetic exposures may add to complex trait prediction independently of PGS. MS and PGS were calculated based on genotype data and DNA-methylation data in blood samples from adults (Illumina 450 K; N = 2,431; mean age 35.6) and in buccal samples from children (Illumina EPIC; N = 1,128; mean age 9.6) from the Netherlands Twin Register. Weights to construct the scores were obtained from results of large epigenome-wide association studies (EWASs) based on whole blood or cord blood methylation data and genome-wide association studies (GWASs). In adults, MSs in blood predicted independently from PGSs, and outperformed PGSs for BMI, prenatal maternal smoking, and smoking status, but not for birth weight. The largest amount of variance explained by the multi-omics prediction model was for current vs. never smoking (54.6%) of which 54.4% was captured by the MS. The two predictors captured 16% of former vs. never smoking initiation variance (MS:15.5%, PGS: 0.5%), 17.7% of prenatal maternal smoking variance (MS:16.9%, PGS: 0.8%), 11.9% of BMI variance (MS: 6.4%, PGS 5.5%), and 1.9% of birth weight variance (MS: 0.4%, PGS: 1.5%). In children, MSs in buccal samples did not show independent predictive value. The largest amount of variance explained by the two predictors was for prenatal maternal smoking (2.6%), where the MSs contributed 1.5%. These results demonstrate that blood DNA MS in adults explain substantial variance in current smoking, large variance in former smoking, prenatal smoking, and BMI, but not in birth weight. Buccal cell DNA methylation scores have lower predictive value, which could be due to different tissues in the EWAS discovery studies and target sample, as well as to different ages. This study illustrates the value of combining polygenic scores with information from methylation data for complex traits and exposure prediction.

Dataset Information

Genetic estimators of DNA methylation provide insights into the molecular basis of polygenic traits.

Publications

Genetic estimators of DNA methylation provide insights into the molecular basis of polygenic traits.

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