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65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), Meeting of the Central European Network (CEN: German Region, Austro-Swiss Region and Polish Region) of the International Biometric Society (IBS)

06.09. - 09.09.2020, Berlin (online conference)

Polygenic Risk Score Approaches for Methylation Data in Multi-Ethnic Populations

Meeting Abstract

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  • Anke Huels - Rollins School of Public Health, Emory University, Atlanta, United States

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), Meeting of the Central European Network (CEN: German Region, Austro-Swiss Region and Polish Region) of the International Biometric Society (IBS). Berlin, 06.-09.09.2020. Düsseldorf: German Medical Science GMS Publishing House; 2021. DocAbstr. 317

doi: 10.3205/20gmds372, urn:nbn:de:0183-20gmds3727

Published: February 26, 2021

© 2021 Huels.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at http://creativecommons.org/licenses/by/4.0/.


Outline

Text

Polygenic approaches often access more variance of complex traits than is possible by single variant approaches. For genotype data, polygenic risk scores (PRS) are widely used for risk prediction as well as in association and interaction studies. Recently, interest has been growing in transferring PRS approaches to DNA methylation data (methylation risk scores, MRS), which can be used 1) as biomarkers for environmental exposures, 2) in association analyses in which single CpG sites do not achieve significance, 3) as dimension reduction approach in interaction and mediation analyses and 4) to predict individual risks of disease or treatment success. One of the biggest challenges for PRS is its limited applicability across ancestries. We adopted the popular PRS pruning and thresholding approach to methylation data and evaluated its applicability across ancestries by using publicly available data from 1199 samples with African, European and Indian ancestry. First, we used the Co-Methylation with genomic CpG Background (CoMeBack) method to define Co-methylated Regions (CMRs), spanning sets of array probes constructed based on all genomic CpG sites (similar to “LD clusters” in genotype data). Next, we selected one CpG site from each CMR based on its association with the trait of interest in an independent reference dataset (p-value below specific threshold, “pruning and thresholding”). Finally, we calculated a methylation risk score for each sample as a sum of the remaining beta values weighted by the corresponding beta estimates from the independent summary statistics. In contrast to PRS, our preliminary findings suggest that the derived MRS are comparable across different ancestries, which indicates their broad applicability even for ethnically heterogeneous study populations. Finally, we will apply this approach in the multi-ethnic Drakenstein Child Health Study to better understand the biological mechanisms behind the association between prenatal air pollution exposure and infant lung function.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.