Chen Lyu1,2, Manyan Huang1, Nianjun Liu1, Zhongxue Chen1, Philip J Lupo3, Benjamin Tycko4, John S Witte5,6, Charlotte A Hobbs7, Ming Li1. 1. Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, IN. 2. Department of Population Health, New York University Grossman School of Medicine, New York, NY. 3. Department of Pediatrics, Baylor College of Medicine, Houston, TX. 4. Center for Discovery and Innovation, Nutley, NJ. 5. Department of Epidemiology and Population Health, Stanford University, Stanford, CA. 6. Department of Biomedical Data Sciences, Stanford University, Stanford, CA. 7. Rady Children's Institute for Genomic Medicine, San Diego, CA.
Abstract
MOTIVATION: CpG sites within the same genomic region often share similar methylation patterns and tend to be co-regulated by multiple genetic variants that may interact with one another. RESULTS: We propose a multi-trait methylation random field (multi-MRF) method to evaluate the joint association between a set of CpG sites and a set of genetic variants. The proposed method has several advantages. First, it is a multi-trait method that allows flexible correlation structures between neighboring CpG sites (e.g., distance-based correlation). Second, it is also a multi-locus method that integrates the effect of multiple common and rare genetic variants. Third, it models the methylation traits with a beta distribution to characterize their bimodal and interval properties. Through simulations, we demonstrated that the proposed method had improved power over some existing methods under various disease scenarios. We further illustrated the proposed method via an application to a study of congenital heart defects (CHD) with 83 cardiac tissue samples. Our results suggested that gene BACE2, a mQTL candidate, colocalized with expression QTLs in artery tibial and harbored genetic variants with nominal significant associations in two genome-wide association studies of CHD. AVAILABILITY: https://github.com/chenlyu2656/Multi-MRF. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: CpG sites within the same genomic region often share similar methylation patterns and tend to be co-regulated by multiple genetic variants that may interact with one another. RESULTS: We propose a multi-trait methylation random field (multi-MRF) method to evaluate the joint association between a set of CpG sites and a set of genetic variants. The proposed method has several advantages. First, it is a multi-trait method that allows flexible correlation structures between neighboring CpG sites (e.g., distance-based correlation). Second, it is also a multi-locus method that integrates the effect of multiple common and rare genetic variants. Third, it models the methylation traits with a beta distribution to characterize their bimodal and interval properties. Through simulations, we demonstrated that the proposed method had improved power over some existing methods under various disease scenarios. We further illustrated the proposed method via an application to a study of congenital heart defects (CHD) with 83 cardiac tissue samples. Our results suggested that gene BACE2, a mQTL candidate, colocalized with expression QTLs in artery tibial and harbored genetic variants with nominal significant associations in two genome-wide association studies of CHD. AVAILABILITY: https://github.com/chenlyu2656/Multi-MRF. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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