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Novel DNA methylation marker discovery by assumption-free genome-wide association analysis of cognitive function in twins.

ABSTRACT: Privileged by rapid increase in available epigenomic data, epigenome-wide association studies (EWAS) are to make a profound contribution to understand the molecular mechanism of DNA methylation in cognitive aging. Current statistical methods used in EWAS are dominated by models based on multiple assumptions, for example, linear relationship between molecular profiles and phenotype, normal distribution for the methylation data and phenotype. In this study, we applied an assumption-free method, the generalized correlation coefficient (GCC), and compare it to linear models, namely the linear mixed model and kinship model. We use DNA methylation associated with a cognitive score in 400 and 206 twins as discovery and replication samples respectively. DNA methylation associated with cognitive function using GCC, linear mixed model, and kinship model, identified 65 CpGs (p < 1e-04) from discovery sample displaying both nonlinear and linear correlations. Replication analysis successfully replicated 9 of these top CpGs. When combining results of GCC and linear models to cover diverse patterns of relationships, we identified genes like KLHDC4, PAPSS2, and MRPS18B as well as pathways including focal adhesion, axon guidance, and some neurological signaling. Genomic region-based analysis found 15 methylated regions harboring 11 genes, with three verified in gene expression analysis, also the 11 genes were related to top functional clusters including neurohypophyseal hormone and maternal aggressive behaviors. The GCC approach detects valuable methylation sites missed by traditional linear models. A combination of methylation markers from GCC and linear models enriched biological pathways sensible in neurological function that could implicate cognitive performance and cognitive aging.

SUBMITTER: Mohammadnejad A

PROVIDER: S-EPMC7884045 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Novel DNA methylation marker discovery by assumption-free genome-wide association analysis of cognitive function in twins.

Mohammadnejad Afsaneh A Soerensen Mette M Baumbach Jan J Mengel-From Jonas J Li Weilong W Lund Jesper J Li Shuxia S Christiansen Lene L Christensen Kaare K Hjelmborg Jacob V B JVB Tan Qihua Q

Aging cell 20210202 2

Privileged by rapid increase in available epigenomic data, epigenome-wide association studies (EWAS) are to make a profound contribution to understand the molecular mechanism of DNA methylation in cognitive aging. Current statistical methods used in EWAS are dominated by models based on multiple assumptions, for example, linear relationship between molecular profiles and phenotype, normal distribution for the methylation data and phenotype. In this study, we applied an assumption-free method, th ...[more]

PMID: 33528912

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Project description:BackgroundHypertension is a crucial risk factor for developing cardiovascular disease and reducing life expectancy. We aimed to detect DNA methylation (DNAm) variants potentially related to systolic blood pressure (SBP) and diastolic blood pressure (DBP) by conducting epigenome-wide association studies in 60 and 59 Chinese monozygotic twin pairs, respectively.MethodsGenome-wide DNA methylation profiling in whole blood of twins was performed using Reduced Representation Bisulfite Sequencing, yielding 551,447 raw CpGs. Association between DNAm of single CpG and blood pressure was tested by applying generalized estimation equation. Differentially methylated regions (DMRs) were identified by comb-P approach. Inference about Causation through Examination of Familial Confounding was utilized to perform the causal inference. Ontology enrichment analysis was performed using Genomic Regions Enrichment of Annotations Tool. Candidate CpGs were quantified using Sequenom MassARRAY platform in a community population. Weighted gene co-expression network analysis (WGCNA) was conducted using gene expression data.ResultsThe median age of twins was 52 years (95% range 40, 66). For SBP, 31 top CpGs (p < 1 × 10-4) and 8 DMRs were identified, with several DMRs within NFATC1, CADM2, IRX1, COL5A1, and LRAT. For DBP, 43 top CpGs (p < 1 × 10-4) and 12 DMRs were identified, with several DMRs within WNT3A, CNOT10, and DAB2IP. Important pathways, such as Notch signaling pathway, p53 pathway by glucose deprivation, and Wnt signaling pathway, were significantly enriched for SBP and DBP. Causal inference analysis suggested that DNAm at top CpGs within NDE1, MYH11, SRRM1P2, and SMPD4 influenced SBP, while SBP influenced DNAm at CpGs within TNK2. DNAm at top CpGs within WNT3A influenced DBP, while DBP influenced DNAm at CpGs within GNA14. Three CpGs mapped to WNT3A and one CpG mapped to COL5A1 were validated in a community population, with a hypermethylated and hypomethylated direction in hypertension cases, respectively. Gene expression analysis by WGCNA further identified some common genes and enrichment terms.ConclusionWe detect many DNAm variants that may be associated with blood pressure in whole blood, particularly the loci within WNT3A and COL5A1. Our findings provide new clues to the epigenetic modification underlying hypertension pathogenesis.

Dataset Information

Novel DNA methylation marker discovery by assumption-free genome-wide association analysis of cognitive function in twins.

Publications

Novel DNA methylation marker discovery by assumption-free genome-wide association analysis of cognitive function in twins.

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