Gene methylation co-regulation network analysis of all-cause mortaltiy in ageing individuals

Jesper Lund, Jan Baumbach, Qihua Tan

Research output: Contribution to conference without publisher/journalPosterResearchpeer-review


Mortality is a hot topic within genetics and epidemiology and is especially a focus in older population studies. While remaining blurry, today's technologies enable us to explore much of these uncharted lands of mortality in greater detail and find causes of mortality through means of epigenetics e.g. histone modifications or methylation-based data. In this study, we explore methylation data and aims to find mortality associated gene-clusters to help shed light on mortality in the older populations. Based on large-scale mortality data on the Lothian birth cohorts of older people (LBC1921, LBC1936, N=1,425), we summarized DNA methylation levels at the promoter regions (TSS200, 1stExon, TSS1500) collected using Illumina 450K bead chip arrays. We then perform weighted-gene methylation correlation network analysis, in order to elucidate gene-clusters with significant mortality association, utilizing Cox proportional hazards models and the clusterProfiler R-package. By analysis of gene promoter methylation levels, 27 gene-modules were discovered whereof 19 significant gene-modules (p < 0.05, p = 0.00014 to 0.044) were identified through means of their eigengene (first principal component) with respect to mortality. The overall module significance found using Kruskal Wallis Test reported a P-value of 3.5E-282. Using the top genes ranked by Cox models, with criterion p < 0.05 (N=3,535), we filtered modules based on intramodular connectivity
Original languageEnglish
Publication date16. Oct 2018
Publication statusPublished - 16. Oct 2018
EventAmerican Society of Human Genetics 2018 - San Diego Convention Center in San Diego, California, San Diego, United States
Duration: 16. Oct 201820. Oct 2018
Conference number: 2018


ConferenceAmerican Society of Human Genetics 2018
LocationSan Diego Convention Center in San Diego, California
Country/TerritoryUnited States
CitySan Diego
Internet address


  • Epigenetics
  • Weighted Gene Correlation Network Analysis
  • Genetics
  • Gene experssion
  • Methylation


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