medRxivGenetic & Genomic MedicinePreprint
Blood-based epigenome-wide analyses on the prevalence and incidence of nineteen common disease states
Robert Francis HillaryiD, Daniel L. McCartneyiD, Elena BernabeuiD, Danni A. GaddiD, Yipeng ChengiD, Aleksandra D. ChybowskaiD, Hannah M. SmithiD, Lee MurphyiD, Nicola WrobeliD, Archie I CampbelliD, Rosie May WalkeriD, Caroline HaywardiD, Kathryn Louise EvansiD, Andrew Mark McIntoshiD, Riccardo Emilio MarioniiD
Abstract
BackgroundBlood DNA methylation can inform us about the biological mechanisms that underlie common disease states. Previous epigenome-wide analyses of common diseases often focus solely on the prevalence or incidence of individual conditions and rely on small sample sizes, which may limit power to discover disease-associated loci. ResultsWe conduct blood-based epigenome-wide association studies on the prevalence of 14 common disease states in Generation Scotland (nindividuals[≤]18,413, nCpGs=752,722). We also utilise health record linkage to perform epigenome-wide analyses on the incidence of 19 disease states. We present a structured literature review on existing epigenome-wide analyses for all 19 disease states to assess the degree of replication within the existing literature and the novelty of the present findings. We identify 69 associations between CpGs and the prevalence of four disease states at baseline, of which 58 are novel. We also uncover 64 CpGs that associate with the incidence of two disease states (COPD and type 2 diabetes), of which 56 are novel. These associations were independent from common lifestyle risk factors. We highlight poor replication across the existing literature. Here, replication was defined by the reporting of at least one common gene in >2 studies examining the same disease state. Existing blood-based epigenome-wide analyses showed evidence of replication for only 4/19 disease states (with up-to-15% of unique genes replicated for lung cancer). ConclusionsOur summary data and structured review of the literature provide an important platform to guide future studies that examine the role of blood DNA methylation in complex disease states.
- organism: human
- assay: DNA methylation
- research focus: differential expression
- approach: statistical model
- Citations
- 13
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