An overview of DNA methylation-derived trait score methods and applications

Journal article

Major Depression (MD) is a leading cause of global disease burden, and both experimental and population-based studies suggest that differences in DNA methylation (DNAm) may be associated with the condition. However, previous DNAm studies have not so far been widely replicated, suggesting a need for larger meta-analysis studies. In the present study, the Psychiatric Genomics Consortium Major Depressive Disorder working group conducted a meta-analysis of methylome-wide association analysis (MWAS) for life-time MD across 18 studies of 24,754 European-ancestry participants (5,443 MD cases) and an East Asian sample (243 cases, 1846 controls). We identified fifteen CpG sites associated with lifetime MD with methylome-wide significance (p < 6.42e-8). Top CpG effect sizes in European ancestries were positively correlated with those from an independent East Asian MWAS (r = 0.482 and p = 0.068 for significant CpG sites, r = 0.261 and p = 0.009 for the top 100 CpG sites). Methylation score (MS) created using the MWAS summary statistics was significantly associated with MD status in an out-of-sample classification analysis (beta = 0.122, p = 0.005, AUC = 0.53). MS was also associated with five inflammatory markers, with the strongest association found with Tumor Necrosis Factor Beta (beta=-0.154, p=1.5e-5). Mendelian randomisation (MR) analysis demonstrated that 23 CpG sites were potentially causally associated with MD and six of those were replicated in an independent mQTL dataset (Wald's ratio test, absolute β ranged from 0.056 to 0.932, p ranged from 7e-3 to 4.58e-6). CpG sites located in the Major Histocompatibility complex (MHC) region showed the strongest evidence from MR analysis of being associated with MD. Our study provides evidence that variations in DNA methylation are associated with MD, and further evidence supporting involvement of the immune system. Larger sample sizes in diverse ancestries are likely to reveal replicable associations to improve mechanistic inferences with the potential to inform molecular target identification

Authors: Nabais, MF; Gadd, DA; Hannon, E; Mill, J; McRae, AF

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: BioMed Central
• Journal: Genome Biology
• Volume: 24
• Issue: 1
• Pages: 28-28
• Article number: 28
• Publication date: 2023-02-16
• DOI: 10.1186/s13059-023-02855-7
• EISSN: 1474-760X
• ISSN: 1474-7596
• Language: English
• Keywords: Genetics; Human genetics; Biology; DNA; Epigenetics; Trait; Bioinformatics; Gene expression; Computational biology; Evolutionary biology; Methylation; Computer science; DNA microarray; DNA methylation; Gene