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

Afsaneh Mohammadnejad, Mette Soerensen, Jan Baumbach, Jonas Mengel-From, Weilong Li, Jesper Lund, Shuxia Li, Lene Christiansen, Kaare Christensen, Jacob V.B. Hjelmborg, Qihua Tan

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


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.

Original languageEnglish
Article numbere13293
JournalAging Cell
Issue number2
StatePublished - Feb 2021


  • Cognitive function
  • epigenetics
  • generalized correlation coefficient
  • linear regression
  • twins


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