About this Research Topic
Over the recent decade, genetic epidemiology methods have become increasingly important as means to understand the molecular mechanisms underlying disease risk. Through genome-wide association studies (GWAS), genetic variants influencing disease risk have been highlighted, substantially contributing to our understanding of disease biology. The results from GWAS have been carried forward to e.g. pathway analysis, polygenic risk score modelling, and Mendelian randomization studies, resulting in important insight into underlying mechanisms and causal associations. Accumulating evidence points towards the interplay between genetic and environmental risk factors (e.g. life stress, pollution, socioeconomic circumstances) in health and disease, where genetic propensity may make subgroups of individuals more susceptible or resilient to environmental insults. Epigenetic factors may be important links between environmental factors and gene expression, and epigenetic studies have made substantial contributions to the field, e.g. by highlighting genes and pathways where methylation variation is of importance, and by demonstrating the role of accelerated aging using epigenetic clocks.
This Research Topic aims to highlight how genetic epidemiology can help us understand age-related diseases and the role of their risk and protective factors. Examples are cardio- and cerebrovascular disease, type-2 diabetes, Alzheimer's disease and related dementias, Parkinson's disease, and late-life depression, and how these are associated and influenced by genetics, epigenetics, and factors such as inflammation, cholesterol, overweight, smoking and alcohol, sleep, socioeconomic circumstances, and personality traits. We welcome Original Research articles, Brief Research Reports, and Reviews applying various methods to human data, including (but not limited to):
- Genome-wide association analyses
- Genetic correlation
- Polygenic risk scores
- Mendelian randomization
- Gene-environment interplay
- Epigenome-wide association analyses
- Epigenetic clocks
Research based on publicly available summary statistics as well as individual level data are welcome. In particular, studies that evaluate biological pathways or are able to make causal inferences through innovative study design are encouraged for submission.
Keywords: age-related disease, risk factors, epidemiology, genetics, epigenetics
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.