The prevalence of age-related diseases is increasing along with the global life expectancy, adding substantial burden to individuals and society. Diseases such as cardiovascular disease, stroke, type-2 diabetes, and dementia are now some of our most common causes of late-life morbidity and mortality, causing substantial loss of healthy years and premature deaths. Most age-related diseases are highly complex, influenced by both genetic and environmental factors as well as interactions between them. Moreover, co-morbidities are common in late-life, and many age-related diseases are associated and share a number of risk factors. Of dual importance are protective factors for mitigating the severity or delaying onset of age-related diseases in order to ultimately lengthen lifespan and quality of life. Risk and protective factors for aging-related diseases can act through a combination of the same genetic and environmental factors, yet invoke different biological pathways.
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.
The prevalence of age-related diseases is increasing along with the global life expectancy, adding substantial burden to individuals and society. Diseases such as cardiovascular disease, stroke, type-2 diabetes, and dementia are now some of our most common causes of late-life morbidity and mortality, causing substantial loss of healthy years and premature deaths. Most age-related diseases are highly complex, influenced by both genetic and environmental factors as well as interactions between them. Moreover, co-morbidities are common in late-life, and many age-related diseases are associated and share a number of risk factors. Of dual importance are protective factors for mitigating the severity or delaying onset of age-related diseases in order to ultimately lengthen lifespan and quality of life. Risk and protective factors for aging-related diseases can act through a combination of the same genetic and environmental factors, yet invoke different biological pathways.
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.
