Neuroticism is an important risk factor for a variety of psychiatric disorders, such as depression, anxiety and schizophrenia. It has also been associated with other health-related traits like longevity and well-being. Therefore, identifying the genes responsible for individual differences in neuroticism is also highly relevant for numerous other traits. We discovered 124 novel genetic regions (at the time of analysis) related to neuroticism. This is a sharp increase compared to previous studies (16 genetic regions), and shows that very large samples are needed in order to detect the modest effects of many genes. The results suggest that genes associated with neuroticism are predominantly expressed in frontal cortical regions, and mainly in three specific cell types.
We also examined the genetic overlap between neuroticism and depression, since high scores on neuroticism often co-occur with depressive symptoms. By getting to know more about the shared genetic influences of neuroticism and depression, knowledge about one trait might be utilized to learn more about the other. The depression sample consisted of 688,809 individuals. The study identified 45 genetic regions associated with depression, many of which matched those found for neuroticism. An earlier study revealed two genetically distinct components for neuroticism. The current results clearly show that one component is genetically very similar to depression. This suggests that biological information on this component might be particularly relevant also in studying the genetics of depression.
Concluding, neuroticism is an important risk factor for depression. Hence, insights into the biological mechanisms underlying neuroticism may eventually be informative for the development of drugs to treat depression. Our study is the most comprehensive study into the genetics and biological mechanisms of neuroticism to date, and provides very specific starting points for follow-up studies.
Causes of individual differences in cognitive and mental health
The main goal of our study is to quantify and understand the role of genetic variants, the environment (including lifestyle), and their interaction on outcomes related to cognitive health. In doing so we will combine expertise of statistical genetics, medical genetics, bioinformatics and functional genomics. We are specifically interested in the following health-relevant outcomes from the U.K. Biobank data: cognitive function (incl. normal function and dementia), mental health (incl. depression, neuroticism, personality, smoking, and alcohol drinking), and brain MRI. Our research will contribute to quantifying and understanding how several risk factors (e.g. lifestyle, environment, genes), both separately and in combination, influence cognitive health as well as the comorbidities between different cognitive health outcomes. Our study will consist of a combination of methods, including: - Genome-wide association studies (GWAS) that aim to identify individual genetic variants associated with a particular outcome. - Comorbidity analyses, using e.g. meta-analytic techniques, LD score regression or BOLD-GREML methods to quantify the extent of genetic overlap between particular outcomes - Gene-set analyses (e.g. using MAGMA and INRICH tools) and bioinformatic secondary analyses to understand genetic findings in terms of their biological function - Heterogeneity analyses to determine genetic subgroups of individuals - Annotation of genetic findings using external information from e.g. expression or quantitative proteomics data - Gene-by-environment correlation and interaction analyses to quantify the relevance of the interplay between genes and environment (including lifestyle) on outcomes related to cognitive health We aim to use all available observations in the UKB that are currently released and will be released in the future, and that have been successfully genotyped and have measures of relevant outcomes.
|Lead investigator:||Danielle Posthuma|
|Lead institution:||VU University Amsterdam|