Harnessing Progress in Psychiatric Genetics to Advance Population Mental Health

Abstract

Advances in genomics and neuroscience have ushered in unprecedented opportunities to increase our understanding of the biological underpinnings of mental disorders, yet there has been limited progress in translating knowledge on genetic risk factors to reduce the burden of these conditions in the population. We describe the challenges and opportunities afforded by the growth of large-scale population health databases, progress in genomics, and collaborative efforts in epidemiology and neuroscience to develop informed population-wide interventions for mental disorders. Future progress is likely to benefit from the following efforts: expansion of large collaborative studies of mental disorders to include more systematically ascertained multiethnic samples from biobanks and registries, harmonization of phenotypic characterization in registry and population samples to extend clinical diagnosis to transdiagnostic concepts, systematic investigation of the influences of both specific and nonspecific environmental factors that may combine with genetic susceptibility to confer increased risk of specific mental disorders, and implementation of study designs that can inform gene–environment interactions. Such data can ultimately be combined to develop comprehensive models of risks of, interventions for, and outcomes of mental disorders. With its focus on phenotypic characterization, sampling, study designs, and analytic methods, epidemiology will be central to progress in translating genomics to public health.

DRAGON-Data: A platform and protocol for integrating genomic and phenotypic data across large psychiatric cohorts

“…In fact, it has been explicitly suggested that the majority of samples used in published genetic discovery studies have not been collected with the required amount of phenotypic data necessary to advance diagnostics, stratification and treatment 18 . Thus, many research groups have directed their efforts to access resources with large amounts of routinely collected data, such as population biobanks and electronic health record systems, from which rich phenotypic data can be derived 18-20 . However, some common limitations of these include selection biases and underrepresentation of clinically severe disorders 20 21 .…”

“…Commonalities in genetic risk factors might help identify a shared underlying biology, but this line of inquiry cannot be pursued without well-characterised cross-disorder samples, scarce even within large international consortia. In fact, it has been explicitly suggested that the majority of samples used in published genetic discovery studies have not been collected with the required amount of phenotypic data necessary to advance diagnostics, stratification and treatment 18 . Thus, many research groups have directed their efforts to access resources with large amounts of routinely collected data, such as population biobanks and electronic health record systems, from which rich phenotypic data can be derived [18][19][20] .…”

Genetic Overlap Profiles of Cognitive Ability in Psychotic and Affective Illnesses: A Multisite Study of Multiplex Pedigrees

“…Recently, large-scale consortia have made tremendous strides to assemble large case-control samples (2). However, most of the genetic architecture of psychiatric disorders remains unclear (3). A complementary approach, which may provide additional insight, is to identify behaviors that overlap genetically with risk for psychiatric illness, which may also provide a rubric for prioritization of measures to be included in future research.…”

Study on the Relationship Between Musculoskeletal Disorders, BDNF Gene, TPH-2 Gene, and Mental Health in Coal Mine Workers in China

“…In addition to demographic characteristics, the working and living environment, and other factors affecting mental health, studies have found that the effect of gene polymorphisms on mental health cannot be ignored [5]. Brain-derived neurotrophic factor (BDNF) is a mediator of neuronal survival and plasticity of dopaminergic, cholinergic, and serotonergic neurons in the central nervous system (CNF) [6].…”