The invited review includes a detailed overview of tools and resources that aid in interpreting GWAS results and is published in Biological Psychiatry.
Genome-wide association studies (GWAS) are uncovering an ever-increasing number of genetic variants related to neuropsychiatric conditions. Schizophrenia, depression, autism, bipolar disorder: All these, and many more, are now understood to be polygenic in nature, which means that the variation in hundreds of genes contributes to their aetiology. As important as this understanding may be, it challenges traditional ways of studying genetic disease. Mendelian diseases are caused by only one or very few mutations, allowing targeted gene manipulation in animal and cellular models. With the complexity that polygenic traits entail, however, other approaches are required to bridge the gap between GWAS and neurobiology.
As part of a University Research Fellowship at the Department of Complex Trait Genetics, Emil Uffelmann and Danielle Posthuma reviewed resources and methods used by geneticists to point to the most-likely biological mechanism underlying a psychiatric condition for the journal Biological Psychiatry. Because meaningful functional experiments cannot be performed with hundreds of mutations, geneticists aim to identify convergent patterns in their data that implicate specific cell-types, tissues, biological pathways or developmental stages. This would allow biologists to resort to their arsenal of experimental appliances and to probe that tissues’ or cell-types’ involvement in a given psychiatric condition. To get there, geneticists can use external data resources on e.g. gene-expression to prioritize a number of genes in their GWAS results. With newly-developed statistical methods, they can subsequently search for convergent functions among those genes.
Uffelmann and Posthuma outline several obstacles that need to be overcome in order to make this strategy a winning one. Among them is the relative scarcity of patient data and an overreliance on adult post-mortem tissue in current resources that may not accurately reflect the consequences of genetic disturbances observed in GWASs. Future resources need to be extended to account for the multi-dimensional nature of neuropsychiatric traits. Moreover, it will necessitate interdisciplinary approaches to solve the ramifications of polygenic-trait architectures. Ultimately, it will be neurobiologists that will need to confirm the results of genetics in-silico analyses in functional follow-up studies. To make this process as efficient and successful as possible, both fields need to actively collaborate in order to capitalize on each other’s domain-specific expertise. New consortia such as Brainscapes are much needed to trailblaze such concerted boundary breaching.
The open access, pre-proof version of the review is available from Biological Psychiatry’s website