Project description
Drawing on evolutionary psychiatry to understand depression
Hundreds of millions of people around the world suffer from depression, a mental health condition that is vastly under-reported due to social stigma or no access to screening. Global data show that 80 % of people diagnosed with depression live in low to middle-income countries. Against this background, the EU-funded DIVERGE project will investigate how heritability and environmental factors impact disease development. It will draw from the new perspective of evolutionary psychiatry to address the question of whether genetic risk factors play a role. DIVERGE will also study the interplay between traumatic life events and genetic susceptibility. The findings will shed new light on the aetiology of depression.
Objective
Depression affects 300 million people and represents one of the biggest challenges to human health to date. Of the burden, 80% pertains to low- and middle-income countries. It is thus imperative to understand the global causes of depression to design effective targeted interventions. DIVERGE will build the first ancestrally diverse data resource for depression, generated from biobanks (N=1.8M) and new studies in Pakistan (N=20K) as well as sub-Saharan Africa (N=13K) with deep phenotyping and genotyping.
Differences in depression risk between populations have been shaped by the environment, demography and diverging evolutionary history. Using the novel perspective of evolutionary psychiatry, DIVERGE will comprehensively characterise the genetic architecture of depression and assess how it has been shaped by natural selection. Thereby, I will illuminate how heritability, environmental factors and their interplay affect disease development. I will develop a new method, trans-ethnic colocalization, to address the fundamental question whether genetic risk factors are transferable across populations. This is important to ensure that health benefits of precision medicine can be shared within and across populations.
In addition to the big picture approach, I aim to identify specific causes of the disorder. The diversity of the data together with the application of population-matched inheritance models will empower the discovery of novel genetic loci for depression. I will develop and apply cutting-edge methods, including trans-ethnic fine-mapping with functional annotations to uncover biological mechanisms underlying depression loci. Trauma, such as exposure to violence, is a strong risk factor for depression. DIVERGE will investigate the interplay between traumatic life events and genetic susceptibility which could help understand how mental illness differs across groups. These innovations will lead to a step change in our understanding of the aetiology of depression.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
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Funding Scheme
ERC-STG - Starting GrantHost institution
WC1E 6BT London
United Kingdom