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DIVERGE

Financiado

Depression in diverse populations Unravelling the interplay between genes and e...

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... ver más

31/01/2026

UNIVERSITY COLLEGE...

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

UNIVERSITY COLLEGE LONDON No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 4 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2021-01-13

Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:

ERC-2020-STG: ERC STARTING GRANTS

I+D

Cerrada hace 5 años

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4 Participantes

UNIVERSITY COLLEGE LONDON

2.29M€ | Lider

LABORATORIOS OJER PHARMA

898.93K€ | Participante

LAHORE INSTITUTE OF RESEARCH...

Últimas noticias

29-11-2024: IDAE En las últimas 48 horas el Organismo IDAE ha otorgado 4 concesiones

29-11-2024: ECE En las últimas 48 horas el Organismo ECE ha otorgado 2 concesiones

29-11-2024: CMVAMADRID En las últimas 48 horas el Organismo CMVAMADRID ha otorgado 37 concesiones

Duración del proyecto: 60 meses Fecha Inicio: 2021-01-13
Fecha Fin: 2026-01-31

Líder del proyecto

UNIVERSITY COLLEGE LONDON

TRL 4-5

Presupuesto del proyecto 2M€

Descripción del proyecto 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.

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