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GWAS Study

Genetic architecture of brain age and its causal relations with brain and mental disorders.

Leonardsen EH, Vidal-Piñeiro D, Roe JM et al.

37165155 PubMed ID
GWAS Study Type
28104 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

LE
Leonardsen EH
VD
Vidal-Piñeiro D
RJ
Roe JM
FO
Frei O
SA
Shadrin AA
IO
Iakunchykova O
DL
de Lange AG
KT
Kaufmann T
TB
Taschler B
SS
Smith SM
AO
Andreassen OA
WT
Wolfers T
WL
Westlye LT
WY
Wang Y
Chapter II

Abstract

Summary of the research findings

The difference between chronological age and the apparent age of the brain estimated from brain imaging data-the brain age gap (BAG)-is widely considered a general indicator of brain health. Converging evidence supports that BAG is sensitive to an array of genetic and nongenetic traits and diseases, yet few studies have examined the genetic architecture and its corresponding causal relationships with common brain disorders. Here, we estimate BAG using state-of-the-art neural networks trained on brain scans from 53,542 individuals (age range 3-95 years). A genome-wide association analysis across 28,104 individuals (40-84 years) from the UK Biobank revealed eight independent genomic regions significantly associated with BAG (p < 5 × 10-8) implicating neurological, metabolic, and immunological pathways - among which seven are novel. No significant genetic correlations or causal relationships with BAG were found for Parkinson's disease, major depressive disorder, or schizophrenia, but two-sample Mendelian randomization indicated a causal influence of AD (p = 7.9 × 10-4) and bipolar disorder (p = 1.35 × 10-2) on BAG. These results emphasize the polygenic architecture of brain age and provide insights into the causal relationship between selected neurological and neuropsychiatric disorders and BAG.

28,104 individuals

Chapter III

Study Statistics

Key metrics and study information

28104
Total Participants
GWAS
Study Type
No
Replicated
U.K.
Recruitment Country
Chapter IV

AI-Generated Summary

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