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GWAS Study

Regulatory Genomic Circuitry of Brain Age by Integrative Functional Genomic Analyses.

Zhao X, Yang A, Ding J et al.

40795387 PubMed ID
GWAS Study Type
35702 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

ZX
Zhao X
YA
Yang A
DJ
Ding J
YY
Yang YT
ZX
Zhao XM
Chapter II

Abstract

Summary of the research findings

Brain age gap (BAG) is a valuable biomarker for evaluating brain healthy status and detecting age-associated cognitive degeneration. However, the genetic architecture of BAG and the underlying mechanisms are poorly understood. Here, we estimated brain age from magnetic resonance imaging with improved accuracy using our proposed adversarial convolution network (ACN), followed by applying the ACN model to an elder cohort from UK Biobank. The genetic heritability of BAG was significantly enriched in the regulatory regions and implicated in glial cells. We prioritized a set of BAG-associated genes, and further characterized their expression patterns across brain cell types and regions. Two BAG-associated genes, RUNX2 and KLF3, were found as associated with epigenetic clock and diverse aging-related biological pathways. Finally, two BAG-associated hub transcription factors, KLF3 and SOX10, were identified as regulators of pleiotropic risk genes from diverse brain disorders. Altogether, we improve the estimation of BAG, and identify BAG-associated genes and regulatory networks that are implicated in brain disorders.

35,702 European ancestry individuals

Chapter III

Study Statistics

Key metrics and study information

35702
Total Participants
GWAS
Study Type
No
Replicated
European
Ancestry
U.K.
Recruitment Country
Chapter IV

Analysis

Comprehensive review of health and genetic findings

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