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

Abstract

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.

Genome-wide analysis of brain age identifies 25 associated loci and unveils relationships with mental and physical health

“…Two prior studies on BAG have attempted to replicate variant discoveries, albeit with limited success. 17,20 Here we observed a high degree of consistency between discovery and replication results, with 23 out of 25 loci showing consistent effect directions, and 16 loci attaining nominal significance in replication analyses. Notably, polygenic scores accounted for about 2-3% of the phenotypic variance, a remarkable proportion when compared to traits such as intelligence and major depressive disorder, which necessitated considerably larger discovery samples to attain similar prediction accuracies.…”

“…Novelty of the discovered loci was examined by comparing our results against four previous genetic studies on BAG reporting discoveries at genome-wide significance levels. 17,18,20,21 We used the clumping algorithm in PLINK v1.90b6.8 and regarded our own discoveries as novel if they did not clump together with previously reported variants, using a linkage disequilibrium threshold of R 2 = 0.1 and a clumping window of 10 Mbp (--clump-r2 0.1 --clump-kb 10000).…”

“…14,15 While previous genetic studies suggest that BAG exhibits a substantial heritable component, only few studies have identified specific genetic variants that contribute to BAG. [15][16][17][18][19][20][21] To refine the genetic architecture of BAG and identify potential therapeutic targets for healthy aging, further research is imperative.…”

“…We discover novel loci in a sample of 32,634 individuals of white-British ancestry, and replicate our findings in a cross-ancestry sample of 7,259 individuals. This constitutes a 34% increase in sample size (about 10,000 more) compared to the most recent study 20 First, we prioritize genes using complementary fine-mapping, annotation, and co-localization strategies that integrate information from multiple omics resources. Second, we replicate variant effects and calculate polygenic scores to estimate the present yield in variance explanation.…”

The Genetic Architecture of Multimodal Human Brain Age

“…While previous GWAS 19 have associated BAG with common genetic variants [e.g., single nucleotide polymorphism (SNP)], they primarily focused on GM-BAG 9,[20][21][22] or did not comprehensively capture the genetic architecture of the multimodal BAG 19 via post-GWAS analyses in order to biologically validate the GWAS signals. It is crucial to holistically identify the genetic factors associated with multimodal BAGs (GM, WM, and FC-BAG), where each BAG reflects distinct and/or similar neurobiological facets of human brain aging.…”