ArticleJournal of the American Statistical Association2025
Identifying genetic variants for brain connectivity using Ball Covariance Ranking and Aggregation.
Article in Journal of the American Statistical Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Understanding the genetic architecture of brain functions is essential to clarify the biological etiologies of behavioral and psychiatric disorders. Functional connectivity, representing pairwise correlations of neural activities between brain regions, is moderately heritable. Current methods to identify single nucleotide polymorphisms (SNPs) linked to functional connectivity either neglect the complex structure of functional connectivity or fail to control false discoveries. Therefore, we propose a SNP-set hypothesis test, Ball Covariance Ranking and Aggregation (BCRA), to select and test the significance of SNP sets related to functional connectivity, incorporating matrix structure and controlling false discovery rate. Additionally, we present subsample-BCRA, a faster version for large-scale datasets. Simulation studies show both methods effectively detect SNPs with interactive structures, with subsample-BCRA shortens the running time by 700 folds. Applying our method to UK Biobank data from 34,129 individuals, we identify 10 SNP-sets with 29 SNPs significantly impacting functional connectivity. Gene-based analyses reveal three SNPs as eQTLs of gene
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