Identifying single-nucleotide polymorphisms (SNPs) intersecting Alzheimer’s disease pathology and end-of-life traits using genomic informational field theory (GIFT)

Abstract Quantitative genome-wide association studies (GWAS) typically use additive linear models to assess average phenotypic differences between genotype groups. While effective for identifying common variants in large cohorts, these methods compress detailed phenotypic data into summary statistics, potentially limiting detection of subtle genotype–phenotype relationships. Genomic Informational Field Theory (GIFT) is a newly developed framework that preserves fine-grained trait structure by analysing ranked phenotypic configurations rather than relying on group means. We applied GIFT to genetic and neuropathological data from the Brains for Dementia Research cohort and directly compared its performance with conventional GWAS. Principal component analysis (PCA) was used to derive independent quantitative traits linked to Alzheimer’s disease neuropathology (CERAD, Thal phase, and Braak staging), with and without inclusion of age at death. Both GWAS and GIFT were conducted on the same filtered genotype dataset. Both approaches identified genome-wide significant associations (p