Researchers developed enhanced polygenic risk scores for Alzheimer's disease by incorporating chromatin interaction and expression quantitative trait loci (eQTL) data to better map genetic variants to genes. Testing across 331,896 UK Biobank participants and 3,370 additional subjects, this functionally-informed approach consistently outperformed traditional position-based gene mapping, particularly improving detection of sex-dependent and age-at-onset associations. The breakthrough addresses a critical limitation in current genetic risk assessment: most disease-associated variants lie in non-coding regions that can regulate genes across vast genomic distances, yet standard methods only consider variants within gene boundaries. This advancement could significantly enhance early Alzheimer's detection and personalized prevention strategies, as polygenic risk scores increasingly guide clinical decisions about cognitive screening and lifestyle interventions. The improved accuracy particularly benefits identification of at-risk individuals before symptom onset, when preventive measures may be most effective. However, this preprint awaits peer review, and the findings require validation across diverse populations beyond the predominantly European ancestry cohorts studied. The work represents an incremental but meaningful step toward precision medicine in neurodegenerative disease prevention.