02313nas a2200385   4500000000100000000000100001008004100002260001500043653004500058653003100103653001700134100003500151700002400186700002300210700001300233700001700246700002400263700001600287700001500303700001600318700001800334700002400352700002300376700001900399700002000418700001700438700001800455700001700473245009800490856005500588300000900643490000700652520125400659022001401913       2026                            d  c2026-09-2310aComputational biology and bioinformatics10aNeurodegenerative Diseases10aNeuroscience1 aPramod Bharadwaj Chandrashekar1 aSayali Anil Alatkar1 aNoah Cohen Kalafut1 aTing Jin1 aChirag Gupta1 aRyan Conway Burczak1 aXiang Huang1 aShuang Liu1 aAthan Z. Li1 aKiran Girdhar1 aGeorgios Voloudakis1 aGabriel E. Hoffman1 aJaroslav Bendl1 aJohn F. Fullard1 aDonghoon Lee1 aPanos Roussos1 aDaifeng Wang00aPersonalized single-cell transcriptomics reveals molecular diversity in Alzheimer’s disease  uhttps://www.nature.com/articles/s41467-026-72310-1  a95960 v173 aAlzheimer’s disease (AD) is highly heterogeneous and driven by diverse molecular and cellular mechanisms. Functional genomics investigates these mechanisms from genetic variants to gene expression and regulation. We performed personalized functional genomics analysis on population-scale single-nucleus RNA-seq data, with cross-cohort validation across multiple cohorts comprising over 1900 individual brains, capturing donor-level cell type interactions and gene regulatory networks. Using a knowledge-guided graph neural network, we learned latent representations of each donor’s functional genomics that accurately classified AD phenotypes, identified molecularly defined subpopulations, and traced disease progression trajectories. Our importance scores, derived from graph attentions, identified significant inter-donor differences and prioritized personalized cell type genes and regulatory networks. Finally, we identified gene regulatory QTLs (grQTLs) linking genetic variants to donor-level regulatory changes, providing insights into gene regulatory relationships beyond traditional eQTLs. All results are summarized into a personalized functional genomics atlas for AD, including an open-source framework, iBrainMap, for general use.  a2041-1723