Single-subject proteomic signatures in Alzheimer's disease reflect clinical phenotypes and distinguish asymptomatic from symptomatic cases.

introductionAlzheimer's disease (AD) exhibits considerable inter-individual variability in clinical presentation, neuropathological burden, and underlying molecular processes. Conventional cohort-based analyses of omics molecular data often mask individual-level heterogeneity, limiting insights into precision therapeutic strategies. To address this challenge, we developed INdividual-level DIfferential GenOmics (INDIGO), a computational framework that quantifies molecular deviations for each individual relative to healthy controls, enabling subject-specific profiling of disease-associated alterations in proteomic data, with a framework that is readily applicable to other omics modalities.

methodsWe applied INDIGO to dorsolateral prefrontal cortex (DLPFC) proteomic data from the Religious Orders Study and Memory and Aging Project cohort (

resultsLimited overlap was observed between cohort-level differential expression analysis and INDIGO single-subject analyses. Individual deviations in various processes, including metabolic, immune, and epigenetic pathways, exhibited sex- and disease stage-specific patterns. Amyloid clearance and immune activation were strongly associated with DISCUSSION: These results demonstrate that single-subject omics profiling can resolve individual molecular signatures aligned with clinical and neuropathological variation in AD. By linking molecular heterogeneity with disease phenotypes, INDIGO provides a scalable framework for precision modeling and novel therapeutic target discovery.