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

Overview

1. The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, USA
2. The Jackson Laboratory, Bar Harbor, Maine, USA

Abstract

INTRODUCTION: Alzheimer'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.

METHODS: We applied INDIGO to dorsolateral prefrontal cortex (DLPFC) proteomic data from the Religious Orders Study and Memory and Aging Project cohort (N = 610). Protein‐level deviations were aggregated into gene set activity scores for Kyoto Encyclopedia of Genes and Genomes pathways and curated AD Biodomain annotations. Functional alterations across AD and asymptomatic AD (AsymAD) individuals were evaluated and correlated with clinical metrics including apolipoprotein E (APOE) genotype, Braak stage, Consortium to Establish a Registry for Alzheimer's Disease (CERAD), and Mini‐Mental State Examination scores. Graph‐based clustering was used to identify molecularly distinct subgroups based on shared patterns of functional dysregulation.

RESULTS: Limited 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 APOE ε4 dosage, higher amyloid and tau burden, and cognitive decline, whereas upregulation of mitochondrial and synaptic modules correlated positively with preserved cognitive function. By linking individuals through concordant directional proteomic changes, we identified molecularly coherent subgroups that transcended conventional diagnostic boundaries and included both AD and AsymAD subjects. Each subgroup displayed distinct functional signatures defined by a unique set of key regulatory proteins.

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.

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Data availability statement

The analysis workflows and rendered HTML reports supporting this study are available at https://avijitpodder‐ap.github.io/ssproteomics‐workflow/ (https://avijitpodder-ap.github.io/ssproteomics-workflow/). The full source code and documentation are available in the GitHub repository https://github.com/avijitpodder‐AP/ssproteomics‐workflow (https://github.com/avijitpodder-AP/ssproteomics-workflow)

Reproduced under the paper's license (CC BY-NC), from the paper cited above.

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This paper

Podder, A., Liew, Y. J., Cary, G. A., Carter, G. W., & Uyar, A. (2026). Single-subject proteomic signatures in Alzheimer's disease reflect clinical phenotypes and distinguish asymptomatic from symptomatic cases. Alzheimer's & dementia (New York, N. Y.), 12(2), e70264. https://doi.org/10.1002/trc2.70264

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