Organ aging signatures in the plasma proteome track health and disease.

Animal studies show aging varies between individuals as well as between organs within an individual1-4, but whether this is true in humans and its effect on age-related diseases is unknown. We utilized levels of human blood plasma proteins originating from specific organs to measure organ-specific aging differences in living individuals. Using machine learning models, we analysed aging in 11 major organs and estimated organ age reproducibly in five independent cohorts encompassing 5,676 adults across the human lifespan. We discovered nearly 20% of the population show strongly accelerated age in one organ and 1.7% are multi-organ agers. Accelerated organ aging confers 20-50% higher mortality risk, and organ-specific diseases relate to faster aging of those organs. We find individuals with accelerated heart aging have a 250% increased heart failure risk and accelerated brain and vascular aging predict Alzheimer's disease (AD) progression independently from and as strongly as plasma pTau-181 (ref. 5), the current best blood-based biomarker for AD. Our models link vascular calcification, extracellular matrix alterations and synaptic protein shedding to early cognitive decline. We introduce a simple and interpretable method to study organ aging using plasma proteomics data, predicting diseases and aging effects.

Plasma proteomics in the UK Biobank reveals youthful brains and immune systems promote healthspan and longevity.

Organ-derived plasma protein signatures derived from aptamer protein arrays track organ-specific aging, disease, and mortality in humans, but the robustness and clinical utility of these models and their biological underpinnings remain unknown. Here, we estimate biological age of 11 organs from 44,526 individuals in the UK Biobank using an antibody-based proteomics platform to model disease and mortality risk. Organ age estimates are associated with future onset of heart failure (heart age HR=1.83), chronic obstructive pulmonary disease (lung age HR=1.39), type II diabetes (kidney age HR=1.58), and Alzheimer's disease (brain age HR=1.81) and sensitive to lifestyle factors such as smoking and exercise, hormone replacement therapy, or supplements. Remarkably, the accrual of aged organs progressively increases mortality risk while a youthful brain and immune system are uniquely associated with disease-free longevity. These findings support the use of plasma proteins for monitoring organ health and the efficacy of drugs targeting organ aging disease.

Proteomics of brain, CSF, and plasma identifies molecular signatures for distinguishing sporadic and genetic Alzheimer's disease.

Proteomic studies for Alzheimer's disease (AD) are instrumental in identifying AD pathways but often focus on single tissues and sporadic AD cases. Here, we present a proteomic study analyzing 1305 proteins in brain tissue, cerebrospinal fluid (CSF), and plasma from patients with sporadic AD, TREM2 risk variant carriers, patients with autosomal dominant AD (ADAD), and healthy individuals. We identified 8 brain, 40 CSF, and 9 plasma proteins that were altered in individuals with sporadic AD, and we replicated these findings in several external datasets. We identified a proteomic signature that differentiated TREM2 variant carriers from both individuals with sporadic AD and healthy individuals. The proteins associated with sporadic AD were also altered in patients with ADAD, but with a greater effect size. Brain-derived proteins associated with ADAD were also replicated in additional CSF samples. Enrichment analyses highlighted several pathways, including those implicated in AD (calcineurin and Apo E), Parkinson's disease (α-synuclein and LRRK2), and innate immune responses (SHC1, ERK-1, and SPP1). Our findings suggest that combined proteomics across brain tissue, CSF, and plasma can be used to identify markers for sporadic and genetically defined AD.