Organelle Aging Predicts Human Disease

Aging affects cellular organelles differently, but whether subcellular aging predicts human disease remains unknown. Here, we integrated organelle-enriched proteins in plasma and cerebrospinal fluid proteomes from 61,931 individuals to model aging of 10 organelles across the human lifespan. Organelle aging was heterogeneous with lysosomes, plasma membranes, and Golgi compartments accelerating rapidly after age 60. Individuals with four or more prematurely aged compartments exhibited up to 22-fold higher kidney disease risk and up to 8-fold higher mortality risk. Major diseases are characterized by distinct organelle aging signatures and disease risk increased with the number of accelerated organelles. APOE-ε4 dosage was associated with lysosomal and mitochondrial aging and reduced PDP1 levels, implicating altered energy metabolism. Decomposition of organelle signature coefficients into biological programs further showed that diseases are associated with distinct subcellular patterns. These findings establish organelle-resolved aging as a measurable dimension of human biology, revealing subcellular mechanisms underlying disease susceptibility and resilience.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-11-03
DOI
https://doi.org/10.64898/2026.11.01.763400
Primary Topic
Genetics, Aging, and Longevity in Model Organisms
Type
preprint
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preprint

Organelle Aging Predicts Human Disease

Daisy Yi Ding, Amelia Farinas, Tony Wyss‐Coray, Kenneth L. Chen et al.
bioRxiv (Cold Spring Harbor Laboratory)
Genetics, Aging, and Longevity in Model Organisms
preprint

Organelle Aging Predicts Human Disease

Daisy Yi Ding, Amelia Farinas, Tony Wyss‐Coray, Kenneth L. Chen, Hamilton Se‐Hwee Oh, Kejun Ying, Alina A. Isakova, Veronica Augustina Bot, Carl Ma, Kyle KunHyung Roh
preprint en

Abstract

Aging affects cellular organelles differently, but whether subcellular aging predicts human disease remains unknown. Here, we integrated organelle-enriched proteins in plasma and cerebrospinal fluid proteomes from 61,931 individuals to model aging of 10 organelles across the human lifespan. Organelle aging was heterogeneous with lysosomes, plasma membranes, and Golgi compartments accelerating rapidly after age 60. Individuals with four or more prematurely aged compartments exhibited up to 22-fold higher kidney disease risk and up to 8-fold higher mortality risk. Major diseases are characterized by distinct organelle aging signatures and disease risk increased with the number of accelerated organelles. APOE-ε4 dosage was associated with lysosomal and mitochondrial aging and reduced PDP1 levels, implicating altered energy metabolism. Decomposition of organelle signature coefficients into biological programs further showed that diseases are associated with distinct subcellular patterns. These findings establish organelle-resolved aging as a measurable dimension of human biology, revealing subcellular mechanisms underlying disease susceptibility and resilience.

bioRxiv (Cold Spring Harbor Laboratory)
Stanford University (US), Icahn School of Medicine at Mount Sinai (US)
Genetics, Aging, and Longevity in Model Organisms
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Organelle Aging Predicts Human Disease — Daisy Yi Ding, Amelia Farinas, et al. · bioRxiv (Cold Spring Harbor Laboratory) (2026) | TGRS Research Map | TGRS