Evidence map›Paper›PMID 41727111›Full record

ArticlebioRxiv : the preprint server for biology2026

Cellular Aging Signatures in the Plasma Proteome Record Human Health and Disease.

Daisy Yi Ding, Veronica Augustina Bot, Kenneth L Chen, James Groves, Róbert Pálovics, Daisuke Masuda, Amelia Farinas, Hamilton Se-Hwee Oh, Viktoria Wagner, Nannan Lu and 5 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Daisy Yi DingDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0003-2914-9557
Veronica Augustina BotThe Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, CA, USA.ORCID 0009-0008-5060-1142
Kenneth L ChenDivisions of Hematology and Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
James GrovesDementia Research Centre, UCL Queen Square Institute of Neurology, London, UK.
Róbert PálovicsDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.
Daisuke MasudaWu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
Amelia FarinasThe Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, CA, USA.ORCID 0000-0002-6697-8883
Hamilton Se-Hwee OhNash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID 0000-0001-8192-7593
Viktoria WagnerDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0002-1957-0658
Nannan LuDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.
Global Neurodegeneration Proteomics Consortium (GNPC)
Carlos CruchagaDepartment of Psychiatry, Washington University, St. Louis, MO, USA.ORCID 0000-0002-0276-2899
Alina IsakovaThe Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, CA, USA.ORCID 0000-0003-1113-6889
Jonathan M SchottDementia Research Centre, UCL Queen Square Institute of Neurology, London, UK.ORCID 0000-0003-2059-024X
Tony Wyss-CorayDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0001-5893-0831

Funding

Stanford Alzheimer's Disease Research CenterAdmin Supp: Developing iPSC models for AD and PDP30AG066515 · NIA · STANFORD UNIVERSITY · PI Lisa Goldman Rosas · 2020 to 2026
$29.0M
Working Memory in Parkinson Disease: A Cognitive & Systems Neuroscience ApproachP50AG047366 · NIA · STANFORD UNIVERSITY · PI HENDERSON, VICTOR · 2015 to 2019
$7.9M
Molecular signature of parabiosisR01AG072255 · NIA · STANFORD UNIVERSITY · PI WYSS-CORAY, TONY · 2021 to 2025
$2.4M
NIA NIH HHS P30 AG066515NIA NIH HHS P50 AG047366NIA NIH HHS R01 AG072255
6 · The paper itself

Abstract

Aging is asynchronous across cells and organs, but whether plasma proteins can capture cell type-specific aging and predict disease and mortality remains unknown. We developed machine learning models to estimate the biological age of more than 40 distinct cell types-spanning neuronal, immune, glial, endocrine, epithelial, and musculoskeletal origins-using over 7,000 plasma proteins measured in 60,000 individuals across three cohorts, comprising the largest human plasma proteomics aging study to date. Individuals showed heterogeneous aging profiles, with 20-25% exhibiting accelerated aging in a single cell type and 1-3% across ten or more cell types. APOE genotype showed antagonistic aging effects in different cell types: APOE4 carriers exhibited older astrocytes but younger macrophages, while APOE2 carriers showed the inverse. Cellular aging signatures were uniquely associated with disease status and predicted incident disease and mortality over 15 years of follow-up. Amyotrophic lateral sclerosis (ALS) showed the strongest association with skeletal myocyte aging (hazard ratio = 12.7 for extreme accelerated versus youthful aging). In Alzheimer's disease (AD), prevalent cases showed accelerated aging across multiple neural and peripheral cell types, with extreme astrocyte aging conferring AD risk comparable to APOE4 carrier status. Moreover, extreme astrocyte aging increased AD risk in APOE4/4 carriers threefold, while youthful astrocytes strikingly reduced risk. Beyond neurodegeneration, respiratory cell aging identified smokers at 58% higher lung cancer risk, and myeloid aging identified normoglycemic individuals at higher diabetes risk. Both specific cellular vulnerabilities and cumulative aging burden influenced survival, wherein youthful immune or neuronal profiles were protective. A polycellular aging risk score provided robust mortality risk stratification across platforms and cohorts. These findings establish a framework for quantifying biological aging at the cellular resolution using plasma proteomics, revealing heterogeneity in aging trajectories and their impact on disease susceptibility and resilience.

Identifiers

PMID41727111
PMCPMC12919083

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.