Evidence map›Paper›PMID 36459652›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Age-related brain atrophy is not a homogenous process: Different functional brain networks associate differentially with aging and blood factors.

Nikola T Markov, Cutter A Lindbergh, Adam M Staffaroni, Kevin Perez, Michael Stevens, Khiem Nguyen, Natalia F Murad, Corrina Fonseca, Judith Campisi, Joel Kramer and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 8% of its field
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

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.

  1. Pooled it
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  6. Clinical utility and prospective of TMS-EEG: Updated review from an international expert group.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2026
    Review
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  13. Immunological biomarkers of aging.Journal of immunology (Baltimore, Md. : 1950) · 2025
    Review
  14. Article
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  18. Observational
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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

11 authors at 3 institutions in 4 countries.

Nikola T MarkovBuck AI Platform, Buck Institute for Research on Aging, Novato, CA 94945.ORCID 0000-0003-1417-1161
Cutter A LindberghDepartment of Neurology, Memory and Aging Center, University of California San Francisco, Weill Institute for Neurosciences, San Francisco, CA 94158.
Adam M StaffaroniDepartment of Neurology, Memory and Aging Center, University of California San Francisco, Weill Institute for Neurosciences, San Francisco, CA 94158.
Kevin PerezBuck AI Platform, Buck Institute for Research on Aging, Novato, CA 94945.
Michael StevensBuck AI Platform, Buck Institute for Research on Aging, Novato, CA 94945.
Khiem NguyenBuck AI Platform, Buck Institute for Research on Aging, Novato, CA 94945.ORCID 0000-0002-7306-588X
Natalia F MuradBuck AI Platform, Buck Institute for Research on Aging, Novato, CA 94945.
Corrina FonsecaDepartment of Neurology, Memory and Aging Center, University of California San Francisco, Weill Institute for Neurosciences, San Francisco, CA 94158.
Judith CampisiBuck AI Platform, Buck Institute for Research on Aging, Novato, CA 94945.
Joel KramerDepartment of Neurology, Memory and Aging Center, University of California San Francisco, Weill Institute for Neurosciences, San Francisco, CA 94158.
David FurmanBuck AI Platform, Buck Institute for Research on Aging, Novato, CA 94945.ORCID 0000-0002-3654-9519
Buck Institute for Research on Aging · USUniversity of California, San Francisco · USUniversity of Connecticut · US

Funding

Research Education ComponentP30AG062422 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Gil Dan Rabinovici · 2019 to 2026
$36.9M
PrPSc SPECIFIC INTERACTION WITH NOVEL PrP-Fc FUSION PROTEINSP50AG023501 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HUANG, YADONG · 2004 to 2018
$27.1M
Single cell analysis coreP01AG066591 · NIA · BUCK INSTITUTE FOR RESEARCH ON AGING · PI ELLERBY, LISA M · 2021 to 2025
$15.5M
Mechanisms of Executive Decline in Normal AgingR01AG032289 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Kaitlin B Casaletto, JOEL H KRAMER · 2009 to 2026
$8.3M
Biological Predictors Of Brain Aging Trajectories Diversity Supplement: African American Outreach And The Intersection Between Social Determinants Of Health And Biomarkers Of Degenerative DiseaseRF1AG032289 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KRAMER, JOEL H · 2020 to 2021
$5.3M
Effects of chronic inflammation on brain structure and functionR01AG048234 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KRAMER, JOEL H · 2015 to 2019
$3.2M
Optimizing Clinical Trial Endpoints in Frontotemporal DementiaK23AG061253 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI STAFFARONI, ADAM MARK · 2019 to 2023
$946k
NIA NIH HHS K23 AG061253NIA NIH HHS P01 AG066591NIA NIH HHS P30 AG062422NIA NIH HHS P50 AG023501NIA NIH HHS R01 AG032289NIA NIH HHS R01 AG048234NIA NIH HHS RF1 AG032289
6 · The paper itself

Abstract

Aging is characterized by a progressive loss of brain volume at an estimated rate of 5% per decade after age 40. While these morphometric changes, especially those affecting gray matter and atrophy of the temporal lobe, are predictors of cognitive performance, the strong association with aging obscures the potential parallel, but more specific role, of individual subject physiology. Here, we studied a cohort of 554 human subjects who were monitored using structural MRI scans and blood immune protein concentrations. Using machine learning, we derived a cytokine clock (CyClo), which predicted age with good accuracy (Mean Absolute Error = 6 y) based on the expression of a subset of immune proteins. These proteins included, among others, Placenta Growth Factor (PLGF) and Vascular Endothelial Growth Factor (VEGF), both involved in angiogenesis, the chemoattractant vascular cell adhesion molecule 1 (VCAM-1), the canonical inflammatory proteins interleukin-6 (IL-6) and tumor necrosis factor alpha (TNFα), the chemoattractant IP-10 (CXCL10), and eotaxin-1 (CCL11), previously involved in brain disorders. Age, sex, and the CyClo were independently associated with different functionally defined cortical networks in the brain. While age was mostly correlated with changes in the somatomotor system, sex was associated with variability in the frontoparietal, ventral attention, and visual networks. Significant canonical correlation was observed for the CyClo and the default mode, limbic, and dorsal attention networks, indicating that immune circulating proteins preferentially affect brain processes such as focused attention, emotion, memory, response to social stress, internal evaluation, and access to consciousness. Thus, we identified immune biomarkers of brain aging which could be potential therapeutic targets for the prevention of age-related cognitive decline.

Indexed as

BrainVascular Endothelial Growth Factor AAdultAgingAtrophyCytokinesHumansResearch PersonnelCytokinesVascular Endothelial Growth Factor Aagingbrain agingcytokine clockcytokinesgray matter volume

Identifiers

PMID36459652
PMCPMC9894212
OpenAlexW4310780424

What OpenQuestion holds

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LicenceCC BY
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 OpenQuestion graph.