Evidence mapPaperPMID 40295347Full record

ArticleGeroScience2025

Global and tissue-specific transcriptomic dysregulation in human aging: Pathways and predictive biomarkers.

Muhammad Arif, Andrea Lehoczki, György Haskó, Falk W Lohoff, Zoltan Ungvari, Pal Pacher

Abstract read
In one paragraph

Article in GeroScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
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  8. Review
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

6 authors.

Muhammad ArifLaboratory of Cardiovascular Physiology and Tissue Injury, National Institute On Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA. muhammad.arif@gu.se.
Andrea LehoczkiDoctoral College/Institute of Preventive Medicine and Public Health, International Training Program in Geroscience, Semmelweis University, Budapest, Hungary.
György HaskóDepartment of Anesthesiology, Columbia University, New York, NY, USA.
Falk W LohoffSection On Clinical Genomics and Experimental Therapeutics, National Institute On Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA.
Zoltan UngvariVascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
Pal PacherLaboratory of Cardiovascular Physiology and Tissue Injury, National Institute On Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA. pacher@mail.nih.gov.ORCID 0000-0001-7036-8108

Funding

Radiation-induced astrocyte dysfunction and cognitive declineR01NS100782 · NINDS · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI ZOLTAN Istvan UNGVARI · 2021 to 2022
$686k
Cerebromicrovascular rejuvenation by heterochronic blood exchangeR01AG072295 · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · 2025 to 2025
$433k
Cerebral microhemorrhages and gait abnormalities in agingR01AG055395 · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · 2025 to 2025
$424k
Innovációs és Technológiai Minisztérium TKP2021-NKTA-47Knut och Alice Wallenbergs Stiftelse KAW 2020.0239NIA NIH HHS R01 AG055395NIA NIH HHS R01AG055395NIA NIH HHS R01 AG068295NIA NIH HHS R01AG068295NIA NIH HHS R01 AG072295NIA NIH HHS R01AG072295NINDS NIH HHS R01 NS100782NINDS NIH HHS R01NS100782
6 · The paper itself

Abstract

Aging is a universal biological process that impacts all tissues, leading to functional decline and increased susceptibility to age-related diseases, particularly cardiometabolic disorders. While aging is characterized by hallmarks such as mitochondrial dysfunction, chronic inflammation, and dysregulated metabolism, the molecular mechanisms driving these processes remain incompletely understood, particularly in a tissue-specific context. To address this gap, we conducted a comprehensive transcriptomic analysis across 40 human tissues using data from the Genotype-Tissue Expression (GTEx) project, comparing individuals younger than 40 years with those older than 65 years. We identified over 17,000 differentially expressed genes (DEGs) across tissues, with distinct patterns of up- and down-regulation. Enrichment analyses revealed that up-regulated DEGs were associated with inflammation, immune responses, and apoptosis, while down-regulated DEGs were linked to mitochondrial function, oxidative phosphorylation, and metabolic processes. Using gene co-expression network (GCN) analyses, we identified 1,099 genes as dysregulated nodes (DNs) shared across tissues, reflecting global aging-associated transcriptional shifts. Integrating machine learning approaches, we pinpointed key aging biomarkers, including GDF15 and EDA2R, which demonstrated strong predictive power for aging and were particularly relevant in cardiometabolic tissues such as the heart, liver, skeletal muscle, and adipose tissue. These genes were also validated in plasma proteomics studies and exhibited significant correlations with clinical cardiometabolic health indicators. This study provides a multi-tissue, integrative perspective on aging, uncovering both systemic and tissue-specific molecular signatures. Our findings advance understanding of the molecular underpinnings of aging and identify novel biomarkers that may serve as therapeutic targets for promoting healthy aging and mitigating age-related diseases.

Indexed as

AgingTranscriptomeAdultAgedBiomarkersFemaleGene Expression ProfilingGrowth Differentiation Factor 15HumansMaleMiddle AgedBiomarkersGDF15 protein, humanGrowth Differentiation Factor 15Aging biomarkersCardiometabolic healthGene co-expression networksInflammationMachine learningMitochondrial dysfunctionTranscriptomics

Identifiers

PMID40295347
PMCPMC12397481

What Socratic holds

Textmetadata
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 Socratic graph.