Evidence map›Paper›PMID 41013779›Full record

ArticleGenome medicine2025

Personalized transcriptional network analysis links age-related loss of gene coordination to individual biological aging.

Hao-Tian Wang, Fu-Hui Xiao, Long Zhao, Qian Su, Tian-Rui Xia, Li-Qin Yang, Si-Yu Ma, Qing-Peng Kong

Abstract read
In one paragraph

Article in Genome medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

8 authors.

Hao-Tian Wang *State Key Laboratory of Genetic Evolution & Animal Models, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650201, China.
Fu-Hui Xiao *State Key Laboratory of Genetic Evolution & Animal Models, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650201, China. agingstudy_xiao@163.com.
Long ZhaoState Key Laboratory of Genetic Evolution & Animal Models, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650201, China.
Qian SuState Key Laboratory of Genetic Evolution & Animal Models, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650201, China.
Tian-Rui XiaState Key Laboratory of Genetic Evolution & Animal Models, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650201, China.
Li-Qin YangState Key Laboratory of Genetic Evolution & Animal Models, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650201, China.
Si-Yu MaState Key Laboratory of Genetic Evolution & Animal Models, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650201, China.
Qing-Peng KongState Key Laboratory of Genetic Evolution & Animal Models, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650201, China. kongqp@mail.kiz.ac.cn.

Funding

CAS Project for Young Scientists in Basic Research YSBR-076High level Talent Promotion and Training Project of Kunming 2020SCP001National Key R&D Program of China 2023YFC3603400National Natural Science Foundation of China 82371580National Natural Science Foundation of China 82401833National Natural Science Foundation of China 82430049Reserve Talent Project of Young and Middle-aged Academic and Technical Leaders in Yunnan Province 202305AC160029Yunnan Fundamental Research Projects 202301AT070281Yunnan Fundamental Research Projects 202401AW070011
6 · The paper itself

Abstract

backgroundAging is characterized by the decline in biological functions, accompanied by changes in gene-to-gene transcriptional coordination, which can be estimated by expression coordination in gene transcriptional network. Notably, gene networks and coordinated expression relationships (CERs) showed inter-individual variability, while personalized aging-related gene expression coordination dynamics in human cohorts have yet to be investigated.

methodsIn this study, we constructed 15,933 personalized transcriptional networks across 26 tissues from 967 donors aged 20 to 80 years old, using the sample-specific network (SSN) framework based on data from the Gene-Tissue Expression (GTEx) project.

resultsWe identified gene-gene CERs and characterized their age-dependent dynamic trends across tissues, observing a universal trend of increased gene-to-gene coordination loss during aging across tissues. The count of lost CERs is also positively correlated with individual-level aging and senescence-related molecular phenotypes. Notably, we revealed that the lost CERs have potential as biomarkers for individual aging and health status. In addition, we identified gene coordination loss events exhibiting significant positive correlation with age, defined as aging-related lost relationships (ARLRs), which may be functionally associated with pathways related to proteolytic processes. Finally, we showed that ARLRs may contribute to deleterious effects and increased pathogenicity through gene dosage imbalances.

conclusionsThis study establishes, for the first time, a connection between the loss of gene-to-gene expression coordination and individual-level aging progress. It provides proof-of-principle evidence for using lost gene coordinated expression relationships as biomarkers of healthy aging and highlights the potential risks associated with coordination loss in specific biological pathways during aging.

Indexed as

AgingGene Regulatory NetworksAdultAgedAged, 80 and overFemaleGene Expression ProfilingGene Expression RegulationHumansMaleMiddle AgedYoung AdultAgingBiomarkerGene expressionGene regulatory networkGenomicsTranscriptional coordination

Identifiers

PMID41013779
PMCPMC12465313

What Socratic holds

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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.