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The Effect of Aging on Tissues01:19

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Several body functions deteriorate with age. The external signs of aging are easily identifiable. For example, the skin becomes dry, less elastic, and thins out, forming wrinkles. The skin of the face begins to appear looser due to a decrease in the levels of elastic and collagen fibers in the connective tissue. Additionally, melanin production in the hair follicle decreases with age, resulting in gray hair. Moreover, the senses of sight and hearing decline, so glasses and hearing aids may...
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Proteomic landscape of multidimensional aging phenotypes.

Zhi Cao1, Han Chen2,3, Jiahao Min2

  • 1Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.

Genome Medicine
|October 17, 2025
PubMed
Summary

This study identified 71 plasma proteins linked to aging phenotypes, with 12 showing potential for drug targeting in aging-related diseases. These findings improve understanding of aging biomarkers and therapeutic strategies.

Keywords:
AgingGeneticsMendelian randomizationMetabolomeProteome

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Area of Science:

  • Gerontology
  • Proteomics
  • Biomarker Discovery

Background:

  • Aging process evaluation and targeted therapy can be advanced by understanding proteomic signatures.
  • The proteomic landscape of multidimensional aging phenotypes is not well-characterized.
  • Identifying aging biomarkers and their molecular mechanisms is crucial.

Purpose of the Study:

  • To identify potential proteomic biomarkers of the aging process.
  • To decipher the molecular mechanisms underlying aging phenotypes.
  • To explore causal relationships between plasma proteome and aging.

Main Methods:

  • Analysis of 2920 plasma proteomic biomarkers in 48,728 UK Biobank participants.
  • Two-sample Mendelian randomization (MR) to assess causal effects on aging phenotypes.
  • Replication in the FinnGen cohort and bioinformatic analyses for functional insights.

Main Results:

  • 17, 37, 12, 18, and 1 proteins causally linked to different aging metrics (KDM-BA acceleration, PhenoAge acceleration, frailty, LTL, healthspan).
  • 71 distinct plasma proteins associated with multidimensional aging phenotypes identified.
  • 12 proteins implicated in inflammation and senescence identified as drug targets; 22 genetic variants and metabolic pathways highlighted.

Conclusions:

  • Findings enhance understanding of the proteomic landscape in aging.
  • Provides opportunities for personalized aging monitoring.
  • Offers potential for effective therapeutic strategies in aging-related diseases.