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Related Concept Videos

Proteomics01:33

Proteomics

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
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TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis
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TMT-Based Quantitative Proteomic Analysis Reveals Proteomic Changes Involved in Longevity.

Zongkui Wang1, Rong Zhang1, Fengjuan Liu1

  • 1Chinese Academy of Medical Sciences and Peking Union Medical College, Institute of Blood Transfusion, Chengdu, 610052, China.

Proteomics. Clinical Applications
|November 29, 2018
PubMed
Summary

Researchers identified 175 plasma proteins linked to longevity in Bama natives. Five key proteins (MMP2, CCL5, PF4, IGFBP2, C9) can predict healthy aging and longevity with high accuracy.

Keywords:
TMTbama longevity hotspotcomplement and coagulation cascadesgluconeogenesis/glycolysisproteomics

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Area of Science:

  • Biochemistry
  • Gerontology
  • Proteomics

Background:

  • Individual lifespans exhibit significant variation, making longevity a persistent area of scientific and public interest.
  • Understanding the biological underpinnings of exceptional longevity is crucial for promoting healthy aging.

Purpose of the Study:

  • To identify plasma proteins associated with longevity using advanced proteomics techniques.
  • To discover potential biomarkers for predicting healthy aging and longevity.

Main Methods:

  • Tandem mass tags (TMT)-based proteomics was employed to analyze plasma from a Bama longevity group and a control group.
  • Differentially expressed proteins (DEPs) were identified and subsequently validated using a separate dataset.

Main Results:

  • 175 DEPs were identified between Bama natives and controls, primarily involved in complement/coagulation cascades, glyco/lipid metabolism, and actin cytoskeleton regulation.
  • Validation confirmed lower plasma levels of MMP2, CCL5, and PF4, and higher levels of IGFBP2 and C9 in the longevous group.
  • A combination of these five proteins achieved a high area under the curve (AUC) of 0.991 in ROC analysis for distinguishing longevous individuals.

Conclusions:

  • Complement and coagulation cascades, glyco/lipid metabolism, and inflammatory/immune responses are implicated in longevity.
  • The identified differentially expressed proteins show potential as clinically useful biomarkers for assessing healthy aging and predicting longevity.