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Mitochondria are eukaryotic cellular organelles that are known to produce energy through a process called oxidative phosphorylation. Besides their primary function, mitochondria are involved in various cellular processes, including cell growth, differentiation, signaling, metabolism, and senescence. Age-related changes cause a decline in mitochondrial quality and integrity due to increased mitochondrial mutations and oxidative damage. Thus, aging can severely impact mitochondrial functions,...
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Measuring biological age: Insights from omics studies.

Eva Kočar1, Robert Šket2, Ana Halužan Vasle3

  • 1University of Ljubljana, Faculty of Medicine, Institute of Biochemistry and Molecular Genetics, Centre for Functional Genomics and Bio-Chips, Ljubljana 1000, Slovenia.

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Summary
This summary is machine-generated.

Biological ageing is a complex process studied using advanced omics technologies. These methods help discover biomarkers and develop personalized strategies for healthy ageing.

Keywords:
ageingbiological ageingcomputational modellingnutritionomicsphysical fitness

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Area of Science:

  • Gerontology and Systems Biology
  • Leveraging multi-omics for understanding biological ageing

Background:

  • Biological ageing is a complex, multifactorial process involving molecular and cellular changes.
  • High-throughput omics technologies enable comprehensive analysis of biomolecules for ageing research.

Purpose of the Study:

  • To review recent advances in applying genomics, epigenomics, metabolomics, and microbiomics to ageing research.
  • To highlight contributions to biomarker discovery, mechanistic insights, and translational opportunities in ageing.

Main Methods:

  • Genomic analysis to identify longevity-associated genetic variants.
  • Epigenetic clocks for predicting biological age.
  • Proteomic, metabolomic, and microbiomic profiling for ageing trajectories.
  • Integration of multi-omics data with clinical and lifestyle factors using AI and machine learning.

Main Results:

  • Genomic variants linked to extreme longevity identified.
  • Epigenetic clocks serve as reliable biological age predictors.
  • Proteomic, metabolomic, and microbiome signatures reflect ageing processes.
  • Interventions like exercise and diet can reduce biological age.
  • Emergence of microbiome clocks and organ/sex-specific ageing trajectories.

Conclusions:

  • Omics technologies and computational modeling are revolutionizing ageing biology.
  • Holistic definition of biological age and personalized healthy ageing strategies are emerging.
  • Multi-omics integration offers powerful tools for understanding and intervening in the ageing process.