| Title: | Measuring biological age : insights from omics studies |
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| Authors: | ID Kočar, Eva (Author)
ID Šket, Robert (Author)
ID Halužan Vasle, Ana (Author)
ID Avguštin, Gorazd (Author)
ID Benedik, Evgen (Author)
ID Koroušić-Seljak, Barbara (Author)
ID Simić, Pavle (Author)
ID Martinko, Antonio (Author)
ID Morrison, Shawnda A. (Author)
ID Sorić, Maroje (Author)
ID Skrt, Mihaela (Author)
ID Polak, Tomaž (Author)
ID Tesovnik, Tine (Author)
ID Jenko Bizjan, Barbara (Author)
ID Kovač, Jernej (Author)
ID Battelino, Tadej (Author)
ID Rozman, Damjana (Author)
ID Poklar Ulrih, Nataša (Author)
ID Bogovič Matijašić, Bojana (Author)
ID Jurak, Gregor (Author)
ID Moškon, Miha (Author)
ID Režen, Tadeja (Author) |
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| Files: |  PDF - Presentation file, download (2,08 MB)
MD5: 8913A024DDB48A70BB4C22BEAF87503C
 URL - Source URL, visit https://www.sciencedirect.com/science/article/pii/S1568163725003344
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| Language: | English |
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| Typology: | 1.02 - Review Article |
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| Organization: |  UKC LJ - Ljubljana University Medical Centre
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| Abstract: | Biological ageing is a systemic, multifactorial process driven by progressive molecular and cellular alterations whose complexity necessitates systems-level approaches. Advances in high-throughput omics technologies now allow simultaneous quantification of millions of biomolecules from a single specimen, enabling longitudinal, integrative profiling across multiple molecular layers. This review synthesizes recent progress in applying genomics, epigenomics, metabolomics and microbiomics to ageing research, highlighting their contributions to biomarker discovery, mechanistic insight, and translational opportunities. Genomic studies reveal genetic variants that promote extreme longevity, while epigenetic clocks provide robust predictors of biological age. The blood proteome can be used to calculate proteome-based scores and evaluate temporal changes in ageing trajectories in an organ- and sex-specific manner. Metabolomic signatures identify key metabolites reflecting ageing trajectories, and microbiome research demonstrates that gut microbial composition mirrors and modulates biological ageing, with microbiome clocks emerging. The omics approaches have further elucidated the impact of exercise and diet providing evidence that interventions can reduce biological age. The integration of multi-omics with clinical and lifestyle data, powered by machine learning and artificial intelligence, is paving the way for a holistic definition of biological age and the development of personalized healthy ageing strategies. This review highlights how the omics technologies and computational modelling are transforming ageing biology into strategies for personalized healthy ageing. |
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| Keywords: | ageing, biological ageing, omics, physical fitness, nutrition, computational modelling |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Year of publishing: | 2026 |
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| Number of pages: | str. 1-28 |
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| Numbering: | Vol. 114, [article no. ]ǂ102988 |
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| PID: | 20.500.12556/DiRROS-25055  |
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| UDC: | 612.013:575 |
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| ISSN on article: | 1568-1637 |
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| DOI: | 10.1016/j.arr.2025.102988 |
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| COBISS.SI-ID: | 261021955 |
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| Note: |
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| Publication date in DiRROS: | 08.01.2026 |
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| Views: | 418 |
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| Downloads: | 109 |
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