ArticleGenome medicine2024
Exploring multi-omics and clinical characteristics linked to accelerated biological aging in Asian women of reproductive age: insights from the S-PRESTO study.
Article in Genome medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Enteric-colonizedGut microbes · 2026Article
- Longitudinal infection trajectories and biological aging acceleration in adults: a prospective cohort study.GeroScience · 2026Article
- Fecal Microbiome and Serum Metabolome Profiles of the Ovarian Failure Mouse Model.Applied biochemistry and biotechnology · 2026Article
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- From the lab to lifestyle: epigenetic clocks in personalized aging and health.Biogerontology · 2026Review
- Association between the Framingham steatosis index and osteoarthritis: evidence of mediation by phenotypic age.Scientific reports · 2026Article
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- Advances in multi-omics and aging clock research for female reproductive health and aging.MedScience · 2026Review
- Expanded gut microbial genomes from Chinese populations reveal population-specific genomic features related to human physiological traits.Genome medicine · 2025Article
- Association of longitudinal body mass index trajectories with phenotypic age acceleration: a cross-sectional study based on growth mixture modeling.GeroScience · 2025Article
- Dyslipidemia and aging: the non-linear association between atherogenic index of plasma (AIP) and aging acceleration.Cardiovascular diabetology · 2025Article
- The epigenetic influence of diet-induced gut microbiome changes in precision nutrition - a systematic review.Gastroenterology and hepatology from bed to bench · 2025Review
- Association between triglyceride-glucose and triglyceride-glucose related indices with all-cause mortality in depression participants: a cohort study from NHANES.Frontiers in psychiatry · 2025Article
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22 authors.
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Abstract
backgroundPhenotypic age (PhenoAge), a widely used marker of biological aging, has been shown to be a robust predictor of all-cause mortality and morbidity in different populations. Existing studies on biological aging have primarily focused on individual domains, resulting in a lack of a comprehensive understanding of the multi-systemic dysregulation that occurs in aging.
methodsPhenoAge was evaluated based on a linear combination of chronological age (CA) and 9 clinical biomarkers in 952 multi-ethnic Asian women of reproductive age. Phenotypic age acceleration (PhenoAgeAccel), an aging biomarker, represents PhenoAge after adjusting for CA. This study conducts an in-depth association analysis of PhenoAgeAccel with clinical, nutritional, lipidomic, gut microbiome, and genetic factors.
resultsHigher adiposity, glycaemia, plasma saturated fatty acids, kynurenine pathway metabolites, GlycA, riboflavin, nicotinamide, and insulin-like growth factor binding proteins were positively associated with PhenoAgeAccel. Conversely, a healthier diet and higher levels of pyridoxal phosphate, all-trans retinol, betaine, tryptophan, glutamine, histidine, apolipoprotein B, and insulin-like growth factors were inversely associated with PhenoAgeAccel. Lipidomic analysis found 132 lipid species linked to PhenoAgeAccel, with PC(O-36:0) showing the strongest positive association and CE(24:5) demonstrating the strongest inverse association. A genome-wide association study identified rs9864994 as the top genetic variant (P = 5.69E-07) from the ZDHHC19 gene. Gut microbiome analysis revealed that Erysipelotrichaceae UCG-003 and Bacteroides vulgatus were inversely associated with PhenoAgeAccel. Integrative network analysis of aging-related factors underscored the intricate links among clinical, nutritional and lipidomic variables, such as positive associations between kynurenine pathway metabolites, amino acids, adiposity, and insulin resistance. Furthermore, potential mediation effects of blood biomarkers related to inflammation, immune response, and nutritional and energy metabolism were observed in the associations of diet, adiposity, genetic variants, and gut microbial species with PhenoAgeAccel.
conclusionsOur findings provide a comprehensive analysis of aging-related factors across multiple platforms, delineating their complex interconnections. This study is the first to report novel signatures in lipidomics, gut microbiome and blood biomarkers specifically associated with PhenoAgeAccel. These insights are invaluable in understanding the molecular and metabolic mechanisms underlying biological aging and shed light on potential interventions to mitigate accelerated biological aging by targeting modifiable factors.
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