We are moving past the era of simplistic “biological age” scores and entering the age of “multi-omic integration.” This comprehensive review synthesizes the current state of the art in measuring biological aging, arguing that no single clock—whether epigenetic (DNA methylation), proteomic (blood proteins), or metabolic—can accurately capture the systemic decline of the human body. The authors, led by Eva Kočar at the University of Ljubljana, contend that aging is asynchronous; your liver may be “older” than your heart, and your immune system may be aging faster than your brain.
The “Big Idea” here is the shift from linear aging trajectories to “ageotypes”—distinct patterns of aging (e.g., metabolic vs. immune agers). The paper aggregates data from genomics (protective centenarian variants like FOXO3), epigenomics (the impact of diet and exercise on methylation clocks), and the emerging fields of microbiomics and metabolomics. Crucially, it highlights a major translational gap: while we have identified thousands of biomarkers (from decreased NAD+ to specific gut bacteria like Bacteroides), the correlation between different “clocks” remains poor. A person might score “young” on a methylation clock but “old” on a proteomic one. The authors conclude that the future lies in AI-driven, non-linear models that integrate these disparate layers to guide personalized interventions—specifically highlighting strength training and plant-forward nutrition as the most validated modulators of these clocks to date.
Source:
- Open Access Paper: Measuring biological age: Insights from omics studies
- Context: University of Ljubljana, Slovenia; Ageing Research Reviews.
- Impact Evaluation: The impact score of this journal is 12.4 (2024 Impact Factor) and a CiteScore of 14.2, evaluated against a typical high-end range of 0–15+ for specialized reviews. Therefore, this is an Elite impact journal, ranking Q1 in Geriatrics & Gerontology and Cell Biology.
Part 2: The Biohacker Analysis
Study Design Specifications:
- Type: Systematic Review / Narrative Review. (Note: This is not a primary intervention trial; it synthesizes data from multiple human and animal studies).
- Subjects: N/A (Reviews data from cohorts such as UK Biobank, NHANES, CALERIE, and the Twin Nutrition Study).
- Lifespan Analysis: Not applicable (Review article).
- Lifespan Data: The review cites efficacy data from external trials (e.g., Ca-AKG extending mouse lifespan and reducing human epigenetic age by ~8 years in retrospective analysis).
Mechanistic Deep Dive: The paper dissects aging through four primary “omics” lenses, identifying actionable targets for biohackers:
- Epigenetic Drift & 1-C Metabolism: It reinforces that DNA methylation is heavily influenced by One-Carbon metabolism. Deficiencies in folate, B12, or choline lead to “epigenetic drift.”
- Proteostasis & Inflammaging: It identifies specific plasma protein signatures (SASPs) like GDF15 and CXCL12(senokines) that drive systemic aging.
- Metabolic Flexibility (NAD+ & Lipids): Aging is characterized by a decline in NAD+ and an increase in ceramides and acylcarnitines, reflecting mitochondrial beta-oxidation defects.
- Microbiome Uniqueness: A key finding is that healthy aging is associated with a unique gut microbiome drift. As you age, your gut flora should become less like the average population and more distinct, dominated by Bacteroidesand depleted of core genera found in younger people.
Novelty: The review’s strongest contribution is the concept of “Asynchronous Aging”: the explicit recognition that different tissues age at different rates and that current clocks (like Horvath or GrimAge) are often discordant. It also elevates the “Microbiome Ageotype”—the idea that gut composition alone can predict survival outcomes in the oldest-old (80+ years), specifically linked to tryptophan metabolites (indoles) in plasma.