Exploring the role of β2-microglobulin in the relationship between physical activity and DNAm-predicted PhenoAge: Evidence from a population-based and mice single-cell RNA-sequencing study
Bibliographic record
Abstract
INTRODUCTION: Physical activity (PA) is recognized as a cornerstone of healthy aging, yet the molecular mechanisms linking PA to biological aging remain poorly understood. β2-microglobulin (β2M), an inflammatory and aging biomarker, has emerged as a potential mediator of these effects. DNA methylation (DNAm)-based biological aging indicators, such as PhenoAge, provide a means to assess the relationship between PA, β2M, and aging at the molecular level. OBJECTIVES: This study aimed to investigate whether β2M mediates the association between PA and DNAm-predicted PhenoAge. Additionally, this study sought to explore the underlying molecular mechanisms using single-cell RNA sequencing (scRNA-seq) in mice. METHODS: This study analyzed data from 936 participants in the U.S. population, assessing associations between PA, β2M levels, and PhenoAge using weighted multivariable regression and mediation models. β2M levels and PhenoAge were measured in blood samples and calculated using validated DNA methylation algorithms. To investigate molecular mechanisms, scRNA-seq was performed on peripheral blood samples from exercise and control mice. RESULTS: In fully adjusted models, higher PA levels were significantly associated with lower PhenoAge (β = -0.014, p = 0.034) and β2M levels (β = -0.006, p = 0.032). Mediation analysis revealed that β2M mediated 37.67 % of the association between PA and PhenoAge (p = 0.042). Stratified analyses showed stronger effects in males and individuals with higher body mass index (BMI). In mice, scRNA-seq analysis demonstrated that exercise modulated β2M expression and enhanced immune, inflammatory, mitochondrial, and circadian pathways, particularly in B cells and myeloid cells. CONCLUSION: This study provides evidence that β2M mediates the beneficial effects of PA on biological aging. PA promotes healthy aging through molecular and cellular mechanisms, particularly benefiting individuals with higher baseline inflammation or metabolic dysfunction. These insights advance our understanding of the interplay between PA, β2M, and aging, offering directions for interventions to promote longevity and healthspan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".