ArticleBiogerontology2025
A multi-tissue integration of immunocytes and inflammaging biomarkers predicts biological age through LASSO-optimized modeling.
Article in Biogerontology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Immunosenescence, a recognized hallmark of aging, is characterized by imbalances in immunocyte populations and a state of chronic inflammation. However, the tissue-specific dynamics of these changes and their potential as predictive biomarkers for aging remain poorly characterized. In this study, we established a multi-tissue immunological signature as a robust predictor of biological age by integrating immunocyte and cytokine profiling. Using Sprague-Dawley (SD) rats from five age groups (1-12 months), we systematically quantified 45 immunocyte subsets across peripheral blood, mesenteric lymph nodes, thymus, and spleen using flow cytometry, and profiled 22 serum cytokines/chemokines via Flexible Multi-Analyte Profiling (xMAP). Firstly, classic age-dependent shifts were observed across our rat samples, including progressive thymic involution and depletion of peripheral T-cells. Cytokine levels exhibited age-related chronic inflammation progression, marked by elevated IL-1α, granulocyte colony-stimulating factor (G-CSF), and TNF-α. To integrate these multidimensional datasets into a predictive aging metric, we employed Least Absolute Shrinkage and Selection Operator (LASSO) regression, selecting 22 biomarkers through regularization (λ = 0.111). The integrated model combining cellular and cytokine data demonstrated superior performance (training R
Indexed as
Identifiers
41359082What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.