Evidence mapPaperPMID 40726806Full record

ArticleLymphatics2025

Biological Age, Aging Clocks, and the Interplay with Lymphoid Neoplasms: Mechanisms and Clinical Frontiers.

Xiaocan Wu, Hanna Liu, Kejun Ying

Abstract read
In one paragraph

Article in Lymphatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xiaocan WuCollege of Pharmacy, Fujian University of Traditional Chinese Medicine, Fuzhou 350108, China.
Hanna LiuSchool of Pharmacy, Massachusetts College of Pharmacy and Health Sciences, Boston, MA 02115, USA.
Kejun YingHarvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA.ORCID 0000-0002-1791-6176

Funding

NIA NIH HHS F99 AG088431
6 · The paper itself

Abstract

Lymphoid neoplasms (LN), a diverse group of malignancies arising from lymphocytes, exhibit a striking increase in incidence with chronological age, suggesting a deep connection with the aging process. While chronological age remains a primary risk factor, the concept of biological age, reflecting an individual's physiological state and susceptibility to age-related diseases, offers a more nuanced understanding of this relationship. Aging clocks, particularly epigenetic clocks based on DNA methylation, provide quantitative measures of biological age and have revealed associations between accelerated aging and increased cancer risk, including LN. Immunosenescence, the age-related decline in immune function characterized by thymic involution, altered lymphocyte populations, and chronic inflammation (inflammaging), appears to be a key mechanistic link between aging and LN development, potentially providing a more accurate predictor of cancer risk than mutation accumulation alone. Accelerated biological aging, measured by various clocks, correlates with LN risk and progression (e.g., in chronic lymphocytic leukemia), and may influence treatment tolerance and outcomes, particularly in older adults who are often burdened by frailty and comorbidities like sarcopenia. Integrating biological age assessments into clinical practice holds promise for refining diagnosis, prognosis, and personalizing treatment strategies (including guiding intensity and considering anti-aging interventions), and improving outcomes for patients with LN. This review synthesizes the current understanding of the intricate relationship between LN, immunosenescence, biological age, and aging clocks, highlighting clinical implications and key future research directions aimed at translating these insights into better patient care.

Indexed as

agingbiological agelymphoid neoplasmsomics

Identifiers

PMID40726806
PMCPMC12290914

What Socratic holds

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Registered trials

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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.