Evidence map›Paper›PMID 42185655›Full record

ReviewBiogerontology2026

Single-cell eQTL-based Mendelian randomization identifies immune cell subtype-specific regulators of epigenetic aging and prioritizes candidate therapeutic targets.

Chun Zhang, Jingqi Zhang

Abstract readReview
PubMed Publisher
In one paragraph

Review in Biogerontology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Chun Zhang *Chongqing Three Gorges Medical College, Chongqing, 404120, China.
Jingqi Zhang *School of Clinical Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, China. zhangjingqi@stu.cdutcm.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epigenetic aging clocks offer precise measures of biological age, yet the causal contributions of immune gene expression within specific cell subtypes to epigenetic aging remain poorly understood. By integrating single-cell eQTL data from the OneK1K cohort with GWAS summary statistics for four epigenetic clocks (HannumAge Acceleration, IEAA, PhenoAge Acceleration, and GrimAge Acceleration), we performed two-sample Mendelian randomization across diverse immune cell subtypes, followed by colocalization analysis and gene-level phenome-wide association studies. We identified 11 eGene-cell type pairs surviving Bonferroni correction, including NUCKS1 in CD4 NC T cells and NCR3 in Classic Monocytes as risk-increasing eGenes for HannumAge Acceleration, and HSPA1B in Classic Monocytes as protective across multiple clocks. ANP32E in Classic Monocytes represented the strongest risk signal for GrimAge Acceleration (OR = 2.683), while BCAS4 in CD8 EM T cells was the strongest protective association (OR = 0.683). Colocalization confirmed NUCKS1 (PP.H4 = 87%) and NCR3 (PP.H4 = 69%) as high-confidence causal eGenes, and PheWAS revealed no genome-wide significant off-target associations for the prioritized targets, supporting their specificity. These findings establish cell subtype-specific causal roles for immune gene expression in epigenetic aging and prioritize NUCKS1, NCR3, and ANP32E as candidate targets for interventions aimed at promoting healthy aging.

Indexed as

AgingEpigenesis, GeneticQuantitative Trait LociGenome-Wide Association StudyHumansMendelian Randomization AnalysisMonocytesSingle-Cell AnalysisColocalizationEpigenetic agingImmune cell subtypesMendelian randomizationSingle-cell eQTL

Identifiers

PMID42185655

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.