Evidence map›Paper›PMID 41521072›Full record

ReviewBMB reports2026

Genetic architecture of human aging and longevity: Insights from genome-wide association studies.

Dabin Yoon, Jungsoo Gim

Abstract readReview
In one paragraph

Review in BMB reports, 2026. 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

2 authors.

Dabin YoonWell-aging Medicare Institute (G-LAMP Project Group), Chosun University, Gwangju 61452, Korea.
Jungsoo GimWell-aging Medicare Institute (G-LAMP Project Group), Chosun University, Gwangju 61452; Department of Biomedical Science, Chosun University, Gwangju 61452l; Brain Korea FOUR Department of Integrative Biological Sciences, Chosun University, Gwangju 61452, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aging represents a fundamental evolutionary feature shared across all living organisms, intrinsically coupled with development and lifespan. It is orchestrated by a complex polygenic architecture involving numerous small-effect variants distributed across diverse biological pathways, giving rise to striking interindividual variation in aging trajectories and lifespan. Over the past decade and a half, genome-wide association studies (GWAS) have uncovered multiple loci associated with lifespan, healthspan, exceptional longevity, and aging, converging on key biological processes such as lipid metabolism, inflammation, insulin/IGF signaling, and DNA repair. These discoveries have illuminated conserved molecular networks underlying the regulation of aging and longevity. Nevertheless, the identified variants collectively account for only a modest fraction of heritability, underscoring that aging and longevity arise from the cumulative and coordinated actions of myriad common alleles within complex biological networks. In this minireview, we synthesize major genetic insights from GWAS of aging and longevity, delineate recurrent pathways and molecular themes, and discuss how these findings refine our understanding of the genomic foundations of lifespan variation. We further highlight outstanding challenges, including phenotypic heterogeneity, ancestry-specific effects, and the limited predictive power of current models, and propose conceptual directions for future research aimed at establishing a more comprehensive and mechanistic framework for the genetic architecture of human aging and healthy longevity. [BMB Reports 2026; 59(1): 2-12].

Indexed as

AgingLongevityGenome-Wide Association StudyHumans

Identifiers

PMID41521072
PMCPMC12867182

What OpenQuestion holds

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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.