Evidence map›Paper›PMID 41121378›Full record

ArticleGenome medicine2025

Polygenic risk for Alzheimer's disease in healthy aging: age-related and APOE-driven effects on brain structures and cognition.

Hao-Jie Chen, Xinyi Dong, Yichen Wang, Kexin Wang, Guozheng Feng, Tianyu Bai, Mingkai Zhang, Kaiyu Gan, Jun-Jie Peng, Weijie Huang and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Cognitive-behavioral phenotypes inFrontiers in molecular neuroscience · 2026
    Article
  4. 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

13 authors.

Hao-Jie ChenState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.ORCID 0000-0002-4362-1056
Xinyi DongState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.ORCID 0000-0003-0068-5137
Yichen WangState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.ORCID 0009-0006-4283-7986
Kexin WangState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.ORCID 0009-0004-9567-5306
Guozheng FengTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA.ORCID 0000-0002-6937-8592
Tianyu BaiState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.ORCID 0009-0002-9357-5497
Mingkai ZhangDepartment of Neurology, XuanWu Hospital of Capital Medical University, Beijing, China.ORCID 0009-0001-9846-123X
Kaiyu GanFaculty of Psychology, Beijing Normal University, Beijing, China.ORCID 0009-0009-0745-9918
Jun-Jie PengDivision of Gene Expression Dynamics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan.ORCID 0009-0009-0252-5939
Weijie HuangCollege of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, MOE Key Laboratory of Brain Computer Intelligence Technology, Nanjing, 211106, China.
Zhanjun ZhangState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
Ni ShuState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China. nshu@bnu.edu.cn.ORCID 0000-0003-2420-2910
Guolin MaDepartment of Radiology, China-Japan Friendship Hospital, Beijing, 100029, China. maguolin1007@qq.com.

Funding

STI2030-Major Projects 2022ZD0213300
6 · The paper itself

Abstract

backgroundAlzheimer's disease (AD) is characterized by progressive neurodegeneration and cognitive decline with age. The genetic architecture of AD involves multiple loci, including the apolipoprotein E gene (APOE). The polygenic risk scores for AD (AD-PRS) provide a comprehensive genome-wide assessment of AD risk, yet their age-related effects on brain structures and cognitive function in cognitively unimpaired individuals remain largely undefined.

methodsWe analyzed cognitively unimpaired, genetically unrelated Caucasians from the UK Biobank (N = 21,236, 64.5 ± 7.6 years). AD-PRS was derived using a Bayesian approach incorporating approximately 5 million genetic variants (UK Biobank's standard PRS). Brain structures were measured with regional gray matter (GM) volumes and tract-wise microstructural white matter (WM) integrity. Cognitive performance was evaluated with executive function, visuospatial function, reasoning, and memory. Sliding window analyses were performed to investigate age-related polygenic effects on brain structures, and mediation analyses tested whether structural changes mediated the gene-cognition relationship across different age groups. Analyses were replicated using two custom PRSs-one including APOE and the other excluding APOE regions-calculated with the clumping-and-thresholding approach.

resultsHigh AD-PRS was associated with accelerated GM atrophy (particularly in the hippocampus, thalamus, and parahippocampus), increased cerebral ventricular volume, and reduced WM integrity (especially in the fornix, cingulum, and superior fronto-occipital fasciculus). These polygenic effects demonstrated significant age-related amplification (p

conclusionsHigh polygenic risk for AD may be associated with accelerated cognitive decline in healthy aging, mediated by structural changes within hippocampal-thalamic regions and their connecting WM tracts. We provide insights into the early pathogenesis of AD and support the potential for age-targeted screening and early intervention for individuals at high genetic risk.

Indexed as

Alzheimer DiseaseApolipoproteins EBrainCognitionGenetic Predisposition to DiseaseHealthy AgingMultifactorial InheritanceAgedAged, 80 and overFemaleGray MatterHumansMagnetic Resonance ImagingMaleMiddle AgedRisk FactorsApoE protein, humanApolipoproteins EAlzheimer’s diseaseAPOEBrain agingCognitive declinePolygenic risk scoreUK Biobank

Identifiers

PMID41121378
PMCPMC12539216

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.