Evidence map›Paper›PMID 41478820›Full record

SynthesisThe journal of prevention of Alzheimer's disease2026

Multi-omics integration reveals shared genetic architecture between metabolic markers and gray matter atrophy in Alzheimer's Disease.

Piaoran Wang, Xiangzheng Wu, Fengyu Sun, Hongchuan Zhang, Yurong Jiang, Qiuhui Wang, Hao Ding, Yujing Zhou, Feng Liu, Huaigui Liu

Abstract readMeta-Analysis
In one paragraph

Synthesis in The journal of prevention of Alzheimer's disease, 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. Metabolic Syndrome and Dementia Risk in Older Adults: A Narrative Review.The Kaohsiung journal of medical sciences · 2026
    Review
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

10 authors.

Piaoran WangDepartment of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Xiangzheng WuDepartment of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Fengyu SunDepartment of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Hongchuan ZhangDepartment of Radiology, Yijishan Hospital of Wannan Medical College, Wuhu, Anhui, China.
Yurong JiangDepartment of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Qiuhui WangDepartment of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Hao DingDepartment of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China; School of Medical Imaging, Tianjin Medical University, Tianjin, China.
Yujing ZhouDepartment of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China. Electronic address: yjzhou0613@163.com.
Feng LiuDepartment of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China. Electronic address: fengliu@tmu.edu.cn.
Huaigui LiuDepartment of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China; Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA. Electronic address: liuhuaigui@tmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by widespread gray matter volume (GMV) reductions. Emerging evidence links glucose and lipid metabolic dysregulation to AD pathophysiology. However, the extent to which AD-related GMV alterations and metabolic traits share a common genetic basis remains poorly understood.

objectivesTo explore the shared genetic architecture between GMV alterations in AD and metabolites related to glucose and lipid metabolism, aiming to provide biological insights into the prevention and treatment of AD.

designThis is a multimodal, cross-disciplinary study combining neuroimaging meta-analysis, transcriptome-neuroimaging association analysis, conjunctional false discovery rate (conjFDR) analysis, and functional enrichment analysis to identify the shared genetic architecture between AD-related brain structural alterations and metabolic traits.

settingPublic databases and European populations.

participantsThe meta-analysis included 49 studies (1945 CE patients and 2598 controls). The largest genome-wide association study (GWAS) summary statistics were used for AD (N MEASUREMENTS: We conducted a voxel-based morphometric meta-analysis of GMV in AD by systematically reviewing 49 neuroimaging studies, identified through a literature search in PubMed and Web of Science using a predefined search strategy. Building upon these neuroanatomical findings, we performed a transcriptome-neuroimaging association analysis using data from the Allen Human Brain Atlas to identify genes spatially correlated with GMV alterations. To further explore the shared genetic architecture, we integrated GWAS summary statistics for AD and five metabolic markers using conjFDR analysis. Finally, functional enrichment analyses were performed to elucidate the biological relevance of the identified genes through this integrative framework.

resultsConsistent GMV reductions in AD were observed in the bilateral middle temporal gyrus, right superior temporal gyrus, and other key subcortical regions. The conjFDR analysis identified 20, 17, 78, 87, and 82 genes shared between AD-related GMV reductions and GLU, HbA1c, HDL-C, LDL-C, and TG, respectively. Notably, 6 genes were shared across all five metabolic markers. Enrichment analysis implicated these genes in biological processes related to Aβ aggregation and phosphatidylinositol metabolism.

conclusionsThis study reveals a convergent genetic architecture underlying AD-related GMV atrophy and metabolic dysfunction. These findings may offer novel insights into the molecular interplay between systemic metabolism and neurodegeneration in AD and highlight potential targets for therapeutic strategies.

Indexed as

Alzheimer DiseaseGray MatterAtrophyBiomarkersBrainGenome-Wide Association StudyGlucoseHumansMultiomicsNeuroimagingBiomarkersGlucoseAlzheimer’s diseaseGene expressionGenome-wide association studiesGray matter volumeMetabolic markers

Identifiers

PMID41478820
PMCPMC12869038

What OpenQuestion holds

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LicenceCC BY
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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.