Evidence map›Paper›PMID 41645184›Full record

ArticleJournal of translational medicine2026

A phenome-wide hunt for risk factors of Alzheimer's disease: from metabolic clues to neuroimaging evidence.

Dongming Liu, Ancha Baranova, Wenxi Sun, Hongbao Cao, Bing Zhang, Fuquan Zhang, Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s Disease Metabolomics Consortium

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of translational medicine, 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

8 authors.

Dongming Liu *Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China.
Ancha Baranova *School of Systems Biology, George Mason University, Manassas, VA, 20110, USA.
Wenxi Sun *Suzhou Guangji Hospital, Suzhou Jiangsu Province, Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu Province, 215137, China.
Hongbao CaoSchool of Systems Biology, George Mason University, Manassas, VA, 20110, USA.
Bing Zhang *Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China.
Fuquan Zhang *Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China. zfqeee@126.com.ORCID http://orcid.org/0000-0003-3204-8191
Alzheimer’s Disease Neuroimaging Initiative
Alzheimer’s Disease Metabolomics Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study systematically investigated phenotypes causally associated with Alzheimer's disease (AD) across the phenome and validated the findings at cognitive and neuroimaging levels using real-world clinical data.

methodsWe performed phenome-wide Mendelian Randomization (MR) analyses on genetic proxies for over 860 disease phenotypes to identify traits causally associated with AD. Lipid metabolism-related phenotypes identified through MR were further examined in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset to assess associations with AD risk, brain structure, and cognition.

resultsMR analyses revealed a significant causal association between lipid metabolism, particularly low-density lipoprotein cholesterol (LDL-C), and the risk of AD (OR: 1.05, 95% CI: 1.03-1.07). In ADNI, higher LDL-C indicators correlated with increased AD risk, reduced hippocampal and entorhinal volumes, and poorer cognitive performance. Notably, elevated cholesterol-to-total lipid ratios in small LDL particles were negatively associated with the entorhinal-hippocampal complex. Among cognitively normal individuals, higher LDL-C indicators were associated with smaller hippocampus-amygdala transition area (HATA) and CA3 head volumes. In those with mild cognitive impairment, higher LDL-C was associated with reduced entorhinal surface area.

conclusionsOur findings suggest that disrupted LDL-C metabolism may play a causal role in the development and progression of AD.

Indexed as

Alzheimer DiseaseNeuroimagingPhenomicsAgedBrainCholesterol, LDLCognitionFemaleHumansLipid MetabolismMaleMendelian Randomization AnalysisPhenotypeRisk FactorsCholesterol, LDLAlzheimer’s diseaseHippocampusLow-density lipoproteinMendelian randomizationMetabolic syndrome

Identifiers

PMID41645184
PMCPMC12973621

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LicenceCC BY-NC-ND
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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 OpenQuestion graph.