Evidence map›Paper›PMID 40579668›Full record

ArticleGeroScience2026

Plasma lipidomic fingerprinting enables high-accuracy biomarker discovery for Alzheimer's disease: a targeted LC-MRM/MS approach.

Xia Gao, Xiaoqin Cheng, Peipei Chen, Ling Lin, Xiaoyu Wang, Runbing Xu, Huali Shen, Qian Yang

Abstract read
In one paragraph

Article in GeroScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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.

Xia GaoDepartment of Experimental Surgery, Tangdu Hospital, The Fourth Military Medical University, Xi'an , 710038, Shaanxi, P. R. China.
Xiaoqin ChengDepartment of Neurology, Zhongshan Hospital, Fudan University, Shanghai, 200032, P. R. China.
Peipei ChenInstitutes of Biomedical Sciences, Fudan University, Shanghai, 200032, P. R. China.
Ling LinShanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Xiaoyu WangInstitutes of Biomedical Sciences, Fudan University, Shanghai, 200032, P. R. China.
Runbing XuHematology and Oncology Department, Beijing University of Chinese Medicine Affiliated Dongzhimen Hospital, Beijing, 100700, China.
Huali ShenInstitutes of Biomedical Sciences, Fudan University, Shanghai, 200032, P. R. China. shenhuali@fudan.edu.cn.
Qian YangDepartment of Experimental Surgery, Tangdu Hospital, The Fourth Military Medical University, Xi'an , 710038, Shaanxi, P. R. China. qianyang@fmmu.edu.cn.

Funding

General Medical Research Program 24YXYJ0124Innovative research community project 82221001-4Key project of National Natural Science Foundation 31930048National Key Research and Development Program 2021YFA1301601National Natural Science Foundation of China 82272174Phoenix Talent Initiation Program 2023YFJH006Science and Technology Innovation 2030 Major Projects 2022ZD0211600
6 · The paper itself

Abstract

Dysregulation of lipid metabolism is increasingly recognized as a key factor in the pathogenesis of Alzheimer's disease (AD). Unfortunately, an accurate lipidomic fingerprints in AD patients' biofluids remains challenging. A comprehensive analysis of plasma samples from 26 patients with AD and 30 healthy individuals was performed using untargeted and targeted lipidomics techniques with strict lipid annotation criteria. By monitoring characteristic fragments per precursor, we achieved precise lipid characterization and quantification for approximately 270 lipid species. Multivariate statistical analysis revealed a distinct lipid profile between AD patients and controls, with 72 lipids significantly altered (FC > 1.5 or < 0.667, VIP > 1, P < 0.05). Notably, a biomarker analysis based on the multivariate exploratory receiver operating characteristic (ROC) curve identified a comprehensive panel consisting of 10 novel lipids as potential markers for AD, achieving 98.2% accuracy with a favorable auxiliary diagnostic value (area under curve of 0.995). Additionally, the higher levels of SM(d18:1/16:0), SM(d18:1/18:1), and LPE 18:0 were strongly correlated with the clinical dementia rating (CDR) and mini-mental state examination (MMSE) scores, underscoring the therapeutic potential of lipid modulation in AD. These findings reveal the intricate relationship between lipid alterations and AD pathology and emphasize the necessity for LC-MRM/MS lipidomics with rigorous criteria in the discovery of reliable biomarkers, enriching our understanding of lipid roles in neurodegenerative processes and informing future mechanistic investigations and drug target development.

Indexed as

Alzheimer DiseaseLipidomicsLipidsAgedAged, 80 and overBiomarkersCase-Control StudiesChromatography, LiquidFemaleHumansLipid MetabolismMaleMass SpectrometryMiddle AgedROC CurveBiomarkersLipidsAlzheimer's diseaseBiomarkersMachine learningTargeted lipidomics

Identifiers

PMID40579668
PMCPMC12972415

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.