Evidence map›Paper›PMID 37891827›Full record

ArticleBrain sciences2023

Alteration of Metabolic Profiles during the Progression of Alzheimer's Disease.

Wuhan Yu, Lihua Chen, Xuebing Li, Tingli Han, Yang Yang, Cheng Hu, Weihua Yu, Yang Lü

Open access · goldAbstract read
In one paragraph

Article in Brain sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.8field-weighted citation impact, top 14% of its field
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

12 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Review
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  4. Review
  5. Article
  6. Article
  7. Cell type-specific master metabolic regulators of Alzheimer's disease.bioRxiv : the preprint server for biology · 2025
    Article
  8. Article
  9. Review
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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 at 2 institutions in 2 countries.

Wuhan YuDepartment of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Lihua ChenDepartment of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Xuebing LiDepartment of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Tingli HanDepartment of Obsetric and Gyncology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Yang YangDepartment of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400716, China.
Cheng HuDepartment of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Weihua YuInstitutes of Neuroscience, Chongqing Medical University, Chongqing 400016, China.
Yang LüDepartment of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.ORCID 0000-0002-9425-2967
The Affiliated Yongchuan Hospital of Chongqing Medical University · CNUniversity of Auckland · NZ

Funding

Chongqing Medical University doctoral and postgraduate innovation project CYYY-BSYJSCXXM-202205Intelligent Medicine Program of Chongqing Medical University ZHYX2019008, ZHYX202110Key Project of Technological Innovation and Application Development of Chongqing Science & Technology Bureau CSTC2021jscx-gksb-N0020National Key R&D Program of China 2018YFC2001700Science Innovation Programs Led by the Academicians in Chongqing under Project cstc2020yszx-jscxX0006, cstc2019yszx-jscxX0004the Science and Technology Research Program Of Chongqing Municipal Education Commission KJQN20190010
6 · The paper itself

Abstract

(1) Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder that threatens the population health of older adults. However, the mechanisms of the altered metabolism involved in AD pathology are poorly understood. The aim of the study was to identify the potential biomarkers of AD and discover the metabolomic changes produced during the progression of the disease. (2) Methods: Gas chromatography-mass spectrometry (GC-MS) was used to measure the concentrations of the serum metabolites in a cohort of subjects with AD (n = 88) and a cognitively normal control (CN) group (n = 85). The patients were classified as very mild (n = 25), mild (n = 27), moderate (n = 25), and severe (n = 11). The serum metabolic profiles were analyzed using multivariate and univariate approaches. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied to identify the potential biomarkers of AD. Biofunctional enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes. (3) Results: Our results revealed considerable separation between the AD and CN groups. Six metabolites were identified as potential biomarkers of AD (AUC > 0.85), and the diagnostic model of three metabolites could predict the risk of AD with high accuracy (AUC = 0.984). The metabolic enrichment analysis revealed that carbohydrate metabolism deficiency and the disturbance of amino acid, fatty acid, and lipid metabolism were involved in AD progression. Especially, the pathway analysis highlighted that l-glutamate participated in four crucial nervous system pathways (including the GABAergic synapse, the glutamatergic synapse, retrograde endocannabinoid signaling, and the synaptic vesicle cycle). (4) Conclusions: Carbohydrate metabolism deficiency and amino acid dysregulation, fatty acid, and lipid metabolism disorders were pivotal events in AD progression. Our study may provide novel insights into the role of metabolic disorders in AD pathogenesis and identify new markers for AD diagnosis.

Indexed as

Alzheimer’s diseasemetabolic pathwaymetabolomicsserum metabolic change

Identifiers

PMID37891827
PMCPMC10605479
OpenAlexW4387639034

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.