Evidence map›Paper›PMID 40470292›Full record

ArticleFrontiers in neuroscience2025

Deep and periventricular white matter hyperintensities exhibit differential metabolic profiles in arteriosclerotic cerebral small vessel disease: an untargeted metabolomics study.

Shisheng Ye, Kaiyan Feng, Guofang Zeng, Jiaxin Cai, Lijuan Liang, Jiaxin Chen, Qishan He, Jianhui Mai, Qiaoling Wu, Chunwan Chen and 6 more

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 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. Article
  3. 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

16 authors.

Shisheng Ye *Department of Neurology, The First Affiliated Hospital, Jinan University, Guangzhou, China.
Kaiyan Feng *Department of Neurology, Maoming People's Hospital, Maoming, China.
Guofang Zeng *Department of Neurology, Maoming People's Hospital, Maoming, China.
Jiaxin CaiThe First School of Clinical Medicine, Southern Medical University, Guangzhou, China.
Lijuan LiangThe First School of Clinical Medicine, Guangdong Medical University, Zhanjiang, China.
Jiaxin ChenThe First School of Clinical Medicine, Guangdong Medical University, Zhanjiang, China.
Qishan HeThe First School of Clinical Medicine, Southern Medical University, Guangzhou, China.
Jianhui MaiDepartment of Neurology, Maoming People's Hospital, Maoming, China.
Qiaoling WuDepartment of Integrated Therapy, Maoming People's Hospital, Maoming, China.
Chunwan ChenDepartment of Neurology, Maoming People's Hospital, Maoming, China.
Haifeng HuangDepartment of Neurology, Maoming People's Hospital, Maoming, China.
Li YuanDepartment of Neurology, Maoming People's Hospital, Maoming, China.
Hai ChenDepartment of Neurology, Maoming People's Hospital, Maoming, China.
Yizhong LiDepartment of Radiology, Maoming People's Hospital, Maoming, China.
Hao LiDepartment of Neurology, The First Affiliated Hospital, Jinan University, Guangzhou, China.
Xiong ZhangDepartment of Neurology, The First Affiliated Hospital, Jinan University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Although white matter hyperintensities (WMH) are radiologically classified as deep WMH (DWMH) and periventricular WMH (PVWMH) based on spatial distribution, the distinct metabolic perturbations driving their pathogenesis remain incompletely characterized. Methods: This study integrated untargeted metabolomics with MRI phenotyping to delineate metabolic perturbations of WMH in arteriosclerotic cerebral small vessel disease (aCSVD) patients ( Results: We identified 15, 16, and 16 key metabolites meeting both differential expression and WGCNA hub criteria for DWMH, PVWMH, and TWMH, respectively. Pathway Enrichment identified α-linolenic acid and linoleic acid metabolism as common pathway perturbed across both WMH categories. Key metabolites of the pathway, including docosahexaenoic acid (DHA) and stearidonic acid (SDA), demonstrated robust inverse associations with WMH volumes in confounder-adjusted linear regression models. Notably, both WMH categories share common metabolites, particularly polyunsaturated fatty acids (PUFA), while PVWMH-specific metabolites were primarily carnitine derivatives, and DWMH-specific metabolites were prostaglandin E2 and etodolac. Conclusion: These findings offer new insights into the metabolic mechanisms underlying DWMH and PVWMH in aCSVD. However, the cross-sectional nature of the study does not allow for causal conclusions. Future longitudinal studies are needed to validate the temporal relationships between metabolic perturbations and WMH progression.

Indexed as

arteriosclerotic cerebral small vessel diseasedeep white matter hyperintensitiesperiventricular white matter hyperintensitiesuntargeted metabolomicsweighted gene correlation network analysis

Identifiers

PMID40470292
PMCPMC12133732

What Socratic 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 Socratic graph.