AUTHOR=Ye Shisheng , Feng Kaiyan , Zeng Guofang , Cai Jiaxin , Liang Lijuan , Chen Jiaxin , He Qishan , Mai Jianhui , Wu Qiaoling , Chen Chunwan , Huang Haifeng , Yuan Li , Chen Hai , Li Yizhong , Li Hao , Zhang Xiong 

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

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 19 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2025.1607242

DOI=10.3389/fnins.2025.1607242

ISSN=1662-453X

ABSTRACT=IntroductionAlthough 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.MethodsThis study integrated untargeted metabolomics with MRI phenotyping to delineate metabolic perturbations of WMH in arteriosclerotic cerebral small vessel disease (aCSVD) patients (n = 30) versus controls (n = 29). Plasma metabolic profiles were analyzed using UPLC-MS. Weighted gene correlation network analysis (WGCNA) evaluated associations between metabolite clusters and clinical traits, including DWMH volume, PVWMH volume and total WMH (TWMH) volume.ResultsWe 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.ConclusionThese 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.