Evidence map›Paper›PMID 42365266›Full record

ArticleBMC microbiology2026

Integrated analysis of gut microbiota, serum metabolomics, and proteomics reveals novel associations with clinical symptoms in patients with cerebral infarction.

Na Li, Jun Ma, Hui Yan, Jiye Liang, Xinwei Wu, Xiaolin Yu, Mei Lu, Xingbang Wang

Abstract read
In one paragraph

Article in BMC microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Na LiDepartment of Dermatology, Jinan Central Hospital, Jinan, Shandong, China.
Jun MaDepartment of Geriatric Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Hui YanDepartment of Neurology, Yucheng People's Hospital, Dezhou, Shandong, China.
Jiye LiangDepartment of Neurology, Yucheng People's Hospital, Dezhou, Shandong, China.
Xinwei WuDepartment of Geriatric Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Xiaolin YuDepartment of Geriatric Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Mei LuDepartment of Geriatric Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Xingbang WangDepartment of Geriatric Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China. 813142708@qq.com.

Funding

the Natural Science Foundation of Shandong Province of China ZR2021MH241
6 · The paper itself

Abstract

backgroundCerebral infarction (CI) is a major cause of adult disability and mortality worldwide. Mounting evidence supports the critical role of the gut-brain axis in cerebrovascular disease progression. This study aimed to characterize the alterations in gut microbiota, serum metabolome, and serum proteome in patients with CI, and to identify multi-omics signatures associated with clinical symptoms.

methodsA total of 20 CI patients and 20 healthy controls (HC) were enrolled. Fecal microbiota was profiled using 16 S rRNA gene high-throughput sequencing. Serum metabolomics and proteomics were analyzed using ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and data-independent acquisition (DIA) proteomics, respectively. Spearman correlation and multi-omics integration were applied to explore the associations among microbiota, metabolites, proteins, and clinical indicators.

resultsCI patients displayed significant gut microbiota dysbiosis, with a markedly lower gut microbiota health index (GMHI) and higher microbiota disorder index (MDI) compared with HC (P < 0.001). The genera g_norank_o_RF39 and Oxalobacter were significantly enriched in CI patients, whereas Clostridium_sensu_stricto_1 and Agathobacter were enriched in HC. Metabolomic analysis identified 445 differential metabolites, mainly involved in glycerophospholipid metabolism, phenylalanine metabolism, and caffeine metabolism. Proteomic analysis revealed 140 differentially expressed proteins linked to inflammatory responses, calcium signaling, and NF-κB signaling. Multi-omics integration showed that signature gut microbiota was strongly correlated (P < 0.005) with key serum metabolites and proteins implicated in CI pathogenesis.

conclusionsThis integrated multi-omics study revealed distinct gut microbiota, serum metabolomic, and proteomic alterations in CI patients. The microbiota-metabolite-protein regulatory axes provide novel insights into the gut-brain axis in CI and may serve as potential diagnostic biomarkers or therapeutic targets.

Indexed as

Cerebral InfarctionGastrointestinal MicrobiomeMetabolomicsProteomicsAgedBacteriaBiomarkersDysbiosisFecesFemaleHumansMaleMetabolomeMiddle AgedMultiomicsProteomeBiomarkersProteomeRNA, Ribosomal, 16SCerebral infarctionGut–brain axisGut microbiotaInflammationMetabolomicsMulti-omics integrationProteomics

Identifiers

PMID42365266
PMCPMC13573331

What Socratic holds

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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 Socratic graph.