Alterations in Gut Microbiota and Plasma Metabolites: A Multi-omics Study of Mild Cognitive Impairment in Parkinson's Disease

Zihao LinYangdanyu LiYuning LiuBo YangPeixiao YinChengyang GuanYating FangLiying YangKun ZanGuiyun CuiLu YuXiaojie Wang^*Chuanying Xu^*

• The Affiliated Hospital of Xuzhou Medical University, Xuzhou, China

Introduction: Emerging evidence suggests that gut microbiota and plasma metabolites may be associated with progression of Parkinson's disease (PD). The interplay between gut microbiota and plasma metabolites in influencing the progression of cognitive impairment in PD requires further exploration. Our objective was to investigate the roles of gut microbiota and plasma metabolites in PD cognitive impairment. Methods: We recruited 100 individuals with PD and 50 healthy controls (HCs). After excluding participants based on education level and cognitive screening criteria, the final cohort comprised 38 PD patients and 40 HCs. Fecal and plasma specimens were examined. Cognitive function was assessed via the Montreal Cognitive Assessment (MoCA). Gut microbiota was analyzed through 16S rRNA sequencing, and plasma metabolites were evaluated via Liquid Chromatography–Mass Spectrometry (LC-MS). Using Spearman correlation to analyze the association between gut microbiota and plasma metabolites. Results: PD patients with mild cognitive impairment (PD-MCI) exhibited distinct microbial and metabolic profiles compared to PD patients with normal cognition (PD-NC). Both Gut Microbiota Health Index (GMHI) and Microbial Dysbiosis Index (MDI) indicated significant gut dysbiosis in PD-MCI. Multi-algorithm differential abundance analysis identified g__Eggerthella as a core depleted genus in PD-MCI, consistently validated across both LEfSe and MaAsLin2 analyses. Additional microbial alterations included depletion of Short-Chain Fatty Acids (SCFA)-producing genera (g__Blautia, g__Lachnoclostridium, g__Erysipelatoclostridium, g__norank_f__norank_o__Oscillospirales, g__Megasphaera, and g__Lactococcus) and enrichment of g__Senegalimassilia in PD-MCI. Metabolite analysis revealed that phenylalanine metabolism (including phenylacetylglutamine, 2-hydroxycinnamic acid, N-acetyl-L-phenylalanine, and phenylacetylglycine) and PPAR signaling pathways (including 8-hydroxy-5Z,9E,11Z,14Z-eicosatetraenoic acid) were downregulated in the PD-MCI group, while choline metabolism in cancer (including PC(18:1(11Z)/18:3(6Z,9Z,12Z)) and LysoPC(18:3(6Z,9Z,12Z)/0:0)) was upregulated. Notably, phenylacetylglutamine demonstrated robust diagnostic potential (AUC=0.8222), emerging as a promising biomarker for PD-MCI. Correlation analysis revealed significant associations between key microbial taxa (particularly g__Eggerthella and SCFA-producing genera) and metabolites (phenylacetylglutamine, and uridine 2',3'-cyclic phosphate), suggesting their interactive role in PD cognitive impairment through gut-brain axis mechanisms. Conclusions: Our multi-omics study revealed distinct gut microbiota and metabolite alterations in PD with cognitive impairment, highlighting gut-brain axis dysfunction. Key microbial and metabolic markers demonstrated diagnostic potential, providing new insights into the pathophysiology of PD-related cognitive decline and potential targets for future therapeutic strategies.