Table 1_High-efficacy serum biomarkers PCSK9 and LCAT predict cognitive impairment in Parkinson’s disease.docx

BackgroundCognitive impairment (CI) is a prevalent and debilitating non-motor symptom in Parkinson’s disease (PD), yet reliable early diagnostic biomarkers are lacking. This study aimed to identify serum biomarkers associated with PD-CI and investigate the synergistic contributions of lipid metabolism and inflammatory signaling.
MethodsIn this retrospective, cross-sectional study, six candidate proteins (INPP5D, FLNA, ICAM-1, PCSK9, JAK1, and LCAT) were selected based on our previously published discovery-phase serum proteomics analysis and were quantified via ELISA in an independent cohort of 75 PD patients and 35 age-matched healthy controls (HCs). All participants underwent comprehensive cognitive assessments (MoCA, MMSE, CDR). Multivariate regression, receiver operating characteristic (ROC) analysis, and bioinformatics tools were employed to evaluate diagnostic potential and pathway associations.
ResultsPD patients showed significantly lower MoCA and MMSE scores than HC, accompanied by elevated serum ICAM-1, PCSK9, and JAK1, and decreased INPP5D and FLNA. Notably, as MoCA scores declined, serum ICAM-1, PCSK9, JAK1, and LCAT levels gradually increased, while INPP5D and FLNA decreased. ROC analysis indicated that these biomarkers, particularly PCSK9 and LCAT, effectively distinguished PD-NC from PD-CI. Bioinformatics analyses highlighted focal adhesion and JAK-STAT signaling as key pathways, with ICAM1 and ITGB2 as central nodes in the protein–protein interaction network.
ConclusionAll six serum biomarkers showed potential in distinguishing PD-NC from PD-CI, with PCSK9 and LCAT being the most effective. The findings propose a pathogenic cascade integrating neuroinflammation, lipid metabolism, and cell adhesion dysfunction, offering new mechanistic insights and potential avenues for early diagnosis and therapeutic intervention in PD-CI.