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March 10, 2026Cellular and Molecular Neurobiology3 citationsOpen Access

Peripheral Inflammatory Biomarkers in Parkinson’s Disease: Clinical Correlations and Stratification

GJGuo-Yun JiangLFLi FanJYJinhui Yin

Key Points

  • This research aims to explore the clinical relevance and mechanistic implications of peripheral inflammatory biomarkers in Parkinson's disease.
  • Analyzed data from the Parkinson's Progression Markers Initiative (PPMI).
  • Derived six peripheral inflammatory indices from clinical assessments and biomarker data.
  • Used statistical methods including Spearman correlation and multiple linear regression to analyze associations.
  • Performed unsupervised k-means clustering to identify inflammatory clusters.
  • NLR and SII were significantly elevated in Parkinson’s disease, with NLR showing the strongest correlation with clinical symptoms.
  • Distinct inflammatory clusters were identified, with the high-inflammation cluster exhibiting worse cognitive function and motor progression.
  • Correlations were found between peripheral biomarkers and non-motor symptoms such as cognitive decline and olfactory impairment.

Abstract

Growing evidence underscores neuroinflammation's role in Parkinson's disease (PD), with accumulating evidence suggesting a potential role for peripheral inflammation. The clinical applicability and mechanistic relevance of peripheral inflammatory biomarkers in PD remain to be fully elucidated. We analyzed data from the Parkinson's Progression Markers Initiative (PPMI), including longitudinal clinical assessments, blood counts, cerebrospinal fluid (CSF) biomarkers, and genetic data. Six peripheral inflammatory indices were derived: neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI). Spearman correlation, multiple linear regression, and generalized estimating equations were employed to examine associations. Unsupervised k-means clustering was performed to identify distinct inflammatory clusters, with differences assessed using ANCOVA analysis. NLR and SII were significantly elevated in PD, with NLR showing the strongest association. Peripheral inflammatory biomarkers showed distinct clinical correlations, with NLR demonstrating associations with both non-motor (cognitive decline, olfactory impairment, and depression, p < 0.001) and motor symptoms (p < 0.001). SII, and SIRI showed correlations with motor progression (p < 0.001), while SII additionally associated with sleepiness disorders (p < 0.001). Cluster analysis identified two distinct inflammatory clusters: a high-inflammation cluster demonstrating significantly worse cognitive function (p = 0.008), olfactory impairment (p < 0.001), and autonomic dysfunction (p < 0.001) at baseline, along with accelerated motor (p = 0.038) and cognitive decline (p < 0.001) during follow-up. This high-inflammation cluster also showed elevated CSF neurodegeneration markers including pTau, tTau, NfL, and GFAP (p < 0.05). Peripheral inflammatory biomarkers show robust associations with clinical features in PD, highlighting their potential as markers associated with disease features and progression, and suggesting a basis for inflammatory-based subgrouping.

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Cite This Study

Jiang et al. (2026) studied this question.

synapsesocial.com/papers/69af95de70916d39fea4dedehttps://doi.org/10.1007/s10571-026-01708-8
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