Peripheral immune alterations are widely reported in Parkinson's disease (PD), but their biological meaning and clinical utility remain uncertain because circulating immune profiles are shaped by aging, latent infection, medication exposure, comorbidity, disease stage, and preanalytical conditions. This concept-driven narrative review examines how technically valid peripheral immune findings should be biologically interpreted and clinically qualified through an immune-context phenotyping framework. Available human evidence suggests alterations in neutrophil- and monocyte-related inflammatory indices and cellular states, α-synuclein-responsive T-cell pathways, cytotoxic and regulatory T-cell states, B-cell phenotypic alterations, and peripheral-central immune associations. Much of this evidence, however, derives from cross-sectional and cohort-dependent studies, and within the human evidence considered in this review, PD specificity remains insufficiently established for most candidate signals. An observed blood difference may reflect altered production, survival, differentiation, redistribution, denominator effects, systemic inflammatory context, or measurement-related distortion rather than a single disease mechanism. Immune-context phenotyping, therefore, integrates trait, state, disease-trajectory, measurement, and treatment contexts with biological identifiability, disease-control comparisons, cross-compartment corroboration, repeated sampling, and external validation. The framework adapts established biomarker concepts to distinguish diagnostic, prognostic, monitoring, predictive, pharmacodynamic/response, and treatment-selection claims without treating peripheral target engagement, CNS engagement, pathway modification, and clinical benefit as equivalent. Based on the human evidence considered in this review, no peripheral immune phenotype appears ready for stand-alone clinical implementation in PD. The proposed framework defines a testable path from descriptive peripheral immune associations toward biologically coherent, temporally informative, and clinically qualified phenotypes.
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Kahveci et al. (2026) studied this question.
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