Identification and clinical validation of autophagy-related genes as potential biomarkers of Parkinson’s disease and their correlation with immune infiltration

Apr 2, 2026Clinical neurology and neurosurgery

Autophagy-related genes as possible markers of Parkinson's disease and their link to immune system involvement

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Abstract

A four-gene diagnostic model for Parkinson's disease achieved a favorable diagnostic performance with an AUC of 0.845.

Twenty-eight differentially expressed autophagy-related genes were identified in the study.
The model includes the genes PRKD1, CAMP, MCOLN3, and ATG9B, which may serve as diagnostic markers.
Increased expression of PRKD1, CAMP, and ATG9B was observed in PBMCs from Parkinson's disease patients compared to healthy controls.
MCOLN3 expression was found to be decreased in patients with Parkinson's disease.
Plasma levels of CAMP protein were reduced in Parkinson's disease and showed diagnostic potential with an AUC of 0.771.
The study suggests significant associations between the identified genes and immune cell subsets, indicating immune microenvironment alterations in Parkinson's disease.

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BACKGROUND: Parkinson's disease (PD) is the second most common progressive neurodegenerative disease that severely affects the quality of life and there is an urgent need to explore unique and effective diagnostic markers. The present study aimed to develop and validate a multigene combination model for the diagnosis of PD based on autophagy-related genes (ARGs) and to discover their correlation with immune infiltrating cells.

METHODS: We downloaded the dataset GSE49126 from the database and retrieved ARGs from three databases. Differentially expressed ARGs were filtered by three machine algorithms and applied to construct diagnostic models. We then analyzed the differences in immune microenvironment between PD and controls utilizing ImmuCellAI and CIBERSORT, followed by investigating the correlation between markers and immune cells to better understand the molecular interactions mechanisms. Finally, the expression of key ARGs was validated in Peripheral blood mononuclear cells (PBMC) and plasma using RT-qPCR and ELISA respectively.

RESULTS: A total of 28 differentially expressed ARGs were identified, and a four-gene diagnostic model (PRKD1, CAMP, MCOLN3, and ATG9B) was established, demonstrating favorable diagnostic performance (AUC = 0.845, 95% CI: 0.736-0.954). Immune infiltration analysis revealed alterations in the immune microenvironment in PD, and correlation analysis indicated significant associations between model ARGs and immune cell subsets. RT-qPCR validation showed increased expression of PRKD1, CAMP, and ATG9B in PBMCs from patients with PD compared with age- and sex-matched healthy controls (p < 0.05), consistent with transcriptomic findings. In contrast, MCOLN3 expression was decreased in patients with PD. Plasma CAMP protein levels were reduced in PD and demonstrated diagnostic potential (AUC = 0.771, 95% CI: 0.696-0.845).

CONCLUSIONS: An ARG-based diagnostic model comprising PRKD1, CAMP, MCOLN3, and ATG9B demonstrated potential diagnostic value for PD and revealed associations between autophagy-related signatures and immune alterations. These findings provide exploratory evidence supporting the involvement of autophagy-immune interactions in PD and warrant further validation in larger prospective cohorts.

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Identification and clinical validation of autophagy-related genes as potential biomarkers of Parkinson’s disease and their correlation with immune infiltration

Abstract

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