Research overview
The text below is the source article’s original abstract under a verified reuse license. cc by
BackgroundInflammatory mechanisms are critically engaged in the pathogenesis of Parkinson's disease (PD). The objective of this research was to detect circulating inflammatory proteins that potentially elevate the susceptibility to PD.MethodsA two-sample Mendelian randomization (MR) analysis was performed to determine the causal effects of 91 circulating inflammatory proteins (14,824 participants) on PD (33,674 cases and 449,056 controls) by using genome-wide association study (GWAS) summary data. The MR analysis utilized three complementary approaches: inverse variance weighted (IVW), weighted median, and MR-Egger. Among them, IVW was the principal method. Additionally, we utilized the Drug-Gene Interaction Database (DGIdb) to select potential therapeutic targets for proteins associated with PD.ResultsOur MR analysis revealed that six circulating inflammatory proteins were associated with PD. Three of them conferred a protective effect against PD, including TNFRSF9 (odds ratio [OR]: 0.83, 95% confidence interval [CI]: 0.74-0.92, p = 5.09 × 10-4), Flt3L (OR: 0.89, 95% CI: 0.81-0.99, p = 0.026), and TGF-α (OR: 0.86, 95% CI: 0.75-0.99, p = 0.04). Three additional proteins were connected with an increased risk of PD, namely, IL-18 (OR: 1.13, 95% CI: 1.02-1.24, p = 0.016), CD6 (OR: 1.08, 95% CI: 1.01-1.16, p = 0.023), and IL-17A (OR: 1.18, 95% CI: 1.01-1.38, p = 0.033).ConclusionOur research revealed the pathogenic contribution of several inflammatory proteins to PD development, providing new perspectives on the mechanisms and therapy of PD.
Scientific assessment
Research question
Assess the question within the original study’s scope.
Methods & sample
Check the source article for study design and sample details.
Key findings
An editorially approved findings summary is not yet published for this record.
Limitations
Generalizability, bias and clinical meaning require separate assessment.
Methods, samples and clinical conclusions are not inferred from bibliographic metadata.