New research explores how antimicrobial exposure affects Parkinson’s disease risk

Large study reveals surprising links between common antibiotics, antifungal treatments, and Parkinson’s risk—could certain medications offer protection?

Study: Effects of antimicrobial exposure on the risk of ParkinsonStudy: Effects of antimicrobial exposure on the risk of Parkinson's disease. Image Credit: AlexandrMusuc/Shutterstock.com

In a recent study published in the Parkinsonism & Related Disorders, a group of researchers evaluated the impact of antimicrobial exposure on the risk of developing Parkinson's disease (PD) (a disorder that affects movement, causing tremors, stiffness, and balance issues) using a nested case-control study design.

Background 

PD is affecting over 6.1 million people worldwide, with prevalence projected to exceed 12 million by 2040. Genetic and environmental factors contribute to PD's etiology, and disruption of the intestinal microbiome (dysbiosis) may play a critical role.

Research shows that aggregated alpha-synuclein can propagate from the gut to the brain via the vagus nerve, triggering inflammation and neuronal loss. Recent studies suggest that antimicrobial use alters gut microbiome diversity, potentially increasing PD risk.

However, further research is needed to explore these associations across diverse populations and account for confounding factors like infections.

About the study 

A case-control study was conducted utilizing data from the Clinical Practice Research Datalink GOLD (CPRD GOLD), a comprehensive, population-based database that provides demographic and clinical information from a United Kingdom (UK)- wide network of electronic health records spanning over 1,700 general practices since 1987.

The study focused on outpatient prescriptions recorded from 1995 to 2019. Prescriptions issued by general practitioners are automatically logged, ensuring accurate tracking of drug usage and corresponding diagnoses.

In the UK, antibiotics are exclusively available through prescriptions, enhancing the reliability of the data for drug safety research. The study received approval from both the Rutgers Institutional Review Board and the CPRD Independent Scientific Advisory Committee.

All registered cases of PD were identified using specific Read codes, requiring participants to be at least 25 years old with a minimum of 12 months of baseline data. Exclusion criteria included prior diagnoses of various forms of Parkinsonism and exposure to specific dopamine-modulating agents.

Based on several demographic factors, each PD case was matched to up to 15 control subjects without a PD history.

Antimicrobial exposure was defined by prescriptions filled at least 12 months before the index date, categorized by type, duration, and frequency of prescriptions. Generalized estimating equations were used for statistical analysis, and findings were presented as adjusted odds ratios with confidence intervals. Significant results were determined by false discovery rate-adjusted p-values.

Study results 

The study included 12,557 PD cases and 80,804 matched control subjects. The median follow-up time was 26.0 years (interquartile range (IQR) 17.4-40.4) for PD cases and 25.3 years (IQR 17.1-43.0) for controls.

The average age was similar between groups, with PD cases having a mean age of 73.6 years (± 9.82) and controls at 73.4 years (± 9.56). Notably, chronic obstructive pulmonary disease (COPD) was more prevalent among control subjects (5.90%) compared to PD cases (3.97%, p < 0.0001).

Additionally, respiratory infections occurred more frequently in the control group, averaging 1.30 occurrences per person compared to 1.06 in PD cases (p < 0.0001).

An inverse dose-response relationship was observed between the number of penicillin courses prescribed and PD risk across multiple periods. For those receiving five or more penicillin courses 1-5 years prior to the index date, the odds ratio (OR) was 0.85 (95% CI 0.76–0.95, p = 0.043).

Similarly, the OR was 0.84 (95% CI 0.73-0.95, p = 0.059) for 6-10 years prior and 0.87 (95% CI 0.74-1.02, p = 0.291) for 11-15 years prior. The number of macrolide courses also showed an inverse association with PD risk during the 1-5 year exposure period, though this was not statistically significant (OR 0.89-0.91, 95% CI: 0.79-0.99, adjusted p = 0.140-0.167).

A similar pattern was noted for cephalosporins, with dose-related decreases in ORs for exposures occurring 6-10 years and 11-15 years prior, but these did not reach statistical significance.

In contrast, there was a significant association between antifungal courses and increased PD risk, particularly with exposure to two or more courses within 1-5 years before diagnosis (OR 1.16, 95% CI: 1.06-1.27, p = 0.020).

Furthermore, an increased risk of developing PD was linked to the number of genitourinary tract infections (beta = 0.08, adjusted p = 0.003), skin infections (beta = 0.07, adjusted p = 0.003), and the overall infection count (beta = 0.06, adjusted p = 0.01) within the same timeframe.

No significant dose-response relationship was found between tetracycline exposure and PD risk, while data regarding lincosamide and imidazole exposure were inconclusive due to a limited number of exposed subjects. Sensitivity analyses yielded results consistent with the primary findings, increasing the accuracy of the study's conclusions.

Conclusions 

To summarize, in the study, adults prescribed multiple courses of penicillins over the last 15 years exhibited a modestly reduced risk of PD. Conversely, those receiving two or more courses of antifungal drugs in recent years had a modestly increased risk of PD.

The adjusted OR for PD after exposure to antifungal medications was 1.16. These findings highlight the unexpected protective effect of penicillins and raise questions about the role of the mycobiome in PD, suggesting that antifungal exposure may serve as a marker rather than a trigger for future disease.

Journal reference:
Vijay Kumar Malesu

Written by

Vijay Kumar Malesu

Vijay holds a Ph.D. in Biotechnology and possesses a deep passion for microbiology. His academic journey has allowed him to delve deeper into understanding the intricate world of microorganisms. Through his research and studies, he has gained expertise in various aspects of microbiology, which includes microbial genetics, microbial physiology, and microbial ecology. Vijay has six years of scientific research experience at renowned research institutes such as the Indian Council for Agricultural Research and KIIT University. He has worked on diverse projects in microbiology, biopolymers, and drug delivery. His contributions to these areas have provided him with a comprehensive understanding of the subject matter and the ability to tackle complex research challenges.    

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