Background
Parkinson’s disease (PD) is one of the most common neurodegenerative disorders, with a prevalence of PD exceeding 1% in the population 65 years of age and older and up to 5% in those 85 years of age and older, which creates a huge burden on public health. Currently, there is no cure for PD, and the available therapeutic options only result in a partial improvement of symptoms [
1,
2]. At least 50% of nigrostriatal neurons have already been lost by the time the clinical diagnosis of PD is made [
3]. Patients with hypertension are reported to have a 60–90% higher risk of developing PD [
4‐
6]. Additionally, hypertension is one of the most common chronic diseases globally, especially in the elderly population. Consequently, the early identification and intervention into the factors that influence PD in patients with hypertension is of the utmost importance.
In recent years, the involvement of antihypertensive therapy in the pathogenesis of PD has attracted attention. Cell and animal studies suggest that angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), and calcium channel blockers (CCBs) might have neuroprotective effects on PD [
7,
8]. On the other hand, a human cell model showed that treatment with beta-adrenoceptor blockers (BBs) led to a significant increase in the expression of α-synuclein (SNCA) mRNA levels and elevated αsynuclein protein concentrations, which might facilitate the development of PD [
9]. Epidemiological studies have examined the associations between antihypertensive agents and the risk of PD; however, the results have been inconsistent [
10]. Considering the widespread use of antihypertensive drugs and their potential as an intervenable target, it is of great interest to determine their impact on the development of PD in hypertensive patients.
Here, we intend to provide a comprehensive evaluation of the effect of antihypertensive drugs on PD by combining multiple real-world data. Pharmacovigilance data can be used to discover ADR signals. Meta-analysis is a crucial information source for evidence-based medicine and clinical decision-making since it summarizes evidence; UK Biobank provided an additional information source to enhance the credibility of the conclusions; Genome-wide association studies (GWAS); and Mendelian randomization analyses offer an opportunity to further clarify the causal relationship and underlying mechanisms linking antihypertensive drugs and PD.
Discussion
This study reports the most comprehensive assessment of the association between NBB use and PD development by analysis of the pharmacovigilance dataset, meta-analysis, the UK Biobank dataset, and MR analysis. The FAERS database, which may be subject to reporting bias, precisely directed our research focus toward NBBs when investigating the association between commonly used antihypertensive drugs and the onset of PD. While the meta-analysis and UK Biobank Cohort analysis provided a higher level of evidence for this association. Our meta-analysis of 12 studies demonstrated that NBB use was associated with a 64% increased risk of PD compared with nonusers. The result of the UK Biobank Cohort analysis was similar to the result of the meta-analysis. MR analysis identifies the long-term modulation of ADRB2 on PD risk, which further explains the possible targets of NBB triggering PD risk. Using multiple data sources, this study has consistently shown an association between the use of NBBs and an increased risk of PD.
The association between BB exposure and the development of PD has been found in many epidemiological studies. A study including 145,098 patients who received BBs, and 1,187,151 nonusers, showed that BB users had 1.51 times the risk of incident PD compared with nonusers [
22]. However, the results were inconsistent, in a case–control analysis conducted using the General Practice Research Database in the UK, it was observed that the utilization of BBs did not significantly modify the PD risk (OR, 1.16; 95% CI 0.95–1.41) [
23]. The results of our study indicate that an elevated risk of PD was not observed across all BBs, but rather limited to NBBs. Consistent with our research, Gronich et al. conducted a nested case–control study involving a cohort of 1,762,164 individuals. Their investigation similarly revealed variations in the risk of PD across different subtypes of BBs, with the utilization of NBBs being linked to an elevated risk of PD (RR, 2.04; 95% CI, 1.90–2.20) [
29]. In addition, a nested case–control study involving 2225 newly diagnosed PD patients revealed a lack of significant association between PD and BBs (OR, 1.05; 95%CI, 0.91–1.20), except for propranolol, an NBB (OR, 2.11; 95%CI, 1.38–3.23) [
20].
Several studies suggest that the increase in the risk of PD associated with NBB use can be explained by reverse causation. For instance, Hopfner et al. proposed that the increased risk of PD could be attributed to protopathic bias, as prodromal PD commonly presents with a non-specific action tremor that is often treated with NBBs, particularly propranolol [
21]. In our sensitivity analyses, the findings remained consistent even after excluding patients who exhibited tremors before the date of Parkinson’s disease diagnosis. Similarly, a secondary analysis by Gronich et al. restricted the patient population to those without essential tremors at baseline and found that the effect remained significant (RR for propranolol 1.90; 95% CI 1.72–2.09) [
29]. To augment the reliability of our findings, we conducted an MR analysis. Noteworthy aspects of this analysis encompass the utilization of genetic variants within genes responsible for encoding drug targets as proxies for the potential impact of BBs. This approach effectively mitigates confounding factors and eliminates the possibility of reverse causation bias. The MR analysis revealed a significant reduction in the risk of PD associated with elevated expression of the ADRB2 gene in blood samples. Conversely, no correlation was observed between the expression of the ADRB1 gene and the risk of developing PD.
These findings are supported by mechanistic research. In human SK-N-MC neuroblastoma cells, it has been demonstrated that ADRB2 agonists decrease the abundance of SNCA mRNA and the production of alpha-synuclein protein. Conversely, ADRB2 antagonists have been shown to increase the expression of SNCA, leading to increased oxidative stress in mitochondria, dopaminergic neurodegeneration, and an elevated risk for PD [
9]. It is important to note that SBBs specifically target ADRB1 receptors without affecting ADRB2 receptors. While NBBs block both ADRB1 and ADRB2 receptors. This provides a more comprehensive justification for our findings in observational studies, which demonstrated a higher risk of developing PD associated with the use of NBBs rather than SBBs.
Hypertension has been identified as a risk factor for PD [
30]. However, the current evidence does not support the idea that existing antihypertensive medications can effectively reduce the risk of PD. Even in our study, NBBs were associated with increased risk for PD. In light of this, it becomes even more meaningful to focus on preventive measures targeting hypertension through lifestyle modifications and other non-pharmacological approaches. On the other hand, individuals with pre-existing hypertension, especially those with additional risk factors for PD, should consider alternative antihypertensive treatment options whenever possible, due to the potential risk of PD associated with NBBs.
Strengths and limitations
There are several strengths in our study. Analyzing real-world pharmacovigilance data provides an additional information source. Meta-analysis can make significant contributions to issues by risk for various antihypertensive drugs combining the results from current epidemiological studies. Due to the large number of participants and cases in the UK Biobank data, we were able to compare the risk of developing PD with an active control and evaluate the association between various antihypertensive drugs and PD development. In addition, our data were collected before diagnosis, avoiding potential recall and selection biases as well as misclassification during follow-up. Finally, robust sensitivity analyses also increased our confidence in the results. More importantly, we observed consistent associations between NBBs and the risk of PD across 3 independent approaches from the meta-analysis, pharmacovigilance database, and UK biobank. With the uniform results, Mendelian randomization analysis which employed genetic variation as an instrumental variable to discover and quantify causation was also used, thereby overcoming the impact of possible confounding and reverse causality.
This study had some limitations that need to be considered in the interpretation of the findings. First, it was an observational study based on multiple sources, therefore, reverse causality might exist. However, the study rigorously adjusted for confounding factors and validated the association through Mendelian randomization analysis, thereby addressing this issue to the best extent possible. Second, in the FAERS data, the reported PD may have also been owing to other reasons aside from the administration of antihypertensive agents despite our limiting the analysis to participants with hypertension. Third, there was substantial statistical heterogeneity among the included studies in our meta-analysis which must be noted even though we used a random-effects model to pool the effect estimates and reported subgroup analysis to explore heterogeneity. Fourth, there was a chance of misclassification of antihypertensive agents used in the UK Biobank data during follow-up because antihypertensive agent use was only evaluated once at baseline. Fifth, as the UK Biobank did not collect information on the use of antihypertensive agents (i.e., dosage, frequency, and duration), we could not explore the possible dose–response relationship.
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