Parkinson’s disease (PD) is the second most common neurodegenerative disorder, affecting >1% of the worldwide population ≥65 years of age, and is characterized primarily by slow movement, tremors, and rigidity (1, 2). The etiology of PD remains unknown, although it is believed to result from a combination of genetic, environmental, and behavioral factors by progressive loss of dopaminergic neurons in the substantia nigra and accumulation of α-synuclein within Lewy bodies (3–5). Pathophysiologically, PD has been associated with α-synuclein misfolding and aggregation, mitochondrial dysfunction, impairment of protein clearance, neuroinflammation, and oxidative stress (6–8). Epigenetic modifications, which can connect environment or behavior factors with the genetic changes underlying disease (9, 10), have been shown to modulate the immune systems of patients with PD (11–22).

Glycoprotein non-metastatic melanoma protein B (GPNMB), a type I transmembrane protein involved in immune cell maturation and activation (23), has been shown to be a promising biomarker of PD risk (24–27). GPNMB is highly expressed in macrophages and microglia, which play a significant role in neuroinflammation, and was shown to be upregulated in disease-associated microglia in neurodegenerative animal models (28, 29). A prominent single-nucleotide polymorphism (SNP) of GPNMB, rs199347, plays a significant role in modulating systemic immune response, especially neuroinflammation (21–26, 30). The rs199347 variant genotype and minor allele involves a guanine instead of the reference alanine (31) and has been identified as highly associated with PD risk (24). Recently, GPNMB was shown to promote the toxic aggregation of the alpha-synuclein protein in substantia nigra, which is believed to contribute to neurodegeneration, and could be a potential target for PD treatment (24, 32). Furthermore, recent proteomic analyses of cerebrospinal fluid have identified GPNMB as a primary causal protein in PD emphasizing its role in the disease’s heterogeneity and causality (33). Notably, studies involving animal models have demonstrated that overexpression of GPNMB can mitigate degeneration of dopaminergic neurons and provide anti-neuroinflammatory benefits (34, 35).The differences among the rs199347 genotypes (AA, AG, and GG) are significantly associated with GPNMB expression in the brain as well as whole blood (24, 25, 27, 36–39). Moreover, large, integrated GWAS on methylation data from brain samples of patients with PD found that the association between GPNMB and PD could be regulated by DNA methylation (25, 27, 39). Indeed, hypomethylation at cg17274742, which is proximal to the 7p15 chromosomal region in which GPNMB is located, is associated with increased GPNMB expression in PD patients (25, 27).

Alcohol consumption can affect epigenetic modification and gene expression (40–42), and associated DNA methylation changes have been observed in both the peripheral and central nervous systems (43, 44). Chronic alcohol consumption can trigger neuroinflammation resulting in central nervous system injury and possibly neurodegeneration (45–48). High alcohol consumption has been shown to increase GPNMB levels (49, 50) suggesting an involvement with PD. However, the connection between alcohol drinking and PD remains poorly understood, and epidemiological studies show contradictory data (51–55). Whether PD is caused by chronic alcohol consumption remains unclear (53–56), although chronic alcohol consumption has been found to drive biological mechanisms with significant changes to DNA methylation in serum and brain tissues (40, 41, 43, 44).

To date, no study has evaluated the role of alcohol intake on the expression of GPNMB, and specifically the PD-associated GPNMB SNP rs199347, and DNA methylation. Identifying methylation patterns associated with alcohol consumption and GPNMB expression could help elucidate the influence of alcohol consumption on the risk of PD.

Overall, 1,357 participants comprising 648 men and 709 women were included in the study ( Table 1 ). The mean GPNMB cg17274742 methylation levels (beta values) for individuals with chronic alcohol consumption was 0.9484 ± 0.0009 (mean ± standard error), compared to 0.9484 ± 0.0003 for those who did not chronically consume alcohol. For the non-chronic group, the number (percentage) of participants with the GPNMB rs199347 AA, AG, and GG genotypes was 633 (51.72%), 511 (41.75%), 80 (6.54%), respectively. For the chronic alcohol-drinking group, the number (percentage) with the GPNMB rs199347 AA, AG, and GG genotypes were 66 (49.62%), 53 (39.85%), and 14 (10.53%), respectively. The methylation levels and genotype distribution did not differ significantly between the chronic alcohol consumers and the other study participants.

The GPNMB rs199347 variant and alcohol consumption was not significantly associated with the methylation of cg17274742 ( Table 2 ). However, men had significantly lower levels of cg17274742 methylation compared to women (β = −0.00302, p = 0.0169), while hypertensive patients had significantly higher levels of cg17274742 methylation compared to non-hypertensive patients (β = 0.00208, p = 0.0171).

GPNMB rs199347 variant and alcohol drinking had a significant interaction (p = 0.0102) with the methylation of cg17274742 ( Table 3 ). After stratifying by alcohol consumption, rs199347 was not significantly associated with the methylation of cg17274742 in the control group. However, compared to the rs199347 AA genotype, the GG genotype was significantly associated with lower levels of methylation at cg17274742 (β = −0.00635, p = 0.0366).

After combining the rs199347 genotypes and alcohol consumption ( Table 4 ), cg17274742 was significantly hypomethylated among chronic alcohol drinkers with the rs199347 GG genotype compared to the control group with the AA genotype (β= −0.00654, p = 0.0187).

Using data from a large, national prospective cohort study, we identified an association between cg17274742 methylation status, the GPNMB rs199347 polymorphism, and alcohol consumption. Our findings suggest that carriers of the rs199347 GG genotype and those who chronically consume alcohol have significantly more cg17274742 hypomethylation, which may result in increased GPNMB expression. This is the first study to find a relationship between a specific GPNMB polymorphism and alcohol-associated methylation changes suggesting that a lifestyle change, particularly a reduction in alcohol consumption for carriers of the rs199347 GG genotype, could reduce GPNMB expression, which is highly correlated with the risk of PD.

Recent studies highlight the importance and benefits of involving diverse and multiethnic populations in genetic studies (70, 71), including more accurately representing the risks of genetically associated diseases in different populations (72). Most published GWAS and methylomic studies involving the GPNMB rs199347 variant were conducted in majority-white study populations (36–39, 73, 74). Our study uses information obtained from the Taiwan Biobank (TWB), the largest biobank in East Asia with dense SNP array data, and leverages its high-coverage whole-genome sequencing and DNA methylation data in a population of Han Chinese (58). Notably, the rs199347 genotype frequencies observed in our study (A = 0.72, G = 0.28) are roughly equivalent to those reported by the Allele Frequency Aggregator Project in East Asia (A = 0.716, G = 0.283), which is different from the frequencies reported in white individuals (A = 0.59, G = 0.41) (31). While the TWB provides a robust dataset for understanding genetic associations in the Han Chinese population, it is crucial to discuss the generalizability of our findings beyond this group. The genetic and lifestyle diversity across different populations may impact the observed associations. Therefore, further studies are needed to explore how genetic differences between populations might influence the relationship between the GPNMB rs199347 variant, alcohol consumption, and Parkinson’s disease risk. Addressing these potential impacts would enhance the broader applicability of our findings and contribute to a more comprehensive understanding of genetic risk factors across diverse populations.

A novel integrative approach has been developed to align expression quantitative trait loci (eQTL) with genome-wide association study (GWAS) signals in Parkinson’s disease (PD), utilizing an updated PD GWAS dataset. This strategy highlighted the methylation site cg17274742 within the GPNMB gene, a site of interest for Coloc analysis, which investigates common causal variants shared between eQTL and GWAS data. Methylation at this specific locus not only affects gene expression but also influences splicing activities at the GPNMB/NUPL2 locus facilitated by robust protein–protein interactions. These interactions may connect to genes associated with either Mendelian or sporadic forms of PD (25). The presence of PD-associated variants at this methylation site reveals critical molecular pathways influencing the pathogenesis of PD, thereby emphasizing the significant role of both genetic and epigenetic factors in its development. In our study, we found that males had more cg17274742 hypomethylation, which may increase GPNMB expression. After correcting for age, the prevalence of PD in men is approximately 1.4 times higher than that in women (75), although a 2014 meta-analysis suggests that this difference is evident only in the 50- to 59-year age group (59). Additionally, we found that hypertension was associated with cg17274742 hypermethylation, which could decrease GPNMB expression and potentially reduce PD risk (24, 36). Published evidence connecting hypertension and PD diagnosis is contradictory (76–81), and different effects of hypertension have been observed in white versus Asian populations (76–79). Moreover, some antihypertensive medications may contribute to PD risk; inhibitors of the renin–angiotensin–aldosterone system may delay proinflammatory effects, and alpha-1-adrenergic receptor antagonists can enhance glycolysis and could reduce PD risk (82–87).

Chronic alcohol consumption can damage the central nervous system (45), and a recent translational study suggests a strong correlation between alcohol use disorder and the inflammatory response in the brain (45). Chronic alcohol consumption can trigger pro-inflammatory cytokines by activating peripheral macrophages and microglia in the central nervous system, which may alter the neuroinflammatory state in the brain (46, 47). Previous studies have noted the importance of different biological processes and functions of GPNMB, including cell differentiation and development, inflammation and immune response, progression, and neurodegeneration deterioration (23). Additionally, the Genotype-Tissue Expression (GTEx) project has identified that the GPNMB rs199347 variant significantly influences gene expression in various brain tissues, including the basal ganglia, cerebellum, and frontal cortex (88, 89). These regions are closely linked to neural mechanisms, particularly the dopaminergic pathways, which are crucial in the pathophysiology of PD (3, 6). The impact of this variant on these brain regions underscores its potential role in the clinical manifestations of PD. Our finding suggests that lifestyle changes, particularly a reduction in alcohol consumption for carriers of the rs199347 GG genotype, could modulate GPNMB expression, thereby identifying a potentially modifiable risk factor in Parkinson’s disease.

Our study was limited by the uncertainty around the amount of alcohol consumption. The TWB survey quantifies alcohol consumption in milliliters (ml), not milligrams (mg), and is therefore difficult to standardize across the study population. Additionally, data on alcohol consumption were self-reported and are subject to recall bias. Another limitation of our investigation concerns our inability to comprehensively account for all potential confounding variables, including dietary habits, lifestyle choices, and environmental exposures. Nevertheless, we mitigated this by controlling for a range of well-documented risk and protective factors, such as age, body mass index (BMI), smoking status, alcohol consumption, coffee intake, serum uric acid levels, and hypertension, all of which have been extensively studied in PD epidemiological research.

Ultimately, our results provide insight into the genetic and lifestyle factors associated with GPNMB expression, which is a potential biomarker and therapeutic target of PD. Future experiments using animal models or human cell lines to examine the underlying mechanisms behind this potential neuroinflammatory association in the central nervous system are warranted.

In summary, we found that having the GG genotype of GPNMB rs199347 with drinking habits decreases GPNMB methylation among Taiwan Biobank participants. These results provide information on the genetic and lifestyle factors that contribute to the expression, which is a PD potential biomarker and therapeutic target of PD, and could be used as a reference for experimental, longitudinal, or intervention studies evaluating the disease and its associated variables and mechanisms.

The access to and use of the Taiwan Biobank data in the present work was approved by the Ethics and Governance Council (EGC) of Taiwan Biobank (approval number: TWBR10907-05) and the Institutional Review Board (IRB) of National Health Research Institutes, Taiwan (approval number: EC1090402-E). The data collection of Taiwan Biobank was approved by the Ethics and Governance Council (EGC) of Taiwan Biobank and the Department of Health and Welfare, Taiwan (Wei-Shu-I-Tzu NO.1010267471). The data utilized in this study are sourced from the Taiwan Biobank, accessible at (https://www.twbiobank.org.tw/). Due to restrictions, the data are not publicly available and were used under license specifically for this study. However, these data can be obtained from the corresponding author, Yung-Po Liaw, upon reasonable request and with permission from the Taiwan Biobank.

Our study involves patients enrolled in the Taiwan Biobank (TWB). TWB was approved by the Institutional Review Board on Biomedical Science Research/IRB-BM, Academia Sinica and by the Ethics and Governance Council of Taiwan Biobank, Taiwan. Written informed consent was obtained before data collection from each participant in accordance with institutional requirements and the principles of the Declaration of Helsinki. This study was approved by the Institutional Review Board of the Chung Shan Medical University Hospital (CS1–20009). Participants in the Taiwan Biobank provided their written informed consent during enrollment. All methods were performed according to the relevant guidelines and regulations.

Y-CC: Conceptualization, Investigation, Validation, Visualization, Writing – original draft. Y-CL: Methodology, Validation, Writing – review & editing. ON: Investigation, Methodology, Supervision, Validation, Writing – review & editing. C-HH: Data curation, Formal analysis, Methodology, Writing – review & editing. J-HZ: Data curation, Formal analysis, Methodology, Writing – review & editing. S-LW: Conceptualization, Investigation, Validation, Writing – review & editing. Y-PL: Conceptualization, Funding acquisition, Investigation, Resources, Validation, Writing – review & editing.