Epigenetic associations of GPNMB rs199347 variant with alcohol consumption in Parkinson's disease.

Introduction: Alcohol consumption can induce a neuroinflammatory response and contribute to the progression of neurodegeneration. However, its association with Parkinson's disease (PD), the second most common neurodegenerative disorder, remains undetermined. Recent studies suggest that the glycoprotein non-metastatic melanoma protein B (GPNMB) is a potential biomarker for PD. We evaluated the association of rs199347, a variant of the GPNMB gene, with alcohol consumption and methylation upstream of GPNMB. Methods: We retrieved genetic and DNA methylation data obtained from participants enrolled in the Taiwan Biobank (TWB) between 2008 and 2016. After excluding individuals with incomplete or missing information about potential PD risk factors, we included 1,357 participants in our final analyses. We used multiple linear regression to assess the association of GPNMB rs199347 and chronic alcohol consumption (and other potential risk factors) with GPNMB cg17274742 methylation. Results: There was no difference between the distribution of GPNMB rs199347 genotypes between chronic alcohol consumers and the other study participants. A significant interaction was observed between the GPNMB rs199347 variant and alcohol consumption (p = 0.0102) concerning cg17274742 methylation. Compared to non-chronic alcohol consumers with the AA genotype, alcohol drinkers with the rs199347 GG genotype had significantly lower levels (hypomethylation) of cg17274742 (p = 0.0187). Conclusion: Alcohol consumption among individuals with the rs199347 GG genotype was associated with lower levels of cg17274742 methylation, which could increase expression of the GPNMB gene, an important neuroinflammatory-related risk gene for PD.

The association between different impact exercises and osteoporosis: an analysis of data from the Taiwan biobank.

Osteoporosis is a prevalent condition marked by reduced bone density and an elevated risk of fractures, especially among postmenopausal women. Exercise plays a crucial role in preventing and managing osteoporosis, with weight-bearing and impact exercises being particularly effective in enhancing bone density and mitigating disease risk. This study investigated the relationship between various types of impact exercises and osteoporosis using data from the Taiwan Biobank (TWB). The study sample comprised 5,123 individuals without osteoporosis and 1,770 individuals with the condition. Student's t-test and logistic regression analyses were utilized to assess the associations between exercise types and osteoporosis risk. Results indicated that high-impact exercise significantly reduced the likelihood of developing osteoporosis compared to no exercise (odds ratio; OR = 0.573, 95% CI: 0.406-0.810, P = 0.002). Conversely, low-impact exercises did not show a significant overall association with osteoporosis (OR = 1.160, 95% CI: 0.932-1.445, P = 0.184). Stratified analysis by sex revealed that high-impact exercise was protective against osteoporosis in men (OR = 0.391, 95% CI: 0.202-0.755, P = 0.005), but not significantly so in women (OR = 0.671, 95% CI: 0.438-1.027, P = 0.066). These findings suggest that high-impact exercise is associated with a reduced risk of osteoporosis, particularly among Taiwanese men aged 30 to 70.

Using machine learning-based algorithms to construct cardiovascular risk prediction models for Taiwanese adults based on traditional and novel risk factors.

OBJECTIVE: To develop and validate machine learning models for predicting coronary artery disease (CAD) within a Taiwanese cohort, with an emphasis on identifying significant predictors and comparing the performance of various models. METHODS: This study involved a comprehensive analysis of clinical, demographic, and laboratory data from 8,495 subjects in Taiwan Biobank (TWB) after propensity score matching to address potential confounding factors. Key variables included age, gender, lipid profiles (T-CHO, HDL_C, LDL_C, TG), smoking and alcohol consumption habits, and renal and liver function markers. The performance of multiple machine learning models was evaluated. RESULTS: The cohort comprised 1,699 individuals with CAD identified through self-reported questionnaires. Significant differences were observed between CAD and non-CAD individuals regarding demographics and clinical features. Notably, the Gradient Boosting model emerged as the most accurate, achieving an AUC of 0.846 (95% confidence interval [CI] 0.819-0.873), sensitivity of 0.776 (95% CI, 0.732-0.820), and specificity of 0.759 (95% CI, 0.736-0.782), respectively. The accuracy was 0.762 (95% CI, 0.742-0.782). Age was identified as the most influential predictor of CAD risk within the studied dataset. CONCLUSION: The Gradient Boosting machine learning model demonstrated superior performance in predicting CAD within the Taiwanese cohort, with age being a critical predictor. These findings underscore the potential of machine learning models in enhancing the prediction accuracy of CAD, thereby supporting early detection and targeted intervention strategies. TRIAL REGISTRATION: Not applicable.

Risk of diabetes mellitus based on the interactive association between G6PD rs72554664 polymorphism and sex in Taiwan Biobank individuals.

The presence of glucose-6-phosphate dehydrogenase (G6PD) deficiency may increase the risk of type 2 diabetes mellitus (T2DM), with differing prevalence between males and females. Although G6PD deficiency is an X-linked genetic condition, its interaction with sex regarding T2DM risk among the Taiwanese population has not been fully explored. This study aimed to investigate the association between G6PD deficiency and T2DM risk in the Taiwanese population, focusing on the potential influence of sex. Data were obtained from the Taiwan Biobank (TWB) database, involving 85,334 participants aged 30 to 70 years. We used multiple logistic regression analysis to assess the interaction between G6PD rs72554664 and sex in relation to T2DM risk. The T2DM cohort comprised 55.35% females and 44.65% males (p < 0.001). The TC + TT genotype of rs72554664 was associated with an increased risk of T2DM, with an odds ratio (OR) of 1.95 (95% CI: 1.39-2.75), and males showed an OR of 1.31 (95% CI: 1.19-1.44). Notably, the G6PD rs72554664-T allelic variant in hemizygous males significantly elevated the T2DM risk (OR), 4.57; p < 0.001) compared to females with the CC genotype. Our findings suggest that the G6PD rs72554664 variant, in conjunction with sex, significantly affects T2DM risk, particularly increasing susceptibility in males. The association of the G6PD rs72554664-T allelic variant with a higher risk of T2DM highlights the importance of sex-specific mechanisms in the interplay between G6PD deficiency and T2DM.

Polymorphism rs3733591 of the SLC2A9 gene and metabolic syndrome affect gout risk in Taiwan Biobank subjects.

Background: Over the past few decades, gout and diseases like metabolic syndrome (MetS) have become more prevalent. Attempts have been made in Taiwan to identify the genes responsible for gout. A few gene loci, among them SLC2A9, have been identified using Taiwan Biobank (TWB) data. We, therefore, examined whether MetS could also account for the association between polymorphism SLC2A9 rs3733591 and gout. Methods: The final analysis consisted of 73,558 subjects, of whom 2,709 had gout. To estimate the likelihood of gout occurrence based on rs3733591 and MetS, we used logistic regression models. Results: Rs3733591-TC + CC compared to TT genotype was associated with gout (OR, 1.15; 95% CI, 1.06-1.25). Also associated with gout was MetS (OR, 1.21; 95% CI, 1.10-1.33). A significant interaction was seen between rs3733591 and MetS (p-value = 0.039). Using rs3733591-TT/no MetS as the reference group, the ORs (95% CI) for gout was 1.24 (1.11-1.38) for TC + CC/no MetS, 1.35 (1.17-1.56) for TT/MetS, and 1.39 (1.22-1.58) for TC + CC/MetS. However, subgroup analysis defined by sex showed no significant associations in women. Conclusion: In summary, metabolic syndrome and SLC2A9 rs3733591 genotypes were interactively associated with gout in Taiwanese men, but not women.

Metabolic syndrome risk in adult coffee drinkers with the rs301 variant of the LPL gene.

BACKGROUND: Metabolic syndrome (MetS), a cluster of metabolic and cardiovascular risk factors is influenced by environmental, lifestyle, and genetic factors. We explored whether coffee consumption and the rs301 variant of the lipoprotein lipase (LPL) gene are related to MetS. METHODS: We conducted multiple logistic regression analyses using data gathered from 9523 subjects in Taiwan Biobank (TWB). RESULTS: Our findings indicated that individuals who consumed coffee had a reduced odds ratio (OR) for MetS (0.750 (95% confidence interval [CI] 0.653-0.861) compared to non-coffee drinkers. Additionally, the risk of MetS was lower for individuals with the 'TC' and 'CC' genotypes of rs301 compared to those with the 'TT' genotype. Specifically, the OR for MetS was 0.827 (95% CI 0.721-0.949) for the 'TC' genotype and 0.848 (95% CI 0.610-1.177) for the 'CC' genotype. We observed an interaction between coffee consumption and the rs301 variant, with a p-value for the interaction of 0.0437. Compared to the reference group ('no coffee drinking/TT'), the ORs for MetS were 0.836 (95% CI 0.706-0.992) for 'coffee drinking/TT', 0.557 (95% CI 0.438-0.707) for 'coffee drinking/TC', and 0.544 (95% CI 0.319-0.927) for 'coffee drinking/CC'. Notably, MetS was not observed in non-coffee drinkers regardless of their rs301 genotype. CONCLUSION: Our findings suggest that rs301 genotypes may protect against MetS in Taiwanese adults who consume coffee compared to non-coffee drinkers.

Susceptibility to eye diseases in relation to age and kidney failure among Taiwanese adults.

BACKGROUND: The kidney and eyes share common pathways and are thought to be closely connected. Chronic kidney disease and major eye diseases, such as cataract and glaucoma, are strongly associated with age. However, further investigation is needed to understand the joint impact of age and kidney diseases on eye diseases. In this study, we assessed the risk of eye diseases in relation to age and kidney failure in Taiwanese adults. METHODS: Our study included 127,561 cancer-free volunteers aged 30 to 70 years who participated in the Taiwan Biobank (TWB) project from 2008 to 2020. Information on the main exposures (kidney failure and age) and the outcome (eye diseases, including glaucoma, cataract, xerophthalmia, and retinal detachment) was collected through questionnaires. RESULTS: In general, kidney failure and older age were independently associated with a higher risk of eye, particularly cataract and retinal detachment: prevalence odds ratio (POR); 95% confidence interval (CI) = 2.480; 1.635-3.761 for cataract and 3.885; 1.968-7.666 for retinal detachment. A significant interaction between kidney failure and age on cataract was observed (p-value = 0.0002). Age-stratified analysis revealed a higher risk of cataract among patients with kidney failure aged below 50 (POR = 6.534; 95% CI = 2.493-17.124) and between 50 and 60 years (POR = 3.957; 95%CI = 1.986-7.881). Combining kidney failure and age (reference: no kidney failure and age < 50 years), kidney failure in all age groups was associated with a higher risk of cataract. The PORs; 95% CIs were 10.725; 4.227-27.211 for patients below 50 years, 28.487; 14.270-56.866 for those aged 50-60 years, and 43.183; 24.434-72.824 for those > 60 years. Combining cataract and age (reference: no cataract and age < 50 years), patients below 50 years had the highest risk of kidney failure (POR; 95% CI = 9.510; 3.722-24.297). CONCLUSIONS: Our study suggests that age and kidney failure may jointly contribute to eye diseases, particularly cataract. The association between cataract and kidney failure could be bidirectional, especially in individuals below 50 years. This significant bidirectional relationship underscores the need for screening patients with cataract for kidney failure and vice versa, particularly in younger adults.

The association between smoking cessation and lifestyle/genetic variant rs6265 among the adult population in Taiwan.

Recent studies showed significant associations between socio-demographic, lifestyle factors, polymorphic variant rs6265, and smoking cessation behaviours. We examined rs6265 TT, TC and CC genotypes and their association with socio-demographic and other variables, including mental health status, drinking, exercise, and smoking behaviour among Taiwanese adults. Data on rs6265 were retrieved from the Taiwan Biobank, which contained genetic data collected between 2008 to 2019 from 20,584 participants (aged 30-70 years). Participants who smoked for more than 6 months prior to enrolment were categorized as smokers. If they had smoked and later quit for more than 6 months, they were classified as former smokers. Information regarding drinking, exercise, depression, and bipolar disorder were obtained through questionnaires and were categorized as either as affirmative (yes) or negative (no) responses. In contrast to previous studies, we found that the association between the polymorphism rs6265 and smoking behaviour was not significant (P-value = 0.8753). Males with lower education levels, young persons, and alcohol drinkers showed significant smoking behaviours (P-value < .0001). This population-based study indicates that rs6265 has no significant correlations with smoking cessation behaviour among adults in Taiwan.