Rujipat Wasitthankasem

Type 2 diabetes is a heterogeneous disease with strong genetic components. We showed earlier that newly diagnosed type 2 diabetes in Thai patients could be categorized into four clusters. This study aimed to determine the evidence of hereditary factors in these type 2 diabetes clusters. A total of 487 subjects who were diagnosed with type 2 diabetes in two years were enrolled in the Siriraj Diabetes Center, Siriraj Hospital Bangkok, Bangkok, Thailand. They were divided into four clusters as previously described. The associations between patients' characteristics, degree of family history of diabetes (FHD), and type 2 diabetes clusters were tested using multinomial logistic regression. Among four clusters of newly diagnosed type 2 diabetes, there were significant differences in characteristics at baseline, including age at diagnosis, BMI, waist circumference, blood sugar levels, vital signs, triglyceride, HDL, calculated LDL, creatinine and eGFR (all p < .05). A relatively young age at the time of diabetes diagnosis was associated with having second-degree relatives with diabetes (p < .05) in all clusters when using mild age-related diabetes (MARD) cluster with no FHD as a control. Patients in the severe insulin-deficient diabetes (SIDD) cluster had more first-degree relatives with diabetes (odds ratio = 1.85; p = .0354), while patients in the metabolic syndrome diabetes (MSD) cluster (odds ratio = 10.73; p < .001) and the mild obesity-related diabetes (MOD) group (odds ratio = 6.66; p = .002), had more second-degree relatives with diabetes. Genetic factors might have various roles in the pathogenesis of type 2 diabetes, at least in newly diagnosed Thai patients. Our findings supported that genetic heterogeneity contributed to clinical heterogeneity or four different clusters. Further studies are needed in a larger sample size of these patients is needed to identify genetic loci associated with each cluster.

Polygenic Risk Scores (PRS) are now playing an important role in predicting overall risk of breast cancer risk by means of adding contribution factors across independent genetic variants influencing the disease. However, PRS models may work better in some ethnic populations compared to others, thus requiring populaion-specific validation. This study evaluates the performance of 140 previously published PRS models in a Thai population, an underrepresented ethnic group. To rigorously evaluate the performance of 140 breast PRS models, we employed generalized linear models (GLM) combined with a robust evaluation strategy, including Five-fold cross validation and bootstrap analysis in which each model was tested across 1,000 bootstrap iterations to ensure the robustness of our findings and to identify models with consistently strong predictive ability. Among the 140 models evaluated, 38 demonstrated robust predictive ability, identified through > 163 bootstrap iterations (95% CI: 163.88). PGS004688 exhibited the highest performance, achieving an AUROC of 0.5930 (95% CI: 0.5903–0.5957) and a McFadden’s pseudo R ² of 0.0146 (95% CI: 0.0139–0.0153). Women in the 90 ^th percentile of PRS had a 1.83-fold increased risk of breast cancer compared to those within the 30 ^th to 70 ^th percentiles (95% CI: 1.04–3.18). This study highlights the importance of local validation for PRS models derived from diverse populations, demonstrating their potential for personalized breast cancer risk assessment. Model PGS004688, with its robust performance and significant risk stratification, warrants further investigation for clinical implementation in breast cancer screening and prevention strategies. Our findings emphasize the need for adapting and utilizing PRS in diverse populations to provide more accessible public health solutions.

Improved awareness of the hepatitis C virus (HCV) transmission has contributed to the overall decline in the HCV infection rate in some developing countries including Thailand. Chronic HCV infection in some rural Thai communities, however, presents a challenge in the efforts to treat and manage HCV-related diseases. Published and unpublished studies have suggested an unusually high incidence of HCV infection in a Thai province of Phetchabun compared to elsewhere in Thailand. To determine the magnitude of HCV infection and identify potential factors contributing to the higher rate of HCV infection in this province, we performed a population-based study in Phetchabun (n = 1667) and the neighboring Khon Kaen province (n = 1410) where HCV prevalence is much lower. Individuals between 30 and 64 years old completed detailed questionnaires designed to identify HCV risk factors and provided blood samples for anti-HCV antibody screening. The anti-HCV seropositive rates were 15.5% (259/1667) in Phetchabun and 3.6% (51/1410) in Khon Kaen. Positive samples were subsequently genotyped for HCV core gene sequence and assessed for the hepatitis B virus surface antigen (HBsAg) and human immunodeficiency virus antigen/antibody (HIV Ag/Ab). More individuals in Phetchabun possessed the combined presence of HBsAg (5.0%) and HIV Ag/Ab (0.4%) than those in Khon Kaen (3.9% HBsAg and 0.0% HIV Ag/Ab). While male gender, intravenous drug use (IVDU) and tattoos were significant HCV risk factors in both provinces (p <0.05), education less than high school and agriculture-related occupation were additionally associated with HCV in Phetchabun. HCV genotypes 6, 3, and 1 were identified in similar frequency in both provinces. We estimated that prevalence of HCV seropositivity and viremic carriers were higher in Phetchabun (143 and 111 per 1000) than in Khon Kaen (34 and 22 per 1000). Finally, we derived a simple risk factor-based scoring system as a useful preclinical tool to screen individuals at risk of chronic HCV infection prior to intervention. Knowledge gained from this study will assist in HCV screening and promote access to anti-viral treatment in high-risk groups.