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Background: The present study aimed to estimate the additive interaction of family history of diabetes and hypertension on the diagnosis of diabetes among individuals aged 45 years and above in India. The coexistence of these two exposures may act synergistically on the risk of diabetes, leading to adverse health outcomes. Methods: The study utilized the data from the Longitudinal Ageing Study in India (LASI) Wave 1 (2017–2018). The total sample size for the current study was 58,612 individuals aged 45 years and above. Multivariable logistic regression models were employed to determine the individual and joint effect of a family history of diabetes with hypertension on diabetes. An additive model was applied to assess the interaction effect of the family medical history of diabetes with hypertension on the diagnosis of diabetes by calculating three different measures of additive interaction such as the relative excess risk due to interaction (RERI), attribution proportion due to interaction (AP), and synergy index (S). Results: The prevalence of diabetes was three times higher among individuals with family history of diabetes (27.8% vs. 9.2%) than those without family history. Individuals with family history of diabetes (AOR: 2.47, CI: 2.11 2.89) had 2.47 times higher odds of having diabetes than those without family history. The prevalence of diabetes was significantly higher among individuals with hypertension and family history of diabetes (46.6%, 95% CI: 39.7–53.6) than those without the coexistence of family history of diabetes and hypertension (9.9%, 95% CI: 9.5–10.4), individuals with hypertension and without a family history of diabetes (22.7%, 95% CI: 21.2–24.2), and individuals with family history of diabetes and without hypertension (16.5%, 95% CI: 14.5–18.7). Moreover, the adjusted odds ratio (AOR) of the joint effect between family medical history of diabetes and hypertension on diabetes was 9.28 (95% CI: 7.51–11.46). In the adjusted model, the RERI, AP, and S for diabetes were 3.5 (95% CI: 1.52–5.47), 37% (0.37; 95% CI: 0.22–0.51), and 1.69 (95% CI: 1.31–2.18) respectively, which indicates that there is a significant positive interaction between family history of diabetes and hypertension on the diagnosis of diabetes. The study findings on interaction effects further demonstrate consistent results for two models of hypertension (self-reported hypertension and hypertensive individuals receiving medication) even after adjustment with potential confounding factors on diabetes (self-reported diabetes and individuals with diabetes receiving medication). Conclusions: The study findings strongly suggest that the interaction of family history of diabetes with hypertension has a positive and significant effect on the risk of diabetes even after adjustment with potential confounding factors. Furthermore, the findings indicate a synergistic effect, emphasizing the importance of considering both family medical history of diabetes and hypertension when assessing diabetes risk and designing preventive strategies or interventions. [ABSTRACT FROM AUTHOR]

We evaluated the performance of various polygenic risk score (PRS) models derived from European (EU), South Asian (SA), and Punjabi Asian Indians (AI) studies on 13,974 subjects from AI ancestry. While all models successfully predicted Coronary artery disease (CAD) risk, the AI, SA, and EU + AI were superior predictors and more transportable than the EU model; the predictive performance in training and test sets was 18% and 22% higher in AI and EU + AI models, respectively than in EU. Comparing individuals with extreme PRS quartiles, the AI and EU + AI captured individuals with high CAD risk showed 2.6 to 4.6 times higher efficiency than the EU. Interestingly, including the clinical risk score did not significantly change the performance of any genetic model. The enrichment of diversity variants in EU PRS improves risk prediction and transportability. Establishing population-specific normative and risk factors and inclusion into genetic models would refine the risk stratification and improve the clinical utility of CAD PRS., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: More than 250 loci have been identified by genome-wide scans for type 2 diabetes in different populations. South Asians have a very different manifestation of the diseases and hence role of these loci need to be investigated among Indians with huge burden of cardio-metabolic disorders. Thus the present study aims to validate the recently identified GWAS loci in an endogamous caste population in North India. Methods: 219 T2D cases and 184 controls were recruited from hospitals and genotyped for 15 GWAS loci of T2D. Regression models adjusted for covariates were run to examine the association for T2D and fasting glucose levels. Results: We validated three variants for T2D namely, rs11634397 at ZFAND6 (OR = 3.05, 95%CI = 1.02–9.19, p = 0.047) and rs8042680 at PRC1 (OR = 3.67, 95%CI = 1.13–11.93, p = 0.031) showing higher risk and rs6813195 at TMEM154 (OR = 0.28, 95%CI = 0.09–0.90, p = 0.033) showing protective effect. The combined risk of 9 directionally consistent variants was also found to be significantly associated with T2D (OR = 1.91, 95%CI = 1.18–3.08, p = 0.008). One variant rs10842994 at KLHDC5 was validated for 9.15mg/dl decreased fasting glucose levels (SE = -17.25–1.05, p = 0.027). Conclusion: We confirm the role of ZFAND6, PRC1 and TMEM154 in the pathophysiology of type 2 diabetes among Indians. More efforts are needed with larger sample sizes to validate the diabetes GWAS loci in South Asian populations for wider applicability. [ABSTRACT FROM AUTHOR]