Horng-Yih Ou Taiwan

• Chronic Kidney Disease: Illuminating Disease Pathways Through Data Science
  Tai-Shuan LaiTaiwan Speaker Chronic Kidney Disease: Illuminating Disease Pathways Through Data Science Chronic kidney disease (CKD) represents an escalating global health burden, affecting more than 800 million individuals worldwide and contributing substantially to end-stage kidney disease, cardiovascular morbidity, and premature mortality. Although numerous epidemiological studies have identified potential CKD risk factors, progress in prevention and disease-modifying therapies has been hindered by the difficulty of distinguishing causal determinants from non-causal associations. The rapid expansion of large-scale biobanks, together with advances in genetic epidemiology—particularly genome-wide association studies (GWAS) and Mendelian randomization (MR)—offers an important opportunity to address these challenges and advance translational CKD research. In this session, we present an integrated, data-driven framework for investigating CKD pathogenesis by combining GWAS and MR, with a particular emphasis on insights derived from East Asian populations. Using the Taiwan Biobank, which comprises more than 180,000 extensively phenotyped participants with genome-wide data, we illustrate how genetic approaches can complement conventional observational analyses and support the development of precision nephrology. We first highlight Mendelian randomization as a quasi-experimental approach that exploits the random allocation of genetic variants at conception to strengthen causal inference. Using hyperuricemia as a representative example, we demonstrate how robust observational associations with incident CKD may not necessarily reflect causality. While elevated serum urate levels were consistently associated with increased CKD risk in traditional analyses, multiple MR methods using both individual-level and summary-level data did not support a causal effect on kidney disease progression. These findings are consistent with recent randomized clinical trials and underscore the value of MR in prioritizing therapeutic targets. We next extend the MR framework to complex and correlated biological systems through multivariable Mendelian randomization. Focusing on thyroid-related traits, including thyroid-stimulating hormone and free thyroxine, we show how multivariable MR can disentangle intertwined endocrine influences on kidney function. Across East Asian and European populations, genetically predicted thyroid-stimulating hormone exhibited a consistent causal inverse association with estimated glomerular filtration rate, whereas free thyroxine showed no independent causal effect. This example highlights the ability of MR to clarify mechanistic pathways that are difficult to resolve using observational data alone. Beyond causal inference, we demonstrate the value of GWAS in uncovering novel genetic determinants of CKD-related traits. A multi-trait GWAS approach using MTAG was applied to jointly analyze urinary albumin-to-creatinine ratio and kidney function, substantially enhancing discovery power. This strategy identified multiple novel loci associated with albuminuria in an East Asian population and implicated biologically relevant pathways, including proximal tubular albumin endocytosis and primary cilia function. Integrative gene prioritization incorporating kidney-specific expression quantitative trait loci, deleteriousness metrics, and Mendelian kidney disease gene databases further strengthened biological interpretation. Finally, we introduce trajectory GWAS as an innovative approach that leverages repeated measurements of kidney function to identify genetic determinants of longitudinal eGFR decline. By modeling kidney function trajectories rather than cross-sectional measures, this method revealed loci associated with progressive kidney function loss that were not detected by conventional GWAS designs. Conclusion. Taken together, the integration of GWAS, Mendelian randomization, and longitudinal biobank analyses provides a robust framework for improving causal understanding of CKD. Continued accumulation of high-quality population-specific data and international collaboration will be essential for translating these insights into clinical research and future strategies for CKD prevention and management.

  Chun-Liang LinTaiwan Moderator
• Investigating the Pathophysiological Role of Sweet Taste Receptor in the Development of Diabetes-
  Hung-Tsung WuTaiwan Speaker Investigating the Pathophysiological Role of Sweet Taste Receptor in the Development of Diabetes

  Horng-Yih OuTaiwan Moderator Investigating the Pathophysiological Role of Sweet Taste Receptor in the Development of Diabetes-