Advancing Asian-Centric Liver Disease Treatment: Machine Learning Applications in MASLD and MetALD Precision Medicine
Main Applicant – A/Prof Tan Nguan Soon, Lee Kong Chian School of Medicine, Nanyang Technological University (NTU)

Singapore’s diverse genetic backgrounds within a shared environment provide a unique opportunity to study the genetic variation influencing disease outcomes, particularly liver diseases like Metabolic Dysfunction-associated Steatotic Liver Disease (MASLD) and Metabolic Alcoholic Liver Disease (MetALD).

The genetic predisposition to these diseases in Asian populations, including Singaporeans, is under-researched, casting doubt on the effectiveness of therapies based on Western genomic data. Risk factors for MASLD and MetALD are complicated by diverse dietary patterns, alcohol consumption, and metabolic traits specific to Asians. Notably, Asians are more likely to have lean MASLD and are four times more likely to develop hepatocellular carcinoma than Caucasians, suggesting distinct aetiologies. With MASLD becoming more prevalent, precision medicine is needed to develop personalized strategies for detecting and treating these liver diseases in Asian contexts.

Our research, leveraging data from the PRECISE-SG100K cohort, aims to identify specific genomic risks associated with MASLD in Singaporeans. By integrating machine learning, we will explore the interactions between genetic risks, dietary patterns, and alcohol consumption. The insights will lead to novel, tailored treatments for MASLD, potentially reducing the healthcare impact of these liver diseases in Asian populations.