👤 Lianna W Wat

Fructose metabolism is linked to metabolic dysfunction-associated steatotic liver disease (MASLD), but the regulatory mechanisms governing fructose uptake remain poorly understood. Here, we demonstrate that MASLD livers exhibit increased uptake of fructose-derived carbons compared to healthy livers and identify that the MASLD hepatocyte secretome can increase fructose metabolism. By performing fractionation and untargeted proteomics, we uncover a role for Angiopoietin-like 3 (ANGPTL3) as a regulator of hepatic fructose metabolism, independent of its role as a lipoprotein lipase (LPL) inhibitor. Circulating ANGPTL3 levels increase in response to fructose exposure, consistent with an action as a fructose sensor. Angptl3 knockdown in the liver resulted in a significant reduction in the uptake of hepatic fructose metabolites in vivo and downregulation of the facilitative hepatic fructose transporter slc2a8 (GLUT8) and fructolysis enzymes. This work demonstrates the existence of extracellular control of hepatic fructose metabolism through ANGPTL3. Show less

Recent large-scale genome-wide association studies identified novel genetic variants associated with obesity and body mass index (BMI) in addition to the well-described FTO and MC4R genetic variants. This study aimed to examine 13 previously reported obesity and/or BMI-associated loci for associations with obesity in Chinese. This was a cross-sectional case-control study in 470 obese cases (BMI > or =27.5 kg/m(2)) and 700 normal-weight controls (18.5 < or = BMI < or = 23.0 kg/m(2)). A significant association with obesity could be replicated (one tailed P < 0.05) in seven of the 13 single-nucleotide polymorphisms (SNPs) in the case-control study. These included GNPDA2 rs10938397 (P = 7.3 x 10(-4)); FTO rs8050136 (P = 8 x 10(-4)); MC4R rs17782313 (P = 1.2 x 10(-3)); KCTD15 rs29941 (P = 8 x 10(-3)); SFRS10-ETV5-DGKG rs7647305 (P = 0.023); SEC16B-RASAL2 rs10913469 (P = 0.041); and NEGR1 rs3101336 (P = 0.046). Combined genetic risk scores were calculated, and we observed ORs ranging from 1.17 to 1.23 for each unit increase in the genetic risk scores. Associations with obesity-related quantitative traits were analyzed separately for cases and controls. KCTD15 SNP rs29941 (P = 1 x 10(-3)) was significantly associated with fasting glucose in the control group, whereas only the FTO SNP rs8050136 was associated with BMI (P = 3.5 x 10(-3)) in the obese group. However, in an extension study of 1938 subjects from the population-based Hong Kong Cardiovascular Risk Factors Prevalence Study, rs8050136, rs10938397, and rs17782313 showed significant associations with BMI. We have succeeded in replicating, in a Chinese population, the associations with obesity in seven SNPs reported in recent genome-wide association studies. Further functional and fine-mapping studies to elucidate the roles of these putative obesity-related genes and genetic variants are warranted. Show less