👤 Charles E McCulloch

Obesity is associated with adipose tissue (AT) dysfunction marked by cellular hypertrophy, inflammation, hypoxia and fibrosis. Angiopoietin-like protein 4 (ANGPTL4) inhibits lipoprotein lipase which regulates triglyceride storage. Recently, inhibition of ANGPTL4 has been suggested as potential treatment for type 2 diabetes. Here we evaluate ANGPTL4's role in diabetes and examine ANGPTL4 in relation to markers of AT dysfunction and fatty liver disease. We obtained a unique set of paired samples from subjects undergoing weight loss surgery including subcutaneous AT (SCAT), omental AT (OMAT), liver, thigh muscle biopsies and serum including a post-surgical SCAT biopsy after 9 months. SCAT ANGPTL4 expression and circulating protein levels were higher in people with diabetes and correlated with glucose levels and HOMA-IR but not BMI. At post-surgical follow up, SCAT ANGPTL4 declined in subjects with diabetes to levels of those without diabetes. ANGPTL4 expression correlated with HIF1A and inflammation (MCP-1, IL-6). We found that SCAT ANGPTL4 was closely linked with the expression of ANGPTL4 in the liver and represented a good proxy for liver steatosis. We suggest the elevation of ANGPTL4 levels in diabetes and the association with inflammation and hypoxia is due to a compensatory mechanism to limit further AT dysfunction. A reduction of ANGPTL4 for the treatment of T2DM as previously suggested is thus unlikely to be of further benefit. Show less

Hereditary hemorrhagic telangiectasia (HHT) is caused by mutations in TGFβ/BMP9 pathway genes and characterized by vascular malformations (VM) including arteriovenous malformations (AVM) in lung, liver, and brain, which lead to severe complications including intracranial hemorrhage (ICH) from brain VM. The clinical heterogeneity of HHT suggests a role for genetic modifier effects. Common variants in loci that modify phenotype severity in Tgfb knockout mice were previously reported as associated with lung AVM in HHT. Common variants in candidate genes were reported as associated with sporadic brain AVM and/or ICH. We investigated whether these variants are associated with HHT organ VM or with ICH from brain VM in 752 Caucasian HHT patients enrolled by the Brian Vascular Malformation Consortium. We genotyped 11 candidate variants: four variants reported as associated with lung AVM in HHT (PTPN14 rs2936018, USH2A rs700024, ADAM17 rs12474540, rs10495565), and seven variants reported as associated with sporadic BAVM or ICH (APOE ε2, ANGPTL4 rs11672433, EPHB4 rs314308, IL6 rs1800795, IL1B rs1143627, ITGB8 rs10486391, TNFA rs361525). Association of genotype with any VM, lung AVM, liver VM, brain VM or brain VM ICH was evaluated by multivariate logistic regression adjusted for age, gender, and family clustering. None of the 11 variants was significantly associated with any phenotype. There was a trend toward association of USH2A rs700024 with ICH (OR = 2.77, 95% CI = 1.13-6.80, p = .026). We did not replicate previously reported associations with HHT lung AVM and variants in Tgfb modifier loci. We also did not find significant associations between variants reported in sporadic brain AVM and VM or ICH in HHT. Show less

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes. Show less