Determinants of plasma levels of gcg and metabolic impact of glucagon receptor signalling - a UK Biobank study
Winther-Sorensen, M.; Garcia, S. L.; Bartholdy, A.; Ottenheijm, M. E.; Banasik, K.; Brunak, S.; Sorensen, C. M.; Gluud, L. L.; Knop, F. K.; Holst, J. J.; Rosenkilde, M. M.; Jensen, M. K.; Wewer Albrechtsen, N. J.
Show abstract
Aims/hypothesesGlucagon and Glucagon-like peptide-1 (GLP-1) are derived from the same precursor; proglucagon (gcg), and dual agonists of their receptors are currently explored for the treatment of obesity and steatotic liver disease. Elevated levels of endogenous glucagon (hyperglucagonaemia) have been linked with hyperglycaemia in individuals with type 2 diabetes but are also observed in individuals with obesity and metabolic dysfunction-associated steatotic liver disease (MASLD). It is unknown whether type 2 diabetes, obesity or MASLD causes hyperglucagonaemia or vice versa. We investigated potential determinants of plasma gcg and associations of glucagon receptor signalling with metabolic diseases based on data from the UK Biobank. MethodsWe used exome sequencing data from the UK Biobank for [~]410,000 Caucasians to identify glucagon receptor variants and grouped them based on their known or predicted signalling. Plasma levels of gcg estimated using Olink technology was available for a subset of the cohort ([~]40,000). We determined associations between glucagon receptor variants and gcg with BMI, type 2 diabetes, and liver fat (quantified by liver MRI) and performed survival analyses to investigate if elevated gcg predicts type 2 diabetes development. ResultsObesity, MASLD, and type 2 diabetes independently associated with elevated plasma levels of gcg. Baseline gcg levels were statistically significantly associated with the risk of type 2 diabetes development over a 14-year follow-up period (hazard ratio = 1.13; 95% confidence interval (CI) = 1.09, 1.17, p < 0.0001). This association was of the same magnitude across strata of BMI. Carriers of glucagon receptor variants with reduced cAMP signalling had elevated levels of gcg ({beta} = 0.847; CI = 0.04, 1.66; p = 0.04), and carriers of variants with a predicted frameshift mutation had significantly higher levels of liver fat compared to wild-type controls ({beta} = 0.504; CI = 0.03, 0.98; p = 0.04). Conclusions/interpretationOur findings support that glucagon receptor signalling is involved in MASLD and type 2 diabetes, and that plasma levels of gcg are determined by genetic variation in the glucagon receptor, obesity, type 2 diabetes, and MASLD. Determining the molecular signalling pathways downstream of glucagon receptor activation may guide the development of biased GLP-1/glucagon co-agonist with improved metabolic benefits. Research in contextWhat is already known about this subject? O_LIGlucagon contributes to fasting hyperglycaemia in type 2 diabetes C_LIO_LIHyperglucagonemia is often observed in metabolic dysfunction-associated steatotic liver disease (MASLD), obesity and type 2 diabetes C_LIO_LIGlucagon/GLP-1 co-agonists have superior metabolic benefits compared to monoagonists C_LI What is the key question? What are key determinants of plasma proglucagon (gcg) and is elevated plasma gcg a cause or consequence (or both) of type 2 diabetes? What are the new findings? O_LIPlasma levels of gcg are increased in type 2 diabetes, MASLD and obesity independently of each other C_LIO_LIIncreased plasma gcg associates with higher risk of type 2 diabetes development C_LIO_LIGlucagon signalling associates with hepatic fat C_LI How might this impact on clinical practice in the foreseeable future? O_LIBiased glucagon receptor-regulating agents may be beneficial in the treatment of obesity and MASLD. C_LI
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Skeletal muscle and intermuscular adipose tissue gene expression profiling identifies new biomarkers with prognostic significance for insulin resistance progression and intervention response 95%
- Birth weight, BMI in adulthood and latent autoimmune diabetes in adults: A Mendelian randomization study 94%
- Circulating metabolites and the risk of type 2 diabetes: a prospective study of 11,896 young adults from four Finnish cohorts 94%
Similar papers in this journal
- Plasma proteomic signatures of adiposity are associated with cardiovascular risk factors and type 2 diabetes risk in a multi-ethnic Asian population 94%
- GAS6 and AXL promote insulin resistance by rewiring insulin signaling and increasing insulin receptor trafficking to endosomes 93%
- Genome-Wide Association Meta-Analysis Using a Recessive Model Illuminates Genetic Architecture of Type 2 Diabetes 93%
Similar papers in this journal
- Reduced somatostatin signalling leads to hypersecretion of glucagon in mice fed a high fat diet 95%
- Spatiotemporal regulation of GIPR signaling impacts glucose homeostasis as revealed in studies of a common GIPR variant. 94%
- Increased TGFβ /Activin-Smad2 signaling is associated with pancreatic β-cell dysfunction and glucose intolerance in gestational diabetes mellitus 94%
Similar papers in this journal
- Integrated miRNA_mRNA Analysis Reveals Dysregulated Regulatory Networks in Visceral Adipose Tissue Linked to Obesity and Type 2 Diabetes 94%
- Proteomic associations with fluctuation and long-term changes in BMI: A 40-year follow-up study 93%
- Treatment outcomes with oral anti-hyperglycaemic therapies in people with diabetes secondary to a pancreatic condition (type 3c diabetes): A population-based cohort study 92%
Similar papers in this journal
- Metabolic Drivers of Dysglycemia in Pregnancy: Ethnic-Specific GWAS of 146 Metabolites and 1-Sample Mendelian Randomisation Analyses in a UK Multi-Ethnic Birth Cohort 94%
- GLP-1 Receptor Agonist Improves Metabolic Disease in a Pre-clinical Model of Lipodystrophy 93%
- Coordinated regulation of gene expression and microRNA changes in adipose tissue and circulating extracellular vesicles in response to pioglitazone treatment in humans with type 2 diabetes 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.