The secretion of insulin and glucagon from the pancreas and the incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) from the gastrointestinal tract is essential for glucose homeostasis. Several novel treatment strategies for type 2 diabetes (T2D) mimic GLP-1 actions or inhibit incretin degradation (DPP4 inhibitors), but none is thus far aimed at increasing the secretion of endogenous incretins. In order to identify new potential therapeutic targets for treatment of T2D, we performed a meta-analysis of a GWAS and an exome-wide association study of circulating insulin, glucagon, GIP, and GLP-1 concentrations measured during an oral glucose tolerance test in up to 7,828 individuals. We identified 6 genome-wide significant functional loci associated with plasma incretin concentrations in or near the SLC5A1 (encoding SGLT1), GIPR, ABO, GLP2R, F13A1, and HOXD1 genes and studied the effect of these variants on mRNA expression in pancreatic islet and on metabolic phenotypes. Immunohistochemistry showed expression of GIPR, ABO, and HOXD1 in human enteroendocrine cells and expression of ABO in pancreatic islets, supporting a role in hormone secretion. This study thus provides candidate genes and insight into mechanisms by which secretion and breakdown of GIP and GLP-1 are regulated.
Peter Almgren, Andreas Lindqvist, Ulrika Krus, Liisa Hakaste, Emilia Ottosson-Laakso, Olof Asplund, Emily Sonestedt, Rashmi B. Prasad, Esa Laurila, Marju Orho-Melander, Olle Melander, Tiinamaija Tuomi, Jens Juul Holst, Peter M. Nilsson, Nils Wierup, Leif Groop, Emma Ahlqvist
This article was first published November 2, 2017. Usage data is cumulative from November 2017 through November 2017.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.