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Discovery of new gene associated with diabetes risk suggests link with body clock

A connection between the body clock and abnormalities in metabolism and diabetes has been suggested in new research by an international team involving the University of Oxford, the Wellcome Trust Sanger Institute and the MRC Epidemiology Unit in Cambridge.

The researchers have identified a gene involved in the way the body responds to the 24 hour day-night cycle that is strongly linked to high blood sugar levels and an increased risk of type 2 diabetes. The results of the genome-wide association scan are published in Nature Genetics.

"We have extremely strong, incontrovertible evidence that the gene encoding melatonin receptor 1B is associated with high fasting glucose levels and increased risk of type 2 diabetes," says Professor Mark McCarthy of the Oxford Centre for Diabetes, Endocrinology and Metabolism at the University of Oxford.

Melatonin is a hormone that is strongly tied to control of our sleep-wake cycles, with concentrations in the blood peaking at night-time and dipping during the day. As a result, melatonin is implicated in conditions like jetlag and sleep disorders.

Disrupted sleep patterns are known to be associated with a range of health problems including metabolic disorders like diabetes, but it is not understood how they are connected. In identifying a link between a melatonin receptor and blood sugar levels, this study provides genetic evidence that mechanisms controlled by our body clock are connected to the machinery that keeps us metabolically healthy. It seems likely that the action of melatonin on the pancreas is being disturbed in this case, the researchers suggest.

Read more at Wellcome trust Sanger institute's press release...


Publication details:

Variants in MTNR1B influence fasting glucose levels.
Prokopenko I, Langenberg C, Florez JC, Saxena R, Soranzo N, Thorleifsson G, Loos RJ, Manning AK, Jackson AU, Aulchenko Y, Potter SC, Erdos MR, Sanna S, Hottenga JJ, Wheeler E, Kaakinen M, Lyssenko V, Chen WM, Ahmadi K, Beckmann JS, Bergman RN, Bochud M, Bonnycastle LL, Buchanan TA, Cao A, Cervino A, Coin L, Collins FS, Crisponi L, de Geus EJ, Dehghan A, Deloukas P, Doney AS, Elliott P, Freimer N, Gateva V, Herder C, Hofman A, Hughes TE, Hunt S, Illig T, Inouye M, Isomaa B, Johnson T, Kong A, Krestyaninova M, Kuusisto J, Laakso M, Lim N, Lindblad U, Lindgren CM, McCann OT, Mohlke KL, Morris AD, Naitza S, Orrù M, Palmer CN, Pouta A, Randall J, Rathmann W, Saramies J, Scheet P, Scott LJ, Scuteri A, Sharp S, Sijbrands E, Smit JH, Song K, Steinthorsdottir V, Stringham HM, Tuomi T, Tuomilehto J, Uitterlinden AG, Voight BF, Waterworth D, Wichmann HE, Willemsen G, Witteman JC, Yuan X, Zhao JH, Zeggini E, Schlessinger D, Sandhu M, Boomsma DI, Uda M, Spector TD, Penninx BW, Altshuler D, Vollenweider P, Jarvelin MR, Lakatta E, Waeber G, Fox CS, Peltonen L, Groop LC, Mooser V, Cupples LA, Thorsteinsdottir U, Boehnke M, Barroso I, Van Duijn C, Dupuis J, Watanabe RM, Stefansson K, McCarthy MI, Wareham NJ, Meigs JB, Abecasis GR
Nat Genet. 2008;. PMID: 19060907 DOI: 10.1038/ng.290

 

 

March 2009
ENGAGE Young Investigator

Inga Prokopenko

Oxford Centre for Diabetes, Endocrinology and Metabolism &Wellcome Trust Centre for Human Genetics, University of Oxford, UK

Inga is interested in understanding the genetic architecture underlying susceptibility to complex disorders and in dissecting the genetic background of quantitative phenotypes in healthy individuals. Her work is focussed on the genetics of Type 2 Diabetes (T2D) and related quantitative glycaemic and metabolic traits. Inga is involved in several ENGAGE work packages and participates in studies on genome wide data integration and meta-analysis, developing approaches for combining phenotypic data from multiple cohorts, CNV detection and analysis and genetic refinement by resequencing. In 2008 she coordinated the efforts of ENGAGE cohorts participating in the identification of the novel gene MTNR1B for Fasting Glucose and T2D within MAGIC (Meta-Analyses of Glucose and Insulin-related traits Consortium).