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13.09.2017 | Article | Ausgabe 12/2017 Open Access

Diabetologia 12/2017

Transethnic insight into the genetics of glycaemic traits: fine-mapping results from the Population Architecture using Genomics and Epidemiology (PAGE) consortium

Zeitschrift:
Diabetologia > Ausgabe 12/2017
Autoren:
Stephanie A. Bien, James S. Pankow, Jeffrey Haessler, Yinchang N. Lu, Nathan Pankratz, Rebecca R. Rohde, Alfred Tamuno, Christopher S. Carlson, Fredrick R. Schumacher, Petra Bůžková, Martha L. Daviglus, Unhee Lim, Myriam Fornage, Lindsay Fernandez-Rhodes, Larissa Avilés-Santa, Steven Buyske, Myron D. Gross, Mariaelisa Graff, Carmen R. Isasi, Lewis H. Kuller, JoAnn E. Manson, Tara C. Matise, Ross L. Prentice, Lynne R. Wilkens, Sachiko Yoneyama, Ruth J. F. Loos, Lucia A. Hindorff, Loic Le Marchand, Kari E. North, Christopher A. Haiman, Ulrike Peters, Charles Kooperberg
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1007/​s00125-017-4405-1) contains peer-reviewed but unedited supplementary material, which is available to authorised users.
A correction to this article is available online at https://​doi.​org/​10.​1007/​s00125-017-4476-z.

Abstract

Aims/hypothesis

Elevated levels of fasting glucose and fasting insulin in non-diabetic individuals are markers of dysregulation of glucose metabolism and are strong risk factors for type 2 diabetes. Genome-wide association studies have discovered over 50 SNPs associated with these traits. Most of these loci were discovered in European populations and have not been tested in a well-powered multi-ethnic study. We hypothesised that a large, ancestrally diverse, fine-mapping genetic study of glycaemic traits would identify novel and population-specific associations that were previously undetectable by European-centric studies.

Methods

A multiethnic study of up to 26,760 unrelated individuals without diabetes, of predominantly Hispanic/Latino and African ancestries, were genotyped using the Metabochip. Transethnic meta-analysis of racial/ethnic-specific linear regression analyses were performed for fasting glucose and fasting insulin. We attempted to replicate 39 fasting glucose and 17 fasting insulin loci. Genetic fine-mapping was performed through sequential conditional analyses in 15 regions that included both the initially reported SNP association(s) and denser coverage of SNP markers. In addition, Metabochip-wide analyses were performed to discover novel fasting glucose and fasting insulin loci. The most significant SNP associations were further examined using bioinformatic functional annotation.

Results

Previously reported SNP associations were significantly replicated (p ≤ 0.05) in 31/39 fasting glucose loci and 14/17 fasting insulin loci. Eleven glycaemic trait loci were refined to a smaller list of potentially causal variants through transethnic meta-analysis. Stepwise conditional analysis identified two loci with independent secondary signals (G6PC2-rs477224 and GCK-rs2908290), which had not previously been reported. Population-specific conditional analyses identified an independent signal in G6PC2 tagged by the rare variant rs77719485 in African ancestry. Further Metabochip-wide analysis uncovered one novel fasting insulin locus at SLC17A2-rs75862513.

Conclusions/interpretation

These findings suggest that while glycaemic trait loci often have generalisable effects across the studied populations, transethnic genetic studies help to prioritise likely functional SNPs, identify novel associations that may be population-specific and in turn have the potential to influence screening efforts or therapeutic discoveries.

Data availability

The summary statistics from each of the ancestry-specific and transethnic (combined ancestry) results can be found under the PAGE study on dbGaP here: https://​www.​ncbi.​nlm.​nih.​gov/​projects/​gap/​cgi-bin/​study.​cgi?​study_​id=​phs000356.​v1.​p1

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