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A common Greenlandic TBC1D4 variant confers muscle insulin resistance and type 2 diabetes

Abstract

The Greenlandic population, a small and historically isolated founder population comprising about 57,000 inhabitants, has experienced a dramatic increase in type 2 diabetes (T2D) prevalence during the past 25 years1. Motivated by this, we performed association mapping of T2D-related quantitative traits in up to 2,575 Greenlandic individuals without known diabetes. Using array-based genotyping and exome sequencing, we discovered a nonsense p.Arg684Ter variant (in which arginine is replaced by a termination codon) in the gene TBC1D4 with an allele frequency of 17%. Here we show that homozygous carriers of this variant have markedly higher concentrations of plasma glucose (β = 3.8 mmol l−1, P = 2.5 × 10−35) and serum insulin (β = 165 pmol l−1, P = 1.5 × 10−20) 2 hours after an oral glucose load compared with individuals with other genotypes (both non-carriers and heterozygous carriers). Furthermore, homozygous carriers have marginally lower concentrations of fasting plasma glucose (β = −0.18 mmol l−1, P = 1.1 × 10−6) and fasting serum insulin (β = −8.3 pmol l−1, P = 0.0014), and their T2D risk is markedly increased (odds ratio (OR) = 10.3, P = 1.6 × 10−24). Heterozygous carriers have a moderately higher plasma glucose concentration 2 hours after an oral glucose load than non-carriers (β = 0.43 mmol l−1, P = 5.3 × 10−5). Analyses of skeletal muscle biopsies showed lower messenger RNA and protein levels of the long isoform of TBC1D4, and lower muscle protein levels of the glucose transporter GLUT4, with increasing number of p.Arg684Ter alleles. These findings are concomitant with a severely decreased insulin-stimulated glucose uptake in muscle, leading to postprandial hyperglycaemia, impaired glucose tolerance and T2D. The observed effect sizes are several times larger than any previous findings in large-scale genome-wide association studies of these traits2,3,4 and constitute further proof of the value of conducting genetic association studies outside the traditional setting of large homogeneous populations.

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Figure 1: Greenlandic study population.
Figure 2: Associations between 2-h plasma glucose levels and genotypes, as determined by Metabochip assay.
Figure 3: Effect of the p.Arg684Ter nonsense polymorphism in TBC1D4.

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Acknowledgements

We thank I. Kleist, as well as all colleagues at the Physician’s Clinic, Nuuk, Greenland. We also thank J. F. Wojtaszewski for comments and X. Zhou for discussions about GEMMA. The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent research centre at the University of Copenhagen and is partly funded by an unrestricted donation from the Novo Nordisk Foundation. This project was also funded by the Danish Council for Independent Research (Medical Sciences), the Steno Diabetes Center and the Villum Foundation. The IHIT study was supported by Karen Elise Jensen’s Foundation, NunaFonden, the Medical Research Council of Denmark, the Medical Research Council of Greenland and the Commission for Scientific Research in Greenland. None of the funding agencies had any role in the study design or in the collection or interpretation of the data.

Author information

Authors and Affiliations

Authors

Contributions

T.H. and A.A. conceived and headed the project. I.M., R.N. and A.A. designed the statistical set-up, and T.H., N.G., A.P.G. and O.P. designed the experimental set-up for the DNA extraction, genotyping and sequencing. A.L. provided the Danish samples. M.E.J., P.B. and K.B.-J. provided the Greenlandic samples, collected and defined the phenotypes and provided context for these samples. I.M. and A.A. performed the admixture, relatedness and linkage disequilibrium analyses. I.M. carried out the statistical part of the association analysis and N.G. carried out the medical part, with input from A.A., T.H., O.P. and R.N. The Chinese samples were analysed by X.W., G.S., X.J., J.A.-A. and J.W. N.G. analysed the Danish samples. X.W., G.S., X.J., J.A.-A. and J.W. performed the library constructions and sequencing. T.S.K. performed the mapping and genotyping for the sequencing data. M.F. and R.N. performed the selection analysis. N.T.K. collected muscle biopsies, and J.T.T., T.S.N., M.A.A. and J.R.Z. experimentally analysed and interpreted the TBC1D4 and GLUT4 expression data. N.G., I.M., A.A. and T.H. wrote most of the manuscript, with input from R.N., O.P., M.E.J. and P.B. All authors approved the final version of the manuscript.

Corresponding authors

Correspondence to Anders Albrechtsen or Torben Hansen.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Linkage disequilibrium (LD) and relatedness in the IHIT cohort.

a, The mean LD at chromosome 13 as a function of distance estimated for a Danish population sample (Denmark) and for the IHIT cohort (Greenland). LD is measured in r2 values, and distance is measured as number of SNPs. b, A heat map of pairwise relatedness estimates based on the Metabochip SNP data from the individuals from the IHIT cohort and their estimated admixture proportions. k1 is an estimate of the fraction of sites where two individuals share one allele identity by descent (IBD), and k2 is an estimate of the fraction of sites where they share two alleles IBD. The estimates were achieved using the software tool RelateAdmix, which provides maximum likelihood estimates that take admixture into account by allowing alleles to be IBD only if the alleles are from the same population. The vast majority of the approximately 4 million pairwise estimates have a relatedness coefficient r of less than 1%, where r = 0.5k1 + k2.

Extended Data Figure 2 Association between fasting plasma glucose level, fasting serum insulin level and 2-h serum insulin level and the SNPs on the Metabochip for the IHIT cohort.

Analyses were done using an additive model and quantile-transformed phenotypes. Left, QQ plots with 95% confidence interval. The λ value is the genomic control inflation factor. Right, Manhattan plots showing the −log10[P] values. The red dashed horizontal line indicates the 0.05 significance threshold after Bonferroni correction for multiple testing.

Extended Data Figure 3 The region surrounding rs7330796.

a, Association results for all tested Metabochip SNPs in a 2-Mb region surrounding rs7330796 (shown as a dashed vertical line). Each SNP is represented by a coloured circle. The position of the circle along the x axis shows the genomic position of the SNP. The position of the circle along the left y axis shows the −log10[P] value of the SNP when testing for association with 2-h plasma glucose levels using an additive model. The colour of the circle indicates the r2 value between the SNP and rs7330796. The circle representing rs7330796 has a label to the left of it so that it can be identified. The solid blue curve (right y axis) illustrates the recombination rates from the Chinese HapMap (CHB) panel. Bottom, the protein-coding genes in the region are shown. b, Pairwise LD in the Greenlandic population for all SNPs with a MAF >0.05 in a 10-Mb region surrounding rs7330796. LD is measured in r2 and was estimated from the IHIT study sample.

Extended Data Figure 4 Mean 2-h plasma glucose levels in the IHIT cohort stratified by Inuit admixture proportion.

a, The three possible genotypes of rs7330796 (zero copies of the minor allele (WT), one copy (HE) and two copies (HO)). b, The three possible genotypes of p.Arg684Ter (zero copies of the p.Arg684Ter variant (WT), one copy (HE) and two copies (HO)). Error bars are s.e.m. and were estimated for each admixture proportion using a standard linear regression model.

Extended Data Figure 5 Selection analysis.

a, Haplotype structure of a 500-kilobase pair (kbp) region around the coding SNP rs61736969. For each SNP, the ancestral state is coloured red, while the derived allele is coloured yellow. Haplotypes are ordered according to the coding SNP rs61736969 (p.Arg684Ter), whose position is highlighted. Haplotypes above the black line carry the derived allele for rs61736969. b, The empirical distribution of the derived intra-allelic nucleotide diversity (DIND) values, computed on a 500-kbp region, for all SNPs with the same derived allele frequency as the coding SNP rs61736969. DIND is a measure of the ratio of the nucleotide diversity of haplotypes carrying the derived allele to the nucleotide diversity of haplotypes carrying the ancestral allele. The DIND value for the coding SNP rs61736969 is highlighted by a dashed line and lies in the top 5% of the distribution.

Extended Data Figure 6 Expression of TBC1D4 and GLUT4 in humans.

a, The mRNA expression levels of the long and short TBC1D4 isoforms in a range of different human tissues (measured in arbitrary units, a.u.). b, The mRNA expression levels of both TBC1D4 isoforms in human pancreatic islet cell preparations from five individuals (in a.u.). The five individuals are not Greenlandic and do not carry the p.Arg684Ter variant. The mean value for each of the isoforms is shown as a horizontal line. c, The mRNA expression levels of the short TBC1D4 isoform in skeletal muscle from nine Greenlanders: three with zero copies of the p.Arg684Ter variant (WT), three with one copy of the p.Arg684Ter variant (HE) and three with two copies of the p.Arg684Ter variant (HO). The arbitrary units (a.u.) are on the same scale as in Fig. 3d. The mean value for each genotype group is shown as a horizontal line. d, The protein abundance of GLUT4 in the same nine Greenlanders as in c (measured in a.u.). The mean value for each genotype group is shown as a horizontal line.

Extended Data Table 1 Clinical characteristics of genotyped individuals from the IHIT and B99 Greenland population studies
Extended Data Table 2 LD and allele frequency estimates from the 1000 Genomes Project data for SNPs in TBC1D4
Extended Data Table 3 Association of TBC1D4 p.Arg684Ter with metabolic traits in the B99 cohort and in both the IHIT and B99 combined by meta-analysis

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Moltke, I., Grarup, N., Jørgensen, M. et al. A common Greenlandic TBC1D4 variant confers muscle insulin resistance and type 2 diabetes. Nature 512, 190–193 (2014). https://doi.org/10.1038/nature13425

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