Thomas Sparsø

A variant near MTNR1B is associated with increased fasting plasma glucose levels and type 2 diabetes risk

In genome-wide association (GWA) data from 2,151 nondiabetic French subjects, we identified rs1387153, near MTNR1B (which encodes the melatonin receptor 2 (MT2)), as a modulator of fasting plasma glucose (FPG; P = 1.3 × 10−7). In European populations, the rs1387153 T allele is associated with increased FPG (β = 0.06 mmol/l, P = 7.6 × 10−29, N = 16,094), type 2 diabetes (T2D) risk (odds ratio (OR) = 1.15, 95% CI = 1.08–1.22, P = 6.3 × 10−5, cases N = 6,332) and risk of developing hyperglycemia or diabetes over a 9-year period (hazard ratio (HR) = 1.20, 95% CI = 1.06–1.36, P = 0.005, incident cases N = 515). RT-PCR analyses confirm the presence of MT2 transcripts in neural tissues and show MT2 expression in human pancreatic islets and beta cells. Our data suggest a possible link between circadian rhythm regulation and glucose homeostasis through the melatonin signaling pathway.

Resequencing of 200 human exomes identifies an excess of low-frequency non-synonymous coding variants

Targeted capture combined with massively parallel exome sequencing is a promising approach to identify genetic variants implicated in human traits. We report exome sequencing of 200 individuals from Denmark with targeted capture of 18,654 coding genes and sequence coverage of each individual exome at an average depth of 12-fold. On average, about 95% of the target regions were covered by at least one read. We identified 121,870 SNPs in the sample population, including 53,081 coding SNPs (cSNPs). Using a statistical method for SNP calling and an estimation of allelic frequencies based on our population data, we derived the allele frequency spectrum of cSNPs with a minor allele frequency greater than 0.02. We identified a 1.8-fold excess of deleterious, non-syonomyous cSNPs over synonymous cSNPs in the low-frequency range (minor allele frequencies between 2% and 5%). This excess was more pronounced for X-linked SNPs, suggesting that deleterious substitutions are primarily recessive.

Genetic evidence that raised Sex Hormone Binding Globulin (SHBG) levels reduce the risk of type 2 diabetes

Epidemiological studies consistently show that circulating sex hormone binding globulin (SHBG) levels are lower in type 2 diabetes patients than non-diabetic individuals, but the causal nature of this association is controversial. Genetic studies can help dissect causal directions of epidemiological associations because genotypes are much less likely to be confounded, biased or influenced by disease processes. Using this Mendelian randomization principle, we selected a common single nucleotide polymorphism (SNP) near the SHBG gene, rs1799941, that is strongly associated with SHBG levels. We used data from this SNP, or closely correlated SNPs, in 27 657 type 2 diabetes patients and 58 481 controls from 15 studies. We then used data from additional studies to estimate the difference in SHBG levels between type 2 diabetes patients and controls. The SHBG SNP rs1799941 was associated with type 2 diabetes [odds ratio (OR) 0.94, 95% CI: 0.91, 0.97; P = 2 × 10−5], with the SHBG raising allele associated with reduced risk of type 2 diabetes. This effect was very similar to that expected (OR 0.92, 95% CI: 0.88, 0.96), given the SHBG-SNP versus SHBG levels association (SHBG levels are 0.2 standard deviations higher per copy of the A allele) and the SHBG levels versus type 2 diabetes association (SHBG levels are 0.23 standard deviations lower in type 2 diabetic patients compared to controls). Results were very similar in men and women. There was no evidence that this variant is associated with diabetes-related intermediate traits, including several measures of insulin secretion and resistance. Our results, together with those from another recent genetic study, strengthen evidence that SHBG and sex hormones are involved in the aetiology of type 2 diabetes.

G-allele of Intronic rs10830963 in MTNR1B Confers Increased Risk of Impaired Fasting Glycemia and Type 2 Diabetes Through an Impaired Glucose-Stimulated Insulin Release Studies Involving 19,605 Europeans

OBJECTIVE Genome-wide association studies have identified several variants within the MTNR1B locus that are associated with fasting plasma glucose (FPG) and type 2 diabetes. We refined the association signal by direct genotyping and examined for associations of the variant displaying the most independent effect on FPG with isolated impaired fasting glycemia (i-IFG), isolated impaired glucose tolerance (i-IGT), type 2 diabetes, and measures of insulin release and peripheral and hepatic insulin sensitivity. RESEARCH DESIGN AND METHODS We examined European-descent participants in the Inter99 study (n = 5,553), in a sample of young healthy Danes (n = 372), in Danish twins (n = 77 elderly and n = 97 young), in additional Danish type 2 diabetic patients (n = 1,626) and control subjects (n = 505), in the Data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR) study (n = 4,656), in the North Finland Birth Cohort 86 (n = 5,258), and in the Haguenau study (n = 1,461). RESULTS The MTNR1B intronic variant, rs10830963, carried most of the effect on FPG and showed the strongest association with FPG (combined P = 5.3 × 10−31) and type 2 diabetes. The rs10830963 G-allele increased the risk of i-IFG (odds ratio [OR] 1.64, P = 5.5 × 10−11) but not i-IGT. The G-allele was associated with a decreased insulin release after oral and intravenous glucose challenges (P < 0.01) but not after injection of tolbutamide. In elderly twins, the G-allele associated with hepatic insulin resistance (P = 0.017). CONCLUSIONS The G-allele of MTNR1B rs10830963 increases risk of type 2 diabetes through a state of i-IFG and not through i-IGT. The same allele associates with estimates of β-cell dysfunction and hepatic insulin resistance.

Combined Analyses of 20 Common Obesity Susceptibility Variants

OBJECTIVE Genome-wide association studies and linkage studies have identified 20 validated genetic variants associated with obesity and/or related phenotypes. The variants are common, and they individually exhibit small-to-modest effect sizes. RESEARCH DESIGN AND METHODS In this study we investigate the combined effect of these variants and their ability to discriminate between normal weight and overweight/obese individuals. We applied receiver operating characteristics (ROC) curves, and estimated the area under the ROC curve (AUC) as a measure of the discriminatory ability. The analyses were performed cross-sectionally in the population-based Inter99 cohort where 1,725 normal weight, 1,519 overweight, and 681 obese individuals were successfully genotyped for all 20 variants. RESULTS When combining all variants, the 10% of the study participants who carried more than 22 risk-alleles showed a significant increase in probability of being both overweight with an odds ratio of 2.00 (1.47–2.72), P = 4.0 × 10−5, and obese with an OR of 2.62 (1.76–3.92), P = 6.4 × 10−7, compared with the 10% of the study participants who carried less than 14 risk-alleles. Discrimination ability for overweight and obesity, using the 20 single nucleotide polymorphisms (SNPs), was determined to AUCs of 0.53 and 0.58, respectively. When combining SNP data with conventional nongenetic risk factors of obesity, the discrimination ability increased to 0.64 for overweight and 0.69 for obesity. The latter is significantly higher (P < 0.001) than for the nongenetic factors alone (AUC = 0.67). CONCLUSIONS The discriminative value of the 20 validated common obesity variants is at present time sparse and too weak for clinical utility, however, they add to increase the discrimination ability of conventional nongenetic risk factors.

Genetic Architecture of Vitamin B 12 and Folate Levels Uncovered Applying Deeply Sequenced Large Datasets

Genome-wide association studies have mainly relied on common HapMap sequence variations. Recently, sequencing approaches have allowed analysis of low frequency and rare variants in conjunction with common variants, thereby improving the search for functional variants and thus the understanding of the underlying biology of human traits and diseases. Here, we used a large Icelandic whole genome sequence dataset combined with Danish exome sequence data to gain insight into the genetic architecture of serum levels of vitamin B12 (B12) and folate. Up to 22.9 million sequence variants were analyzed in combined samples of 45,576 and 37,341 individuals with serum B12 and folate measurements, respectively. We found six novel loci associating with serum B12 (CD320, TCN2, ABCD4, MMAA, MMACHC) or folate levels (FOLR3) and confirmed seven loci for these traits (TCN1, FUT6, FUT2, CUBN, CLYBL, MUT, MTHFR). Conditional analyses established that four loci contain additional independent signals. Interestingly, 13 of the 18 identified variants were coding and 11 of the 13 target genes have known functions related to B12 and folate pathways. Contrary to epidemiological studies we did not find consistent association of the variants with cardiovascular diseases, cancers or Alzheimers disease although some variants demonstrated pleiotropic effects. Although to some degree impeded by low statistical power for some of these conditions, these data suggest that sequence variants that contribute to the population diversity in serum B12 or folate levels do not modify the risk of developing these conditions. Yet, the study demonstrates the value of combining whole genome and exome sequencing approaches to ascertain the genetic and molecular architectures underlying quantitative trait associations.

Physiologic Characterization of Type 2 Diabetes–Related Loci

For the past two decades, genetics has been widely explored as a tool for unraveling the pathogenesis of diabetes. Many risk alleles for type 2 diabetes and hyperglycemia have been detected in recent years through massive genome-wide association studies and evidence exists that most of these variants influence pancreatic β-cell function. However, risk alleles in five loci seem to have a primary impact on insulin sensitivity. Investigations of more detailed physiologic phenotypes, such as the insulin response to intravenous glucose or the incretion hormones, are now emerging and give indications of more specific pathologic mechanisms for diabetes-related risk variants. Such studies have shed light on the function of some loci but also underlined the complex nature of disease mechanism. In the future, sequencing-based discovery of low-frequency variants with higher impact on intermediate diabetes-related traits is a likely scenario and identification of new pathways involved in type 2 diabetes predisposition will offer opportunities for the development of novel therapeutic and preventative approaches.

AHSG Tag Single Nucleotide Polymorphisms Associate With Type 2 Diabetes and Dyslipidemia: Studies of Metabolic Traits in 7,683 White Danish Subjects

OBJECTIVE—The gene encoding the α2 Heremans-Schmid glycoprotein (AHSG) is a credible biological and positional candidate gene for type 2 diabetes and the metabolic syndrome, and previous attempts to relate AHSG variation with type 2 diabetes and obesity in Swedish and French Caucasians have been largely successful. We related seven frequent AHSG tag single nucleotide polymorphisms to a range of metabolic traits, including type 2 diabetes, obesity, and dyslipidemia. RESEARCH DESIGN AND METHODS—The polymorphisms were genotyped in 7,683 white Danish subjects using Taqman allelic discrimination or chip-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, providing a statistical power of >99% to replicate previous findings. Data were analyzed in case-control and haplotype settings, and quantitative metabolic traits were examined for association. Moreover, epistatic effects between AHSG variants and insulin receptor substrate-1 (IRS1) and β-2-adrenergic receptor polymorphisms were investigated. RESULTS—The −469T>G (rs2077119) and IVS6+98C>T (rs2518136) polymorphisms were associated with type 2 diabetes (P = 0.007 and P = 0.006, respectively, or Pcorr = 0.04 and Pcorr = 0.03, respectively, following correction for multiple hypothesis testing), and in a combined analysis of the present and a previous study −469T>G remained significant (odds ratio 0.90 [95% CI 0.84–0.97]; P = 0.007). Furthermore, two AHSG haplotypes were associated with dyslipidemia (P = 0.003 and Pcorr = 0.009). Thr248Met (rs4917) tended to associate with lower fasting and post–oral glucose tolerance test serum insulin release (P = 0.02, Pcorr = 0.1 for fasting and P = 0.04, Pcorr = 0.2 for area under the insulin curve) and improved insulin sensitivity estimated by the homeostasis model assessment of insulin resistance (9.0 vs. 8.6 mmol · l−1 · pmol−1 · l−1; P = 0.01, Pcorr = 0.06). Indications of epistatic effects of AHSG variants with the IRS1 Gly971Arg polymorphism were observed for fasting serum triglyceride concentrations. CONCLUSIONS—Based on present and previous findings, common variation in AHSG may contribute to the interindividual variation in metabolic traits.

Type 2 Diabetes Risk Alleles Near BCAR1 and in ANK1 Associate With Decreased β-Cell Function Whereas Risk Alleles Near ANKRD55 and GRB14 Associate With Decreased Insulin Sensitivity in the Danish Inter99 Cohort

CONTEXT Recently, 10 novel type 2 diabetes (T2D) susceptibility single nucleotide polymorphisms (SNPs) in ZMIZ1, ANK1, KLHDC5, TLE1, ANKRD55, CILP2, MC4R, BCAR1, HMG20A, and GRB14 loci were discovered in MetaboChip-genotyped populations of European ancestry. OBJECTIVE The aim of the present study was to characterize prediabetic quantitative traits underlying these SNP associations and to calculate the amount of interindividual variation in glycemic traits explained by these and previous T2D susceptibility variants. DESIGN AND PARTICIPANTS A total of 5739 Danish individuals naive to glucose-lowering medication were included in quantitative trait studies, and case-control analyses were performed in 1892 patients with T2D and 6603 normoglycemic control subjects. Participants without known T2D underwent an oral glucose tolerance test, and measures of insulin release and sensitivity were estimated from insulinogenic, disposition, BIGTT, and Matsuda indexes. RESULTS We confirmed associations of ZMIZ1, KLHDC5, CILP2, HMG20A, ANK1, ANKRD55, and BCAR1 with T2D. The risk T allele of BCAR1 rs7202877 associated with decreased disposition index (P = .02). The C allele of ANK1 rs516946 associated with decreased insulinogenic (P = .005) and disposition (P = .002) indexes. The G allele of ANKRD55 rs459193 associated with decreased Matsuda index (P = .02) adjusted for waist circumference. The C allele of GRB14 rs13389219 associated with both increased insulinogenic (P = .04) and decreased Matsuda (P = .05) indexes. All validated European T2D variants still only explained a few percentage points of glycemic trait variation. CONCLUSIONS BCAR1 rs7202877 may mediate its diabetogenic impact through impaired β-cell function, but this finding needs to be replicated in independent studies. In addition, we substantiated previous evidence that ANK1 rs516946 confers impaired insulin release and that ANKRD55 rs459193 and GRB14 rs13389219 associate with insulin resistance.

Genetic Risk Score of 46 Type 2 Diabetes Risk Variants Associates With Changes in Plasma Glucose and Estimates of Pancreatic β-Cell Function Over 5 Years of Follow-Up

More than 40 genetic risk variants for type 2 diabetes have been validated. We aimed to test whether a genetic risk score associates with the incidence of type 2 diabetes and with 5-year changes in glycemic traits and whether the effects were modulated by changes in BMI and lifestyle. The Inter99 study population was genotyped for 46 variants, and a genetic risk score was constructed. During a median follow-up of 11 years, 327 of 5,850 individuals developed diabetes. Physical examinations and oral glucose tolerance tests were performed at baseline and after 5 years (n = 3,727). The risk of incident type 2 diabetes was increased with a hazard ratio of 1.06 (95% CI 1.03–1.08) per risk allele. While the population in general had improved glucose regulation during the 5-year follow-up period, each additional allele in the genetic risk score was associated with a relative increase in fasting, 30-min, and 120-min plasma glucose values and a relative decrease in measures of β-cell function over the 5-year period, whereas indices of insulin sensitivity were unaffected. The effect of the genetic risk score on 5-year changes in fasting plasma glucose was stronger in individuals who increased their BMI. In conclusion, a genetic risk score based on 46 variants associated strongly with incident type 2 diabetes and 5-year changes in plasma glucose and β-cell function. Individuals who gain weight may be more susceptible to the cumulative impact of type 2 diabetes risk variants on fasting plasma glucose.