Carl Platou

Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes

Genome-wide association (GWA) studies have identified multiple loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D). Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to identify variants with modest effects, we carried out meta-analysis of three T2D GWA scans comprising 10,128 individuals of European descent and ∼2.2 million SNPs (directly genotyped and imputed), followed by replication testing in an independent sample with an effective sample size of up to 53,975. We detected at least six previously unknown loci with robust evidence for association, including the JAZF1 (P = 5.0 × 10−14), CDC123-CAMK1D (P = 1.2 × 10−10), TSPAN8-LGR5 (P = 1.1 × 10−9), THADA (P = 1.1 × 10−9), ADAMTS9 (P = 1.2 × 10−8) and NOTCH2 (P = 4.1 × 10−8) gene regions. Our results illustrate the value of large discovery and follow-up samples for gaining further insights into the inherited basis of T2D.

Insomnia and the Risk of Acute Myocardial Infarction A Population Study

Background— Few prospective studies have investigated insomnia in relation to risk for coronary heart disease. We assessed insomnia symptoms and risk of acute myocardial infarction (AMI) in a large, population-based study. Methods and Results— A total of 52 610 men and women were followed up for a first AMI, and 2368 incident AMIs occurred during 11.4 years of follow-up, either identified at hospitals or by the National Cause of Death Registry. In our analyses, we adjusted for age, sex, marital status, education, shift work, blood pressure, lipids, diabetes mellitus, body mass index, physical activity, smoking, and alcohol consumption. Difficulties initiating and maintaining sleep and having a feeling of nonrestorative sleep were associated with a moderate increase in AMI risk. The multiadjusted hazard ratios for AMI were 1.45 (95% confidence interval 1.18–1.80) for people with difficulties initiating sleep almost every night, 1.30 (1.01–1.68) for those with difficulties maintaining sleep almost every night, and 1.27 (1.03–1.57) for those with a feeling of nonrestorative sleep more than once a week compared with people who never experienced these sleep difficulties. When we combined the symptoms, a dose-dependent association was seen between the number of insomnia symptoms and AMI risk (P for trend 0.003). Alternative multivariable models and different sensitivity analyses suggest that the results were robust, especially concerning difficulties initiating sleep. Conclusions— Insomnia is associated with a moderately increased risk for AMI.

Systematic evaluation of coding variation identifies a candidate causal variant in TM6SF2 influencing total cholesterol and myocardial infarction risk.

Blood lipid levels are heritable, treatable risk factors for cardiovascular disease. We systematically assessed genome-wide coding variation to identify new genes influencing lipid traits, fine map known lipid loci and evaluate whether low-frequency variants with large effects exist for these traits. Using an exome array, we genotyped 80,137 coding variants in 5,643 Norwegians. We followed up 18 variants in 4,666 Norwegians and identified ten loci with coding variants associated with a lipid trait (P < 5 × 10−8). One variant in TM6SF2 (encoding p.Glu167Lys), residing in a known genome-wide association study locus for lipid traits, influences total cholesterol levels and is associated with myocardial infarction. Transient TM6SF2 overexpression or knockdown of Tm6sf2 in mice alters serum lipid profiles, consistent with the association observed in humans, identifying TM6SF2 as a functional gene within a locus previously known as NCAN-CILP2-PBX4 or 19p13. This study demonstrates that systematic assessment of coding variation can quickly point to a candidate causal gene.

Insomnia and the risk of incident heart failure: a population study

AIMS Insomnia is highly prevalent among heart failure patients, but only a few small studies have investigated insomnia symptoms and risk of heart failure. We aimed to assess the prospective association between self-reported insomnia symptoms and the risk of incident heart failure in a large Norwegian cohort. METHODS AND RESULTS Baseline data on insomnia symptoms, including difficulty initiating sleep, difficulty maintaining sleep and having non-restorative sleep, socio-demographic variables, and health status, including established cardiovascular risk factors, were collected from 54 279 men and women 20-89 years of age who participated in the Nord-Trøndelag Health study (HUNT) between 1995 and 1997 and were free from known heart failure at baseline. The cohort was followed for incident heart failure from baseline through 2008. We used Cox proportional hazard models to assess the association of baseline insomnia symptoms with the risk of heart failure. A total of 1412 cases of heart failure occurred during a mean follow-up of 11.3 years (SD = 2.9 years), either identified at hospitals or by the National Cause of Death Registry. There was a dose-dependent association between the number of insomnia symptoms and risk of heart failure. The multi-adjusted hazard ratios were 0.96 (0.57-1.61), 1.35 (0.72-2.50), and 4.53 (1.99-10.31) for people with one, two, and three insomnia symptoms, compared with people with none of the symptoms (P for trend 0.021). CONCLUSIONS Insomnia is associated with an increased risk of incident heart failure. If our results are confirmed by others and causation is proved, evaluation of insomnia symptoms might have consequences for cardiovascular prevention.

FTO, Type 2 Diabetes, and Weight Gain Throughout Adult Life: A Meta-Analysis of 41,504 Subjects From the Scandinavian HUNT, MDC, and MPP Studies

OBJECTIVE FTO is the most important polygene identified for obesity. We aimed to investigate whether a variant in FTO affects type 2 diabetes risk entirely through its effect on BMI and how FTO influences BMI across adult life span. RESEARCH DESIGN AND METHODS Through regression models, we assessed the relationship between the FTO single nucleotide polymorphisms rs9939609, type 2 diabetes, and BMI across life span in subjects from the Norwegian population-based HUNT study using cross-sectional and longitudinal perspectives. For replication and meta-analysis, we used data from the Malmö Diet and Cancer (MDC) and Malmö Preventive Project (MPP) cohorts, comprising a total sample of 41,504 Scandinavians. RESULTS The meta-analysis revealed a highly significant association for rs9939609 with both type 2 diabetes (OR 1.13; P = 4.5 × 10−8) and the risk to develop incident type 2 diabetes (OR 1.16; P = 3.2 × 10−8). The associations remained also after correction for BMI and other anthropometric measures. Furthermore, we confirmed the strong effect on BMI (0.28 kg/m2 per risk allele; P = 2.0 × 10−26), with no heterogeneity between different age-groups. We found no differences in change of BMI over time according to rs9939609 risk alleles, neither overall (∆BMI = 0.0 [−0.05, 0.05]) nor in any individual age stratum, indicating no further weight gain attributable to FTO genotype in adults. CONCLUSIONS We have identified that a variant in FTO alters type 2 diabetes risk partly independent of its observed effect on BMI. The additional weight gain as a result of the FTO risk variant seems to occur before adulthood, and the BMI difference remains stable thereafter.

Thyroid function and the risk of coronary heart disease: 12‐year follow‐up of the HUNT Study in Norway

In a mortality follow‐up of the HUNT Study, serum TSH within the reference range was positively associated with the risk of coronary death in women. We now aimed to confirm the association of high serum TSH with the risk of coronary heart disease, using hospital‐based diagnoses of myocardial infarction.

Underlying Genetic Models of Inheritance in Established Type 2 Diabetes Associations

For most associations of common single nucleotide polymorphisms (SNPs) with common diseases, the genetic model of inheritance is unknown. The authors extended and applied a Bayesian meta-analysis approach to data from 19 studies on 17 replicated associations with type 2 diabetes. For 13 SNPs, the data fitted very well to an additive model of inheritance for the diabetes risk allele; for 4 SNPs, the data were consistent with either an additive model or a dominant model; and for 2 SNPs, the data were consistent with an additive or recessive model. Results were robust to the use of different priors and after exclusion of data for which index SNPs had been examined indirectly through proxy markers. The Bayesian meta-analysis model yielded point estimates for the genetic effects that were very similar to those previously reported based on fixed- or random-effects models, but uncertainty about several of the effects was substantially larger. The authors also examined the extent of between-study heterogeneity in the genetic model and found generally small between-study deviation values for the genetic model parameter. Heterosis could not be excluded for 4 SNPs. Information on the genetic model of robustly replicated association signals derived from genome-wide association studies may be useful for predictive modeling and for designing biologic and functional experiments.

No large-effect low-frequency coding variation found for myocardial infarction

Genome-wide association studies have identified variants, primarily common, that are associated with coronary artery disease or myocardial infarction (MI), but have not tested the majority of the low frequency and rare variation in the genome. We explored the hypothesis that previously untested low frequency (1-5% minor allele frequency) and rare (<1% minor allele frequency) coding variants are associated with MI. We genotyped 2906 MI cases and 6738 non-MI controls from Norway using the Illumina HumanExome Beadchip, allowing for direct genotyping of 85 972 polymorphic coding variants as well as 48 known GWAS SNPs. We followed-up 34 coding variants in an additional 2350 MI cases and 2318 controls from Norway. We evaluated exome array coverage in a subset of these samples using whole exome sequencing (N = 151). The exome array provided successful genotyping for an estimated 72.5% of Norwegian loss-of-function or missense variants with frequency >1% and 66.2% of variants <1% frequency observed more than once. Despite 80% power in the two-stage study (N = 14 312) to detect association with low-frequency variants with high effect sizes [odds ratio (OR) >1.86 and >1.36 for 1 and 5% frequency, respectively], we did not identify any novel genes or single variants that reached significance. This suggests that low-frequency coding variants with large effect sizes (OR >2) may not exist for MI. Larger sample sizes may identify coding variants with more moderate effects.

Insomnia and the Risk of Acute Myocardial Infarction

Background— Few prospective studies have investigated insomnia in relation to risk for coronary heart disease. We assessed insomnia symptoms and risk of acute myocardial infarction (AMI) in a large, population-based study. Methods and Results— A total of 52 610 men and women were followed up for a first AMI, and 2368 incident AMIs occurred during 11.4 years of follow-up, either identified at hospitals or by the National Cause of Death Registry. In our analyses, we adjusted for age, sex, marital status, education, shift work, blood pressure, lipids, diabetes mellitus, body mass index, physical activity, smoking, and alcohol consumption. Difficulties initiating and maintaining sleep and having a feeling of nonrestorative sleep were associated with a moderate increase in AMI risk. The multiadjusted hazard ratios for AMI were 1.45 (95% confidence interval 1.18–1.80) for people with difficulties initiating sleep almost every night, 1.30 (1.01–1.68) for those with difficulties maintaining sleep almost every night, and 1.27 (1.03–1.57) for those with a feeling of nonrestorative sleep more than once a week compared with people who never experienced these sleep difficulties. When we combined the symptoms, a dose-dependent association was seen between the number of insomnia symptoms and AMI risk (P for trend 0.003). Alternative multivariable models and different sensitivity analyses suggest that the results were robust, especially concerning difficulties initiating sleep. Conclusions— Insomnia is associated with a moderately increased risk for AMI.

Evaluation of four novel genetic variants affecting hemoglobin A1c levels in a population-based type 2 diabetes cohort (the HUNT2 study)

BackgroundChronic hyperglycemia confers increased risk for long-term diabetes-associated complications and repeated hemoglobin A1c (HbA1c) measures are a widely used marker for glycemic control in diabetes treatment and follow-up. A recent genome-wide association study revealed four genetic loci, which were associated with HbA1c levels in adults with type 1 diabetes. We aimed to evaluate the effect of these loci on glycemic control in type 2 diabetes.MethodsWe genotyped 1,486 subjects with type 2 diabetes from a Norwegian population-based cohort (HUNT2) for single-nucleotide polymorphisms (SNPs) located near the BNC2, SORCS1, GSC and WDR72 loci. Through regression models, we examined their effects on HbA1c and non-fasting glucose levels individually and in a combined genetic score model.ResultsNo significant associations with HbA1c or glucose levels were found for the SORCS1, BNC2, GSC or WDR72 variants (all P-values > 0.05). Although the observed effects were non-significant and of much smaller magnitude than previously reported in type 1 diabetes, the SORCS1 risk variant showed a direction consistent with increased HbA1c and glucose levels, with an observed effect of 0.11% (P = 0.13) and 0.13 mmol/l (P = 0.43) increase per risk allele for HbA1c and glucose, respectively. In contrast, the WDR72 risk variant showed a borderline association with reduced HbA1c levels (β = -0.21, P = 0.06), and direction consistent with decreased glucose levels (β = -0.29, P = 0.29). The allele count model gave no evidence for a relationship between increasing number of risk alleles and increasing HbA1c levels (β = 0.04, P = 0.38).ConclusionsThe four recently reported SNPs affecting glycemic control in type 1 diabetes had no apparent effect on HbA1c in type 2 diabetes individually or by using a combined genetic score model. However, for the SORCS1 SNP, our findings do not rule out a possible relationship with HbA1c levels. Hence, further studies in other populations are needed to elucidate whether these novel sequence variants, especially rs1358030 near the SORCS1 locus, affect glycemic control in type 2 diabetes.