Non-Cholesterol Sterol Levels Predict Hyperglycemia and Conversion to Type 2 Diabetes in Finnish Men

Peer reviewe

Mitochondrial genome copy number measured by DNA sequencing in human blood is strongly associated with metabolic traits via cell-type composition differences

Background Mitochondrial genome copy number (MT-CN) varies among humans and across tissues and is highly heritable, but its causes and consequences are not well understood. When measured by bulk DNA sequencing in blood, MT-CN may reflect a combination of the number of mitochondria per cell and cell-type composition. Here, we studied MT-CN variation in blood-derived DNA from 19184 Finnish individuals using a combination of genome (N = 4163) and exome sequencing (N = 19034) data as well as imputed genotypes (N = 17718). Results We identified two loci significantly associated with MT-CN variation: a common variant at the MYB-HBS1L locus (P = 1.6 x 10(-8)), which has previously been associated with numerous hematological parameters; and a burden of rare variants in the TMBIM1 gene (P = 3.0 x 10(-8)), which has been reported to protect against non-alcoholic fatty liver disease. We also found that MT-CN is strongly associated with insulin levels (P = 2.0 x 10(-21)) and other metabolic syndrome (metS)-related traits. Using a Mendelian randomization framework, we show evidence that MT-CN measured in blood is causally related to insulin levels. We then applied an MT-CN polygenic risk score (PRS) derived from Finnish data to the UK Biobank, where the association between the PRS and metS traits was replicated. Adjusting for cell counts largely eliminated these signals, suggesting that MT-CN affects metS via cell-type composition. Conclusion These results suggest that measurements of MT-CN in blood-derived DNA partially reflect differences in cell-type composition and that these differences are causally linked to insulin and related traits.Peer reviewe

Exome sequencing of Finnish isolates enhances rare-variant association power.

Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power

Genetic basis and outcome in a nationwide study of Finnish patients with hypertrophic cardiomyopathy

Aims Nationwide large-scale genetic and outcome studies in cohorts with hypertrophic cardiomyopathy (HCM) have not been previously published. Methods and results We sequenced 59 cardiomyopathy-associated genes in 382 unrelated Finnish patients with HCM and found 24 pathogenic or likely pathogenic mutations in six genes in 38.2% of patients. Most mutations were located in sarcomere genes (MYBPC3, MYH7, TPM1, and MYL2). Previously reported mutations by our study group (MYBPC3-Gln1061Ter, MYH7-Arg1053Gln, and TPM1-Asp175Asn) and a fourth major mutation MYH7-Val606Met accounted for 28.0% of cases. Mutations in GLA and PRKAG2 were found in three patients. Furthermore, we found 49 variants of unknown significance in 31 genes in 20.4% of cases. During a 6.7 +/- 4.2 year follow-up, annual all-cause mortality in 482 index patients and their relatives with HCM was higher than that in the matched Finnish population (1.70 vs. 0.87%; P <0.001). Sudden cardiac deaths were rare (n = 8). Systolic heart failure (hazard ratio 17.256, 95% confidence interval 3.266-91.170, P = 0.001) and maximal left ventricular wall thickness (hazard ratio 1.223, 95% confidence interval 1.098-1.363, P <0.001) were independent predictors of HCM-related mortality and life-threatening cardiac events. The patients with a pathogenic or likely pathogenic mutation underwent an implantable cardioverter defibrillator implantation more often than patients without a pathogenic or likely pathogenic mutation (12.9 vs. 3.5%, P <0.001), but there was no difference in all-cause or HCM-related mortality between the two groups. Mortality due to HCM during 10 year follow-up among the 5.2 million population of Finland was studied from death certificates of the National Registry, showing 269 HCM-related deaths, of which 32% were sudden. Conclusions We identified pathogenic and likely pathogenic mutations in 38% of Finnish patients with HCM. Four major sarcomere mutations accounted for 28% of HCM cases, whereas HCM-related mutations in non-sarcomeric genes were rare. Mortality in patients with HCM exceeded that of the general population. Finally, among 5.2 million Finns, there were at least 27 HCM-related deaths annually.Peer reviewe

Profiles of glucose metabolism in different prediabetes phenotypes, classified by fasting glycemia, 2-hour OGTT, glycated hemoglobin, and 1-hour OGTT:An IMI DIRECT study

Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants (N = 2,111) underwent a 2-h 75-g oral glucose tolerance test (OGTT) at baseline and 48 months. HbA1c was also measured. We classified participants as having isolated prediabetes defect (impaired fasting glucose [IFG], impaired glucose tolerance [IGT], or HbA1c indicative of prediabetes [IA1c]), two defects (IFG+IGT, IFG+IA1c, or IGT+IA1c), or all defects (IFG+IGT+IA1c). β-Cell function (BCF) and insulin sensitivity were assessed from OGTT. At baseline, in pooling of participants with isolated defects, they showed impairment in both BCF and insulin sensitivity compared with healthy control subjects. Pooled groups with two or three defects showed progressive further deterioration. Among groups with isolated defect, those with IGT showed lower insulin sensitivity, insulin secretion at reference glucose (ISRr), and insulin secretion potentiation (P &lt; 0.002). Conversely, those with IA1c showed higher insulin sensitivity and ISRr (P &lt; 0.0001). Among groups with two defects, we similarly found differences in both BCF and insulin sensitivity. At 48 months, we found higher type 2 diabetes incidence for progressively increasing number of prediabetes defects (odds ratio &gt;2, P &lt; 0.008). In conclusion, the prediabetes groups showed differences in type/degree of glucometabolic impairment. Compared with the pooled group with isolated defects, those with double or triple defect showed progressive differences in diabetes incidence.</p

Whole blood co-expression modules associate with metabolic traits and type 2 diabetes : an IMI-DIRECT study

Background The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D. Methods Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts. Results We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling. Conclusions Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.Peer reviewe

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

Effects of SLCO1B1 Genetic Variant on Metabolite Profile in Participants on Simvastatin Treatment

Organic-anion-transporting polypeptide 1B1 (OATP1B1), encoded by the solute carrier organic anion transporter family member 1B1 gene (SLCO1B1), is highly expressed in the liver and transports several endogenous metabolites into the liver, including statins. Previous studies have not investigated the association of SLCO1B1 rs4149056 variant with the risk of type 2 diabetes (T2D) or determined the metabolite signature of the C allele of SLCO1B1 rs4149056 (SLCO1B1 rs4149056-C allele) in a large randomly selected population. SLCO1B1 rs4149056-C inhibits OATP1B1 transporter and is associated with increased levels of blood simvastatin concentrations. Our study is to first to show that SLCO1B1 rs4149056 variant is not significantly associated with the risk of T2D, suggesting that simvastatin has a direct effect on the risk of T2D. Additionally, we investigated the effects of SLCO1B1 rs4149056-C on plasma metabolite concentrations in 1373 participants on simvastatin treatment and in 1368 age- and body-mass index (BMI)-matched participants without any statin treatment. We found 31 novel metabolites significantly associated with SLCO1B1 rs4149056-C in the participants on simvastatin treatment and in the participants without statin treatment. Simvastatin decreased concentrations of dicarboxylic acids, such as docosadioate and dodecanedioate, that may increase beta- and peroxisomal oxidation and increased the turnover of cholesterol into bile acids, resulting in a decrease in steroidogenesis due to limited availability of cholesterol for steroid synthesis. Our findings suggest that simvastatin exerts its effects on the lowering of low-density lipoprotein (LDL) cholesterol concentrations through several distinct pathways in the carriers of SLCO1B1 rs4149056-C, including dicarboxylic acids, bile acids, steroids, and glycerophospholipids

Markers of tissue-specific insulin resistance predict the worsening of hyperglycemia, incident type 2 diabetes and cardiovascular disease.

We investigated the ability of surrogate markers of tissue-specific insulin resistance (IR, Matsuda IR, Adipocyte IR, Liver IR) to predict deterioration of hyperglycemia, incident type 2 diabetes and cardiovascular events in the Metabolic Syndrome in Men (METSIM) Study. The METSIM Study includes 10,197 Finnish men, aged 45-73 years, and examined in 2005-2010. A total of 558 of 8,749 non-diabetic participants at baseline were diagnosed with new-onset diabetes and 239 with a new CVD event during a 5.9-year follow-up of this cohort (2010-2013). Compared to fasting plasma insulin level, Matsuda IR (IR in skeletal muscle) and Adipocyte IR were significantly better predictors of 2-hour plasma glucose and glucose area under the curve after adjustment for confounding factors. Liver IR was the strongest predictor of both incident type 2 diabetes (hazard ratio = 1.83, 95% confidence interval: 1.68-1.98) and cardiovascular events (hazard ratio = 1.31, 95% confidence interval: 1.15-1.48). Hazard ratios for fasting insulin were 1.37 (95% confidence interval: 1.32-1.42) and 1.11 (95% confidence interval: 1.00-1.24), respectively. Tissue-specific markers of IR, Matsuda IR and Adipocyte IR, were superior to fasting plasma insulin level in predicting worsening of hyperglycemia, and Liver IR was superior to fasting insulin level in predicting incident type 2 diabetes and cardiovascular events