Metabolic Syndrome In Men Study Research Articles

Mediation analysis of multiple mediators with incomplete omics data.

There is an increasing interest in using multiple types of omics features (e.g., DNA sequences, RNA expressions, methylation, protein expressions, and metabolic profiles) to study how the relationships between phenotypes and genotypes may be mediated by other omics markers. Genotypes and phenotypes are typically available for all subjects in genetic studies, but typically, some omics data will be missing for some subjects, due to limitations such as cost and sample quality. In this article, we propose a powerful approach for mediation analysis that accommodates missing data among multiple mediators and allows for various interaction effects. We formulate the relationships among genetic variants, other omics measurements, and phenotypes through linear regression models. We derive the joint likelihood for models with two mediators, accounting for arbitrary patterns of missing values. Utilizing computationally efficient and stable algorithms, we conduct maximum likelihood estimation. Our methods produce unbiased and statistically efficient estimators. We demonstrate the usefulness of our methods through simulation studies and an application to the Metabolic Syndrome in Men study.

Metabolite Signature of Simvastatin Treatment Involves Multiple Metabolic Pathways.

Statins inhibit the 3-hydroxy-3-methylglutaryl-CoA reductase enzyme and are the most widely used medication for hypercholesterolemia. Previous studies on the metabolite signature of simvastatin treatment have included only a small number of metabolites. We performed a high-throughput liquid chromatography–tandem mass spectroscopy profiling on the effects of simvastatin treatment on 1098 metabolite concentrations in the participants of the METSIM (Metabolic Syndrome In Men) study including 1332 participants with simvastatin treatment and 6200 participants without statin treatment. We found that simvastatin exerts profound pleiotropic effects on different metabolite pathways, affecting not only lipids, but also amino acids, peptides, nucleotides, carbohydrates, co-factors, vitamins, and xenobiotics. We identified 321 metabolites significantly associated with simvastatin treatment, and 313 of these metabolites were novel. Our study is the first comprehensive evaluation of the metabolic signature of simvastatin treatment in a large population-based study.

Transethnic meta-analysis of exome-wide variants identifies new loci associated with male-specific metabolic syndrome.

Metabolic syndrome (MetS) is a group of very common human conditions promoting strong understand the impact of rare variants, beyond exome-wide association studies, to potentially discover causative variants, across different ethnic populations. We performed transethnic, exome-wide MetS association studies on MetS in men. We analyzed genotype data of 5302 European subjects (2658 cases and 2644 controls), in the discovery stage of the European METabolic Syndrome In Men study, generated from exome chips, and 2481 subjects (714 cases and 1767 controls), in the replication stage, across 6 independent cohorts of 5 ancestries (T2D-GENES consortium), using whole-exome sequencing. We therefore evaluated gene-level and variant-level associations, of rare variants for MetS, using logistic regression (LR) and multivariate analyses (MulA). Gene-based association found the gene for the cholesteryl ester transfer protein (CETP) (from MulA, p value = 4.67×10-9; from LR, p value = 0.009) to well associate with MetS. At two missense variants, from 8 rare variants in CETP, Ala390Pro (rs5880) (from MulA, p value = 1.28×10-7; from LR, p value = 1.34×10-4) and Arg468Gln (rs1800777) (from MulA, p value = 2.40×10-5; from LR, p value = 1.49×10-3) significantly associated with MetS across five ancestries. Our findings highlight novel rare variants of genes that confer MetS susceptibility, in Europeans, that are shared with diverse populations, emphasizing an opportunity to further understand the biological target or genes that underlie MetS, across populations.

Prevalence, genotype and phenotype of familial hypercholesterolemia in 10,194 Finnish men

Abstract Background Familial hypercholesterolemia (FH) is the most frequent monogenic disease with an estimated prevalence of 1:250. The prevalence of different variants varies widely between the populations. According to previous studies, the prevalence of heterozygous FH in Finland has been reported to be 1:400–650, seven Finnish LDLR founder mutations having been considered to cause 80% of FH. Purpose To investigate the genetics of FH in the large Finnish population-based study. Methods The whole exome sequencing using Next Generation Sequencing method was performed for 10,194 men from eastern Finland who participated in the METSIM (Metabolic Syndrome in Men) study. The findings were confirmed by Sanger sequencing. The coding regions of the FH causing genes LDLR, APOB and PCSK9 were sequenced. The pathogenicity of the variants was classified according to the ACMG guidelines, and using the Genome Aggregation Database (gnomAD), and the ClinVar archive. Results Total 22 individuals of 10,194 carry 8 different pathogenic/likely pathogenic (P/LP) FH variants (7 LDLR variants, 1 APOB variant and 0 PCK9 variants). Seven LDLR gene variants classified as P/LP were detected in 21 individuals. Two of the seven variants are founder mutations (p.Pro309Lysfs*59, p.Arg595Gln), four are other previously reported variants (p.Arg124Trp, p.Glu228*, p.Asp266Asn, p.Asp445Glu) and one is a novel variant (p.Gly396Ala). Of the 21 individuals carrying P/LP LDLR variants, 16 carry founder mutations and five other P/LP LDLR variants. Of individuals carrying any P/LP LDLR variant, 28.6% had premature (men <55 years, women <60 years) atherosclerotic cardiovascular disease (CVD): coronary artery disease (CAD) 28.6%, peripheral artery disease (PAD) 0.0%, and stroke or TIA 0.0%. CVD at any age was diagnosed in 38.1% (CAD 33.3%, PAD 4.8%, stroke or TIA 9.5%). Only one individual from 10,194 carry APOB variant which is classified as P/LP. The detected APOB variant is a previously reported variant (p.Gln4494del). None of the 10,194 individuals carry P/LP PCSK9 variants. Thus, the prevalence of P/LP FH variants in the population from eastern Finland was 0.22%, 1 in 463.4 (LDLR variants 0.21%, 1 in 485; APOB variants 0.01%, 1 in 10 194). Of the P/LP variant carriers, 72.7% carry founder mutation of the LDLR, and 27.3% carry other LDLR and APOB variants. Conclusions The prevalence of heterozygous FH in the population-based study of 10,194 men from eastern Finland was 1 in 463.4, which is about the same as previously reported. LDLR variants accounted for the majority of FH cases, and although previously reported Finnish LDLR founder mutations were common, about 30% of the mutations detected were other LDLR and APOB variants. Pathogenic/likely pathogenic APOB variants were, however, rare and PCSK9 variants were not found. Funding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): Kuopio university hospital

The Association of 9 Amino Acids With Cardiovascular Events in Finnish Men in a 12-Year Follow-up Study.

Background and AimsTo investigate the significance of 9 amino acids as risk factors for incident cardiovascular disease events in 9584 Finnish men.Materials and MethodsA total of 9584 men (age 57.4 ± 7.0 years, body mass index 27.2 ± 4.2 kg/m2) from the Metabolic Syndrome in Men study without cardiovascular disease and type 1 diabetes at baseline were included in this study. A total of 662 coronary artery disease (CAD) events, 394 ischemic stroke events, and 966 cardiovascular disease (CVD; CAD and stroke combined) events were recorded in a 12.3-year follow-up. Amino acids were measured using nuclear magnetic resonance platform.ResultsIn Cox regression analysis, phenylalanine and tyrosine were significantly associated with increased risk of CAD and CVD events, and phenylalanine with increased risk of ischemic stroke after the adjustment for confounding factors. Glutamine was significantly associated with decreased risk of stroke and CVD events and nominally with CAD events. Alanine was nominally associated with CAD events.ConclusionWe identified alanine as a new amino acid associated with increased risk of CAD and glutamine as a new amino acid associated with decreased risk of ischemic stroke. We also confirmed that phenylalanine and tyrosine were associated with CAD, ischemic stroke, and CVD events.

Novel biomarkers associated with incident heart failure in 10106 Finnish men.

AimsThere are only a few studies on novel biomarkers for incident heart failure (HF). We investigated the association of multiple circulating biomarkers with incident HF in a large prospective population‐based study.Methods and resultsConventional risk factors and inflammatory biomarkers were measured, and systemic metabolic measures determined by a high‐throughput serum nuclear magnetic resonance platform in a population‐based Metabolic Syndrome in Men study including 10 106 Finnish men without HF at baseline. During an 8.8 year follow‐up, 172 (1.7%) participants developed HF. Adiponectin, high‐sensitivity C‐reactive protein (hs‐CRP), glycoprotein acetyls, alanine, phenylalanine, glycerol, and pyruvate were associated with incident HF in unadjusted Cox regression analyses, in addition to age, systolic blood pressure, body mass index (BMI), waist circumference, fasting plasma glucose and insulin, haemoglobin A1c (HbA1c), and urinary albumin excretion rate (UAER). After adjustment for age, BMI, diabetes, and statin medication, only adiponectin [hazard ratio (HR) 1.18 (1.10–1.26, P = 4.1E‐08)], pyruvate [HR 1.38 (1.28–1.50, P = 8.2E‐05)], and UAER [HR 1.15 (1.11—1.18, P = 7.8E‐06)] remained statistically significant. In principal component analysis of biomarkers associated with HF in univariate Cox regression analysis, we identified six components, explaining 61.7% of total variance. Four principal components, one with significant loadings on waist, BMI, fasting plasma insulin, interleukin 1 receptor antagonist, and hs‐CRP; another on pyruvate, glycoprotein acetyls, alanine, glycerol and HbA1c; third on age and glomerular filtration rate; and fourth on systolic blood pressure, UAER, and adiponectin, significantly associated with incident HF.ConclusionsSeveral novel metabolic and inflammatory biomarkers were associated with incident HF, suggesting early activation of respective pathways in the pathogenesis of HF.

Adipose Tissue Gene Expression Associations Reveal Hundreds of Candidate Genes for Cardiometabolic Traits

Genome-wide association studies (GWASs) have identified thousands of genetic loci associated with cardiometabolic traits including type 2 diabetes (T2D), lipid levels, body fat distribution, and adiposity, although most causal genes remain unknown. We used subcutaneous adipose tissue RNA-seq data from 434 Finnish men from the METSIM study to identify 9,687 primary and 2,785 secondary cis-expression quantitative trait loci (eQTL; <1 Mb from TSS, FDR < 1%). Compared to primary eQTL signals, secondary eQTL signals were located further from transcription start sites, had smaller effect sizes, and were less enriched in adipose tissue regulatory elements compared to primary signals. Among 2,843 cardiometabolic GWAS signals, 262 colocalized by LD and conditional analysis with 318 transcripts as primary and conditionally distinct secondary cis-eQTLs, including some across ancestries. Of cardiometabolic traits examined for adipose tissue eQTL colocalizations, waist-hip ratio (WHR) and circulating lipid traits had the highest percentage of colocalized eQTLs (15% and 14%, respectively). Among alleles associated with increased cardiometabolic GWAS risk, approximately half (53%) were associated with decreased gene expression level. Mediation analyses of colocalized genes and cardiometabolic traits within the 434 individuals provided further evidence that gene expression influences variant-trait associations. These results identify hundreds of candidate genes that may act in adipose tissue to influence cardiometabolic traits.

Genetic Regulation of Enoyl-CoA Hydratase Domain-Containing 3 in Adipose Tissue Determines Insulin Sensitivity in African Americans and Europeans.

Insulin resistance (IR) is a harbinger of type 2 diabetes (T2D) and partly determined by genetic factors. However, genetically regulated mechanisms of IR remain poorly understood. Using gene expression, genotype, and insulin sensitivity data from the African American Genetics of Metabolism and Expression (AAGMEx) cohort, we performed transcript-wide correlation and expression quantitative trait loci (eQTL) analyses to identify IR-correlated cis-regulated transcripts (cis-eGenes) in adipose tissue. These IR-correlated cis-eGenes were tested in the European ancestry individuals in the Metabolic Syndrome in Men (METSIM) cohort for trans-ethnic replication. Comparison of Matsuda index–correlated transcripts in AAGMEx with the METSIM study identified significant correlation of 3,849 transcripts, with concordant direction of effect for 97.5% of the transcripts. cis-eQTL for 587 Matsuda index–correlated genes were identified in both cohorts. Enoyl-CoA hydratase domain-containing 3 (ECHDC3) was the top-ranked Matsuda index–correlated cis-eGene. Expression levels of ECHDC3 were positively correlated with Matsuda index, and regulated by cis-eQTL, rs34844369 being the top cis-eSNP in AAGMEx. Silencing of ECHDC3 in adipocytes significantly reduced insulin-stimulated glucose uptake and Akt Ser473 phosphorylation. RNA sequencing analysis identified 691 differentially expressed genes in ECHDC3-knockdown adipocytes, which were enriched in γ-linolenate biosynthesis, and known IR genes. Thus, our studies elucidated genetic regulatory mechanisms of IR and identified genes and pathways in adipose tissue that are mechanistically involved in IR.

Regulation of Brown Adipose Tissue Function by HuR

Stimulating the metabolic function of brown adipose tissue (BAT) and/or inducing the beiging of white adipocytes (WAT) to BAT‐like cells represent potential therapeutic strategies for increasing energy expenditure and reducing obesity. HuR (ELAVL1) is an RNA binding protein that mediates gene expression through stabilization of mRNA targets and is highly expressed in both WAT and BAT. We identified an inverse correlation between HuR expression and obesity in humans via the METabolic Syndrome In Men study of Finnish men. Thus, we hypothesized that HuR expression in adipocytes plays a critical role in maintaining metabolic homeostasis.Our results show that, compared to control littermates, adipocyte‐specific HuR‐null (adipo‐HuR−/−) mice display a lean phenotype with decreased fat mass and increased energy expenditure, independent of diet. Interestingly, adipo‐HuR−/− mice also show a disruption of BAT structure and function, with increased lipid droplet size, decreased BAT density, and an inability to thermoregulate when subjected to cold. Examination of skeletal muscle suggests that the lean phenotype in adipo‐HuR−/− mice is due to compensatory shivering to thermoregulate in the absence of functional BAT, a result consistent with UCP1−/− mice. Surprisingly, we found no difference in basal expression of UCP1 in BAT from control and adipo‐HuR−/− mice. However, HuR is activated downstream of β3 adrenergic stimulation and appears to play a role in cold/β3 induced UCP1 expression. Additionally, adipo−HuR−/− mice show a decrease in mitochondrial density in both BAT and subcutaneous (sc) WAT, as well as a decrease in brown/beige adipocyte marker genes (PRDM16, Elovl3) in scWAT.In conclusion, our results demonstrate that HuR plays a central role in the structure and function of BAT. Work is ongoing to identify the transcriptome wide changes in HuR‐dependent gene expression as well as the potential role of HuR in beiging of WAT.Support or Funding InformationThis work was partially funded by a University of Cincinnati Heart, Lung, and Vascular Institute Pilot Grant (MT, APO).This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Systems Genetics Approach to Biomarker Discovery: GPNMB and Heart Failure in Mice and Humans.

We describe a simple bioinformatics method for biomarker discovery that is based on the analysis of global transcript levels in a population of inbred mouse strains showing variation for disease-related traits. This method has advantages such as controlled environment and accessibility to heart and plasma tissue in the preclinical selection stage. We illustrate the approach by identifying candidate heart failure (HF) biomarkers by overlaying mouse transcriptome and clinical traits from 91 Hybrid Mouse Diversity Panel (HMDP) inbred strains and human HF transcriptome from the Myocardial Applied Genomics Network (MAGNet) consortium. We found that some of the top differentially expressed genes correlated with known human HF biomarkers, such as galectin-3 and tissue inhibitor of metalloproteinase 1. Using ELISA assays, we investigated one novel candidate, Glycoprotein NMB, in a mouse model of chronic β-adrenergic stimulation by isoproterenol (ISO) induced HF. We observed significantly lower GPNMB plasma levels in the ISO model compared to the control group (p-value = 0.007). In addition, we assessed GPNMB plasma levels among 389 HF cases and controls from the METabolic Syndrome In Men (METSIM) study. Lower levels of GPNMB were also observed in patients with HF from the METSIM study compared to non-HF controls (p-value < 0.0001). In summary, we have identified several candidate biomarkers for HF using the cardiac transcriptome data in a population of mice that may be directly relevant and applicable to human populations.

Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: A soft clustering analysis.

BackgroundType 2 diabetes (T2D) is a heterogeneous disease for which (1) disease-causing pathways are incompletely understood and (2) subclassification may improve patient management. Unlike other biomarkers, germline genetic markers do not change with disease progression or treatment. In this paper, we test whether a germline genetic approach informed by physiology can be used to deconstruct T2D heterogeneity. First, we aimed to categorize genetic loci into groups representing likely disease mechanistic pathways. Second, we asked whether the novel clusters of genetic loci we identified have any broad clinical consequence, as assessed in four separate subsets of individuals with T2D.Methods and findingsIn an effort to identify mechanistic pathways driven by established T2D genetic loci, we applied Bayesian nonnegative matrix factorization (bNMF) clustering to genome-wide association study (GWAS) results for 94 independent T2D genetic variants and 47 diabetes-related traits. We identified five robust clusters of T2D loci and traits, each with distinct tissue-specific enhancer enrichment based on analysis of epigenomic data from 28 cell types. Two clusters contained variant-trait associations indicative of reduced beta cell function, differing from each other by high versus low proinsulin levels. The three other clusters displayed features of insulin resistance: obesity mediated (high body mass index [BMI] and waist circumference [WC]), “lipodystrophy-like” fat distribution (low BMI, adiponectin, and high-density lipoprotein [HDL] cholesterol, and high triglycerides), and disrupted liver lipid metabolism (low triglycerides). Increased cluster genetic risk scores were associated with distinct clinical outcomes, including increased blood pressure, coronary artery disease (CAD), and stroke. We evaluated the potential for clinical impact of these clusters in four studies containing individuals with T2D (Metabolic Syndrome in Men Study [METSIM], N = 487; Ashkenazi, N = 509; Partners Biobank, N = 2,065; UK Biobank [UKBB], N = 14,813). Individuals with T2D in the top genetic risk score decile for each cluster reproducibly exhibited the predicted cluster-associated phenotypes, with approximately 30% of all individuals assigned to just one cluster top decile. Limitations of this study include that the genetic variants used in the cluster analysis were restricted to those associated with T2D in populations of European ancestry.ConclusionOur approach identifies salient T2D genetically anchored and physiologically informed pathways, and supports the use of genetics to deconstruct T2D heterogeneity. Classification of patients by these genetic pathways may offer a step toward genetically informed T2D patient management.

Identification of seven novel loci associated with amino acid levels using single-variant and gene-based tests in 8545 Finnish men from the METSIM study

Comprehensive metabolite profiling captures many highly heritable traits, including amino acid levels, which are potentially sensitive biomarkers for disease pathogenesis. To better understand the contribution of genetic variation to amino acid levels, we performed single variant and gene-based tests of association between nine serum amino acids (alanine, glutamine, glycine, histidine, isoleucine, leucine, phenylalanine, tyrosine, and valine) and 16.6 million genotyped and imputed variants in 8545 non-diabetic Finnish men from the METabolic Syndrome In Men (METSIM) study with replication in Northern Finland Birth Cohort (NFBC1966). We identified five novel loci associated with amino acid levels (P = < 5×10-8): LOC157273/PPP1R3B with glycine (rs9987289, P = 2.3×10-26); ZFHX3 (chr16:73326579, minor allele frequency (MAF) = 0.42%, P = 3.6×10-9), LIPC (rs10468017, P = 1.5×10-8), and WWOX (rs9937914, P = 3.8×10-8) with alanine; and TRIB1 with tyrosine (rs28601761, P = 8×10-9). Gene-based tests identified two novel genes harboring missense variants of MAF <1% that show aggregate association with amino acid levels: PYCR1 with glycine (Pgene = 1.5×10-6) and BCAT2 with valine (Pgene = 7.4×10-7); neither gene was implicated by single variant association tests. These findings are among the first applications of gene-based tests to identify new loci for amino acid levels. In addition to the seven novel gene associations, we identified five independent signals at established amino acid loci, including two rare variant signals at GLDC (rs138640017, MAF=0.95%, Pconditional = 5.8×10-40) with glycine levels and HAL (rs141635447, MAF = 0.46%, Pconditional = 9.4×10-11) with histidine levels. Examination of all single variant association results in our data revealed a strong inverse relationship between effect size and MAF (Ptrend<0.001). These novel signals provide further insight into the molecular mechanisms of amino acid metabolism and potentially, their perturbations in disease.

Differential Associations of Inflammatory Markers With Insulin Sensitivity and Secretion: The Prospective METSIM Study.

Context:Low-grade inflammation is involved in the development of type 2 diabetes and cardiovascular disease (CVD); however, prospective studies evaluating inflammatory markers as predictors of changes in insulin secretion and insulin sensitivity are lacking.Objective:We investigated the associations of glycoprotein acetyls (GlycA), interleukin-1 receptor antagonist (IL-1RA), and high-sensitivity C-reactive protein (hs-CRP) with insulin secretion, insulin sensitivity, incident type 2 diabetes, hypertension, CVD events, and total mortality in the prospective Metabolic Syndrome in Men (METSIM) study.Design:A prospective study.Participants:The cross-sectional METSIM study included 8749 nondiabetic Finnish men aged 45 to 73 years, who had been randomly selected from the population register of Kuopio, Finland. A total of 5401 men participated in the 6.8-year follow-up study.Main Outcome Measures:Changes in insulin secretion, insulin sensitivity, and cardiometabolic traits during the follow-up period and the incidence of type 2 diabetes, hypertension, CVD events, and total mortality.Results:During the follow-up period, GlycA was associated with impaired insulin secretion, hyperglycemia, incident type 2 diabetes (hazard ratio, 1.37; 95% confidence interval, 1.29 to 1.46) and CVD (hazard ratio, 1.21; 95% confidence interval, 1.12 to 1.32). IL-1RA and hs-CRP were associated with adverse changes in insulin sensitivity and obesity-related traits and with total mortality (hazard ratio, 1.13; 95% confidence interval, 1.07 to 1.20; and hazard ratio, 1.08; 95% confidence interval, 1.04 to 1.11, respectively).Conclusions:Inflammatory markers differentially predicted changes in insulin secretion and insulin sensitivity. GlycA predicted impaired insulin secretion, and IL-1RA and hs-CRP predicted changes in insulin sensitivity. Combining the three markers improved the prediction of disease outcomes, suggesting that they capture different aspects of low-grade inflammation.

Genetic risk scores in the prediction of plasma glucose, impaired insulin secretion, insulin resistance and incident type 2 diabetes in the METSIM study.

Many SNPs have been associated with glycaemic traits and type 2 diabetes, but their joint effects on glycaemic traits and the underlying mechanisms leading to hyperglycaemia over time are largely unknown. We aimed to investigate the association of six genetic risk scores (GRSs) with changes in plasma glucose, insulin sensitivity, insulin secretion and incident type 2 diabetes in the prospective METabolic Syndrome In Men (METSIM) study. We generated weighted GRSs for fasting plasma glucose ([FPG] GRSFPG, 35 SNPs), 2h plasma glucose ([2hPG] GRS2hPG, 9 SNPs), insulin secretion (GRSIS, 17 SNPs), insulin resistance (GRSIR, 9 SNPs) and BMI (GRSBMI, 95 SNPs) and a non-weighted GRS for type 2 diabetes (GRST2D, 76 SNPs) in up to 8749 non-diabetic Finnish men. Linear regression was used to test associations of the GRSs with changes in glycaemic traits over time. GRST2D, GRSFPG and GRSIS were associated with an increase in FPG, GRST2D with an increase in glucose AUC and a decrease in insulin secretion, and GRS2hPG with an increase in 2hPG during the follow-up (p<0.0017 for all models). GRST2D, GRSFPG and GRSIS were associated with incident type 2 diabetes (p<0.008 for all models). GRSBMI and GRSIR were not significantly associated with any changes in glycaemic traits. In the METSIM follow-up study, GRST2D, GRSFPG and GRSIS were associated with the worsening of FPG and an increase in incident type 2 diabetes. GRST2D was additionally associated with a decrease in insulin secretion, and GRS2hPG with an increase in 2hPG.

The Metabolic Syndrome in Men study: a resource for studies of metabolic and cardiovascular diseases

The Metabolic Syndrome in Men (METSIM) study is a population-based study including 10,197 Finnish men examined in 2005-2010. The aim of the study is to investigate nongenetic and genetic factors associated with the risk of T2D and CVD, and with cardiovascular risk factors. The protocol includes a detailed phenotyping of the participants, an oral glucose tolerance test, fasting laboratory measurements including proton NMR measurements, mass spectometry metabolomics, adipose tissue biopsies from 1,400 participants, and a stool sample. In our ongoing follow-up study, we have, to date, reexamined 6,496 participants. Extensive genotyping and exome sequencing have been performed for essentially all METSIM participants, and >2,000 METSIM participants have been whole-genome sequenced. We have identified several nongenetic markers associated with the development of diabetes and cardiovascular events, and participated in several genetic association studies to identify gene variants associated with diabetes, hyperglycemia, and cardiovascular risk factors. The generation of a phenotype and genotype resource in the METSIM study allows us to proceed toward a "systems genetics" approach, which includes statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein, or metabolite levels, to provide a global view of the molecular architecture of complex traits.

The Metabolic Syndrome in Men study: a resource for studies of metabolic and cardiovascular diseases

The Metabolic Syndrome in Men study: a resource for studies of metabolic and cardiovascular diseases

Finnish Diabetes Risk Score Is Associated with Impaired Insulin Secretion and Insulin Sensitivity, Drug-Treated Hypertension and Cardiovascular Disease: A Follow-Up Study of the METSIM Cohort.

We investigated the association of the Finnish Diabetes Risk Score (FINDRISC) with insulin secretion, insulin sensitivity, and risk of type 2 diabetes, drug-treated hypertension, cardiovascular (CVD) events and total mortality in a follow-up study of the Metabolic Syndrome in Men (METSIM) cohort. The METSIM study includes 10,197 Finnish men, aged 45–73 years, and examined in 2005–2010. Of 8,749 non-diabetic participants of the METSIM study 693 developed incident type 2 diabetes, 225 started antihypertensive medication, 351 had a CVD event, and 392 died during a 8.2-year follow-up. The FINDRISC was significantly associated with decreases in insulin secretion and insulin sensitivity (P<0.0001), and with a 4.14-fold increased risk of incident type 2 diabetes, 2.43-fold increased risk of drug-treated hypertension, 1.61-fold increased risk of CVD, and 1.55-increased risk of total mortality (the FINDRISC ≥12 vs. < 12 points). In conclusion, the FINDRISC predicts impairment in insulin secretion and insulin sensitivity, the conversion to type 2 diabetes, drug-treated hypertension, CVD events and total mortality.

Fatty acid metabolism is altered in non-alcoholic steatohepatitis independent of obesity

BackgroundNon-alcoholic steatohepatitis (NASH) is associated with changes in fatty acid (FA) metabolism. However, specific changes in metabolism and hepatic mRNA expression related to NASH independent of simple steatosis, obesity and diet are unknown. MethodsLiver histology, serum and liver FA composition and estimated enzyme activities based on the FA ratios in cholesteryl esters and triglycerides were assessed in 92 obese participants of the Kuopio Obesity Surgery Study (KOBS) divided to those with normal liver, steatosis or NASH (30 men and 62 women, age 46.8±9.5years (mean±SD), BMI 44.2±6.2kg/m2). Plasma FA composition was also investigated in the Metabolic Syndrome in Men (METSIM) Study (n=769), in which serum alanine aminotransferase (ALT) was used as a marker of liver disease. ResultsObese individuals with NASH had higher activity of estimated activities of delta-6 desaturase (D6D, p<0.002) and stearoyl-CoA desaturase 1 (SCD1, p<0.002) and lower activity of delta-5 desaturase (D5D, p<0.002) when compared to individuals with normal liver. Estimated activities of D5D, D6D and SCD1 correlated positively between liver and serum indicating that serum estimates reflected liver metabolism. Accordingly, NASH was associated with higher hepatic mRNA expression of corresponding genes FADS1, FADS2 and SCD. Finally, differences in FA metabolism that associated with NASH in obese individuals were also associated with high ALT in the METSIM Study. ConclusionsWe demonstrated alterations in FA metabolism and endogenous desaturase activities that associate with NASH, independent of obesity and diet. This suggests that changes in endogenous FA metabolism are related to NASH and that they may contribute to the progression of the disease.

Gene‐diet interaction of a common FADS1 variant with marine polyunsaturated fatty acids for fatty acid composition in plasma and erythrocytes among men

Limited information exists on how the relationship between dietary intake of fat and fatty acids in erythrocytes and plasma is modulated by polymorphisms in the FADS gene cluster. We examined gene-diet interaction of total marine PUFA intake with a known gene encoding Δ-5 desaturase enzyme (FADS1) variant (rs174550) for fatty acids in erythrocyte membranes and plasma phospholipids (PL), cholesteryl esters (CE), and triglycerides (TG). In this cross-sectional study, fatty acid compositions were measured using GC, and total intake of polyunsaturated fat from fish and fish oil was estimated using a food frequency questionnaire in a subsample (n = 962) of the Metabolic Syndrome in Men Study. We found nominally significant gene-diet interactions for eicosapentaenoic acid (EPA, 20:5n-3) in erythrocytes (pinteraction = 0.032) and for EPA in plasma PL (pinteraction = 0.062), CE (pinteraction = 0.035), and TG (pinteraction = 0.035), as well as for docosapentaenoic acid (22:5n-3) in PL (pinteraction = 0.007). After excluding omega-3 supplement users, we found a significant gene-diet interaction for EPA in erythrocytes (pinteraction < 0.003). In a separate cohort of the Kuopio Obesity Surgery Study, the same locus was strongly associated with hepatic mRNA expression of FADS1 (p = 1.5 × 10(-10) ). FADS1 variants may modulate the relationship between marine fatty acid intake and circulating levels of long-chain omega-3 fatty acids.

Both fasting and glucose-stimulated proinsulin levels predict hyperglycemia and incident type 2 diabetes: a population-based study of 9,396 Finnish men.

BackgroundHyperproinsulinemia is an indicator of β-cell dysfunction, and fasting proinsulin levels are elevated in patients with hyperglycemia. It is not known whether proinsulin levels after a glucose load are better predictors of hyperglycemia and type 2 diabetes than fasting proinsulin.MethodsParticipants were 9,396 Finnish men (mean±SD, age 57.3±7.1 years, BMI 27.0±4.0 kg/m2) of the population-based METabolic Syndrome In Men Study who were non-diabetic at the recruitment, and who participated in a 6-year follow-up study. Proinsulin and insulin levels were measured in the fasting state and 30 and 120 min after an oral glucose load. Area under the curve (AUC) and proinsulin to insulin ratios were calculated.ResultsFasting proinsulin, proinsulin at 30 min and proinsulin AUC during the first 30 min of an oral glucose tolerance test significantly predicted both the worsening of hyperglycemia and type 2 diabetes after adjustment for confounding factors. Further adjustment for insulin sensitivity (Matsuda index) or insulin secretion (Disposition index) weakened these associations. Insulin sensitivity had a major impact on these associations.ConclusionOur results suggest that proinsulin in the fasting state and after an oral glucose load similarly predict the worsening of hyperglycemia and conversion to type 2 diabetes.