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Abstract Aims: There 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 results: Conventional 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. Conclusions: Several novel metabolic and inflammatory biomarkers were associated with incident HF, suggesting early activation of respective pathways in the pathogenesis of HF.
Abstract 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.
Abstract Background: Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as a promising experimental tool for translational heart research and drug development. However, their usability as a human adult cardiomyocyte model is limited by their functional immaturity. Our aim is to analyse quantitatively those characteristics and how they differ from adult CMs. Methods and Results: We have developed a novel in silico model with all essential functional electrophysiology and calcium handling features of hiPSC-CMs. Importantly, the virtual cell recapitulates the immature intracellular ion dynamics that are characteristic for hiPSC-CMs, as quantified based our in vitro imaging data. The strong “calcium clock” is a source for a dual function of excitation-contraction coupling in hiPSC-CMs: action potential and calciumtransientmorphology vary substantially depending on the activation sequence of underlying ionic currents and fluxes that is altered in spontaneous vs. paced mode. Furthermore, parallel simulations with hiPSC-CM and adult cardiomyocyte models demonstrate the central differences. Results indicate that hiPSC-CMs translate poorly the disease specific phenotypes of Brugada syndrome, long QT Syndrome and catecholaminergic polymorphic ventricular tachycardia, showing less robustness and greater tendency for arrhythmic events than adult CMs. Based on a comparative sensitivity analysis, hiPSC-CMs share some features with adult CMs, but are still functionally closer to prenatal CMs than adult CMs. A database analysis of 3000 hiPSC-CM model variants suggests that hiPSC-CMs recapitulate poorly fundamental physiological properties of adult CMs. Single modifications do not appear to solve this problem, which is mostly contributed by the immaturity of intracellular calcium handling. Conclusion: Our data indicates that translation of findings from hiPSC-CMs to human disease should be made with great caution. Furthermore, we established a mathematical platform that can be used to improve the translation from hiPSC-CMs to human, and to quantitatively evaluate hiPSC-CMs development toward more general and valuable model for human cardiac diseases.
Abstract Background: The gut microbiome is a complex and metabolically active community that directly influences host phenotypes. In this study, we profile gut microbiota using 16S rRNA gene sequencing in 531 well-phenotyped Finnish men from the Metabolic Syndrome In Men (METSIM) study. Results: We investigate gut microbiota relationships with a variety of factors that have an impact on the development of metabolic and cardiovascular traits. We identify novel associations between gut microbiota and fasting serum levels of a number of metabolites, including fatty acids, amino acids, lipids, and glucose. In particular, we detect associations with fasting plasma trimethylamine N-oxide (TMAO) levels, a gut microbiota-dependent metabolite associated with coronary artery disease and stroke. We further investigate the gut microbiota composition and microbiota–metabolite relationships in subjects with different body mass index and individuals with normal or altered oral glucose tolerance. Finally, we perform microbiota co-occurrence network analysis, which shows that certain metabolites strongly correlate with microbial community structure and that some of these correlations are specific for the pre-diabetic state. Conclusions: Our study identifies novel relationships between the composition of the gut microbiota and circulating metabolites and provides a resource for future studies to understand host–gut microbiota relationships.
Abstract 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.
Abstract Recent genome-wide association studies (GWAS) have identified variants associated with high-density lipoprotein cholesterol (HDL-C) located in or near the ANGPTL8 gene. Given the extensive sharing of GWAS loci across populations, we hypothesized that at least one shared variant at this locus affects HDL-C. The HDL-C–associated variants are coincident with expression quantitative trait loci for ANGPTL8 and DOCK6 in subcutaneous adipose tissue; however, only ANGPTL8 expression levels are associated with HDL-C levels. We identified a 400-bp promoter region of ANGPTL8 and enhancer regions within 5 kb that contribute to regulating expression in liver and adipose. To identify variants functionally responsible for the HDL-C association, we performed fine-mapping analyses and selected 13 candidate variants that overlap putative regulatory regions to test for allelic differences in regulatory function. Of these variants, rs12463177-G increased transcriptional activity (1.5-fold, P = 0.004) and showed differential protein binding. Six additional variants (rs17699089, rs200788077, rs56322906, rs3760782, rs737337, and rs3745683) showed evidence of allelic differences in transcriptional activity and/or protein binding. Taken together, these data suggest a regulatory mechanism at the ANGPTL8 HDL-C GWAS locus involving tissue-selective expression and at least one functional variant.
Abstract Wide-scale profiling technologies including metabolomics broaden the possibility of novel discoveries related to the pathogenesis of type 2 diabetes (T2D). By applying non-targeted metabolomics approach, we investigated here whether serum metabolite profile predicts T2D in a well-characterized study population with impaired glucose tolerance by examining two groups of individuals who took part in the Finnish Diabetes Prevention Study (DPS); those who either early developed T2D (n = 96) or did not convert to T2D within the 15-year follow-up (n = 104). Several novel metabolites were associated with lower likelihood of developing T2D, including indole and lipid related metabolites. Higher indolepropionic acid was associated with reduced likelihood of T2D in the DPS. Interestingly, in those who remained free of T2D, indolepropionic acid and various lipid species were associated with better insulin secretion and sensitivity, respectively. Furthermore, these metabolites were negatively correlated with low-grade inflammation. We replicated the association between indolepropionic acid and T2D risk in one Finnish and one Swedish population. We suggest that indolepropionic acid, a gut microbiota-produced metabolite, is a potential biomarker for the development of T2D that may mediate its protective effect by preservation of β-cell function. Novel lipid metabolites associated with T2D may exert their effects partly through enhancing insulin sensitivity.
Abstract Lipid and lipoprotein subclasses are associated with metabolic and cardiovascular diseases, yet the genetic contributions to variability in subclass traits are not fully understood. We conducted single-variant and gene-based association tests between 15.1M variants from genome-wide and exome array and imputed genotypes and 72 lipid and lipoprotein traits in 8,372 Finns. After accounting for 885 variants at 157 previously identified lipid loci, we identified five novel signals near established loci at HIF3A, ADAMTS3, PLTP, LCAT, and LIPG. Four of the signals were identified with a low-frequency (0.005<minor allele frequency [MAF]<0.05) or rare (MAF<0.005) variant, including Arg123His in LCAT. Gene-based associations (P<10−10) support a role for coding variants in LIPC and LIPG with lipoprotein subclass traits. 30 established lipid-associated loci had a stronger association for a subclass trait than any conventional trait. These novel association signals provide further insight into the molecular basis of dyslipidemia and the etiology of metabolic disorders
Abstract 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.
Abstract Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
Abstract Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
Abstract Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.
Abstract Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.
Abstract To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure–associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure–related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.
Abstract 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.
Abstract In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (FROH) for >1.4 million individuals, we show that FROH is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: FROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44–66%] in the odds of having children. Finally, the effects of FROH are confirmed within full-sibling pairs, where the variation in FROH is independent of all environmental confounding.
Abstract Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4‐23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.