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Abstract Aims: To evaluate risk factors for major adverse cardiac event (MACE) after the first acute coronary syndrome (ACS) and to examine the prevalence of risk factors in post-ACS patients. Methods: We used Finnish population-based myocardial infarction register, FINAMI, data from years 1993–2011 to identify survivors of first ACS (n = 12686), who were then followed up for recurrent events and all-cause mortality for three years. Finnish FINRISK risk factor surveys were used to determine the prevalence of risk factors (smoking, hyperlipidaemia, diabetes and blood pressure) in post-ACS patients (n = 199). Results: Of the first ACS survivors, 48.4% had MACE within three years of their primary event, 17.0% were fatal. Diabetes (p = 4.4 × 10−7), heart failure (HF) during the first ACS attack hospitalization (p = 6.8 × 10−15), higher Charlson index (p = 1.56 × 10−19) and older age (p = .026) were associated with elevated risk for MACE in the three-year follow-up, and revascularization (p = .0036) was associated with reduced risk. Risk factor analyses showed that 23% of ACS survivors continued smoking and cholesterol levels were still high (>5mmol/l) in 24% although 86% of the patients were taking lipid lowering medication. Conclusion: Diabetes, higher Charlson index and HF are the most important risk factors of MACE after the first ACS. Cardiovascular risk factor levels were still high among survivors of first ACS.
Abstract Background: GlycA is a nuclear magnetic resonance (NMR) spectroscopy biomarker that predicts risk of disease from myriad causes. It is heterogeneous; arising from five circulating glycoproteins with dynamic concentrations: alpha-1 antitrypsin (AAT), alpha-1-acid glycoprotein (AGP), haptoglobin (HP), transferrin (TF), and alpha-1-antichymotrypsin (AACT). The contributions of each glycoprotein to the disease and mortality risks predicted by GlycA remain unknown. Methods: We trained imputation models for AAT, AGP, HP, and TF from NMR metabolite measurements in 626 adults from a population cohort with matched NMR and immunoassay data. Levels of AAT, AGP, and HP were estimated in 11,861 adults from two population cohorts with eight years of follow-up, then each biomarker was tested for association with all common endpoints. Whole blood gene expression data was used to identify cellular processes associated with elevated AAT. Results: Accurate imputation models were obtained for AAT, AGP, and HP but not for TF. While AGP had the strongest correlation with GlycA, our analysis revealed variation in imputed AAT levels was the most predictive of morbidity and mortality for the widest range of diseases over the eight year follow-up period, including heart failure (meta-analysis hazard ratio = 1.60 per standard deviation increase of AAT, P-value = 1×10−10), influenza and pneumonia (HR = 1.37, P = 6×10−10), and liver diseases (HR = 1.81, P = 1×10−6). Transcriptional analyses revealed association of elevated AAT with diverse inflammatory immune pathways. Conclusions: This study clarifies the molecular underpinnings of the GlycA biomarker’s associated disease risk, and indicates a previously unrecognised association between elevated AAT and severe disease onset and mortality.
Abstract Aims/hypothesis: A validated mass-spectrometric method was applied to measure Cer(d18:1/16:0), Cer(d18:1/18:0), Cer(d18:1/24:0) and Cer(d18:1/24:1) from serum or plasma samples. These ceramides were analysed in a population-based risk factor study (FINRISK 2002, n = 8045), in a cohort of participants undergoing elective coronary angiography for suspected stable angina pectoris (Western Norway Coronary Angiography Cohort [WECAC], n = 3344) and in an intervention trial investigating improved methods of lifestyle modification for individuals at high risk of the metabolic syndrome (Prevent Metabolic Syndrome [PrevMetSyn], n = 371). Diabetes risk score models were developed to estimate the 10 year risk of incident diabetes. Methods: A validated mass-spectrometric method was applied to measure Cer(d18:1/16:0), Cer(d18:1/18:0), Cer(d18:1/24:0) and Cer(d18:1/24:1) from serum or plasma samples. These ceramides were analysed in a population-based risk factor study (FINRISK 2002, n = 8045), in a cohort of participants undergoing elective coronary angiography for suspected stable angina pectoris (Western Norway Coronary Angiography Cohort [WECAC], n = 3344) and in an intervention trial investigating improved methods of lifestyle modification for individuals at high risk of the metabolic syndrome (Prevent Metabolic Syndrome [PrevMetSyn], n = 371). Diabetes risk score models were developed to estimate the 10 year risk of incident diabetes. Results: Analysis in FINRISK 2002 showed that the Cer(d18:1/18:0)/Cer(d18:1/16:0) ceramide ratio was predictive of incident diabetes (HR per SD 2.23, 95% CI 2.05, 2.42), and remained significant after adjustment for several risk factors, including BMI, fasting glucose and HbA1c (HR 1.34, 95% CI 1.14, 1.57). The finding was validated in the WECAC study (unadjusted HR 1.81, 95% CI 1.53, 2.14; adjusted HR 1.39, 95% CI 1.16, 1.66). In the intervention trial, the ceramide ratio and diabetes risk scores significantly decreased in individuals who had 5% or more weight loss. Conclusions/interpretation: The Cer(d18:1/18:0)/Cer(d18:1/16:0) ratio is an independent predictive biomarker for incident diabetes, and may be modulated by lifestyle intervention.
Abstract Objective: Previous studies on the association between metabolic biomarkers and hypertension have been limited by small sample sizes, low number of studied biomarkers, and cross-sectional study design. In the largest study to date, we assess the cross-sectional and longitudinal associations between high-abundance serum biomarkers and blood pressure (BP). Methods: We studied cross-sectional (N = 36 985; age 50.5 ± 14.2; 53.1% women) and longitudinal (N = 4197; age 49.4 ± 11.8, 55.3% women) population samples of Finnish individuals. We included 53 serum biomarkers and other detailed lipoprotein subclass measures in our analyses. We studied the associations between serum biomarkers and BP using both conventional statistical methods and a machine learning algorithm (gradient boosting) while adjusting for clinical risk factors. Results: Fifty-one of 53 serum biomarkers were cross-sectionally related to BP (adjusted P < 0.05 for all). Conventional linear regression modeling demonstrated that LDL cholesterol, remnant cholesterol, apolipoprotein B, and acetate were positively, and HDL particle size was negatively, associated with SBP change over time (adjusted P < 0.05 for all). Adding serum biomarkers (cross-sectional root-mean-square error: 16.27 mmHg; longitudinal: 17.61 mmHg) in the model with clinical measures (cross-sectional: 16.70 mmHg; longitudinal 18.52 mmHg) improved the machine learning model fit. Glucose, albumin, triglycerides in LDL, glycerol, VLDL particle size, and acetoacetate had the highest importance scores in models related to current or future BP. Conclusions: Our results suggest that serum lipids, and particularly LDL-derived and VLDL-derived cholesterol measures, and glucose metabolism abnormalities are associated with hypertension onset. Use of serum metabolite determination could improve identification of individuals at high risk of developing hypertension.
Abstract Background: Cardiomyocytes secrete atrial natriuretic peptide (ANP) and B-type natriuretic peptide (BNP) in response to mechanical stretching, making them useful clinical biomarkers of cardiac stress. Both human and animal studies indicate a role for ANP as a regulator of blood pressure with conflicting results for BNP. Methods and Results: We used genome-wide association analysis (n=6296) to study the effects of genetic variants on circulating natriuretic peptide concentrations and compared the impact of natriuretic peptide–associated genetic variants on blood pressure (n=27 059). Eight independent genetic variants in 2 known (NPPA-NPPB and POC1B-GALNT4) and 1 novel locus (PPP3CC) associated with midregional proANP (MR-proANP), BNP, aminoterminal proBNP (NT-proBNP), or BNP:NT-proBNP ratio. The NPPA-NPPB locus containing the adjacent genes encoding ANP and BNP harbored 4 independent cis variants with effects specific to either midregional proANP or BNP and a rare missense single nucleotide polymorphism in NT-proBNP seriously altering its measurement. Variants near the calcineurin catalytic subunit gamma gene PPP3CC and the polypeptide N-acetylgalactosaminyltransferase 4 gene GALNT4 associated with BNP:NT-proBNP ratio but not with BNP or midregional proANP, suggesting effects on the post-translational regulation of proBNP. Out of the 8 individual variants, only those correlated with midregional proANP had a statistically significant albeit weak impact on blood pressure. The combined effect of these 3 single nucleotide polymorphisms also associated with hypertension risk (P=8.2×10−4). Conclusions: Common genetic differences affecting the circulating concentration of ANP associated with blood pressure, whereas those affecting BNP did not, highlighting the blood pressure–lowering effect of ANP in the general population.
Abstract Purpose: To investigate whether exposure to systemic antibiotics influences the risk of developing type 2 diabetes and overweight/obesity. Methods: The study sample comprised 2209 (110 with incident diabetes) participants from the population-based Cardiovascular Risk in Young Finns Study (YFS) aged 24–39 years in 2001. The exposure was national linked register data on purchased antibiotic courses between 1993 and 2001. Clinical examinations including BMI were conducted in 2001, 2007 and 2011. Participants with prevalent diabetes in 2001 were excluded. Data on type 2 diabetes was also obtained from two national registers until 2017. Data from four population-based National FINRISK studies were used for replication (N = 24,674, 1866 with incident diabetes). Results: Prior antibiotic exposure (> 5 versus 0–1 antibiotic courses) was associated with subsequent type 2 diabetes in both YFS (OR 2.29; 95%CI 1.33–3.96) and FINRISK (HR 1.73; 95%CI 1.51–1.99). An increased risk for type 2 diabetes was observed in YFS (OR 1.043; 95%CI 1.013–1.074) and FINRISK (HR 1.022; 95%CI 1.016–1.029) per course. Exposure to antibiotics increased the risk of overweight/obesity (BMI > 25 kg/m2) after a 10-year follow-up in YFS (OR 1.043; 95%CI 1.019–1.068) and in FINRISK (OR 1.023; 95%CI 1.018–1.029) at baseline per antibiotic course. Adjustments for confounders from early life in YFS and at baseline in FINRISK, including BMI, socioeconomic status, smoking, insulin, blood pressure, and physical activity, did not appreciably alter the findings. Conclusion: Our results show that exposure to antibiotics was associated with increased risk for future type 2 diabetes and overweight/obesity and support judicious antibiotic prescribing.
Abstract Aims: We investigated the association between quantified metabolite, lipid and lipoprotein measures and incident heart failure hospitalisation (HFH) in the elderly, and examined whether circulating metabolic measures improve HFH prediction. Methods and results: Overall, 80 metabolic measures from the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial were measured by proton nuclear magnetic resonance spectroscopy (n = 5341; 182 HFH events during 2.7‐year follow‐up). We repeated the work in FINRISK 1997 (n = 7330; 133 HFH events during 5‐year follow‐up). In PROSPER, the circulating concentrations of 13 metabolic measures were found to be significantly different in those who were later hospitalised for heart failure after correction for multiple comparisons. These included creatinine, phenylalanine, glycoprotein acetyls, 3‐hydroxybutyrate, and various high‐density lipoprotein measures. In Cox models, two metabolites were associated with risk of HFH after adjustment for clinical risk factors and N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP): phenylalanine [hazard ratio (HR) 1.29, 95% confidence interval (CI) 1.10–1.53; P = 0.002] and acetate (HR 0.81, 95% CI 0.68–0.98; P = 0.026). Both were retained in the final model after backward elimination. Compared to a model with established risk factors and NT‐proBNP, this model did not improve the C‐index but did improve the overall continuous net reclassification index (NRI 0.21; 95% CI 0.06–0.35; P = 0.007) due to improvement in classification of non‐cases (NRI 0.14; 95% CI 0.12–0.17; P < 0.001). Phenylalanine was replicated as a predictor of HFH in FINRISK 1997 (HR 1.23, 95% CI 1.03–1.48; P = 0.023). Conclusion: Our findings identify phenylalanine as a novel predictor of incident HFH, although prediction gains are low. Further mechanistic studies appear warranted.
Abstract Background and aims: Apolipoprotein A-I (apoA-I) infusions represent a potential novel therapeutic approach for the prevention of coronary artery disease (CAD). Although circulating apoA-I concentrations inversely associate with risk of CAD, the evidence base of this representing a causal relationship is lacking. The aim was to assess the causal role of apoA-I using human genetics. Methods: We identified a variant (rs12225230) in APOA1 locus that associated with circulating apoA-I concentrations (p < 5 × 10−8) in 20,370 Finnish participants, and meta-analyzed our data with a previous GWAS of apoA-I. We obtained genetic estimates of CAD from UK Biobank and CARDIoGRAMplusC4D (totaling 122,733 CAD cases) and conducted a two-sample Mendelian randomization analysis. We compared our genetic findings to observational associations of apoA-I with risk of CAD in 918 incident CAD cases among 11,535 individuals from population-based prospective cohorts. Results: ApoA-I was associated with a lower risk of CAD in observational analyses (HR 0.81; 95%CI: 0.75, 0.88; per 1-SD higher apoA-I), with the association showing a dose-response relationship. Rs12225230 associated with apoA-I concentrations (per-C allele beta 0.076 SD; SE: 0.013; p = 1.5 × 10−9) but not with confounders. In Mendelian randomization analyses, apoA-I was not related to risk of CAD (OR 1.13; 95%CI: 0.98,1.30 per 1-SD higher apoA-I), which was different from the observational association. Similar findings were observed using an independent ABCA1 variant in sensitivity analysis. Conclusions: Genetic evidence fails to support a cardioprotective role for apoA-I. This is in line with the cumulative evidence showing that HDL-related phenotypes are unlikely to have a protective role in CAD.
Abstract Background: Immunometabolism plays a central role in many cardiometabolic diseases. However, a robust map of immune-related gene networks in circulating human cells, their interactions with metabolites, and their genetic control is still lacking. Here, we integrate blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts (total N = 2168), including a subset of individuals with matched multi-omic data at 7-year follow-up. Results: We identify topologically replicable gene networks enriched for diverse immune functions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophil activity. These immune gene modules show complex patterns of association with 158 circulating metabolites, including lipoprotein subclasses, lipids, fatty acids, amino acids, small molecules, and CRP. Genome-wide scans for module expression quantitative trait loci (mQTLs) reveal five modules with mQTLs that have both cis and trans effects. The strongest mQTL is in ARHGEF3 (rs1354034) and affects a module enriched for platelet function, independent of platelet counts. Modules of mast cell/basophil and neutrophil function show temporally stable metabolite associations over 7-year follow-up, providing evidence that these modules and their constituent gene products may play central roles in metabolic inflammation. Furthermore, the strongest mQTL in ARHGEF3 also displays clear temporal stability, supporting widespread trans effects at this locus. Conclusions: This study provides a detailed map of natural variation at the blood immunometabolic interface and its genetic basis, and may facilitate subsequent studies to explain inter-individual variation in cardiometabolic disease.
Abstract Aims/hypothesis: Metabolomics technologies have identified numerous blood biomarkers for type 2 diabetes risk in case−control studies of middle-aged and older individuals. We aimed to validate existing and identify novel metabolic biomarkers predictive of future diabetes in large cohorts of young adults. Methods: NMR metabolomics was used to quantify 229 circulating metabolic measures in 11,896 individuals from four Finnish observational cohorts (baseline age 24–45 years). Associations between baseline metabolites and risk of developing diabetes during 8–15 years of follow-up (392 incident cases) were adjusted for sex, age, BMI and fasting glucose. Prospective metabolite associations were also tested with fasting glucose, 2 h glucose and HOMA-IR at follow-up. Results: Out of 229 metabolic measures, 113 were associated with incident type 2 diabetes in meta-analysis of the four cohorts (ORs per 1 SD: 0.59–1.50; p< 0.0009). Among the strongest biomarkers of diabetes risk were branched-chain and aromatic amino acids (OR 1.31–1.33) and triacylglycerol within VLDL particles (OR 1.33–1.50), as well as linoleic n-6 fatty acid (OR 0.75) and non-esterified cholesterol in large HDL particles (OR 0.59). The metabolic biomarkers were more strongly associated with deterioration in post-load glucose and insulin resistance than with future fasting hyperglycaemia. A multi-metabolite score comprised of phenylalanine, non-esterified cholesterol in large HDL and the ratio of cholesteryl ester to total lipid in large VLDL was associated with future diabetes risk (OR 10.1 comparing individuals in upper vs lower fifth of the multi-metabolite score) in one of the cohorts (mean age 31 years). Conclusions/interpretation: Metabolic biomarkers across multiple molecular pathways are already predictive of the long-term risk of diabetes in young adults. Comprehensive metabolic profiling may help to target preventive interventions for young asymptomatic individuals at increased risk.
Abstract Objective: This study aimed to investigate the role of cytokines as intermediates in the pathway from increased adiposity to disease. Methods: BMI and circulating levels of up to 41 cytokines were measured in individuals from three Finnish cohort studies (n = 8,293). Mendelian randomization (MR) was used to assess the impact of BMI on circulating cytokines and the impact of BMI‐driven cytokines on risk of obesity‐related diseases. Results: Observationally, BMI was associated with 19 cytokines. For every SD increase in BMI, causal effect estimates were strongest for hepatocyte growth factor, monocyte chemotactic protein‐1 (MCP‐1), and tumor necrosis factor–related apoptosis‐inducing ligand (TRAIL) and were as ratios of geometric means 1.13 (95% CI: 1.08‐1.19), 1.08 (95% CI: 1.04‐1.14), and 1.13 (95% CI: 1.04‐1.21), respectively. TRAIL was associated with a small increase in the odds of coronary artery disease (odds ratio: 1.03; 95% CI: 1.00‐1.06). There was inconsistent evidence for a protective role of MCP‐1 against inflammatory bowel diseases. Conclusions: Observational and MR estimates of the effect of BMI on cytokine levels were generally concordant. There was little evidence for an effect of raised levels of BMI‐driven cytokines on disease. These findings illustrate the challenges of MR when applied in the context of molecular mediation.
Background Sudden cardiac death (SCD) accounts for up to half of cardiac mortality. The risk of SCD is heritable but the underlying genetic variants are largely unknown. We investigated whether common genetic variants predisposing to arrhythmia or related electrocardiographic phenotypes, including QT-interval prolongation, are associated with increased risk of SCD. Methodology/Principal Findings We studied the association between 28 candidate SNPs and SCD in a meta-analysis of four population cohorts (FINRISK 1992, 1997, 2002 and Health 2000, n = 27,629) and two forensic autopsy series (The Helsinki Sudden Death Study and The Tampere Autopsy Study, n = 694). We also studied the association between established cardiovascular risk factors and SCD. Causes of death were reviewed using registry-based health and autopsy data. Cox regression and logistic regression models were adjusted for age, sex, and geographic region. The total number of SCDs was 716. Two novel SNPs were associated with SCD: SCN5A rs41312391 (relative risk [RR] 1.27 per minor T allele, 95% CI 1.11–1.45, P = 3.4×10−4) and rs2200733 in 4q25 (RR 1.28 per minor T allele, 95% CI 1.11–1.48, P = 7.9×10−4). We also replicated the associations for 9p21 (rs2383207, RR 1.13 per G allele, 95% CI 1.01–1.26, P = 0.036), as well as for male sex, systolic blood pressure, diabetes, cigarette smoking, low physical activity, coronary heart disease, and digoxin use (P<0.05). Conclusions/Significance Two novel genetic variants, one in the cardiac sodium channel gene SCN5A and another at 4q25 previously associated with atrial fibrillation, are associated with SCD.
Abstract The contribution of de novo variants in severe intellectual disability (ID) has been extensively studied whereas the genetics of mild ID has been less characterized. To elucidate the genetics of milder ID we studied 442 ID patients enriched for mild ID (>50%) from a population isolate of Finland. Using exome sequencing, we show that rare damaging variants in known ID genes are observed significantly more often in severe (27%) than in mild ID (13%) patients. We further observe a significant enrichment of functional variants in genes not yet associated with ID (OR: 2.1). We show that a common variant polygenic risk significantly contributes to ID. The heritability explained by polygenic risk score is the highest for educational attainment (EDU) in mild ID (2.2%) but lower for more severe ID (0.6%). Finally, we identify a Finland enriched homozygote variant in the CRADD ID associated gene.
Abstract Objective: To conduct a comprehensive analysis of circulating metabolites and incident stroke in large prospective population-based settings. Methods: We investigated the association of metabolites with risk of stroke in 7 prospective cohort studies including 1,791 incident stroke events among 38,797 participants in whom circulating metabolites were measured by nuclear magnetic resonance technology. The relationship between metabolites and stroke was assessed with Cox proportional hazards regression models. The analyses were performed considering all incident stroke events and ischemic and hemorrhagic events separately. Results: The analyses revealed 10 significant metabolite associations. Amino acid histidine (hazard ratio [HR] per SD 0.90, 95% confidence interval [CI] 0.85, 0.94; p = 4.45 × 10−5), glycolysis-related metabolite pyruvate (HR per SD 1.09, 95% CI 1.04, 1.14; p = 7.45 × 10−4), acute-phase reaction marker glycoprotein acetyls (HR per SD 1.09, 95% CI 1.03, 1.15; p = 1.27 × 10−3), cholesterol in high-density lipoprotein (HDL) 2, and several other lipoprotein particles were associated with risk of stroke. When focused on incident ischemic stroke, a significant association was observed with phenylalanine (HR per SD 1.12, 95% CI 1.05, 1.19; p = 4.13 × 10−4) and total and free cholesterol in large HDL particles. Conclusions: We found association of amino acids, glycolysis-related metabolites, acute-phase reaction markers, and several lipoprotein subfractions with the risk of stroke. These findings support the potential of metabolomics to provide new insights into the metabolic changes preceding stroke.
Purpose: To investigate whether exposure to systemic antibiotics influences the risk of developing type 2 diabetes and overweight/obesity. Methods: The study sample comprised 2209 (110 with incident diabetes) participants from the population-based Cardiovascular Risk in Young Finns Study (YFS) aged 24–39 years in 2001. The exposure was national linked register data on purchased antibiotic courses between 1993 and 2001. Clinical examinations including BMI were conducted in 2001, 2007 and 2011. Participants with prevalent diabetes in 2001 were excluded. Data on type 2 diabetes was also obtained from two national registers until 2017. Data from four population-based National FINRISK studies were used for replication (N = 24,674, 1866 with incident diabetes). Results: Prior antibiotic exposure (> 5 versus 0–1 antibiotic courses) was associated with subsequent type 2 diabetes in both YFS (OR 2.29; 95%CI 1.33–3.96) and FINRISK (HR 1.73; 95%CI 1.51–1.99). An increased risk for type 2 diabetes was observed in YFS (OR 1.043; 95%CI 1.013–1.074) and FINRISK (HR 1.022; 95%CI 1.016–1.029) per course. Exposure to antibiotics increased the risk of overweight/obesity (BMI > 25 kg/m2) after a 10-year follow-up in YFS (OR 1.043; 95%CI 1.019–1.068) and in FINRISK (OR 1.023; 95%CI 1.018–1.029) at baseline per antibiotic course. Adjustments for confounders from early life in YFS and at baseline in FINRISK, including BMI, socioeconomic status, smoking, insulin, blood pressure, and physical activity, did not appreciably alter the findings. Conclusion: Our results show that exposure to antibiotics was associated with increased risk for future type 2 diabetes and overweight/obesity and support judicious antibiotic prescribing.
Abstract Background: Chronic obstructive pulmonary disease (COPD) is a common lung disorder characterized by persistent and progressive airflow limitation as well as systemic changes. Metabolic changes in blood may help detect COPD in an earlier stage and predict prognosis. Methods: We conducted a comprehensive study of circulating metabolites, measured by proton Nuclear Magnetic Resonance Spectroscopy, in relation with COPD and lung function. The discovery sample consisted of 5557 individuals from two large population-based studies in the Netherlands, the Rotterdam Study and the Erasmus Rucphen Family study. Significant findings were replicated in 12,205 individuals from the Lifelines-DEEP study, FINRISK and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) studies. For replicated metabolites further investigation of causality was performed, utilizing genetics in the Mendelian randomization approach. Results: There were 602 cases of COPD and 4955 controls used in the discovery meta-analysis. Our logistic regression results showed that higher levels of plasma Glycoprotein acetyls (GlycA) are significantly associated with COPD (OR = 1.16, P = 5.6 × 10−4 in the discovery and OR = 1.30, P = 1.8 × 10−6 in the replication sample). A bi-directional two-sample Mendelian randomization analysis suggested that circulating blood GlycA is not causally related to COPD, but that COPD causally increases GlycA levels. Using the prospective data of the same sample of Rotterdam Study in Cox-regression, we show that the circulating GlycA level is a predictive biomarker of COPD incidence (HR = 1.99, 95%CI 1.52–2.60, comparing those in the highest and lowest quartile of GlycA) but is not significantly associated with mortality in COPD patients (HR = 1.07, 95%CI 0.94–1.20). Conclusions: Our study shows that circulating blood GlycA is a biomarker of early COPD pathology.
Background Atrial fibrillation (AF) is an important heart rhythm disorder in aging populations. The gut microbiome composition has been previously related to cardiovascular disease risk factors. Whether the gut microbial profile is also associated with the risk of AF remains unknown. Methods We examined the associations of prevalent and incident AF with gut microbiota in the FINRISK 2002 study, a random population sample of 6763 individuals. We replicated our findings in an independent case–control cohort of 138 individuals in Hamburg, Germany. Findings Multivariable-adjusted regression models revealed that prevalent AF (N = 116) was associated with nine microbial genera. Incident AF (N = 539) over a median follow-up of 15 years was associated with eight microbial genera with false discovery rate (FDR)-corrected P < 0.05. Both prevalent and incident AF were associated with the genera Enorma and Bifidobacterium (FDR-corrected P < 0.001). AF was not significantly associated with bacterial diversity measures. Seventy-five percent of top genera (Enorma, Paraprevotella, Odoribacter, Collinsella, Barnesiella, Alistipes) in Cox regression analyses showed a consistent direction of shifted abundance in an independent AF case–control cohort that was used for replication. Interpretation Our findings establish the basis for the use of microbiome profiles in AF risk prediction. However, extensive research is still warranted before microbiome sequencing can be used for prevention and targeted treatment of AF. Funding This study was funded by European Research Council, German Ministry of Research and Education, Academy of Finland, Finnish Medical Foundation, and the Finnish Foundation for Cardiovascular Research, the Emil Aaltonen Foundation, and the Paavo Nurmi Foundation.
Abstract Copy number variants (CNVs) are associated with syndromic and severe neurological and psychiatric disorders (SNPDs), such as intellectual disability, epilepsy, schizophrenia, and bipolar disorder. Although considered high-impact, CNVs are also observed in the general population. This presents a diagnostic challenge in evaluating their clinical significance. To estimate the phenotypic differences between CNV carriers and non-carriers regarding general health and well-being, we compared the impact of SNPD-associated CNVs on health, cognition, and socioeconomic phenotypes to the impact of three genome-wide polygenic risk score (PRS) in two Finnish cohorts (FINRISK, n = 23,053 and NFBC1966, n = 4895). The focus was on CNV carriers and PRS extremes who do not have an SNPD diagnosis. We identified high-risk CNVs (DECIPHER CNVs, risk gene deletions, or large [>1 Mb] CNVs) in 744 study participants (2.66%), 36 (4.8%) of whom had a diagnosed SNPD. In the remaining 708 unaffected carriers, we observed lower educational attainment (EA; OR = 0.77 [95% CI 0.66–0.89]) and lower household income (OR = 0.77 [0.66–0.89]). Income-associated CNVs also lowered household income (OR = 0.50 [0.38–0.66]), and CNVs with medical consequences lowered subjective health (OR = 0.48 [0.32–0.72]). The impact of PRSs was broader. At the lowest extreme of PRS for EA, we observed lower EA (OR = 0.31 [0.26–0.37]), lower-income (OR = 0.66 [0.57–0.77]), lower subjective health (OR = 0.72 [0.61–0.83]), and increased mortality (Cox’s HR = 1.55 [1.21–1.98]). PRS for intelligence had a similar impact, whereas PRS for schizophrenia did not affect these traits. We conclude that the majority of working-age individuals carrying high-risk CNVs without SNPD diagnosis have a modest impact on morbidity and mortality, as well as the limited impact on income and educational attainment, compared to individuals at the extreme end of common genetic variation. Our findings highlight that the contribution of traditional high-risk variants such as CNVs should be analyzed in a broader genetic context, rather than evaluated in isolation.
Abstract Background: Cardiac hypertrophy increases the risk of developing heart failure and cardiovascular death. The neutrophil inflammatory protein, lipocalin‐2 (LCN2/NGAL), is elevated in certain forms of cardiac hypertrophy and acute heart failure. However, a specific role for LCN2 in predisposition and etiology of hypertrophy and the relevant genetic determinants are unclear. Here, we defined the role of LCN2 in concentric cardiac hypertrophy in terms of pathophysiology, inflammatory expression networks, and genomic determinants. Methods and Results: We used 3 experimental models: a polygenic model of cardiac hypertrophy and heart failure, a model of intrauterine growth restriction and Lcn2‐knockout mouse; cultured cardiomyocytes; and 2 human cohorts: 114 type 2 diabetes mellitus patients and 2064 healthy subjects of the YFS (Young Finns Study). In hypertrophic heart rats, cardiac and circulating Lcn2 was significantly overexpressed before, during, and after development of cardiac hypertrophy and heart failure. Lcn2 expression was increased in hypertrophic hearts in a model of intrauterine growth restriction, whereas Lcn2‐knockout mice had smaller hearts. In cultured cardiomyocytes, Lcn2 activated molecular hypertrophic pathways and increased cell size, but reduced proliferation and cell numbers. Increased LCN2 was associated with cardiac hypertrophy and diastolic dysfunction in diabetes mellitus. In the YFS,LCN2 expression was associated with body mass index and cardiac mass and with levels of inflammatory markers. The single‐nucleotide polymorphism, rs13297295, located near LCN2 defined a significant cis‐eQTL for LCN2 expression. Conclusions: Direct effects of LCN2 on cardiomyocyte size and number and the consistent associations in experimental and human analyses reveal a central role for LCN2 in the ontogeny of cardiac hypertrophy and heart failure.
Protein-altering variants that are protective against human disease provide in vivo validation of therapeutic targets. Here we use genotyping data from UK Biobank (n = 337,151 unrelated White British individuals) and FinnGen (n = 176,899) to conduct a search for protein-altering variants conferring lower intraocular pressure (IOP) and protection against glaucoma. Through rare protein-altering variant association analysis, we find a missense variant in ANGPTL7 in UK Biobank (rs28991009, p.Gln175His, MAF = 0.8%, genotyped in 82,253 individuals with measured IOP and an independent set of 4,238 glaucoma patients and 250,660 controls) that significantly lowers IOP (β = -0.53 and -0.67 mmHg for heterozygotes, -3.40 and -2.37 mmHg for homozygotes, P = 5.96 x 10-9 and 1.07 x 10-13 for corneal compensated and Goldman-correlated IOP, respectively) and is associated with 34% reduced risk of glaucoma (P = 0.0062). In FinnGen, we identify an ANGPTL7 missense variant at a greater than 50-fold increased frequency in Finland compared with other populations (rs147660927, p.Arg220Cys, MAF Finland = 4.3%), which was genotyped in 6,537 glaucoma patients and 170,362 controls and is associated with a 29% lower glaucoma risk (P = 1.9 x 10-12 for all glaucoma types and also protection against its subtypes including exfoliation, primary open-angle, and primary angle-closure). We further find three rarer variants in UK Biobank, including a protein-truncating variant, which confer a strong composite lowering of IOP (P = 0.0012 and 0.24 for Goldman-correlated and corneal compensated IOP, respectively), suggesting the protective mechanism likely resides in the loss of interaction or function. Our results support inhibition or down-regulation of ANGPTL7 as a therapeutic strategy for glaucoma.
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 Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to similar to 1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (minor allele frequency ≤ 0.01) variant BP associations (P < 5 x 10(−8)), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were similar to 8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.
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 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 Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 ×10−8), 10 of which associate with CVD risk including five new loci-COL5A1, GLTPD2, SPTLC3, MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD.
Abstract Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10−72), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10−4), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10−5). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.
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.
A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.
BACKGROUND: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.