Prognostic Value of Cardiovascular Biomarkers in the Population.

Importance: Identification of individuals at high risk for atherosclerotic cardiovascular disease within the population is important to inform primary prevention strategies. Objective: To evaluate the prognostic value of routinely available cardiovascular biomarkers when added to established risk factors. Design, Setting, and Participants: Individual-level analysis including data on cardiovascular biomarkers from 28 general population-based cohorts from 12 countries and 4 continents with assessments by participant age. The median follow-up was 11.8 years. Exposure: Measurement of high-sensitivity cardiac troponin I, high-sensitivity cardiac troponin T, N-terminal pro-B-type natriuretic peptide, B-type natriuretic peptide, or high-sensitivity C-reactive protein. Main Outcomes and Measures: The primary outcome was incident atherosclerotic cardiovascular disease, which included all fatal and nonfatal events. The secondary outcomes were all-cause mortality, heart failure, ischemic stroke, and myocardial infarction. Subdistribution hazard ratios (HRs) for the association of biomarkers and outcomes were calculated after adjustment for established risk factors. The additional predictive value of the biomarkers was assessed using the C statistic and reclassification analyses. Results: The analyses included 164 054 individuals (median age, 53.1 years [IQR, 42.7-62.9 years] and 52.4% were women). There were 17 211 incident atherosclerotic cardiovascular disease events. All biomarkers were significantly associated with incident atherosclerotic cardiovascular disease (subdistribution HR per 1-SD change, 1.13 [95% CI, 1.11-1.16] for high-sensitivity cardiac troponin I; 1.18 [95% CI, 1.12-1.23] for high-sensitivity cardiac troponin T; 1.21 [95% CI, 1.18-1.24] for N-terminal pro-B-type natriuretic peptide; 1.14 [95% CI, 1.08-1.22] for B-type natriuretic peptide; and 1.14 [95% CI, 1.12-1.16] for high-sensitivity C-reactive protein) and all secondary outcomes. The addition of each single biomarker to a model that included established risk factors improved the C statistic. For 10-year incident atherosclerotic cardiovascular disease in younger people (aged <65 years), the combination of high-sensitivity cardiac troponin I, N-terminal pro-B-type natriuretic peptide, and high-sensitivity C-reactive protein resulted in a C statistic improvement from 0.812 (95% CI, 0.8021-0.8208) to 0.8194 (95% CI, 0.8089-0.8277). The combination of these biomarkers also improved reclassification compared with the conventional model. Improvements in risk prediction were most pronounced for the secondary outcomes of heart failure and all-cause mortality. The incremental value of biomarkers was greater in people aged 65 years or older vs younger people. Conclusions and Relevance: Cardiovascular biomarkers were strongly associated with fatal and nonfatal cardiovascular events and mortality. The addition of biomarkers to established risk factors led to only a small improvement in risk prediction metrics for atherosclerotic cardiovascular disease, but was more favorable for heart failure and mortality.

Genome-wide characterization of circulating metabolic biomarkers.

Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism1-7. This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases8-11. Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associations. We use detailed metabolic profiling of lipoprotein- and lipid-associated variants to better characterize how known lipid loci and novel loci affect lipoprotein metabolism at a granular level. We demonstrate the translational utility of comprehensively phenotyped molecular data, characterizing the metabolic associations of intrahepatic cholestasis of pregnancy. Finally, we observe substantial genetic pleiotropy for multiple metabolic pathways and illustrate the importance of careful instrument selection in Mendelian randomization analysis, revealing a putative causal relationship between acetone and hypertension. Our publicly available results provide a foundational resource for the community to examine the role of metabolism across diverse diseases.

Integration of polygenic and gut metagenomic risk prediction for common diseases.

Multiomics has shown promise in noninvasive risk profiling and early detection of various common diseases. In the present study, in a prospective population-based cohort with ~18 years of e-health record follow-up, we investigated the incremental and combined value of genomic and gut metagenomic risk assessment compared with conventional risk factors for predicting incident coronary artery disease (CAD), type 2 diabetes (T2D), Alzheimer disease and prostate cancer. We found that polygenic risk scores (PRSs) improved prediction over conventional risk factors for all diseases. Gut microbiome scores improved predictive capacity over baseline age for CAD, T2D and prostate cancer. Integrated risk models of PRSs, gut microbiome scores and conventional risk factors achieved the highest predictive performance for all diseases studied compared with models based on conventional risk factors alone. The present study demonstrates that integrated PRSs and gut metagenomic risk models improve the predictive value over conventional risk factors for common chronic diseases.

Evidence for the additivity of rare and common variant burden throughout the spectrum of intellectual disability.

Intellectual disability (ID) is a common disorder, yet there is a wide spectrum of impairment from mild to profoundly affected individuals. Mild ID is seen as the low extreme of the general distribution of intelligence, while severe ID is often seen as a monogenic disorder caused by rare, pathogenic, highly penetrant variants. To investigate the genetic factors influencing mild and severe ID, we evaluated rare and common variation in the Northern Finland Intellectual Disability cohort (n = 1096 ID patients), a cohort with a high percentage of mild ID (n = 550) and from a population bottleneck enriched in rare, damaging variation. Despite this enrichment, we found only a small percentage of ID was due to recessive Finnish-enriched variants (0.5%). A larger proportion was linked to dominant variation, with a significant burden of rare, damaging variation in both mild and severe ID. This rare variant burden was enriched in more severe ID (p = 2.4e-4), patients without a relative with ID (p = 4.76e-4), and in those with features associated with monogenic disorders. We also found a significant burden of common variants associated with decreased cognitive function, with no difference between mild and more severe ID. When we included common and rare variants in a joint model, the rare and common variants had additive effects in both mild and severe ID. A multimodel inference approach also found that common and rare variants together best explained ID status (ΔAIC = 16.8, ΔBIC = 10.2). Overall, we report evidence for the additivity of rare and common variant burden throughout the spectrum of intellectual disability.

Functional EPAS1/HIF2A missense variant is associated with hematocrit in Andean highlanders.

Hypoxia-inducible factor pathway genes are linked to adaptation in both human and nonhuman highland species. EPAS1, a notable target of hypoxia adaptation, is associated with relatively lower hemoglobin concentration in Tibetans. We provide evidence for an association between an adaptive EPAS1 variant (rs570553380) and the same phenotype of relatively low hematocrit in Andean highlanders. This Andean-specific missense variant is present at a modest frequency in Andeans and absent in other human populations and vertebrate species except the coelacanth. CRISPR-base-edited human cells with this variant exhibit shifts in hypoxia-regulated gene expression, while metabolomic analyses reveal both genotype and phenotype associations and validation in a lowland population. Although this genocopy of relatively lower hematocrit in Andean highlanders parallels well-replicated findings in Tibetans, it likely involves distinct pathway responses based on a protein-coding versus noncoding variants, respectively. These findings illuminate how unique variants at EPAS1 contribute to the same phenotype in Tibetans and a subset of Andean highlanders despite distinct evolutionary trajectories.

Pulmonary primary oxysterol and bile acid synthesis as a predictor of outcomes in pulmonary arterial hypertension.

Pulmonary arterial hypertension (PAH) is a rare and fatal vascular disease with heterogeneous clinical manifestations. To date, molecular determinants underlying the development of PAH and related outcomes remain poorly understood. Herein, we identify pulmonary primary oxysterol and bile acid synthesis (PPOBAS) as a previously unrecognized pathway central to PAH pathophysiology. Mass spectrometry analysis of 2,756 individuals across five independent studies revealed 51 distinct circulating metabolites that predicted PAH-related mortality and were enriched within the PPOBAS pathway. Across independent single-center PAH studies, PPOBAS pathway metabolites were also associated with multiple cardiopulmonary measures of PAH-specific pathophysiology. Furthermore, PPOBAS metabolites were found to be increased in human and rodent PAH lung tissue and specifically produced by pulmonary endothelial cells, consistent with pulmonary origin. Finally, a poly-metabolite risk score comprising 13 PPOBAS molecules was found to not only predict PAH-related mortality but also outperform current clinical risk scores. This work identifies PPOBAS as specifically altered within PAH and establishes needed prognostic biomarkers for guiding therapy in PAH.

C-reactive protein modifies lipoprotein(a)-related risk for coronary heart disease: the BiomarCaRE project.

BACKGROUND AND AIMS: Recent investigations have suggested an interdependence of lipoprotein(a) [Lp(a)]-related risk for cardiovascular disease with background inflammatory burden. The aim the present analysis was to investigate whether high-sensitive C-reactive protein (hsCRP) modulates the association between Lp(a) and coronary heart disease (CHD) in the general population. METHODS: Data from 71 678 participants from 8 European prospective population-based cohort studies were used (65 661 without/6017 with established CHD at baseline; median follow-up 9.8/13.8 years, respectively). Fine and Gray competing risk-adjusted models were calculated according to accompanying hsCRP concentration (<2 and ≥2 mg/L). RESULTS: Among CHD-free individuals, increased Lp(a) levels were associated with incident CHD irrespective of hsCRP concentration: fully adjusted sub-distribution hazard ratios [sHRs (95% confidence interval)] for the highest vs. lowest fifth of Lp(a) distribution were 1.45 (1.23-1.72) and 1.48 (1.23-1.78) for a hsCRP group of <2 and ≥2 mg/L, respectively, with no interaction found between these two biomarkers on CHD risk (Pinteraction = 0.82). In those with established CHD, similar associations were seen only among individuals with hsCRP ≥ 2 mg/L [1.34 (1.03-1.76)], whereas among participants with a hsCRP concentration <2 mg/L, there was no clear association between Lp(a) and future CHD events [1.29 (0.98-1.71)] (highest vs. lowest fifth, fully adjusted models; Pinteraction = 0.024). CONCLUSIONS: While among CHD-free individuals Lp(a) was significantly associated with incident CHD regardless of hsCRP, in participants with CHD at baseline, Lp(a) was related to recurrent CHD events only in those with residual inflammatory risk. These findings might guide adequate selection of high-risk patients for forthcoming Lp(a)-targeting compounds.

Regional and temporal differences in the associations between cardiovascular disease and its classic risk factors: an analysis of 49 cohorts from 11 European countries.

AIMS: The regional and temporal differences in the associations between cardiovascular disease (CVD) and its classic risk factors are unknown. The current study examined these associations in different European regions over a 30-year period. METHODS AND RESULTS: The study sample comprised 553 818 individuals from 49 cohorts in 11 European countries (baseline: 1982-2012) who were followed up for a maximum of 10 years. Risk factors [sex, smoking, diabetes, non-HDL cholesterol, systolic blood pressure (BP), and body mass index (BMI)] and CVD events (coronary heart disease or stroke) were harmonized across cohorts. Risk factor-outcome associations were analysed using multivariable-adjusted Cox regression models, and differences in associations were assessed using meta-regression. The differences in the risk factor-CVD associations between central Europe, northern Europe, southern Europe, and the UK were generally small. Men had a slightly higher hazard ratio (HR) in southern Europe (P = 0.043 for overall difference), and those with diabetes had a slightly lower HR in central Europe (P = 0.022 for overall difference) compared with the other regions. Of the six CVD risk factors, minor HR decreases per decade were observed for non-HDL cholesterol [7% per mmol/L; 95% confidence interval (CI), 3-10%] and systolic BP (4% per 20 mmHg; 95% CI, 1-8%), while a minor HR increase per decade was observed for BMI (7% per 10 kg/m2; 95% CI, 1-13%). CONCLUSION: The results demonstrate that all classic CVD risk factors are still relevant in Europe, irrespective of regional area. Preventive strategies should focus on risk factors with the greatest population attributable risk.

All classic cardiovascular disease (CVD) risk factors are still relevant in Europe, irrespective of regional area. The differences in the associations of CVD risk factors with overt CVD between regions of Europe are generally small. Minor temporal hazard decreases were observed for non-HDL cholesterol and systolic blood pressure, while a minor hazard increase was observed for body mass index.

Role of Gut Microbiota in Statin-Associated New-Onset Diabetes-A Cross-Sectional and Prospective Analysis of the FINRISK 2002 Cohort.

BACKGROUND: Dyslipidemia is treated effectively with statins, but treatment has the potential to induce new-onset type-2 diabetes. Gut microbiota may contribute to this outcome variability. We assessed the associations of gut microbiota diversity and composition with statins. Bacterial associations with statin-associated new-onset type-2 diabetes (T2D) risk were also prospectively evaluated. METHODS: We examined shallow-shotgun-sequenced fecal samples from 5755 individuals in the FINRISK-2002 population cohort with a 17+-year-long register-based follow-up. Alpha-diversity was quantified using Shannon index and beta-diversity with Aitchison distance. Species-specific differential abundances were analyzed using general multivariate regression. Prospective associations were assessed with Cox regression. Applicable results were validated using gradient boosting. RESULTS: Statin use associated with differing taxonomic composition (R2, 0.02%; q=0.02) and 13 differentially abundant species in fully adjusted models (MaAsLin; q<0.05). The strongest positive association was with Clostridium sartagoforme (ß=0.37; SE=0.13; q=0.02) and the strongest negative association with Bacteroides cellulosilyticus (ß=-0.31; SE=0.11; q=0.02). Twenty-five microbial features had significant associations with incident T2D in statin users, of which only Bacteroides vulgatus (HR, 1.286 [1.136-1.457]; q=0.03) was consistent regardless of model adjustment. Finally, higher statin-associated T2D risk was seen with [Ruminococcus] torques (ΔHRstatins, +0.11; q=0.03), Blautia obeum (ΔHRstatins, +0.06; q=0.01), Blautia sp. KLE 1732 (ΔHRstatins, +0.05; q=0.01), and beta-diversity principal component 1 (ΔHRstatin, +0.07; q=0.03) but only when adjusting for demographic covariates. CONCLUSIONS: Statin users have compositionally differing microbiotas from nonusers. The human gut microbiota is associated with incident T2D risk in statin users and possibly has additive effects on statin-associated new-onset T2D risk.

Microbiome-based risk prediction in incident heart failure: a community challenge.

Heart failure (HF) is a major public health problem. Early identification of at-risk individuals could allow for interventions that reduce morbidity or mortality. The community-based FINRISK Microbiome DREAM challenge (synapse.org/finrisk) evaluated the use of machine learning approaches on shotgun metagenomics data obtained from fecal samples to predict incident HF risk over 15 years in a population cohort of 7231 Finnish adults (FINRISK 2002, n=559 incident HF cases). Challenge participants used synthetic data for model training and testing. Final models submitted by seven teams were evaluated in the real data. The two highest-scoring models were both based on Cox regression but used different feature selection approaches. We aggregated their predictions to create an ensemble model. Additionally, we refined the models after the DREAM challenge by eliminating phylum information. Models were also evaluated at intermediate timepoints and they predicted 10-year incident HF more accurately than models for 5- or 15-year incidence. We found that bacterial species, especially those linked to inflammation, are predictive of incident HF. This highlights the role of the gut microbiome as a potential driver of inflammation in HF pathophysiology. Our results provide insights into potential modeling strategies of microbiome data in prospective cohort studies. Overall, this study provides evidence that incorporating microbiome information into incident risk models can provide important biological insights into the pathogenesis of HF.

Waist-hip ratio is superior to BMI in predicting liver-related outcomes and synergizes with harmful alcohol use.

BACKGROUND: Obesity is associated with liver disease, but the best obesity-related predictor remains undefined. Controversy exists regarding possible synergism between obesity and alcohol use for liver-related outcomes (LRO). We assessed the predictive performance for LROs, and synergism with alcohol use, of abdominal obesity (waist-hip ratio, WHR), and compared it to overall obesity (body mass index, BMI). METHODS: Forty-thousand nine-hundred twenty-two adults attending the Finnish health-examination surveys, FINRISK 1992-2012 and Health 2000 studies, were followed through linkage with electronic healthcare registries for LROs (hospitalizations, cancers, and deaths). Predictive performance of obesity measures (WHR, waist circumference [WC], and BMI) were assessed by Fine-Gray models and time-dependent area-under-the-curve (AUC). RESULTS: There are 355 LROs during a median follow-up of 12.9 years (509047.8 person-years). WHR and WC emerge as more powerful predictors of LROs than BMI. WHR shows significantly better 10-year AUC values for LROs (0.714, 95% CI 0.685-0.743) than WC (0.648, 95% CI 0.617-0.679) or BMI (0.550, 95% CI 0.514-0.585) both overall and separately among men and women. WHR is predictive also in BMI strata. Absolute 10-year risks of LROs are more dependent on WHR than BMI. Moreover, WHR shows a significant supra-additive interaction effect with harmful alcohol use for liver-related outcomes (excess 10-year cumulative incidence of 2.8% from the interaction), which is not seen between BMI and harmful alcohol use. CONCLUSIONS: WHR is a better predictor than BMI or WC for LROs, and WHR better reflects the synergism with harmful alcohol use. WHR should be included in clinical assessment when evaluating obesity-related risks for liver outcomes.

Obesity has been linked to liver disease, but the most accurate measure for predicting obesity-related liver disease outcomes remains uncertain. In this study, we analyzed data from over 40,000 adults to compare the extent to which different measures of obesity can predict liver-related outcomes, such as severe liver disease, liver failure, or death from liver disease. The measures of obesity were the ratio of waist circumference to hip circumference (waist-hip ratio, WHR), waist circumference (WC), and body mass index (BMI). Our findings reveal that WHR and WC are stronger predictors of these outcomes than BMI. In particular, WHR demonstrated superior predictive ability and this predictive ability was influenced by harmful alcohol use. This study suggests that WHR may be a relatively simple but useful measure for clinicians to use when predicting obesity-related risks for liver health.

An arrhythmogenic metabolite in atrial fibrillation.

BACKGROUND: Long-chain acyl-carnitines (ACs) are potential arrhythmogenic metabolites. Their role in atrial fibrillation (AF) remains incompletely understood. Using a systems medicine approach, we assessed the contribution of C18:1AC to AF by analysing its in vitro effects on cardiac electrophysiology and metabolism, and translated our findings into the human setting. METHODS AND RESULTS: Human iPSC-derived engineered heart tissue was exposed to C18:1AC. A biphasic effect on contractile force was observed: short exposure enhanced contractile force, but elicited spontaneous contractions and impaired Ca2+ handling. Continuous exposure provoked an impairment of contractile force. In human atrial mitochondria from AF individuals, C18:1AC inhibited respiration. In a population-based cohort as well as a cohort of patients, high C18:1AC serum concentrations were associated with the incidence and prevalence of AF. CONCLUSION: Our data provide evidence for an arrhythmogenic potential of the metabolite C18:1AC. The metabolite interferes with mitochondrial metabolism, thereby contributing to contractile dysfunction and shows predictive potential as novel circulating biomarker for risk of AF.

Decreasing national trends in diabetic complications hide regional differences: a prospective population-based study using health care registers in Finland.

Objectives. To examine whether possibilities to improve care among patients with diabetes are reflected in the numbers of cardiovascular complications at national and regional level in Finland. Methods. The study population included all patients with diabetes in Finland since 1964. The incidences of first acute coronary syndrome, ischemic stroke and lower limb amputation were examined for the period from 2010 to 2017. The age- and sex-standardised incidence rates were calculated for the first events. Adjusted Poisson regression mixed models were used to calculate average annual trends and assess regional variation of incidences during the periods 2010 to 2013 and 2014 to 2017 in the university hospital districts (UHDs) and hospital districts (HDs). Results. The nationwide incidence of first acute coronary syndrome decreased among patients with diabetes by 2.7% (95% confidence interval 2.3%; 3.0%), ischemic stroke by 2.0% (1.5%; 2.4%) and major lower limb amputation by 4.6% (3.1%; 5.9%) annually. The sexes differed only in the decrease in acute coronary events. The annual decrease among males was 2.1% (1.6%; 2.6%) and among females was 3.4% (2.8%; 4.0%) (p = .001). Marked variation was observed among UHDs and HDs in the incidences of cardiovascular events and lower limb amputations in patients with diabetes. The variation in annual trends of diabetic complications was most pronounced in acute coronary syndrome among UHDs with an estimated variance of 0.0006 (p = .034). Conclusions. The decrease in the incidence of first cardiovascular events among patients with diabetes continued from 2010 to 2017 in Finland. However, the declining national incidence rates hide regional differences which should be a target for improvement.

Greengenes2 unifies microbial data in a single reference tree.

Studies using 16S rRNA and shotgun metagenomics typically yield different results, usually attributed to PCR amplification biases. We introduce Greengenes2, a reference tree that unifies genomic and 16S rRNA databases in a consistent, integrated resource. By inserting sequences into a whole-genome phylogeny, we show that 16S rRNA and shotgun metagenomic data generated from the same samples agree in principal coordinates space, taxonomy and phenotype effect size when analyzed with the same tree.

Drinking alcohol in moderation is associated with lower rate of all-cause mortality in individuals with higher rather than lower educational level: findings from the MORGAM project.

The association between socioeconomic status (SES) and alcohol-related diseases has been widely explored. Less is known, however, on whether the association of moderate drinking with all-cause mortality is modified by educational level (EL). Using harmonized data from 16 cohorts in the MORGAM Project (N = 142,066) the association of pattern of alcohol intake with hazard of all-cause mortality across EL (lower = primary-school; middle = secondary-school; higher = university/college degree) was assessed using multivariable Cox-regression and spline curves. A total of 16,695 deaths occurred in 11.8 years (median). In comparison with life-long abstainers, participants drinking 0.1-10 g/d of ethanol had 13% (HR = 0.87; 95%CI: 0.74-1.02), 11% (HR = 0.89; 0.84-0.95) and 5% (HR = 0.95; 0.89-1.02) lower rate of death in higher, middle and lower EL, respectively. Conversely, drinkers > 20 g/d had 1% (HR = 1.01; 0.82-1.25), 10% (HR = 1.10; 1.02-1.19) and 17% (HR = 1.17; 1.09-1.26) higher rate of death. The association of alcohol consumption with all-cause mortality was nonlinear, with a different J-shape by EL levels. It was consistent across both sexes and in various approaches of measuring alcohol consumption, including combining quantity and frequency and it was more evident when the beverage of preference was wine. We observed that drinking in moderation (≤ 10 g/d) is associated with lower mortality rate more evidently in individuals with higher EL than in people with lower EL, while heavy drinking is associated with higher mortality rate more evidently in individuals with lower EL than in people with higher EL, suggesting that advice on reducing alcohol intake should especially target individuals of low EL.

Persistent organic pollutants associate with liver disease in a Finnish general population sample.

BACKGROUND AND AIMS: Persistent organic pollutants (POPs) have multiple adverse effects on human health. Recent studies show a possible association with liver disease, but population-based data are scarce. In this population-based study, we studied the associations between POPs and biomarkers of liver disease and incident liver disease. METHODS: This study consisted of 2789 adults that participated in the environmental toxin subset of the Finnish health-examination survey, FINRISK 2007. Toxins were measured from serum samples, and standard liver tests and dynamic aspartate aminotransferase-alanine aminotransferase ratio (dAAR) were measured as biomarkers of liver function. Associations between POPs and the biomarkers were then analysed using linear regression. Associations between POPs and incident liver disease (n = 36) were analysed by Cox regression. RESULTS: Organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs) and several perfluorinated alkyl substances exhibited statistically significant positive associations with several biomarkers of liver injury (betacoefficient per SD 0.04-0.14, p < 0.05). These associations were stronger in subgroups of individuals with obesity or non-alcoholic fatty liver disease. OCPs, PCBs and perfluoro-octanoic acid also had significant positive associations with dAAR, which can be used to predict risk of incident severe liver outcomes (beta coefficient per SD 0.05-0.08, p < 0.05). OCPs and PCBs were also significantly and positively associated with incident liver disease (hazard ratio per SD 1.82 95% CI 1.21-2.73, p < 0.01 and hazard ratio per SD 1.69, 95% CI 1.07-2.68, p < 0.05 respectively). CONCLUSIONS: Several POPs show positive associations with markers of liver injury and incident liver disease, suggesting that environmental toxins are important risk factors for chronic liver disease.

Biomarker-based prediction of fatal and non-fatal cardiovascular outcomes in individuals with diabetes mellitus.

AIMS: The role of biomarkers in predicting cardiovascular outcomes in high-risk individuals is not well established. We aimed to investigate benefits of adding biomarkers to cardiovascular risk assessment in individuals with and without diabetes. METHODS AND RESULTS: We used individual-level data of 95 292 individuals of the European population harmonized in the Biomarker for Cardiovascular Risk Assessment across Europe consortium and investigated the prognostic ability of high-sensitivity cardiac troponin I (hs-cTnI), N-terminal prohormone of brain natriuretic peptide (NT-proBNP), and high-sensitivity C-reactive protein (hs-CRP). Cox-regression models were used to determine adjusted hazard ratios of diabetes and log-transformed biomarkers for fatal and non-fatal cardiovascular events. Models were compared using the likelihood ratio test. Stratification by specific biomarker cut-offs was performed for crude time-to-event analysis using Kaplan-Meier plots. Overall, 6090 (6.4%) individuals had diabetes at baseline, median follow-up was 9.9 years. Adjusting for classical risk factors and biomarkers, diabetes [HR 2.11 (95% CI 1.92, 2.32)], and all biomarkers (HR per interquartile range hs-cTnI 1.08 [95% CI 1.04, 1.12]; NT-proBNP 1.44 [95% CI 1.37, 1.53]; hs-CRP 1.27 [95% CI 1.21, 1.33]) were independently associated with cardiovascular events. Specific cut-offs for each biomarker identified a high-risk group of individuals with diabetes losing a median of 15.5 years of life compared to diabetics without elevated biomarkers. Addition of biomarkers to the Cox-model significantly improved the prediction of outcomes (likelihood ratio test for nested models P < 0.001), accompanied by an increase in the c-index (increase to 0.81). CONCLUSION: Biomarkers improve cardiovascular risk prediction in individuals with and without diabetes and facilitate the identification of individuals with diabetes at highest risk for cardiovascular events.

In this work, the role of cardiac biomarkers measured from blood to predict cardiovascular events and death is tested in individuals of the general population and particularly in those with known diabetes. The work is based on a cooperation of different population studies across Europe and includes more than 90 000 individuals, with more than 6000 having diabetes. We could demonstrate that the determination of three cardiac biomarkers helps to identify individuals at highest risk for cardiovascular events (e.g. myocardial infarction or stroke) and death, despite accounting for known cardiovascular risk factors in these individuals. Therefore, these biomarkers should be considered for routine risk assessment for cardiovascular diseases and could improve the early identification of high-risk individuals, consequently leading to an earlier initiation of preventive therapies.

Gut microbiome and atrial fibrillation-results from a large population-based study.

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.