Genetic determinants of complement activation in the general population.

Complement is a fundamental innate immune response component. Its alterations are associated with severe systemic diseases. To illuminate the complement's genetic underpinnings, we conduct genome-wide association studies of the functional activity of the classical (CP), lectin (LP), and alternative (AP) complement pathways in the Cooperative Health Research in South Tyrol study (n = 4,990). We identify seven loci, encompassing 13 independent, pathway-specific variants located in or near complement genes (CFHR4, C7, C2, MBL2) and non-complement genes (PDE3A, TNXB, ABO), explaining up to 74% of complement pathways' genetic heritability and implicating long-range haplotypes associated with LP at MBL2. Two-sample Mendelian randomization analyses, supported by transcriptome- and proteome-wide colocalization, confirm known causal pathways, establish within-complement feedback loops, and implicate causality of ABO on LP and of CFHR2 and C7 on AP. LP causally influences collectin-11 and KAAG1 levels and the risk of mouth ulcers. These results build a comprehensive resource to investigate the role of complement in human health.

Trends and symptoms of SARS-CoV-2 infection: a longitudinal study on an Alpine population representative sample.

OBJECTIVES: The continuous monitoring of SARS-CoV-2 infection waves and the emergence of novel pathogens pose a challenge for effective public health surveillance strategies based on diagnostics. Longitudinal population representative studies on incident events and symptoms of SARS-CoV-2 infection are scarce. We aimed at describing the evolution of the COVID-19 pandemic during 2020 and 2021 through regular monitoring of self-reported symptoms in an Alpine community sample. DESIGN: To this purpose, we designed a longitudinal population representative study, the Cooperative Health Research in South Tyrol COVID-19 study. PARTICIPANTS AND OUTCOME MEASURES: A sample of 845 participants was retrospectively investigated for active and past infections with swab and blood tests, by August 2020, allowing adjusted cumulative incidence estimation. Of them, 700 participants without previous infection or vaccination were followed up monthly until July 2021 for first-time infection and symptom self-reporting: COVID-19 anamnesis, social contacts, lifestyle and sociodemographic data were assessed remotely through digital questionnaires. Temporal symptom trajectories and infection rates were modelled through longitudinal clustering and dynamic correlation analysis. Negative binomial regression and random forest analysis assessed the relative importance of symptoms. RESULTS: At baseline, the cumulative incidence of SARS-CoV-2 infection was 1.10% (95% CI 0.51%, 2.10%). Symptom trajectories mimicked both self-reported and confirmed cases of incident infections. Cluster analysis identified two groups of high-frequency and low-frequency symptoms. Symptoms like fever and loss of smell fell in the low-frequency cluster. Symptoms most discriminative of test positivity (loss of smell, fatigue and joint-muscle aches) confirmed prior evidence. CONCLUSIONS: Regular symptom tracking from population representative samples is an effective screening tool auxiliary to laboratory diagnostics for novel pathogens at critical times, as manifested in this study of COVID-19 patterns. Integrated surveillance systems might benefit from more direct involvement of citizens' active symptom tracking.

Cluster analysis of angiotensin biomarkers to identify antihypertensive drug treatment in population studies.

BACKGROUND: The recent progress in molecular biology generates an increasing interest in investigating molecular biomarkers as markers of response to treatments. The present work is motivated by a study, where the objective was to explore the potential of the molecular biomarkers of renin-angiotensin-aldosterone system (RAAS) to identify the undertaken antihypertensive treatments in the general population. Population-based studies offer an opportunity to assess the effectiveness of treatments in real-world scenarios. However, lack of quality documentation, especially when electronic health record linkage is unavailable, leads to inaccurate reporting and classification bias. METHOD: We present a machine learning clustering technique to determine the potential of measured RAAS biomarkers for the identification of undertaken treatments in the general population. The biomarkers were simultaneously determined through a novel mass-spectrometry analysis in 800 participants of the Cooperative Health Research In South Tyrol (CHRIS) study with documented antihypertensive treatments. We assessed the agreement, sensitivity and specificity of the resulting clusters against known treatment types. Through the lasso penalized regression, we identified clinical characteristics associated with the biomarkers, accounting for the effects of cluster and treatment classifications. RESULTS: We identified three well-separated clusters: cluster 1 (n = 444) preferentially including individuals not receiving RAAS-targeting drugs; cluster 2 (n = 235) identifying angiotensin type 1 receptor blockers (ARB) users (weighted kappa κw = 74%; sensitivity = 73%; specificity = 83%); and cluster 3 (n = 121) well discriminating angiotensin-converting enzyme inhibitors (ACEi) users (κw = 81%; sensitivity = 55%; specificity = 90%). Individuals in clusters 2 and 3 had higher frequency of diabetes as well as higher fasting glucose and BMI levels. Age, sex and kidney function were strong predictors of the RAAS biomarkers independently of the cluster structure. CONCLUSIONS: Unsupervised clustering of angiotensin-based biomarkers is a viable technique to identify individuals on specific antihypertensive treatments, pointing to a potential application of the biomarkers as useful clinical diagnostic tools even outside of a controlled clinical setting.

Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease.

The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.

Determinants of SARS-CoV-2 nasopharyngeal testing in a rural community sample susceptible of first infection: the CHRIS COVID-19 study.

To characterize COVID-19 epidemiology, numerous population-based studies have been undertaken to model the risk of SARS-CoV-2 infection. Less is known about what may drive the probability to undergo testing. Understanding how much testing is driven by contextual or individual conditions is important to delineate the role of individual behavior and to shape public health interventions and resource allocation. In the Val Venosta/Vinschgau district (South Tyrol, Italy), we conducted a population-representative longitudinal study on 697 individuals susceptible to first infection who completed 4,512 repeated online questionnaires at four-week intervals between September 2020 and May 2021. Mixed-effects logistic regression models were fitted to investigate associations of self-reported SARS-CoV-2 testing with individual characteristics (social, demographic, and biological) and contextual determinants. Testing was associated with month of reporting, reflecting the timing of both the pandemic intensity and public health interventions, COVID-19-related symptoms (odds ratio, OR:8.26; 95% confidence interval, CI:6.04-11.31), contacts with infected individuals within home (OR:7.47, 95%CI:3.81-14.62) or outside home (OR:9.87, 95%CI:5.78-16.85), and being retired (OR:0.50, 95%CI:0.34-0.73). Symptoms and next within- and outside-home contacts were the leading determinants of swab testing predisposition in the most acute phase of the pandemics. Testing was not associated with age, sex, education, comorbidities, or lifestyle factors. In the study area, contextual determinants reflecting the course of the pandemic were predominant compared to individual sociodemographic characteristics in explaining the SARS-CoV-2 probability of testing. Decision makers should evaluate whether the intended target groups were correctly prioritized by the testing campaign.

Reverse Remodeling and Functional Improvement of Left Ventricle in Patients with Chronic Heart Failure Treated with Sacubitril/Valsartan: Comparison between Non-Ischemic and Ischemic Etiology.

Sacubitril/valsartan (SV) has been demonstrated to reduce cardiovascular mortality, hospitalization for heart failure and to induce reverse ventricular remodeling. The present study was designed to confirm the effects of SV in a selected population of patients with HFrEF and to evaluate the different responses between patients with an ischemic or a non-ischemic etiology. A total of 79 patients with indication of SV were recruited prospectively during a timelapse of 4 years. SV was overall associated to a reduction of end-diastolic and end-systolic volume, of NT-proBNP levels, furosemide dosage and NYHA functional class, together with an increase in EF. These changes were more evident in patients with non-ischemic dilated cardiomyopathy, who showed a significant improvement in ventricular volumes, ejection fraction, TAPSE and blood levels of NT-proBNP. Kaplan-Meier curves confirmed a greater benefit in terms of ejection-fraction improvement in non-ischemic patients compared to the ischemic group. The results of the present study confirm the positive effect of SV on NYHA functional class, NT- proBNP, left ventricular volumes and EF in HFrEF patients, showing evidence of association of SV with ventricular remodeling in patients with dilated cardiomyopathy of non-ischemic etiology compared to the ischemic group.

Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways.

The QT interval is an electrocardiographic measure representing the sum of ventricular depolarization and repolarization, estimated by QRS duration and JT interval, respectively. QT interval abnormalities are associated with potentially fatal ventricular arrhythmia. Using genome-wide multi-ancestry analyses (>250,000 individuals) we identify 177, 156 and 121 independent loci for QT, JT and QRS, respectively, including a male-specific X-chromosome locus. Using gene-based rare-variant methods, we identify associations with Mendelian disease genes. Enrichments are observed in established pathways for QT and JT, and previously unreported genes indicated in insulin-receptor signalling and cardiac energy metabolism. In contrast for QRS, connective tissue components and processes for cell growth and extracellular matrix interactions are significantly enriched. We demonstrate polygenic risk score associations with atrial fibrillation, conduction disease and sudden cardiac death. Prioritization of druggable genes highlight potential therapeutic targets for arrhythmia. Together, these results substantially advance our understanding of the genetic architecture of ventricular depolarization and repolarization.

Associations of Polymorphisms in the Peroxisome Proliferator-Activated Receptor Gamma Coactivator-1 Alpha Gene With Subsequent Coronary Heart Disease: An Individual-Level Meta-Analysis.

Background: The knowledge of factors influencing disease progression in patients with established coronary heart disease (CHD) is still relatively limited. One potential pathway is related to peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PPARGC1A), a transcription factor linked to energy metabolism which may play a role in the heart function. Thus, its associations with subsequent CHD events remain unclear. We aimed to investigate the effect of three different SNPs in the PPARGC1A gene on the risk of subsequent CHD in a population with established CHD. Methods: We employed an individual-level meta-analysis using 23 studies from the GENetIcs of sUbSequent Coronary Heart Disease (GENIUS-CHD) consortium, which included participants (n = 80,900) with either acute coronary syndrome, stable CHD, or a mixture of both at baseline. Three variants in the PPARGC1A gene (rs8192678, G482S; rs7672915, intron 2; and rs3755863, T528T) were tested for their associations with subsequent events during the follow-up using a Cox proportional hazards model adjusted for age and sex. The primary outcome was subsequent CHD death or myocardial infarction (CHD death/myocardial infarction). Stratified analyses of the participant or study characteristics as well as additional analyses for secondary outcomes of specific cardiovascular disease diagnoses and all-cause death were also performed. Results: Meta-analysis revealed no significant association between any of the three variants in the PPARGC1A gene and the primary outcome of CHD death/myocardial infarction among those with established CHD at baseline: rs8192678, hazard ratio (HR): 1.01, 95% confidence interval (CI) 0.98-1.05 and rs7672915, HR: 0.97, 95% CI 0.94-1.00; rs3755863, HR: 1.02, 95% CI 0.99-1.06. Similarly, no significant associations were observed for any of the secondary outcomes. The results from stratified analyses showed null results, except for significant inverse associations between rs7672915 (intron 2) and the primary outcome among 1) individuals aged ≥65, 2) individuals with renal impairment, and 3) antiplatelet users. Conclusion: We found no clear associations between polymorphisms in the PPARGC1A gene and subsequent CHD events in patients with established CHD at baseline.

Comprehensive Update and Revision of Nomenclature on Complement C6 and C7 Variants.

Complement genes encompass a wide array of variants, giving rise to numerous protein isoforms that have often been shown to exhibit clinical significance. Given that these variants have been discovered over a span of 50 y, one challenging consequence is the inconsistency in the terminology used to classify them. This issue is prominently evident in the nomenclature used for complement C6 and C7 variants, for which we observed a great discrepancy between previously published works and variants described in current genome browsers. This report discusses the causes for the discrepancies in C6 and C7 nomenclature and seeks to establish a classification system that would unify existing and future variants. The inconsistency in the methods used to annotate amino acids and the modifications pinpointed in the C6 and C7 primers are some of the factors that contribute greatly to the discrepancy in the nomenclature. Several variants that were classified incorrectly are highlighted in this report, and we showcase first-hand how a unified classification system is important to match previous with current genetic information. Ultimately, we hope that the proposed classification system of nomenclature becomes an incentive for studies on complement variants and their physiological and/or pathological effects.

A Mendelian randomization study investigating the causal role of inflammation on Parkinson's disease.

There is increasing evidence for inflammation as a determinant in the pathogenesis of Parkinson's disease, but its role in parkinsonian neurodegeneration remains elusive. It is not clear whether inflammatory cascades are causes or consequences of dopamine neuron death. In the present study, we aim to perform an in-depth statistical investigation of the causal relationship between inflammation and Parkinson's disease using a two-sample Mendelian randomization design. Genetic instruments were selected using summary-level data from the largest genome-wide association studies to date (sample size ranging from 13 955 to 204 402 individuals) conducted on a European population for the following inflammation biomarkers: C-reactive protein, interleukin-6, interleukin 1 receptor antagonist and tumour necrosis factor α. Genetic association data on Parkinson's disease (56 306 cases and 1 417 791 controls) and age at onset of Parkinson's disease (28 568 cases) were obtained from the International Parkinson's Disease Genomics Consortium. On primary analysis, causal associations were estimated on sets of strong (P-value < 5 × 10-8; F-statistic > 10) and independent (linkage disequilibrium r2 < 0.001) genetic instruments using the inverse-variance weighted method. In sensitivity analysis, we estimated causal effects using robust Mendelian randomization methods and after removing pleiotropic genetic variants. Reverse causation was also explored. We repeated the analysis on different data sources for inflammatory biomarkers to check the consistency of the findings. In all the three data sources selected for interleukin-6, we found statistical evidence for an earlier age at onset of Parkinson's disease associated with increased interleukin-6 concentration [years difference per 1 log-unit increase = -2.364, 95% confidence interval (CI) = -4.789-0.060; years difference per 1 log-unit increase = -2.011, 95% CI = -3.706 to -0.317; years difference per 1 log-unit increase = -1.569, 95% CI = -2.891 to -0.247]. We did not observe any statistical evidence for causal effects of C-reactive protein, interleukin 1 receptor antagonist and tumour necrosis factor α on both Parkinson's disease and its age at onset. Results after excluding possible pleiotropic genetic variants were consistent with findings from primary analyses. When investigating reverse causation, we did not find evidence for a causal effect of Parkinson's disease or age at onset on any biomarkers of inflammation. We found evidence for a causal association between the onset of Parkinson's disease and interleukin-6. The findings of this study suggest that the pro-inflammatory activity of the interleukin-6 cytokine could be a determinant of prodromal Parkinson's disease.

GCN5 contributes to intracellular lipid accumulation in human primary cardiac stromal cells from patients affected by Arrhythmogenic cardiomyopathy.

Arrhythmogenic cardiomyopathy (ACM) is a genetic disease associated with sudden cardiac death and cardiac fibro-fatty replacement. Over the last years, several works have demonstrated that different epigenetic enzymes can affect not only gene expression changes in cardiac diseases but also cellular metabolism. Specifically, the histone acetyltransferase GCN5 is known to facilitate adipogenesis and modulate cardiac metabolism in heart failure. Our group previously demonstrated that human primary cardiac stromal cells (CStCs) contribute to adipogenesis in the ACM pathology. Thus, this study aims to evaluate the role of GCN5 in ACM intracellular lipid accumulation. To do so, CStCs were obtained from right ventricle biopsies of ACM patients and from samples of healthy cadaveric donors (CTR). GCN5 expression was increased both in ex vivo and in vitro ACM samples compared to CTR. When GCN5 expression was silenced or pharmacologically inhibited by the administration of MB-3, we observed a reduction in lipid accumulation and a mitigation of reactive oxygen species (ROS) production in ACM CStCs. In agreement, transcriptome analysis revealed that the presence of MB-3 modified the expression of pathways related to cellular redox balance. Altogether, our findings suggest that GCN5 inhibition reduces fat accumulation in ACM CStCs, partially by modulating intracellular redox balance pathways.

Prospective epidemiological, molecular, and genetic characterization of a novel coronavirus disease in the Val Venosta/Vinschgau: the CHRIS COVID-19 study protocol.

The COVID-19 pandemic has been threatening the healthcare and socioeconomic systems of entire nations. While population-based surveys to assess the distribution of SARS-CoV-2 infection have become a priority, pre-existing longitudinal studies are ideally suited to assess the determinants of COVID-19 onset and severity.The Cooperative Health Research In South Tyrol (CHRIS) study completed the baseline recruitment of 13,393 adults from the Venosta/Vinschgau rural district in 2018, collecting extensive phenotypic and biomarker data, metabolomic data, densely imputed genotype and whole-exome sequencing data.Based on CHRIS, we designed a prospective study, called CHRIS COVID-19, aimed at: 1) estimating the incidence of SARS-CoV-2 infections; 2) screening for and investigating the determinants of incident infection among CHRIS participants and their household members; 3) monitoring the immune response of infected participants prospectively.An online screening questionnaire was sent to all CHRIS participants and their household members. A random sample of 1450 participants representative of the district population was invited to assess active (nasopharyngeal swab) or past (serum antibody test) infections. We prospectively invited for complete SARS-CoV-2 testing all questionnaire completers gauged as possible cases of past infection and their household members. In positive tested individuals, antibody response is monitored quarterly for one year. Untested and negative participants receive the screening questionnaire every four weeks until gauged as possible incident cases or till the study end.Originated from a collaboration between researchers and community stakeholders, the CHRIS COVID-19 study aims at generating knowledge about the epidemiological, molecular, and genetic characterization of COVID-19 and its long-term sequelae.

Genetic and Metabolic Determinants of Atrial Fibrillation in a General Population Sample: The CHRIS Study.

Atrial fibrillation (AF) is a supraventricular arrhythmia deriving from uncoordinated electrical activation with considerable associated morbidity and mortality. To expand the limited understanding of AF biological mechanisms, we performed two screenings, investigating the genetic and metabolic determinants of AF in the Cooperative Health Research in South Tyrol study. We found 110 AF cases out of 10,509 general population individuals. A genome-wide association scan (GWAS) identified two novel loci (p-value < 5 × 10-8) around SNPs rs745582874, next to gene PBX1, and rs768476991, within gene PCCA, with genotype calling confirmed by Sanger sequencing. Risk alleles at both SNPs were enriched in a family detected through familial aggregation analysis of the phenotype, and both rare alleles co-segregated with AF. The metabolic screening of 175 metabolites, in a subset of individuals, revealed a 41% lower concentration of lysophosphatidylcholine lysoPC a C20:3 in AF cases compared to controls (p-adj = 0.005). The genetic findings, combined with previous evidence, indicate that the two identified GWAS loci may be considered novel genetic rare determinants for AF. Considering additionally the association of lysoPC a C20:3 with AF by metabolic screening, our results demonstrate the valuable contribution of the combined genomic and metabolomic approach in studying AF in large-scale population studies.

Prevalence and determinants of serum antibodies to SARS-CoV-2 in the general population of the Gardena valley.

Estimating the spread of SARS-CoV-2 infection in communities is critical. We surveyed 2244 stratified random sample community members of the Gardena valley, a winter touristic area, amidst the first expansion phase of the COVID-19 pandemic in Europe. We measured agreement between Diasorin and Abbott serum bioassay outputs and the Abbott optimal discriminant threshold of serum neutralisation titres with recursive receiver operating characteristic curve. We analytically adjusted serum antibody tests for unbiased seroprevalence estimate and analysed the determinants of infection with non-response weighted multiple logistic regression. SARS-CoV-2 seroprevalence was 26.9% (95% CI 25.2-28.6) by June 2020. The bioassays had a modest agreement with each other. At a lower threshold than the manufacturer's recommended level, the Abbott assay reflected greater discrimination of serum neutralisation capacity. Seropositivity was associated with place and economic activity, not with sex or age. Symptoms like fever and weakness were age-dependent. SARS-CoV-2 mitigation strategies should account for context in high prevalence areas.

Association between non-alcoholic fatty liver disease and impaired cardiac sympathetic/parasympathetic balance in subjects with and without type 2 diabetes-The Cooperative Health Research in South Tyrol (CHRIS)-NAFLD sub-study.

BACKGROUND AND AIMS: Cardiovascular disease (CVD) is the leading cause of death in patients with non-alcoholic fatty liver disease (NAFLD), both with and without type 2 diabetes mellitus (T2DM). Cardiac autonomic dysfunction is a risk factor for CVD morbidity and mortality. The aim of this pilot study was to assess whether there is an association between NAFLD and impaired cardiac autonomic function. METHODS AND RESULTS: Among the first 4979 participants from the Cooperative Health Research in South Tyrol (CHRIS) study, we randomly recruited 173 individuals with T2DM and 183 age- and sex-matched nondiabetic controls. Participants underwent ultrasonography and vibration-controlled transient elastography (Fibroscan®, Echosens) to assess hepatic steatosis and liver stiffness. The low-to-high-frequency (LF/HF) power ratio and other heart rate variability (HRV) measures were calculated from a 20-min resting electrocardiogram (ECG) to derive a measure of cardiac sympathetic/parasympathetic imbalance. Among the 356 individuals recruited for the study, 117 had NAFLD and T2DM, 56 had T2DM alone, 68 had NAFLD alone, and 115 subjects had neither condition. Individuals with T2DM and NAFLD (adjusted odds ratio [OR] 4.29, 95% confidence intervals [CI] 1.90-10.6) and individuals with NAFLD alone (adjusted OR 3.41, 95% CI 1.59-7.29), but not those with T2DM alone, had a substantially increased risk of having cardiac sympathetic/parasympathetic imbalance, compared with those without NAFLD and T2DM. Logistic regression models were adjusted for age, sex, body mass index (BMI), hypertension, dyslipidemia, insulin resistance, hemoglobin A1c (HbA1c), C-reactive protein (CRP), and Fibroscan®-measured liver stiffness. CONCLUSIONS: NAFLD was associated with cardiac sympathetic/parasympathetic imbalance, regardless of the presence or absence of T2DM, liver stiffness, and other potential confounding factors.

Should We Continue Assessing Glomerular Filtration Rate with the Cockroft-Gault Formula in NOAC-Treated Patients? The Magnitude of the Problem.

Despite the proven superiority of the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) over the Cockcroft-Gault (CG) formula, current guidelines recommend the latter to assess renal function in patients treated with non-vitamin K antagonist oral anticoagulants (NOACs). To assess the relationship between the CG and the recommended CKD-EPI formulas, in a cohort of atrial fibrillation (AF) patients treated with NOACs, and the misclassifications introduced by the CG formula for renal function levels, we estimated renal function with three equations: CG, CKD-EPI with body surface adjustment (1.73 mL/m2, CKD-EPI) and without such adjustment (CKD-EPI_noBSA), in all consecutive AF patients discharged from NOACs from the Cardiology Division of a main city hospital between February 1st and May 31st 2018. We compared the different estimates of glomerular filtration rate and potential renal function class misclassifications. We reclassified 37/115 patients (32.1%) when switching from the CG to the CKD-EPI; and 24/115 (20.8%) switching from the CG to the CKD-EPI_noBSA formulas. Class reallocation was distributed across all levels of renal function, but mostly affected the "hyper-normal" function. In estimating consequences of such reallocation, a change in NOAC dosages would have occurred in 10/115 patients (8.7%) when switching from the CG to the CKD-EPI formula and in 10/115 patients when switching from the CG to the CKD-EPI_noBSA formula. Although the CG method has been traditionally used to calculate renal function in all NOAC studies, a renal dysfunction class reallocation occurs in a substantial fraction of hospital-admitted AF patients with the use of better estimates of renal function.

Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction.

The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.

Silencing of CCR4-NOT complex subunits affects heart structure and function.

The identification of genetic variants that predispose individuals to cardiovascular disease and a better understanding of their targets would be highly advantageous. Genome-wide association studies have identified variants that associate with QT-interval length (a measure of myocardial repolarization). Three of the strongest associating variants (single-nucleotide polymorphisms) are located in the putative promotor region of CNOT1, a gene encoding the central CNOT1 subunit of CCR4-NOT: a multifunctional, conserved complex regulating gene expression and mRNA stability and turnover. We isolated the minimum fragment of the CNOT1 promoter containing all three variants from individuals homozygous for the QT risk alleles and demonstrated that the haplotype associating with longer QT interval caused reduced reporter expression in a cardiac cell line, suggesting that reduced CNOT1 expression might contribute to abnormal QT intervals. Systematic siRNA-mediated knockdown of CCR4-NOT components in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) revealed that silencing CNOT1 and other CCR4-NOT genes reduced their proliferative capacity. Silencing CNOT7 also shortened action potential duration. Furthermore, the cardiac-specific knockdown of Drosophila orthologs of CCR4-NOT genes in vivo (CNOT1/Not1 and CNOT7/8/Pop2) was either lethal or resulted in dilated cardiomyopathy, reduced contractility or a propensity for arrhythmia. Silencing CNOT2/Not2, CNOT4/Not4 and CNOT6/6L/twin also affected cardiac chamber size and contractility. Developmental studies suggested that CNOT1/Not1 and CNOT7/8/Pop2 are required during cardiac remodeling from larval to adult stages. To summarize, we have demonstrated how disease-associated genes identified by GWAS can be investigated by combining human cardiomyocyte cell-based and whole-organism in vivo heart models. Our results also suggest a potential link of CNOT1 and CNOT7/8 to QT alterations and further establish a crucial role of the CCR4-NOT complex in heart development and function.This article has an associated First Person interview with the first author of the paper.

Microbiota, type 2 diabetes and non-alcoholic fatty liver disease: protocol of an observational study.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is characterized by triglyceride accumulation in the hepatocytes in the absence of alcohol overconsumption, commonly associated with insulin resistance and obesity. Both NAFLD and type 2 diabetes (T2D) are characterized by an altered microbiota composition, however the role of the microbiota in NAFLD and T2D is not well understood. To assess the relationship between alteration in the microbiota and NAFLD while dissecting the role of T2D, we established a nested study on T2D and non-T2D individuals within the Cooperative Health Research In South Tyrol (CHRIS) study, called the CHRIS-NAFLD study. Here, we present the study protocol along with baseline and follow-up characteristics of study participants. METHODS: Among the first 4979 CHRIS study participants, 227 individuals with T2D were identified and recalled, along with 227 age- and sex-matched non-T2D individuals. Participants underwent ultrasound and transient elastography examination to evaluate the presence of hepatic steatosis and liver stiffness. Additionally, sampling of saliva and faeces, biochemical measurements and clinical interviews were carried out. RESULTS: We recruited 173 T2D and 183 non-T2D participants (78% overall response rate). Hepatic steatosis was more common in T2D (63.7%) than non-T2D (36.3%) participants. T2D participants also had higher levels of liver stiffness (median 4.8 kPa, interquartile range (IQR) 3.7, 5.9) than non-T2D participants (median 3.9 kPa, IQR 3.3, 5.1). The non-invasive scoring systems like the NAFLD fibrosis score (NFS) suggests an increased liver fibrosis in T2D (mean - 0.55, standard deviation, SD, 1.30) than non-T2D participants (mean - 1.30, SD, 1.17). DISCUSSION: Given the comprehensive biochemical and clinical characterization of study participants, once the bioinformatics classification of the microbiota will be completed, the CHRIS-NAFLD study will become a useful resource to further our understanding of the relationship between microbiota, T2D and NAFLD.

Lipidomics, Atrial Conduction, and Body Mass Index.

BACKGROUND: Lipids are increasingly involved in cardiovascular risk prediction as potential proarrhythmic influencers. However, knowledge is limited about the specific mechanisms connecting lipid alterations with atrial conduction. METHODS: To shed light on this issue, we conducted a broad assessment of 151 sphingo- and phospholipids, measured using mass spectrometry, for association with atrial conduction, measured by P wave duration (PWD) from standard electrocardiograms, in the MICROS study (Microisolates in South Tyrol) (n=839). Causal pathways involving lipidomics, body mass index (BMI), and PWD were assessed using 2-sample Mendelian randomization analyses based on published genome-wide association studies of lipidomics (n=4034) and BMI (n=734 481), and genetic association analysis of PWD in 5 population-based studies (n=24 236). RESULTS: We identified an association with relative phosphatidylcholine 38:3 (%PC 38:3) concentration, which was replicated in the ORCADES (Orkney Complex Disease Study; n=951), with a pooled association across studies of 2.59 (95% CI, 1.3-3.9; P=1.1×10-4) ms PWD per mol% increase. While being independent of cholesterol, triglycerides, and glucose levels, the %PC 38:3-PWD association was mediated by BMI. Results supported a causal effect of BMI on both PWD ( P=8.3×10-5) and %PC 38:3 ( P=0.014). CONCLUSIONS: Increased %PC 38:3 levels are consistently associated with longer PWD, partly because of the confounding effect of BMI. The causal effect of BMI on PWD reinforces evidence of BMI's involvement into atrial electrical activity.