Coupling Interval Variability Differentiates Ventricular Ectopic Complexes Arising in the Aortic Sinus of Valsalva and Great Cardiac Vein From Other Sources

Objectives The objective of this study was to determine whether premature ventricular contractions (PVCs) arising from the aortic sinuses of Valsalva (SOV) and great cardiac vein (GCV) have coupling interval (CI) characteristics that differentiate them from other ectopic foci. Background PVCs occur at relatively fixed CI from the preceding normal QRS complex in most patients. However, we observed patients with PVCs originating in unusual areas (SOV and GCV) in whom the PVC CI was highly variable. We hypothesized that PVCs from these areas occur seemingly randomly because of the lack of electrotonic effects of the surrounding myocardium. Methods Seventy-three consecutive patients referred for PVC ablation were assessed. Twelve consecutive PVC CIs were recorded. The ΔCI (maximum – minimum CI) was measured. Results We studied 73 patients (age 50 ± 16 years, 47% male). The PVC origin was right ventricular (RV) in 29 (40%), left ventricular (LV) in 17 (23%), SOV in 21 (29%), and GCV in 6 (8%). There was a significant difference between the mean ΔCI of RV/LV PVCs compared with SOV/GCV PVCs (33 ± 15 ms vs. 116 ± 52 ms, p 60 ms demonstrated a sensitivity of 89%, specificity of 100%, positive predictive value of 100%, and negative predictive value of 94%. Cardiac events were more common in the SOV/GCV group versus the RV/LV group (7 of 27 [26%] vs. 2 of 46 [4%], p < 0.02). Conclusions ΔCI is more pronounced in PVCs originating from the SOV or GCV. A ΔCI of 60 ms helps discriminate the origin of PVCs before diagnostic electrophysiological study and may be associated with increased frequency of cardiac events

Monomorphic Ventricular Arrhythmias in Athletes.

Ventricular arrhythmias are challenging to manage in athletes with concern for an elevated risk of sudden cardiac death (SCD) during sports competition. Monomorphic ventricular arrhythmias (MMVA), while often benign in athletes with a structurally normal heart, are also associated with a unique subset of idiopathic and malignant substrates that must be clearly defined. A comprehensive evaluation for structural and/or electrical heart disease is required in order to exclude cardiac conditions that increase risk of SCD with exercise, such as hypertrophic cardiomyopathy and arrhythmogenic right ventricular cardiomyopathy. Unique issues for physicians who manage this population include navigating athletes through the decision of whether they can safely continue their chosen sport. In the absence of structural heart disease, therapies such as radiofrequency catheter ablation are very effective for certain arrhythmias and may allow for return to competitive sports participation. In this comprehensive review, we summarise the recommendations for evaluating and managing athletes with MMVA

Managing climate risk in water supply systems : materials and tools designed to empower technical professionals to better understand key issues

This manual has been developed as a learning tool to be used with a companion series of practical exercises. They have been developed to provide a hands-on approach to learning key concepts in hydrology and climate science as they relate to climate risk management in water supply systems, as introduced in the text

Circadian variability patterns predict and guide premature ventricular contraction ablation procedural inducibility and outcomes

Background Infrequent intraprocedural premature ventricular complexes (PVCs) may impede radiofrequency catheter ablation (RFA) outcome, and pharmacologic induction is unpredictable. Objective The purpose of this study was to determine whether PVC circadian variation could help predict drug response. Methods Consecutive patients referred for RFA with detailed Holter monitoring and frequent monomorphic PVCs were included. Patients were divided into 3 groups based on hourly PVC count relationship to corresponding mean heart rate (HR) during each of the 24 hours on Holter: fast-HR-dependent PVC (F-HR-PVC) type for a positive correlation (Pearson, P <.05), slow-HR-dependent PVC (S-HR-PVC) type for a negative correlation, and independent-HR-PVC (I-HR-PVC) when no correlation was found. Results Fifty-one of the 101 patients (50.5%) had F-HR-PVC, 39.6% I-HR-PVC, and 9.9% S-HR-PVC; 30.7% had infrequent intraprocedural PVC requiring drug infusion. The best predictor of infrequent PVC was number of hours with PVC count <120/h on Holter (area under the curve 0.80, sensitivity 83.9%, specificity 74.3%, for ≥2 h). Only F-HR-PVC patients responded to isoproterenol. Isoproterenol washout or phenylephrine infusion was successful for the 3 S-HR-PVC patients, and no drug could increase PVC frequency in the 12 I-HR-PVC patients. Long-term RFA success rate in patients with frequent PVCs at baseline (82.9%) was similar to those with infrequent PVC who responded to a drug (77.8%; P = .732) but significantly higher than for those who did not respond to any drug (15.4%; P <.0001). Conclusion A simple analysis of Holter PVC circadian variability provides incremental value to guide pharmacologic induction of PVCs during RFA and predict outcome. Patients with infrequent I-HR-PVC had the least successful outcomes from RF ablation

Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers.

Genetic studies of type 1 diabetes (T1D) have identified 50 susceptibility regions, finding major pathways contributing to risk, with some loci shared across immune disorders. To make genetic comparisons across autoimmune disorders as informative as possible, a dense genotyping array, the Immunochip, was developed, from which we identified four new T1D-associated regions (P < 5 × 10(-8)). A comparative analysis with 15 immune diseases showed that T1D is more similar genetically to other autoantibody-positive diseases, significantly most similar to juvenile idiopathic arthritis and significantly least similar to ulcerative colitis, and provided support for three additional new T1D risk loci. Using a Bayesian approach, we defined credible sets for the T1D-associated SNPs. The associated SNPs localized to enhancer sequences active in thymus, T and B cells, and CD34(+) stem cells. Enhancer-promoter interactions can now be analyzed in these cell types to identify which particular genes and regulatory sequences are causal.This research uses resources provided by the Type 1 Diabetes Genetics Consortium, a collaborative clinical study sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), the National Institute of Allergy and Infectious Diseases (NIAID), the National Human Genome Research Institute (NHGRI), the National Institute of Child Health and Human Development (NICHD) and JDRF and supported by grant U01 DK062418 from the US National Institutes of Health. Further support was provided by grants from the NIDDK (DK046635 and DK085678) to P.C. and by a joint JDRF and Wellcome Trust grant (WT061858/09115) to the Diabetes and Inflammation Laboratory at Cambridge University, which also received support from the NIHR Cambridge Biomedical Research Centre. ImmunoBase receives support from Eli Lilly and Company. C.W. and H.G. are funded by the Wellcome Trust (089989). The Cambridge Institute for Medical Research (CIMR) is in receipt of a Wellcome Trust Strategic Award (100140). We gratefully acknowledge the following groups and individuals who provided biological samples or data for this study. We obtained DNA samples from the British 1958 Birth Cohort collection, funded by the UK Medical Research Council and the Wellcome Trust. We acknowledge use of DNA samples from the NIHR Cambridge BioResource. We thank volunteers for their support and participation in the Cambridge BioResource and members of the Cambridge BioResource Scientific Advisory Board (SAB) and Management Committee for their support of our study. We acknowledge the NIHR Cambridge Biomedical Research Centre for funding. Access to Cambridge BioResource volunteers and to their data and samples are governed by the Cambridge BioResource SAB. Documents describing access arrangements and contact details are available at http://www.cambridgebioresource.org.uk/. We thank the Avon Longitudinal Study of Parents and Children laboratory in Bristol, UK, and the British 1958 Birth Cohort team, including S. Ring, R. Jones, M. Pembrey, W. McArdle, D. Strachan and P. Burton, for preparing and providing the control DNA samples. This study makes use of data generated by the Wellcome Trust Case Control Consortium, funded by Wellcome Trust award 076113; a full list of the investigators who contributed to the generation of the data is available from http://www.wtccc.org.uk/.This is the author accepted manuscript. The final version is available via NPG at http://www.nature.com/ng/journal/v47/n4/full/ng.3245.html

Genome Wide Association Identifies PPFIA1 as a Candidate Gene for Acute Lung Injury Risk Following Major Trauma

Acute Lung Injury (ALI) is a syndrome with high associated mortality characterized by severe hypoxemia and pulmonary infiltrates in patients with critical illness. We conducted the first investigation to use the genome wide association (GWA) approach to identify putative risk variants for ALI. Genome wide genotyping was performed using the Illumina Human Quad 610 BeadChip. We performed a two-stage GWA study followed by a third stage of functional characterization. In the discovery phase (Phase 1), we compared 600 European American trauma-associated ALI cases with 2266 European American population-based controls. We carried forward the top 1% of single nucleotide polymorphisms (SNPs) at p<0.01 to a replication phase (Phase 2) comprised of a nested case-control design sample of 212 trauma-associated ALI cases and 283 at-risk trauma non-ALI controls from ongoing cohort studies. SNPs that replicated at the 0.05 level in Phase 2 were subject to functional validation (Phase 3) using expression quantitative trait loci (eQTL) analyses in stimulated B-lymphoblastoid cell lines (B-LCL) in family trios. 159 SNPs from the discovery phase replicated in Phase 2, including loci with prior evidence for a role in ALI pathogenesis. Functional evaluation of these replicated SNPs revealed rs471931 on 11q13.3 to exert a cis-regulatory effect on mRNA expression in the PPFIA1 gene (p = 0.0021). PPFIA1 encodes liprin alpha, a protein involved in cell adhesion, integrin expression, and cell-matrix interactions. This study supports the feasibility of future multi-center GWA investigations of ALI risk, and identifies PPFIA1 as a potential functional candidate ALI risk gene for future research

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).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.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract 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

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD