Genetic and environmental determinants of diastolic heart function

Diastole is the sequence of physiological events that occur in the heart during ventricular filling and principally depends on myocardial relaxation and chamber stiffness. Abnormal diastolic function is related to many cardiovascular disease processes and is predictive of health outcomes, but its genetic architecture is largely unknown. Here, we use machine learning cardiac motion analysis to measure diastolic functional traits in 39,559 participants of the UK Biobank and perform a genome-wide association study. We identified 9 significant, independent loci near genes that are associated with maintaining sarcomeric function under biomechanical stress and genes implicated in the development of cardiomyopathy. Age, sex and diabetes were independent predictors of diastolic function and we found a causal relationship between genetically-determined ventricular stiffness and incident heart failure. Our results provide insights into the genetic and environmental factors influencing diastolic function that are relevant for identifying causal relationships and potential tractable targets

Heritability of haemodynamics in the ascending aorta

From Springer Nature via Jisc Publications RouterHistory: received 2020-03-23, accepted 2020-06-25, registration 2020-08-17, pub-electronic 2020-09-01, online 2020-09-01, collection 2020-12Publication status: PublishedFunder: Medical Research Council; doi: http://dx.doi.org/10.13039/501100000265; Grant(s): MR/K501311/1Funder: Engineering and Physical Sciences Research Council; doi: http://dx.doi.org/10.13039/501100000266; Grant(s): EP/N509565/1Funder: British Heart Foundation; doi: http://dx.doi.org/10.13039/501100000274; Grant(s): Personal ChairAbstract: Blood flow in the vasculature can be characterised by dimensionless numbers commonly used to define the level of instabilities in the flow, for example the Reynolds number, Re. Haemodynamics play a key role in cardiovascular disease (CVD) progression. Genetic studies have identified mechanosensitive genes with causal roles in CVD. Given that CVD is highly heritable and abnormal blood flow may increase risk, we investigated the heritability of fluid metrics in the ascending aorta calculated using patient-specific data from cardiac magnetic resonance (CMR) imaging. 341 participants from 108 British Caucasian families were phenotyped by CMR and genotyped for 557,124 SNPs. Flow metrics were derived from the CMR images to provide some local information about blood flow in the ascending aorta, based on maximum values at systole at a single location, denoted max, and a ‘peak mean’ value averaged over the area of the cross section, denoted pm. Heritability was estimated using pedigree-based (QTDT) and SNP-based (GCTA-GREML) methods. Estimates of Reynolds number based on spatially averaged local flow during systole showed substantial heritability (hPed2=41%[P=0.001], hSNP2=39%[P=0.002]), while the estimated heritability for Reynolds number calculated using the absolute local maximum velocity was not statistically significant (12–13%; P>0.05). Heritability estimates of the geometric quantities alone; e.g. aortic diameter (hPed2=29%[P=0.009], hSNP2=30%[P=0.010]), were also substantially heritable, as described previously. These findings indicate the potential for the discovery of genetic factors influencing haemodynamic traits in large-scale genotyped and phenotyped cohorts where local spatial averaging is used, rather than instantaneous values. Future Mendelian randomisation studies of aortic haemodynamic estimates, which are swift to derive in a clinical setting, will allow for the investigation of causality of abnormal blood flow in CVD

Phenotypic expression and outcomes in individuals with rare genetic variants of hypertrophic cardiomyopathy

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is caused by rare variants in sarcomere-encoding genes, but little is known about the clinical significance of these variants in the general population. OBJECTIVES: The goal of this study was to compare lifetime outcomes and cardiovascular phenotypes according to the presence of rare variants in sarcomere-encoding genes among middle-aged adults. METHODS: This study analyzed whole exome sequencing and cardiac magnetic resonance imaging in UK Biobank participants stratified according to sarcomere-encoding variant status. RESULTS: The prevalence of rare variants (allele frequency <0.00004) in HCM-associated sarcomere-encoding genes in 200,584 participants was 2.9% (n = 5,712; 1 in 35), and the prevalence of variants pathogenic or likely pathogenic for HCM (SARC-HCM-P/LP) was 0.25% (n = 493; 1 in 407). SARC-HCM-P/LP variants were associated with an increased risk of death or major adverse cardiac events compared with controls (hazard ratio: 1.69; 95% confidence interval [CI]: 1.38-2.07; P < 0.001), mainly due to heart failure endpoints (hazard ratio: 4.23; 95% CI: 3.07-5.83; P < 0.001). In 21,322 participants with both cardiac magnetic resonance imaging and whole exome sequencing, SARC-HCM-P/LP variants were associated with an asymmetric increase in left ventricular maximum wall thickness (10.9 ± 2.7 mm vs 9.4 ± 1.6 mm; P < 0.001), but hypertrophy (≥13 mm) was only present in 18.4% (n = 9 of 49; 95% CI: 9%-32%). SARC-HCM-P/LP variants were still associated with heart failure after adjustment for wall thickness (hazard ratio: 6.74; 95% CI: 2.43-18.7; P < 0.001). CONCLUSIONS: In this population of middle-aged adults, SARC-HCM-P/LP variants have low aggregate penetrance for overt HCM but are associated with an increased risk of adverse cardiovascular outcomes and an attenuated cardiomyopathic phenotype. Although absolute event rates are low, identification of these variants may enhance risk stratification beyond familial disease

Human Hereditary Cardiomyopathy Shares a Genetic Substrate With Bicuspid Aortic Valve.

The complex genetics underlying human cardiac disease is evidenced by its heterogenous manifestation, multigenic basis, and sporadic occurrence. These features have hampered disease modeling and mechanistic understanding. Here, we show that 2 structural cardiac diseases, left ventricular noncompaction (LVNC) and bicuspid aortic valve, can be caused by a set of inherited heterozygous gene mutations affecting the NOTCH ligand regulator MIB1 (MINDBOMB1) and cosegregating genes. We used CRISPR-Cas9 gene editing to generate mice harboring a nonsense or a missense MIB1 mutation that are both found in LVNC families. We also generated mice separately carrying these MIB1 mutations plus 5 additional cosegregating variants in the ASXL3, APCDD1, TMX3, CEP192, and BCL7A genes identified in these LVNC families by whole exome sequencing. Histological, developmental, and functional analyses of these mouse models were carried out by echocardiography and cardiac magnetic resonance imaging, together with gene expression profiling by RNA sequencing of both selected engineered mouse models and human induced pluripotent stem cell-derived cardiomyocytes. Potential biochemical interactions were assayed in vitro by coimmunoprecipitation and Western blot. Mice homozygous for the MIB1 nonsense mutation did not survive, and the mutation caused LVNC only in heteroallelic combination with a conditional allele inactivated in the myocardium. The heterozygous MIB1 missense allele leads to bicuspid aortic valve in a NOTCH-sensitized genetic background. These data suggest that development of LVNC is influenced by genetic modifiers present in affected families, whereas valve defects are highly sensitive to NOTCH haploinsufficiency. Whole exome sequencing of LVNC families revealed single-nucleotide gene variants of ASXL3, APCDD1, TMX3, CEP192, and BCL7A cosegregating with the MIB1 mutations and LVNC. In experiments with mice harboring the orthologous variants on the corresponding Mib1 backgrounds, triple heterozygous Mib1 Apcdd1 Asxl3 mice showed LVNC, whereas quadruple heterozygous Mib1 Cep192 Tmx3;Bcl7a mice developed bicuspid aortic valve and other valve-associated defects. Biochemical analysis suggested interactions between CEP192, BCL7A, and NOTCH. Gene expression profiling of mutant mouse hearts and human induced pluripotent stem cell-derived cardiomyocytes revealed increased cardiomyocyte proliferation and defective morphological and metabolic maturation. These findings reveal a shared genetic substrate underlying LVNC and bicuspid aortic valve in which MIB1-NOTCH variants plays a crucial role in heterozygous combination with cosegregating genetic modifiers.This study was supported by grants PID2019-104776RB-I00 and PID2020-120326RB-I00, CB16/11/00399 (CIBER CV) financed by MCIN/AEI/10.13039/501100011033, a grant from the Fundación BBVA (Ref. BIO14_298), and a grant from Fundació La Marató de TV3 (Ref. 20153431) to J.L.d.l.P. M.S.-A. was supported by a PhD contract from the Severo Ochoa Predoctor-al Program (SVP-2014-068723) of the MCIN/AEI/10.13039/501100011033. J.R.G.-B. was supported by SEC/FEC-INV-BAS 21/021. A.R. was funded by grants from MCIN (PID2021123925OB-I00), TerCel (RD16/0011/0024), AGAUR (2017-SGR-899), and Fundació La Marató de TV3 (201534-30). J.M.P.-P. was supported by RTI2018-095410-B-I00 (MCIN) and PY2000443 (Junta de Andalucía). B.I. was supported by the European Commission (H2020-HEALTH grant No. 945118) and by MCIN (PID2019-107332RB-I00). DO’R was sup-ported by the Medical Research Council (MC-A658-5QEB0) and KAMcG by the British Heart Foundation (RG/19/6/34387, RE/18/4/34215). The cost of this publication was supported in part with funds from the European Regional Devel-opment Fund. The Centro Nacional de Investigaciones Cardiovasculares is sup-ported by the ISCIII, the MCIN, and the Pro Centro Nacional de Investigaciones Cardiovasculares Foundation and is a Severo Ochoa Center of Excellence (grant CEX2020001041-S) financed by MCIN/AEI/10.13039/501100011033. For the purpose of open access, the authors have applied a CC BY public copyright license to any Author Accepted Manuscript version arising.S

Genetic and environmental determinants of diastolic heart function

Diastole is the sequence of physiological events that occur in the heart during ventricular filling and principally depends on myocardial relaxation and chamber stiffness. Abnormal diastolic function is related to many cardiovascular disease processes and is predictive of health outcomes, but its genetic architecture is largely unknown. Here, we use machine learning cardiac motion analysis to measure diastolic functional traits in 39,559 participants of the UK Biobank and perform a genome-wide association study. We identified 9 significant, independent loci near genes that are associated with maintaining sarcomeric function under biomechanical stress and genes implicated in the development of cardiomyopathy. Age, sex and diabetes were independent predictors of diastolic function and we found a causal relationship between genetically-determined ventricular stiffness and incident heart failure. Our results provide insights into the genetic and environmental factors influencing diastolic function that are relevant for identifying causal relationships and potential tractable targets

Biallelic Loss of Function Variants in Myocardial Zonula Adherens Protein Gene (MYZAP) Cause a Severe Recessive Form of Dilated Cardiomyopathy.

This study has been funded by grants from the Spanish Society of Cardiology (basic research grant 2021) to Dr Ochoa, Spanish Ministry of Science PLEC2022-009235 MCIN/AEI/10.13039/501100011033 co-funded by the European Union NextGenerationEU/PRTR to Drs Lara-Pezzi, Gómez-Gaviro, and Garcia-Pavia, and PID2021-124629OB-I00 and TED2021-129774B-C22 to Dr Lara-Pezzi, and from Instituto de Salud Carlos III (ISCIII) DTS22/00030 co-funded by the European Union to Dr Gómez-Gaviro. Drs Lara-Pezzi, Ware, and Garcia-Pavia are funded by the Pathfinder Cardiogenomics Programme of the European Innovation Council of the European Union (DCM-NEXT project; project 101115416). The CNIC is supported by the ISCIII, the Ministerio de Ciencia e Innovación (MCIN) and the Pro CNIC Foundation and is a Severo Ochoa Center of Excellence (grant CEX2020-001041-S funded by MICIN/ AEI/10.13039/501100011033). Drs Ware, McGurk, and Barton have been funded by the Medical Research Council (United Kingdom), Sir Jules Thorn Charitable Trust (21JTA), Wellcome Trust (107469/Z/15/Z), British Heart Foundation (RE/18/4/34215, FS/IPBSRF/22/27059), and the National Institute for Health and Care Research (NIHR) Imperial College Biomedical Research Centre. Part of this research was made possible through access to the data and findings generated by the 100 000 Genomes Project. The 100 000 Genomes Project is managed by Genomics England Limited (a wholly owned company of the Department of Health and Social Care). The 100 000 Genomes Project is funded by the NIHR and National Heart Service (NHS) England. The Wellcome Trust, Cancer Research UK and the Medical Research Council have also funded research infrastructure. The 100 000 Genomes Project uses data provided by patients and collected by the NHS as part of their care and support. The UK Biobank recruited 500 000 participants aged 40 to 69 years across the UK between 2006 and 2010 (National Research Ethics Service, 11/NW/0382; 10.1371/journal. pmed.1001779). This study was conducted under terms of access approval number 47602. Written informed consent was provided.S

Environmental and genetic predictors of human cardiovascular ageing

Abstract Cardiovascular ageing is a process that begins early in life and leads to a progressive change in structure and decline in function due to accumulated damage across diverse cell types, tissues and organs contributing to multi-morbidity. Damaging biophysical, metabolic and immunological factors exceed endogenous repair mechanisms resulting in a pro-fibrotic state, cellular senescence and end-organ damage, however the genetic architecture of cardiovascular ageing is not known. Here we use machine learning approaches to quantify cardiovascular age from image-derived traits of vascular function, cardiac motion and myocardial fibrosis, as well as conduction traits from electrocardiograms, in 39,559 participants of UK Biobank. Cardiovascular ageing is found to be significantly associated with common or rare variants in genes regulating sarcomere homeostasis, myocardial immunomodulation, and tissue responses to biophysical stress. Ageing is accelerated by cardiometabolic risk factors and we also identify prescribed medications that are potential modifiers of ageing. Through large-scale modelling of ageing across multiple traits our results reveal insights into the mechanisms driving premature cardiovascular ageing and reveal potential molecular targets to attenuate age-related processes

The penetrance of rare variants in cardiomyopathy-associated genes: A cross-sectional approach to estimating penetrance for secondary findings.

Understanding the penetrance of pathogenic variants identified as secondary findings (SFs) is of paramount importance with the growing availability of genetic testing. We estimated penetrance through large-scale analyses of individuals referred for diagnostic sequencing for hypertrophic cardiomyopathy (HCM; 10,400 affected individuals, 1,332 variants) and dilated cardiomyopathy (DCM; 2,564 affected individuals, 663 variants), using a cross-sectional approach comparing allele frequencies against reference populations (293,226 participants from UK Biobank and gnomAD). We generated updated prevalence estimates for HCM (1:543) and DCM (1:220). In aggregate, the penetrance by late adulthood of rare, pathogenic variants (23% for HCM, 35% for DCM) and likely pathogenic variants (7% for HCM, 10% for DCM) was substantial for dominant cardiomyopathy (CM). Penetrance was significantly higher for variant subgroups annotated as loss of function or ultra-rare and for males compared to females for variants in HCM-associated genes. We estimated variant-specific penetrance for 316 recurrent variants most likely to be identified as SFs (found in 51% of HCM- and 17% of DCM-affected individuals). 49 variants were observed at least ten times (14% of affected individuals) in HCM-associated genes. Median penetrance was 14.6% (±14.4% SD). We explore estimates of penetrance by age, sex, and ancestry and simulate the impact of including future cohorts. This dataset reports penetrance of individual variants at scale and will inform the management of individuals undergoing genetic screening for SFs. While most variants had low penetrance and the costs and harms of screening are unclear, some individuals with highly penetrant variants may benefit from SFs

Systematic large-scale assessment of the genetic architecture of left ventricular noncompaction reveals diverse etiologies

Purpose: To characterize the genetic architecture of left ventricular noncompaction (LVNC) and investigate the extent to which it may represent a distinct pathology or a secondary phenotype associated with other cardiac diseases. Methods: We performed rare variant association analysis with 840 LVNC cases and 125,748 gnomAD population controls, and compared results to similar analyses on dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM). Results: We observed substantial genetic overlap indicating that LVNC often represents a phenotypic variation of DCM or HCM. In contrast, truncating variants in MYH7, ACTN2, and PRDM16 were uniquely associated with LVNC and may reflect a distinct LVNC etiology. In particular, MYH7 truncating variants (MYH7tv), generally considered nonpathogenic for cardiomyopathies, were 20-fold enriched in LVNC cases over controls. MYH7tv heterozygotes identified in the UK Biobank and healthy volunteer cohorts also displayed significantly greater noncompaction compared with matched controls. RYR2 exon deletions and HCN4 transmembrane variants were also enriched in LVNC, supporting prior reports of association with arrhythmogenic LVNC phenotypes. Conclusion: LVNC is characterized by substantial genetic overlap with DCM/HCM but is also associated with distinct noncompaction and arrhythmia etiologies. These results will enable enhanced application of LVNC genetic testing and help to distinguish pathological from physiological noncompaction