Systematic large-scale assessment of the genetic architecture of left ventricular noncompaction reveals diverse etiologies
Year: 2021
Type: article
Study design: Observational Study
Abstract: Background Left ventricular non-compaction (LVNC) is a condition characterised by trabeculations in the myocardial wall and is the subject of considerable conjecture as to whether it represents a distinct pathology or a secondary phenotype associated with other cardiac diseases, particularly cardiomyopathies. We sought to investigate the genetic architecture of LVNC by identifying genes and variant classes robustly associated with disease and comparing these to other genetically characterised cardiomyopathies. Methods We performed rare variant association analysis using six different LVNC cohorts comprising 840 cases together with 125,748 gnomAD population controls and compared results to similar analyses with dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) cases. Results We observed substantial overlap in genes and variant classes enriched in LVNC and DCM/HCM, indicating that in many cases LVNC belongs to a spectrum of more established cardiomyopathies, with non-compaction representing a phenotypic variation in patients with DCM- or HCM-causing variants. In contrast, five variant classes were uniquely enriched in LVNC cases, of which truncating variants in MYH7, ACTN2 and PRDM16 may represent a distinct LVNC aetiology. MYH7 truncating variants are generally considered as non-pathogenic but were detected in 2% of LVNC cases compared to 0.1% of controls, including a cluster of variants around a single splice region. Individuals with MYH7 truncating variants identified in the UK Biobank and cohorts of healthy volunteers also displayed significantly greater non-compaction compared to matched controls, with 50% meeting the diagnostic criteria for LVNC. Additionally, structural variants (exon deletions) in RYR2 and missense variants in the transmembrane region of HCN4 were enriched in LVNC cases, confirming prior reports regarding the association of these variant classes with combined LVNC and arrhythmia phenotypes. Conclusions We demonstrated that genetic association analysis can clarify the relationship between LVNC and established cardiomyopathies, highlighted substantial overlap with DCM/HCM but also identified variant classes associated with distinct LVNC and with joint LVNC/arrhythmia phenotypes. These results underline the complex genetic landscape of LVNC and inform how genetic testing in LVNC cases should be pursued and interpreted.
Source: Genetics in Medicine
Authors: Francesco Mazzarotto, Megan H. Hawley, Matteo Beltrami, Leander Beekman, Antonio de Marvao, Kathryn A. McGurk, Ben Statton, Beatrice Boschi, Francesca Girolami, Angharad M. Roberts, Elisabeth M. Lodder, Mona Allouba, Soha Romeih, Yasmine Aguib, A. John Baksi, Antonis Pantazis, Sanjay K. Prasad, Elisabetta Cerbai, Magdi H. Yacoub, Declan P. O’Regan, Stuart A. Cook, James S. Ware, Birgit Funke, Iacopo Olivotto, Connie R. Bezzina, Paul J.R. Barton, Roddy Walsh
Institutions: Royal Brompton & Harefield NHS Foundation Trust, Azienda Ospedaliero-Universitaria Careggi, University of Florence, Imperial College London, Amsterdam University Medical Centers, University of Amsterdam, MRC London Institute of Medical Sciences, Meyer Children's Hospital, Harefield Hospital, National University of Singapore, Duke-NUS Medical School, National Heart Centre Singapore, Harvard University, Massachusetts General Hospital
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,900
Funders: Wellcome Trust, National Institute for Health and Care Research, British Heart Foundation, Academy of Medical Sciences, Imperial College London, Imperial College Healthcare NHS Trust, European Commission, Fondation Leducq, Ministero della Salute, Università degli Studi di Firenze, Mason Medical Research Trust, Horizon 2020 Framework Programme, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, Medical Research Council, Agenzia Italiana del Farmaco, Ministero della Salute, NIHR Imperial Biomedical Research Centre
Awards: G1267581739, G1452829347, Research Excellence (round 3), G1853935037, G2076520454, Next generation sequencing of inherited cardiac conditions, G2763868019, G4012304641, Machine learning to model disease mechanisms and predict outcomes in cardiomyopathy, G4450932479, G5201182482, Genomic dissection of inherited cardiomyopathies: identifying alleles, genes and mechanisms, for patient stratification., Using machine learning to predict clinical outcomes in heart failure, G6868616705, Comprehensive molecular diagnostics for inherited cardiac disease, G7646030622, G7678070407, G849084591, Genomic dissection of inherited cardiomyopathies: identifying alleles, genes and mechanisms, for patient stratification.
OpenAlex ID: W3122761490