Genome-wide association analysis reveals insights into the genetic architecture of right ventricular structure and function

[1]  Yike Guo,et al.  A population-based phenome-wide association study of cardiac and aortic structure and function , 2020, Nature Medicine.

[2]  P. Matthews,et al.  Genetic and functional insights into the fractal structure of the heart , 2020, Nature.

[3]  M. Geijer,et al.  Loss of supervillin causes myopathy with myofibrillar disorganization and autophagic vacuoles , 2020, Brain : a journal of neurology.

[4]  Joao A. C. Lima,et al.  Analysis of cardiac magnetic resonance imaging in 36,000 individuals yields genetic insights into dilated cardiomyopathy , 2020, Nature Communications.

[5]  Christopher D. Brown,et al.  The GTEx Consortium atlas of genetic regulatory effects across human tissues , 2019, Science.

[6]  Lisa Bastarache,et al.  Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation , 2019, JMIR Medical Informatics.

[7]  Gregory M. Cooper,et al.  CADD: predicting the deleteriousness of variants throughout the human genome , 2018, Nucleic Acids Res..

[8]  Milton Pividori,et al.  Integrating predicted transcriptome from multiple tissues improves association detection , 2018, bioRxiv.

[9]  M. Kanai,et al.  Genetic analysis of quantitative traits in the Japanese population links cell types to complex human diseases , 2018, Nature Genetics.

[10]  Ben Glocker,et al.  Automated cardiovascular magnetic resonance image analysis with fully convolutional networks , 2017, Journal of Cardiovascular Magnetic Resonance.

[11]  Erdogan Taskesen,et al.  Functional mapping and annotation of genetic associations with FUMA , 2017, Nature Communications.

[12]  P. Visscher,et al.  Multi-trait analysis of genome-wide association summary statistics using MTAG , 2017, Nature Genetics.

[13]  Christopher E. Berndsen,et al.  Deregulated Ca2+ cycling underlies the development of arrhythmia and heart disease due to mutant obscurin , 2017, Science Advances.

[14]  Steven B Marston,et al.  Obscurin variants and inherited cardiomyopathies , 2017, Biophysical Reviews.

[15]  B. Patham,et al.  Hypothyroidism and the Heart. , 2017, Methodist DeBakey cardiovascular journal.

[16]  H. Hakonarson,et al.  Exome-wide association study reveals novel susceptibility genes to sporadic dilated cardiomyopathy , 2017, PloS one.

[17]  Stefan K. Piechnik,et al.  Reference ranges for cardiac structure and function using cardiovascular magnetic resonance (CMR) in Caucasians from the UK Biobank population cohort , 2017, Journal of Cardiovascular Magnetic Resonance.

[18]  Ayellet V. Segrè,et al.  Colocalization of GWAS and eQTL Signals Detects Target Genes , 2016, bioRxiv.

[19]  Stephen Burgess,et al.  PhenoScanner: a database of human genotype–phenotype associations , 2016, Bioinform..

[20]  Hedi Peterson,et al.  g:Profiler—a web server for functional interpretation of gene lists (2016 update) , 2016, Nucleic Acids Res..

[21]  P. Matthews,et al.  UK Biobank’s cardiovascular magnetic resonance protocol , 2015, Journal of Cardiovascular Magnetic Resonance.

[22]  M. Daly,et al.  An Atlas of Genetic Correlations across Human Diseases and Traits , 2015, Nature Genetics.

[23]  Joris M. Mooij,et al.  MAGMA: Generalized Gene-Set Analysis of GWAS Data , 2015, PLoS Comput. Biol..

[24]  N. Wray,et al.  Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance components analysis , 2015, Nature Genetics.

[25]  P. Elliott,et al.  UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age , 2015, PLoS medicine.

[26]  Michael Q. Zhang,et al.  Integrative analysis of 111 reference human epigenomes , 2015, Nature.

[27]  J. Hirschhorn,et al.  Biological interpretation of genome-wide association studies using predicted gene functions , 2015, Nature Communications.

[28]  M. Daly,et al.  LD Score regression distinguishes confounding from polygenicity in genome-wide association studies , 2014, Nature Genetics.

[29]  Ellen T. Gelfand,et al.  The Genotype-Tissue Expression (GTEx) project , 2013, Nature Genetics.

[30]  Eurie L. Hong,et al.  Annotation of functional variation in personal genomes using RegulomeDB , 2012, Genome research.

[31]  S. Apostolakis,et al.  The Right Ventricle in Health and Disease: Insights into Physiology, Pathophysiology and Diagnostic Management , 2012, Cardiology.

[32]  A. Noordegraaf,et al.  The role of the right ventricle in pulmonary arterial hypertension , 2011, European Respiratory Review.

[33]  H. Hakonarson,et al.  ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data , 2010, Nucleic acids research.

[34]  D. Bluemke,et al.  Relation of cardiovascular risk factors to right ventricular structure and function as determined by magnetic resonance imaging (results from the multi-ethnic study of atherosclerosis). , 2010, The American journal of cardiology.

[35]  Reedik Mägi,et al.  GWAMA: software for genome-wide association meta-analysis , 2010, BMC Bioinformatics.

[36]  Yurii S. Aulchenko,et al.  ProbABEL package for genome-wide association analysis of imputed data , 2010, BMC Bioinformatics.

[37]  R. Bloch,et al.  Muscle giants: molecular scaffolds in sarcomerogenesis. , 2009, Physiological reviews.

[38]  Thomas Meitinger,et al.  Genetic variants associated with cardiac structure and function: a meta-analysis and replication of genome-wide association data. , 2009, JAMA.

[39]  Jon Wakefield,et al.  Bayes factors for genome‐wide association studies: comparison with P‐values , 2009, Genetic epidemiology.

[40]  Sean Connors,et al.  Arrhythmogenic right ventricular cardiomyopathy type 5 is a fully penetrant, lethal arrhythmic disorder caused by a missense mutation in the TMEM43 gene. , 2008, American journal of human genetics.

[41]  D. Garrod,et al.  Desmosome structure, composition and function. , 2008, Biochimica et biophysica acta.

[42]  Hedi Peterson,et al.  g:Profiler—a web-based toolset for functional profiling of gene lists from large-scale experiments , 2007, Nucleic Acids Res..

[43]  Nuala A Sheehan,et al.  Adjusting for treatment effects in studies of quantitative traits: antihypertensive therapy and systolic blood pressure , 2005, Statistics in medicine.

[44]  James C Moon,et al.  Interstudy reproducibility of right ventricular volumes, function, and mass with cardiovascular magnetic resonance. , 2004, American heart journal.

[45]  M. Parast,et al.  Characterization of Palladin, a Novel Protein Localized to Stress Fibers and Cell Adhesions , 2000, The Journal of cell biology.

[46]  N. Danchin,et al.  Additional predictive value of both left and right ventricular ejection fractions on long-term survival in idiopathic dilated cardiomyopathy. , 1997, European heart journal.

[47]  I. Palacios,et al.  Right ventricular dysfunction: an independent predictor of adverse outcome in patients with myocarditis. , 1994, American heart journal.

[48]  D. Berman,et al.  Variable spectrum and prognostic implications of left and right ventricular ejection fractions in patients with and without clinical heart failure after acute myocardial infarction. , 1986, The American journal of cardiology.