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Mehdizadeh K, Soveizi M, Askarinejad A, Elahifar A, Masoumi T, Fazelifar AF, Asadian S, Maleki M, Kalayinia S. Combination of FLNC and JUP variants causing arrhythmogenic cardiomyopathy in an Iranian family with different clinical features. BMC Cardiovasc Disord 2024; 24:442. [PMID: 39180012 PMCID: PMC11342628 DOI: 10.1186/s12872-024-04126-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 08/16/2024] [Indexed: 08/26/2024] Open
Abstract
BACKGROUND Arrhythmogenic cardiomyopathy (ACM) characterized by progressive myocardial loss and replacement with fibro-fatty tissue is a major cause of sudden cardiac death (SCD). In particular, ACM with predominantly left ventricular involvement, known as arrhythmogenic left ventricular cardiomyopathy (ALVC), has a poor prognosis. METHODS The proband underwent whole-exome sequencing (WES) to determine the etiology of ALVC. Family members were then analyzed using PCR and Sanger sequencing. Clinical evaluations including 12-lead ECG, transthoracic echocardiography, and cardiac MRI were performed for all available first-degree relatives. RESULTS WES identified two variants in the FLNC (c.G3694A) and JUP (c.G1372A) genes, the combination of which results in ALVC and SCD. CONCLUSION The present study comprehensively investigates the involvement of two discovered variants of FLNC and JUP in the pathogenesis of ALVC. More study is necessary to elucidate the genetic factors involved in the etiology of ALVC.
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Affiliation(s)
- Kasra Mehdizadeh
- Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Mahdieh Soveizi
- Cardiogenetic Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Amir Askarinejad
- Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Amin Elahifar
- Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Tannaz Masoumi
- Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Amir Farjam Fazelifar
- Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Sanaz Asadian
- Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Majid Maleki
- Cardiogenetic Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Samira Kalayinia
- Cardiogenetic Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran.
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2
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Pottinger TD, Motelow JE, Povysil G, Moreno CAM, Ren Z, Phatnani H, Aitman TJ, Santoyo-Lopez J, Mitsumoto H, Goldstein DB, Harms MB. Rare variant analyses validate known ALS genes in a multi-ethnic population and identifies ANTXR2 as a candidate in PLS. BMC Genomics 2024; 25:651. [PMID: 38951798 PMCID: PMC11218304 DOI: 10.1186/s12864-024-10538-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 06/17/2024] [Indexed: 07/03/2024] Open
Abstract
BACKGROUND Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting over 300,000 people worldwide. It is characterized by the progressive decline of the nervous system that leads to the weakening of muscles which impacts physical function. Approximately, 15% of individuals diagnosed with ALS have a known genetic variant that contributes to their disease. As therapies that slow or prevent symptoms continue to develop, such as antisense oligonucleotides, it is important to discover novel genes that could be targets for treatment. Additionally, as cohorts continue to grow, performing analyses in ALS subtypes, such as primary lateral sclerosis (PLS), becomes possible due to an increase in power. These analyses could highlight novel pathways in disease manifestation. METHODS Building on our previous discoveries using rare variant association analyses, we conducted rare variant burden testing on a substantially larger multi-ethnic cohort of 6,970 ALS patients, 166 PLS patients, and 22,524 controls. We used intolerant domain percentiles based on sub-region Residual Variation Intolerance Score (subRVIS) that have been described previously in conjunction with gene based collapsing approaches to conduct burden testing to identify genes that associate with ALS and PLS. RESULTS A gene based collapsing model showed significant associations with SOD1, TARDBP, and TBK1 (OR = 19.18, p = 3.67 × 10-39; OR = 4.73, p = 2 × 10-10; OR = 2.3, p = 7.49 × 10-9, respectively). These genes have been previously associated with ALS. Additionally, a significant novel control enriched gene, ALKBH3 (p = 4.88 × 10-7), was protective for ALS in this model. An intolerant domain-based collapsing model showed a significant improvement in identifying regions in TARDBP that associated with ALS (OR = 10.08, p = 3.62 × 10-16). Our PLS protein truncating variant collapsing analysis demonstrated significant case enrichment in ANTXR2 (p = 8.38 × 10-6). CONCLUSIONS In a large multi-ethnic cohort of 6,970 ALS patients, collapsing analyses validated known ALS genes and identified a novel potentially protective gene, ALKBH3. A first-ever analysis in 166 patients with PLS found a candidate association with loss-of-function mutations in ANTXR2.
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Affiliation(s)
- Tess D Pottinger
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, USA.
- Department of Internal Medicine, Columbia University Irving Medical Center, New York, NY, USA.
- Division of General Medicine, Department of Medicine, 622 West 168 , New York, NY, 10032, USA.
| | - Joshua E Motelow
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - Gundula Povysil
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | | | - Zhong Ren
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Hemali Phatnani
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Center for Motor Neuron Biology and Disease, Columbia University Irving Medical Center, New York, NY, USA
- New York Genome Center, New York, NY, USA
| | - Timothy J Aitman
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, Scotland, UK
| | | | - Hiroshi Mitsumoto
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - David B Goldstein
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Matthew B Harms
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Center for Motor Neuron Biology and Disease, Columbia University Irving Medical Center, New York, NY, USA
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3
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Mukhopadhyay S, Dixit P, Khanom N, Sanghera G, McGurk KA. The Genetic Factors Influencing Cardiomyopathies and Heart Failure across the Allele Frequency Spectrum. J Cardiovasc Transl Res 2024:10.1007/s12265-024-10520-y. [PMID: 38771459 DOI: 10.1007/s12265-024-10520-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 05/03/2024] [Indexed: 05/22/2024]
Abstract
Heart failure (HF) remains a major cause of mortality and morbidity worldwide. Understanding the genetic basis of HF allows for the development of disease-modifying therapies, more appropriate risk stratification, and personalised management of patients. The advent of next-generation sequencing has enabled genome-wide association studies; moving beyond rare variants identified in a Mendelian fashion and detecting common DNA variants associated with disease. We summarise the latest GWAS and rare variant data on mixed and refined HF aetiologies, and cardiomyopathies. We describe the recent understanding of the functional impact of titin variants and highlight FHOD3 as a novel cardiomyopathy-associated gene. We describe future directions of research in this field and how genetic data can be leveraged to improve the care of patients with HF.
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Affiliation(s)
- Srinjay Mukhopadhyay
- National Heart and Lung Institute, Imperial College London, LMS Building, Hammersmith Campus, London, UK
- School of Medicine, Cardiff University, Wales, UK
| | - Prithvi Dixit
- National Heart and Lung Institute, Imperial College London, LMS Building, Hammersmith Campus, London, UK
| | - Najiyah Khanom
- National Heart and Lung Institute, Imperial College London, LMS Building, Hammersmith Campus, London, UK
| | - Gianluca Sanghera
- National Heart and Lung Institute, Imperial College London, LMS Building, Hammersmith Campus, London, UK
| | - Kathryn A McGurk
- National Heart and Lung Institute, Imperial College London, LMS Building, Hammersmith Campus, London, UK.
- MRC Laboratory of Medical Sciences, Imperial College London, London, UK.
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4
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Jones RE, Hammersley DJ, Zheng S, McGurk KA, de Marvao A, Theotokis PI, Owen R, Tayal U, Rea G, Hatipoglu S, Buchan RJ, Mach L, Curran L, Lota AS, Simard F, Reddy RK, Talukder S, Yoon WY, Vazir A, Pennell DJ, O'Regan DP, Baksi AJ, Halliday BP, Ware JS, Prasad SK. Assessing the association between genetic and phenotypic features of dilated cardiomyopathy and outcome in patients with coronary artery disease. Eur J Heart Fail 2024; 26:46-55. [PMID: 37702310 PMCID: PMC11216513 DOI: 10.1002/ejhf.3033] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 08/17/2023] [Accepted: 09/11/2023] [Indexed: 09/14/2023] Open
Abstract
AIMS To examine the relevance of genetic and cardiovascular magnetic resonance (CMR) features of dilated cardiomyopathy (DCM) in individuals with coronary artery disease (CAD). METHODS AND RESULTS This study includes two cohorts. First, individuals with CAD recruited into the UK Biobank (UKB) were evaluated. Second, patients with CAD referred to a tertiary centre for evaluation with late gadolinium enhancement (LGE)-CMR were recruited (London cohort); patients underwent genetic sequencing as part of the research protocol and long-term follow-up. From 31 154 individuals with CAD recruited to UKB, rare pathogenic variants in DCM genes were associated with increased risk of death or major adverse cardiac events (hazard ratio 1.57, 95% confidence interval [CI] 1.22-2.01, p < 0.001). Of 1619 individuals with CAD included from the UKB CMR substudy, participants with a rare variant in a DCM-associated gene had lower left ventricular ejection fraction (LVEF) compared to genotype negative individuals (mean 47 ± 10% vs. 57 ± 8%, p < 0.001). Of 453 patients in the London cohort, 63 (14%) had non-infarct pattern LGE (NI-LGE) on CMR. Patients with NI-LGE had lower LVEF (mean 38 ± 18% vs. 48 ± 16%, p < 0.001) compared to patients without NI-LGE, with no significant difference in the burden of rare protein altering variants in DCM-associated genes between groups (9.5% vs. 6.7%, odds ratio 1.5, 95% CI 0.4-4.3, p = 0.4). NI-LGE was not independently associated with adverse clinical outcomes. CONCLUSION Rare pathogenic variants in DCM-associated genes impact left ventricular remodelling and outcomes in stable CAD. NI-LGE is associated with adverse remodelling but is not an independent predictor of outcome and had no rare genetic basis in our study.
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5
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Pottinger TD, Motelow JE, Povysil G, Moreno CAM, Ren Z, Phatnani H, Aitman TJ, Santoyo-Lopez J, Mitsumoto H, Goldstein DB, Harms MB. Rare variant analyses validate known ALS genes in a multi-ethnic population and identifies ANTXR2 as a candidate in PLS. RESEARCH SQUARE 2023:rs.3.rs-3721598. [PMID: 38196621 PMCID: PMC10775375 DOI: 10.21203/rs.3.rs-3721598/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Background Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting over 30,000 people in the United States. It is characterized by the progressive decline of the nervous system that leads to the weakening of muscles which impacts physical function. Approximately, 15% of individuals diagnosed with ALS have a known genetic variant that contributes to their disease. As therapies that slow or prevent symptoms, such as antisense oligonucleotides, continue to develop, it is important to discover novel genes that could be targets for treatment. Additionally, as cohorts continue to grow, performing analyses in ALS subtypes, such as primary lateral sclerosis (PLS), becomes possible due to an increase in power. These analyses could highlight novel pathways in disease manifestation. Methods Building on our previous discoveries using rare variant association analyses, we conducted rare variant burden testing on a substantially larger cohort of 6,970 ALS patients from a large multi-ethnic cohort as well as 166 PLS patients, and 22,524 controls. We used intolerant domain percentiles based on sub-region Residual Variation Intolerance Score (subRVIS) that have been described previously in conjunction with gene based collapsing approaches to conduct burden testing to identify genes that associate with ALS and PLS. Results A gene based collapsing model showed significant associations with SOD1, TARDBP, and TBK1 (OR=19.18, p = 3.67 × 10-39; OR=4.73, p = 2 × 10-10; OR=2.3, p = 7.49 × 10-9, respectively). These genes have been previously associated with ALS. Additionally, a significant novel control enriched gene, ALKBH3 (p = 4.88 × 10-7), was protective for ALS in this model. An intolerant domain based collapsing model showed a significant improvement in identifying regions in TARDBP that associated with ALS (OR=10.08, p = 3.62 × 10-16). Our PLS protein truncating variant collapsing analysis demonstrated significant case enrichment in ANTXR2 (p=8.38 × 10-6). Conclusions In a large multi-ethnic cohort of 6,970 ALS patients, rare variant burden testing validated known ALS genes and identified a novel potentially protective gene, ALKBH3. A first-ever analysis in 166 patients with PLS found a candidate association with loss-of-function mutations in ANTXR2.
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Affiliation(s)
- Tess D. Pottinger
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
- Department of Internal Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Joshua E. Motelow
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Gundula Povysil
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | | | - Zhong Ren
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Hemali Phatnani
- Department of Neurology, Columbia University Irving Medical Center, New York, New York, United States of America
- Center for Motor Neuron Biology and Disease, Columbia University Irving Medical Center, New York, New York, United States of America
- New York Genome Center, New York, New York, United States of America
| | | | - Timothy J. Aitman
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, Scotland
| | | | | | - Hiroshi Mitsumoto
- Department of Neurology, Columbia University Irving Medical Center, New York, New York, United States of America
| | | | - David B. Goldstein
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Matthew B. Harms
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
- Department of Neurology, Columbia University Irving Medical Center, New York, New York, United States of America
- Center for Motor Neuron Biology and Disease, Columbia University Irving Medical Center, New York, New York, United States of America
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6
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Pottinger TD, Motelow JE, Povysil G, Moreno CAM, Ren Z, Phatnani H, Aitman TJ, Santoyo-Lopez J, Mitsumoto H, Goldstein DB, Harms MB. Rare variant analyses validate known ALS genes in a multi-ethnic population and identifies ANTXR2 as a candidate in PLS. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.30.23296353. [PMID: 37873269 PMCID: PMC10593055 DOI: 10.1101/2023.09.30.23296353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Background Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting over 30,000 people in the United States. It is characterized by the progressive decline of the nervous system that leads to the weakening of muscles which impacts physical function. Approximately, 15% of individuals diagnosed with ALS have a known genetic variant that contributes to their disease. As therapies that slow or prevent symptoms, such as antisense oligonucleotides, continue to develop, it is important to discover novel genes that could be targets for treatment. Additionally, as cohorts continue to grow, performing analyses in ALS subtypes, such as primary lateral sclerosis (PLS), becomes possible due to an increase in power. These analyses could highlight novel pathways in disease manifestation. Methods Building on our previous discoveries using rare variant association analyses, we conducted rare variant burden testing on a substantially larger cohort of 6,970 ALS patients from a large multi-ethnic cohort as well as 166 PLS patients, and 22,524 controls. We used intolerant domain percentiles based on sub-region Residual Variation Intolerance Score (subRVIS) that have been described previously in conjunction with gene based collapsing approaches to conduct burden testing to identify genes that associate with ALS and PLS. Results A gene based collapsing model showed significant associations with SOD1, TARDBP, and TBK1 (OR=19.18, p = 3.67 × 10-39; OR=4.73, p = 2 × 10-10; OR=2.3, p = 7.49 × 10-9, respectively). These genes have been previously associated with ALS. Additionally, a significant novel control enriched gene, ALKBH3 (p = 4.88 × 10-7), was protective for ALS in this model. An intolerant domain based collapsing model showed a significant improvement in identifying regions in TARDBP that associated with ALS (OR=10.08, p = 3.62 × 10-16). Our PLS protein truncating variant collapsing analysis demonstrated significant case enrichment in ANTXR2 (p=8.38 × 10-6). Conclusions In a large multi-ethnic cohort of 6,970 ALS patients, rare variant burden testing validated known ALS genes and identified a novel potentially protective gene, ALKBH3. A first-ever analysis in 166 patients with PLS found a candidate association with loss-of-function mutations in ANTXR2.
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Affiliation(s)
- Tess D. Pottinger
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
- Department of Internal Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Joshua E. Motelow
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Gundula Povysil
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | | | - Zhong Ren
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Hemali Phatnani
- Department of Neurology, Columbia University Irving Medical Center, New York, New York, United States of America
- Center for Motor Neuron Biology and Disease, Columbia University Irving Medical Center, New York, New York, United States of America
- New York Genome Center, New York, New York, United States of America
| | | | - Timothy J. Aitman
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, Scotland
| | | | | | - Hiroshi Mitsumoto
- Department of Neurology, Columbia University Irving Medical Center, New York, New York, United States of America
| | | | | | | | - David B. Goldstein
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Matthew B. Harms
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
- Department of Neurology, Columbia University Irving Medical Center, New York, New York, United States of America
- Center for Motor Neuron Biology and Disease, Columbia University Irving Medical Center, New York, New York, United States of America
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7
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Lee DSM, Cardone KM, Zhang DY, Abramowitz S, DePaolo JS, Aragam KG, Biddinger K, Conery M, Dilitikas O, Hoffman-Andrews L, Judy RL, Khan A, Kulo I, Puckelwartz MJ, Reza N, Satterfield BA, Singhal P, Arany ZP, Cappola TP, Carruth E, Day SM, Do R, Haggarty CM, Joseph J, McNally E, Nadkarni G, Owens AT, Rader DJ, Ritchie MD, Sun Y, Voight BF, Levin MG, Damrauer SM. Common- and rare-variant genetic architecture of heart failure across the allele frequency spectrum. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.16.23292724. [PMID: 37503172 PMCID: PMC10371173 DOI: 10.1101/2023.07.16.23292724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Heart failure (HF) is a complex trait, influenced by environmental and genetic factors, that affects over 30 million individuals worldwide. Historically, the genetics of HF have been studied in Mendelian forms of disease, where rare genetic variants have been linked to familial cardiomyopathies. More recently, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with risk of HF. However, the relative importance of genetic variants across the allele-frequency spectrum remains incompletely characterized. Here, we report the results of common- and rare-variant association studies of all-cause heart failure, applying recently developed methods to quantify the heritability of HF attributable to different classes of genetic variation. We combine GWAS data across multiple populations including 207,346 individuals with HF and 2,151,210 without, identifying 176 risk loci at genome-wide significance (p < 5×10-8). Signals at newly identified common-variant loci include coding variants in Mendelian cardiomyopathy genes (MYBPC3, BAG3), as well as regulators of lipoprotein (LPL) and glucose metabolism (GIPR, GLP1R), and are enriched in cardiac, muscle, nerve, and vascular tissues, as well as myocyte and adipocyte cell types. Gene burden studies across three biobanks (PMBB, UKB, AOU) including 27,208 individuals with HF and 349,126 without uncover exome-wide significant (p < 3.15×10-6) associations for HF and rare predicted loss-of-function (pLoF) variants in TTN, MYBPC3, FLNC, and BAG3. Total burden heritability of rare coding variants (2.2%, 95% CI 0.99-3.5%) is highly concentrated in a small set of Mendelian cardiomyopathy genes, and is lower than heritability attributable to common variants (4.3%, 95% CI 3.9-4.7%) which is more diffusely spread throughout the genome. Finally, we demonstrate that common-variant background, in the form of a polygenic risk score (PRS), significantly modifies the risk of HF among carriers of pathogenic truncating variants in the Mendelian cardiomyopathy gene TTN. These findings suggest a significant polygenic component to HF exists that is not captured by current clinical genetic testing.
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Affiliation(s)
- David S M Lee
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Katie M Cardone
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - David Y Zhang
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Sarah Abramowitz
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - John S DePaolo
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Krishna G Aragam
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Kiran Biddinger
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Mitchell Conery
- Genomics and Computational Biology Graduate Group, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Ozan Dilitikas
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Lily Hoffman-Andrews
- Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Renae L Judy
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
| | - Iftikhar Kulo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Megan J Puckelwartz
- Department of Pharmacology, Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Nosheen Reza
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | | | - Pankhuri Singhal
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Zoltan P Arany
- Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Cardiovascular Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Thomas P Cappola
- Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Eric Carruth
- Department of Translational Data Science and Informatics, Geisinger, Danville, PA
| | - Sharlene M Day
- Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Cardiovascular Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Ron Do
- The Charles Bronfman Institute for Personalized Medicine, Mount Sinai Icahn School of Medicine, New York, NY
- Biome Phenomics Center, Mount Sinai Icahn School of Medicine, New York, NY
- Department of Genetics and Genomic Sciences, Mount Sinai Icahn School of Medicine, New York, NY
| | | | - Jacob Joseph
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Elizabeth McNally
- Center for Genetic Medicine, Bluhm Cardiovascular Institute, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Girish Nadkarni
- Division of Nephrology, Department of Medicine, Mount Sinai Icahn School of Medicine, New York, NY
| | - Anjali T Owens
- Cardiovascular Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Daniel J Rader
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Division of Translational Medicine and Human Genetics, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Yan Sun
- Deparment of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA
| | - Benjamin F Voight
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA
| | - Michael G Levin
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA
| | - Scott M Damrauer
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Cardiovascular Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA
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8
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Bozkurt B, Ahmad T, Alexander KM, Baker WL, Bosak K, Breathett K, Fonarow GC, Heidenreich P, Ho JE, Hsich E, Ibrahim NE, Jones LM, Khan SS, Khazanie P, Koelling T, Krumholz HM, Khush KK, Lee C, Morris AA, Page RL, Pandey A, Piano MR, Stehlik J, Stevenson LW, Teerlink JR, Vaduganathan M, Ziaeian B. Heart Failure Epidemiology and Outcomes Statistics: A Report of the Heart Failure Society of America. J Card Fail 2023; 29:1412-1451. [PMID: 37797885 PMCID: PMC10864030 DOI: 10.1016/j.cardfail.2023.07.006] [Citation(s) in RCA: 85] [Impact Index Per Article: 85.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/07/2023]
Affiliation(s)
- Biykem Bozkurt
- Winters Center for Heart Failure, Cardiology, Baylor College of Medicine, Houston, Texas.
| | - Tariq Ahmad
- Heart Failure Program Yale School of Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Kevin M Alexander
- Cardiovascular Medicine, Stanford University, Stanford University School of Medicine, Stanford, California
| | | | - Kelly Bosak
- KU Medical Center, School Of Nursing, Kansas City, Kansas
| | - Khadijah Breathett
- Division of Cardiology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Gregg C Fonarow
- Division of Cardiology, University of California Los Angeles, Los Angeles, California
| | - Paul Heidenreich
- Cardiovascular Medicine, Stanford University, Stanford University School of Medicine, Stanford, California
| | - Jennifer E Ho
- Advanced Heart Failure and Transplant Cardiology, Beth Israel Deaconess, Boston, Massachusetts
| | - Eileen Hsich
- Cardiovascular Medicine, Cleveland Clinic, Cleveland, Ohio
| | - Nasrien E Ibrahim
- Advanced Heart Failure and Transplant, Cardiovascular Medicine, Brigham and Women's Hospital, Boston, MA
| | - Lenette M Jones
- Department of Health Behavior and Biological Sciences, University of Michigan, School of Nursing, Ann Arbor, Michigan
| | - Sadiya S Khan
- Northwestern University, Cardiology Feinberg School of Medicine, Chicago, Illinois
| | - Prateeti Khazanie
- Advanced Heart Failure and Transplant Cardiology, UC Health, Aurora, Colorado
| | - Todd Koelling
- Frankel Cardiovascular Center. University of Michigan, Ann Arbor, Michigan
| | - Harlan M Krumholz
- Heart Failure Program Yale School of Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Kiran K Khush
- Cardiovascular Medicine, Stanford University, Stanford University School of Medicine, Stanford, California
| | - Christopher Lee
- Boston College William F. Connell School of Nursing, Boston, Massachusetts
| | - Alanna A Morris
- Division of Cardiology, Emory School of Medicine, Atlanta, Georgia
| | - Robert L Page
- Departments of Clinical Pharmacy and Physical Medicine, University of Colorado, Aurora, Colorado
| | - Ambarish Pandey
- Cardiology, Department of Medicine, UT Southwestern Medical Center, Dallas, Texas
| | | | - Josef Stehlik
- Advanced Heart Failure Section, Cardiology, University of Utah School of Medicine, Salt Lake City, Utah
| | | | - John R Teerlink
- Cardiology University of California San Francisco (UCSF), San Francisco, California
| | - Muthiah Vaduganathan
- Cardiovascular Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Boback Ziaeian
- Division of Cardiology, University of California Los Angeles, Los Angeles, California
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9
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Sinagra G, Gigli M, Dal Ferro M. Heart failure with reduced ejection fraction and monogenic dilated cardiomyopathy: Distinct diseases? Insights from randomized controlled trials. Eur J Heart Fail 2023; 25:1267-1269. [PMID: 37349858 DOI: 10.1002/ejhf.2943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Accepted: 06/18/2023] [Indexed: 06/24/2023] Open
Affiliation(s)
- Gianfranco Sinagra
- Cardiothoracovascular Department, Azienda Sanitaria Universitaria Giuliano Isontina (ASUGI), University of Trieste, Trieste, Italy
- European Reference Network for rare, low-prevalence, or complex diseases of the Heart (ERN GUARD-Heart)
| | - Marta Gigli
- Cardiothoracovascular Department, Azienda Sanitaria Universitaria Giuliano Isontina (ASUGI), University of Trieste, Trieste, Italy
- European Reference Network for rare, low-prevalence, or complex diseases of the Heart (ERN GUARD-Heart)
| | - Matteo Dal Ferro
- Cardiothoracovascular Department, Azienda Sanitaria Universitaria Giuliano Isontina (ASUGI), University of Trieste, Trieste, Italy
- European Reference Network for rare, low-prevalence, or complex diseases of the Heart (ERN GUARD-Heart)
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10
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Barat A, Chen CW, Patel-Murray N, McMurray JJV, Packer M, Solomon SD, Desai AS, Rouleau JL, Zile MR, Attari Z, Zhang C, Xu H, Hartman N, Hon C, Healey M, Chutkow W, O'Donnell CJ, Jacob J, Lefkowitz M, Mendelson MM, Wandel S, Yates D, Gimpelewicz C. Clinical characteristics of heart failure with reduced ejection fraction patients with rare pathogenic variants in dilated cardiomyopathy-associated genes: A subgroup analysis of the PARADIGM-HF trial. Eur J Heart Fail 2023; 25:1256-1266. [PMID: 37191081 DOI: 10.1002/ejhf.2886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 04/18/2023] [Accepted: 05/08/2023] [Indexed: 05/17/2023] Open
Abstract
AIMS To evaluate the prevalence of pathogenic variants in genes associated with dilated cardiomyopathy (DCM) in a clinical trial population with heart failure and reduced ejection fraction (HFrEF) and describe the baseline characteristics by variant carrier status. METHODS AND RESULTS This was a post hoc analysis of the Phase 3 PARADIGM-HF trial. Forty-four genes, divided into three tiers, based on definitive, moderate or limited evidence of association with DCM, were assessed for rare predicted loss-of-function (pLoF) variants, which were prioritized using ClinVar annotations, measures of gene transcriptional output and evolutionary constraint, and pLoF confidence predictions. Prevalence was reported for pLoF variant carriers based on DCM-associated gene tiers. Clinical features were compared between carriers and non-carriers. Of the 1412 HFrEF participants with whole-exome sequence data, 68 (4.8%) had at least one pLoF variant in the 8 tier-1 genes (definitive/strong association with DCM), with Titin being most commonly affected. The prevalence increased to 7.5% when considering all 44 genes. Among patients with idiopathic aetiology, 10.0% (23/229) had tier-1 variants only and 12.6% (29/229) had tier-1, -2 or -3 variants. Compared to non-carriers, tier-1 carriers were younger (4 years; adjusted p-value [padj ] = 4 × 10-3 ), leaner (27.8 kg/m2 vs. 29.4 kg/m2 ; padj = 3.2 × 10-3 ), had lower ejection fraction (27.3% vs. 29.8%; padj = 5.8 × 10-3 ), and less likely to have ischaemic aetiology (37.3% vs. 67.4%; padj = 4 × 10-4 ). CONCLUSION Deleterious pLoF variants in genes with definitive/strong association with DCM were identified in ∼5% of HFrEF patients from a PARADIGM-HF trial subset, who were younger, had lower ejection fraction and were less likely to have had an ischaemic aetiology.
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Affiliation(s)
- Ana Barat
- Novartis Ireland Ltd, Dublin, Ireland
| | - Chien-Wei Chen
- Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA
| | | | - John J V McMurray
- University of Glasgow, BHF Cardiovascular Research Centre, Glasgow, UK
| | - Milton Packer
- Baylor University Medical Center, Baylor Heart and Vascular Institute, Dallas, TX, USA
| | - Scott D Solomon
- Cardiovascular Division, Brigham and Women's Hospital, Boston, MA, USA
| | - Akshay S Desai
- Cardiovascular Division, Brigham and Women's Hospital, Boston, MA, USA
| | - Jean L Rouleau
- Institut de Cardiologie de Montréal, Université de Montréal, Montreal, Quebec, Canada
| | - Michael R Zile
- Medical University of South Carolina, Charleston, SC, USA
- Ralph H. Johnson Department of Veterans Affairs Medical Center, Charleston, SC, USA
| | - Zenab Attari
- Global Development Operations, Novartis, Hyderabad, India
| | - Cong Zhang
- Novartis Institutes for Biomedical Research, Shanghai, China
| | - Huilei Xu
- Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | | | - Claudia Hon
- Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | - Margaret Healey
- Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | - William Chutkow
- Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | | | - Jaison Jacob
- Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | | | | | | | - Denise Yates
- Novartis Institutes for Biomedical Research, Cambridge, MA, USA
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11
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Elliott MD, Marasa M, Cocchi E, Vena N, Zhang JY, Khan A, Krishna Murthy S, Bheda S, Milo Rasouly H, Povysil G, Kiryluk K, Gharavi AG. Clinical and Genetic Characteristics of CKD Patients with High-Risk APOL1 Genotypes. J Am Soc Nephrol 2023; 34:909-919. [PMID: 36758113 PMCID: PMC10125632 DOI: 10.1681/asn.0000000000000094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 01/04/2023] [Indexed: 02/11/2023] Open
Abstract
SIGNIFICANCE STATEMENT APOL1 high-risk genotypes confer a significant risk of kidney disease, but variability in patient outcomes suggests the presence of modifiers of the APOL1 effect. We show that a diverse population of CKD patients with high-risk APOL1 genotypes have an increased lifetime risk of kidney failure and higher eGFR decline rates, with a graded risk among specific high-risk genotypes. CKD patients with high-risk APOL1 genotypes have a lower diagnostic yield for monogenic kidney disease. Exome sequencing revealed enrichment of rare missense variants within the inflammasome pathway modifying the effect of APOL1 risk genotypes, which may explain some clinical heterogeneity. BACKGROUND APOL1 genotype has significant effects on kidney disease development and progression that vary among specific causes of kidney disease, suggesting the presence of effect modifiers. METHODS We assessed the risk of kidney failure and the eGFR decline rate in patients with CKD carrying high-risk ( N =239) and genetically matched low-risk ( N =1187) APOL1 genotypes. Exome sequencing revealed monogenic kidney diseases. Exome-wide association studies and gene-based and gene set-based collapsing analyses evaluated genetic modifiers of the effect of APOL1 genotype on CKD. RESULTS Compared with genetic ancestry-matched patients with CKD with low-risk APOL1 genotypes, those with high-risk APOL1 genotypes had a higher risk of kidney failure (Hazard Ratio [HR]=1.58), a higher decline in eGFR (6.55 versus 3.63 ml/min/1.73 m 2 /yr), and were younger at time of kidney failure (45.1 versus 53.6 years), with the G1/G1 genotype demonstrating the highest risk. The rate for monogenic kidney disorders was lower among patients with CKD with high-risk APOL1 genotypes (2.5%) compared with those with low-risk genotypes (6.7%). Gene set analysis identified an enrichment of rare missense variants in the inflammasome pathway in individuals with high-risk APOL1 genotypes and CKD (odds ratio=1.90). CONCLUSIONS In this genetically matched cohort, high-risk APOL1 genotypes were associated with an increased risk of kidney failure and eGFR decline rate, with a graded risk between specific high-risk genotypes and a lower rate of monogenic kidney disease. Rare missense variants in the inflammasome pathway may act as genetic modifiers of APOL1 effect on kidney disease.
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Affiliation(s)
- Mark D. Elliott
- Division of Nephrology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
- Department of Medicine, Center for Precision Medicine and Genomics, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
- Columbia University Vagelos College of Physicians and Surgeons, Institute for Genomic Medicine, New York, NY
- Division of Nephrology, Department of Medicine, University of Calgary, Calgary, Canada
| | - Maddalena Marasa
- Division of Nephrology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
- Department of Medicine, Center for Precision Medicine and Genomics, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
| | - Enrico Cocchi
- Division of Nephrology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
- Department of Medicine, Center for Precision Medicine and Genomics, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
- Department of Pediatrics, Universita’ degli Studi di Torino, Torino Italy
| | - Natalie Vena
- Department of Medicine, Center for Precision Medicine and Genomics, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
- Columbia University Vagelos College of Physicians and Surgeons, Institute for Genomic Medicine, New York, NY
| | - Jun Y. Zhang
- Division of Nephrology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
- Department of Medicine, Center for Precision Medicine and Genomics, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
| | - Sarath Krishna Murthy
- Department of Medicine, Center for Precision Medicine and Genomics, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
| | - Shiraz Bheda
- Department of Medicine, Center for Precision Medicine and Genomics, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
| | - Hila Milo Rasouly
- Division of Nephrology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
- Department of Medicine, Center for Precision Medicine and Genomics, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
| | - Gundula Povysil
- Columbia University Vagelos College of Physicians and Surgeons, Institute for Genomic Medicine, New York, NY
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
- Department of Medicine, Center for Precision Medicine and Genomics, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
- Columbia University Vagelos College of Physicians and Surgeons, Institute for Genomic Medicine, New York, NY
| | - Ali G. Gharavi
- Division of Nephrology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
- Department of Medicine, Center for Precision Medicine and Genomics, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
- Columbia University Vagelos College of Physicians and Surgeons, Institute for Genomic Medicine, New York, NY
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12
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Masri A, Reza N. Genetic Testing for Cardiomyopathies in Japan: Embarking on a Journey of Discovery. J Card Fail 2023; 29:815-817. [PMID: 37169423 DOI: 10.1016/j.cardfail.2023.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 03/07/2023] [Indexed: 05/13/2023]
Affiliation(s)
- Ahmad Masri
- Division of Cardiovascular Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland
| | - Nosheen Reza
- Division of Cardiovascular Medicine, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.
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13
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Alkelai A, Greenbaum L, Shohat S, Povysil G, Malakar A, Ren Z, Motelow JE, Schechter T, Draiman B, Chitrit-Raveh E, Hughes D, Jobanputra V, Shifman S, Goldstein DB, Kohn Y. Genetic insights into childhood-onset schizophrenia: The yield of clinical exome sequencing. Schizophr Res 2023; 252:138-145. [PMID: 36645932 DOI: 10.1016/j.schres.2022.12.033] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 12/19/2022] [Accepted: 12/26/2022] [Indexed: 01/15/2023]
Abstract
Childhood-onset schizophrenia (COS) is a rare form of schizophrenia with an onset prior to 13 years of age. Although genetic factors play a role in COS etiology, only a few causal variants have been reported to date. This study presents a diagnostic exome sequencing (ES) in 37 Israeli Jewish families with a proband diagnosed with COS. By implementing a trio/duo ES approach and applying a well-established diagnostic pipeline, we detected clinically significant variants in 7 probands (19 %). These single nucleotide variants and indels were mostly inherited. The implicated genes were ANKRD11, GRIA2, CHD2, CLCN3, CLTC, IGF1R and MICU1. In a secondary analysis that compared COS patients to 4721 healthy controls, we observed that patients had a significant enrichment of rare loss of function (LoF) variants in LoF intolerant genes associated with developmental diseases. Taken together, ES could be considered as a valuable tool in the genetic workup for COS patients.
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Affiliation(s)
- Anna Alkelai
- Institute for Genomic Medicine, Columbia University Medical Center, New York, USA; Regeneron Genetics Center, Tarrytown, NY, USA.
| | - Lior Greenbaum
- The Danek Gertner Institute of Human Genetics, Sheba Medical Center, Tel Hashomer, Israel; The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel; Sackler Faculty of Medicine, Tal Aviv University, Tel Aviv, Israel
| | - Shahar Shohat
- Department of Genetics, The Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Gundula Povysil
- Institute for Genomic Medicine, Columbia University Medical Center, New York, USA
| | - Ayan Malakar
- Institute for Genomic Medicine, Columbia University Medical Center, New York, USA
| | - Zhong Ren
- Institute for Genomic Medicine, Columbia University Medical Center, New York, USA
| | - Joshua E Motelow
- Institute for Genomic Medicine, Columbia University Medical Center, New York, USA; Department of Pediatrics, Division of Critical Care and Hospital Medicine, Columbia University Irving Medical Center, New York-Presbyterian Morgan Stanley Children's Hospital of New York, New York, NY, USA
| | - Tanya Schechter
- Department of Child and Adolescent Psychiatry, Jerusalem Mental Health Center, Eitanim Psychiatric Hospital, Israel
| | - Benjamin Draiman
- Department of Child and Adolescent Psychiatry, Jerusalem Mental Health Center, Eitanim Psychiatric Hospital, Israel
| | - Eti Chitrit-Raveh
- Department of Child and Adolescent Psychiatry, Jerusalem Mental Health Center, Eitanim Psychiatric Hospital, Israel
| | - Daniel Hughes
- Institute for Genomic Medicine, Columbia University Medical Center, New York, USA
| | - Vaidehi Jobanputra
- Department of Pathology and Cell Biology, Columbia University, New York, NY, USA; New York Genome Center, New York, NY, USA
| | - Sagiv Shifman
- Department of Genetics, The Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - David B Goldstein
- Institute for Genomic Medicine, Columbia University Medical Center, New York, USA
| | - Yoav Kohn
- Department of Child and Adolescent Psychiatry, Jerusalem Mental Health Center, Eitanim Psychiatric Hospital, Israel; Hadassah-Hebrew University School of Medicine, Jerusalem, Israel
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14
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Nomura S, Ono M. Precision and genomic medicine for dilated and hypertrophic cardiomyopathy. Front Cardiovasc Med 2023; 10:1137498. [PMID: 36950287 PMCID: PMC10025380 DOI: 10.3389/fcvm.2023.1137498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 02/15/2023] [Indexed: 03/08/2023] Open
Abstract
Cardiomyopathy develops through an interaction of genetic and environmental factors. The clinical manifestations of both dilated cardiomyopathy and hypertrophic cardiomyopathy are diverse, but genetic testing defines the causative genes in about half of cases and can predict clinical prognosis. It has become clear that cardiomyopathy is caused not only by single rare variants but also by combinations of multiple common variants, and genome-wide genetic research is important for accurate disease risk assessment. Single-cell analysis research aimed at understanding the pathophysiology of cardiomyopathy is progressing rapidly, and it is expected that genomic analysis and single-cell molecular profiling will be combined to contribute to more detailed stratification of cardiomyopathy.
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Affiliation(s)
- Seitaro Nomura
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Correspondence: Seitaro Nomura
| | - Minoru Ono
- Department of Cardiac Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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15
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Motelow JE, Lippa NC, Hostyk J, Feldman E, Nelligan M, Ren Z, Alkelai A, Milner JD, Gharavi AG, Tang Y, Goldstein DB, Kernie SG. Risk Variants in the Exomes of Children With Critical Illness. JAMA Netw Open 2022; 5:e2239122. [PMID: 36306130 PMCID: PMC9617179 DOI: 10.1001/jamanetworkopen.2022.39122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
IMPORTANCE Diagnostic genetic testing can lead to changes in management in the pediatric intensive care unit. Genetic risk in children with critical illness but nondiagnostic exome sequencing (ES) has not been explored. OBJECTIVE To assess the association between loss-of-function (LOF) variants and pediatric critical illness. DESIGN, SETTING, AND PARTICIPANTS This genetic association study examined ES first screened for causative variants among 267 children at the Morgan Stanley Children's Hospital of NewYork-Presbyterian, of whom 22 were otherwise healthy with viral respiratory failure; 18 deceased children with bronchiolitis from the Office of the Chief Medical Examiner of New York City, of whom 14 were previously healthy; and 9990 controls from the Institute for Genomic Medicine at Columbia University Irving Medical Center. The ES data were generated between January 1, 2015, and December 31, 2020, and analyzed between January 1, 2017, and September 2, 2022. EXPOSURE Critical illness. MAIN OUTCOMES AND MEASURES Odds ratios and P values for genes and gene-sets enriched for rare LOF variants and the loss-of-function observed/expected upper bound fraction (LOEUF) score at which cases have a significant enrichment. RESULTS This study included 285 children with critical illness (median [range] age, 4.1 [0-18.9] years; 148 [52%] male) and 9990 controls. A total of 228 children (80%) did not receive a genetic diagnosis. After quality control (QC), 231 children harbored excess rare LOF variants in genes with a LOEUF score of 0.680 or less (intolerant genes) (P = 1.0 × 10-5). After QC, 176 children without a diagnosis harbored excess ultrarare LOF variants in intolerant genes but only in those without a known disease association (odds ratio, 1.8; 95% CI, 1.3-2.5). After QC, 25 children with viral respiratory failure harbored excess ultrarare LOF variants in intolerant genes but only in those without a known disease association (odds ratio, 2.8; 95% CI, 1.1-6.6). A total of 114 undiagnosed children were enriched for de novo LOF variants in genes without a known disease association (observed, 14; expected, 6.8; enrichment, 2.05). CONCLUSIONS AND RELEVANCE In this genetic association study, excess LOF variants were observed among critically ill children despite nondiagnostic ES. Variants lay in genes without a known disease association, suggesting future investigation may connect phenotypes to causative genes.
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Affiliation(s)
- Joshua E. Motelow
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
- Division of Critical Care and Hospital Medicine, Department of Pediatrics, Columbia University Irving Medical Center, NewYork-Presbyterian Morgan Stanley Children's Hospital, New York, New York
| | - Natalie C. Lippa
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
| | - Joseph Hostyk
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
| | - Evin Feldman
- Division of Critical Care and Hospital Medicine, Department of Pediatrics, Columbia University Irving Medical Center, NewYork-Presbyterian Morgan Stanley Children's Hospital, New York, New York
| | - Matthew Nelligan
- Division of Critical Care and Hospital Medicine, Department of Pediatrics, Columbia University Irving Medical Center, NewYork-Presbyterian Morgan Stanley Children's Hospital, New York, New York
| | - Zhong Ren
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
| | - Anna Alkelai
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, New York
| | | | - Ali G. Gharavi
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
- Division of Nephrology, Department of Medicine, Columbia University Irving Medical Center, NewYork-Presbyterian, New York, New York
| | - Yingying Tang
- Molecular Genetics Laboratory, New York City Office of Chief Medical Examiner, New York, New York
| | - David B. Goldstein
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
| | - Steven G. Kernie
- Division of Critical Care and Hospital Medicine, Department of Pediatrics, Columbia University Irving Medical Center, NewYork-Presbyterian Morgan Stanley Children's Hospital, New York, New York
- NewYork-Presbyterian Hospital, New York, New York
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16
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Zhao L, Li Q, Kuang Y, Xu P, Sun X, Meng Q, Wang W, Zeng Y, Chen B, Fu J, Dong J, Zhu J, Luo Y, Gu H, Li C, Li C, Wu L, Mao X, Fan H, Liu R, Zhang Z, Li Q, Du J, He L, Jin L, Wang L, Sang Q. Heterozygous loss-of-function variants in LHX8 cause female infertility characterized by oocyte maturation arrest. Genet Med 2022; 24:2274-2284. [PMID: 36029299 DOI: 10.1016/j.gim.2022.07.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 07/21/2022] [Accepted: 07/22/2022] [Indexed: 11/26/2022] Open
Abstract
PURPOSE The genetic causes of oocyte maturation arrest leading to female infertility are largely unknown, and no population-based genetic analysis has been applied in cohorts of patients with infertility. We aimed to identify novel pathogenic genes causing oocyte maturation arrest by using a gene-based burden test. METHODS Through comparison of exome sequencing data from 716 females with infertility characterized by oocyte maturation arrest and 3539 controls, we performed a gene-based burden test and identified a novel pathogenic gene LHX8. Splicing event was evaluated using a minigene assay, expression of LHX8 protein was assessed in HeLa cells, and nuclear subcellular localization was determined in both HeLa cells and mouse oocytes. RESULTS A total of 5 heterozygous loss-of-function LHX8 variants were identified from 6 independent families (c.389+1G>T, c.412C>T [p.Arg138∗], c.282C>A [p.Cys94∗]; c.257dup [p.Tyr86∗]; and c.180del, [p.Ser61Profs∗30]). All the identified variants in LHX8 produced truncated LHX8 protein and resulted in loss of LHX8 nuclear localization in both HeLa cells and mouse oocytes. CONCLUSION By combining genetic evidence and functional evaluations, we identified a novel pathogenic gene LHX8 and established the causative relationship between LHX8 haploinsufficiency and female infertility characterized by oocyte maturation arrest.
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Affiliation(s)
- Lin Zhao
- Institute of Pediatrics, Children's Hospital of Fudan University, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China; NHC Key Lab of Reproduction Regulation, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Fudan University, Shanghai, China
| | - Qun Li
- Institute of Pediatrics, Children's Hospital of Fudan University, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China; Human Phenome Institute, Fudan University, Shanghai, China
| | - Yanping Kuang
- Reproductive Medicine Center, Shanghai Ninth Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Peng Xu
- Hainan Jinghua Hejing Hospital for Reproductive Medicine, Haikou, China
| | - Xiaoxi Sun
- Shanghai Ji Ai Genetics and IVF Institute, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China
| | - Qingxia Meng
- Center for Reproduction and Genetics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Wenjing Wang
- Institute of Pediatrics, Children's Hospital of Fudan University, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China
| | - Yang Zeng
- Institute of Pediatrics, Children's Hospital of Fudan University, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China
| | - Biaobang Chen
- NHC Key Lab of Reproduction Regulation, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Fudan University, Shanghai, China
| | - Jing Fu
- Shanghai Ji Ai Genetics and IVF Institute, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China
| | - Jie Dong
- Institute of Pediatrics, Children's Hospital of Fudan University, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China
| | - Jiawei Zhu
- Center for Reproduction and Genetics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Yuxi Luo
- Institute of Pediatrics, Children's Hospital of Fudan University, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China
| | - Hao Gu
- Institute of Pediatrics, Children's Hospital of Fudan University, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China
| | - Caihong Li
- Shenyang Jinghua Hospital, Liaoning, China
| | - Chunyi Li
- Shenyang Jinghua Hospital, Liaoning, China
| | - Ling Wu
- Reproductive Medicine Center, Shanghai Ninth Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Xiaoyan Mao
- Reproductive Medicine Center, Shanghai Ninth Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Huizhen Fan
- Institute of Pediatrics, Children's Hospital of Fudan University, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China
| | - Ruyi Liu
- Institute of Pediatrics, Children's Hospital of Fudan University, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China
| | - Zhihua Zhang
- Institute of Pediatrics, Children's Hospital of Fudan University, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China
| | - Qiaoli Li
- Institute of Pediatrics, Children's Hospital of Fudan University, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China
| | - Jing Du
- NHC Key Lab of Reproduction Regulation, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Fudan University, Shanghai, China
| | - Lin He
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Lei Wang
- Institute of Pediatrics, Children's Hospital of Fudan University, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China.
| | - Qing Sang
- Institute of Pediatrics, Children's Hospital of Fudan University, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China.
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17
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Heinzel FR, Shah SJ. The future of heart failure with preserved ejection fraction : Deep phenotyping for targeted therapeutics. Herz 2022; 47:308-323. [PMID: 35767073 PMCID: PMC9244058 DOI: 10.1007/s00059-022-05124-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/19/2022] [Indexed: 12/25/2022]
Abstract
Heart failure (HF) with preserved ejection fraction (HFpEF) is a multi-organ, systemic syndrome that involves multiple cardiac and extracardiac pathophysiologic abnormalities. Because HFpEF is a heterogeneous syndrome and resistant to a "one-size-fits-all" approach it has proven to be very difficult to treat. For this reason, several research groups have been working on methods for classifying HFpEF and testing targeted therapeutics for the HFpEF subtypes identified. Apart from conventional classification strategies based on comorbidity, etiology, left ventricular remodeling, and hemodynamic subtypes, researchers have been combining deep phenotyping with innovative analytical strategies (e.g., machine learning) to classify HFpEF into therapeutically homogeneous subtypes over the past few years. Despite the growing excitement for such approaches, there are several potential pitfalls to their use, and there is a pressing need to follow up on data-driven HFpEF subtypes in order to determine their underlying mechanisms and molecular basis. Here we provide a framework for understanding the phenotype-based approach to HFpEF by reviewing (1) the historical context of HFpEF; (2) the current HFpEF paradigm of comorbidity-induced inflammation and endothelial dysfunction; (3) various methods of sub-phenotyping HFpEF; (4) comorbidity-based classification and treatment of HFpEF; (5) machine learning approaches to classifying HFpEF; (6) examples from HFpEF clinical trials; and (7) the future of phenomapping (machine learning and other advanced analytics) for the classification of HFpEF.
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Affiliation(s)
- Frank R Heinzel
- Medizinische Klinik mit Schwerpunkt Kardiologie, Charité - Universitätsmedizin, Campus Virchow-Klinikum, Berlin, Germany.
- Partner Site Berlin, Deutsches Zentrum für Herz-Kreislauf-Forschung eV, Berlin, Germany.
| | - Sanjiv J Shah
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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18
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Carruth ED, Qureshi M, Alsaid A, Kelly MA, Calkins H, Murray B, Tichnell C, Sturm AC, Baras A, Kirchner HL, Fornwalt BK, James CA, Haggerty CM. Loss-of-Function FLNC Variants Are Associated With Arrhythmogenic Cardiomyopathy Phenotypes When Identified Through Exome Sequencing of a General Clinical Population. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2022; 15:e003645. [PMID: 35699965 PMCID: PMC9388603 DOI: 10.1161/circgen.121.003645] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND The FLNC gene has recently garnered attention as a likely cause of arrhythmogenic cardiomyopathy, which is considered an actionable genetic condition. However, the association with disease in an unselected clinical population is unknown. We hypothesized that individuals with loss-of-function variants in FLNC (FLNCLOF) would have increased odds for arrhythmogenic cardiomyopathy-associated phenotypes versus variant-negative controls in the Geisinger MyCode cohort. METHODS We identified rare, putative FLNCLOF among 171 948 individuals with exome sequencing linked to health records. Associations with arrhythmogenic cardiomyopathy phenotypes from available diagnoses and cardiac evaluations were investigated. RESULTS Sixty individuals (0.03%; median age 58 years [47-70 interquartile range], 43% male) harbored 27 unique FLNCLOF. These individuals had significantly increased odds ratios for dilated cardiomyopathy (odds ratio, 4.9 [95% CI, 2.6-7.6]; P<0.001), supraventricular tachycardia (odds ratio, 3.2 [95% CI, 1.1-5.6]; P=0.048), and left-dominant arrhythmogenic cardiomyopathy (odds ratio, 4.2 [95% CI, 1.4-7.9]; P=0.03). Echocardiography revealed reduced left ventricular ejection fraction (52±13% versus 57±9%; P=0.001) associated with FLNCLOF. Overall, at least 9% of FLNCLOF patients demonstrated evidence of penetrant disease. CONCLUSIONS FLNCLOF variants are associated with increased odds of ventricular arrhythmia and dysfunction in an unselected clinical population. These findings support genomic screening of FLNC for actionable secondary findings.
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Affiliation(s)
- Eric D. Carruth
- Dept of Translational Data Science and Informatics, Geisinger, Danville, PA
| | | | - Amro Alsaid
- The Heart Institute, Geisinger, Danville, PA
| | | | - Hugh Calkins
- Dept of Medicine, Division of Cardiology, Johns Hopkins Medical Center, Baltimore, MD
| | - Brittney Murray
- Dept of Medicine, Division of Cardiology, Johns Hopkins Medical Center, Baltimore, MD
| | - Crystal Tichnell
- Dept of Medicine, Division of Cardiology, Johns Hopkins Medical Center, Baltimore, MD
| | - Amy C. Sturm
- The Heart Institute, Geisinger, Danville, PA,Genomic Medicine Institute, Geisinger, Danville, PA
| | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY
| | - H. Lester Kirchner
- Dept of Translational Data Science and Informatics, Geisinger, Danville, PA,Dept of Population Health Sciences, Geisinger, Danville, PA
| | - Brandon K. Fornwalt
- Dept of Translational Data Science and Informatics, Geisinger, Danville, PA,The Heart Institute, Geisinger, Danville, PA,Dept of Radiology, Geisinger, Danville, PA
| | - Cynthia A. James
- Dept of Medicine, Division of Cardiology, Johns Hopkins Medical Center, Baltimore, MD
| | - Christopher M. Haggerty
- Dept of Translational Data Science and Informatics, Geisinger, Danville, PA,The Heart Institute, Geisinger, Danville, PA
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19
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Kucher AN, Sleptcov AA, Nazarenko MS. Genetic Landscape of Dilated Cardiomyopathy. RUSS J GENET+ 2022. [DOI: 10.1134/s1022795422030085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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20
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Winter MJ, Ono Y, Ball JS, Walentinsson A, Michaelsson E, Tochwin A, Scholpp S, Tyler CR, Rees S, Hetheridge MJ, Bohlooly-Y M. A Combined Human in Silico and CRISPR/Cas9-Mediated in Vivo Zebrafish Based Approach to Provide Phenotypic Data for Supporting Early Target Validation. Front Pharmacol 2022; 13:827686. [PMID: 35548346 PMCID: PMC9082939 DOI: 10.3389/fphar.2022.827686] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 02/16/2022] [Indexed: 12/29/2022] Open
Abstract
The clinical heterogeneity of heart failure has challenged our understanding of the underlying genetic mechanisms of this disease. In this respect, large-scale patient DNA sequencing studies have become an invaluable strategy for identifying potential genetic contributing factors. The complex aetiology of heart failure, however, also means that in vivo models are vital to understand the links between genetic perturbations and functional impacts as part of the process for validating potential new drug targets. Traditional approaches (e.g., genetically-modified mice) are optimal for assessing small numbers of genes, but less practical when multiple genes are identified. The zebrafish, in contrast, offers great potential for higher throughput in vivo gene functional assessment to aid target prioritisation, by providing more confidence in target relevance and facilitating gene selection for definitive loss of function studies undertaken in mice. Here we used whole-exome sequencing and bioinformatics on human patient data to identify 3 genes (API5, HSPB7, and LMO2) suggestively associated with heart failure that were also predicted to play a broader role in disease aetiology. The role of these genes in cardiovascular system development and function was then further investigated using in vivo CRISPR/Cas9-mediated gene mutation analysis in zebrafish. We observed multiple impacts in F0 knockout zebrafish embryos (crispants) following effective somatic mutation, including changes in ventricle size, pericardial oedema, and chamber malformation. In the case of lmo2, there was also a significant impact on cardiovascular function as well as an expected reduction in erythropoiesis. The data generated from both the human in silico and zebrafish in vivo assessments undertaken supports further investigation of the potential roles of API5, HSPB7, and LMO2 in human cardiovascular disease. The data presented also supports the use of human in silico genetic variant analysis, in combination with zebrafish crispant phenotyping, as a powerful approach for assessing gene function as part of an integrated multi-level drug target validation strategy.
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Affiliation(s)
- Matthew J Winter
- Biosciences, College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom
| | - Yosuke Ono
- Living Systems Institute, College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom
| | - Jonathan S Ball
- Biosciences, College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom
| | - Anna Walentinsson
- Translational Science and Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Erik Michaelsson
- Early Clinical Development, Research and Early Development, Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Anna Tochwin
- Biosciences, College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom
| | - Steffen Scholpp
- Living Systems Institute, College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom
| | - Charles R Tyler
- Biosciences, College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom
| | - Steve Rees
- Discovery Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom
| | - Malcolm J Hetheridge
- Biosciences, College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom
| | - Mohammad Bohlooly-Y
- Translational Genomics, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
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21
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Alkelai A, Greenbaum L, Docherty AR, Shabalin AA, Povysil G, Malakar A, Hughes D, Delaney SL, Peabody EP, McNamara J, Gelfman S, Baugh EH, Zoghbi AW, Harms MB, Hwang HS, Grossman-Jonish A, Aggarwal V, Heinzen EL, Jobanputra V, Pulver AE, Lerer B, Goldstein DB. The benefit of diagnostic whole genome sequencing in schizophrenia and other psychotic disorders. Mol Psychiatry 2022; 27:1435-1447. [PMID: 34799694 DOI: 10.1038/s41380-021-01383-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 10/25/2021] [Accepted: 10/27/2021] [Indexed: 01/04/2023]
Abstract
Schizophrenia has a multifactorial etiology, involving a polygenic architecture. The potential benefit of whole genome sequencing (WGS) in schizophrenia and other psychotic disorders is not well studied. We investigated the yield of clinical WGS analysis in 251 families with a proband diagnosed with schizophrenia (N = 190), schizoaffective disorder (N = 49), or other conditions involving psychosis (N = 48). Participants were recruited in Israel and USA, mainly of Jewish, Arab, and other European ancestries. Trio (parents and proband) WGS was performed for 228 families (90.8%); in the other families, WGS included parents and at least two affected siblings. In the secondary analyses, we evaluated the contribution of rare variant enrichment in particular gene sets, and calculated polygenic risk score (PRS) for schizophrenia. For the primary outcome, diagnostic rate was 6.4%; we found clinically significant, single nucleotide variants (SNVs) or small insertions or deletions (indels) in 14 probands (5.6%), and copy number variants (CNVs) in 2 (0.8%). Significant enrichment of rare loss-of-function variants was observed in a gene set of top schizophrenia candidate genes in affected individuals, compared with population controls (N = 6,840). The PRS for schizophrenia was significantly increased in the affected individuals group, compared to their unaffected relatives. Last, we were also able to provide pharmacogenomics information based on CYP2D6 genotype data for most participants, and determine their antipsychotic metabolizer status. In conclusion, our findings suggest that WGS may have a role in the setting of both research and genetic counseling for individuals with schizophrenia and other psychotic disorders and their families.
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Affiliation(s)
- Anna Alkelai
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA.
| | - Lior Greenbaum
- The Danek Gertner Institute of Human Genetics, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Anna R Docherty
- Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Andrey A Shabalin
- Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Gundula Povysil
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
| | - Ayan Malakar
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
| | - Daniel Hughes
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
| | - Shannon L Delaney
- New York State Psychiatric Institute, Columbia University, New York City, NY, USA
| | - Emma P Peabody
- Psychology Research Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - James McNamara
- Psychology Research Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - Sahar Gelfman
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
| | - Evan H Baugh
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
| | - Anthony W Zoghbi
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
- New York State Psychiatric Institute, Columbia University, New York City, NY, USA
- New York State Psychiatric Institute, Office of Mental Health, New York, NY, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Matthew B Harms
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Center for Motor Neuron Biology and Disease, Columbia University Irving Medical Center, New York, NY, USA
| | - Hann-Shyan Hwang
- Department of Medicine, National Taiwan University School of Medicine, Taipei, Taiwan
| | - Anat Grossman-Jonish
- The Danek Gertner Institute of Human Genetics, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - Vimla Aggarwal
- Department of Pathology and Cell Biology, Columbia University, New York, NY, USA
| | - Erin L Heinzen
- Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Vaidehi Jobanputra
- Center for Motor Neuron Biology and Disease, Columbia University Irving Medical Center, New York, NY, USA
- New York Genome Center, New York, NY, USA
| | - Ann E Pulver
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Bernard Lerer
- Biological Psychiatry Laboratory, Department of Psychiatry, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - David B Goldstein
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
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22
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Sun Y, Xiao L, Li K, Wang H, Song X, Li Z, Li C, Chen Y, Li S, Huang J, Tan L, Hu D, Yu T, Li R, Wang H, Jin L, Shi L, Marian AJ, Wang DW. Shared Genetic Etiology of Primary Dilated Cardiomyopathy and Ischemic Dilated Cardiomyopathy. Front Cardiovasc Med 2021; 8:752662. [PMID: 37273834 PMCID: PMC10236477 DOI: 10.3389/fcvm.2021.752662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 10/26/2021] [Indexed: 06/06/2023] Open
Abstract
Background: Mutations in genes encoding sarcomere and cytoskeletal proteins are major causes of primary dilated cardiomyopathy (DCM). Likewise, ischemic myocardial injury is a major cause of secondary cardiac remodeling, which, in a subset, is severe and resembles DCM. The latter is referred to as ischemic dilated cardiomyopathy (IDCM). We postulated the presence of pathogenic and likely pathogenic variants (PVs and LPVs, respectively) in genes known to cause primary DCM might predispose the heart to severe cardiac dilatation and dysfunction post myocardial ischemic injury, i.e., IDCM. Methods: We performed whole-exome sequencing in 1,041 patients with primary DCM, 215 patients with IDCM, and 414 healthy controls. Indices of cardiac size and function were similar between those with primary and ischemic DCM. PVs and LPVs, including the truncating variants in 36 genes known to cause primary DCM were identified and compared among the three groups. Results: Pathogenic variants and LPVs were detected in 266 individuals, comprised of 215/1,041 (20.7%) patients with DCM, 27/215 (12.6%) patients with IDCM, and 24/414 (5.8%) control individuals. PVs and LPVs in the TTN gene were the most common and detected in 130/1,041 (12.5%) of patients with DCM, 15/215 (7.0%) of cases with IDCM, and 10/414 (2.4%) control individuals. Of 135 TTNtv, 118 involved exons that were >90% spliced in. These variants were found in 120/1,041 (11.5%) of DCM patients, 6/215 (2.8%) of IDCM cases, and only in 1/414 (0.2%) of the control population (p < 0.001 among the three groups). Conclusions: Pathogenic variants and LPVs in genes known to cause primary DCM are enriched in patients with IDCM, suggesting that such variants function as susceptibility alleles for cardiac dilatation and dysfunction in post myocardial ischemic injury. Thus, IDCM shares a partial genetic etiology with the primary DCM.
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Affiliation(s)
- Yang Sun
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
| | - Lei Xiao
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
| | - Ke Li
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
| | - Hong Wang
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
| | - Xiuli Song
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
| | - Zongzhe Li
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
| | - Chenze Li
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
| | - Yanghui Chen
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
| | - Shiyang Li
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
| | - Jin Huang
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
| | - Lun Tan
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
| | - Dong Hu
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
| | - Ting Yu
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Rui Li
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
| | - Hong Wang
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Li Jin
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
- Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Leming Shi
- Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Ali J. Marian
- Center for Cardiovascular Genetics, Institute of Molecular Medicine and Department of Medicine, University of Texas Health Sciences Center at Houston, Houston, TX, United States
| | - Dao Wen Wang
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Huazhong University of Science and Technology, Wuhan, China
- Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
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23
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Ahmed Z, Zeeshan S, Liang BT. RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients. Hum Genomics 2021; 15:67. [PMID: 34774109 PMCID: PMC8590246 DOI: 10.1186/s40246-021-00367-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 10/31/2021] [Indexed: 01/08/2023] Open
Abstract
Background Heart failure (HF) is one of the most common complications of cardiovascular diseases (CVDs) and among the leading causes of death in the US. Many other CVDs can lead to increased mortality as well. Investigating the genetic epidemiology and susceptibility to CVDs is a central focus of cardiology and biomedical life sciences. Several studies have explored expression of key CVD genes specially in HF, yet new targets and biomarkers for early diagnosis are still missing to support personalized treatment. Lack of gender-specific cardiac biomarker thresholds in men and women may be the reason for CVD underdiagnosis in women, and potentially increased morbidity and mortality as a result, or conversely, an overdiagnosis in men. In this context, it is important to analyze the expression and enrichment of genes with associated phenotypes and disease-causing variants among high-risk CVD populations. Methods We performed RNA sequencing focusing on key CVD genes with a great number of genetic associations to HF. Peripheral blood samples were collected from a broad age range of adult male and female CVD patients. These patients were clinically diagnosed with CVDs and CMS/HCC HF, as well as including cardiomyopathy, hypertension, obesity, diabetes, asthma, high cholesterol, hernia, chronic kidney, joint pain, dizziness and giddiness, osteopenia of multiple sites, chest pain, osteoarthritis, and other diseases. Results We report RNA-seq driven case–control study to analyze patterns of expression in genes and differentiating the pathways, which differ between healthy and diseased patients. Our in-depth gene expression and enrichment analysis of RNA-seq data from patients with mostly HF and other CVDs on differentially expressed genes and CVD annotated genes revealed 4,885 differentially expressed genes (DEGs) and regulation of 41 genes known for HF and 23 genes related to other CVDs, with 15 DEGs as significantly expressed including four genes already known (FLNA, CST3, LGALS3, and HBA1) for HF and CVDs with the enrichment of many pathways. Furthermore, gender and ethnic group specific analysis showed shared and unique genes between the genders, and among different races. Broadening the scope of the results in clinical settings, we have linked the CVD genes with ICD codes. Conclusions Many pathways were found to be enriched, and gender-specific analysis showed shared and unique genes between the genders. Additional testing of these genes may lead to the development of new clinical tools to improve diagnosis and prognosis of CVD patients. Supplementary Information The online version contains supplementary material available at 10.1186/s40246-021-00367-8.
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Affiliation(s)
- Zeeshan Ahmed
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, 112 Paterson Street, New Brunswick, NJ, 08901, USA. .,Department of Medicine, Robert Wood Johnson Medical School, Rutgers Biomedical and Health Sciences, 125 Paterson St, New Brunswick, NJ, USA. .,Department of Genetics and Genome Sciences, UConn Health, 400 Farmington Ave, Farmington, CT, USA. .,Pat and Jim Calhoun Cardiology Center, UConn School of Medicine, University of Connecticut Health Center, 263 Farmington Ave, Farmington, CT, USA.
| | - Saman Zeeshan
- Rutgers Cancer Institute of New Jersey, Rutgers University, 195 Little Albany St, New Brunswick, NJ, USA
| | - Bruce T Liang
- Pat and Jim Calhoun Cardiology Center, UConn School of Medicine, University of Connecticut Health Center, 263 Farmington Ave, Farmington, CT, USA
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24
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Abstract
The number of therapies for heart failure (HF) with reduced ejection fraction has nearly doubled in the past decade. In addition, new therapies for HF caused by hypertrophic and infiltrative disease are emerging rapidly. Indeed, we are on the verge of a new era in HF in which insights into the biology of myocardial disease can be matched to an understanding of the genetic predisposition in an individual patient to inform precision approaches to therapy. In this Review, we summarize the biology of HF, emphasizing the causal relationships between genetic contributors and traditional structure-based remodelling outcomes, and highlight the mechanisms of action of traditional and novel therapeutics. We discuss the latest advances in our understanding of both the Mendelian genetics of cardiomyopathy and the complex genetics of the clinical syndrome presenting as HF. In the phenotypic domain, we discuss applications of machine learning for the subcategorization of HF in ways that might inform rational prescribing of medications. We aim to bridge the gap between the biology of the failing heart, its diverse clinical presentations and the range of medications that we can now use to treat it. We present a roadmap for the future of precision medicine in HF.
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25
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Abstract
Endotyping is an emerging concept in which diseases are classified into distinct subtypes based on underlying molecular mechanisms. Heart failure (HF) is a complex clinical syndrome that encompasses multiple endotypes with differential risks of adverse events, and varying responses to treatment. Identifying these distinct endotypes requires molecular-level investigation involving multi-"omics" approaches, including genomics, transcriptomics, proteomics, and metabolomics. The derivation of these HF endotypes has important implications in promoting individualized treatment and facilitating more targeted selection of patients for clinical trials, as well as in potentially revealing new pathways of disease that may serve as therapeutic targets. One challenge in the integrated analysis of high-throughput omics and detailed clinical data is that it requires the ability to handle "big data", a task for which machine learning is well suited. In particular, unsupervised machine learning has the ability to uncover novel endotypes of disease in an unbiased approach. In this review, we will discuss recent efforts to identify HF endotypes and cover approaches involving proteomics, transcriptomics, and genomics, with a focus on machine-learning methods.
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Affiliation(s)
- Lusha W Liang
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center
| | - Yuichi J Shimada
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center
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26
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Halvorsen M, Samuels J, Wang Y, Greenberg BD, Fyer AJ, McCracken JT, Geller DA, Knowles JA, Zoghbi AW, Pottinger TD, Grados MA, Riddle MA, Bienvenu OJ, Nestadt PS, Krasnow J, Goes FS, Maher B, Nestadt G, Goldstein DB. Exome sequencing in obsessive-compulsive disorder reveals a burden of rare damaging coding variants. Nat Neurosci 2021; 24:1071-1076. [PMID: 34183866 DOI: 10.1038/s41593-021-00876-8] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 05/18/2021] [Indexed: 02/05/2023]
Abstract
Obsessive-compulsive disorder (OCD) affects 1-2% of the population, and, as with other complex neuropsychiatric disorders, it is thought that rare variation contributes to its genetic risk. In this study, we performed exome sequencing in the largest OCD cohort to date (1,313 total cases, consisting of 587 trios, 41 quartets and 644 singletons of affected individuals) and describe contributions to disease risk from rare damaging coding variants. In case-control analyses (n = 1,263/11,580), the most significant single-gene result was observed in SLITRK5 (odds ratio (OR) = 8.8, 95% confidence interval 3.4-22.5, P = 2.3 × 10-6). Across the exome, there was an excess of loss of function (LoF) variation specifically within genes that are LoF-intolerant (OR = 1.33, P = 0.01). In an analysis of trios, we observed an excess of de novo missense predicted damaging variants relative to controls (OR = 1.22, P = 0.02), alongside an excess of de novo LoF mutations in LoF-intolerant genes (OR = 2.55, P = 7.33 × 10-3). These data support a contribution of rare coding variants to OCD genetic risk.
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Affiliation(s)
- Mathew Halvorsen
- Department of Genetics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA
| | - Jack Samuels
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ying Wang
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Benjamin D Greenberg
- Department of Psychiatry and Human Behavior, Brown Medical School, Providence, RI, USA
| | - Abby J Fyer
- New York State Psychiatric Institute, College of Physicians and Surgeons at Columbia University, New York, NY, USA
| | - James T McCracken
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at Los Angeles, Los Angeles, CA, USA
| | - Daniel A Geller
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - James A Knowles
- SUNY Downstate Medical Center College of Medicine, Brooklyn, NY, USA
| | - Anthony W Zoghbi
- New York State Psychiatric Institute, College of Physicians and Surgeons at Columbia University, New York, NY, USA
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
| | - Tess D Pottinger
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
| | - Marco A Grados
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Mark A Riddle
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - O Joseph Bienvenu
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Paul S Nestadt
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Janice Krasnow
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Fernando S Goes
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Brion Maher
- Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Gerald Nestadt
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - David B Goldstein
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA.
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27
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Povysil G, Butler-Laporte G, Shang N, Wang C, Khan A, Alaamery M, Nakanishi T, Zhou S, Forgetta V, Eveleigh RJ, Bourgey M, Aziz N, Jones SJ, Knoppers B, Scherer SW, Strug LJ, Lepage P, Ragoussis J, Bourque G, Alghamdi J, Aljawini N, Albes N, Al-Afghani HM, Alghamdi B, Almutairi MS, Mahmoud ES, Abu-Safieh L, El Bardisy H, Harthi FSA, Alshareef A, Suliman BA, Alqahtani SA, Almalik A, Alrashed MM, Massadeh S, Mooser V, Lathrop M, Fawzy M, Arabi YM, Mbarek H, Saad C, Al-Muftah W, Jung J, Mangul S, Badji R, Thani AA, Ismail SI, Gharavi AG, Abedalthagafi MS, Richards JB, Goldstein DB, Kiryluk K. Rare loss-of-function variants in type I IFN immunity genes are not associated with severe COVID-19. J Clin Invest 2021; 131:147834. [PMID: 34043590 PMCID: PMC8279578 DOI: 10.1172/jci147834] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 05/25/2021] [Indexed: 12/25/2022] Open
Abstract
A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,864 COVID-19 cases (713 with severe and 1,151 with mild disease) and 15,033 ancestry-matched population controls across 4 independent COVID-19 biobanks. We tested whether rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only 1 rare pLOF mutation across these genes among 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We found no evidence of association of rare LOF variants in the 13 candidate genes with severe COVID-19 outcomes.
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Affiliation(s)
- Gundula Povysil
- Institute for Genomic Medicine, Columbia University, New York, New York, USA
| | - Guillaume Butler-Laporte
- Lady Davis Institute for Medical Research, Montréal, Québec, Canada
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montréal, Québec, Canada
| | - Ning Shang
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, New York, USA
| | - Chen Wang
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, New York, USA
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, New York, USA
| | - Manal Alaamery
- Developmental Medicine Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
- Saudi Human Genome Project at King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Tomoko Nakanishi
- Lady Davis Institute for Medical Research, Montréal, Québec, Canada
- Department of Human Genetics, McGill University, Montréal, Québec, Canada
- Kyoto-McGill International Collaborative School in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Sirui Zhou
- Lady Davis Institute for Medical Research, Montréal, Québec, Canada
| | | | - Robert J.M. Eveleigh
- Canadian Centre for Computational Genomics, McGill University, Montréal, Québec, Canada
- McGill Genome Center, McGill University, Montréal, Québec, Canada
| | - Mathieu Bourgey
- Canadian Centre for Computational Genomics, McGill University, Montréal, Québec, Canada
- McGill Genome Center, McGill University, Montréal, Québec, Canada
| | - Naveed Aziz
- Canadian COVID Genomics Network, HostSeq Project, Canada
| | | | | | | | - Lisa J. Strug
- Canadian COVID Genomics Network, HostSeq Project, Canada
| | - Pierre Lepage
- Canadian Centre for Computational Genomics, McGill University, Montréal, Québec, Canada
| | - Jiannis Ragoussis
- Department of Human Genetics, McGill University, Montréal, Québec, Canada
- Canadian Centre for Computational Genomics, McGill University, Montréal, Québec, Canada
| | - Guillaume Bourque
- Department of Human Genetics, McGill University, Montréal, Québec, Canada
- McGill Genome Center, McGill University, Montréal, Québec, Canada
- Canadian Centre for Computational Genomics, McGill University, Montréal, Québec, Canada
| | | | - Nora Aljawini
- KACST-BWH Centre of Excellence for Biomedicine, Joint Centers of Excellence Program, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Nour Albes
- KACST-BWH Centre of Excellence for Biomedicine, Joint Centers of Excellence Program, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Hani M. Al-Afghani
- Laboratory Department, Security Forces Hospital, General Directorate of Medical Services, Ministry of Interior, Makkah, Saudi Arabia
| | - Bader Alghamdi
- Developmental Medicine Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
| | - Mansour S. Almutairi
- Developmental Medicine Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
| | - Ebrahim Sabri Mahmoud
- Ministry of the National Guard Health Affairs, King Abdullah International Medical Research Center and King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
| | - Leen Abu-Safieh
- Genomics Research Department, Saudi Human Genome Project, King Fahad Medical City and King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Hadeel El Bardisy
- Genomics Research Department, Saudi Human Genome Project, King Fahad Medical City and King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Fawz S. Al Harthi
- Genomics Research Department, Saudi Human Genome Project, King Fahad Medical City and King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | | | - Bandar Ali Suliman
- College of Applied Medical Sciences, Taibah University, Madina, Saudi Arabia
| | - Saleh A. Alqahtani
- Liver Transplant Unit, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
- Division of Gastroenterology and Hepatology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Abdulaziz Almalik
- Life Science and Environmental Institute, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - May M. Alrashed
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Salam Massadeh
- Developmental Medicine Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
- Saudi Human Genome Project at King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Vincent Mooser
- Department of Human Genetics, McGill University, Montréal, Québec, Canada
| | - Mark Lathrop
- Department of Human Genetics, McGill University, Montréal, Québec, Canada
- Canadian COVID Genomics Network, HostSeq Project, Canada
- Canadian Centre for Computational Genomics, McGill University, Montréal, Québec, Canada
| | - Mohamed Fawzy
- Genomics Research Department, Saudi Human Genome Project, King Fahad Medical City and King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Yaseen M. Arabi
- Ministry of the National Guard Health Affairs, King Abdullah International Medical Research Center and King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
| | - Hamdi Mbarek
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Chadi Saad
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Wadha Al-Muftah
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Junghyun Jung
- Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, California, USA
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Serghei Mangul
- Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, California, USA
| | - Radja Badji
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Asma Al Thani
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Said I. Ismail
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Ali G. Gharavi
- Institute for Genomic Medicine, Columbia University, New York, New York, USA
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, New York, USA
- Center for Precision Medicine and Genomics, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, New York, USA
| | - Malak S. Abedalthagafi
- Genomics Research Department, Saudi Human Genome Project, King Fahad Medical City and King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - J. Brent Richards
- Lady Davis Institute for Medical Research, Montréal, Québec, Canada
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montréal, Québec, Canada
- Kyoto-McGill International Collaborative School in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Twin Research, King’s College London, London, United Kingdom
| | - David B. Goldstein
- Institute for Genomic Medicine, Columbia University, New York, New York, USA
- Department of Genetics & Development, Columbia University, New York, New York, USA
| | - Krzysztof Kiryluk
- Institute for Genomic Medicine, Columbia University, New York, New York, USA
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, New York, USA
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28
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Sub-genic intolerance, ClinVar, and the epilepsies: A whole-exome sequencing study of 29,165 individuals. Am J Hum Genet 2021; 108:965-982. [PMID: 33932343 DOI: 10.1016/j.ajhg.2021.04.009] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 04/08/2021] [Indexed: 12/23/2022] Open
Abstract
Both mild and severe epilepsies are influenced by variants in the same genes, yet an explanation for the resulting phenotypic variation is unknown. As part of the ongoing Epi25 Collaboration, we performed a whole-exome sequencing analysis of 13,487 epilepsy-affected individuals and 15,678 control individuals. While prior Epi25 studies focused on gene-based collapsing analyses, we asked how the pattern of variation within genes differs by epilepsy type. Specifically, we compared the genetic architectures of severe developmental and epileptic encephalopathies (DEEs) and two generally less severe epilepsies, genetic generalized epilepsy and non-acquired focal epilepsy (NAFE). Our gene-based rare variant collapsing analysis used geographic ancestry-based clustering that included broader ancestries than previously possible and revealed novel associations. Using the missense intolerance ratio (MTR), we found that variants in DEE-affected individuals are in significantly more intolerant genic sub-regions than those in NAFE-affected individuals. Only previously reported pathogenic variants absent in available genomic datasets showed a significant burden in epilepsy-affected individuals compared with control individuals, and the ultra-rare pathogenic variants associated with DEE were located in more intolerant genic sub-regions than variants associated with non-DEE epilepsies. MTR filtering improved the yield of ultra-rare pathogenic variants in affected individuals compared with control individuals. Finally, analysis of variants in genes without a disease association revealed a significant burden of loss-of-function variants in the genes most intolerant to such variation, indicating additional epilepsy-risk genes yet to be discovered. Taken together, our study suggests that genic and sub-genic intolerance are critical characteristics for interpreting the effects of variation in genes that influence epilepsy.
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29
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Abstract
Designated as an emerging epidemic in 1997, heart failure (HF) remains a major clinical and public health problem. This review focuses on the most recent studies identified by searching the Medline database for publications with the subject headings HF, epidemiology, prevalence, incidence, trends between 2010 and present. Publications relevant to epidemiology and population sciences were retained for discussion in this review after reviewing abstracts for relevance to these topics. Studies of the epidemiology of HF over the past decade have improved our understanding of the HF syndrome and of its complexity. Data suggest that the incidence of HF is mostly flat or declining but that the burden of mortality and hospitalization remains mostly unabated despite significant ongoing efforts to treat and manage HF. The evolution of the case mix of HF continues to be characterized by an increasing proportion of cases with preserved ejection fraction, for which established effective treatments are mostly lacking. Major disparities in the occurrence, presentation, and outcome of HF persist particularly among younger Black men and women. These disturbing trends reflect the complexity of the HF syndrome, the insufficient mechanistic understanding of its various manifestations and presentations and the challenges of its management as a chronic disease, often integrated within a context of aging and multimorbidity. Emerging risk factors including omics science offer the promise of discovering new mechanistic pathways that lead to HF. Holistic management approaches must recognize HF as a syndemic and foster the implementation of multidisciplinary approaches to address major contributors to the persisting burden of HF including multimorbidity, aging, and social determinants of health.
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Affiliation(s)
- Véronique L Roger
- Department of Quantitative Health Sciences and Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN. Now at Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health. Véronique L Roger, MD, MPH is now at Chief, Epidemiology and Community Health Branch National Heart, Lung and Blood Institute, National Institutes of Health
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30
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Ren Z, Povysil G, Hostyk JA, Cui H, Bhardwaj N, Goldstein DB. ATAV: a comprehensive platform for population-scale genomic analyses. BMC Bioinformatics 2021; 22:149. [PMID: 33757430 PMCID: PMC7988908 DOI: 10.1186/s12859-021-04071-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 03/14/2021] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND A common approach for sequencing studies is to do joint-calling and store variants of all samples in a single file. If new samples are continually added or controls are re-used for several studies, the cost and time required to perform joint-calling for each analysis can become prohibitive. RESULTS We present ATAV, an analysis platform for large-scale whole-exome and whole-genome sequencing projects. ATAV stores variant and per site coverage data for all samples in a centralized database, which is efficiently queried by ATAV to support diagnostic analyses for trios and singletons, as well as rare-variant collapsing analyses for finding disease associations in complex diseases. Runtime logs ensure full reproducibility and the modularized ATAV framework makes it extensible to continuous development. Besides helping with the identification of disease-causing variants for a range of diseases, ATAV has also enabled the discovery of disease-genes by rare-variant collapsing on datasets containing more than 20,000 samples. Analyses to date have been performed on data of more than 110,000 individuals demonstrating the scalability of the framework. To allow users to easily access variant-level data directly from the database, we provide a web-based interface, the ATAV data browser ( http://atavdb.org/ ). Through this browser, summary-level data for more than 40,000 samples can be queried by the general public representing a mix of cases and controls of diverse ancestries. Users have access to phenotype categories of variant carriers, as well as predicted ancestry, gender, and quality metrics. In contrast to many other platforms, the data browser is able to show data of newly-added samples in real-time and therefore evolves rapidly as more and more samples are sequenced. CONCLUSIONS Through ATAV, users have public access to one of the largest variant databases for patients sequenced at a tertiary care center and can look up any genes or variants of interest. Additionally, since the entire code is freely available on GitHub, ATAV can easily be deployed by other groups that wish to build their own platform, database, and user interface.
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Affiliation(s)
- Zhong Ren
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.
| | - Gundula Povysil
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Joseph A Hostyk
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Hongzhu Cui
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Nitin Bhardwaj
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - David B Goldstein
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
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31
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Rare variant contribution to human disease in 281,104 UK Biobank exomes. Nature 2021; 597:527-532. [PMID: 34375979 PMCID: PMC8458098 DOI: 10.1038/s41586-021-03855-y] [Citation(s) in RCA: 199] [Impact Index Per Article: 66.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 07/28/2021] [Indexed: 02/08/2023]
Abstract
Genome-wide association studies have uncovered thousands of common variants associated with human disease, but the contribution of rare variants to common disease remains relatively unexplored. The UK Biobank contains detailed phenotypic data linked to medical records for approximately 500,000 participants, offering an unprecedented opportunity to evaluate the effect of rare variation on a broad collection of traits1,2. Here we study the relationships between rare protein-coding variants and 17,361 binary and 1,419 quantitative phenotypes using exome sequencing data from 269,171 UK Biobank participants of European ancestry. Gene-based collapsing analyses revealed 1,703 statistically significant gene-phenotype associations for binary traits, with a median odds ratio of 12.4. Furthermore, 83% of these associations were undetectable via single-variant association tests, emphasizing the power of gene-based collapsing analysis in the setting of high allelic heterogeneity. Gene-phenotype associations were also significantly enriched for loss-of-function-mediated traits and approved drug targets. Finally, we performed ancestry-specific and pan-ancestry collapsing analyses using exome sequencing data from 11,933 UK Biobank participants of African, East Asian or South Asian ancestry. Our results highlight a significant contribution of rare variants to common disease. Summary statistics are publicly available through an interactive portal ( http://azphewas.com/ ).
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