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Daas F, Gupta P, Kiblawi F. Multiple vascular anomalies and refractory pericardial effusion in a young patient with Cantu syndrome: a case report and review of the literature. BMC Pediatr 2023; 23:644. [PMID: 38114927 PMCID: PMC10731865 DOI: 10.1186/s12887-023-04446-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 11/28/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND Cantu syndrome is a rare and complex multisystem disorder characterized by hypertrichosis, facial dysmorphism, osteochondroplasia and cardiac abnormalities. With only 150 cases reported worldwide, Cantu syndrome is now gaining wider recognition due to molecular testing and a growing body of literature that further characterizes the syndrome and some of its most important features. Cardiovascular pathology previously described in the literature include cardiomegaly, pericardial effusion, vascular dilation and tortuosity, and other congenital heart defects. However, cardiovascular involvement is highly variable amongst individuals with Cantu syndrome. In some instances, it can be extensive and severe requiring surgical management and long term follow up. CASE PRESENTATION Herein we report a case of a fourteen-year-old female who presented with worsening pericardial effusion of unknown etiology, and echocardiographic findings of concentric left ventricular hypertrophy, a mildly dilated aortic root and ascending aorta. Her medical history was notable for hemoptysis and an episode of pulmonary hemorrhage secondary to multiple aortopulmonary collaterals that were subsequently embolized in early childhood. She was initially managed with Ibuprofen and Colchicine but continued to worsen, and ultimately required a pericardial window for the management of refractory pericardial effusion. Imaging studies obtained on subsequent visits revealed multiple dilated and tortuous blood vessels in the head, neck, chest, and pelvis. A cardiomyopathy molecular studies panel was sent, and a pathogenic variant was identified in the ABCC9 gene, confirming the molecular diagnosis of autosomal dominant Cantu syndrome. CONCLUSIONS Vascular anomalies and significant cardiac involvement are often present in Cantu syndrome, however there are currently no established screening recommendations or surveillance protocols in place. The triad of hypertrichosis, facial dysmorphism, and unexplained cardiovascular involvement in any patient should raise suspicion for Cantu syndrome and warrant further investigation. Initial cardiac evaluation and follow up should be indicated in any patient with a clinical and/or molecular diagnosis of Cantu syndrome. Furthermore, whole body imaging should be utilized to evaluate the extent of vascular involvement and dictate long term monitoring and care.
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Affiliation(s)
- Falastine Daas
- Department of Pediatrics, St. Joseph's University Medical Center, 703 Main Street, Paterson, NJ, 07503, USA.
| | - Punita Gupta
- Department of Pediatrics Division of Genetics, St. Joseph's University Medical Center, 703 Main Street, Paterson, NJ, 07503, USA
| | - Fuad Kiblawi
- Department of Pediatrics Division of Cardiology, St. Joseph's University Medical Center, 703 Main Street, Paterson, NJ, 07503, USA
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Chou E, Pirruccello JP, Ellinor PT, Lindsay ME. Genetics and mechanisms of thoracic aortic disease. Nat Rev Cardiol 2023; 20:168-180. [PMID: 36131050 DOI: 10.1038/s41569-022-00763-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/03/2022] [Indexed: 11/09/2022]
Abstract
Aortic disease has many forms including aortic aneurysm and dissection, aortic coarctation or abnormalities in aortic function, such as loss of aortic distensibility. Genetic analysis in humans is one of the most important experimental approaches in uncovering disease mechanisms, but the relative infrequency of thoracic aortic disease compared with other cardiovascular conditions such as coronary artery disease has hindered large-scale identification of genetic associations. In the past decade, advances in machine learning technology coupled with large imaging datasets from biobank repositories have facilitated a rapid expansion in our capacity to measure and genotype aortic traits, resulting in the identification of dozens of genetic associations. In this Review, we describe the history of technological advances in genetic discovery and explain how newer technologies such as deep learning can rapidly define aortic traits at scale. Furthermore, we integrate novel genetic observations provided by these advances into our current biological understanding of thoracic aortic disease and describe how these new findings can contribute to strategies to prevent and treat aortic disease.
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Affiliation(s)
- Elizabeth Chou
- Division of Vascular and Endovascular Surgery, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
| | - James P Pirruccello
- Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
| | - Patrick T Ellinor
- Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA
| | - Mark E Lindsay
- Harvard Medical School, Boston, MA, USA.
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA.
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA.
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Pirruccello JP, Chaffin MD, Chou EL, Fleming SJ, Lin H, Nekoui M, Khurshid S, Friedman SF, Bick AG, Arduini A, Weng LC, Choi SH, Akkad AD, Batra P, Tucker NR, Hall AW, Roselli C, Benjamin EJ, Vellarikkal SK, Gupta RM, Stegmann CM, Juric D, Stone JR, Vasan RS, Ho JE, Hoffmann U, Lubitz SA, Philippakis AA, Lindsay ME, Ellinor PT. Deep learning enables genetic analysis of the human thoracic aorta. Nat Genet 2022; 54:40-51. [PMID: 34837083 PMCID: PMC8758523 DOI: 10.1038/s41588-021-00962-4] [Citation(s) in RCA: 79] [Impact Index Per Article: 39.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 09/30/2021] [Indexed: 11/16/2022]
Abstract
Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. We trained a deep learning model to evaluate the dimensions of the ascending and descending thoracic aorta in 4.6 million cardiac magnetic resonance images from the UK Biobank. We then conducted genome-wide association studies in 39,688 individuals, identifying 82 loci associated with ascending and 47 with descending thoracic aortic diameter, of which 14 loci overlapped. Transcriptome-wide analyses, rare-variant burden tests and human aortic single nucleus RNA sequencing prioritized genes including SVIL, which was strongly associated with descending aortic diameter. A polygenic score for ascending aortic diameter was associated with thoracic aortic aneurysm in 385,621 UK Biobank participants (hazard ratio = 1.43 per s.d., confidence interval 1.32-1.54, P = 3.3 × 10-20). Our results illustrate the potential for rapidly defining quantitative traits with deep learning, an approach that can be broadly applied to biomedical images.
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Affiliation(s)
- James P Pirruccello
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
- Precision Cardiology Laboratory, The Broad Institute & Bayer US LLC, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Mark D Chaffin
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
- Precision Cardiology Laboratory, The Broad Institute & Bayer US LLC, Cambridge, MA, USA
| | - Elizabeth L Chou
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Division of Vascular and Endovascular Surgery, Massachusetts General Hospital, Boston, MA, USA
| | - Stephen J Fleming
- Precision Cardiology Laboratory, The Broad Institute & Bayer US LLC, Cambridge, MA, USA
- Data Sciences Platform, Broad Institute, Cambridge, MA, USA
| | - Honghuang Lin
- Framingham Heart Study, Boston University and National Heart, Lung, and Blood Institute, Framingham, MA, USA
- Department of Medicine, Section of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA
| | - Mahan Nekoui
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Shaan Khurshid
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
| | | | - Alexander G Bick
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alessandro Arduini
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
- Precision Cardiology Laboratory, The Broad Institute & Bayer US LLC, Cambridge, MA, USA
| | - Lu-Chen Weng
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
| | - Seung Hoan Choi
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
| | - Amer-Denis Akkad
- Precision Cardiology Laboratory, The Broad Institute & Bayer US LLC, Cambridge, MA, USA
| | - Puneet Batra
- Data Sciences Platform, Broad Institute, Cambridge, MA, USA
| | | | - Amelia W Hall
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
| | - Carolina Roselli
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
- University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Emelia J Benjamin
- Framingham Heart Study, Boston University and National Heart, Lung, and Blood Institute, Framingham, MA, USA
- Department of Medicine, Cardiology and Preventive Medicine Sections, Boston University School of Medicine, Boston, MA, USA
- Epidemiology Department, Boston University School of Public Health, Boston, MA, USA
| | | | - Rajat M Gupta
- Department of Medicine, Divisions of Cardiovascular Medicine and Genetics, Brigham and Women's Hospital, Boston, MA, USA
| | - Christian M Stegmann
- Precision Cardiology Laboratory, The Broad Institute & Bayer US LLC, Cambridge, MA, USA
| | - Dejan Juric
- Harvard Medical School, Boston, MA, USA
- Cancer Center, Massachusetts General Hospital, Boston, MA, USA
| | - James R Stone
- Harvard Medical School, Boston, MA, USA
- Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
| | - Ramachandran S Vasan
- Framingham Heart Study, Boston University and National Heart, Lung, and Blood Institute, Framingham, MA, USA
- Department of Medicine, Cardiology and Preventive Medicine Sections, Boston University School of Medicine, Boston, MA, USA
- Epidemiology Department, Boston University School of Public Health, Boston, MA, USA
| | - Jennifer E Ho
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Udo Hoffmann
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Cardiovascular Imaging Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Steven A Lubitz
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Anthony A Philippakis
- Data Sciences Platform, Broad Institute, Cambridge, MA, USA
- GV, Mountain View, CA, USA
| | - Mark E Lindsay
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Thoracic Aortic Center, Massachusetts General Hospital, Boston, MA, USA
| | - Patrick T Ellinor
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA.
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, MA, USA.
- Precision Cardiology Laboratory, The Broad Institute & Bayer US LLC, Cambridge, MA, USA.
- Harvard Medical School, Boston, MA, USA.
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McClenaghan C, Huang Y, Matkovich SJ, Kovacs A, Weinheimer CJ, Perez R, Broekelmann TJ, Harter TM, Lee JM, Remedi MS, Nichols CG. The Mechanism of High-Output Cardiac Hypertrophy Arising From Potassium Channel Gain-of-Function in Cantú Syndrome. FUNCTION (OXFORD, ENGLAND) 2020; 1:zqaa004. [PMID: 32865539 PMCID: PMC7446247 DOI: 10.1093/function/zqaa004] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Revised: 06/08/2020] [Accepted: 06/10/2020] [Indexed: 01/06/2023]
Abstract
Dramatic cardiomegaly arising from gain-of-function (GoF) mutations in the ATP-sensitive potassium (KATP) channels genes, ABCC9 and KCNJ8, is a characteristic feature of Cantú syndrome (CS). How potassium channel over-activity results in cardiac hypertrophy, as well as the long-term consequences of cardiovascular remodeling in CS, is unknown. Using genome-edited mouse models of CS, we therefore sought to dissect the pathophysiological mechanisms linking KATP channel GoF to cardiac remodeling. We demonstrate that chronic reduction of systemic vascular resistance in CS is accompanied by elevated renin-angiotensin signaling, which drives cardiac enlargement and blood volume expansion. Cardiac enlargement in CS results in elevation of basal cardiac output, which is preserved in aging. However, the cardiac remodeling includes altered gene expression patterns that are associated with pathological hypertrophy and are accompanied by decreased exercise tolerance, suggestive of reduced cardiac reserve. Our results identify a high-output cardiac hypertrophy phenotype in CS which is etiologically and mechanistically distinct from other myocardial hypertrophies, and which exhibits key features of high-output heart failure (HOHF). We propose that CS is a genetically-defined HOHF disorder and that decreased vascular smooth muscle excitability is a novel mechanism for HOHF pathogenesis.
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Affiliation(s)
- Conor McClenaghan
- Center for the Investigation of Membrane Excitability Diseases, Washington University School of Medicine, St. Louis, MO 63110, USA,Departments of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Yan Huang
- Center for the Investigation of Membrane Excitability Diseases, Washington University School of Medicine, St. Louis, MO 63110, USA,Departments of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Scot J Matkovich
- Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Attila Kovacs
- Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carla J Weinheimer
- Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Ron Perez
- Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Thomas J Broekelmann
- Departments of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Theresa M Harter
- Center for the Investigation of Membrane Excitability Diseases, Washington University School of Medicine, St. Louis, MO 63110, USA,Departments of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jin-Moo Lee
- Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Maria S Remedi
- Center for the Investigation of Membrane Excitability Diseases, Washington University School of Medicine, St. Louis, MO 63110, USA,Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Colin G Nichols
- Center for the Investigation of Membrane Excitability Diseases, Washington University School of Medicine, St. Louis, MO 63110, USA,Departments of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO 63110, USA,Corresponding author. E-mail:
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