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Amendola LM, Coffey AJ, Lowry J, Avecilla J, Malhotra A, Chawla A, Thacker S, Taylor JP, Rajkumar R, Brown CM, Golden-Grant K, Hejja R, Lee JA, Medrano P, Milewski B, Mullen F, Walker A, Huertez-Vasquez A, Longoni M, Perry DL, Hostin D, Ajay SS, Kesari A, Strom SP, Margulies E, Belmont J, Lanfear DE, Taft RJ. Development of a comprehensive cardiovascular disease genetic risk assessment test. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.06.24306379. [PMID: 38766118 PMCID: PMC11100944 DOI: 10.1101/2024.05.06.24306379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Background Despite monogenic and polygenic contributions to cardiovascular disease (CVD), genetic testing is not widely adopted, and current tests are limited by the breadth of surveyed conditions and interpretation burden. Methods We developed a comprehensive clinical genome CVD test with semi-automated interpretation. Monogenic conditions and risk alleles were selected based on the strength of disease association and evidence for increased disease risk, respectively. Non-CVD secondary findings genes, pharmacogenomic (PGx) variants and CVD polygenic risk scores (PRS) were assessed for inclusion. Test performance was modeled using 2,594 genomes from the 1000 Genomes Project, and further investigated in 20 previously tested individuals. Results The CVD genome test is composed of a panel of 215 CVD gene-disease pairs, 35 non-CVD secondary findings genes, 4 risk alleles or genotypes, 10 PGx genes and a PRS for coronary artery disease. Modeling of test performance using samples from the 1000 Genomes Project revealed ~6% of individuals with a monogenic finding in a CVD-associated gene, 6% with a risk allele finding, ~1% with a non-CVD secondary finding, and 93% with CVD-associated PGx variants. Assessment of blinded clinical samples showed complete concordance with prior testing. An average of 4 variants were reviewed per case, with interpretation and reporting time ranging from 9-96 min. Conclusions A genome sequencing based CVD genetic risk assessment can provide comprehensive genetic disease and genetic risk information to patients with CVD. The semi-automated and limited interpretation burden suggest that this testing approach could be scaled to support population-level initiatives.
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Affiliation(s)
| | | | | | | | | | | | - Stetson Thacker
- Illumina Inc., San Diego, CA 92122
- GenomOncology, Cleveland, OH 44113
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Longoni M, Bhasin K, Ward A, Lee D, Nisson M, Bhatt S, Rodriguez F, Dash R. Real-world utilization of guideline-directed genetic testing in inherited cardiovascular diseases. Front Cardiovasc Med 2023; 10:1272433. [PMID: 37915745 PMCID: PMC10616303 DOI: 10.3389/fcvm.2023.1272433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 09/29/2023] [Indexed: 11/03/2023] Open
Abstract
Background Cardiovascular disease continues to be the leading cause of death globally. Clinical practice guidelines aimed at improving disease management and positively impacting major cardiac adverse events recommend genetic testing for inherited cardiovascular conditions such as dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), long QT syndrome (LQTS), hereditary amyloidosis, and familial hypercholesterolemia (FH); however, little is known about how consistently practitioners order genetic testing for these conditions in routine clinical practice. This study aimed to assess the adoption of guideline-directed genetic testing for patients diagnosed with DCM, HCM, LQTS, hereditary amyloidosis, or FH. Methods This retrospective cohort study captured real-world evidence of genetic testing from ICD-9-CM and ICD-10-CM codes, procedure codes, and structured text fields of de-identified patient records in the Veradigm Health Insights Ambulatory EHR Research Database linked with insurance claims data. Data analysis was conducted using an automated electronic health record analysis engine. Patient records in the Veradigm database were sourced from more than 250,000 clinicians serving over 170 million patients in outpatient primary care and specialty practice settings in the United States and linked insurance claims data from public and private insurance providers. The primary outcome measure was evidence of genetic testing within six months of condition diagnosis. Results Between January 1, 2017, and December 31, 2021, 224,641 patients were newly diagnosed with DCM, HCM, LQTS, hereditary amyloidosis, or FH and included in this study. Substantial genetic testing care gaps were identified. Only a small percentage of patients newly diagnosed with DCM (827/101,919; 0.8%), HCM (253/15,507; 1.6%), LQTS (650/56,539; 1.2%), hereditary amyloidosis (62/1,026; 6.0%), or FH (718/49,650; 1.5%) received genetic testing. Conclusions Genetic testing is underutilized across multiple inherited cardiovascular conditions. This real-world data analysis provides insights into the delivery of genomic healthcare in the United States and suggests genetic testing guidelines are rarely followed in practice.
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Affiliation(s)
- Mauro Longoni
- Global Medical Affairs Organization, Illumina, Inc., San Diego, CA, United States
| | | | | | | | | | - Sucheta Bhatt
- Global Medical Affairs Organization, Illumina, Inc., San Diego, CA, United States
| | - Fatima Rodriguez
- HealthPals Inc., Redwood, CA, United States
- Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, CA, United States
| | - Rajesh Dash
- HealthPals Inc., Redwood, CA, United States
- Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, CA, United States
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Matalon DR, Zepeda-Mendoza CJ, Aarabi M, Brown K, Fullerton SM, Kaur S, Quintero-Rivera F, Vatta M. Clinical, technical, and environmental biases influencing equitable access to clinical genetics/genomics testing: A points to consider statement of the American College of Medical Genetics and Genomics (ACMG). Genet Med 2023; 25:100812. [PMID: 37058144 DOI: 10.1016/j.gim.2023.100812] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 02/07/2023] [Indexed: 04/15/2023] Open
Affiliation(s)
- Dena R Matalon
- Division of Medical Genetics, Department of Pediatrics, Stanford Medicine, Stanford University, Stanford, CA
| | - Cinthya J Zepeda-Mendoza
- Divisions of Hematopathology and Laboratory Genetics and Genomics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Mahmoud Aarabi
- UPMC Medical Genetics and Genomics Laboratories, UPMC Magee-Womens Hospital, Pittsburgh, PA; Departments of Pathology and Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | | | - Stephanie M Fullerton
- Division of Medical Genetics, Department of Medicine, University of Washington School of Medicine, Seattle, WA; Department of Bioethics & Humanities, University of Washington School of Medicine, Seattle, WA
| | - Shagun Kaur
- Department of Child Health, Phoenix Children's Hospital, University of Arizona College of Medicine-Phoenix, Phoenix, AZ
| | - Fabiola Quintero-Rivera
- Division of Genetic and Genomic Medicine, Departments of Pathology, Laboratory Medicine, and Pediatrics, University of California Irvine, Irvine, CA
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Dellefave-Castillo LM, Cirino AL, Callis TE, Esplin ED, Garcia J, Hatchell KE, Johnson B, Morales A, Regalado E, Rojahn S, Vatta M, Nussbaum RL, McNally EM. Assessment of the Diagnostic Yield of Combined Cardiomyopathy and Arrhythmia Genetic Testing. JAMA Cardiol 2022; 7:966-974. [PMID: 35947370 PMCID: PMC9366660 DOI: 10.1001/jamacardio.2022.2455] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Importance Genetic testing can guide management of both cardiomyopathies and arrhythmias, but cost, yield, and uncertain results can be barriers to its use. It is unknown whether combined disease testing can improve diagnostic yield and clinical utility for patients with a suspected genetic cardiomyopathy or arrhythmia. Objective To evaluate the diagnostic yield and clinical management implications of combined cardiomyopathy and arrhythmia genetic testing through a no-charge, sponsored program for patients with a suspected genetic cardiomyopathy or arrhythmia. Design, Setting, and Participants This cohort study involved a retrospective review of DNA sequencing results for cardiomyopathy- and arrhythmia-associated genes. The study included 4782 patients with a suspected genetic cardiomyopathy or arrhythmia who were referred for genetic testing by 1203 clinicians; all patients participated in a no-charge, sponsored genetic testing program for cases of suspected genetic cardiomyopathy and arrhythmia at a single testing site from July 12, 2019, through July 9, 2020. Main Outcomes and Measures Positive gene findings from combined cardiomyopathy and arrhythmia testing were compared with findings from smaller subtype-specific gene panels and clinician-provided diagnoses. Results Among 4782 patients (mean [SD] age, 40.5 [21.3] years; 2551 male [53.3%]) who received genetic testing, 39 patients (0.8%) were Ashkenazi Jewish, 113 (2.4%) were Asian, 571 (11.9%) were Black or African American, 375 (7.8%) were Hispanic, 2866 (59.9%) were White, 240 (5.0%) were of multiple races and/or ethnicities, 138 (2.9%) were of other races and/or ethnicities, and 440 (9.2%) were of unknown race and/or ethnicity. A positive result (molecular diagnosis) was confirmed in 954 of 4782 patients (19.9%). Of those, 630 patients with positive results (66.0%) had the potential to inform clinical management associated with adverse clinical outcomes, increased arrhythmia risk, or targeted therapies. Combined cardiomyopathy and arrhythmia gene panel testing identified clinically relevant variants for 1 in 5 patients suspected of having a genetic cardiomyopathy or arrhythmia. If only patients with a high suspicion of genetic cardiomyopathy or arrhythmia had been tested, at least 137 positive results (14.4%) would have been missed. If testing had been restricted to panels associated with the clinician-provided diagnostic indications, 75 of 689 positive results (10.9%) would have been missed; 27 of 75 findings (36.0%) gained through combined testing involved a cardiomyopathy indication with an arrhythmia genetic finding or vice versa. Cascade testing of family members yielded 402 of 958 positive results (42.0%). Overall, 2446 of 4782 patients (51.2%) had only variants of uncertain significance. Patients referred for arrhythmogenic cardiomyopathy had the lowest rate of variants of uncertain significance (81 of 176 patients [46.0%]), and patients referred for catecholaminergic polymorphic ventricular tachycardia had the highest rate (48 of 76 patients [63.2%]). Conclusions and Relevance In this study, comprehensive genetic testing for cardiomyopathies and arrhythmias revealed diagnoses that would have been missed by disease-specific testing. In addition, comprehensive testing provided diagnostic and prognostic information that could have potentially changed management and monitoring strategies for patients and their family members. These results suggest that this improved diagnostic yield may outweigh the burden of uncertain results.
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Affiliation(s)
- Lisa M Dellefave-Castillo
- Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Allison L Cirino
- Cardiovascular Division, Brigham and Women's Hospital, Boston, Massachusetts.,Institute of Health Professions, Massachusetts General Hospital, Boston
| | | | | | - John Garcia
- Invitae Corporation, San Francisco, California
| | | | | | - Ana Morales
- Invitae Corporation, San Francisco, California
| | | | | | | | | | - Elizabeth M McNally
- Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
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