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O’Neill MJ, Ng CA, Aizawa T, Sala L, Bains S, Winbo A, Ullah R, Shen Q, Tan CY, Kozek K, Vanags LR, Mitchell DW, Shen A, Wada Y, Kashiwa A, Crotti L, Dagradi F, Musu G, Spazzolini C, Neves R, Bos JM, Giudicessi JR, Bledsoe X, Gamazon ER, Lancaster M, Glazer AM, Knollmann BC, Roden DM, Weile J, Roth F, Salem JE, Earle N, Stiles R, Agee T, Johnson CN, Horie M, Skinner J, Ackerman MJ, Schwartz PJ, Ohno S, Vandenberg JI, Kroncke BM. Multiplexed Assays of Variant Effect and Automated Patch-clamping Improve KCNH2-LQTS Variant Classification and Cardiac Event Risk Stratification. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.01.24301443. [PMID: 38370760 PMCID: PMC10871451 DOI: 10.1101/2024.02.01.24301443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Background Long QT syndrome (LQTS) is a lethal arrhythmia syndrome, frequently caused by rare loss-of-function variants in the potassium channel encoded by KCNH2. Variant classification is difficult, often owing to lack of functional data. Moreover, variant-based risk stratification is also complicated by heterogenous clinical data and incomplete penetrance. Here, we sought to test whether variant-specific information, primarily from high-throughput functional assays, could improve both classification and cardiac event risk stratification in a large, harmonized cohort of KCNH2 missense variant heterozygotes. Methods We quantified cell-surface trafficking of 18,796 variants in KCNH2 using a Multiplexed Assay of Variant Effect (MAVE). We recorded KCNH2 current density for 533 variants by automated patch clamping (APC). We calibrated the strength of evidence of MAVE data according to ClinGen guidelines. We deeply phenotyped 1,458 patients with KCNH2 missense variants, including QTc, cardiac event history, and mortality. We correlated variant functional data and Bayesian LQTS penetrance estimates with cohort phenotypes and assessed hazard ratios for cardiac events. Results Variant MAVE trafficking scores and APC peak tail currents were highly correlated (Spearman Rank-order ρ = 0.69). The MAVE data were found to provide up to pathogenic very strong evidence for severe loss-of-function variants. In the cohort, both functional assays and Bayesian LQTS penetrance estimates were significantly predictive of cardiac events when independently modeled with patient sex and adjusted QT interval (QTc); however, MAVE data became non-significant when peak-tail current and penetrance estimates were also available. The area under the ROC for 20-year event outcomes based on patient-specific sex and QTc (AUC 0.80 [0.76-0.83]) was improved with prospectively available penetrance scores conditioned on MAVE (AUC 0.86 [0.83-0.89]) or attainable APC peak tail current data (AUC 0.84 [0.81-0.88]). Conclusion High throughput KCNH2 variant MAVE data meaningfully contribute to variant classification at scale while LQTS penetrance estimates and APC peak tail current measurements meaningfully contribute to risk stratification of cardiac events in patients with heterozygous KCNH2 missense variants.
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Affiliation(s)
- Matthew J. O’Neill
- Vanderbilt University School of Medicine, Medical Scientist Training Program, Nashville, TN, USA
- These authors contributed equally
| | - Chai-Ann Ng
- Mark Cowley Lidwill Research Program in Cardiac Electrophysiology, Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia
- School of Clinical Medicine, UNSW Sydney, Darlinghurst, NSW, Australia
- These authors contributed equally
| | - Takanori Aizawa
- Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine Kyoto, Japan
| | - Luca Sala
- IRCCS, Istituto Auxologico Italiano, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics, Milano, Italy
| | - Sahej Bains
- Department of Molecular Pharmacology & Experimental Therapeutics (Windland Smith Rice Sudden Death Genomics Laboratory), Mayo Clinic, Rochester, MN, USA
| | - Annika Winbo
- Department of Physiology, University of Auckland, Auckland, New Zealand
| | - Rizwan Ullah
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Qianyi Shen
- Mark Cowley Lidwill Research Program in Cardiac Electrophysiology, Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia
| | - Chek-Ying Tan
- Mark Cowley Lidwill Research Program in Cardiac Electrophysiology, Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia
| | - Krystian Kozek
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Loren R. Vanags
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Devyn W. Mitchell
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Alex Shen
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yuko Wada
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Asami Kashiwa
- Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine Kyoto, Japan
| | - Lia Crotti
- IRCCS, Istituto Auxologico Italiano, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics, Milano, Italy
- Department of Medicine and Surgery, University Milano Bicocca, Milan, Italy
| | - Federica Dagradi
- IRCCS, Istituto Auxologico Italiano, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics, Milano, Italy
| | - Giulia Musu
- IRCCS, Istituto Auxologico Italiano, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics, Milano, Italy
| | - Carla Spazzolini
- IRCCS, Istituto Auxologico Italiano, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics, Milano, Italy
| | - Raquel Neves
- Department of Molecular Pharmacology & Experimental Therapeutics (Windland Smith Rice Sudden Death Genomics Laboratory), Mayo Clinic, Rochester, MN, USA
| | - J. Martijn Bos
- Department of Molecular Pharmacology & Experimental Therapeutics (Windland Smith Rice Sudden Death Genomics Laboratory), Mayo Clinic, Rochester, MN, USA
| | - John R. Giudicessi
- Department of Molecular Pharmacology & Experimental Therapeutics (Windland Smith Rice Sudden Death Genomics Laboratory), Mayo Clinic, Rochester, MN, USA
| | - Xavier Bledsoe
- Vanderbilt University School of Medicine, Medical Scientist Training Program, Nashville, TN, USA
| | - Eric R. Gamazon
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Megan Lancaster
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Andrew M. Glazer
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bjorn C. Knollmann
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dan M. Roden
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jochen Weile
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Frederick Roth
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Joe-Elie Salem
- Department of Cardiovascular Medicine, Hôpital Bichat, APHP, Université de Paris Cité, Paris, France
| | - Nikki Earle
- Department of Medicine, University of Auckland, Auckland, New Zealand
| | - Rachael Stiles
- Department of Cardiology, Waikato Hospital, Hamilton, New Zealand
| | - Taylor Agee
- Department of Chemistry, Mississippi State University, Starkville, MS 39759, USA
| | | | - Minoru Horie
- Department of Cardiovascular Medicine, Shiga University of Medical Science, Shiga, Japan
| | - Jonathan Skinner
- Sydney Children’s Hospital Network, University of Sydney, Sydney, Australia
| | - Michael J. Ackerman
- Department of Molecular Pharmacology & Experimental Therapeutics (Windland Smith Rice Sudden Death Genomics Laboratory), Mayo Clinic, Rochester, MN, USA
| | - Peter J. Schwartz
- IRCCS, Istituto Auxologico Italiano, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics, Milano, Italy
| | - Seiko Ohno
- Department of Bioscience and Genetics, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Jamie I. Vandenberg
- Mark Cowley Lidwill Research Program in Cardiac Electrophysiology, Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia
- School of Clinical Medicine, UNSW Sydney, Darlinghurst, NSW, Australia
| | - Brett M. Kroncke
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
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Caudal A, Snyder MP, Wu JC. Harnessing human genetics and stem cells for precision cardiovascular medicine. CELL GENOMICS 2024; 4:100445. [PMID: 38359791 PMCID: PMC10879032 DOI: 10.1016/j.xgen.2023.100445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 09/22/2023] [Accepted: 10/25/2023] [Indexed: 02/17/2024]
Abstract
Human induced pluripotent stem cell (iPSC) platforms are valuable for biomedical and pharmaceutical research by providing tissue-specific human cells that retain patients' genetic integrity and display disease phenotypes in a dish. Looking forward, combining iPSC phenotyping platforms with genomic and screening technologies will continue to pave new directions for precision medicine, including genetic prediction, visualization, and treatment of heart disease. This review summarizes the recent use of iPSC technology to unpack the influence of genetic variants in cardiovascular pathology. We focus on various state-of-the-art genomic tools for cardiovascular therapies-including the expansion of genetic toolkits for molecular interrogation, in vitro population studies, and function-based drug screening-and their current applications in patient- and genome-edited iPSC platforms that are heralding new avenues for cardiovascular research.
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Affiliation(s)
- Arianne Caudal
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Michael P Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Joseph C Wu
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Greenstone Biosciences, Palo Alto, CA 94304, USA.
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O'Neill MJ, Sala L, Denjoy I, Wada Y, Kozek K, Crotti L, Dagradi F, Kotta MC, Spazzolini C, Leenhardt A, Salem JE, Kashiwa A, Ohno S, Tao R, Roden DM, Horie M, Extramiana F, Schwartz PJ, Kroncke BM. Continuous Bayesian variant interpretation accounts for incomplete penetrance among Mendelian cardiac channelopathies. Genet Med 2023; 25:100355. [PMID: 36496179 PMCID: PMC9992222 DOI: 10.1016/j.gim.2022.12.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 12/05/2022] [Accepted: 12/05/2022] [Indexed: 12/12/2022] Open
Abstract
PURPOSE The congenital Long QT Syndrome (LQTS) and Brugada Syndrome (BrS) are Mendelian autosomal dominant diseases that frequently precipitate fatal cardiac arrhythmias. Incomplete penetrance is a barrier to clinical management of heterozygotes harboring variants in the major implicated disease genes KCNQ1, KCNH2, and SCN5A. We apply and evaluate a Bayesian penetrance estimation strategy that accounts for this phenomenon. METHODS We generated Bayesian penetrance models for KCNQ1-LQT1 and SCN5A-LQT3 using variant-specific features and clinical data from the literature, international arrhythmia genetic centers, and population controls. We analyzed the distribution of posterior penetrance estimates across 4 genotype-phenotype relationships and compared continuous estimates with ClinVar annotations. Posterior estimates were mapped onto protein structure. RESULTS Bayesian penetrance estimates of KCNQ1-LQT1 and SCN5A-LQT3 are empirically equivalent to 10 and 5 clinically phenotype heterozygotes, respectively. Posterior penetrance estimates were bimodal for KCNQ1-LQT1 and KCNH2-LQT2, with a higher fraction of missense variants with high penetrance among KCNQ1 variants. There was a wide distribution of variant penetrance estimates among identical ClinVar categories. Structural mapping revealed heterogeneity among "hot spot" regions and featured high penetrance estimates for KCNQ1 variants in contact with calmodulin and the S6 domain. CONCLUSIONS Bayesian penetrance estimates provide a continuous framework for variant interpretation.
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Affiliation(s)
- Matthew J O'Neill
- Vanderbilt University School of Medicine, Medical Scientist Training Program, Vanderbilt University, Nashville, TN
| | - Luca Sala
- IRCCS, Istituto Auxologico Italiano, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics, Milano, Italy
| | - Isabelle Denjoy
- Department of Cardiovascular Medicine, Hôpital Bichat, APHP, Université de Paris Cité, Paris, France
| | - Yuko Wada
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Krystian Kozek
- Vanderbilt University School of Medicine, Medical Scientist Training Program, Vanderbilt University, Nashville, TN
| | - Lia Crotti
- IRCCS, Istituto Auxologico Italiano, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics, Milano, Italy
| | - Federica Dagradi
- IRCCS, Istituto Auxologico Italiano, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics, Milano, Italy
| | - Maria-Christina Kotta
- IRCCS, Istituto Auxologico Italiano, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics, Milano, Italy
| | - Carla Spazzolini
- IRCCS, Istituto Auxologico Italiano, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics, Milano, Italy
| | - Antoine Leenhardt
- Department of Cardiovascular Medicine, Hôpital Bichat, APHP, Université de Paris Cité, Paris, France
| | - Joe-Elie Salem
- Department of Cardiovascular Medicine, Hôpital Bichat, APHP, Université de Paris Cité, Paris, France
| | - Asami Kashiwa
- Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine Kyoto, Japan
| | - Seiko Ohno
- Department of Bioscience and Genetics, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN
| | - Dan M Roden
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Departments of Medicine, Pharmacology, and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
| | - Minoru Horie
- Department of Cardiovascular Medicine, Shiga University of Medical Science, Shiga, Japan
| | - Fabrice Extramiana
- Department of Cardiovascular Medicine, Hôpital Bichat, APHP, Université de Paris Cité, Paris, France
| | - Peter J Schwartz
- IRCCS, Istituto Auxologico Italiano, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics, Milano, Italy
| | - Brett M Kroncke
- Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN.
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Schwartz PJ, Sala L. The impact of genetics on the long QT syndrome: myth or reality? Curr Opin Cardiol 2023; 38:149-156. [PMID: 36789771 DOI: 10.1097/hco.0000000000001027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
PURPOSE OF REVIEW To summarize and critically assess the contribution of genetics to the Long QT Syndrome (LQTS), with specific reference to the unraveling of its underlying mechanisms and to its impact on clinical practice. RECENT FINDINGS The evolution towards our current approach to therapy for LQTS patients is examined in terms of risk stratification, gene-specific management, and assessment of the clinical impact that genetic modifiers may have in modulating the natural history of the patients. Glimpses are provided on the newest multidisciplinary approaches to study disease mechanisms, test new candidate drugs and identify precision treatments. SUMMARY It is undeniable that genetics has revolutionized our mechanistic understanding of cardiac channelopathies. Its impact has been enormous but, curiously, the way LQTS patients are being treated today is largely the same that was used in the pregenetic era, even though management has been refined and gene-specific differences allow a more individually tailored antiarrhythmic protection. The synergy of genetic findings with modern in vitro and in silico tools may expand precision treatments; however, they will need to prove more effective than the current therapeutic approaches and equally safe.
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Affiliation(s)
- Peter J Schwartz
- Istituto Auxologico Italiano IRCCS, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics
| | - Luca Sala
- Istituto Auxologico Italiano IRCCS, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics.,Department of Biotechnology and Biosciences, University of Milano - Bicocca, Milan, Italy
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Glazer AM. Genetics of congenital arrhythmia syndromes: the challenge of variant interpretation. Curr Opin Genet Dev 2022; 77:102004. [PMID: 36368182 PMCID: PMC9743411 DOI: 10.1016/j.gde.2022.102004] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 10/10/2022] [Accepted: 10/11/2022] [Indexed: 11/11/2022]
Abstract
Congenital arrhythmia syndromes are rare genetic disorders that can cause a high risk of sudden cardiac death. Expert panels have affirmed 15 genes that are linked to congenital arrhythmias. These genes mostly encode cardiac ion channel proteins or associated regulatory proteins that generate the cardiac action potential. Common genetic variation modulates the risk of rare variants and partially explains the incomplete penetrance of these disorders. As genetic testing becomes more prevalent, a major challenge is that most detected variants are annotated as variants of uncertain significance. This review will highlight emerging methods that are refining our understanding of arrhythmia genetics, including phenotype risk scores, large cohorts, in vitro functional assays, structural models, and computational predictions.
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Affiliation(s)
- Andrew M Glazer
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
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6
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Ng CA, Ullah R, Farr J, Hill AP, Kozek KA, Vanags LR, Mitchell DW, Kroncke BM, Vandenberg JI. A massively parallel assay accurately discriminates between functionally normal and abnormal variants in a hotspot domain of KCNH2. Am J Hum Genet 2022; 109:1208-1216. [PMID: 35688148 PMCID: PMC9300756 DOI: 10.1016/j.ajhg.2022.05.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 05/03/2022] [Indexed: 01/09/2023] Open
Abstract
Many genes, including KCNH2, contain "hotspot" domains associated with a high density of variants associated with disease. This has led to the suggestion that variant location can be used as evidence supporting classification of clinical variants. However, it is not known what proportion of all potential variants in hotspot domains cause loss of function. Here, we have used a massively parallel trafficking assay to characterize all single-nucleotide variants in exon 2 of KCNH2, a known hotspot for variants that cause long QT syndrome type 2 and an increased risk of sudden cardiac death. Forty-two percent of KCNH2 exon 2 variants caused at least 50% reduction in protein trafficking, and 65% of these trafficking-defective variants exerted a dominant-negative effect when co-expressed with a WT KCNH2 allele as assessed using a calibrated patch-clamp electrophysiology assay. The massively parallel trafficking assay was more accurate (AUC of 0.94) than bioinformatic prediction tools (REVEL and CardioBoost, AUC of 0.81) in discriminating between functionally normal and abnormal variants. Interestingly, over half of variants in exon 2 were found to be functionally normal, suggesting a nuanced interpretation of variants in this "hotspot" domain is necessary. Our massively parallel trafficking assay can provide this information prospectively.
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Affiliation(s)
- Chai-Ann Ng
- Mark Cowley Lidwill Research Program in Cardiac Electrophysiology, Victor Chang Cardiac Research Institute, Darlinghurst, NSW 2010, Australia; School of Clinical Medicine, UNSW Sydney, Darlinghurst, NSW, Australia
| | - Rizwan Ullah
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Jessica Farr
- Mark Cowley Lidwill Research Program in Cardiac Electrophysiology, Victor Chang Cardiac Research Institute, Darlinghurst, NSW 2010, Australia; School of Computer Science and Engineering, UNSW Sydney, Kensington, NSW, Australia
| | - Adam P Hill
- Mark Cowley Lidwill Research Program in Cardiac Electrophysiology, Victor Chang Cardiac Research Institute, Darlinghurst, NSW 2010, Australia; School of Clinical Medicine, UNSW Sydney, Darlinghurst, NSW, Australia
| | - Krystian A Kozek
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Loren R Vanags
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Devyn W Mitchell
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Brett M Kroncke
- Vanderbilt Center for Arrhythmia Research and Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA.
| | - Jamie I Vandenberg
- Mark Cowley Lidwill Research Program in Cardiac Electrophysiology, Victor Chang Cardiac Research Institute, Darlinghurst, NSW 2010, Australia; School of Clinical Medicine, UNSW Sydney, Darlinghurst, NSW, Australia.
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Kuntz CP, Woods H, McKee AG, Zelt NB, Mendenhall JL, Meiler J, Schlebach JP. Towards generalizable predictions for G protein-coupled receptor variant expression. Biophys J 2022; 121:2712-2720. [PMID: 35715957 DOI: 10.1016/j.bpj.2022.06.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 05/31/2022] [Accepted: 06/13/2022] [Indexed: 11/30/2022] Open
Abstract
Missense mutations that compromise the plasma membrane expression (PME) of integral membrane proteins are the root cause of numerous genetic diseases. Differentiation of this class of mutations from those that specifically modify the activity of the folded protein has proven useful for the development and targeting of precision therapeutics. Nevertheless, it remains challenging to predict the effects of mutations on the stability and/ or expression of membrane proteins. In this work, we utilize deep mutational scanning data to train a series of artificial neural networks to predict the PME of transmembrane domain variants of G protein-coupled receptors from structural and/ or evolutionary features. We show that our best-performing network, which we term the PME predictor, can recapitulate mutagenic trends within rhodopsin and can differentiate pathogenic transmembrane domain variants that cause it to misfold from those that compromise its signaling. This network also generates statistically significant predictions for the relative PME of transmembrane domain variants for another class A G protein-coupled receptor (β2 adrenergic receptor) but not for an unrelated voltage-gated potassium channel (KCNQ1). Notably, our analyses of these networks suggest structural features alone are generally sufficient to recapitulate the observed mutagenic trends. Moreover, our findings imply that networks trained in this manner may be generalizable to proteins that share a common fold. Implications of our findings for the design of mechanistically specific genetic predictors are discussed.
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Affiliation(s)
- Charles P Kuntz
- Department of Chemistry, Indiana University, Bloomington, Indiana
| | - Hope Woods
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee; Chemical and Physical Biology Program, Vanderbilt University, Nashville, Tennessee
| | - Andrew G McKee
- Department of Chemistry, Indiana University, Bloomington, Indiana
| | - Nathan B Zelt
- Department of Chemistry, Indiana University, Bloomington, Indiana
| | - Jeffrey L Mendenhall
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee; Chemical and Physical Biology Program, Vanderbilt University, Nashville, Tennessee
| | - Jens Meiler
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee; Institute for Drug Discovery, Leipzig University Medical School, Leipzig, Saxony, Germany.
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Horie M, Ohno S, Ai T. Pandora will never regret having opened her box: reappraisal of genes associated with CPVT and SQTS. Eur Heart J 2021; 43:1511-1513. [PMID: 34864954 DOI: 10.1093/eurheartj/ehab794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- Minoru Horie
- Department of Cardiovascular Medicine, Shiga University of Medical Science, Ohtsu, Japan
| | - Seiko Ohno
- Department of Cardiovascular Medicine, Shiga University of Medical Science, Ohtsu, Japan.,Department of Bioscience and Genetics, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Tomohiko Ai
- Department of Clinical Laboratory Medicine, Juntendo University School of Medicine, Tokyo, Japan.,Krannert Institute of Cardiology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
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