Precision Versus Traditional Medicine—Clinical Questions Trigger Progress in Basic Science
2019; Lippincott Williams & Wilkins; Volume: 124; Issue: 4 Linguagem: Inglês
10.1161/circresaha.119.314629
ISSN1524-4571
Autores Tópico(s)Acupuncture Treatment Research Studies
ResumoHomeCirculation ResearchVol. 124, No. 4Precision Versus Traditional Medicine—Clinical Questions Trigger Progress in Basic Science Free AccessEditorialPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessEditorialPDF/EPUBPrecision Versus Traditional Medicine—Clinical Questions Trigger Progress in Basic ScienceA Favor Not Always Returned Peter J. Schwartz and Luca Sala Peter J. SchwartzPeter J. Schwartz Correspondence to Peter J. Schwartz, MD, Center for Cardiac Arrhythmias of Genetic Origin, Istituto Auxologico Italiano IRCCS, Via Pier Lombardo, 22 - 20135 Milan, Italy. Email E-mail Address: [email protected] From Istituto Auxologico Italiano, IRCCS, Center for Cardiac Arrhythmias of Genetic Origin (P.J.S.), Milan, Italy. Laboratory of Cardiovascular Genetics (P.J.S., L.S.), Milan, Italy. and Luca SalaLuca Sala Laboratory of Cardiovascular Genetics (P.J.S., L.S.), Milan, Italy. Originally published14 Feb 2019https://doi.org/10.1161/CIRCRESAHA.119.314629Circulation Research. 2019;124:459–461This article is a commentary on the followingPredicting Patient Response to the Antiarrhythmic Mexiletine Based on Genetic VariationGenetics is a fast-growing tree bearing many different fruits. One of the most attractive is precision medicine. We all fell in love with it and still are. But, as grandmothers used to say, "even when in love, keep your eyes open if you don't want to be fooled." The issue of precision medicine is especially relevant in arrhythmogenic disorders of genetic origin because channelopathies and cardiomyopathies carry a significant risk for sudden cardiac death. It follows that the affected patients could benefit from insights on prognosis, management strategies, and therapies based on gene- and mutation-specific data.Article, see p 539In the case of long-QT syndrome (LQTS1,2), the story evolved rapidly. The probability of a first cardiac event before age 40 years and before initiation of therapy is lower among LQT1 than among LQT2 and LQT3 patients.3 The triggers for cardiac events are gene-specific, with exercise and emotional stress playing a major role for LQT1, while auditory stimuli are especially important for LQT2 and rest or sleep favor events in LQT3 patients.4 Relevant here is that, already in 1995, a first gene-specific therapy was proposed, namely the sodium channel blocker mexiletine.5 Mexiletine shortened QTc by almost 100 ms in the initial group of LQT3 patients, mostly carrying the ΔKPQ mutation.5 When this preliminary success was confirmed by other investigators, the 2013 guidelines introduced the recommendation for LQT3 patients with a QTc >500 ms to add mexiletine to β-blockers whenever a shortening >40 ms was observed during an acute oral drug test,6 and this finding was confirmed again in 2016 by Mazzanti et al.7In this issue of the Journal, Zhu et al8 deciphered the molecular mechanism of action of mexiletine on the cardiac sodium channel (NaV1.5) and generated, through a systems biology approach, a model to predict the clinical response of QTc to mexiletine based on mutation-specific in vitro biophysical parameters.First, the authors identified through a refined approach based on voltage-clamp fluorometry which of the 4 voltage-sensitive domains (VSDs) of NaV1.5 is involved in the pharmacological effect of mexiletine. They elegantly engineered sodium channels with a fluorophore sequentially tethered to each of the 4 charged S4 segments, allowing individual recordings of time and voltage dependence of each VSD. In the presence of mexiletine, only the VSD of the third domain of NaV1.5 (DIII-VSD) exhibited a marked hyperpolarization in the steady-state fluorescence-voltage activation curve, suggesting that mexiletine binding to the channel pore may prevent the transition of the DIII-pore domain (S5-S6 segments) to a completely closed state during membrane repolarization, thus forcing the DIII-VSD to remain activated. These findings significantly refine our understanding of the mechanism of action of Class Ib antiarrhythmic drugs, generally described by the modulated-receptor theory by Hille et al, by integrating the conformational status of the pore and of the inactivation gate with that of DIII-VSD.The authors wondered whether this mechanism could explain the heterogeneous clinical response to mexiletine observed with different LQT3 variants; ingeniously, they harnessed the opposite sensitivity to mexiletine of 2 LQT3 mutations: the sensitive SCN5A-R1626P and the insensitive (or less sensitive) SCN5A-M1652R. They correlated the DIII-VSD steady-state activation status to mexiletine sensitivity with the idea that the 2 terms should positively correlate, as it did actually occur because of the opposite effects carried by these mutations on DIII-VSD activation: stabilization of DIII-VSD activated conformation by the mexiletine-sensitive SCN5A-R1626P and defective activation by the mexiletine-insensitive SCN5A-M1652R. Data on 15 additional LQT3 mutations confirmed that the voltage dependence of DIII-VSD activation is indeed the key determinant of mexiletine TB of NaV1.5.However, features like use-dependent block and INa block are more relevant for the in vivo pharmacological effects of Class Ib antiarrhythmic drugs as they respectively refer to a drug's ability to be effective during tachycardia and to its predisposition to preferentially block the late component of INa without affecting conduction velocity.The modeling of use-dependent block and late INa block is more complex than that of TB and could not be described by a single parameter. Accordingly, the authors used a partial-least square regression modeling approach, based on 14 variables describing NaV1.5 gating properties, to elucidate how channel gating parameters may affect use-dependent block and late INa block by mexiletine. A second model, trained with data from 32 patients (13 variants), was then built to predict the mexiletine-induced QTc shortening in LQT3 patients whose variants were previously used to characterize NaV1.5 gating parameters. Interestingly, just 2 NaV1.5 gating parameters—DIII-VSD activation and τ of slow recovery from inactivation—turned out to be sufficient to predict the impact of mexiletine QTc shortening in vivo.The performances of this model were assessed in a blind retrospective clinical examination involving 8 LQT3 patients. The authors characterized in vitro 2 main gating parameters (DIII-VSD activation and slow recovery) of 5 LQT3 variants. Fed with these data, the model correctly predicted the response to mexiletine in 7 patients but failed the prediction in one patient whose baseline QTc was extremely prolonged (814 ms), suggesting that the model is suitable for patients with a QTc 550 ms), a physician should consider whether to test mexiletine and decide rapidly. As the model proposed can operate only once both genotype and biophysical properties of a variant are known, something almost impossible in the case of a de novo mutation with unavailable biophysical data, the necessary time for the "prediction" would simply not be available for most patients. However, these predictions are not really necessary as current practice has been in place since the 1995 study that opened the era of gene-specific management for LQTS,5 a publication curiously not quoted by Zhu et al.8 Half of the daily dose of mexiletine is given orally under continuous ECG monitoring and, within 90 to 120 minutes, the peak plasma concentration is reached; whenever QTc shortens by >40 ms then mexiletine is added to the therapy.2,5,6 All this can be done safely in just 2 hours with the advantage of being directly tailored to the response of the individual patient. This is not meant to deny the merits and potential value of the model described, but as a reminder that traditional medicine had already addressed and solved this problem long ago.The statement by Zhu et al8 that their partial-least square regression model allows "patient-specific predictions" appears also a bit optimistic. Indeed, the baseline QTc does not depend solely on the presence of a specific point mutation, as shown by the numerous studies on modifier genes performed in founder populations where, despite a large number of subjects sharing the same disease-causing mutation, the distribution of QTc values can be quite large.13 The inclusion in their model of concurrent genetic factors, polymorphisms and pharmacological data as additional predictors, could help refining genotype-phenotype correlations and improving risk stratification.Finally, Zhu et al8 correctly indicate that induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) "have emerged as a useful model for studying LQT syndrome" and indeed platforms based on stem cells could offer significant contributions, particularly for the potential of iPSC models in pharmacological approaches.14 This is clearly the main path toward precision medicine, as shown by the value of iPSC-CMs in identifying, for example, LQT2 patients responders to drugs acting on trafficking defect15 and then confirming in the same patients the findings observed in their iPSC-CMs.16 In this line of thought, it would be extremely valuable to exploit and extend the model by Zhu et al8 to predict, validate and match the pharmacological results obtained in cardiomyocytes derived from LQT3 patient-specific iPSCs either with results from heterologous systems or with the pharmacological response of the donors.Despite some aspects that warranted qualification, the study by Zhu et al8 is a significant contribution to the progressive understanding of how genetics and the biophysical properties of ion channels can interact with clinical responses. It is reasonable to hope that the novel approach proposed by these authors could become a new tool useful for modeling additional arrhythmogenic cardiac disorders of genetic origin.AcknowledgmentsWe are grateful to Pinuccia De Tomasi, BS, for expert editorial support.Sources of FundingThis work was partially supported by the Leducq Foundation for Cardiovascular Research grant 18CVD05 Towards Precision Medicine with Human iPSCs for Cardiac Channelopathies, and by a Marie Skłodowska-Curie Individual Fellowship (H2020-MSCA-IF-2017 No. 795209) to L.S.DisclosuresNone.FootnotesThe opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.Correspondence to Peter J. Schwartz, MD, Center for Cardiac Arrhythmias of Genetic Origin, Istituto Auxologico Italiano IRCCS, Via Pier Lombardo, 22 - 20135 Milan, Italy. Email p.[email protected]itReferences1. Schwartz PJ, Periti M, Malliani A. The long Q-T syndrome.Am Heart J. 1975; 89:378–390. doi.org/10.1016/0002-8703(75)90089-7CrossrefMedlineGoogle Scholar2. Schwartz PJ, Ackerman MJ. The long QT syndrome: a transatlantic clinical approach to diagnosis and therapy.Eur Heart J. 2013; 34:3109–3116. doi: 10.1093/eurheartj/eht089CrossrefMedlineGoogle Scholar3. Priori SG, Schwartz PJ, Napolitano C, Bloise R, Ronchetti E, Grillo M, Vicentini A, Spazzolini C, Nastoli J, Bottelli G, Folli R, Cappelletti D. Risk stratification in the long-QT syndrome.N Engl J Med. 2003; 348:1866–1874. doi: 10.1056/NEJMoa022147CrossrefMedlineGoogle Scholar4. Schwartz PJ, Priori SG, Spazzolini C, et al. Genotype-phenotype correlation in the long-QT syndrome: gene-specific triggers for life-threatening arrhythmias.Circulation. 2001; 103:89–95. doi.org/10.1161/01.CIR.103.1.89LinkGoogle Scholar5. Schwartz PJ, Priori SG, Locati EH, Napolitano C, Cantù F, Towbin JA, Keating MT, Hammoude H, Brown AM, Chen LS, Colatsky TJ. Long QT syndrome patients with mutations of the SCN5A and HERG genes have differential responses to Na+ channel blockade and to increases in heart rate. Implications for gene-specific therapy.Circulation. 1995; 92:3381–3386. doi.org/10.1161/01.CIR.92.12.3381LinkGoogle Scholar6. Priori SG, Wilde AA, Horie M, et al. HRS/EHRA/APHRS expert consensus statement on the diagnosis and management of patients with inherited primary arrhythmia syndromes: document endorsed by HRS, EHRA, and APHRS in May 2013 and by ACCF, AHA, PACES, and AEPC in June 2013.Heart Rhythm. 2013; 10:1932–1963. doi: 10.1016/j.hrthm.2013.05.014CrossrefMedlineGoogle Scholar7. Mazzanti A, Maragna R, Faragli A, Monteforte N, Bloise R, Memmi M, Novelli V, Baiardi P, Bagnardi V, Etheridge SP, Napolitano C, Priori SG. Gene-specific therapy with mexiletine reduces arrhythmic events in patients with long QT syndrome type 3.J Am Coll Cardiol. 2016; 67:1053–1058. doi: 10.1016/j.jacc.2015.12.033CrossrefMedlineGoogle Scholar8. Zhu W, Mazzanti A, Voelker TL, Hou P, Moreno JD, Angsutararux P, Naegle KM, Priori SG, Silva JR. Predicting patient response to the antiarrhythmic mexiletine based on genetic variation: personalized medicine for long QT syndrome.Circ Res. 2019; 124:539–552. doi: 10.1161/CIRCRESAHA.118.314050LinkGoogle Scholar9. Bos J, Crotti L, Rohatgi R, Schwartz PJ, Ackerman MJ. Mexiletine shortens the QT interval in patients with either type 1 or type 2 Long QT.Heart Rhythm. 2018; 15(suppl):S450.Google Scholar10. The Sicilian Gambit. A new approach to the classification of antiarrhythmic drugs based on their actions on arrhythmogenic mechanisms. Task Force of the Working Group on Arrhythmias of the European Society of Cardiology.Circulation. 1991; 84:1831–1851. doi.org/10.1161/01.CIR.84.4.1831LinkGoogle Scholar11. Members of the Sicilian Gambit. New approaches to antiarrhythmic therapy; emerging therapeutic applications of the cell biology of cardiac arrhythmias.Eur Heart J. 2001; 22:2148–2163. doi.org/10.1053/euhj.2001.3036CrossrefMedlineGoogle Scholar12. Wilde AA, Moss AJ, Kaufman ES, et al. Clinical aspects of type 3 long-QT syndrome: an International Multicenter Study.Circulation. 2016; 134:872–882. doi: 10.1161/CIRCULATIONAHA.116.021823LinkGoogle Scholar13. Schwartz PJ, Crotti L, George AL. Modifier genes for sudden cardiac death.Eur Heart J. 2018; 39:3925–3931. doi: 10.1093/eurheartj/ehy502MedlineGoogle Scholar14. Sala L, Bellin M, Mummery CL. Integrating cardiomyocytes from human pluripotent stem cells in safety pharmacology: has the time come?Br J Pharmacol. 2017; 174:3749–3765. doi: 10.1111/bph.13577CrossrefMedlineGoogle Scholar15. Mehta A, Ramachandra CJA, Singh P, Chitre A, Lua CH, Mura M, Crotti L, Wong P, Schwartz PJ, Gnecchi M, Shim W. Identification of a targeted and testable antiarrhythmic therapy for long-QT syndrome type 2 using a patient-specific cellular model.Eur Heart J. 2018; 39:1446–1455. doi: 10.1093/eurheartj/ehx394CrossrefMedlineGoogle Scholar16. Schwartz PJ, Gnecchi M, Dagradi F, Castelletti S, Parati G, Spazzolini C, Sala L, Crotti L. From patient-specific induced pluripotent stem cells to clinical translation in Long QT Syndrome type 2.Eur Hear J. In press. doi: 10.1093/eurheartj/ehz023Google Scholar Previous Back to top Next FiguresReferencesRelatedDetailsCited By Gnecchi M, Sala L and Schwartz P (2021) Precision Medicine and cardiac channelopathies: when dreams meet reality, European Heart Journal, 10.1093/eurheartj/ehab007, 42:17, (1661-1675), Online publication date: 1-May-2021. Crotti L, Spazzolini C, Tester D, Ghidoni A, Baruteau A, Beckmann B, Behr E, Bennett J, Bezzina C, Bhuiyan Z, Celiker A, Cerrone M, Dagradi F, De Ferrari G, Etheridge S, Fatah M, Garcia-Pavia P, Al-Ghamdi S, Hamilton R, Al-Hassnan Z, Horie M, Jimenez-Jaimez J, Kanter R, Kaski J, Kotta M, Lahrouchi N, Makita N, Norrish G, Odland H, Ohno S, Papagiannis J, Parati G, Sekarski N, Tveten K, Vatta M, Webster G, Wilde A, Wojciak J, George A, Ackerman M and Schwartz P (2019) Calmodulin mutations and life-threatening cardiac arrhythmias: insights from the International Calmodulinopathy Registry, European Heart Journal, 10.1093/eurheartj/ehz311, 40:35, (2964-2975), Online publication date: 14-Sep-2019. Sala L, Gnecchi M and Schwartz P (2019) Long QT Syndrome Modelling with Cardiomyocytes Derived from Human-induced Pluripotent Stem Cells, Arrhythmia & Electrophysiology Review, 10.15420/aer.2019.1.1, 8:2, (105-110), Online publication date: 2-May-2019. Bos J, Crotti L, Rohatgi R, Castelletti S, Dagradi F, Schwartz P and Ackerman M (2019) Mexiletine Shortens the QT Interval in Patients With Potassium Channel–Mediated Type 2 Long QT Syndrome, Circulation: Arrhythmia and Electrophysiology, 12:5, Online publication date: 1-May-2019.Related articlesPredicting Patient Response to the Antiarrhythmic Mexiletine Based on Genetic VariationWandi Zhu, et al. Circulation Research. 2019;124:539-552 February 15, 2019Vol 124, Issue 4 Advertisement Article InformationMetrics © 2019 American Heart Association, Inc.https://doi.org/10.1161/CIRCRESAHA.119.314629PMID: 30763224 Originally publishedFebruary 14, 2019 Keywordsmexiletinegeneticssodiuminduced pluripotent stem cellsEditorialslong QT syndromePDF download Advertisement SubjectsArrhythmiasElectrophysiologyGeneticsInformation TechnologyIon Channels/Membrane TransportSudden Cardiac DeathTranslational Studies
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