<p>We sincerely appreciate the opportunity to reply to the letter from Dr. Müller-Wöhrstein et al. regarding our paper.<span><sup>1</sup></span> We are grateful for their insightful reevaluation, raising important points in the discussion.</p><p>In their letter, the authors highlighted the challenges and the need for cautious interpretation of functional analyses, especially for ion channels, by re-evaluating the five <i>SCN1A</i> variants we previously classified as gain-of-function (GOF) or “mixed,” using their newly developed in silico prediction tool, SCION.<span><sup>2</sup></span></p><p>We concur that the functional analysis of <i>SCN1A</i> variants is complex and that the currently available approaches, including those used in our study, have significant limitations. Although patch-clamp electrophysiology remains the gold standard for direct in vitro biophysical characterization, its technical demands and multiparametric nature, including current density, activation, fast inactivation, recovery from inactivation, and persistent current, impose limitations.<span><sup>3, 4</sup></span> As more parameters are integrated, classification into a simple binary framework of GOF or loss-of-function (LOF) becomes increasingly difficult.<span><sup>3, 5</sup></span> Moreover, neuronal dysfunction from a given variant may not be solely attributable to altered channel activity but may also result from impaired protein trafficking or expression, implying in vivo properties could differ from electrophysiological data.<span><sup>3</sup></span></p><p>Recent emerging in silico tools, such as paralogue-based patch-clamp studies,<span><sup>6</sup></span> and machine learning-based predictors, such as funNCion<span><sup>7</sup></span> and SCION,<span><sup>2</sup></span> offer alternative approaches for evaluating <i>SCN1A</i> variant function. Although these tools show relatively high concordance with patch-clamp data<span><sup>2, 6</sup></span> and expand our interpretive capabilities, their clinical utility remains limited. We acknowledge these constraints and highlight the need for more accurate and clinically translatable prediction tools.</p><p>Despite these methodological limitations, our study, as well as a few previous studies<span><sup>8-10</sup></span> proposed the previously unrecognized possibility that non-LOF forms of Dravet syndrome (DS) may exist, and no clear evidence has disproved this hypothesis thus far. Our study also suggests that there may be subtle differences in the clinical course and antiseizure medication responsiveness between the LOF and non-LOF groups, based on a combination of experimental and computational approaches,<span><sup>1, 11</sup></span> even among individuals who satisfy the standard clinical criteria for DS. DS is a clinically heterogeneous disorder with variability in seizure severity, response to antiseizure medications, and developmental outcomes, despite shared diagnostic criteria.<span><sup>12</sup></span> Where
我们真诚地感谢有机会回复Müller-Wöhrstein等人关于我们论文1的来信我们感谢他们富有洞察力的重新评价,在讨论中提出了重要的观点。在他们的信中,作者强调了对功能分析进行谨慎解释的挑战和必要性,特别是对于离子通道,通过使用他们新开发的硅预测工具scion .2重新评估我们之前归类为功能获得(GOF)或“混合”的五种SCN1A变体。我们同意SCN1A变体的功能分析是复杂的,目前可用的方法,包括我们研究中使用的方法,都有很大的局限性。尽管膜片钳电生理学仍然是直接体外生物物理表征的金标准,但其技术要求和多参数特性(包括电流密度、激活、快速失活、失活后恢复和持续电流)施加了限制。3,4随着越来越多的参数被整合,将其分类为简单的GOF或LOF二元框架变得越来越困难。此外,特定变异的神经元功能障碍可能不仅仅归因于通道活性的改变,也可能是蛋白质运输或表达受损的结果,这意味着体内特性可能与电生理数据不同。最近出现的硅工具,如基于对话的膜片钳研究6和基于机器学习的预测器,如funcion7和SCION 2,为评估SCN1A变异功能提供了替代方法。尽管这些工具与膜片钳数据显示出相对较高的一致性,并扩展了我们的解释能力,但它们的临床应用仍然有限。我们承认这些限制,并强调需要更准确和临床可翻译的预测工具。尽管存在这些方法学上的局限性,我们的研究以及之前的一些研究(8-10)提出了一种以前未被认识到的可能性,即非lof形式的Dravet综合征(DS)可能存在,迄今为止还没有明确的证据反驳这一假设。我们的研究还表明,基于实验和计算方法的结合,LOF组和非LOF组在临床病程和抗癫痫药物反应性方面可能存在细微差异,即使在满足DS标准临床标准的个体中也是如此。尽管有共同的诊断标准,但退行性椎体滑移是一种临床异质性疾病,在癫痫发作严重程度、对抗癫痫药物的反应和发育结局方面具有可变性这种变异的起源是一个科学和临床重要的挑战,我们认为从遗传变异的功能见解可能是阐明其机制的潜在方法。总之,尽管变异功能评估仍然存在挑战,但其解释对治疗决策越来越重要,包括分子治疗的潜在应用。我们的发现开启了讨论,尽管可能罕见,但并非所有的DS病例都是由LOF变异引起的。scn1a相关疾病的复杂性突出了对整合临床、遗传和功能证据的多维方法的需求。我们希望我们的文章能提高人们对遗传变异鉴定的重要性的认识,以及功能表征的附加价值。需要进一步的研究来验证我们的观察结果,并推进scn1a相关疾病的个性化治疗策略。这项工作得到了国家神经病学和精神病学中心(Y. Kobayashi, K. Inoue)和日本医学研究与开发机构(AMED)的内部基金的部分资助,资助编号:JP24ek0109674, JP24ek0109760, JP24ek0109617, JP24ek0109648和JP24ek0109677 (N. Matsumoto);日本科学促进协会(JSPS) KAKENHI,资助号JP24K02230 (N. Matsumoto);武田科学基金会(N. Matsumoto)。我们确认,我们已经阅读了《华尔街日报》关于出版伦理问题的立场,并确认本报告符合这些准则。获得了国家神经病学和精神病学中心伦理委员会的伦理批准(编号:A2024-037)。支持本研究结果的数据可根据通讯作者的合理要求提供。
{"title":"Reply to Letter to the Editor regarding the article “SCN1A gain of function effects in Dravet syndrome: Insights into clinical phenotypes and therapeutic implications”","authors":"Yoko Kobayashi Takahashi, Kenshiro Tabata, Shimpei Baba, Eri Takeshita, Noriko Sumitomo, Yuko Shimizu-Motohashi, Takashi Saito, Eiji Nakagawa, Atsushi Ishii, Shinichi Hirose, Mitsuhiro Kato, Naomichi Matsumoto, Hirofumi Komaki, Ken Inoue","doi":"10.1002/epi4.70153","DOIUrl":"10.1002/epi4.70153","url":null,"abstract":"<p>We sincerely appreciate the opportunity to reply to the letter from Dr. Müller-Wöhrstein et al. regarding our paper.<span><sup>1</sup></span> We are grateful for their insightful reevaluation, raising important points in the discussion.</p><p>In their letter, the authors highlighted the challenges and the need for cautious interpretation of functional analyses, especially for ion channels, by re-evaluating the five <i>SCN1A</i> variants we previously classified as gain-of-function (GOF) or “mixed,” using their newly developed in silico prediction tool, SCION.<span><sup>2</sup></span></p><p>We concur that the functional analysis of <i>SCN1A</i> variants is complex and that the currently available approaches, including those used in our study, have significant limitations. Although patch-clamp electrophysiology remains the gold standard for direct in vitro biophysical characterization, its technical demands and multiparametric nature, including current density, activation, fast inactivation, recovery from inactivation, and persistent current, impose limitations.<span><sup>3, 4</sup></span> As more parameters are integrated, classification into a simple binary framework of GOF or loss-of-function (LOF) becomes increasingly difficult.<span><sup>3, 5</sup></span> Moreover, neuronal dysfunction from a given variant may not be solely attributable to altered channel activity but may also result from impaired protein trafficking or expression, implying in vivo properties could differ from electrophysiological data.<span><sup>3</sup></span></p><p>Recent emerging in silico tools, such as paralogue-based patch-clamp studies,<span><sup>6</sup></span> and machine learning-based predictors, such as funNCion<span><sup>7</sup></span> and SCION,<span><sup>2</sup></span> offer alternative approaches for evaluating <i>SCN1A</i> variant function. Although these tools show relatively high concordance with patch-clamp data<span><sup>2, 6</sup></span> and expand our interpretive capabilities, their clinical utility remains limited. We acknowledge these constraints and highlight the need for more accurate and clinically translatable prediction tools.</p><p>Despite these methodological limitations, our study, as well as a few previous studies<span><sup>8-10</sup></span> proposed the previously unrecognized possibility that non-LOF forms of Dravet syndrome (DS) may exist, and no clear evidence has disproved this hypothesis thus far. Our study also suggests that there may be subtle differences in the clinical course and antiseizure medication responsiveness between the LOF and non-LOF groups, based on a combination of experimental and computational approaches,<span><sup>1, 11</sup></span> even among individuals who satisfy the standard clinical criteria for DS. DS is a clinically heterogeneous disorder with variability in seizure severity, response to antiseizure medications, and developmental outcomes, despite shared diagnostic criteria.<span><sup>12</sup></span> Where ","PeriodicalId":12038,"journal":{"name":"Epilepsia Open","volume":"10 6","pages":"2036-2038"},"PeriodicalIF":2.9,"publicationDate":"2025-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/epi4.70153","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145344302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}