Peyton Murin, Nicholas F. Schulze, Vivian D. Gao, Manouela V. Valtcheva, Stefanie Geisler
<p>We sincerely thank Drs. Blitshteyn, Stingl, and Schofield for their thoughtful and encouraging comments on our recent publication, “Uncovering Hidden Profiles: From Pain-Centric to Multi-Symptom Small Fiber Neuropathy” [<span>1</span>]. We are pleased that our findings resonate with clinicians who see patients across the spectrum of dysautonomia, postinfectious, and autoimmune disorders. As highlighted in their letter, our study demonstrates that small fiber neuropathy (SFN) encompasses a broad constellation of sensory, autonomic, and systemic symptoms that extend beyond neuropathic pain. Blitshteyn et al. underscore the importance of considering the full phenotypic spectrum of SFN, including fatigue and myalgia, which our analysis identified as highly prevalent and clinically meaningful.</p><p>We share the authors' interest in the role of the immune system in the pathophysiology of SFN. Fatigue and myalgia are defining features of disorders such as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), fibromyalgia, and Long COVID, where immune dysfunction and small fiber abnormalities have been documented in a subset of patients [<span>2-6</span>]. The convergence of these findings with the “myalgic” SFN subgroup points to potential shared immune-mediated mechanisms and underscores the need for systematic investigation of clinically and biologically distinct SFN subtypes.</p><p>At present, most symptom assessment scales have focused almost exclusively on the painful symptoms [<span>7, 8</span>]. However, as the authors point out, this narrow focus risks overlooking patients in whom fatigue, myalgia, or dysautonomia predominate, potentially delaying diagnosis and treatment. Broader awareness and systematic incorporation of autonomic and systemic symptoms into clinical assessments, coupled with objective measures such as skin biopsy and quantitative autonomic testing, could substantially improve diagnostic accuracy and patient care. Future studies integrating detailed phenotyping with serologic, immunologic, and neurophysiologic profiling will be critical to elucidate causal mechanisms and guide the development of targeted therapies. Moreover, as the authors propose, randomized controlled trials of immunomodulatory interventions in a subset of patients with SFN represent an important future direction and could move the field toward curative rather than palliative approaches in SFN [<span>9</span>].</p><p>We appreciate the opportunity to engage in this important dialog and fully endorse continued collaboration across specialties to better characterize and treat multisystem forms of SFN and related disorders.</p><p><b>Peyton Murin:</b> conceptualization, writing – original draft, writing – review and editing. <b>Stefanie Geisler:</b> writing – review and editing, conceptualization. <b>Nicholas F. Schulze, Vivian D. Gao, and Manouela V. Valtcheva:</b> writing – review and editing.</p><p>There is no funding associated with this letter to the
我们衷心感谢dr。Blitshteyn, Stingl和Schofield对我们最近出版的“揭示隐藏的特征:从以疼痛为中心到多症状的小纤维神经病”发表了深思熟虑和鼓舞人心的评论。我们很高兴我们的发现引起了临床医生的共鸣,他们看到了各种各样的自主神经异常、感染后和自身免疫性疾病。正如他们在信中强调的那样,我们的研究表明,小纤维神经病(SFN)包括广泛的感觉、自主神经和全身症状,这些症状超出了神经性疼痛。Blitshteyn等人强调了考虑SFN全表型谱的重要性,包括疲劳和肌痛,我们的分析认为这是非常普遍和有临床意义的。我们和作者一样对免疫系统在SFN病理生理中的作用感兴趣。疲劳和肌痛是肌痛性脑脊髓炎/慢性疲劳综合征(ME/CFS)、纤维肌痛和长COVID等疾病的定义特征,其中免疫功能障碍和小纤维异常已在一部分患者中被记录[2-6]。这些发现与“肌痛性”SFN亚群的趋同,指出了潜在的共同免疫介导机制,并强调了对临床和生物学上不同的SFN亚型进行系统研究的必要性。目前,大多数症状评估量表几乎只关注疼痛症状[7,8]。然而,正如作者指出的那样,这种狭隘的关注有可能忽视疲劳、肌痛或自主神经异常为主的患者,从而可能延误诊断和治疗。更广泛的认识和系统地将自主神经和全身症状纳入临床评估,再加上皮肤活检和定量自主神经测试等客观措施,可以大大提高诊断准确性和患者护理。未来的研究将详细的表型分析与血清学、免疫学和神经生理学分析结合起来,对于阐明因果机制和指导靶向治疗的发展至关重要。此外,正如作者所提出的那样,对SFN患者进行免疫调节干预的随机对照试验代表了一个重要的未来方向,并可能使SFN bbb领域朝着治愈而不是姑息的方向发展。我们很高兴有机会参与这一重要的对话,并完全支持跨专业继续合作,以更好地表征和治疗多系统形式的SFN和相关疾病。佩顿·穆林:概念化,写作-原稿,写作-审查和编辑。Stefanie Geisler:写作-评论和编辑,概念化。Nicholas F. Schulze, Vivian D. Gao, Manouela V. Valtcheva:写作-评论与编辑。这封给编辑的信没有任何资金来源。最初的研究得到了美国国立卫生研究院/国家推进转化科学中心(UL1 TR002345)和国家癌症研究所(R37CA267905)的资助。作者没有什么可报告的。作者没有什么可报告的。作者声明无利益冲突。数据共享不适用于本文,因为在当前研究中没有生成或分析数据集。
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