The typical clinical practice that neurologists employ to diagnose undifferentiated inflammatory syndromes of the central nervous system (CNS) is first to generate a broad differential diagnosis for each patient and then to send individual tests targeting each possibility. This “candidate-based” approach is often challenging, as the list of potential causes of meningitis and encephalitis is extensive, and many diseases share clinical features. As a result, approximately 50% of patients presenting with acute meningoencephalitis are never given a specific diagnosis. Novel diagnostic methods are needed, particularly those that do not rely upon sending individual tests but rather use tests that broadly screen for the presence of neurologic disease in an unbiased fashion. Such methods would allow for more optimal use of limited biologic specimens such as cerebrospinal fluid (CSF) or brain tissue. In this 2-part podcast, the American Neurological Association investigates the use of unbiased diagnostics in the evaluation of infectious and autoimmune etiologies of meningitis and encephalitis by interviewing Drs Michael Wilson and Samuel Pleasure, 2 neuroimmunologists working in the University of California, San Francisco (UCSF) Department of Neurology and UCSF’s recently formed Center for Next-Gen Precision Diagnostics. Neuroinfectious diseases and autoantibody syndromes are frequent considerations in patients presenting with meningitis or encephalitis, and each carries the potential for a broad differential diagnosis for which unbiased diagnostic techniques may be useful. It is also of paramount interest to develop approaches that would allow rapid discrimination of these 2 broad types of pathophysiology, because the therapeutic interventions are in many cases quite distinct. Metagenomic next generation sequencing (mNGS) is one such method that is clinically available for the diagnosis of CNS infections, developed by the UCSF Center for NextGen Precision Diagnostics. As described by Dr Wilson in Part 1 of ANA Investigates: Pioneering Unbiased Diagnostics, mNGS entails extracting, amplifying, and sequencing all the nucleic acid in a CSF sample. These sequence data are then used to determine the identity of the nonhuman genetic material by cross-referencing the sequences with public databases. This direct-detection diagnostic method is clinically available and provides a broad screen for the presence of a wide range of infections, including bacteria, fungi, and RNA and DNA viruses. In contrast, unbiased techniques for the diagnosis of novel CNS autoantibody syndromes remain research-based. As described by Dr Pleasure in Part 2, the UCSF group developed a discovery pipeline to screen for novel autoantibodies by first exposing rodent brain tissue to a patient’s CSF to determine whether antibodies are present that bind to neural antigens. If the CSF stains neural tissue, a programmable

中文翻译：

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ANA 调查：开创性的无偏见诊断

神经科医师用于诊断中枢神经系统 (CNS) 未分化炎症综合征的典型临床实践是首先为每位患者生成广泛的鉴别诊断，然后针对每种可能性发送单独的测试。这种“基于候选者”的方法通常具有挑战性，因为脑膜炎和脑炎的潜在原因清单很广泛，而且许多疾病具有共同的临床特征。因此，大约 50% 的急性脑膜脑炎患者从未得到明确诊断。需要新的诊断方法，特别是那些不依赖于发送单个测试而是使用以公正的方式广泛筛查神经系统疾病存在的测试的方法。这种方法将允许更优化地使用有限的生物样本，例如脑脊液 (CSF) 或脑组织。在这个由 2 部分组成的播客中，美国神经病学协会通过采访在加利福尼亚大学旧金山分校工作的 2 位神经免疫学家 Michael Wilson 和 Samuel Pleasure 博士，调查了在评估脑膜炎和脑炎的传染性和自身免疫性病因时使用公正的诊断方法（ UCSF）神经病学系和 UCSF 最近成立的下一代精密诊断中心。神经感染性疾病和自身抗体综合征是脑膜炎或脑炎患者的常见考虑因素，每一种都有可能进行广泛的鉴别诊断，而无偏见的诊断技术可能对其有用。开发能够快速区分这两种广泛类型的病理生理学的方法也很重要，因为治疗干预在许多情况下是截然不同的。宏基因组下一代测序 (mNGS) 是一种临床上可用于诊断 CNS 感染的方法，由加州大学旧金山分校 NextGen 精密诊断中心开发。正如威尔逊博士在 ANA Investigates: Pioneering Unbiased Diagnostics 第 1 部分所述，mNGS 需要提取、扩增和测序脑脊液样本中的所有核酸。然后将这些序列数据用于通过将序列与公共数据库交叉引用来确定非人类遗传材料的身份。这种直接检测诊断方法在临床上是可用的，并为各种感染的存在提供了广泛的筛查，包括细菌、真菌、RNA 和 DNA 病毒。相比之下，诊断新型 CNS 自身抗体综合征的公正技术仍然以研究为基础。正如 Pleasure 博士在第 2 部分中所描述的那样，加州大学旧金山分校的小组开发了一个发现管道来筛选新的自身抗体，方法是首先将啮齿动物的脑组织暴露于患者的脑脊液中，以确定是否存在与神经抗原结合的抗体。如果脑脊液染色神经组织，一个可编程的 UCSF 小组开发了一个发现管道来筛选新的自身抗体，首先将啮齿动物的脑组织暴露于患者的脑脊液中，以确定是否存在与神经抗原结合的抗体。如果脑脊液染色神经组织，一个可编程的 UCSF 小组开发了一个发现管道来筛选新的自身抗体，首先将啮齿动物的脑组织暴露于患者的脑脊液中，以确定是否存在与神经抗原结合的抗体。如果脑脊液染色神经组织，一个可编程的