Jacqui Nimmo, Samuel Keat, Louis De Muynck, B. Paul Morgan
Dysregulation of the complement system plays an important role in the pathogenesis of neurodegenerative diseases, including Alzheimer's disease (AD). In post-mortem AD brains, complement is deposited in and around amyloid plaques, and peri-plaque complement activation drives synapse loss in AD mouse models. Studies to date have focused on amyloid pathology; however, aggregated tau is also involved in neuronal loss in AD. Primary tauopathies are characterised by tau pathology in the absence of amyloid. The role of complement in human tauopathies remains largely unexplored. Here, we address this knowledge gap by assessing complement activation in human tauopathy brains using immunohistochemistry and well-characterised detection tools. Post-mortem pre-frontal cortex was obtained from three tauopathy subtypes, Pick's disease (PiD), globular glial tauopathy (GGT) and corticobasal degeneration (CBD) (3–5 cases each). C1q and the complement activation markers iC3b and terminal complement complex (TCC) were assessed by immunohistochemistry and were elevated in all tauopathy cases compared to controls, with C1q and C3b/iC3b deposition particularly prominent on neurons, demonstrating complement activation on these cells. TCC deposits were present on and adjacent neurons in all tauopathy brains examined and were significantly increased compared to controls in CBD and GGT. Uniquely in GGT, abundant deposition of C3b/iC3b on myelin was also observed, implicating complement in GGT-associated demyelination. To validate these findings, complement proteins (C1q, C3, factor B), regulators (factor I, clusterin) and activation products (Ba, C3b/iC3b, and TCC) were measured in brain homogenates by ELISA, revealing significant elevation in C3b/iC3b, Ba, and FI in CBD and GGT cases compared to controls. Together, our data demonstrate complement activation on and adjacent neurons in post-mortem brains from all tauopathy subtypes.
{"title":"Complement dysregulation in human tauopathies","authors":"Jacqui Nimmo, Samuel Keat, Louis De Muynck, B. Paul Morgan","doi":"10.1111/bpa.70017","DOIUrl":"10.1111/bpa.70017","url":null,"abstract":"<p>Dysregulation of the complement system plays an important role in the pathogenesis of neurodegenerative diseases, including Alzheimer's disease (AD). In post-mortem AD brains, complement is deposited in and around amyloid plaques, and peri-plaque complement activation drives synapse loss in AD mouse models. Studies to date have focused on amyloid pathology; however, aggregated tau is also involved in neuronal loss in AD. Primary tauopathies are characterised by tau pathology in the absence of amyloid. The role of complement in human tauopathies remains largely unexplored. Here, we address this knowledge gap by assessing complement activation in human tauopathy brains using immunohistochemistry and well-characterised detection tools. Post-mortem pre-frontal cortex was obtained from three tauopathy subtypes, Pick's disease (PiD), globular glial tauopathy (GGT) and corticobasal degeneration (CBD) (3–5 cases each). C1q and the complement activation markers iC3b and terminal complement complex (TCC) were assessed by immunohistochemistry and were elevated in all tauopathy cases compared to controls, with C1q and C3b/iC3b deposition particularly prominent on neurons, demonstrating complement activation on these cells. TCC deposits were present on and adjacent neurons in all tauopathy brains examined and were significantly increased compared to controls in CBD and GGT. Uniquely in GGT, abundant deposition of C3b/iC3b on myelin was also observed, implicating complement in GGT-associated demyelination. To validate these findings, complement proteins (C1q, C3, factor B), regulators (factor I, clusterin) and activation products (Ba, C3b/iC3b, and TCC) were measured in brain homogenates by ELISA, revealing significant elevation in C3b/iC3b, Ba, and FI in CBD and GGT cases compared to controls. Together, our data demonstrate complement activation on and adjacent neurons in post-mortem brains from all tauopathy subtypes.</p>","PeriodicalId":9290,"journal":{"name":"Brain Pathology","volume":"35 6","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bpa.70017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cynthia Hawkins, Kenneth Aldape, David Capper, Andreas von Deimling, Caterina Giannini, Mark R. Gilbert, Thomas S. Jacques, David Jones, Takashi Komori, David N. Louis, Sabine Mueller, MacLean Nasrallah, Brent A. Orr, Arie Perry, Stefan M. Pfister, Felix Sahm, Chitra Sarkar, Matija Snuderl, David Solomon, Pascale Varlet, Pieter Wesseling, Guido Reifenberger
<p>Classification systems serve to group and organize data according to common relations or affinities so that they may be compared with other data. The classification system used will depend on what the classes are intended to cluster and what data are available to define these classes. Thus, the history and evolution of classifications trace the development of methods used to organize, categorize, and systematize knowledge, organisms, and objects based on shared characteristics. These systems have evolved over centuries, influenced by cultural, scientific, and technological advancements.</p><p>Tumor classifications have similarly evolved alongside advances in medicine, biology, and technology. These systems aim to categorize neoplasms based on various characteristics to improve diagnosis, prognostication, and treatment decisions. The earliest classifications relied primarily on clinical presentation, location, and macroscopic appearance of the cancer. Advances in microscopy and development of tissue staining techniques during the 19th century allowed pathologists to examine the cellular structure of tumors, as exemplified by the work of Virchow [<span>1</span>] who contributed significantly to the understanding of cancer as a disease originating from abnormal cells within the tissue. This era saw the introduction of histological classification systems, in which cancers were categorized based on their presumed tissue and/or cell of origin and the normal cells they resembled. In parallel, the concepts of benign versus malignant tumors were more clearly defined.</p><p>For central nervous system (CNS) tumors particularly gliomas, the early 20th century brought the first broadly recognized classification, published in 1926 by Bailey and Cushing [<span>2</span>]. This approach was based on a detailed study of a large series of brain tumors coupled with medical records of patients that had been followed from presentation to death; the goal was to provide better prognostic information and treatment planning, thus cementing clinical utility as a major endpoint of classification. In the mid-20th century, efforts were undertaken to establish cancer classifications that could be used around the world. The initial World Health Organization (WHO) histologic classification manuals provided guidelines for categorizing tumors by their microscopic appearance and provided a framework for identifying cancer subtypes within specific organs [<span>3</span>].</p><p>The first edition of the WHO classification of CNS tumors was published in 1979 and included a grading system to distinguish tumors with presumed similar histogenesis (e.g., astrocytic) with different degrees of aggressiveness (e.g., pilocytic astrocytoma versus glioblastoma multiforme) [<span>4</span>]. This classification followed WHO Expert Committee on Health Statistics recommendations that specified three necessary elements of a classification: anatomic site, histologic tumor type, and grade as an ind
分类系统的作用是根据共同关系或亲缘关系对数据进行分组和组织,以便与其他数据进行比较。所使用的分类系统将取决于打算聚类的类和定义这些类的可用数据。因此,分类法的历史和演变追溯了基于共同特征来组织、分类和系统化知识、生物和对象的方法的发展。这些系统在文化、科学和技术进步的影响下已经发展了几个世纪。肿瘤分类也随着医学、生物学和技术的进步而发展。这些系统旨在根据不同的特征对肿瘤进行分类,以提高诊断、预测和治疗决策。最早的分类主要依靠临床表现、部位和肿瘤的宏观外观。显微术的进步和19世纪组织染色技术的发展使病理学家能够检查肿瘤的细胞结构,例如Virchow[1]的工作,他对癌症作为一种起源于组织内异常细胞的疾病的理解做出了重大贡献。这个时代引入了组织学分类系统,根据假定的组织和/或细胞起源以及它们相似的正常细胞对癌症进行分类。同时,良性肿瘤和恶性肿瘤的概念也更加明确。对于中枢神经系统(CNS)肿瘤,特别是胶质瘤,20世纪初出现了第一个被广泛认可的分类,1926年由Bailey和Cushing[2]发表。这种方法是基于对大量脑肿瘤的详细研究,并结合患者从出现到死亡的医疗记录;目的是提供更好的预后信息和治疗计划,从而巩固临床效用作为分类的主要终点。20世纪中期,人们开始努力建立可在世界各地使用的癌症分类。世界卫生组织(世卫组织)最初的组织学分类手册提供了根据显微外观对肿瘤进行分类的指南,并提供了在特定器官内识别癌症亚型的框架。WHO第一版中枢神经系统肿瘤分类于1979年出版,其中包括一个分级系统,用于区分推定具有相似组织发生(如星形细胞)和不同侵袭程度(如毛细胞星形细胞瘤和多形性胶质母细胞瘤)的肿瘤。这一分类遵循了世卫组织卫生统计专家委员会的建议,其中规定了分类的三个必要要素:解剖部位、组织学肿瘤类型和作为恶性程度指标的分级。对于中枢神经系统肿瘤,分级所依据的原则一直存在争议(部分仍然存在争议)。z<e:1> lch提出了从0到IV的5个临床恶性肿瘤等级:0级指的是可手术治愈的实质外病变;I级被认为是良性的,但治愈的可能性较小;II至IV级从交界性恶性到高度恶性,通常是致命的,根据自然病程(分别为3-5年、1-3年和0.5-1年)不同,生存期不同。虽然在最近的世卫组织分类中没有完全以这种方式使用,但这将“临床”恶性肿瘤的概念,而不是纯粹的组织学恶性肿瘤,正式纳入了世卫组织随后对中枢神经系统肿瘤的分类。然而,随着时间的推移,随着治疗模式的改变和许多中枢神经系统肿瘤预后的改善,这仍然是一个有点难以实施的概念。肿瘤分级是基于当前结果还是基于“自然史”(定义为肿瘤未经治疗的潜在临床病程)仍在争论中。这两种系统都有其固有的问题——前者可能需要随着治疗模式的变化而频繁地改变分级,甚至根据患者诊断的可用治疗方法对同一肿瘤进行不同的分级。当“自然史”与目前治疗的既定临床结果之间存在显著差距时,后者可能导致混淆(例如,wnt激活的髓母细胞瘤仍被认为是CNS WHO IV级,尽管目前治疗的长期生存率超过90%)。世卫组织第二版和第三版中枢神经系统肿瘤分类(分别于1993年和2000年出版)随着临床和生物学知识的增加而发展[7,8]。世卫组织第四版中枢神经系统肿瘤分类(2007年)受到现在广泛使用免疫组织化学更准确地识别细胞类型和生理相关细胞特征(如增殖[9])的显著影响。 这开启了一个分类日益复杂的时代,与此同时,技术的发展也更加迅速。在2007年世卫组织的分类中,就识别为一种独特肿瘤类型所应满足的最低标准奠定了一些基础(尽管在使用分子检测之前)。这些是:来自不同机构的两份或两份以上的报告,描述了肿瘤类型,以及不同的形态,位置,年龄分布和生物学行为。值得注意的是,组织学变异(现在的亚型)和模式的概念得到了认可:亚型在组织学上是可识别的,与临床结果有一定的相关性,但仍然是肿瘤类型的一部分;组织学上可识别的模式因此值得注意,但没有明显的临床意义。这些概念也可能适用于分子数据。在过去二十年中,高通量基因组技术的出现,如下一代测序,进一步改变了癌症分类。像癌症基因组图谱(TCGA; https://www.cancer.gov/ccg/research/genome-sequencing/tcga)和国际癌症基因组联盟(ICGC;现在的ICGC- argo https://www.icgc-argo.org/)这样的大型项目绘制了许多癌症的遗传改变,导致了除了组织学和免疫组织化学之外,基于分子特征的分类的发展。2014年,国际神经病理学会(International Society of Neuropathology-Haarlem)发布了中枢神经系统肿瘤分类和分级共识指南b[10],神经肿瘤学界首次将分子特征纳入肿瘤分类,随后将其纳入修订后的第4版WHO分类[11,12]。这导致一些新的肿瘤类型被引入世卫组织的中枢神经系统肿瘤分类,以及一些缺乏足够公开证据来做出决定的类型(所谓的次级判断)。然而,满足新的肿瘤类型定义所需的具体标准并没有明确规定。随着越来越多的先进技术可以应用于分类并用于扩展科学知识,每次分类更新往往变得更加复杂。随着转录组学,特别是表观遗传学(在这种情况下,DNA甲基化)谱分析的使用越来越多,肿瘤分类变得更加精细,如第5版(2021)WHO CNS肿瘤分类[13,14]所示:有更多的肿瘤类型和更多的推荐技术来诊断这些类型。尽管如此,尽管这些肿瘤类型之间存在可检测到的分子差异,有时非常有意义(例如,wnt激活与3组髓母细胞瘤),但这些差异可能并不总是转化为临床行为或治疗方法的变化(例如,经典与间充质idh野生型胶质母细胞瘤)。因此,这种情况提出了一个问题:如何最有意义地定义肿瘤类型?此外,是什么构成了新的肿瘤类型,而不是现有类型的预后/分级标记?这些不是新问题,而是每当新技术产生关于一组肿瘤的新数据层时就会出现的问题。肿瘤根据共性(如临床、组织学或分子特征)进行分组;随着分子和临床研究的增加,一组肿瘤成员之间的差异将会出现。问题是,现在或将来在生物学上或临床上具有重要意义的相对较小的差异,何时才能保证更精确地指定肿瘤类型。这是病理学和肿瘤学领域中“合并者”和“分裂者”之间长期存在的争论。文献具有明显的分裂者偏差,因为更容易发表表明子分类方法与统计显着差异相关的发现;因此,在过去的十年中,大多数研究文章建议进一步的诊断分类区分的有效性。相比之下,临床和治疗指南倾向于将分子不同但目前没有明显不同结果或治疗方法的肿瘤归为一类。例如,idh野生型胶质母细胞瘤的术后治疗主要由MGMT启动子甲基化状态指导,而不是由组织学或DNA甲基化亚型指导。重要的是,没有明确的规则指导将这些区别纳入分类。例如,什么时候肿瘤与邻近的肿瘤有足够的区别,可以被认为是一种单独的疾病,什么时候特定肿瘤类型的异质性足以将该群体细分为更均匀的亚群(即亚型)?值得注意的是,在现实中,使用越来越先进的技术对肿瘤进行分类,并没有找到“基本真理”。 另一方面,大多数人会同意理想情况下(1)改变肿瘤类型的概念及其作为不同实体的识别应该具有预后和预测意义,(2)分类的复杂性不应超过其临床实用性。尽管如此,肿瘤类型之间的分子差异,即使现在没有临床意义,
{"title":"cIMPACT-NOW update 10: Recommendations for defining new types for central nervous system tumor classification","authors":"Cynthia Hawkins, Kenneth Aldape, David Capper, Andreas von Deimling, Caterina Giannini, Mark R. Gilbert, Thomas S. Jacques, David Jones, Takashi Komori, David N. Louis, Sabine Mueller, MacLean Nasrallah, Brent A. Orr, Arie Perry, Stefan M. Pfister, Felix Sahm, Chitra Sarkar, Matija Snuderl, David Solomon, Pascale Varlet, Pieter Wesseling, Guido Reifenberger","doi":"10.1111/bpa.70018","DOIUrl":"10.1111/bpa.70018","url":null,"abstract":"<p>Classification systems serve to group and organize data according to common relations or affinities so that they may be compared with other data. The classification system used will depend on what the classes are intended to cluster and what data are available to define these classes. Thus, the history and evolution of classifications trace the development of methods used to organize, categorize, and systematize knowledge, organisms, and objects based on shared characteristics. These systems have evolved over centuries, influenced by cultural, scientific, and technological advancements.</p><p>Tumor classifications have similarly evolved alongside advances in medicine, biology, and technology. These systems aim to categorize neoplasms based on various characteristics to improve diagnosis, prognostication, and treatment decisions. The earliest classifications relied primarily on clinical presentation, location, and macroscopic appearance of the cancer. Advances in microscopy and development of tissue staining techniques during the 19th century allowed pathologists to examine the cellular structure of tumors, as exemplified by the work of Virchow [<span>1</span>] who contributed significantly to the understanding of cancer as a disease originating from abnormal cells within the tissue. This era saw the introduction of histological classification systems, in which cancers were categorized based on their presumed tissue and/or cell of origin and the normal cells they resembled. In parallel, the concepts of benign versus malignant tumors were more clearly defined.</p><p>For central nervous system (CNS) tumors particularly gliomas, the early 20th century brought the first broadly recognized classification, published in 1926 by Bailey and Cushing [<span>2</span>]. This approach was based on a detailed study of a large series of brain tumors coupled with medical records of patients that had been followed from presentation to death; the goal was to provide better prognostic information and treatment planning, thus cementing clinical utility as a major endpoint of classification. In the mid-20th century, efforts were undertaken to establish cancer classifications that could be used around the world. The initial World Health Organization (WHO) histologic classification manuals provided guidelines for categorizing tumors by their microscopic appearance and provided a framework for identifying cancer subtypes within specific organs [<span>3</span>].</p><p>The first edition of the WHO classification of CNS tumors was published in 1979 and included a grading system to distinguish tumors with presumed similar histogenesis (e.g., astrocytic) with different degrees of aggressiveness (e.g., pilocytic astrocytoma versus glioblastoma multiforme) [<span>4</span>]. This classification followed WHO Expert Committee on Health Statistics recommendations that specified three necessary elements of a classification: anatomic site, histologic tumor type, and grade as an ind","PeriodicalId":9290,"journal":{"name":"Brain Pathology","volume":"35 6","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bpa.70018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patients with late-onset (LO) multiple system atrophy (MSA), whose initial symptoms appear at age 75 years or older, are more common than previously assumed, but their clinicopathological characteristics remain unclear. We aimed to clarify the clinicopathological features of LO-MSA. Of 102 patients with autopsy-confirmed MSA, 5 were identified as having LO-MSA and 24 as having usual-age-onset MSA (UO-MSA) with a similar disease duration. On the basis of previous reports, we defined UO-MSA as the appearance of initial symptoms between the ages of 55 and 65 years. We compared the clinical pictures of the two groups and assessed their histopathological features using quantitative and semi-quantitative methods. The investigated features included the severity of degeneration in the striatonigral (StrN) and olivopontocerebellar (OPC) systems, the numbers of neurons in the brainstem autonomic and spinal intermediolateral nuclei, and the density of α-synuclein-immunopositive inclusions in the putamen, inferior olivary nucleus, and ventrolateral medulla (VLM). Most patients with both LO-MSA and UO-MSA exhibited the MSA-olivopontocerebellar atrophy (OPCA) subtype (3/5 and 18/24, respectively). The median disease duration for LO-MSA patients was 5.5 years, which was comparable to that for patients in our cohort who had developed symptoms below 75 years of age. Pathologically, degeneration of the StrN and OPC systems in LO-MSA was less severe than that observed in UO-MSA. Quantitative analysis revealed better preservation of neuron numbers in the brainstem autonomic nuclei in LO-MSA than in UO-MSA, with a significantly higher number of serotonergic neurons in the VLM (p = 0.013). The density of α-synuclein-positive inclusions in the putamen was significantly lower in LO-MSA than in UO-MSA (p < 0.001). Neuronal degeneration in LO-MSA may progress more slowly than in UO-MSA. Accordingly, the prognosis of LO-MSA may not necessarily be less favorable than that of MSA generally, especially with appropriate care.
{"title":"Late-onset multiple system atrophy: Neuropathological features associated with slow disease progression","authors":"Misato Ozawa, Rie Saito, Takuya Konno, Yasuko Kuroha, Tetsuhiko Ikeda, Akio Yokoseki, Takashi Tani, Tomoe Sato, Jiro Idezuka, Reiji Koide, Shigeru Fujimoto, Osamu Onodera, Mari Tada, Akiyoshi Kakita","doi":"10.1111/bpa.70016","DOIUrl":"10.1111/bpa.70016","url":null,"abstract":"<p>Patients with late-onset (LO) multiple system atrophy (MSA), whose initial symptoms appear at age 75 years or older, are more common than previously assumed, but their clinicopathological characteristics remain unclear. We aimed to clarify the clinicopathological features of LO-MSA. Of 102 patients with autopsy-confirmed MSA, 5 were identified as having LO-MSA and 24 as having usual-age-onset MSA (UO-MSA) with a similar disease duration. On the basis of previous reports, we defined UO-MSA as the appearance of initial symptoms between the ages of 55 and 65 years. We compared the clinical pictures of the two groups and assessed their histopathological features using quantitative and semi-quantitative methods. The investigated features included the severity of degeneration in the striatonigral (StrN) and olivopontocerebellar (OPC) systems, the numbers of neurons in the brainstem autonomic and spinal intermediolateral nuclei, and the density of α-synuclein-immunopositive inclusions in the putamen, inferior olivary nucleus, and ventrolateral medulla (VLM). Most patients with both LO-MSA and UO-MSA exhibited the MSA-olivopontocerebellar atrophy (OPCA) subtype (3/5 and 18/24, respectively). The median disease duration for LO-MSA patients was 5.5 years, which was comparable to that for patients in our cohort who had developed symptoms below 75 years of age. Pathologically, degeneration of the StrN and OPC systems in LO-MSA was less severe than that observed in UO-MSA. Quantitative analysis revealed better preservation of neuron numbers in the brainstem autonomic nuclei in LO-MSA than in UO-MSA, with a significantly higher number of serotonergic neurons in the VLM (<i>p</i> = 0.013). The density of α-synuclein-positive inclusions in the putamen was significantly lower in LO-MSA than in UO-MSA (<i>p</i> < 0.001). Neuronal degeneration in LO-MSA may progress more slowly than in UO-MSA. Accordingly, the prognosis of LO-MSA may not necessarily be less favorable than that of MSA generally, especially with appropriate care.</p>","PeriodicalId":9290,"journal":{"name":"Brain Pathology","volume":"35 5","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bpa.70016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144101424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thank you very much for presenting this instructive case, which demonstrates classical features of anti-synthetase syndrome (ASS) through its clinical triad (arthritis, myositis, and interstitial lung disease) and characteristic muscle pathology (perifascicular necrosis with MHC-II overexpression). We would like to provide the following insights based on our experience:
In our previous studies, when anti-Ha antibodies were identified via immunoblotting, we further validated results using cell-based assays (CBA) and immunoprecipitation (IP). However, significant discrepancies were observed across these methods. For instance, some samples showed strong positivity in IP but weak reactivity in CBA, while others exhibited faint IP signals despite prominent immunoblot bands. We hypothesize that these inconsistencies may arise from: (1) variations in the conformational structure of the Ha-antigen complex across different platforms; (2) technical differences in antigen presentation and assay conditions. While IP remains the current gold standard, our findings highlight the need for harmonized protocols to improve cross-method reproducibility.
Although the classic ASS triad and perifascicular necrosis are well recognized, our cohort of anti-Ha-positive patients rarely presented with such prototypical features as described in this report by Marie-Thérèse Holzer et al. Potential explanations for this divergence include: (1) Selection bias: there might be some differences in patient referral patterns between neuromuscular centers (focused on myopathy subtypes) and rheumatology centers (prioritizing systemic manifestations); (2) Genetic predispositions: Population-specific HLA haplotypes or modifier genes may influence phenotypic expression.
We aim to publish our previous findings to raise awareness of anti-Ha-associated ASS heterogeneity and encourage multicenter collaborative efforts to validate these observations across diverse populations. Enhanced recognition of anti-Ha antibody cases through interdisciplinary collaboration will ultimately refine the clinicopathological profile of this rare ASS subtype and optimize therapeutic strategies.
{"title":"Comments to the “Letter to the Editor” for the manuscript titled “Clinico-sero-pathological characteristics of anti-Ha antisynthetase syndrome”","authors":"Bing Zhao, Lining Zhang, Tingjun Dai","doi":"10.1111/bpa.70014","DOIUrl":"10.1111/bpa.70014","url":null,"abstract":"<p>Thank you very much for presenting this instructive case, which demonstrates classical features of anti-synthetase syndrome (ASS) through its clinical triad (arthritis, myositis, and interstitial lung disease) and characteristic muscle pathology (perifascicular necrosis with MHC-II overexpression). We would like to provide the following insights based on our experience:</p><p>In our previous studies, when anti-Ha antibodies were identified via immunoblotting, we further validated results using cell-based assays (CBA) and immunoprecipitation (IP). However, significant discrepancies were observed across these methods. For instance, some samples showed strong positivity in IP but weak reactivity in CBA, while others exhibited faint IP signals despite prominent immunoblot bands. We hypothesize that these inconsistencies may arise from: (1) variations in the conformational structure of the Ha-antigen complex across different platforms; (2) technical differences in antigen presentation and assay conditions. While IP remains the current gold standard, our findings highlight the need for harmonized protocols to improve cross-method reproducibility.</p><p>Although the classic ASS triad and perifascicular necrosis are well recognized, our cohort of anti-Ha-positive patients rarely presented with such prototypical features as described in this report by Marie-Thérèse Holzer et al. Potential explanations for this divergence include: (1) Selection bias: there might be some differences in patient referral patterns between neuromuscular centers (focused on myopathy subtypes) and rheumatology centers (prioritizing systemic manifestations); (2) Genetic predispositions: Population-specific HLA haplotypes or modifier genes may influence phenotypic expression.</p><p>We aim to publish our previous findings to raise awareness of anti-Ha-associated ASS heterogeneity and encourage multicenter collaborative efforts to validate these observations across diverse populations. Enhanced recognition of anti-Ha antibody cases through interdisciplinary collaboration will ultimately refine the clinicopathological profile of this rare ASS subtype and optimize therapeutic strategies.</p><p><b>Bing Zhao</b>: Writing—Original draft preparation. <b>Lining Zhang, Tingjun Dai</b>: Writing—Reviewing and Editing.</p>","PeriodicalId":9290,"journal":{"name":"Brain Pathology","volume":"35 5","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bpa.70014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144076081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marie-Therese Holzer, Robert Biesen, Sarah Tansley, Carsten Dittmayer, Werner Stenzel, Udo Schneider
<p>With great interest, we read the article on the clinico-sero-pathological characteristics of anti-Ha antisynthetase syndrome by Zhao et al. [<span>1</span>].</p><p>The authors describe 12 patients with anti-Ha as a single myositis-specific antibody [<span>1</span>]. In light of this manuscript, we would like to add a report and discuss an anti-Ha-positive patient (a 39-years-old female), who was diagnosed and treated at the university hospital Charité Berlin with severe antisynthetase syndrome (ASyS).</p><p>The patient initially presented in 2023 with arthralgia and scaly skin on her palms (see Figure 1A) and was diagnosed with psoriatic arthritis. In the following months, she developed a dry cough and myalgia, and subsequently, in early 2024, progressive dyspnoea and night sweats. Because of the existing prednisolone and TNF-inhibitor treatment for supposed psoriatic arthritis, an infection with <i>pneumocystis jirovecii</i> was suspected. Following a thorough and negative infection screen, the patient was ultimately transferred to the intensive care unit of the Charité with acute respiratory distress syndrome (ARDS) and evaluated for possible lung transplantation (see Figure 1D). Because of progressive respiratory insufficiency, high-dose glucocorticosteroids as well as cyclophosphamide were initiated. The suspected diagnosis was revised to idiopathic inflammatory myopathy (IIM) based on the clinical presentation with arthritis, myalgia with elevated creatine kinase (CK, 939 U/L), scaly exanthema (retrospectively identified as mechanic hands) and rapidly progressive interstitial lung disease (RP-ILD). Immunofluorescence on HEp2 cells revealed a speckled cytoplasmic pattern with a titre of 1:640 (see Figure 1B). Despite repetitive testing of myositis-specific and myositis-associated antibodies with commercial line blots, only anti-Ro52 antibodies were identified. Therefore, after muscle MRI showing patchy oedema and fasciitis, a muscle biopsy of the M. quadriceps was performed. This revealed a histopathological pattern consistent with ASyS: A mild but typical pattern of perifascicular necrosis and atrophy, as well as positive MHC class I and II staining with a perifascicular pattern (particularly for MHC class II) (see Figure 2).</p><p>Combined, the clinical symptoms with a complete clinical triad (Arthritis, Myositis, ILD [<span>2, 3</span>]) and the muscle biopsy consistent with ASyS led to the diagnosis of ASyS [<span>4</span>]. Hence, treatment was expanded to include rituximab (RTX), as a good response to RTX in ASyS had been reported [<span>4, 5</span>]. To search thoroughly for possible autoantibodies in this apparent myositis-specific antibody-negative case, radioimmunoprecipitation was performed at the University of Bath [<span>6</span>] and anti-Ha-antibodies were identified (see Figure 1C). Following RTX therapy, the patient experienced significant improvement of her ILD (see early follow-up CT, Figure 1D). On subsequent outpatient
{"title":"Correspondence to: Clinico-sero-pathological characteristics of anti-Ha antisynthetase syndrome","authors":"Marie-Therese Holzer, Robert Biesen, Sarah Tansley, Carsten Dittmayer, Werner Stenzel, Udo Schneider","doi":"10.1111/bpa.70015","DOIUrl":"10.1111/bpa.70015","url":null,"abstract":"<p>With great interest, we read the article on the clinico-sero-pathological characteristics of anti-Ha antisynthetase syndrome by Zhao et al. [<span>1</span>].</p><p>The authors describe 12 patients with anti-Ha as a single myositis-specific antibody [<span>1</span>]. In light of this manuscript, we would like to add a report and discuss an anti-Ha-positive patient (a 39-years-old female), who was diagnosed and treated at the university hospital Charité Berlin with severe antisynthetase syndrome (ASyS).</p><p>The patient initially presented in 2023 with arthralgia and scaly skin on her palms (see Figure 1A) and was diagnosed with psoriatic arthritis. In the following months, she developed a dry cough and myalgia, and subsequently, in early 2024, progressive dyspnoea and night sweats. Because of the existing prednisolone and TNF-inhibitor treatment for supposed psoriatic arthritis, an infection with <i>pneumocystis jirovecii</i> was suspected. Following a thorough and negative infection screen, the patient was ultimately transferred to the intensive care unit of the Charité with acute respiratory distress syndrome (ARDS) and evaluated for possible lung transplantation (see Figure 1D). Because of progressive respiratory insufficiency, high-dose glucocorticosteroids as well as cyclophosphamide were initiated. The suspected diagnosis was revised to idiopathic inflammatory myopathy (IIM) based on the clinical presentation with arthritis, myalgia with elevated creatine kinase (CK, 939 U/L), scaly exanthema (retrospectively identified as mechanic hands) and rapidly progressive interstitial lung disease (RP-ILD). Immunofluorescence on HEp2 cells revealed a speckled cytoplasmic pattern with a titre of 1:640 (see Figure 1B). Despite repetitive testing of myositis-specific and myositis-associated antibodies with commercial line blots, only anti-Ro52 antibodies were identified. Therefore, after muscle MRI showing patchy oedema and fasciitis, a muscle biopsy of the M. quadriceps was performed. This revealed a histopathological pattern consistent with ASyS: A mild but typical pattern of perifascicular necrosis and atrophy, as well as positive MHC class I and II staining with a perifascicular pattern (particularly for MHC class II) (see Figure 2).</p><p>Combined, the clinical symptoms with a complete clinical triad (Arthritis, Myositis, ILD [<span>2, 3</span>]) and the muscle biopsy consistent with ASyS led to the diagnosis of ASyS [<span>4</span>]. Hence, treatment was expanded to include rituximab (RTX), as a good response to RTX in ASyS had been reported [<span>4, 5</span>]. To search thoroughly for possible autoantibodies in this apparent myositis-specific antibody-negative case, radioimmunoprecipitation was performed at the University of Bath [<span>6</span>] and anti-Ha-antibodies were identified (see Figure 1C). Following RTX therapy, the patient experienced significant improvement of her ILD (see early follow-up CT, Figure 1D). On subsequent outpatient","PeriodicalId":9290,"journal":{"name":"Brain Pathology","volume":"35 5","pages":""},"PeriodicalIF":6.2,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bpa.70015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143970525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jessica A. Beck, Christina Mazcko, Sara Belluco, Mireille Bitar, Daniel Brat, Jonathan W. Bush, Rati Chkheidze, Kara N. Corps, Chad Frank, Caterina Giannini, Craig Horbinski, Jason T. Huse, Jennifer W. Koehler, Andrew D. Miller, C. Ryan Miller, M. Gerard O'Sullivan, Joanna J. Phillips, Daniel R. Rissi, Courtney R. Schott, Anat Stemmer-Rachamimov, Stephen Yip, Amy K. LeBlanc
Comparative pathology boards bring together anatomic pathologists with expertise in canine and human histology to identify shared features, including immune or TME components, tumor subtypes, or prognostic tissue biomarkers. This article summarizes feedback to improve future initiatives and enhance the translational relevance of comparative oncology for human patients.