Multi-omic approaches for biomarker discovery in Moyamoya disease

Laura Gatti, Anna Bersano, Gemma Gorla, Giuliana Pollaci, Tatiana Carrozzini, Antonella Potenza
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The specific mechanism underlying both the progressive arterial wall thickening and the spontaneous angiogenesis of the defective moyamoya vessels remains poorly understood. Moreover, the lack of reliable animal or cellular pre-clinical models and the heterogeneous data on MMD pathophysiology have hampered the clinical validation of powerful biomarkers, as well as the development of tailored therapeutic options.</p><p>The previous investigations aimed at biomarker discovery mainly addressed patients’ peripheral blood samples, which may not reflect the real pathological changes of MMD cerebral vessels. On the other hand, prior interesting studies involving cerebral artery specimens (e.g. middle cerebral artery [MCA]) were performed through RNA microarray techniques, which have several limitations as compared to high-throughput RNA sequencing (RNA-seq). As an example, the long noncoding RNA profile of MMD patients’ MCA provided data regarding antibacterial response, T-cell receptor signalling pathway and cytokine production.<span><sup>1</sup></span> Interestingly, Xu et al. carried out an RNA-seq analysis of MMD patients’ MCA, as compared to atherosclerosis-associated intracranial artery stenosis/occlusion. The authors identified several differential expressed genes mainly involved in extracellular matrix organization and mitochondrial function, thus highlighting novel insights into disease pathogenesis.<span><sup>2</sup></span></p><p>Since the challenging sampling of cerebral artery specimens for transcriptomic studies, other ultrasensitive techniques were recently carried out for molecular profiling of circulating biomarkers from cerebrospinal fluid (CSF) or blood. The study by Ota et al. through a next-generation sequencing (NGS) approach demonstrated that specific changes occurred in the expression levels of extracellular vesicle-derived microRNAs (miRNAs), extracted from intracranial CSF of MMD patients when compared to controls.<span><sup>3</sup></span> The authors suggested that MMD has a specific regulatory mechanism for angiogenesis, different from that found in other ischemic disorders. Proteomic approaches towards MMD patients’ circulating fluids have already been reported. Tandem mass tag (TMT)-labelled proteome analysis was performed on serum-derived exosomes, extracted from pure ischemic or hemorrhagic MMD patients and healthy controls.<span><sup>4</sup></span> Bioinformatic analysis revealed deregulated cell growth/maintenance and indicated disturbed actin dynamics in MMD versus control subjects, as well as immunity dysfunction in hemorrhagic MMD. Similarly, serum proteins were identified using TMT labelling combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS).<span><sup>5</sup></span> Among the differentially expressed proteins, apolipoprotein E (APOE) was selected and evaluated to determine its feasibility as a candidate diagnostic marker of MMD. Another study recently carried out by He and colleagues investigated the potential impact of abnormally expressed serum proteins in MMD pathogenesis.<span><sup>6</sup></span> The authors explored a large number of MMD serum samples by using a data-independent acquisition MS proteomic approach and found differences among MMD subgroups versus control subjects. Interestingly, the quantitative analysis revealed that Filamin A (FLNA) was significantly up-regulated in all MMD subgroups when compared to control subjects. Such evidence is particularly relevant if considering the results obtained through a comprehensive, label-free, quantitative MS-based proteomic characterization of <i>dura mater</i> samples from MMD patients.<span><sup>7</sup></span> Indeed, exactly FLNA emerged among the most abundant detected proteins and was indicated as a second hit gene in MMD pathogenesis, by promoting MMD-like vascular formation. It is a large actin-binding protein, important for cell motility due to providing scaffolds for multiple cytoskeletal proteins.</p><p>Despite numerous findings collected in the proteomics field, very little is known about the overall lipidomics of MMD, or changes in the lipid composition in patients’ circulating fluids. 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Laura Gatti, Anna Bersano, Gemma Gorla, Giuliana Pollaci, Tatiana Carrozzini, and Antonella Potenza: Critical revision, editing and approval of the final version of the article.</p><p>The authors declare no conflict of interest.</p><p>Not Applicable.</p>","PeriodicalId":72605,"journal":{"name":"Clinical and translational discovery","volume":"4 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ctd2.270","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical and translational discovery","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ctd2.270","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Moyamoya disease (MMD) is a rare cerebrovascular condition characterized by a chronic and progressive narrowing of the terminal portion of the bilateral internal carotid arteries, causing the formation of an abnormal vascular network. These compensatory brain vessels often prove insufficient, leading MMD patients to severe ischemic or hemorrhagic clinical manifestations. Surgical treatment, mainly based on direct and indirect revascularization, represents the preferred procedure for MMD patients until now, for improving cerebral hemodynamics and decreasing the pathological collateral network development. The specific mechanism underlying both the progressive arterial wall thickening and the spontaneous angiogenesis of the defective moyamoya vessels remains poorly understood. Moreover, the lack of reliable animal or cellular pre-clinical models and the heterogeneous data on MMD pathophysiology have hampered the clinical validation of powerful biomarkers, as well as the development of tailored therapeutic options.

The previous investigations aimed at biomarker discovery mainly addressed patients’ peripheral blood samples, which may not reflect the real pathological changes of MMD cerebral vessels. On the other hand, prior interesting studies involving cerebral artery specimens (e.g. middle cerebral artery [MCA]) were performed through RNA microarray techniques, which have several limitations as compared to high-throughput RNA sequencing (RNA-seq). As an example, the long noncoding RNA profile of MMD patients’ MCA provided data regarding antibacterial response, T-cell receptor signalling pathway and cytokine production.1 Interestingly, Xu et al. carried out an RNA-seq analysis of MMD patients’ MCA, as compared to atherosclerosis-associated intracranial artery stenosis/occlusion. The authors identified several differential expressed genes mainly involved in extracellular matrix organization and mitochondrial function, thus highlighting novel insights into disease pathogenesis.2

Since the challenging sampling of cerebral artery specimens for transcriptomic studies, other ultrasensitive techniques were recently carried out for molecular profiling of circulating biomarkers from cerebrospinal fluid (CSF) or blood. The study by Ota et al. through a next-generation sequencing (NGS) approach demonstrated that specific changes occurred in the expression levels of extracellular vesicle-derived microRNAs (miRNAs), extracted from intracranial CSF of MMD patients when compared to controls.3 The authors suggested that MMD has a specific regulatory mechanism for angiogenesis, different from that found in other ischemic disorders. Proteomic approaches towards MMD patients’ circulating fluids have already been reported. Tandem mass tag (TMT)-labelled proteome analysis was performed on serum-derived exosomes, extracted from pure ischemic or hemorrhagic MMD patients and healthy controls.4 Bioinformatic analysis revealed deregulated cell growth/maintenance and indicated disturbed actin dynamics in MMD versus control subjects, as well as immunity dysfunction in hemorrhagic MMD. Similarly, serum proteins were identified using TMT labelling combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS).5 Among the differentially expressed proteins, apolipoprotein E (APOE) was selected and evaluated to determine its feasibility as a candidate diagnostic marker of MMD. Another study recently carried out by He and colleagues investigated the potential impact of abnormally expressed serum proteins in MMD pathogenesis.6 The authors explored a large number of MMD serum samples by using a data-independent acquisition MS proteomic approach and found differences among MMD subgroups versus control subjects. Interestingly, the quantitative analysis revealed that Filamin A (FLNA) was significantly up-regulated in all MMD subgroups when compared to control subjects. Such evidence is particularly relevant if considering the results obtained through a comprehensive, label-free, quantitative MS-based proteomic characterization of dura mater samples from MMD patients.7 Indeed, exactly FLNA emerged among the most abundant detected proteins and was indicated as a second hit gene in MMD pathogenesis, by promoting MMD-like vascular formation. It is a large actin-binding protein, important for cell motility due to providing scaffolds for multiple cytoskeletal proteins.

Despite numerous findings collected in the proteomics field, very little is known about the overall lipidomics of MMD, or changes in the lipid composition in patients’ circulating fluids. Nevertheless, it has been recently reported that the main susceptibility genetic factor identified in MMD patients (i.e. Ring Finger Protein 213) is involved in lipid metabolism.8 A previously performed untargeted lipidomic analysis showed a cumulative depletion of lipid assets in plasma of MMD patients, as compared to healthy donors.9 Specifically, a decrease in membrane complex glycosphingolipids circulating in MMD plasma, with respect to healthy donors, was observed, likely suggestive of cerebral cellular recruitment.

More recently, He and colleagues reported a comprehensive and detailed multi-omics analysis of MMD molecular profiles, including genomics (whole-exome sequencing), transcriptomics (RNA-seq) and metabolomics (ultra-high-performance LC-high-resolution MS, UHPLC-HRMS) approaches (Figure 1).10 Notably, the untargeted metabolomics suggested lysophosphatidylcholine (i.e. LPC 16:1-2) as potential diagnostic blood (i.e. serum) biomarker, able to identify MMD patients from healthy subjects and to differentiate ischemic MMD patients from the hemorrhagic ones. LPC is a bioactive lipid known to cause inflammation, endothelial dysfunction and proliferation/migration of vascular smooth muscle cells, displaying effects on angiogenesis function and vascular wall integrity of cerebral vessels. Interestingly, RNA-seq analysis of MMD neurosurgical specimens (e.g. superficial temporal artery; MCA) revealed that the gene expression of LPC-related enzymes (i.e. phospholipase A1 Member A; phospholipase A2 group IIA) was consistently decreased, thus corroborating the lipidomic findings. Such evidence was also confirmed by conventional immunoassays aimed at determining the expression levels of these LPC-related enzymes in MMD patients’ peripheral blood. The study conclusions confirmed that multi-omic signatures are associated with MMD pathophysiological features and suggested a candidate blood biomarker for MMD patients’ stratification.

Data shown in all these research studies strongly underlined the crucial role that omics approaches can exert in attempting to better clarify MMD pathogenesis (Figure 2). Indeed, omics techniques coupled and sustained by experimental in vitro models could pave the way for the search for specific MMD biological markers, hopefully leading to improved disease diagnosis and screening.

In this regard, multi-omic approaches may turn out to be crucial in patients’ risk stratification and precision medicine, allowing for the selection and customization of medical treatment based on individual signatures. In addition, combining multiple omics strategies may also shed light on potential novel targets for MMD therapeutic intervention, as shown above for FLNA and LPC.6, 7, 10

Laura Gatti: Conceptualization; original draft writing and editing. Gemma Gorla: Artworks. Laura Gatti, Anna Bersano, Gemma Gorla, Giuliana Pollaci, Tatiana Carrozzini, and Antonella Potenza: Critical revision, editing and approval of the final version of the article.

The authors declare no conflict of interest.

Not Applicable.

Abstract Image

发现莫亚莫亚病生物标志物的多组学方法
莫亚莫亚病(MMD)是一种罕见的脑血管疾病,其特征是双侧颈内动脉末端部分慢性进行性狭窄,导致异常血管网络的形成。这些代偿性脑血管往往不足,导致 MMD 患者出现严重的缺血性或出血性临床表现。迄今为止,以直接和间接血管再通为主的手术治疗是 MMD 患者的首选治疗方法,可改善脑血流动力学,减少病理侧支网络的形成。人们对有缺陷的 moyamoya 血管的动脉壁逐渐增厚和自发性血管生成的具体机制仍然知之甚少。此外,由于缺乏可靠的动物或细胞临床前模型,以及有关MMD病理生理学的数据参差不齐,这都阻碍了强有力的生物标志物的临床验证,以及量身定制的治疗方案的开发。另一方面,之前涉及大脑动脉标本(如大脑中动脉[MCA])的有趣研究是通过 RNA 微阵列技术进行的,与高通量 RNA 测序(RNA-seq)相比,该技术存在一些局限性。例如,MMD 患者 MCA 的长非编码 RNA 图谱提供了有关抗菌反应、T 细胞受体信号通路和细胞因子产生的数据1。作者发现了几个主要涉及细胞外基质组织和线粒体功能的差异表达基因,从而凸显了对疾病发病机制的新见解。2 由于脑动脉标本的转录组学研究取样具有挑战性,最近又开展了其他超灵敏技术,对脑脊液(CSF)或血液中的循环生物标志物进行分子谱分析。Ota 等人通过新一代测序(NGS)方法进行的研究表明,与对照组相比,从 MMD 患者颅内 CSF 中提取的细胞外囊源性 microRNAs(miRNAs)的表达水平发生了特殊变化。目前已有关于 MMD 患者循环液蛋白质组学方法的报道。4 生物信息学分析显示,与对照组相比,MMD 患者的细胞生长/维持失调,肌动蛋白动力学紊乱,出血性 MMD 患者免疫功能失调。同样,利用 TMT 标记结合液相色谱-串联质谱法(LC-MS/MS)对血清蛋白进行了鉴定。5 在差异表达的蛋白中,选择并评估了载脂蛋白 E(APOE),以确定其作为 MMD 候选诊断标志物的可行性。He 及其同事最近开展的另一项研究调查了异常表达的血清蛋白在 MMD 发病机制中的潜在影响。6 作者采用数据无关的采集 MS 蛋白质组学方法,对大量 MMD 血清样本进行了检测,发现 MMD 亚组与对照组之间存在差异。有趣的是,定量分析显示,与对照组相比,所有 MMD 亚组中的丝胶素 A(FLNA)都明显上调。如果考虑到对 MMD 患者硬脑膜样本进行的全面、无标记、定量 MS 蛋白质组学表征所获得的结果,这些证据就显得尤为重要7 。事实上,FLNA 正是检测到的最丰富的蛋白质之一,并被认为是 MMD 发病机制中的第二个命中基因,能促进 MMD 样血管的形成。它是一种大型肌动蛋白结合蛋白,为多种细胞骨架蛋白提供支架,对细胞运动非常重要。尽管在蛋白质组学领域有大量发现,但人们对 MMD 的总体脂质组学或患者循环液中脂质成分的变化知之甚少。不过,最近有报道称,在 MMD 患者中发现的主要易感遗传因子(即环指蛋白 213)与脂质代谢有关。8 之前进行的一项非靶向脂质组学分析显示,与健康供体相比,MMD 患者血浆中的脂质资产累积消耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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