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Integrative Data Analytic Framework to Enhance Cancer Precision Medicine. 加强癌症精准医疗的综合数据分析框架。
Pub Date : 2021-03-18 eCollection Date: 2021-01-01 DOI: 10.1089/nsm.2020.0015
Thomas Gaudelet, Noël Malod-Dognin, Nataša Pržulj

With the advancement of high-throughput biotechnologies, we increasingly accumulate biomedical data about diseases, especially cancer. There is a need for computational models and methods to sift through, integrate, and extract new knowledge from the diverse available data, to improve the mechanistic understanding of diseases and patient care. To uncover molecular mechanisms and drug indications for specific cancer types, we develop an integrative framework able to harness a wide range of diverse molecular and pan-cancer data. We show that our approach outperforms the competing methods and can identify new associations. Furthermore, it captures the underlying biology predictive of drug response. Through the joint integration of data sources, our framework can also uncover links between cancer types and molecular entities for which no prior knowledge is available. Our new framework is flexible and can be easily reformulated to study any biomedical problem.

随着高通量生物技术的发展,我们积累了越来越多有关疾病,尤其是癌症的生物医学数据。我们需要计算模型和方法来筛选、整合现有的各种数据并从中提取新的知识,从而提高对疾病机理的理解和对患者的护理。为了揭示特定癌症类型的分子机制和药物适应症,我们开发了一个能够利用各种不同分子数据和泛癌症数据的整合框架。我们的研究表明,我们的方法优于其他竞争方法,并能发现新的关联。此外,它还能捕捉到预测药物反应的潜在生物学特性。通过联合整合数据源,我们的框架还能发现癌症类型与分子实体之间的联系,而这些联系是事先无法了解的。我们的新框架非常灵活,可以轻松地重新制定,以研究任何生物医学问题。
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引用次数: 0
On the Consistency between Gene Expression and the Gene Regulatory Network of Corynebacterium glutamicum. 论谷氨酸棒杆菌基因表达与基因调控网络的一致性
Pub Date : 2021-03-08 eCollection Date: 2021-01-01 DOI: 10.1089/nsm.2020.0014
Doglas Parise, Mariana Teixeira Dornelles Parise, Evans Kataka, Rodrigo Bentes Kato, Markus List, Andreas Tauch, Vasco Ariston de Carvalho Azevedo, Jan Baumbach

Background: Transcriptional regulation of gene expression is crucial for the adaptation and survival of bacteria. Regulatory interactions are commonly modeled as Gene Regulatory Networks (GRNs) derived from experiments such as RNA-seq, microarray and ChIP-seq. While the reconstruction of GRNs is fundamental to decipher cellular function, even GRNs of economically important bacteria such as Corynebacterium glutamicum are incomplete. Materials and Methods: Here, we analyzed the predictive power of GRNs if used as in silico models for gene expression and investigated the consistency of the C. glutamicum GRN with gene expression data from the GEO database. Results: We assessed the consistency of the C. glutamicum GRN using real, as well as simulated, expression data and showed that GRNs alone cannot explain the expression profiles well. Conclusion: Our results suggest that more sophisticated mechanisms such as a combination of transcriptional, post-transcriptional regulation and signaling should be taken into consideration when analyzing and constructing GRNs.

背景:基因表达的转录调控对细菌的适应和生存至关重要。通过 RNA-seq、微阵列和 ChIP-seq 等实验得出的基因调控网络(GRN)通常是调控相互作用的模型。虽然重建基因调控网络是解读细胞功能的基础,但即使是谷氨酸棒杆菌(Corynebacterium glutamicum)等具有重要经济价值的细菌的基因调控网络也是不完整的。材料与方法:在此,我们分析了 GRNs 作为基因表达硅学模型的预测能力,并研究了谷氨酸棒杆菌 GRN 与 GEO 数据库中基因表达数据的一致性。结果我们使用真实和模拟表达数据评估了谷氨酸棒状杆菌 GRN 的一致性,结果表明 GRN 无法单独很好地解释表达谱。结论我们的研究结果表明,在分析和构建 GRN 时应考虑更复杂的机制,如转录、转录后调控和信号转导的结合。
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引用次数: 0
An Early Stage Researcher's Primer on Systems Medicine Terminology. 早期研究人员系统医学术语入门。
Pub Date : 2021-02-25 eCollection Date: 2021-02-01 DOI: 10.1089/nsm.2020.0003
Massimiliano Zanin, Nadim A A Aitya, José Basilio, Jan Baumbach, Arriel Benis, Chandan K Behera, Magda Bucholc, Filippo Castiglione, Ioanna Chouvarda, Blandine Comte, Tien-Tuan Dao, Xuemei Ding, Estelle Pujos-Guillot, Nenad Filipovic, David P Finn, David H Glass, Nissim Harel, Tomas Iesmantas, Ilinka Ivanoska, Alok Joshi, Karim Zouaoui Boudjeltia, Badr Kaoui, Daman Kaur, Liam P Maguire, Paula L McClean, Niamh McCombe, João Luís de Miranda, Mihnea Alexandru Moisescu, Francesco Pappalardo, Annikka Polster, Girijesh Prasad, Damjana Rozman, Ioan Sacala, Jose M Sanchez-Bornot, Johannes A Schmid, Trevor Sharp, Jordi Solé-Casals, Vojtěch Spiwok, George M Spyrou, Egils Stalidzans, Blaž Stres, Tijana Sustersic, Ioannis Symeonidis, Paolo Tieri, Stephen Todd, Kristel Van Steen, Milena Veneva, Da-Hui Wang, Haiying Wang, Hui Wang, Steven Watterson, KongFatt Wong-Lin, Su Yang, Xin Zou, Harald H H W Schmidt

Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields. Methods: In this review, we collect and explain more than100 terms related to Systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references. Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic.

背景:系统医学是一种新颖的医学方法,即将人体视为一个系统,由多个部分和多个层次的复杂关系组成,并进一步融入环境的跨学科领域。探索系统医学意味着理解和结合来自截然不同领域的概念,包括医学、生物学、统计学、建模和仿真以及数据科学。这种异质性导致语义问题,这可能会减缓这些高度多样化的领域之间的实现和富有成效的互动。方法:在这篇综述中,我们收集并解释了100多个与系统医学相关的术语。其中包括建模和数据科学术语以及基本的系统医学术语,以及一些综合定义、应用程序示例和相关参考列表。结果:本术语表旨在成为系统医学研究人员面对陌生术语的急救包,在这里他/她可以首先了解它们,更重要的是,为深入研究该主题提供了示例和参考。
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引用次数: 7
2020 Peer Reviewer Thank You 2020同行评审谢谢
Pub Date : 2021-02-01 DOI: 10.1089/nsm.2021.29009.ack
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引用次数: 0
Plasma Metabolomic Signatures of Chronic Obstructive Pulmonary Disease and the Impact of Genetic Variants on Phenotype-Driven Modules. 慢性阻塞性肺病的血浆代谢组特征以及基因变异对表型驱动模块的影响。
Pub Date : 2020-12-01 Epub Date: 2020-12-31 DOI: 10.1089/nsm.2020.0009
Lucas A Gillenwater, Katherine A Pratte, Brian D Hobbs, Michael H Cho, Yonghua Zhuang, Eitan Halper-Stromberg, Charmion Cruickshank-Quinn, Nichole Reisdorph, Irina Petrache, Wassim W Labaki, Wanda K O'Neal, Victor E Ortega, Dean P Jones, Karan Uppal, Sean Jacobson, Gregory Michelotti, Christine H Wendt, Katerina J Kechris, Russell P Bowler

Background: Small studies have recently suggested that there are specific plasma metabolic signatures in chronic obstructive pulmonary disease (COPD), but there have been no large comprehensive study of metabolomic signatures in COPD that also integrate genetic variants. Materials and Methods: Fresh frozen plasma from 957 non-Hispanic white subjects in COPDGene was used to quantify 995 metabolites with Metabolon's global metabolomics platform. Metabolite associations with five COPD phenotypes (chronic bronchitis, exacerbation frequency, percent emphysema, post-bronchodilator forced expiratory volume at one second [FEV1]/forced vital capacity [FVC], and FEV1 percent predicted) were assessed. A metabolome-wide association study was performed to find genetic associations with metabolite levels. Significantly associated single-nucleotide polymorphisms were tested for replication with independent metabolomic platforms and independent cohorts. COPD phenotype-driven modules were identified in network analysis integrated with genetic associations to assess gene-metabolite-phenotype interactions. Results: Of metabolites tested, 147 (14.8%) were significantly associated with at least 1 COPD phenotype. Associations with airflow obstruction were enriched for diacylglycerols and branched chain amino acids. Genetic associations were observed with 109 (11%) metabolites, 72 (66%) of which replicated in an independent cohort. For 20 metabolites, more than 20% of variance was explained by genetics. A sparse network of COPD phenotype-driven modules was identified, often containing metabolites missed in previous testing. Of the 26 COPD phenotype-driven modules, 6 contained metabolites with significant met-QTLs, although little module variance was explained by genetics. Conclusion: A dysregulation of systemic metabolism was predominantly found in COPD phenotypes characterized by airflow obstruction, where we identified robust heritable effects on individual metabolite abundances. However, network analysis, which increased the statistical power to detect associations missed previously in classic regression analyses, revealed that the genetic influence on COPD phenotype-driven metabolomic modules was modest when compared with clinical and environmental factors.

背景:最近的一些小规模研究表明,慢性阻塞性肺病(COPD)存在特定的血浆代谢特征,但目前还没有对慢性阻塞性肺病的代谢组特征进行大规模的综合研究,也没有整合基因变异。材料与方法:使用 Metabolon 全球代谢组学平台对 COPDGene 中 957 名非西班牙裔白人受试者的新鲜冷冻血浆中的 995 种代谢物进行量化。评估了代谢物与五种慢性阻塞性肺病表型(慢性支气管炎、恶化频率、肺气肿百分比、支气管扩张剂后1秒用力呼气容积[FEV1]/用力生命容量[FVC]和FEV1预测百分比)的关联。为了找到与代谢物水平相关的基因,进行了一项全代谢组关联研究。通过独立的代谢组学平台和独立的队列对显著相关的单核苷酸多态性进行了重复性测试。在网络分析中确定了慢性阻塞性肺病表型驱动的模块,并将其与遗传关联整合在一起,以评估基因-代谢组-表型之间的相互作用。结果:在检测的代谢物中,有 147 个代谢物(14.8%)与至少一种慢性阻塞性肺病表型有显著关联。二酰甘油和支链氨基酸与气流阻塞的相关性较高。109种(11%)代谢物存在遗传关联,其中72种(66%)在独立队列中重复。在 20 种代谢物中,遗传学解释了 20% 以上的变异。研究发现了一个由慢性阻塞性肺病表型驱动的稀疏模块网络,其中往往包含之前检测中遗漏的代谢物。在 26 个慢性阻塞性肺病表型驱动的模块中,有 6 个模块包含了具有显著元-QTLs 的代谢物,但遗传学几乎不能解释模块的变异。结论在以气流阻塞为特征的慢性阻塞性肺病表型中主要发现了全身代谢失调,我们在这些表型中发现了对单个代谢物丰度的强大遗传效应。然而,通过网络分析,我们发现与临床和环境因素相比,遗传对慢性阻塞性肺病表型驱动的代谢组学模块的影响不大。
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引用次数: 0
Informatics Inference of Exercise-Induced Modulation of Brain Pathways Based on Cerebrospinal Fluid Micro-RNAs in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. 肌痛性脑脊髓炎/慢性疲劳综合征运动诱导的脑通路调节的信息学推断。
Pub Date : 2020-11-18 eCollection Date: 2020-01-01 DOI: 10.1089/nsm.2019.0009
Vaishnavi Narayan, Narayan Shivapurkar, James N Baraniuk

Introduction: The post-exertional malaise of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) was modeled by comparing micro-RNA (miRNA) in cerebrospinal fluid from subjects who had no exercise versus submaximal exercise. Materials and Methods: Differentially expressed miRNAs were examined by informatics methods to predict potential targets and regulatory pathways affected by exercise. Results: miR-608, miR-328, miR-200a-5p, miR-93-3p, and miR-92a-3p had higher levels in subjects who rested overnight (nonexercise n=45) compared to subjects who had exercised before their lumbar punctures (n=15). The combination was examined in DIANA MiRpath v3.0, TarBase, Cytoscape, and Ingenuity software® to select the intersection of target mRNAs. DIANA found 33 targets that may be elevated after exercise, including TGFBR1, IGFR1, and CDC42. Adhesion and adherens junctions were the most frequent pathways. Ingenuity selected seven targets that had complementary mechanistic pathways involving GNAQ, ADCY3, RAP1B, and PIK3R3. Potential target cells expressing high levels of these genes included choroid plexus, neurons, and microglia. Conclusion: The reduction of this combination of miRNAs in cerebrospinal fluid after exercise suggested upregulation of phosphoinositol signaling pathways and altered adhesion during the post-exertional malaise of ME/CFS. Clinical Trial Registration Nos.: NCT01291758 and NCT00810225.

引言:肌痛性脑脊髓炎/慢性疲劳综合征(ME/CFS)的运动后不适是通过比较没有运动和次最大运动的受试者脑脊液中的微小RNA(miRNA)来建模的。材料和方法:通过信息学方法检测差异表达的miRNA,以预测运动影响的潜在靶点和调节途径。结果:与腰椎穿刺前运动的受试者(n=15)相比,休息过夜(非运动组n=45)的受试对象的miR-608、miR-328、miR-200a-5p、miR-93-3p和miR-92a-3p水平更高。在DIANA MiRpath v3.0、TarBase、Cytoscape和Ingenuity软件®中检测该组合,以选择靶mRNA的交叉点。DIANA发现33个运动后可能升高的靶点,包括TGFBR1、IGFR1和CDC42。粘附和粘附连接是最常见的途径。Ingenuity选择了七个具有互补机制途径的靶标,涉及GNAQ、ADCY3、RAP1B和PIK3R3。表达高水平这些基因的潜在靶细胞包括脉络丛、神经元和小胶质细胞。结论:运动后脑脊液中这种miRNA组合的减少表明,在脑脊髓炎/慢性疲劳综合征运动后不适期间,磷酸肌醇信号通路上调,粘附性改变。临床试验注册号:NCT01291758和NCT00810225。
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引用次数: 1
CovMulNet19, Integrating Proteins, Diseases, Drugs, and Symptoms: A Network Medicine Approach to COVID-19. CovMulNet19,整合蛋白质、疾病、药物和症状:COVID-19 的网络医学方法。
Pub Date : 2020-11-17 eCollection Date: 2020-01-01 DOI: 10.1089/nsm.2020.0011
Nina Verstraete, Giuseppe Jurman, Giulia Bertagnolli, Arsham Ghavasieh, Vera Pancaldi, Manlio De Domenico

Introduction: We introduce in this study CovMulNet19, a comprehensive COVID-19 network containing all available known interactions involving SARS-CoV-2 proteins, interacting-human proteins, diseases and symptoms that are related to these human proteins, and compounds that can potentially target them. Materials and Methods: Extensive network analysis methods, based on a bootstrap approach, allow us to prioritize a list of diseases that display a high similarity to COVID-19 and a list of drugs that could potentially be beneficial to treat patients. As a key feature of CovMulNet19, the inclusion of symptoms allows a deeper characterization of the disease pathology, representing a useful proxy for COVID-19-related molecular processes. Results: We recapitulate many of the known symptoms of the disease and we find the most similar diseases to COVID-19 reflect conditions that are risk factors in patients. In particular, the comparison between CovMulNet19 and randomized networks recovers many of the known associated comorbidities that are important risk factors for COVID-19 patients, through identified similarities with intestinal, hepatic, and neurological diseases as well as with respiratory conditions, in line with reported comorbidities. Conclusion: CovMulNet19 can be suitably used for network medicine analysis, as a valuable tool for exploring drug repurposing while accounting for the intervening multidimensional factors, from molecular interactions to symptoms.

简介CovMulNet19 是一个全面的 COVID-19 网络,包含所有已知的涉及 SARS-CoV-2 蛋白的相互作用、相互作用的人类蛋白、与这些人类蛋白相关的疾病和症状以及可能靶向它们的化合物。材料与方法基于自举法的广泛网络分析方法使我们能够优先列出与 COVID-19 高度相似的疾病清单,以及可能有益于治疗患者的药物清单。作为 CovMulNet19 的一个主要特征,纳入症状可以更深入地描述疾病的病理特征,是 COVID-19 相关分子过程的有用替代物。结果我们重现了许多已知的疾病症状,并发现与 COVID-19 最为相似的疾病反映了患者的风险因素。特别是,CovMulNet19 和随机网络之间的比较通过与肠道、肝脏和神经系统疾病以及呼吸系统疾病的相似性,发现了许多已知的相关并发症,这些并发症是 COVID-19 患者的重要风险因素。结论CovMulNet19 可适当用于网络医学分析,是探索药物再利用的重要工具,同时考虑到从分子相互作用到症状的多维干预因素。
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引用次数: 0
Multiple Sclerosis Atlas: A Molecular Map of Brain Lesion Stages in Progressive Multiple Sclerosis. 多发性硬化症图谱:进展性多发性硬化症脑损伤阶段的分子图谱。
Pub Date : 2020-08-27 eCollection Date: 2020-01-01 DOI: 10.1089/nsm.2020.0006
Tobias Frisch, Maria L Elkjaer, Richard Reynolds, Tanja Maria Michel, Tim Kacprowski, Mark Burton, Torben A Kruse, Mads Thomassen, Jan Baumbach, Zsolt Illes

Introduction: Multiple sclerosis (MS) is a chronic disorder of the central nervous system with an untreatable late progressive phase. Molecular maps of different stages of brain lesion evolution in patients with progressive multiple sclerosis (PMS) are missing but critical for understanding disease development and to identify novel targets to halt progression. Materials and Methods: The MS Atlas database comprises comprehensive high-quality transcriptomic profiles of 98 white matter (WM) brain samples of different lesion types (normal-appearing WM [NAWM], active, chronic active, inactive, remyelinating) from ten progressive MS patients and 25 WM areas from five non-neurological diseased cases. Results: We introduce the first MS brain lesion atlas (msatlas.dk), developed to address the current challenges of understanding mechanisms driving the fate on a lesion basis. The MS Atlas gives means for testing research hypotheses, validating biomarkers and drug targets. It comes with a user-friendly web interface, and it fosters bioinformatic methods for de novo network enrichment to extract mechanistic markers for specific lesion types and pathway-based lesion type comparison. We describe examples of how the MS Atlas can be used to extract systems medicine signatures and demonstrate the interface of MS Atlas. Conclusion: This compendium of mechanistic PMS WM lesion profiles is an invaluable resource to fuel future MS research and a new basis for treatment development.

简介:多发性硬化症(MS)是一种中枢神经系统的慢性疾病,具有不可治疗的晚期进展期。进行性多发性硬化症(PMS)患者脑病变进化不同阶段的分子图谱尚不清楚,但这对于了解疾病发展和确定阻止进展的新靶点至关重要。材料和方法:MS Atlas数据库包括来自10名进展性MS患者的98个不同病变类型(外观正常的WM [NAWM]、活动性、慢性活动性、非活动性、再髓鞘)的脑白质(WM)样本和来自5名非神经系统疾病患者的25个WM区域的全面高质量转录组学图谱。结果:我们介绍了第一个MS脑病变图谱(msatlas.dk),该图谱的开发旨在解决当前在病变基础上理解驱动命运机制的挑战。MS图谱为测试研究假设、验证生物标志物和药物靶点提供了手段。它带有一个用户友好的网络界面,它促进了生物信息学方法,用于从头开始的网络富集,以提取特定病变类型的机制标记和基于通路的病变类型比较。我们描述了如何使用MS Atlas提取系统医学签名的示例,并演示了MS Atlas的接口。结论:这一机制PMS WM病变概况汇编是推动未来MS研究的宝贵资源,并为治疗开发提供了新的基础。
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引用次数: 10
Combining Gene-Disease Associations with Single-Cell Gene Expression Data Provides Anatomy-Specific Subnetworks in Age-Related Macular Degeneration. 将基因-疾病关联与单细胞基因表达数据相结合,为老年性黄斑变性提供解剖特异性子网络
Pub Date : 2020-08-03 eCollection Date: 2020-01-01 DOI: 10.1089/nsm.2020.0005
Philip J Luthert, Christina Kiel

Background: Age-related macular degeneration (AMD) is the most common cause of visual impairment in the developed world. Despite some treatment options for late AMD, there is no intervention that blocks early AMD proceeding to the late and blinding forms. This is partly due to the lack of precise drug targets, despite great advances in genetics, epidemiology, and protein-protein interaction (PPI) networks proposed to be driving the disease pathology. A systems approach to narrow down PPI networks to specific protein drug targets would provide new therapeutic options. Materials and Methods: In this study we analyzed single cell RNAseq (RNA sequencing) datasets of 17 cell types present in choroidal, retinal pigment epithelium (RPE), and neural retina (NR) tissues to explore if a more granular analysis incorporating different cell types exposes more specific pathways and relationships. Furthermore, we developed a novel and systematic gene ontology database (SysGO) to explore if a subcellular classification of processes will further enhance the understanding of the pathogenesis of this complex disorder and its comorbidities with other age-related diseases. Results: We found that 57% of the AMD (risk) genes are among the top 25% expressed genes in ∼1 of the 17 choroidal/RPE/NR cell types, and 9% were among the top 1% of expressed genes. Using SysGO, we identified an enrichment of AMD genes in cell membrane and extracellular anatomical locations, and we found both functional enrichments (e.g., cell adhesion) and cell types (e.g., fibroblasts, microglia) not previously associated with AMD pathogenesis. We reconstructed PPI networks among the top expressed AMD genes for all 17 choroidal/RPE/NR cell types, which provides molecular and anatomical definitions of AMD phenotypes that can guide therapeutic approaches to target this complex disease. Conclusion: We provide mechanism-based AMD endophenotypes that can be exploited in vitro, using computational models and for drug discovery/repurposing.

背景:老年性黄斑变性(AMD)是发达国家最常见的视力损伤原因。尽管对晚期黄斑变性有一些治疗方案,但没有任何干预措施能阻止早期黄斑变性发展为晚期致盲形式。这部分是由于缺乏精确的药物靶点,尽管在遗传学、流行病学和蛋白质-蛋白质相互作用(PPI)网络方面取得了巨大进步,而这些都被认为是疾病病理的驱动因素。采用系统方法缩小 PPI 网络的范围,找到特定的蛋白质药物靶点,将为治疗提供新的选择。材料与方法:在这项研究中,我们分析了脉络膜、视网膜色素上皮(RPE)和神经视网膜(NR)组织中 17 种细胞类型的单细胞 RNAseq(RNA 测序)数据集,以探索结合不同细胞类型的更精细分析是否能揭示更具体的途径和关系。此外,我们还开发了一个新颖、系统的基因本体数据库(SysGO),以探索亚细胞过程分类是否能进一步加深对这种复杂疾病的发病机制及其与其他老年相关疾病的合并症的理解。研究结果我们发现,在 17 种脉络膜/RPE/NR 细胞类型中,有 57% 的 AMD(风险)基因属于前 25% 的表达基因,其中有 9% 属于前 1% 的表达基因。利用SysGO,我们发现了AMD基因在细胞膜和细胞外解剖位置的富集,并发现了以前与AMD发病机制无关的功能富集(如细胞粘附)和细胞类型富集(如成纤维细胞、小胶质细胞)。我们重建了所有 17 种脉络膜/RPE/NR 细胞类型中表达最高的 AMD 基因之间的 PPI 网络,这提供了 AMD 表型的分子和解剖学定义,可以指导针对这种复杂疾病的治疗方法。结论:我们提供了基于机理的 AMD 内表型,可在体外、使用计算模型和药物发现/再利用中加以利用。
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引用次数: 0
Network and Systems Medicine: Position Paper of the European Collaboration on Science and Technology Action on Open Multiscale Systems Medicine. 网络与系统医学:欧洲科技行动合作组织关于开放式多尺度系统医学的立场文件。
Pub Date : 2020-07-06 eCollection Date: 2020-01-01 DOI: 10.1089/nsm.2020.0004
Blandine Comte, Jan Baumbach, Arriel Benis, José Basílio, Nataša Debeljak, Åsmund Flobak, Christian Franken, Nissim Harel, Feng He, Martin Kuiper, Juan Albino Méndez Pérez, Estelle Pujos-Guillot, Tadeja Režen, Damjana Rozman, Johannes A Schmid, Jeanesse Scerri, Paolo Tieri, Kristel Van Steen, Sona Vasudevan, Steven Watterson, Harald H H W Schmidt

Introduction: Network and systems medicine has rapidly evolved over the past decade, thanks to computational and integrative tools, which stem in part from systems biology. However, major challenges and hurdles are still present regarding validation and translation into clinical application and decision making for precision medicine. Methods: In this context, the Collaboration on Science and Technology Action on Open Multiscale Systems Medicine (OpenMultiMed) reviewed the available advanced technologies for multidimensional data generation and integration in an open-science approach as well as key clinical applications of network and systems medicine and the main issues and opportunities for the future. Results: The development of multi-omic approaches as well as new digital tools provides a unique opportunity to explore complex biological systems and networks at different scales. Moreover, the application of findable, applicable, interoperable, and reusable principles and the adoption of standards increases data availability and sharing for multiscale integration and interpretation. These innovations have led to the first clinical applications of network and systems medicine, particularly in the field of personalized therapy and drug dosing. Enlarging network and systems medicine application would now imply to increase patient engagement and health care providers as well as to educate the novel generations of medical doctors and biomedical researchers to shift the current organ- and symptom-based medical concepts toward network- and systems-based ones for more precise diagnoses, interventions, and ideally prevention. Conclusion: In this dynamic setting, the health care system will also have to evolve, if not revolutionize, in terms of organization and management.

导言:在过去十年中,网络和系统医学得到了快速发展,这要归功于部分源自系统生物学的计算和综合工具。然而,在精准医学的验证、临床应用和决策制定方面仍存在重大挑战和障碍。方法:在此背景下,开放多尺度系统医学科技行动合作组织(OpenMultiMed)回顾了以开放科学方法生成和整合多维数据的现有先进技术、网络和系统医学的关键临床应用以及未来的主要问题和机遇。结果:多原子方法和新型数字工具的发展为探索不同尺度的复杂生物系统和网络提供了独特的机会。此外,可查找、可应用、可互操作和可重用原则的应用以及标准的采用,提高了多尺度整合和解释的数据可用性和共享性。这些创新促成了网络与系统医学的首次临床应用,特别是在个性化治疗和药物剂量领域。现在,扩大网络与系统医学的应用将意味着增加患者和医疗服务提供者的参与,以及教育新一代的医生和生物医学研究人员,将目前基于器官和症状的医学概念转变为基于网络和系统的概念,以实现更精确的诊断、干预和理想的预防。结论在这一动态环境中,医疗保健系统也必须在组织和管理方面不断发展,甚至进行革命。
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Network and systems medicine
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