Plasma cell‐free transcriptome profiling in blood plasma from chronic liver disease patients

Supplementary data associated with the data descriptor with title: "Plasma cell‐free transcriptome profiling in blood plasma from chronic liver disease patients" File description: Analyses_results_summary.xlsx: Overview of results showed in the technical validation section. A summary of the contents can be found in the “summary” tab in the file annotation_cohort1.csv: laboratory and clinical annotation of samples/patients belonging to cohort 1. annotation_cohort2.csv: laboratory and clinical annotation of samples/patients belonging to cohort 2. CodeBook_ann_cohort1.xlsx: extended description of variables included in the cohort 1 annotation. CodeBook_ann_cohort2.xlsx: extended description of variables included in the cohort 2 annotation. circRNA_diffexpr.csv: differential abundance analysis of circRNA results, includes detected circRNA with p adjusted < 0.05 and abs(logFC) > 2. hepatocyte_signature_deconvolution.csv: results of the vector regression to deconvolve cell types of origin within the plasma cell-free transcriptome. SuplFig1.pdf: Supplementary figure 1. Gene set enrichment and cellular signatures in NAFLD vs. no NAFLD (cohort 1).(a) Gene set enrichment analysis (GSEA) using GO and Hallmark databases (|NES| > 1, FDR < 0.25). (b) Hepatocyte-specific gene expression (CPM counts, left) and singscore-derived hepatocyte signature (right). (c) Volcano plot of differentially expressed circRNAs (|log2FC| > 2, p < 0.05), identifying 97 dysregulated circRNAs. Significance levels: *p < 0.05, **p < 0.01, ***p < 0.001. SuplFig2.pdf: Supplementary figure 2. Gene set enrichment and cellular signature analysis in cirrhosis vs absence of cirrhosis (cohort 1). (a) Gene set enrichment analysis (GSEA) using GO and Hallmark databases (|NES| > 1, FDR < 0.25). (b) Hepatocyte-specific gene expression (CPM counts, left) and singscore-derived hepatocyte signature (right). (c) Volcano plot showing the differential expression of circRNAs. Statistical significance is indicated as *p < 0.05, **p < 0.01, and ***p < 0.001. SuplFig3.pdf: Supplementary figure 3. Gene set enrichment and cellular signatures in high vs. low fibrosis (cohort 2). (a) Gene set enrichment analysis (GSEA) using GO and Hallmark databases(|NES| > 1, FDR < 0.25). (b) Hepatocyte-specific gene expression (CPM counts, left) and singscore-derived hepatocyte signature (right). (c) Deconvolution analysis showing proportions of neutrophils, NK cells, B cells, and platelets. Significance levels: *p < 0.05, **p < 0.01, ***p < 0.001. SuplFig4.pdf: Supplementary figure 4. Gene set enrichment and cellular signatures in NASH patients at risk of HCC progression (cohort 2). (a) Gene set enrichment analysis (GSEA) using GO and Hallmark databases. (|NES| > 1, FDR < 0.25). (b) Hepatocyte-specific gene expression (CPM counts, left) and singscore-derived hepatocyte signature (right). (c) Deconvolution analysis showing proportions of neutrophils, goblet cells, B cells, and platelets. Significance levels: *p < 0.05, **p < 0.01, ***p < 0.001. Total_RNA_description.pdf: text describing the findings of the Gene set enrichment, hepatocyte signature, circRNA analyses. data_user_agreement.pdf: data user agreement to be signed in order to request access to the dataset deposited in the EGA repository (includes data access and data transfer agreements) DTA_non_EU.pdf: additionall data transfer agreement for non-EU countries to be signed together with the DUA in order to request access to the dataset deposited in the EGA repository How to request access to dataset EGAD50000000775 Dataset: Raw RNA-seq data from blood plasma of patients with liver diseaseEGA Study: EGAS50000000545Data Access Committee (DAC): Ghent University — Prof. Jo Vandesompele Who can apply Access is open to qualified researchers whose proposed use complies with the Data Usage Agreement (DUA), applicable ethics approvals, and participant consent restrictions. Research Purposes include research seeking to advance the understanding of genetics, genomics, disease mechanisms, treatment of disorders, and development of associated analytical or statistical methods, consistent with participant consent and the DUA. Step-by-step process Step 1 — Create or log in to your EGA account Go to https://ega-archive.org and register for an account if you do not already have one. Your EGA account email will be used for access notifications and data download. Step 2 — Submit a Data Access Request through EGA Navigate to the dataset page:https://identifiers.org/ega.dataset/EGAD50000000775 Click “Request Access” and follow the on-screen instructions. EGA will forward the request to the Data Access Committee at Ghent University for review. Step 3 — Complete the Data Usage Agreement (DUA) Download the DUA from this Zenodo repository and complete all required fields, including: User Institution name and address Project abstract (Appendix II) Registered users table (Appendix II) EGA account holders table (Appendix II) The DUA must be signed by: an authorised representative of the User Institution (e.g. research office or department head), and the Principal Investigator of the project. Step 4 — Additional requirements for certain international transfers For certain transfers outside the EU/EEA, UGent may require additional GDPR-related transfer documentation (e.g. Standard Contractual Clauses) before access can be granted. Your institution is located in… Document to complete EU / EEA only data_user_agreement.pdf Outside EU / EEA data_user_agreement.pdf and DTA_non_EU.pdf Fill in all highlighted fields: institution details, PI contact information, research purpose, and the DTA ID number (leave blank — UGent will assign this). Sign where indicated. Step 5 — Send the signed documents to UGent Email the signed documents (scanned or digitally signed PDF) to: UGent Technology Transfer [e-mail] Sint-Pietersnieuwstraat 259000 GhentBelgium Please copy: Prof. Jo [e-mail] Step 6 — Await approval and counter-signature The DAC will review the request. Once approved, UGent will counter-sign the agreement and notify EGA. EGA will then grant access permissions for downloading the dataset. For instructions to reproduce the results in the publication check the github repository: https://github.com/OncoRNALab/GCP_exRNA_liver.git本补充数据集关联于标题为《慢性肝病患者血浆无细胞转录组谱分析（Plasma cell‐free transcriptome profiling in blood plasma from chronic liver disease patients）》的数据描述文章。 ### 文件说明 1. Analyses_results_summary.xlsx：技术验证部分结果概览，文件内"summary"工作表中包含内容摘要。 2. annotation_cohort1.csv：归属队列1的样本/受试者的实验室与临床注释信息。 3. annotation_cohort2.csv：归属队列2的样本/受试者的实验室与临床注释信息。 4. CodeBook_ann_cohort1.xlsx：队列1注释文件中所包含变量的详细说明。 5. CodeBook_ann_cohort2.xlsx：队列2注释文件中所包含变量的详细说明。 6. circRNA_diffexpr.csv：环状RNA（circRNA）差异丰度分析结果，包含校正后P值<0.05且|log2FC|>2的检测到的环状RNA。 7. hepatocyte_signature_deconvolution.csv：血浆无细胞转录组中起源细胞类型反卷积的向量回归分析结果。 8. SuplFig1.pdf：补充图1：队列1中非酒精性脂肪性肝病（NAFLD）组与无NAFLD组的基因集富集及细胞特征分析。(a) 基于基因本体（GO）与特征基因集数据库（Hallmark）的基因集富集分析（Gene Set Enrichment Analysis，GSEA），筛选标准为|标准化富集得分（NES）|>1、错误发现率（FDR）<0.25。(b) 肝细胞特异性基因表达（每百万reads计数（CPM），左图）及单样本基因集评分法（singscore）得到的肝细胞特征得分（右图）。(c) 差异表达环状RNA火山图（volcano plot，|log2FC|>2，P<0.05），共鉴定出97个异常表达的环状RNA。显著性标注：*P<0.05，**P<0.01，***P<0.001。 9. SuplFig2.pdf：补充图2：队列1中肝硬化组与无肝硬化组的基因集富集及细胞特征分析。(a) 基于GO与Hallmark数据库的GSEA，筛选标准为|NES|>1、FDR<0.25。(b) 肝细胞特异性基因表达（CPM计数，左图）及singscore肝细胞特征得分（右图）。(c) 环状RNA差异表达火山图，显著性标注为*P<0.05，**P<0.01，***P<0.001。 10. SuplFig3.pdf：补充图3：队列2中高纤维化组与低纤维化组的基因集富集及细胞特征分析。(a) 基于GO与Hallmark数据库的GSEA，筛选标准为|NES|>1、FDR<0.25。(b) 肝细胞特异性基因表达（CPM计数，左图）及singscore肝细胞特征得分（右图）。(c) 反卷积分析结果，展示中性粒细胞、自然杀伤（NK）细胞、B细胞及血小板的占比。显著性标注：*P<0.05，**P<0.01，***P<0.001。 11. SuplFig4.pdf：补充图4：队列2中存在肝细胞癌（Hepatocellular carcinoma，HCC）进展风险的非酒精性脂肪性肝炎（NASH）患者的基因集富集及细胞特征分析。(a) 基于GO与Hallmark数据库的GSEA，筛选标准为|NES|>1、FDR<0.25。(b) 肝细胞特异性基因表达（CPM计数，左图）及singscore肝细胞特征得分（右图）。(c) 反卷积分析结果，展示中性粒细胞、杯状细胞、B细胞及血小板的占比。显著性标注：*P<0.05，**P<0.01，***P<0.001。 12. Total_RNA_description.pdf：对基因集富集、肝细胞特征及环状RNA分析结果的文字描述。 13. data_user_agreement.pdf：申请访问存放在欧洲基因组-档案库（European Genome-phenome Archive，EGA）的数据集时需签署的数据使用协议（Data Usage Agreement，DUA），包含数据访问与数据传输协议条款。 14. DTA_non_EU.pdf：非欧盟国家申请者在签署DUA之外需额外签署的数据传输协议，用于申请访问EGA存储的数据集。 ### 数据集EGAD50000000775访问申请指南 **数据集**：肝病患者血浆RNA测序（RNA-seq）原始数据 **EGA研究编号**：EGAS50000000545 **数据访问委员会（Data Access Committee，DAC）**：根特大学 — Jo Vandesompele教授 #### 申请资格 符合条件的研究人员均可申请，需确保拟开展的研究符合DUA、适用的伦理审批要求及受试者知情同意限制条款。 研究用途包括旨在推进遗传学、基因组学、疾病机制、疾病治疗及相关分析或统计方法开发的研究，且需符合受试者知情同意要求与DUA条款。 #### 申请流程 步骤1 — 创建或登录EGA账户 访问https://ega-archive.org，若无账户请先注册。EGA账户绑定的邮箱将用于接收访问通知与数据下载相关信息。 步骤2 — 通过EGA提交数据访问申请 跳转至数据集页面：https://identifiers.org/ega.dataset/EGAD50000000775 点击"请求访问"并按照屏幕提示完成操作。 EGA将把您的申请转发至根特大学DAC进行审核。 步骤3 — 签署DUA 从本Zenodo仓库下载DUA并填写所有必填字段，包括： - 用户机构名称与地址 - 项目摘要（附录II） - 注册用户登记表（附录II） - EGA账户持有者登记表（附录II） DUA需由以下两方签署： - 用户机构授权代表（如科研办公室或部门负责人） - 项目首席研究员（Principal Investigator，PI） 步骤4 — 特定国际传输的额外要求 对于欧盟/欧洲经济区（EEA）以外的数据传输，根特大学可能要求额外的通用数据保护条例（General Data Protection Regulation，GDPR）相关传输文件（如标准合同条款），方可授予访问权限。 | 机构所在地 | 需完成的文件 | | ---- | ---- | | 欧盟/EEA | 仅需data_user_agreement.pdf | | 欧盟/EEA以外 | data_user_agreement.pdf 与 DTA_non_EU.pdf | 需填写所有高亮字段：机构详情、PI联系方式、研究目的，以及数据传输协议（DTA）编号（留空，由根特大学分配），并在指定位置签署。 步骤5 — 发送签署完成的文件至根特大学 将签署完成的文件（扫描版或数字签名PDF）发送至： UGent Technology Transfer Office <[e-mail]> Sint-Pietersnieuwstraat 25 9000 Ghent Belgium 请抄送：Jo Vandesompele教授 <[e-mail]> 步骤6 — 等待审核与反向签署 DAC将审核您的申请。审核通过后，根特大学将反向签署协议并通知EGA。EGA随后将授予数据集下载权限。 如需复现论文中的结果，请访问GitHub仓库：https://github.com/OncoRNALab/GCP_exRNA_liver.git