Casey R. Dorr, Weihua Guan W, Guillaume Onyeaghala G, William S Oetting, Roslyn B Mannon, Gaurav Agarwal, Jonathan Maltzman, Arthur Matas, Pamala A Jacobson, Ajay K Israni, for DeKAF Genomics
{"title":"487 对慢性异体移植物功能障碍肾活检中的异体移植物损失进行数字空间分析","authors":"Casey R. Dorr, Weihua Guan W, Guillaume Onyeaghala G, William S Oetting, Roslyn B Mannon, Gaurav Agarwal, Jonathan Maltzman, Arthur Matas, Pamala A Jacobson, Ajay K Israni, for DeKAF Genomics","doi":"10.1017/cts.2024.413","DOIUrl":null,"url":null,"abstract":"<p>OBJECTIVES/GOALS: Assess molecular and cellular mechanisms of allograft loss in kidney biopsies using digital spatial profiling and clinical outcomes data. METHODS/STUDY POPULATION: Patients with chronic allograft dysfunction (CGD), enrolled in the Deterioration of Kidney Allograft Function (DeKAF) study, with or without eventual allograft loss, were included. CGD was defined as a >25% increase in creatinine over 3 months relative to a baseline. Kidney biopsy tissue was assessed by Nanostring GeoMX digital spatial profiling (DSP) after staining with anti-pan-cytokeratin, anti-CD45, anti-CD68, Syto-13, to identify specific cell populations, and Nanostring’s Whole Transcriptome Atlas (WTA), to quantify the distribution of transcripts across the biopsy. Up to 14 regions of interest (ROIs) were selected, with or without glomerulus. CIBERSORT was used to perform cell deconvolution. Clinical and outcomes data were from the DeKAF study and United States Renal Data System. RESULTS/ANTICIPATED RESULTS: Macrophage (M1) cell population abundance was significantly different in ROIs with glomerulus between graft loss and no graft loss. Principle component analysis of differentially expressed genes resulted in transcriptomes in ROIs that cluster together by clinical outcome of graft loss or no graft loss. There were 203 DEGs in ROIs with glomerulus that were different by graft loss or no graft loss. By pathway analysis, these 203 DEGS were enriched in the T-cell activation, integrin signaling and inflammation pathways. DISCUSSION/SIGNIFICANCE: DSP of kidney allograft biopsies allows for the identification and quantification of specific cell types, such as macrophages and molecular transcripts as potential drug targets. This data can be used to understand mechanisms of kidney allograft loss and may lead to improved immune suppression in kidney transplant recipients.</p>","PeriodicalId":15529,"journal":{"name":"Journal of Clinical and Translational Science","volume":"37 1","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"487 Digital Spatial Profiling of Allograft Loss in Kidney Biopsies with Chronic Allograft Dysfunction\",\"authors\":\"Casey R. Dorr, Weihua Guan W, Guillaume Onyeaghala G, William S Oetting, Roslyn B Mannon, Gaurav Agarwal, Jonathan Maltzman, Arthur Matas, Pamala A Jacobson, Ajay K Israni, for DeKAF Genomics\",\"doi\":\"10.1017/cts.2024.413\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>OBJECTIVES/GOALS: Assess molecular and cellular mechanisms of allograft loss in kidney biopsies using digital spatial profiling and clinical outcomes data. METHODS/STUDY POPULATION: Patients with chronic allograft dysfunction (CGD), enrolled in the Deterioration of Kidney Allograft Function (DeKAF) study, with or without eventual allograft loss, were included. CGD was defined as a >25% increase in creatinine over 3 months relative to a baseline. Kidney biopsy tissue was assessed by Nanostring GeoMX digital spatial profiling (DSP) after staining with anti-pan-cytokeratin, anti-CD45, anti-CD68, Syto-13, to identify specific cell populations, and Nanostring’s Whole Transcriptome Atlas (WTA), to quantify the distribution of transcripts across the biopsy. Up to 14 regions of interest (ROIs) were selected, with or without glomerulus. CIBERSORT was used to perform cell deconvolution. Clinical and outcomes data were from the DeKAF study and United States Renal Data System. RESULTS/ANTICIPATED RESULTS: Macrophage (M1) cell population abundance was significantly different in ROIs with glomerulus between graft loss and no graft loss. Principle component analysis of differentially expressed genes resulted in transcriptomes in ROIs that cluster together by clinical outcome of graft loss or no graft loss. There were 203 DEGs in ROIs with glomerulus that were different by graft loss or no graft loss. By pathway analysis, these 203 DEGS were enriched in the T-cell activation, integrin signaling and inflammation pathways. DISCUSSION/SIGNIFICANCE: DSP of kidney allograft biopsies allows for the identification and quantification of specific cell types, such as macrophages and molecular transcripts as potential drug targets. 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引用次数: 0
摘要
目的/目标:利用数字空间图谱和临床结果数据评估肾活检中异体移植物损失的分子和细胞机制。方法/研究对象:纳入慢性同种异体移植功能障碍(CGD)患者,这些患者参加了肾脏同种异体移植功能恶化(DeKAF)研究,无论最终是否出现同种异体移植损失。CGD的定义是3个月内肌酐相对于基线上升25%。肾活检组织经抗泛角蛋白、抗CD45、抗CD68和Syto-13染色后,用Nanostring GeoMX数字空间图谱(DSP)进行评估,以确定特定的细胞群,并用Nanostring的全转录组图谱(WTA)量化活检组织中的转录本分布。在有或没有肾小球的情况下,最多可选择 14 个感兴趣区(ROI)。CIBERSORT用于进行细胞去卷积。临床和结果数据来自 DeKAF 研究和美国肾脏数据系统。结果/预期结果:在有肾小球的 ROI 中,巨噬细胞(M1)群的丰度在移植物丢失和无移植物丢失之间存在显著差异。对差异表达基因进行主成分分析后发现,ROI 中的转录组按照移植物缺失或无移植物缺失的临床结果聚类在一起。在有肾小球的 ROI 中,有 203 个 DEGs 因移植物缺失或无移植物缺失而不同。通过通路分析,这203个DEGS富集在T细胞活化、整合素信号转导和炎症通路中。讨论/意义:肾脏移植活组织的 DSP 可以识别和量化特定的细胞类型,如巨噬细胞和作为潜在药物靶点的分子转录本。这些数据可用于了解肾脏异体移植损失的机制,并可改善肾移植受者的免疫抑制。
487 Digital Spatial Profiling of Allograft Loss in Kidney Biopsies with Chronic Allograft Dysfunction
OBJECTIVES/GOALS: Assess molecular and cellular mechanisms of allograft loss in kidney biopsies using digital spatial profiling and clinical outcomes data. METHODS/STUDY POPULATION: Patients with chronic allograft dysfunction (CGD), enrolled in the Deterioration of Kidney Allograft Function (DeKAF) study, with or without eventual allograft loss, were included. CGD was defined as a >25% increase in creatinine over 3 months relative to a baseline. Kidney biopsy tissue was assessed by Nanostring GeoMX digital spatial profiling (DSP) after staining with anti-pan-cytokeratin, anti-CD45, anti-CD68, Syto-13, to identify specific cell populations, and Nanostring’s Whole Transcriptome Atlas (WTA), to quantify the distribution of transcripts across the biopsy. Up to 14 regions of interest (ROIs) were selected, with or without glomerulus. CIBERSORT was used to perform cell deconvolution. Clinical and outcomes data were from the DeKAF study and United States Renal Data System. RESULTS/ANTICIPATED RESULTS: Macrophage (M1) cell population abundance was significantly different in ROIs with glomerulus between graft loss and no graft loss. Principle component analysis of differentially expressed genes resulted in transcriptomes in ROIs that cluster together by clinical outcome of graft loss or no graft loss. There were 203 DEGs in ROIs with glomerulus that were different by graft loss or no graft loss. By pathway analysis, these 203 DEGS were enriched in the T-cell activation, integrin signaling and inflammation pathways. DISCUSSION/SIGNIFICANCE: DSP of kidney allograft biopsies allows for the identification and quantification of specific cell types, such as macrophages and molecular transcripts as potential drug targets. This data can be used to understand mechanisms of kidney allograft loss and may lead to improved immune suppression in kidney transplant recipients.