PDF(Pubmed)
Abstract：
UNASSIGNED: Antibody-mediated rejection (ABMR) significantly affects transplanted kidney survival, yet the macrophage phenotype, ontogeny, and mechanisms in ABMR remain unclear.
UNASSIGNED: We analyzed post-transplant sequencing and clinical data from GEO and ArrayExpress. Using dimensionality reduction and clustering on scRNA-seq data, we identified macrophage subpopulations and compared their infiltration in ABMR and non-rejection cases. Cibersort quantified these subpopulations in bulk samples. Cellchat, SCENIC, monocle2, and monocle3 helped explore intercellular interactions, predict transcription factors, and simulate differentiation of cell subsets. The Scissor method linked macrophage subgroups with transplant prognosis. Furthermore, hdWGCNA, nichnet, and lasso regression identified key genes associated with core transcription factors in selected macrophages, validated by external datasets.
UNASSIGNED: Six macrophage subgroups were identified in five post-transplant kidney biopsies. M1-like infiltrating macrophages, prevalent in ABMR, correlated with pathological injury severity. MIF acted as a primary intercellular signal in these macrophages. STAT1 regulated monocyte-to-M1-like phenotype transformation, impacting transplant prognosis via the IFNγ pathway. The prognostic models built on the upstream and downstream genes of STAT1 effectively predicted transplant survival. The TLR4-STAT1-PARP9 axis may regulate the pro-inflammatory phenotype of M1-like infiltrating macrophages, identifying PARP9 as a potential target for mitigating ABMR inflammation.
UNASSIGNED: Our study delineates the macrophage landscape in ABMR post-kidney transplantation, underscoring the detrimental impact of M1-like infiltrating macrophages on ABMR pathology and prognosis.
UNASSIGNED: We analyzed post-transplant sequencing and clinical data from GEO and ArrayExpress. Using dimensionality reduction and clustering on scRNA-seq data, we identified macrophage subpopulations and compared their infiltration in ABMR and non-rejection cases. Cibersort quantified these subpopulations in bulk samples. Cellchat, SCENIC, monocle2, and monocle3 helped explore intercellular interactions, predict transcription factors, and simulate differentiation of cell subsets. The Scissor method linked macrophage subgroups with transplant prognosis. Furthermore, hdWGCNA, nichnet, and lasso regression identified key genes associated with core transcription factors in selected macrophages, validated by external datasets.
UNASSIGNED: Six macrophage subgroups were identified in five post-transplant kidney biopsies. M1-like infiltrating macrophages, prevalent in ABMR, correlated with pathological injury severity. MIF acted as a primary intercellular signal in these macrophages. STAT1 regulated monocyte-to-M1-like phenotype transformation, impacting transplant prognosis via the IFNγ pathway. The prognostic models built on the upstream and downstream genes of STAT1 effectively predicted transplant survival. The TLR4-STAT1-PARP9 axis may regulate the pro-inflammatory phenotype of M1-like infiltrating macrophages, identifying PARP9 as a potential target for mitigating ABMR inflammation.
UNASSIGNED: Our study delineates the macrophage landscape in ABMR post-kidney transplantation, underscoring the detrimental impact of M1-like infiltrating macrophages on ABMR pathology and prognosis.
摘要：
■抗体介导的排斥反应（ABMR）显着影响移植肾的存活率，然而巨噬细胞表型，个体发育，ABMR的机制尚不清楚。
我们分析了来自GEO和ArrayExpress的移植后测序和临床数据。在scRNA-seq数据上使用降维和聚类，我们确定了巨噬细胞亚群,并比较了ABMR和非排斥反应病例中巨噬细胞的浸润情况.Cibersort量化了大量样品中的这些亚群。Cellchat,场景,monocle2和monocle3有助于探索细胞间的相互作用，预测转录因子，并模拟细胞亚群的分化。剪刀法将巨噬细胞亚群与移植预后联系起来。此外，hdWGCNA,nichnet,Lasso回归确定了与选定巨噬细胞核心转录因子相关的关键基因，由外部数据集验证。
■在5次移植后肾活检中鉴定出6个巨噬细胞亚群。M1样浸润巨噬细胞，在ABMR中普遍存在，与病理损伤严重程度相关。MIF在这些巨噬细胞中充当主要的细胞间信号。STAT1调节单核细胞向M1样表型转化，通过IFNγ途径影响移植预后。基于STAT1的上游和下游基因建立的预后模型有效地预测了移植存活。TLR4-STAT1-PARP9轴可能调控M1样浸润巨噬细胞的促炎表型,确定PARP9是缓解ABMR炎症的潜在靶标。
■我们的研究描绘了ABMR肾移植后的巨噬细胞景观，强调M1样浸润巨噬细胞对ABMR病理和预后的有害影响。
我们分析了来自GEO和ArrayExpress的移植后测序和临床数据。在scRNA-seq数据上使用降维和聚类，我们确定了巨噬细胞亚群,并比较了ABMR和非排斥反应病例中巨噬细胞的浸润情况.Cibersort量化了大量样品中的这些亚群。Cellchat,场景,monocle2和monocle3有助于探索细胞间的相互作用，预测转录因子，并模拟细胞亚群的分化。剪刀法将巨噬细胞亚群与移植预后联系起来。此外，hdWGCNA,nichnet,Lasso回归确定了与选定巨噬细胞核心转录因子相关的关键基因，由外部数据集验证。
■在5次移植后肾活检中鉴定出6个巨噬细胞亚群。M1样浸润巨噬细胞，在ABMR中普遍存在，与病理损伤严重程度相关。MIF在这些巨噬细胞中充当主要的细胞间信号。STAT1调节单核细胞向M1样表型转化，通过IFNγ途径影响移植预后。基于STAT1的上游和下游基因建立的预后模型有效地预测了移植存活。TLR4-STAT1-PARP9轴可能调控M1样浸润巨噬细胞的促炎表型,确定PARP9是缓解ABMR炎症的潜在靶标。
■我们的研究描绘了ABMR肾移植后的巨噬细胞景观，强调M1样浸润巨噬细胞对ABMR病理和预后的有害影响。
