Rejection is one of the major factors affecting the long-term prognosis of kidney transplantation, and timely recognition and aggressive treatment of rejection is essential to prevent disease progression. RBPs are proteins that bind to RNA to form ribonucleoprotein complexes, thereby affecting RNA stability, processing, splicing, localization, transport, and translation, which play a key role in post-transcriptional gene regulation. However, their role in renal transplant rejection and long-term graft survival is unclear. The aim of this study was to comprehensively analyze the expression of RPBs in renal rejection and use it to construct a robust prediction strategy for long-term graft survival. The microarray expression profiles used in this study were obtained from GEO database. In this study, a total of eight hub RBPs were identified, all of which were upregulated in renal rejection samples. Based on these RBPs, the renal rejection samples could be categorized into two different clusters (cluster A and cluster B). Inflammatory activation in cluster B and functional enrichment analysis showed a strong association with rejection-related pathways. The diagnostic prediction model had a high diagnostic accuracy for T cell mediated rejection (TCMR) in renal grafts (area under the curve = 0.86). The prognostic prediction model effectively predicts the prognosis and survival of renal grafts (p < .001) and applies to both rejection and non-rejection situations. Finally, we validated the expression of hub genes, and patient prognosis in clinical samples, respectively, and the results were consistent with the above analysis.

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.

Blood transfusion after kidney transplantation may increase the risk of sensitization and development of de novo human leukocyte antigen (HLA) donor-specific antibodies (DSAs). This study aimed to evaluate whether blood transfusion during the first year after kidney transplantation influences the development of de novo DSAs and clinical outcomes of kidney transplantation recipients.
This retrospective cohort study included nonsensitized first-time kidney transplantation recipients at Tianjin First Central Hospital from 2010 to 2022. The incidence of de novo DSA development and clinical outcomes between the groups were compared. Luminex single antigen beads were used to monitor DSAs.
Of the 538 non-HLA-sensitized kidney transplantation recipients included in the study, 164 patients who received at least one unit of leukoreduced red blood cell transfusion within the first year (the transfused group), whereas the remaining 374 patients received no blood transfusion (the non-transfused group). Our analysis showed that there was a significant difference in the development of de novo DSAs and de novo anti-class I HLA-Ab between the two groups. Indeed, the transfused recipients had a higher serum creatinine and lower estimated glomerular filtration rate (eGFR) at 1-, 6-, and 12-month (all p > 0.05) after transplantation. Futhermore, a higher incidence of CMV infection, antibody-mediated rejection (AMR), hyper acute rejection (HAR), and delayed graft function (DGF) was identified in the transfused group (all p < 0.05). The graft survival was lower in the transfused group compared with patients in the non-transfused group (P = 0.002). Blood transfusion post-transplantation was a risk factor for de novo DSAs development but not an independent predictive factor for AMR and graft loss (odds ratio = 2.064 [1.243-3.429], p = 0.005).
Our study showed that blood transfusion after transplantation is associated with the occurrence of de novo DSAs increasing an immunological risk for poor clinical outcomes for kidney transplantation recipients.

UNASSIGNED: Vitamin D deficiency (VDD) or vitamin D insufficiency is common in kidney transplant recipients (KTRs). The impact of VDD on clinical outcomes in KTRs remain poorly defined and the most suitable marker for assessing vitamin D nutritional status in KTRs is unknown so far.
UNASSIGNED: We conducted a prospective study including 600 stable KTRs (367 men, 233 women) and a meta-analysis to pool existing evidence to determine whether 25(OH)D or 1,25(OH)2D predicted graft failure and all-cause mortality in stable KTRs.
UNASSIGNED: Compared with a higher 25(OH)D concentration, a low concentration of 25(OH)D was a risk factor for graft failure (HR 0.946, 95% CI 0.912-0.981, p = 0.003), whereas 1,25 (OH)2D was not associated with the study end-point graft loss (HR 0.993, 95% CI 0.977-1.009, p = 0.402). No association was found between either 25(OH)D or 1,25 (OH)2D and all-cause mortality. We furthermore conducted a meta-analysis including 8 studies regarding the association between 25(OH)D or 1,25(OH)2D and graft failure or mortality, including our study. The meta-analysis results were consistent with our study in finding that lower 25(OH)D levels were significantly associated with the risk of graft failure (OR = 1.04, 95% CI: 1.01-1.07), but not associated with mortality (OR = 1.00, 95% CI: 0.98-1.03). Lower 1,25(OH)2D levels were not associated with the risk of graft failure (OR = 1.01, 95% CI: 0.99-1.02) and mortality (OR = 1.01, 95% CI: 0.99-1.02).
UNASSIGNED: Baseline 25(OH)D concentrations but not 1,25(OH)2D concentrations were independently and inversely associated with graft loss in adult KTRs.

The relationship between blood transfusion following kidney transplantation (KT) and the development of de novo donor-specific antibodies (dnDSA) is controversial. This was investigated by conducting a meta-analysis of studies on patients who underwent KT with or without blood transfusion, and by evaluating the effect of post-KT blood transfusion on clinical outcomes of kidney transplant recipients. Relevant studies in the PubMed, EMBASE, and Cochrane Library databases were identified from inception to July 1, 2022. Two reviewers independently extracted data from the selected articles and estimated study quality. A fixed effects or random effects model was used to pool data according to the heterogeneity among studies. Data included in the meta-analysis were derived from 11 studies with a total of 19,543 patients including 6191 with and 13,352 without blood transfusion post-KT. We assessed the pooled associations between blood transfusion and occurrence of dnDSA and clinical outcomes of transplant recipients. Blood transfusion was strongly correlated with the development of dnDSA (relative risk [RR] = 1.40, 95% confidence interval [CI]: 1.17-1.67; P < 0.05). Patients with blood transfusion had a higher risk of developing anti-human leukocyte antigen (HLA) class I dnDSA than non-transfused patients (RR = 1.75, 95% CI: 1.14-2.69; P < 0.05) as well as significantly higher rates of antibody-mediated rejection (AMR) (RR = 1.41, 95% CI: 1.21-2.35; P < 0.05) and graft loss (RR = 1.75, 95% CI: 1.30-2.35; P < 0.05). There were no statistically significant differences between the two groups in the development of anti-HLA antibodies, anti-HLA class II dnDSA, and anti-HLA class I and II dnDSA; delayed graft function; T cell-mediated rejection; acute rejection; borderline rejection; or patient death. Our results suggest that blood transfusion was associated with dnDSA development in KT recipients. The findings of this systematic review also suggest that post-KT blood transfusion recipients have a higher risk of AMR, and graft loss compared with non-transfused patients. Evidence from this meta-analysis indicates that the use of blood transfusion post-KT is associated with a significantly higher risk of immunological sensitization. More and higher quality results from large randomized controlled trials are still needed to inform clinical practice.

The role of m6A modification in kidney transplant-associated immunity, especially in alloimmunity, still remains unknown. This study aims to explore the potential value of m6A-related immune genes in predicting graft loss and diagnosing T cell mediated rejection (TCMR), as well as the possible role they play in renal graft dysfunction.
Renal transplant-related cohorts and transcript expression data were obtained from the GEO database. First, we conducted correlation analysis in the discovery cohort to identify the m6A-related immune genes. Then, lasso regression and random forest were used respectively to build prediction models in the prognosis and diagnosis cohort, to predict graft loss and discriminate TCMR in dysfunctional renal grafts. Connectivity map (CMap) analysis was applied to identify potential therapeutic compounds for TCMR.
The prognostic prediction model effectively predicts the prognosis and survival of renal grafts with clinical indications (P< 0.001) and applies to both rejection and non-rejection situations. The diagnostic prediction model discriminates TCMR in dysfunctional renal grafts with high accuracy (area under curve = 0.891). Meanwhile, the classifier score of the diagnostic model, as a continuity index, is positively correlated with the severity of main pathological injuries of TCMR. Furthermore, it is found that METTL3, FTO, WATP, and RBM15 are likely to play a pivotal part in the regulation of immune response in TCMR. By CMap analysis, several small molecular compounds are found to be able to reverse TCMR including fenoldopam, dextromethorphan, and so on.
Together, our findings explore the value of m6A-related immune genes in predicting the prognosis of renal grafts and diagnosis of TCMR.

The impact of preformed and de novo HLA-DP antibodies after renal transplantation remains controversial and unclear. To address the clinical relevance of HLA-DP antibodies on the outcomes in renal transplantation, we performed a random effect model meta-analysis through a systematic review from inception to December 31, 2021. The outcome was graft loss or acute rejection. Finally five articles were identified as our inclusion criteria. The study which reported 1166 patients included in the final meta-analysis of de novo HLA-DP antibodies after transplantation showed an increased risk of graft loss or acute rejection (OR = 3.6, 95% CI = 1.6-8.10, P = 0.002, I2  = 52%). In the subgroup study, we established that patients with HLA-DP DSA after renal transplantation had a 8.85-fold increased risk of graft loss or acute rejection compared with patients without HLA-DP DSA (p = 0.003).While as for HLA-DP NDSA after renal transplantation, 2.73-fold increased risk of graft loss or acute rejection compared with patients without HLA-DP antibodies (p = 0.04). Besides, the studies which reported 487 patients included in the final meta-analysis of preformed HLA-DP antibodies did not show an increased risk of graft loss or acute rejection (OR = 4.55, 95% CI = 0.79-26.16, P = 0.09, I2  = 57%). The results of our meta-analysis suggested that de novo HLA-DP antibodies especially de novo HLA-DP DSA had a significant deleterious impact on the renal transplant risk of graft loss or acute rejection, while preformed HLA-DP antibodies had a no significant deleterious impact on the risk. The routine detection of HLA-DP antibodies after renal transplantation seems to be very important and may be as one of noninvasive biomarker-guided risk stratification.

UNASSIGNED: Post-transplant diabetes mellitus (PTDM) is a known side effect in transplant recipients administered immunosuppressant drugs, such as tacrolimus. This study aimed to investigate the risk factors related to PTDM, and establish a risk prediction model for PTDM. In addition, we explored the effect of PTDM on the graft survival rate of kidney transplantation recipients.
UNASSIGNED: Patients with pre-diabetes mellitus before kidney transplant were excluded, and 495 kidney transplant recipients were included in our study, who were assigned to the non-PTDM and PTDM groups. The cumulative incidence was calculated at 3 months, 6 months, 1 year, 2 years, and 3 years post-transplantation. Laboratory tests were performed and the tacrolimus concentration, clinical prognosis, and adverse reactions were analyzed. Furthermore, binary logistic regression analysis was used to identify the independent risk factors of PTDM.
UNASSIGNED: Age ≥ 45 years (adjusted odds ratio [aOR] 2.25, 95% confidence interval [CI] 1.14-3.92; P = 0.015), body mass index (BMI) > 25 kg/m2 (aOR 3.12, 95% CI 2.29-5.43, P < 0.001), tacrolimus concentration > 10 ng/mL during the first 3 months post-transplantation (aOR 2.46, 95%CI 1.41-7.38; P < 0.001), transient hyperglycemia (aOR 4.53, 95% CI 1.86-8.03; P < 0.001), delayed graft function (DGF) (aOR 1.31, 95% CI 1.05-2.39; P = 0.019) and acute rejection (aOR 2.16, 95% CI 1.79-4.69; P = 0.005) were identified as independent risk factors of PTDM. The PTDM risk prediction model was developed by including the above six risk factors, and the area under the receiver operating characteristic curve was 0.916 (95% CI 0.862-0.954, P < 0.001). Furthermore, the cumulative graft survival rate was significantly higher in the non- PTDM group than in the PTDM group.
UNASSIGNED: Risk factors related to PTDM were age ≥ 45 years, BMI > 25 kg/m2, tacrolimus concentration > 10 ng/mL during the first 3 months post-transplantation, transient hyperglycemia, DGF and acute rejection.

We aimed to identify feature immune-related genes that correlated with graft rejection and to develop a prognostic model based on immune-related genes in kidney transplantation.
Gene expression profiles were obtained from the GEO database. The GSE36059 dataset was used as a discovery cohort. Then, differential expression analysis and a machine learning method were performed to select feature immune-related genes. After that, univariate and multivariate Cox regression analyses were used to identify prognosis-related genes. A novel Riskscore model was built based on the results of multivariate regression. The levels of these feature genes were also confirmed in an independent single-cell dataset and other GEO datasets.
15 immune-related genes were expressed differently between non-rejection and rejection kidney allografts. Those differentially expressed immune-related genes (DE-IRGs) were mainly associated with immune-related biological processes and pathways. Subsequently, a 5-immune-gene signature was constructed and showed favorable predictive results in the GSE21374 dataset. Recipients were divided into the high-risk and low-risk groups according to the median value of RiskScore. The GO and KEGG analysis indicated that the differentially expressed genes (DEGs) between high-risk and low-risk groups were mainly involved in inflammatory pathways, chemokine-related pathways, and rejection-related pathways. Immune infiltration analysis demonstrated that RiskScore was potentially related to immune infiltration. Kaplan-Meier survival analysis suggested that recipients in the high-risk group had poor graft survival. AUC values of 1- and 3-year graft survival were 0.804 and 0.793, respectively.
Our data suggest that this immune-related prognostic model had good sensitivity and specificity in predicting the 1- and 3-year kidney graft survival and might act as a useful tool for predicting kidney graft loss.

Complement-binding donor-specific human leukocyte antigen (HLA) antibodies in kidney recipients have been associated with a higher risk of allograft rejection and loss. The objective of this meta-analysis was to investigate the correlation between C1q-binding donor-specific antibodies (DSAs) and clinical outcomes in kidney transplantation (KT) recipients.
We conducted systematic searches in the PubMed, EMBASE, and the Cochrane Library databases to identify all studies since inception to August 2021 that compared clinical outcomes between C1q + DSA and C1q-DSA patients who underwent KT. Data were independently extracted by two reviewers who assessed the risk of bias. Data were summarized with fixed effects or random effects models according to heterogeneity. We assessed clinical outcomes including graft loss, rejection, delayed graft function (DGF), and all-cause patient death.
Twenty-six studies with a total of 1337 patients were included: 485 with C1q-binding DSAs, and 850 without C1q-binding DSAs. Compared with the C1q-DSA group, the C1q + DSA group had significant increases in antibody-mediated rejection (AMR) (relative risk [RR] = 2.09, 95% confidence interval [CI], 1.53-2.86; P < 0.00001), graft loss (RR = 2.40, 95% CI, 1.66-3.47; P < 0.00001), and death (RR = 3.13, 95% CI, 1.06-9.23; P = 0.04). The C1q + DSA and C1q-DSA groups did not show significant differences in T-cell-mediated rejection, acute rejection, acute cellular rejection, mixed rejection, or DGF.
The findings of this systematic review suggest that C1q + DSA KT have a higher risk of AMR, graft loss, and death compared with C1q-DSA patients. Monitoring C1q-binding DSAs allows risk stratification of recipients and guides physician management.