Impact of differentially expressed genes and proteins in donor arterial plaque on renal function recovery following allogeneic kidney transplantation

Introduction

Background

Renal allograft transplantation is considered the best treatment strategy for patients with end-stage renal disease. Recent studies have shown that renal allograft transplantation increases life expectancy in patients with renal failure compared with that in patients undergoing long-term dialysis (1,2). In recent years, immunosuppressive regimens, organ quality, and allocation policies have changed (3,4). Owing to the general shortage of organ donors to facilitate allogeneic kidney transplantation, kidneys from older donors (≥65 years old) and donors with comorbidities have been transplanted into recipients (5). In particular, the proportion of expanded criteria donor (ECD) kidneys has increased considerably over the past decade (6). However, expanding the standard donor criteria is associated with adverse outcomes, such as impaired graft function after allogeneic kidney transplantation (7), psychological effects on patients, and an immense social and economic burden on the healthcare system (8). Macroscopic arteriosclerosis of the renal arteries of ECD kidneys is likely to occur, and arteriosclerotic plaques of transplanted renal arteries not only impose technical challenges in establishing arterial anastomosis in the recipients, but also affect the allograft function of the transplanted kidneys (9). However, not all patients with macroscopic renal arteriosclerotic plaques exhibit impaired graft function after surgery.

Rationale and knowledge gap

To our knowledge, no study has explored the gene involved in the formation of arteriosclerotic plaques of transplanted kidneys that may affect transplanted kidney function. Transcriptomics can be used to explore specific genes that lead to impaired graft function due to graft arteriosclerotic plaques and identify relevant genes to provide novel biomarkers for improving transplant management.

Objective

Considering the lack of data on genes related to arteriosclerotic plaque formation in the context of kidney function post-transplant, we aimed to integrate data on arteriosclerotic plaques and normal vascular tissue from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) and verify these data using samples from our center, combined with graft function recovery follow-up 1 year after allogeneic kidney transplantation. Clinical data were used to identify DEGs in renal arteriosclerotic plaques that may functionally impair transplanted kidneys after allogeneic kidney transplantation. We present this article in accordance with the MDAR reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-2024-736/rc).

Methods

Data collection

RNA sequencing data of atherosclerotic plaque and normal artery samples were obtained from the GSE100927 and GSE43292 datasets from the GEO database (https://www.ncbi.nlm.nih.gov/geo/). We retrospectively collected data regarding allograft kidney transplants performed at Beijing Hospital between June 2019 and June 2021. In addition, we obtained the transplanted renal artery specimens of the donors, and clinical data of the donors and recipients for further screening and analysis. All study protocols were approved by the Research Ethics Committee of Beijing Hospital (No. 2024BJYYEC-KY006-01) and informed consent was obtained from all participants. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The inclusion criteria were as follows: (I) aged ≥18 years; and (II) recipients who had completed a 1-year follow-up and had creatinine recovery data. The exclusion criteria were as follows: (I) those who underwent combined transplantation; (II) immune rejection occurred during follow-up; and (III) infections such as BK CMV occurred during follow-up. Immune rejection and infection are common complications after renal transplantation that directly affect the functional recovery of the transplanted kidney. Excluding the above factors can prevent confusing results. Samples were collected immediately after surgical resection, snap-frozen in liquid nitrogen, and stored at −80 ℃ until RNA extraction. Fresh samples were subjected to immunofluorescence, quantitative real-time polymerase chain reaction (qPCR), and western blotting. Baseline data of the donor and recipient, organ preservation demographic variables, and relevant post-transplant outcome measures were collected. Donor renal arteriosclerotic plaques visible to the naked eye were divided into “no or mild” and “moderate or severe” donor arteriosclerotic plaque groups. In this study, three senior urological surgeons participated in the assessment and grading of donor renal artery plaque severity. All physicians had extensive clinical experience and reached a consensus on the evaluation criteria before the study commenced to ensure consistency and reproducibility. Macroscopic assessment was performed immediately after donor nephrectomy. The renal artery was examined, and arteriosclerotic plaques were classified into “no or mild” and “moderate or severe” groups based on plaque thickness, extent, and texture. The no or mild arteriosclerotic plaque group was characterized by thin plaques (<25% arterial lumen stenosis) with largely intact tissue structure, whereas the moderate or severe arteriosclerotic plaque group exhibited significantly thickened plaques (≥25% arterial lumen stenosis) accompanied by pathological features such as fibrosis and calcification. To minimize confounding variables, strict recipient selection criteria were applied, ensuring that only transplant recipients without significant iliac vascular atherosclerosis were included, thereby eliminating the potential influence of recipient vascular factors on post-transplant renal function recovery. According to the estimated glomerular filtration rate (eGFR) of the recipients 1 year after allogeneic kidney transplantation (cutoff 50 mL/min/1.73 m²) (9,10), the “moderate or severe” donor arteriosclerotic plaque group was further divided into a plaque group with impaired graft renal function (eGFR <50 mL/min/1.73 m²) and another with normal transplanted kidney function (eGFR ≥50 mL/min/1.73 m²). Figure 1 shows the experimental procedure. The baseline immunosuppressive regimens included calcineurin inhibitors (tacrolimus and cyclosporine), antimetabolites (mycophenolate mofetil and azathioprine), and steroids. In this study, all patients received standard induction therapy with basiliximab and methylprednisolone. Dosages of tacrolimus and cyclosporine were adjusted based on therapeutic drug monitoring to balance immunosuppression and drug toxicity post-kidney transplantation. Blood levels of tacrolimus and cyclosporine were measured. Tacrolimus was initiated at 0.05–0.15 mg/kg/day, administered orally in two divided doses (every 12 hours), with target trough concentrations (C₀) of 8–12 ng/mL during postoperative months 0–1, 6–10 ng/mL during months 1–3, 5–10 ng/mL during months 4–12, and 5–8 ng/mL beyond 1 year. Cyclosporine was initiated at 4.0–6.0 mg/kg/day, administered twice daily, with therapeutic monitoring using either trough concentration (C₀) or 2-hour post-dose concentration (C₂). The target levels were C₀ 150–300 ng/mL (C₂ 1,000–1,500 ng/mL) during months 0–1, C₀ 150–250 ng/mL (C₂ 800–1,200 ng/mL) during months 1–3, C₀ 120–250 ng/mL (C₂ 600–1,000 ng/mL) during months 4–12, and C₀ 80–150 ng/mL (C₂ >400 ng/mL) beyond 1 year. The specific dosage regimen was dynamically adjusted based on individual patient conditions, therapeutic drug monitoring results, and clinical presentation to optimize long-term graft survival.

Figure 1 Experimental procedure. ****, P<0.0001. DEGs, differentially expressed genes; MMP12, matrix metallopeptidase 12; AQP9, aquaporin 9; qPCR, quantitative real-time polymerase chain reaction; WB, western blot.

Univariate and multivariate analysis

The donor age, sex, body mass index (BMI), diabetes status, hypertension status, cause of death, pump variables (flow and resistance), and cold ischemia time, as well as recipient age, sex, BMI, diabetes status, creatinine before kidney procurement, dialysis time, human leukocyte antigen (HLA) mismatches, panel reactive antibody (PRA), and hypertension status were included in the univariate analysis. The outcome measure was defined as impaired graft function (eGFR <50 mL/min/1.73 m²). Covariates with P<0.05, as determined using univariate analysis, were included in the multivariate analysis. P<0.05 was considered to indicate a significant difference.

Screening of DEGs and intersecting DEGs

The data in the GSE100927 and GSE43292 datasets were normalized using the “limma” package in R to identify DEGs between atherosclerotic plaque and normal artery samples. The filtering conditions were false discovery rate <0.05 and |log₂FC| ≥1.0, where FC is the fold change between the groups. Subsequently, the GSE100927 and GSE43292 datasets were combined to identify intersecting DEGs, and the R package VennDiagram was used to visualize them.

Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses

The “clusterprofiler” package in R was used to conduct GO term (biological process, molecular function, and cellular component) and KEGG pathway enrichment analyses of the intersecting DEGs. Significance was defined as P<0.05, and the data are presented graphically.

Immunofluorescence

The specimens from the “no or mild” and “moderate or severe” donor arteriosclerosis groups were paraffin-embedded, fixed, and sectioned. The prepared paraffin-embedded tissue sections were dried in an oven (37 ℃), followed by deparaffinization in 100% xylene three times (10 minutes each) and gradient ethanol rehydration using 100% ethanol (3 minutes, twice), 95% ethanol (3 minutes, twice), 80% ethanol (3 minutes), and 70% ethanol (3 minutes). After washing with phosphate buffered saline (PBS) three times (5 minutes each) to remove excess ethanol, antigen retrieval was performed by placing the sections in sodium citrate antigen retrieval buffer, heating them in a microwave for 15 minutes, allowing them to cool to room temperature, and performing another PBS wash (three times, 5 minutes each). Blocking was carried out in a humidified chamber using goat serum blocking solution at 37 ℃ for 1 hour, after which the sections were incubated overnight at 4 ℃ primary antibody of AQP9 (Santa Cruz Biotechnology, Danvers, USA) and MMP12 (ab314017). The next day, sections were washed with 1× PBS (three times, 5 minutes each), then incubated with an appropriate fluorescent secondary antibody (1:300 dilution) at 37 ℃ for 1 hour in the dark. After removing the secondary antibody solution [Cell Signaling Technology (CST), Danvers, USA], the sections were washed again with 1× PBS (three times, 5 minutes each) under light-protected conditions. For multiplex fluorescence labeling, steps 5–9 were repeated to incubate with a second primary and secondary antibody. Finally, the sections were mounted using fluorescent mounting medium containing 4',6-diamidino-2-phenylindole (DAPI) and stored in the dark to preserve fluorescence. The sections were observed under a fluorescence microscope (Polaris multispectral tissue imaging quantitative analysis system).

qPCR

Tissue samples from the “no or mild” and “moderate or severe” donor arterial plaque groups were collected. Total RNA was subsequently extracted using the Tissue RNA Purification Kit Plus (ESscience Biotech, Shanghai, China). RNA concentration and purity were assessed using the NanoDrop^® ND-1000 spectrophotometer (Thermo Fisher, Shanghai, China). Total RNA was reverse transcribed to cDNA, and the expression of each gene was detected using qPCR with cDNA as a template. For polymerase chain reaction (PCR) amplification of targeted and housekeeping genes, a cDNA template known to express the target gene was selected. The PCR reaction mixture consisted of 5 µL 2× Master Mix (Yeasen Biotech Co., Shanghai, China), 0.5 µL 10 µM forward specific primer, 0.5 µL 10 µM reverse specific primer, and 2 µL cDNA, with water added to a final volume of 10 µL. The mixture was briefly centrifuged (5,000 rpm) and subjected to PCR with an initial denaturation at 95 ℃ for 10 minutes, followed by 40 cycles of 95 ℃ for 10 seconds and 60 ℃ for 60 seconds (fluorescence collection). The PCR products were then analyzed using 2% agarose gel electrophoresis with ethidium bromide staining with a 100 bp DNA ladder to verify the presence of a single specific amplification band. Subsequently, the PCR products were diluted in a 10-fold gradient, with concentrations ranging from 1× (undiluted) to 1×10⁻⁹. For real-time PCR, all cDNA samples were prepared with a reaction system containing 5 µL 2× Master Mix, 0.5 µL 10 µM forward specific primer, 0.5 µL 10 µM reverse specific primer, and water up to a total volume of 8 µL. The mixture was briefly centrifuged (5,000 rpm) before sample loading. In a 384-well PCR plate, 8 µL of the reaction mix was added to each well, followed by 2 µL cDNA, then sealed with Sealing Film (YuanMu Bio-Technology Co., Shanghai, China), briefly centrifuged, and placed on ice before PCR setup. The plate was then loaded onto the real-time PCR machine for amplification with the following conditions: 95 ℃ for 10 minutes, followed by 40 cycles of 95 ℃ for 10 seconds and 60 ℃ for 60 seconds (fluorescence collection). To generate a melting curve, the reaction was extended post-amplification at 95 ℃ for 10 seconds, 60 ℃ for 60 seconds, 95 ℃ for 15 seconds, and a gradual temperature increase from 60 to 99 ℃. The following primers were used: aquaporin 9 (AQP9) forward, 5'-CTCTCTGAGTTCTTGGGCACG-3'; AQP9 reverse, 5'-CCCAGGGAGGAAGCAATGAC-3'; matrix metallopeptidase 12 (MMP12) forward, 5'-GATGTGGAGTCCCCGATGTC-3'; MMP12 reverse, 5'-GGATTTGGCAAGCGTTGGTT-3'; GAPDH forward, 5'-GACAGTCAGCCGCATCTTCT-3'; and GAPDH reverse, 5'-GCGCCCAATACGACCAAAT-3'.

Western blotting

Pre-cooled radioimmunoprecipitation (RIPA) protein extraction reagent was used to extract the proteins from tissues, and the supernatant was used for protein quantification using the bicinchoninic acid method. RIPA lysis buffer was used to adjust the protein concentration. An 8% separating gel and 5% stacking gel were prepared according to the molecular weight of the target protein. The protein samples were loaded, electrophoresed, transferred onto a membrane, and blocked. The primary and secondary antibodies were then incubated with the membrane and reacted with the ECL reagent (Millipore, Shanghai, China). Finally, data analysis was performed using the Gel Image System ver.4.00 (Tanon, China).

Surgical procedure

In this study, we employed the following standardized donor kidney transplantation surgical techniques to optimize hemodynamics and functional recovery of the transplanted kidney. (I) Donor kidney procurement and processing: the donor kidney was retrieved by an experienced organ retrieval team at the donor hospital using rapid organ perfusion techniques, with University of Wisconsin solution as the perfusion fluid. During the procedure, the arterial condition of the donor kidney was assessed, and arteriosclerotic plaques were graded. The donor kidney was transported in cold preservation solution to the transplant center, where, prior to surgery, arterial reconstruction was performed under an ice bath (e.g., branch vessel suturing or intimal dissection). (II) Recipient preparation and vascular anastomosis: preoperative abdominal imaging [e.g., computed tomography (CT) or ultrasound] was performed to assess the vascular conditions of the recipient and to avoid severe arteriosclerosis that could impair the blood supply to the transplanted kidney. The kidney was typically implanted in the right iliac fossa, with the external iliac artery used as the blood supply artery and the iliac vein as the drainage vein. The arterial anastomosis was performed using end-to-side anastomosis, while venous anastomosis was performed using end-to-side anastomosis, with continuous suturing using 6-0 or 7-0 Prolene sutures (Johnson & Johnson, Shanghai, China). The ureteroneocystostomy was performed using the Lich-Gregoir technique for anti-reflux, and a double J stent (BARD, Shanghai, China) was placed for drainage. A total of four urological surgeons participated in the kidney transplantation procedure and strictly followed the standardized surgical protocol to ensure consistency and reproducibility.

Statistical analysis

Normally distributed data are expressed as the mean ± standard deviation, and comparisons between groups were performed using the paired t-test. Non-normal data are expressed as the median [interquartile range (IQR)], and comparisons between groups were performed using the Wilcoxon rank sum test. Unordered variables were compared using the Chi-squared test. First, univariate logistic analysis was performed on all included factors to identify potential predictors. Variables demonstrating statistically significant associations (P<0.05) in the univariate analysis were then selected as candidate variables. Second, these significant variables were subsequently incorporated into a multivariate logistic regression model to assess their independent effects. Results with P<0.05 were considered statistically significant.

Results

Demographic characteristics

A total of 82 renal allograft recipients were included in this study, and qualified specimens were collected from 20 patients for experimental analysis. Table 1 summarizes the recipient and donor characteristics. All recipients received their first renal allografts. The average age of donors was 46.0±10.9 years in the no/mild group and 54.6±11.2 years in the moderate/severe group, while the average age of recipients was 47.3±9.8 and 48.9±11.6 years, respectively. Male donors accounted for 91.4% and 87.5% of the no/mild and moderate/severe groups, respectively, while male recipients accounted for 82.8% and 66.7%. The donor and recipient BMIs were 23.7±3.4 and 23.7±2.7 kg/m² in the no/mild group and 24.7±4.5 and 23.2±4.0 kg/m² in the moderate/severe group, respectively. Brain death among donors was primarily caused by intracranial bleeding, occurring in 67.2% of the no/mild group and 70.8% of the moderate/severe group. Among the donors, 31.0% in the no/mild group and 62.5% in the moderate/severe group had hypertension, while 6.9% and 25.0% had diabetes. Among the recipients, 94.8% in the no/mild group and 83.3% in the moderate/severe group had hypertension, while 24.1% and 16.7% had diabetes. The median cold ischemia time was 5.4 (IQR, 4.5–7.4) hours in the no/mild group and 6.0 (IQR, 5.1–8.9) hours in the moderate/severe group. Median donor kidney perfusion flow was 114.5±29.1 mL/h in the no/mild group and 89.3±22.3 mL/h in the moderate/severe group, while median donor kidney perfusion resistance was 0.27 (IQR, 0.21–0.31) and 0.35 (IQR, 0.26–0.41), respectively. Median recipient dialysis duration was 19.2 (IQR, 5.75–24) months in the no/mild group and 27.0 (IQR, 6–45) months in the moderate/severe group, and the median number of HLA mismatches was 2.4 (IQR, 2–3) and 2.5 (IQR, 2–3), respectively. All recipients had negative PRA.

Relationship between clinical and histological characteristics and graft renal function recovery

In the univariate Cox proportional hazards analysis, diabetes mellitus in donors [hazard ratio (HR) =31.267, 95% confidence interval (CI): 6.130–159.483, P<0.001], older donors (HR =1.081, 95% CI: 1.013–1.152, P=0.02) was associated with atherosclerotic plaques (HR =11.000, 95% CI: 2.643–45.779, P=0.001), and hypertension in donors (HR =24.000, 95% CI: 2.914–197.640, P=0.003) was an important predictor of impaired renal allograft function (Table 2). No other donor or recipient factors were associated with impaired graft function.

In the multivariate Cox proportional hazards analysis, only diabetes mellitus (HR =13.768, 95% CI: 1.799–105.339, P=0.01) with atherosclerotic plaques (HR =10.359, 95% CI: 1.352–79.391, P=0.02) in donors was an important predictor of impaired renal allograft function (Table 2).

Determination of DEGs and intersecting DEGs

Using |log₂FC| ≥1.0 and adj P<0.05 as the standards, a total of 418 and 109 DEGs were identified in the GSE100927 and GSE43292 datasets, respectively (Figure 2A,2B). As shown in Figure 3 and Table S1, 40 intersecting DEGs, including MMP12 and AQP9, were identified between the two datasets. A literature search revealed that the expression of MMP12 and AQP9 could affect the recovery of renal function, which may be related to the recovery of renal function after allogeneic kidney transplantation. These two genes were selected for further analysis.

Figure 2 Determination of DEGs. Volcano plots for (A) GSE43292 and (B) GSE100927. DEGs, differentially expressed genes.

Figure 3 Determination of intersecting DEGs. Venn diagrams of (A) upregulated and (B) downregulated DEGs. DEGs, differentially expressed genes.

GO term and KEGG pathway enrichment analyses

GO term analysis showed that these intersecting genes could be divided into several basic biological processes, including regulation of smooth muscle cell proliferation and sarcomere, and enzyme-related activities (Figure 4A). KEGG pathway analysis showed that the 40 intersecting genes are mainly related to the regulation of smooth muscle cell proliferation, extracellular matrix disassembly, and transport signaling pathways (Figure 4B).

Figure 4 GO and KEGG analyses. Enriched GO terms (A) and KEGG pathway analyses (B) among the DEGs. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; BP, biological process; CC, cellular component; MF, molecular function; DEGs, differentially expressed genes.

Immunofluorescence

To further study the expression levels of genes in “no or mild” and “moderate or severe” donor arteriosclerosis tissues, we collected 10 samples of “no or mild” and 10 samples of “moderate or severe” donor arteriosclerosis plaque tissues. The expression of MMP12 and AQP9 in “moderate or severe” donor arteriosclerosis plaque tissue was significantly increased compared with that in “no or mild” donor arteriosclerosis plaque tissue (Figure 5). Concurrently, the immunofluorescence results showed that there were differences in the expression of MMP12 and AQP9 between the plaque group with impaired kidney function and that with normal kidney function.

Figure 5 Immunofluorescence analysis. Expression of MMP12 and AQP9 in no/mild arteriosclerosis (A), the moderate/severe arteriosclerotic plaque group with normal renal transplant function (B), and the arterial plaque group with impaired renal transplant function (C). Blue, DAPI for nuclei; green, MMP12/AQP9 expression. MMP12, matrix metallopeptidase 12; AQP9, aquaporin 9; DAPI, 4',6-diamidino-2-phenylindole; eGFR, estimated glomerular filtration rate.

qPCR

The expression of MMP12 and AQP9 in “moderate or severe” donor arteriosclerosis plaque tissue was significantly higher than that in “no or mild” donor arteriosclerosis plaque tissue (P<0.001; Figure 6). These two genes were more highly expressed in the plaque group with impaired kidney function than they were in the plaque group with normal kidney function (P=0.02 and P=0.02, respectively; Figure 6).

Figure 6 qPCR analysis of MMP12 and AQP9 mRNA levels in no/mild arteriosclerosis and moderate/severe arteriosclerotic plaque. (A) Expression of MMP12 in no/mild arteriosclerosis and moderate/severe arteriosclerotic plaque. (B) Expression of AQP9 in no/mild arteriosclerosis and moderate/severe arteriosclerotic plaque. (C) MMP12 expression in the moderate/severe arteriosclerotic plaque groups with normal and impaired renal graft function. (D) AQP9 expression in the moderate/severe arteriosclerotic plaque groups with normal and impaired renal graft function. *, P<0.05; ***, P<0.001. MMP12, matrix metallopeptidase 12; AQP9, aquaporin 9; qPCR, quantitative real-time polymerase chain reaction; eGFR, estimated glomerular filtration rate.

Western blotting

The expression of MMP12 and AQP9 in “moderate or severe” donor arteriosclerosis plaque tissue was significantly higher than that in “no or mild” donor arteriosclerosis plaque tissue (Figure 7). Similar to the immunofluorescence results, there were differences in the levels of the two proteins between the plaque group with impaired kidney function and that with normal kidney function (Figure 7).

Figure 7 Western blot analysis. Expression of MMP12 (A) and AQP9 (B) in no/mild arteriosclerosis, the moderate/severe arteriosclerotic plaque group with normal renal transplant function, and the moderate/severe arteriosclerotic plaque with impaired renal transplant function. MMP12, matrix metallopeptidase 12; AQP9, aquaporin 9; eGFR, estimated glomerular filtration rate; GAPDH, glyceraldehyde-3-phosphate dehydrogenase.

Discussion

Kidney transplantation exhibits significant advantages over dialysis in multiple clinically relevant outcomes. Studies have shown that over time, the relative benefit of kidney transplantation in reducing mortality risk compared to dialysis increases further. Data indicate that the relative risk of death for kidney transplantation in 1985 was 0.44, whereas by 2005, this value had decreased to 0.17, suggesting continuous improvement in the long-term outcomes of kidney transplantation. The research also found that kidney transplantation not only significantly reduces the occurrence of cardiovascular events but also substantially improves patients’ quality of life, with notable benefits in both physical and mental health. These findings further support kidney transplantation as the preferred treatment option for end-stage renal disease (11). Although ECD kidneys have been used to alleviate the shortage of deceased donor organs in clinical practice, expanding the use of standard donor organs inevitably results in complications (12).

Kon et al. showed that the formation of renal arteriosclerotic plaques can lead to the progression of chronic kidney disease and that it indicates the involvement of renal microvessels (13). In addition, some studies have shown that the presence of atherosclerotic plaques in renal arteries is associated with the worsening of chronic kidney disease and microalbuminuria (14-16). These findings suggest that the presence of large-vessel atherosclerotic plaques may be an indicator of chronic kidney injury, which may contribute to poor long-term renal allograft function. By mining the GEO database and verifying our samples, this study confirmed that two DEGs in arteriosclerotic plaques are related to the recovery of transplanted kidney function.

MMP12 belongs to the MMP family, which consists of 23 zinc-dependent endopeptidases that share a common multidomain structure (17). MMPs are involved in extracellular matrix degradation and renewal, and tissue remodeling (18). MMPs have been shown to play key roles in various biological processes, including metabolism and inflammation (19,20). MMP12 is produced by macrophages and plays an important role in the development and instability of atherosclerotic plaques (21). Another study demonstrated that genetic deletion of MMP12 may improve low-grade systemic inflammation and reduce the development of atherosclerotic plaques (22). MMP12 is involved in MMP-mediated macrophage invasion, leading to tissue damage and the rupture of atherosclerotic plaques (23). Niu et al. found that MMP12 produced by macrophages infiltrating the glomeruli may be the main factor causing glomerular fibrosis, injury, and inflammation (24). Some studies have also indicated that the potential mechanism of renal pathology may involve macrophage infiltration and the subsequent expression of MMP12 in the glomerular compartment, resulting in decreased renal function (25,26).

AQPs are a family of membrane water channels responsible for the transport of water and small solutes such as glycerol, gases, and ions (27). AQP9 is a member of the AQP family and serves as a water-selective membrane channel (28). Recent research has shown that AQP9 is primarily expressed in human hepatocytes and neutrophils. In addition to regulating cell migration and the inflammatory response, it regulates lipid uptake and energy metabolism (29). Zhang et al. conducted a biological analysis of 220 samples and showed that AQP9 is involved in atherosclerotic plaque formation and can be used as a marker for acute myocardial infarction (30). Animal and cellular experiments have also shown that AQP9 is involved in the development of atherosclerotic plaques (31). However, AQP9 has not been extensively studied in the context of kidney disease. Studies have shown that AQP9 is a potential prognostic gene in patients with clear-cell renal cell carcinoma. Concurrently, AQP9 may play a key role in tumor microenvironment state transition through lipid metabolism and the P53 and JAK/STAT pathways, which affect M2 macrophage polarization (32). Notably, RG100204, a novel, potent, and selective AQP9 inhibitor, attenuated the increase in serum creatinine levels caused by sepsis in a mouse model of polymicrobial infection, and significantly alleviated the risk related to sepsis-associated renal dysfunction (33). Our results show that AQP9 can affect the recovery of renal function after transplantation; however, the underlying mechanism requires further investigation.

This study had some limitations. First, this was a retrospective, single-center study with a limited number of patients. Therefore, studies on graft function using larger samples are required to confirm our findings. Second, we used follow-up data on graft kidney function for only 1 year after transplantation; long-term follow-up data are needed to verify our results. Third, we failed to elucidate the mechanism by which the DEGs impair transplanted kidney function, and more in-depth research is needed.

Conclusions

MMP12 and AQP9 are DEGs in arteriosclerotic plaques in transplanted kidneys that can affect the functional recovery of transplanted kidneys after allogeneic transplantation. Based on this conclusion, further in-depth research should be conducted to improve the safety and quality of allogeneic kidney transplantation. In addition, a potential strategy for predicting the outcomes of allogeneic kidney transplantation has been proposed.

Acknowledgments

We would like to thank Editage (www.editage.cn) for English language editing.

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-2024-736/rc

Data Sharing Statement: Available at https://tau.amegroups.com/article/view/10.21037/tau-2024-736/dss

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-2024-736/prf

Funding: This study was supported by National High Level Hospital Clinical Research Funding (No. BJ-2022-174).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-2024-736/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All study protocols were approved by the Research Ethics Committee of Beijing Hospital (No. 2024BJYYEC-KY006-01) and informed consent was obtained from all participants. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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