The rapid changes of tissue-typing technology, including the widely used of highly specific molecular typing methods and solid phase analysis technology for detection of alleles specific anti-HLA antibodies, promoted the selection of organ transplant recipients to a more accurate level and promoted the scientific development of organ transplant matching. At present, the graft survival rate has been greatly improved through the prevention and treatment of T-cell-mediated rejection (TCMR), but the humoral immune response, the main cause of late graft loss, is still not effectively controlled.

HLA eplets matching is based on the principle that if a donor HLA antigen shares a specific epitope with a recipient's HLA antigen, that eplets will not be recognized as foreign and will therefore not provoke a humoral immune response. The selection of transplant recipients based on this principle can avoid antibody-mediated rejection (AMR), reduce sensitization after transplantation, and select the most appropriate organs to avoid pre-existing antibodies in the case of persisting HLA antibody positive recipients choosing.

In this study, the HLA high-resolution typing data of kidney transplant recipients from 2014 to the end of 2017 were analyzed with HLA Matchmaker for eplets mismatching number. To analyze the incidence of dnDSA and AMR after kidney transplant recipients with different eplets mismatching number posttransplant, and to elucidate the important role of tissue configuration patterns based on HLA eplets matching in long-term graft survival.

This study is a retrospective cohort study. The investigators design to analyze the HLA high-resolution typing data of kidney transplant recipients from 2014 to the end of 2017 with HLA Matchmaker for eplets mismatching number, and analyze the incidence of dnDSA and AMR after kidney transplant recipients with different eplets mismatching number post transplant, and elucidate the important role of tissue configuration patterns based on HLA eplets matching in long-term graft survival.

The study contents including the followings:

1. Collecting the HLA high resolution typing data The high-resolution HLA typing data of the recipients were analyzed with the HLA Matchmaker software for Eplets mismatching numbers, and the experiment groups were conducted according to the results of Eplets mismatching numbers. Based on the normal distribution characteristics of the Eplets mismatching numbers and the references, the study is divided into the following four groups: group 1, with the Eplets mismatching numbers <5; 2. Group 2, with Eplets mismatching numbers 5-19; Group 3, with Eplets mismatching numbers 20-35; Group 4: with Eplets mismatching numbers greater than or equal to 36.
2. Collecting Clinical follow-up data of patients after kidney transplantation. It mainly includes renal function, DSA level, and pathological diagnosis data of diseases and venereal diseases.

1) sCr： 1 month, 6 months, 1 year, 2 years after surgery... 2) Preoperative PRA-: 1 month, 6 months, 1 year, 2 years after surgery... 3) Preoperative PRA+:2 weeks after surgery, January, march, June, September, 1 year, 2 years...

4) DSA was classified according to the type of antibody: DSA of HLA A site, DSA of HLA B site, DSA of HLA C site, DSA of HLA DR site, DSA of HLA DQ site; 5) According to DSA MFI value classification：MFI<3000, 3000≤MFI<6000, 6000≤MFI<10000,MFI≥10000; 6) AMR：Pathological biopsy data collection (according to Banff 2013 standard diagnosis) 3. Statistical analysis SPSS17.0 Chinese version was used for descriptive analysis of the data. The continuous variable is represented by the mean plus or minus the standard deviation. The chi-square test analyzed the relationship between the Eplets mismatching numbers and the generation of dnDSA, as well as the differences in the Eplets mismatching numbers between the DSA positive group and the DSA negative group, and the differences in Eplets mismatching numbers between the AMR group and the non-AMR group. Kaplan-meier survival curve was used to analyze the differences in long-term graft survival among groups with different Eplets mismatching numbers. P<0.05 was considered statistically significant.

Inclusion Criteria:

• Patients with normal or nearly normal renal function after transplantation
• Patients with abnormal renal function indicators after transplantation but in a stable state without loss of function (serum creatinine 176-265 mmol/l)
• Patients who are able to take immunosuppressive agents orally in strict accordance with the doctor's instructions and can be regularly reviewed

Exclusion Criteria:

• All patients with renal transplantation function damage caused by surgical factors, medicinal factors, acute tubular necrosis (ATN) and other factors
• Postoperative patients complicated with malignant tumors or infectious diseases such as tuberculosis and hepatitis

Patients after kidney transplantation.