Lung transplantation is the ultimate treatment option for those with end-stage lung diseases. Unfortunately, the median survival time after lung transplantation is just over 6 years [
Pharmacogenetics, which is the study of genetic differences affecting individual responses to drugs, might help to optimize the initiation and maintenance dosage of tacrolimus to reach its target concentrations rapidly and to reduce its adverse reactions [
Cytokines are thought to be potent depressors of cytochrome P450 (CYP) enzymes and cause the depression of CYP-associated drug metabolism. The CYP gene expression and enzyme activities are downregulated during inflammation, infection, and transplantation rejection [
The recipients with higher IL-18 serum levels had lower tacrolimus
The target tacrolimus concentration, incidence rate of infection, and rejection in lung transplant recipients were higher than those in liver and kidney transplant recipients [
In this study, we examined the IL-10 and IL-18 genotypes of lung transplant recipients to clarify the influence of these genetic variants on tacrolimus elimination after transplantation. We used the
A total of 51 (7 female and 44 male) adult lung transplant recipients who received tacrolimus-based immunosuppressive regimens at Shanghai Pulmonary Hospital between July 2005 and July 2015 were included in this study. Transplant subtypes included 29 single right lung transplants, 16 single left lung transplants, and 6 bilateral lung transplants. All patients were Han Chinese. The mean age (±SD) was
CYP3A5 rs776746, 2 SNPs of IL-18 (rs5744247 and rs1946518), and 3 SNPs of IL-10 (rs1800896, rs1800872, and rs3021097) were genotyped. Peripheral blood samples were collected in ethylenediaminetetraacetic acid (EDTA) tubes and preserved at −20°C before use. DNA was extracted from whole blood using a standard phenol-chloroform method. A multiplexed SNP MassEXTEND assay was designed by the Sequenom MassARRAY Assay Design 3.0 software (San Diego, CA, USA). The 6 SNPs were genotyped using the Sequenom MassARRAY RS1000 according to the standard protocol recommended by the manufacturer. Data were managed using the Sequenom Typer 4.0 software. Hardy-Weinberg equilibrium, allele frequency, and linkage disequilibrium were analyzed using SHEsis software (
Total RNA was extracted using RNeasy kit (Qiagen, Hilden, Germany) following the manufacturer’s protocol. First-strand cDNA was synthesized using High Capacity cDNA Reverse Transcription Kit according to the manufacturer’s instruction (Applied Biosystems, Carlsbad, CA, USA). Quantitative PCR was performed with SYBR Green PCR Master Mix (Applied Biosystems) and Mastercycler ep realplex (Eppendorf, Hamburg, Germany). IL-18 was amplified using the sense primer 5′-CCAAGGAAATCGGCCTCTAT-3′ and antisense primer 5′-TTGTTCTCACAGGAGAGAGTTGA-3′.
Experimental data were analyzed using SPSS version 17.0 (SPSS, USA) and GraphPad Prism version 5.00 (
Allele and genotype frequency of the CYP3A5 rs776746, IL-18 rs5744247, IL-18 rs1946518, IL-10 rs1800896, IL-10 rs1800872, and IL-10 rs3021097 are shown in Table
Allele frequency of CYP3A5, IL-18, and IL-10 polymorphisms in lung transplant recipients (
Gene | SNP | Genotype | Allele | |||
---|---|---|---|---|---|---|
CYP3A5 | rs776746 | GG | AG | AA | G | A |
0.471 (24) | 0.451 (23) | 0.078 (4) | 0.696 (71) | 0.304 (31) | ||
| ||||||
IL-18 | rs5744247 | GG | GC | CC | G | C |
0.118 (6) | 0.510 (26) | 0.373 (19) | 0.373 (38) | 0.627 (64) | ||
| ||||||
IL-18 | rs1946518 | CC | CA | AA | C | A |
0.255 (13) | 0.451 (23) | 0.294 (15) | 0.480 (49) | 0.520 (53) | ||
| ||||||
IL-10 | rs1800896 | AA | AG | GG | A | G |
0.863 (44) | 0.137 (7) | 0 (0) | 0.931 (95) | 0.069 (7) | ||
| ||||||
IL-10 | rs1800872 | AA | AC | CC | A | C |
0.412 (21) | 0.510 (26) | 0.078 (4) | 0.667 (68) | 0.333 (34) | ||
| ||||||
IL-10 | rs3021097 | TT | TC | CC | T | C |
0.431 (22) | 0.490 (25) | 0.078 (4) | 0.676 (69) | 0.324 (33) |
Comparison of tacrolimus concentration/dose ratios in different groups of CYP3A5, IL-18, and IL-10 polymorphisms at different times after drug initiation.
Gene | Locus | Genotype | Week 1 | Week 2 | Week 3 | Week 4 | ||||
---|---|---|---|---|---|---|---|---|---|---|
| | | | | | | | |||
CYP3A5 | rs776746 | GG | | 0.005 | | 0.008 | | 0.003 | | <0.001 |
AG+AA | | | | | ||||||
| ||||||||||
IL-18 | rs5744247 | GG+CG | | 0.002 | | 0.004 | | 0.005 | | 0.026 |
CC | | | | | ||||||
| ||||||||||
IL-18 | rs1946518 | CC | | 0.007 | | 0.018 | | 0.019 | | 0.079 |
CA | | | | | ||||||
AA | | | | | ||||||
| ||||||||||
IL-10 | rs1800896 | AA | | 0.027 | | 0.034 | | 0.24 | | 0.24 |
AG | | | | | ||||||
| ||||||||||
IL-10 | rs1800872 | AA | | 0.985 | | 0.863 | | 0.909 | | 0.605 |
CA+CC | | | | | ||||||
| ||||||||||
IL-10 | rs3021097 | CC+TC | | 1.000 | | 0.909 | | 0.879 | | 0.634 |
TT | | | | |
IL-18 rs5744247 and rs1946518 were shown to be associated with tacrolimus elimination. Therefore, the two genotypes were further investigated in a combination analysis. IL-18 rs5744247 allele C and rs1946518 allele A were shown to be associated with fast tacrolimus metabolism as stated above. Patients in Group 1 carried less than or equal to 1 allele; patients in Group 2 carried 2 alleles; and patients in Group 3 carried greater than or equal to 3 alleles. Group 3 had lower tacrolimus
Combined effect of IL-18 rs5744247 and rs1946518 polymorphisms on tacrolimus concentration/dose (
The lung transplant recipients were divided into 4 groups according to the number of IL-18 alleles associated with fast tacrolimus metabolism and CYP3A5 genotype. Patients in Group 1 were CYP3A5 expressers and carried greater than or equal to 3 alleles; patients in Group 2 were CYP3A5 expressers and carried less than or equal to 2 alleles; patients in Group 3 were CYP3A5 nonexpressers and carried greater than or equal to 3 alleles; patients in Group 4 were CYP3A5 nonexpressers and carried less than or equal to 2 alleles. Among CYP3A5 expresser recipients, the impact of IL-18 polymorphisms on tacrolimus
Combined effect of IL-18 rs5744247 and rs1946518 and CYP3A5 rs776746 polymorphisms on tacrolimus concentration/dose (
IL-18 rs5744247 polymorphism was significantly associated with IL-18 mRNA expression (GG>CG>CC,
Analysis of IL-18 mRNA expressions in liver tissues with different IL-18 polymorphisms. IL-18 expression was determined by real-time PCR. IL-18 rs5744247 polymorphism was significantly associated with IL-18 mRNA expression (GG>CG>CC); IL-18 rs1946518 polymorphism was significantly associated with IL-18 mRNA expression (CC>CA>AA).
CYP3A5 rs776746 was a well-known biomarker for tacrolimus elimination [
Rs1800896 (A-1082G), rs1800872 (A-592C), and rs3021097 (T-819C) were located in the promoter region of IL-10 and were the most IL-10 SNPs genotyped in previous studies [
In the present study, no significant difference of tacrolimus
IL-18 rs5744247 and rs1946518 were two functional polymorphisms. IL-18 rs5744247 C>G variant reflects higher transcriptional activity and higher expression of IL-18 in LPS-stimulated monocytes and a higher serum IL-18 level [
In addition, our data showed that the influence of IL-18 polymorphisms on tacrolimus
In summary, our study suggested that
Our study has several limitations. First, the study population is confined to the Han Chinese nationality. The distribution of gene polymorphisms varies in different ethnicities. So, the conclusions of this study may not be applied to other ethnic populations. Second, this study is a single-center study and a small number of participants were involved. Further study with large sample sizes should been made to verify the association between cytokine gene polymorphisms and tacrolimus elimination.
Interleukin-18
Interleukin-10
Cytochrome P450
Single nucleotide polymorphism
Serum concentration to dose ratio
Ethylenediaminetetraacetic acid
Polymerase chain reaction.
The authors who have taken part in this study declared that they do not have anything to disclose regarding funding or conflict of interests with respect to this manuscript.
Gening Jiang, Junwei Fan, and Xiaoqing Zhang conceived and designed the experiments. Junwei Fan, Tao Zhang, Wei Zhang, Shengtao Lin, Ling Ye, and Yuan Liu performed the experiments. Yuping Li and Boxiong Xie analyzed the data. Xiaoqing Zhang, Junwei Fan, and Yuping Li contributed reagents, materials, and analysis tools. Junwei Fan wrote the paper. Xiaoqing Zhang and Jiandong Xu contributed equally to this work.
This work was funded by the National Natural Science Foundation of China (81202609) to Xiaoqing Zhang.