Published online Mar 28, 2020. doi: 10.3748/wjg.v26.i12.1273
Peer-review started: December 31, 2019
First decision: February 19, 2020
Revised: March 1, 2020
Accepted: March 5, 2020
Article in press: March 5, 2020
Published online: March 28, 2020
Although, liver transplantation serves as the only curative treatment for patients with end-stage liver diseases, it is burdened with complications, which affect survival rates. In addition to clinical risk factors, contribution of recipient and donor genetic prognostic markers has been extensively studied in order to reduce the burden and improve the outcomes. Determination of single nucleotide polymorphisms (SNPs) is one of the most important tools in development of personalized transplant approach. To provide a better insight in recent developments, we review the studies published in the last three years that investigated an association of recipient or donor SNPs with most common issues in liver transplantation: Acute cellular rejection, development of new-onset diabetes mellitus and non-alcoholic fatty liver disease, hepatocellular carcinoma recurrence, and tacrolimus concentration variability. Reviewed studies confirmed previously established SNP prognostic factors, such as PNPLA3 rs738409 for non-alcoholic fatty liver disease development, or the role of CYP3A5 rs776746 in tacrolimus concentration variability. They also identified several novel SNPs, with a reasonably strong association, which have the potential to become useful predictors of post-transplant complications. However, as the studies were typically conducted in one center on relatively low-to-moderate number of patients, verification of the results in other centers is warranted to resolve these limitations. Furthermore, of 29 reviewed studies, 28 used gene candidate approach and only one implemented a genome wide association approach. Genome wide association multicentric studies are needed to facilitate the development of personalized transplant medicine.
Core tip: Better stratification of risk before transplantation and/or selection of appropriate donor are crucial to reduce post-transplant complications and improve outcomes. The contribution of genetic risk associated with single nucleotide polymorphisms for the most common complications along with the immunosuppression after liver transplantation is briefly summarized in this review.
- Citation: Kelava T, Turcic P, Markotic A, Ostojic A, Sisl D, Mrzljak A. Importance of genetic polymorphisms in liver transplantation outcomes. World J Gastroenterol 2020; 26(12): 1273-1285
- URL: https://www.wjgnet.com/1007-9327/full/v26/i12/1273.htm
- DOI: https://dx.doi.org/10.3748/wjg.v26.i12.1273
Liver transplantation (LT) is the only effective treatment for the end-stage liver failure regardless of its etiology. Although patients’ survival following transplantation has markedly improved during the last decades, LT is still burdened with various complications, such as acute cellular rejection (ACR), development of metabolic disorders: New-onset diabetes mellitus (NODM), non-alcoholic fatty liver disease (NAFLD) and/or the recurrence of primary disease like hepatocellular carcinoma (HCC)[1]. Better stratification of risk before transplantation, selection of appropriate donor, and appropriate immunosuppressive therapy might be of crucial importance to reduce these complications and improve the outcomes[2].
The contribution of genetic risk associated with single nucleotide polymorphisms (SNPs) has been extensively investigated. In the present review, we briefly summarize the findings of older investigations for each of the most common complications after LT and give a detailed analysis of discoveries of the studies published in the last three years.
We searched PubMed for articles published after 2017 using a predefined search strategy. For acute cellular rejection we searched PubMed for: “Liver transplantation”, rejection and polymorphism. For new-onset diabetes mellitus we searched PubMed for: “Liver transplantation”, diabetes, and polymorphism. For NAFLD we searched PubMed for: “Liver transplantation”, (NAFLD or steatosis), polymorphism. For HCC recurrence we searched PubMed for: “Liver transplantation”, hepatocellular carcinoma, recurrence, and polymorphism. Finally for tacrolimus pharmacokinetic we searched PubMed for: “Liver transplantation”, tacrolimus, and polymorphism. Similar search for everolimus and sirolimus returned no relevant studies. Books, dissertations, review articles, meta-analyses, non English articles, and unpublished reports were excluded. Studies non-relevant for the topic, as well as studies with data inconsistency, as assessed by the review of the abstracts or full text, were also excluded.
ACR is a common complication after LT with the incidence of 10%-30%. A recently conducted large study showed that ACR is a clinically significant event, associated with an increased risk of graft failure and death. Clinical risk factors for ACR development include younger recipient age, lack of renal impairment, higher AST levels before LT, longer cold ischemic times and older donors. However, genetic risk factors might play a contributory role[3,4]. ACR is a T-cell mediated reaction, therefore, majority of SNP studies are focused on molecules that participate in T-cell activation, signaling and trafficking.
Although positive association was reported for a relatively high number of SNPs, none of them was firmly and consistently associated with ACR. Studies typically report relatively wide 95% confidence interval (CI) for odds ratio (OR) with a limit close to 1 and lack a confirmation from studies conducted in other centers. The role of TNFa-308 and IL10-1082 SNPs remains controversial even after conducted meta-analyses and might depend on ethnicity[5-7].
Our search identified eight novel studies which are summarized in Table 1. All studies were on genes related to the immune system; seven studies were solely on recipients, while the study by Thude et al[8], investigated both donors and recipients. This study reported an association of ACR with incompatibility in human platelet antigen 3 (HPA-3) SNP between the donor and recipient, although on a relatively low number of patients (53 non-rejectors and 43 rejectors). One study investigated SNP (IL28B rs12979860) for which a previous study reported an association with ACR[9], but found no difference[10]. Valero-Hervás et al[11] found the association with complement C3 genotype (95%CI for OR 0.09-0.77) on large number of patients and confirmed independency by multivariate analysis. SNP for IL17 (rs2275913) was associated with risk for ACR, and also with IL-17 plasma concentration and cyclosporine metabolism[12]. Yu et al[13] found a weak association between ACR and CD276 polymorphism, with CI limits close to 1. The remaining studies found either no association or the association was present only in subgroup analysis[14-16].
| Ref. | Etiology/Population | Genes and best 95%CI OR | Key points |
| N (non-ACR/ACR) | |||
| Yu et al[13] | Various | Recipient CD276: rs2127015 (0.05-0.93); NS for: rs11072431, rs11574495, rs12593558, rs12594627, rs3816661 rs7176654; Recipient TREML2: rs4714431, rs6915083, rs7754593, rs9394767 NS1 | Recipient's CD276 (rs2127015) T allele is weakly associated with ACR and with CD276 mRNA expression |
| Eastern Asian | |||
| 334/54 | |||
| Ostojic et al[14] | Alcoholic | Recipient CXCL9: rs10336 NS; Recipient CXCL10: rs3921 NS | No association found. CXCL9 (rs10336) is associated with earlier ACR occurrence and higher plasma CXCL9 concentrations |
| European | |||
| 156/59 | |||
| Sun et al[12] | Various | Recipient IL-17: rs2275913 (0.07-0.77)2 | Associated with increased IL-17 plasma concentration and with cyclosporine metabolism (CYP3A4 and CYP3A5 expression) |
| Eastern Asian | |||
| 66/40 | |||
| Verma et al[16] | Various | Recipient FOXP3: rs3761547, rs3761548, and rs2232365 NS | Association found only in a very small subgroup of steroid resistant ACR patients (N = 5) for rs3761548 |
| Asian | |||
| 86/16 | |||
| Associated with the degree of mixed lymphocyte reaction | |||
| Thude et al[15] | Various | Recipient KLRB1: rs1135816 NS | No association found |
| European | |||
| 163/178 | |||
| Thude et al[8] | Various | Recipient HPA-3 a/b: rs5910 (1.749–41.8); Recipient/donor incompatibility: rs5910 (1.78–7.39); HPA-1, -2, -3, -5, -15 NS for all | HPA-3 incompatibility and HPA-3 b/b genotype were associated with higher incidence of ACR |
| European | |||
| 53/43 | |||
| There was no difference in the time of ACR occurrence | |||
| Fereidooni et al[10] | Various | Recipient IL28B: rs12979860 NS | No association found |
| Western Asian | |||
| 101/39 | |||
| Valero-Hervás et al[11] | Various | Recipient C3 complement rs2230199 (0.09-0.77) | C3FF genotype is associated with lower incidence of ACR, independently after multivariate analysis for sex, HCV infection, therapy and donor type |
| European | |||
| 277/185 |
Although reviewed studies provide some insight into genetic risk for ACR occurrence, no reliable association has been identified. The approach by Thude et al[8], who investigated the recipient-donor relationship, seems to be more promising and should be conducted on larger scale.
NODM is a common metabolic complication after liver transplantation with a reported prevalence of 17%-36% despite the improvements in immunosuppressive regimens[17-19]. NODM has a negative effect on recipient and graft survival, and it is associated with cardiovascular complications, infections, chronic rejection and renal failure[17-20]. So far, clinical parameters such as advanced age, ethnicity, family history, body mass index, hepatitis C virus and immunosuppressive drugs have been reported as risk factors for NODM after LT[21-23].
Identifying patients at high risk of developing NODM is rather necessary for preventing the disease, individualization of immunosuppressive protocols and improving the long-term outcomes after LT. The pathophysiology of NODM resembles that of type 2 diabetes mellitus (T2DM) and it is characterized by impaired insulin secretion and insulin resistance. Thus, the numerous genetic polymorphisms that are involved in T2DM may also be associated with the development of NODM[24]. However, these associations in the post-transplantation setting are only starting to be elucidated.
We reviewed four studies that were published in the last three years (Table 2). With the exception of the study by Husen et al[25], all were conducted on SNPs previously shown to be associated with T2DM in non-transplant patients. Cen et al[26] investigated twelve different recipient’s SNPs and found an association with two different SNPs for adiponectin gene rs1501299 and rs82239, and further confirmed rs1501299 (minor allele frequency, MAF 24%) to be an independent risk factor by multivariate regression. For rs82239, MAF (4.7%) was too low for firmer conclusions[26]. Interestingly, they found no association for KCNJ11 rs5219 SNP for which Parvizi et al[27] previously reported significant association with NODM. Similarly, the lack of association for nine other SNPs previously associated with DM in non-transplant patients was reported in this study[26]. Zhang et al[28] investigated both donor’s and recipient’s SNPs for small ubiquitin-like modifier 4 (SUMO4) rs237025 and found both of them to be associated with NODM. A recent meta-analysis confirmed that this SNP contributes to DM risk in non-transplant patients[29]. The angiotensin gene polymorphism rs699 is well known to be associated with a risk for various cardiovascular conditions. Moreover, its association with insulin sensitivity has also been reported[30]. Mottaghi et al[31] found this SNP to be associated with NODM in liver recipients. Finally, Husen et al[25] found the recipient’s mammalian target of rapamycin mTOR rs2295080 to be associated with NODM in everolimus-treated patients. However, considering that the NODM risk was not a primary study objective and that the number of NODM patients was very low, this result needs further verification.
| Ref. | Etiology/Population | Genes and best 95%CI OR | Key points |
| N (non-NODM/NODM) | |||
| Mottaghi et al[31] | Various | Recipient AGT: rs699 - 7.326 (2.0-26.8), rs4762 – NS | The presence of AGT rs699 T allele may significantly increase the NODM risk |
| Iran | |||
| 62/53 | |||
| Husen et al[25] | Various | Recipient Mtor: rs2295080 (1.48-23.4); rs12139042, rs2536 – NS | rs2295080 CC genotype is associated with a risk of DM on everolimus-based IS |
| European | |||
| 115/121 | DM was a secondary objective, with a very low N of DM patients | ||
| Cen et al[26] | Hepatitis C, HCC | Recipient ADIPOQ: rs1501299 (0.05-0.61)2, rs822396 (0.13-0.70)3; NS for recipient SNPs: ADIPOR2 rs767870, TLR4 rs1927907, CCL5 rs2107538 and rs2280789, CYP3A5 rs776746, PPARA rs4823613, ACE rs4291, HSD11B1 rs4844880, KCNJ11 rs5219, KCNQ1 rs2237892 | ADIPOQ rs1501299 and rs822396 are associated with a risk of NODM |
| China | |||
| 181/75 | rs1501299 is an independent risk factor | ||
| Zhang et al[28] | Various | Recipients SUMO4: rs237025 (1.42-5.91); Donors SUMO4: rs237025 (1.542–9.007) | Donor and recipient rs237025 G allele and their combination were independent predictive factors for NODM |
| China | |||
| 102/24 |
NAFLD is now recognized as the most common etiology of chronic liver disease[32,33], and one of the most common indications for LT, with increasing trends[34,35]. The genetic background of NAFLD is well established and the strongest evidence is provided for PNPLA3 rs738409, which became a major genetic determinant of hepatic fat content[33]. Following liver transplantation NAFLD/non-alcoholic steatohepatitis (NASH) may reoccur or develop de novo, with almost 50% of recipients showing evidence of steatosis after 10 years[36].
Recurrent and/or de novo allograft steatosis could also be genetically driven, and our search identified 4 novel studies, summarized in Table 3, which had analyzed the association between donor and recipient SNPs with steatosis occurrence after LT. The donor PNPLA3 G allele was independently associated with steatosis occurrence in two studies from the same group of authors[37,38]. Míková et al[37] further reported that donor TM6SF2 rs58542926 A allele is associated with higher odds for steatosis development. Additionally, the strongest association was observed when both PNPLA3 G and TM6SF2 A alleles were present in the donor liver (95%CI for OR 2.01-13.0). However, it should be noted that two studies also reported a weak association between recipient PNPLA3 G allele and steatosis in the univariate model[38,39]. Furthermore, Kim et al[39] found that there are higher odds for steatosis development when donor and recipient have PNPLA3 G allele. However, the evidence is weak and CI limits extremely wide, mainly due to a small number of patients. Finally, recipient adiponectin gene SNPs were reported to be weakly associated with de novo steatosis in patients transplanted due to chronic hepatitis C virus (HCV) infection[40].
| Ref. | Etiology/Population | Genes and best 95%CI OR | Key points |
| N (no steatosis/steatosis) | |||
| Míková et al[37] | Various | Donor TM6SF2: rs58542926 (1.28-4.42); Donor PNPLA3: rs738409 (1.28-3.27); Additive: TM6SF2 + PNPLA3 (2.01-13.0); Recipient NS for all | Donor TM6SF2 A allele and PNPLA3 G allele are associated with steatosis in both univariate and multivariate adjusted analyses |
| European | |||
| 139/129 | The additive effect of donor TM6SF2 A allele and donor PNPLA3 G allele is strongly associated with steatosis | ||
| No association when recipients SNPs were analyzed | |||
| John et al[40] | HCV | Recipient adiponectin: rs1501299 (1.09-5.5), rs266729 (0.14-0.75); rs2241766, rs17300539 – NS; Donor – NS for all | Recipient but not donor adiponectin rs1501299 GG genotype is significantly, but weakly associated with de novo steatosis after adjustment for race and HCV genotype |
| North American | |||
| 72/39 | |||
| Kim et al[39] | Various | Recipient PNPLA3: rs738409 (1.00-9.34)1; Donor – NS; Additive donor + recipent: (1.32-117.0)2 | If both, donor and recipient have G allele, the recipient has higher risk for steatosis weak association, small number of patients |
| Eastern Asian | |||
| 23/9 | |||
| Trunečka et al[38] | Various | Donor PNPLA3: rs738409 (1.05-1.75); Recipient PNPLA3: rs738409 (1.02-1.57) | PNPLA3 G allele in donors [OR (95%CI) = 1.62 (1.12-2.33)], but not in recipients is independently associated with steatosis after adjustment for age, disease etiology, BMI, diabetes, hypertension, therapy and lipids |
| European | |||
| 89/87 |
In summary, despite the small number of studies and a relatively small number of patients included, PNPLA3 rs738409 seems to be associated with post-LT steatosis, with novel studies providing stronger evidence for the donor rather than recipient polymorphism. However, based on previous “seed and soil” theory[41] and observations from studies shown in Table 3, we find that it would be of scientific interest to examine the possible interaction effect of donor and recipient genotypes on steatosis occurrence in an adequately powered study. Furthermore, the additive effect of TM6SF2 rs58542926 seems to increase the genetic risk for post-transplant steatosis further.
HCC is the most common type of primary liver cancer and the second leading cause of tumor-related deaths worldwide[42]. Several HCC risk factors including alcohol consumption, HCV, hepatitis B virus (HBV), obesity and T2DM can be addressed through a variety of prevention and treatment methods[43]. Nevertheless HCC is an increasing indication for liver transplantation (LT) worldwide, regardless of the etiology[44,45]. LT provides a highly effective treatment option in selected patients, whereas the post-transplant HCC recurrence still remains a negative predictor of post-transplant survival in a substantial part of recipients[46,47]. Significant efforts have been made to identify risk factors for the HCC recurrence, and some of them as tumor size and number of lesions are implemented in selection criteria and prognostic models[48,49]. Mechanisms involved in the HCC development and recurrence are being extensively investigated, but our current knowledge is still limited, restricting our diagnostic and therapeutic options.
Genetic risk factors play an important role in HCC development. Recent investigations indicate an important role of PNPLA3, EGF and TM6SF2 SNPs in HCC susceptibility[50]. A recently conducted genome-wide association study (GWAS) identified rs2431 SNP for fibronectin type III domain containing 3b (FNDC3B) to be associated with the overall survival of HCC patients who underwent liver resection[51]. However, data on HCC recurrence in patients treated with liver transplantation, where both donor and recipient SNPs might contribute to the genetic risk of HCC reoccurrence are scarce. Our search identified three novel studies (Table 4). All three studies were conducted on genes associated with immune system activity. Zhang et al[52] found the recipient’s SNP for IL-15 (rs10519613) to be associated with the risk of post-transplant HCC recurrence in a cohort of HBV infected patients. Two different studies on toll-like receptor- (TLR) related genes have reported an increased risk of HCC recurrence for donor’s TLR4 (rs1927914) and recipient’s TLR9 (rs187084) polymorphism, respectively[53,54]. Noteworthy, for TLR4 (rs1927914) polymorphism, previous case-control study reported an association with the HCC development[55]. These studies further emphasize the important role of innate immunity activation in liver carcinogenesis[56].
| Ref. | Etiology/Population | Genes and best 95%CI OR | Key points |
| N (non HCC/HCC) | |||
| Shi et al[53] | Various | Donor TLR 4: rs1927914 (1.886-12.5)1; Recipient TLR 4: rs1927914 NS | Donor TLR4 TT variant is an independent risk factor for HCC recurrence [OR 95%CI = 6.499 (1.799-23.481), after correction], and is associated with shorter recurrence free survival and overall survival |
| Eastern Asian | |||
| 49/34 | |||
| Zhang et al[52] | HBV | Recipient IL-15: rs10519613 (1.636–16.168), rs13122930 NS; Donor IL-15: rs10519613 NS; rs13122930 NS | Recipient IL-15 rs10519613 CA/AA genotype is an independent risk factor for shorter tumor free survival and overall survival after correcting for histologic grade, tumor thrombus, tumor stage and UCSF criteria |
| Eastern Asian | |||
| 74/38 | |||
| OR 95 CI for tumor free survival = 2.214 (1.041–4.708), for overall survival = 3.152 (1.358–7.315) | |||
| de la Fuente et al[54] | Various | Recipient TLR9: rs187084 (0.01–0.87); rs5743836 – NS | TLR9 rs187084 TT genotype was associated with a decreased risk of HCC recurrence |
| European | |||
| 139/20 |
One of the most important aspects in patient and graft survival is adequate im-munosuppressive therapy. Introduction of calcineurin inhibitors to immunosuppressive regimen has greatly improved the outcomes after liver transplantation, even more so with tacrolimus[57,58]. However, this is a drug with a narrow therapeutic window and many factors may influence its pharmacokinetic and pharmacodynamic profile. For adequate graft and patient survival it is of crucial importance to avoid both, under and over immunosuppression[59,60]. Tacrolimus is metabolized in liver by cytochrome P450 (CYP) isoforms CYP3A4 and CYP3A5[61]. The most important SNP in estimating the achieved tacrolimus plasma concentration is rs776746, also known as 6986A > G. Patients with GG genotype (also known as CYP3A5*3) are CYP3A5 non-expressors and achieve greater tacrolimus concentration than patients with A allele – CYP3A5 expressors (also known as CYP3A5*1)[62,63]. As CYP3A5 is not expressed only in the liver, but also in the intestine and kidney, both donor and recipient genotypes may influence tacrolimus metabolism and subsequently alter the drug dose-normalized concentration[59,63,64]. Recipient genotype appears to be more important in the early post-transplant period, and donor genotype in later post-transplant period[65].
Our search identified ten novel studies (Table 5). All studies determined the CYP3A5 6986A>G (rs776746) SNP confirming its key role and tried to determine contributory SNPs or to provide additional insight into CYP3A5 6986A>G effects. Liu et al[66] conducted GWAS study on 115 patients and identified several novel SNPs associated with tacrolimus concentration. In early post-transplant period the tacrolimus concentration was associated with donor FAM26F (rs1057192) and rs1927321 SNPs. These two SNPs together with preoperative creatinine concentration explained 22% of variation in tacrolimus concentration. In later post-transplant period the tacrolimus concentration was associated with donor CYP3A5 (rs776746), TELO2 (rs266762), ESYT1 (rs7980521), rs4903096, and also with recipient CYP3A5 (rs776746) and rs7828796. These six SNPs explained 47.8% of variation. Kato et al[67] showed that the variability of tacrolimus concentration caused by CYP3A5 6986A>G (rs776746) genotype can be diminished if the drug is applied intravenously instead of orally. Three studies aimed to identify other important CYPs polymorphisms. The first investigated 29 various SNPs and found two additional SNPs for CYP3A5 (rs4646450 CC genotype and rs15524 TT genotype) to be associated with increased tacrolimus concentration[65], while the second study indicated that rare CYP3A4 SNPs (CYP3A4*20 and CYP3A4*22) may additionally increase tacrolimus concentration[68]. The third study developed a population pharmacokinetic model and found recipient ABCB1 rsl045642 (C3435T), but not CYP3A5 rs776746 (6986A>G) to be independently associated with tacrolimus metabolism. However, as data on donor CYP3A5 SNPs were not included into the model, conclusion should be taken cautiously[69].
| Ref. | Etiology/Population/N | Genes | Key points |
| Liu et al[66] | Various | Recipient, donor | Donor FAM26F (rs1057192) and rs1927321 were associated with Tac concentration in recovery phase (first 2 wk) |
| GWAS, association found for: CYP3A5 (rs776746), TELO2 (rs266762), ESYT1 (rs7980521), FAM26F (rs1057192), chr14: 39860228 (rs4903096) chr9: 118304139 (rs1927321), chr8: 83368297 (rs7828796) | |||
| Eastern Asian | |||
| 115 | Donor CYP3A5 (rs776746), TELO2 (rs266762), ESYT1 (rs7980521) and rs4903096 were associated with Tac concentration in stabilizing phase (third to fourth post-transplantation week) | ||
| Recipient CYP3A5 (rs776746) and rs7828796 were associated with Tac concentration in stabilizing phase (third to fourth post-transplantation week) | |||
| Ou et al[70] | Various | Recipient, donor: CYP3A5 (rs776746)1, TLR 1 (rs574361, rs4833095), TLR2 (rs4696480), TLR3 (rs5743316, rs3775291), TLR4 (rs1927907), TLR7 (rs3853839), TLR9 (rs187084, rs352139, rs5743836) | Donor and recipient CYP3A5*3 genotype were associated with increased Tac concentration |
| Eastern Asian | Donor TLR9 rs352139 AA genotype and TLR4 rs1927907 GG genotype were associated with increased Tac concentration | ||
| 297 | |||
| Patients with donor TLR9 rs352139 G allele had increased CYP3A5 mRNA expression in transplanted liver tissue | |||
| No significant association was found for other eight SNPs | |||
| Deng et al[74] | Not stated | Recipient: CYP3A5 (rs776746)1, CYP2C8 (rs11572080), ABCB1 (rs1045642, rs1128503) | Association with early renal injury was monitored |
| Eastern Asian | CYP3A5*3 was associated with the risk of early renal glomerular lesion | ||
| 136 | CYP2C8*3 was associated with the risk of the tubulointerstitial injury | ||
| No association between ABCB1 SNPs and renal injury | |||
| Kato et al[67] | Various | Recipient, donor: CYP3A5 (rs776746)1 | Differences between administration routes of Tac were investigated |
| Eastern Asian | CYP3A5 genotype influenced Tac concentration when Tac was applied orally, but not when applied intravenously | ||
| 61 | |||
| Gómez-Bravo et al[68] | Not stated | Recipient, donor: CYP3A4 [rs67666821 (CYP3A4*20), rs35599367 (CYP3A4*22)], CYP3A5 (rs776746)1 | CYP3A5*3 genotype was associated with increased Tac concentration |
| European | The presence of rare CYP3A4 SNPs (CYP3A4*20 and CYP3A4*22) in donor liver increases Tac plasma concentrations | ||
| 90 | |||
| Recipient CYP3A4*22 is also associated with increased Tac concentration | |||
| Liu et al[65] | Not stated | Recipient, donor: CYP2B6 (rs3745274), CYP3A4 (rs4646437), CYP3A5 (rs776746, rs15524, rs4646450, rs3800959)1 | CYP3A5 rs776746 GG (CYP3A5*3), rs4646450 CC and rs15524 TT genotypes were associated with higher Tac concentrations |
| Eastern Asian | |||
| 373 | In the short term both donor and recipient CYP3A5 genotype contributed equally, but later the donor genotype had greater effect | ||
| No significant association for the remaining 5 SNPs was found, 13 other SNPs were determined, but excluded from analysis because of low MAF | |||
| Zhang et al[71] | Various | Recipient, donor: CYP3A5 (rs776746)1, SUMO4 (rs237025) | Donor and recipient CYP3A5*3 genotype are associated with increased Tac concentration |
| Eastern Asian | Donor SUMO4 rs237025 AA genotype was independently associated with decreased Tac concentration and with higher CYP3A5 mRNA expression | ||
| 297 | |||
| Chen et al[69] | Not stated | Recipient: CYP3A5 (rs776746), ABCB1 (rs1128503, rs2032582, rsl045642) | In a population pharmacokinetic model recipient ABCB1 rsl045642 (C3435T) was independently associated with Tac pharmacokinetic |
| Eastern Asian | |||
| 125 | As data on donor CYP3A5 (rs776746) were not included into the model conclusion should be taken cautiously | ||
| Ren et al[72] | Not stated | Recipient, donor: CYP3A5 (rs776746)1, FMO3 (rs1800822, rs2266782, rs1736557, rs909530, rs2266780) | Donor and recipient CYP3A5*3 genotype were associated with increased Tac concentration |
| Eastern Asian | Donor FMO3 rs1800822 allele T and rs909530 allele T were associated with decreased Tac concentration, independently on CYP3A5 genotype | ||
| 110 | |||
| Liao et al[73] | HCC | Recipient, donor: CYP3A5 (rs776746)1, C6 (rs9200, rs10052999) | Donor and recipient CYP3A5*3 genotype were confirmed to be associated with greater Tac concentration |
| Eastern Asian | Recipient C6 rs9200 G allele and donor rs10052999 CC/TT genotype were associated with decreased Tac concentration | ||
| 135 |
CYP non-related SNPs may affect tacrolimus concentration indirectly by changing CYP expression. This was demonstrated by Ou et al[70] who showed that lower levels of tacrolimus in TLR9 rs352139 G allele patients were associated with higher CYP3A5 mRNA expression in the liver. Similarly, SUMO4 rs237025 AA genotype was shown to be independently associated with decreased tacrolimus concentration and also with higher CYP3A5 mRNA expression[71]. The association with decreased tacrolimus concentration independent on CYP3A5 genotype was found for the donor FMO3 SNPs (rs1800822 allele T and rs909530 allele T)[72] and also for the sixth complement component (recipient C6 rs9200 G allele and donor rs10052999 CC/TT genotype), but the exact mechanism remains to be investigated[73]. Deng et al[74] analyzed association between tacrolimus metabolism related SNPs and early renal injury and found that CYP3A5*3 was associated with the risk of early glomerular lesion, while CYP2C8*3 was associated with the risk of tubulointerstitial injury.
In summary the reviewed studies confirmed the dominant role of CYP3A5 rs776746, (6986A>G) polymorphism, but also identified few novel SNPs involved in tacrolimus metabolism which might be a promising tool to reduce variability in tacrolimus concentration.
Reviewed studies confirmed previously established SNP prognostic factors such as the PNPLA3 rs738409 for NAFLD development and the role of CYP3A5 rs776746 in tacrolimus metabolism. They also identified several novel SNPs, which have the potential to become useful predictors of ACR, NODM, NAFLD, HCC recurrence, and post-transplant tacrolimus concentration variability. However, as the studies were typically conducted in one center on relatively low-to-moderate number of patients, verification of the results in other centers is warranted to resolve these limitations. Furthermore, of 29 reviewed studies, 28 used gene candidate approach and only one implemented a GWAS approach. GWAS multicentric studies are needed to facilitate the development of personalized transplant medicine.
Manuscript source: Invited Manuscript
Specialty type: Gastroenterology and hepatology
Country of origin: Croatia
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P-Reviewer: Ince V S-Editor: Wang J L-Editor: A E-Editor: Zhang YL
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