International Journal of Hematology

, Volume 98, Issue 3, pp 309–318

The role of non-HLA gene polymorphisms in graft-versus-host disease

Progress in Hematology New clinical and basic aspects of graft-versus-host disease

DOI: 10.1007/s12185-013-1416-7

Cite this article as:
Takami, A. Int J Hematol (2013) 98: 309. doi:10.1007/s12185-013-1416-7

Abstract

A large number of reports have associated various non-HLA gene polymorphisms with the risk and severity of graft-versus-host disease (GVHD). To date, candidate gene studies and genome-wide association studies have been performed to investigate such non-HLA gene polymorphisms in relation to GVHD. Candidate gene studies are hypothesis-driven and cost-effective, whereas genome-wide association studies have the potential to discover new gene polymorphisms, including possible biomarkers and therapeutic targets. Some gene polymorphisms have the potential to affect protein function or gene expression, or to encode minor histocompatibility antigens. Non-HLA genotyping for genes influencing GVHD prior to transplantation should provide useful information that will facilitate choosing the donor, type of graft, conditioning treatment, and GVHD prophylaxis. However, attention should be paid to the need for validation studies and ethical issues.

Keywords

Candidate gene studyGenome-wide association studySingle nucleotide polymorphism

Introduction

Graft-versus-host disease (GVHD) is the main cause of early mortality and morbidity after allogeneic hematopoietic stem cell transplantation (SCT) [13]. Although HLA matching represents the major genetic determinant of the clinical outcome after allogeneic SCT [46], GVHD also occurs in HLA identical transplants, indicating that non-HLA immune-associated genes are also involved in the process. Middeleton et al. [7] were the first to report that non-HLA gene polymorphisms were associated with SCT outcomes, showing a potential role of TNF and IL-10 polymorphisms in predicting acute GVHD. Since then, a large number of non-HLA genes, which mainly impact the individual immune response to infections and inflammatory reactions, have been reported to have polymorphisms associated with the risk and severity of GVHD [819]. These studies prompted us to better define the impact of non-HLA gene polymorphisms on the SCT outcomes and to incorporate these markers into routine pre- and post-transplant strategies. This review offers current knowledge on the contributions of non-HLA polymorphisms of the donor and recipient in GVHD after allogeneic SCT.

Classification of non-HLA gene polymorphisms

A gene polymorphism refers to an individual variation in the sequence of DNA found to cause a more than 1 % gene variation, which contrasts with a mutation, which is defined as an allele sequence found to have less than 1 % gene variation. A gene polymorphism occurs in non-coding regions more frequently than in coding regions. The non-HLA gene polymorphisms include single nucleotide polymorphisms (SNPs), tandem repeats (TRs) and copy number polymorphisms (CNPs), which are named in an allele-based manner (Fig. 1).
https://static-content.springer.com/image/art%3A10.1007%2Fs12185-013-1416-7/MediaObjects/12185_2013_1416_Fig1_HTML.gif
Fig. 1

A schematic diagram of the non-HLA gene polymorphisms

SNPs are individual variations of a DNA sequence, and more than 13 million SNPs have been identified through the 1000 genomes project [20]. A CNP is a difference in the copies of one or more sections of the DNA between individuals owing to duplication or deletion events, and affects a region one kbp to several Mbp in size [2124]. This is in contrast to the TR, such as minisatellites, microsatellites and short tandem repeats, in which a pattern of two to 1000 nucleotides is repeated and the repetitions are directly adjacent to each other.

Studies on the functional effects of gene polymorphisms will be helpful for demonstrating the pathways underlying GVHD. A gene polymorphism is considered to be functional when it affects the protein function or gene expression.

Some polymorphic genes encode proteins which are expressed on the cell surface and give an immunological response when the transplant donor and recipient are not identical, where the polymorphic genes are considered to encode minor histocompatibility antigens (mHAs). mHAs are short peptides that are presented on host HLA molecules and can stimulate alloreactive T-cell immune responses after SCT [25], which may lead to the development of GVHD. A polymorphic gene can encode mHAs that result in peptide sequences that can influence the intracellular processing or presentation of mHA peptides, and the stimulation of an alloreactive response if donors and recipients differ in their mHA genotypes.

Identification of non-HLA gene polymorphisms associated with GVHD

Two approaches are generally used to study non-HLA gene polymorphisms associated with GVHD, namely, candidate gene studies (CGS) and genome-wide association studies (GWAS). The CGS is the approach of choice to test a hypothesis and to confirm the findings of prior studies. Candidate genes are chosen based on their biological significance and/or previous reports showing their association with autoimmune diseases, infection immunity and organ transplant rejection. A genome-wide association study (GWAS) examines many gene polymorphisms with a hypothesis-free basis, and usually focuses on associations of SNPs and CNPs with diseases and traits. The major advantage of a CGS approach is its cost effectiveness and its focus on a particular gene polymorphism with known functional consequences, whereas a GWAS approach is expensive, and the results are often difficult to translate into functional knowledge. On the other hand, the CGS does not generally take into account the influence of confounding factors and considers only gene interactions, whereas the GWAS has the potential to uncover novel SNPs, such as possible biomarkers and therapeutic targets, with no bias.

For both the CGS and GWAS approaches, it is important that the association found in a discovery cohort is repeated using an independent cohort to validate the association. One interesting approach is validation of CGD results by a GWAS. Chien et al. [26] examined whether CGS-identified SNPs had a significant impact on the risk of acute GVHD in a GWAS using an independent cohort, and demonstrated the associations of the IL-2, IL-6, IL-10, CTLA4, HPSE and MTHFR genes with the development of acute GVHD. Validation of the GWAS results using a CGD approach and a functional investigation may also be promising.

Non-HLA polymorphisms associated with GVHD

The non-HLA gene polymorphisms demonstrated by large cohort studies to be associated with GVHD are summarized in Table 1. It should be noted that the polymorphic genes in the recipients are more commonly identified than those in the donors. Using a GWAS, Ogawa et al. [17] determined that there were more than half a million SNPs in 1598 recipient and unrelated donor pairs, and identified five novel SNPs (rs6937034, rs1137282, rs9657655, rs5998746 and rs11873016) associating with the risk of acute GVHD, which were all in the recipients. Compelling evidence from mouse models of GVHD and clinical data have indicated the importance of the cytokine storm in the pathophysiology of acute GVHD, and polymorphisms in cytokine and chemokine genes, such as IFNG, IL-1, IL-2, IL-6, IL-10, IL-17 and TNF, predict the development and severity of acute GVHD, as well as increases in the circulating levels of these cytokines. Activation of inflammatory pathways through these mediators occurs before infusion of donor T cells, which may account for the findings that many gene recipient-derived polymorphisms were critical for the risk of GVHD. These findings may be beneficial when considering the treatment strategy prior to treatment or during the pathogenesis of acute GVHD.
Table 1

Non-HLA gene polymorphisms associated with GVHD

Gene

Polymorphism

Function, ref.

Cohort (cases)

Type of GVHD

Genome

Ref.

BAFF

rs16972217

U

MRD and URD (164)

Acute, chronic

R

[48]

BAFF

rs7993590

U

MRD and URD (164)

Acute, chronic

R

[48]

BAFF

rs12428930

Yes [49]

MRD and URD (164)

Acute, chronic

R

[48]

BAFF

rs2893321

U

MRD and URD (164)

Acute, chronic

R

[48]

BPI

rs4358188

U

MRD and URD (304)

Acute

D

[50]

CCL5

rs1800825

U

(72)

Chronic

R

[51]

CCR5

rs1799987

U

URD (1,370)

Acute

D

[27]

CCR6

rs2301436

U

MRD (161)

Chronic

D

[52]

CCR6

rs3093023

U

MRD (161)

Chronic

D

[52]

CTLA4

rs231775

Yes [53]

MRD (536)

Acute

D

[53]

CTLA4

rs231775

Yes [53]

MRD (225)

Chronic

D

[54]

CTLA4

rs3087243

Yes [55]

URD (322)

Acute

D

[28]

CTLA4

rs3087243

Yes [55]

URD (686)

Acute

R

[26]

DAAM2

rs2504082

U

MRD (228)

Acute

R

[56]

DARC

rs2814778

Yes [57]

MRD (105)

Acute

D

[58]

DARC

rs12075

U

MRD (105)

Acute

D

[58]

ERA

intron 1 (AT)n

U

MRD (108)

Acute

R

[59]

FAS

rs1800682

No [60]

MRD (160)

Acute

R

[61]

FCGR3A

rs396991

Yes [62]

URD (99)

Chronic

R

[9]

FCRL3

rs7528684

Yes [63]

MRD (123)

Chronic

R

[64]

HLA-G

(14 bp)n

Yes [65]

URD (53)

Acute

R

[66]

HMGB1

rs41376448

U

MRD and URD (422)

Acute

R

[67]

HPSE

rs4364254

Yes [68]

URD (414)

Acute, chronic

R

[69]

HPSE

rs4693608

Yes [68]

URD (414)

Acute, chronic

R

[69]

HPSE

rs4364254

Yes [68]

URD (686)

Acute

R

[26]

HSPA1L

rs2075800

U

MRD and URD (64)

Acute

R

[70]

H-Y

Y-chromosome

Yes [71]

MRD and URD (53,988)

Chronic

M

[44]

IFNG

intron 1 (CA)n

Yes [72]

MRD (80)

Acute

R

[73]

IFNG

intron 1 (CA)n

Yes [72]

MRD (80)

Acute

R

[73]

IMPD

rs2278294

U

MRD and URD (240)

Acute

R

[74]

IL-1A

rs1800587

Yes [75]

MRD (115)

Chronic

D

[76]

IL-1RA

(86 bp)n

Yes [77]

MRD (99)

Acute

D

[78]

IL-1RA

(86 bp)n

Yes [77]

MRD (107)

Acute

D

[79]

IL-2

rs2069762

Yes [80]

URD (95)

Acute, chronic

R

[80, 81]

IL-2

rs2069762

Yes [80]

URD (322)

Chronic

R

[28]

IL-2

rs2069762

Yes [80]

URD (686)

Acute

D

[26]

IL-6

rs1800795

Yes [82]

MRD (160)

Acute

D

[61]

IL-6

rs1800795

Yes [82]

MRD (80)

Chronic

R

[73]

IL-6

rs1800795

Yes [82]

MRD (100)

Chronic

R

[83]

IL-6

rs1800795

Yes [82]

MRD and URD (166)

Acute

R

[84]

IL-6

rs1800795

Yes [82]

MRD (93)

Acute

D

[85]

IL-6

rs1800795

Yes [82]

URD (686)

Acute

D

[26]

IL-6

rs1800795

Yes [82]

MRD (612)

Acute

R

[26]

IL-6

rs1800795

Yes [82]

MRD (612)

Acute

D

[26]

IL-10

rs1800872

Yes [86, 87]

MRD (309)

Acute

R

[88]

IL-10

rs1800872

Yes [86, 87]

MRD (100)

Acute

R, D

[83]

IL-10

rs1800872

Yes [86, 87]

MRD (100)

Acute

R

[89]

IL-10

rs1800872

Yes [86, 87]

MRD (953)

Acute

R

[90]

IL-10

rs1800872

Yes [86, 87]

MRD (107)

Chronic

R

[79]

IL-10

rs1800872

Yes [86, 87]

MRD (612)

Acute

R

[26]

IL-10

rs1800871

Yes [86, 87]

MRD (612)

Acute

R

[26]

IL-10

(CA)n

U

MRD (49)

Acute

R

[7]

IL-10

(CA)n

U

MRD (144)

Acute

R

[91]

IL-10

(CA)n

U

MRD and URD (62)

Chronic

D

[92]

IL-10

(CA)n

U

MRD (88)

Acute

R

[93]

IL-10RB

rs2834167

Yes [86, 87]

MRD (309)

Acute

R

[88]

IL-10RB

rs2834167

Yes [86, 87]

MRD (953)

Acute

D

[90]

IL-17

rs2275913

Yes [17]

URD (510)

Acute

R

[16]

IL-17

rs2275913

Yes [17]

URD (438)

Acute

D

[17]

IL-23R

rs11209026

Yes [94]

MRD and URD (407)

Acute

D

[95]

IL-23R

rs11209026

Yes [94]

MRD and URD (231)

Acute

D

[96]

IL-23R

rs11209026

Yes [94]

MRD and URD (304)

Acute

D

[50]

MADCAM1

rs2302217

U

MRD (87)

Chronic

R

[97]

MTHFR

rs1801131

Yes [98]

MRD (159)

Acute

R

[10]

MTHFR

rs1801131

Yes [98]

MRD and URD (304)

Acute

R

[99]

MTHFR

rs1801131

Yes [98]

MRD (612)

Acute

R

[26]

MTHFR

rs1801133

Yes [98]

MRD (140), URD (53)

Acute, chronic

D

[100]

MTHFR

rs1801133

Yes [98]

MRD (140)

Acute

D

[101]

NKG2D

rs1049174

Yes [16]

URD (145)

Acute

D

[14]

NOD2

rs2066844

Yes [102]

URD (342)

Acute

D

[103]

 

rs2066845

     
 

rs2066847

     

NOD2

rs2066844

Yes [102]

MRD (403)

Acute

R, D

[104]

 

rs2066845

     
 

rs2066847

     

PARP1

rs1805410

U

URD (470)

Chronic

R

[105]

PECAM-1(CD31)

rs668

U

MRD (85)

Acute

D

[106]

PECAM-1(CD31)

rs668

U

MRD (102)

Acute

D

[107]

PECAM-1(CD31)

rs12953

U

MRD (112)

Acute

M

[108]

PECAM-1(CD31)

rs1131012

U

MRD (74)

Acute

D

[109]

PTPN22

rs2488457

U

URD (663)

Acute

R

[15]

PTPRC

rs17612648

Yes [110]

URD (44)

Acute

D

[110]

RFC1

rs6844176

U

URD (470)

Acute

R

[105]

TGFB1

rs1800470

Yes [111]

MRD and URD (24)

Acute

R

[112]

TGFB1

rs1800470

Yes [111]

MRD and URD (168)

Acute

R

[113]

TGFB1

rs1800470

Yes [111]

MRD (77)

Acute

D

[114]

TGFB1RII

rs2228048

U

MRD (77)

Acute

R

[114]

TLR1

rs4833079

U

MRD (305)

Acute

R

[115]

TLR4

rs4837656

U

MRD (305)

Acute

R

[115]

TLR4

rs17582214

U

MRD (305)

Acute

R

[115]

TLR4

rs4986791

Yes [116]

MRD (403)

Acute

R, D

[104]

TLR5

rs10737416

U

MRD (305)

Acute

R

[115]

TLR5

rs2800230

U

MRD (305)

Chronic

D

[115]

TLR5

rs2800237

U

MRD (305)

Chronic

D

[115]

TLR6

rs6531656

U

MRD (305)

Acute

D

[115]

TLR10

rs337629

U

MRD (305)

Acute

D

[115]

TNF

(TNFd)n

Yes [73]

MRD (49)

Acute

R

[7]

TNF

(TNFd)n

Yes [73]

MRD (80)

Acute

R

[73]

TNF

(TNFd)n

Yes [73]

MRD and URD (62)

Acute

D

[92]

TNF

rs1799964

Yes [117]

URD (922)

Acute

M

[28]

TNF

rs1800610

U

MRD (160)

Acute, chronic

R, D

[61]

TNF

rs1800630

No [118]

URD (462)

Acute

R, D

[119]

TNF

rs1799724

U

URD (462)

Acute

R, D

[119]

TNFRII

rs1061622

Yes [120]

MRD (104)

Acute

R

[120]

TNFRII

rs1061622

Yes [120]

MRD (104)

Chronic

D

[120]

TNFRII

rs1061622

Yes [120]

URD (462)

Chronic

D

[119]

TSER

(28 bp)n

Yes [121]

MRD and URD (304)

Acute

D

[99]

UGT2B17

129 kbp deletion

Yes [122]

MRD (1,345)

Acute

M

[41]

VDR

intron 8 CNP

Yes [123]

MRD (88)

Acute

R

[93]

VEGFA

rs699947

Yes [124, 125]

MRD (98)

Acute

R

[126]

VEGFA

rs833061

Yes [124, 125]

MRD (98)

Acute

R

[126]

U

rs6937034

U

URD (1,598)

Acute

M

[127]

KRAS

rs1137282

U

URD (1,598)

Acute

M

[127]

U

rs9657655

U

URD (1,598)

Acute

M

[127]

U

rs5998746

U

URD (1,598)

Acute

R

[127]

U

rs11873016

U

URD (1,598)

Acute

R

[127]

CNP copy number polymorphism, TR tandem repeat, U unknown, MRD matched-related donor, URD unrelated donor, D donor, R recipient, M mismatch between recipient and donor

Polymorphisms of immunoregulatory genes associated with GVHD

C–C chemokine receptor type (CCR) 5 is a chemokine receptor and its ligands include C–C motif ligand (CCL) 3, CCL4, CCL5 and CCL3L1. A large cohort study demonstrated that the donor CCL5 genotype significantly influenced the risk of severe acute GVHD and disease-free survival [27].

Harkensee et al. [28] reevaluated 41 previously documented SNPs in two independent, large cohorts, and showed an association of the TNF and CTLA4 SNPs with acute GVHD and an association of the IL-2 SNP with chronic GVHD.

The PTPN22 gene encodes lymphoid-specific phosphatase (Lyp) and is an important negative regulator of T-cell activation involved in the dephosphorylation and inactivation of TCR-associated kinases. A SNP of the PTPN22 promoter gene, rs2488457 (G/C), is associated with the susceptibility to autoimmune diseases. In unrelated bone marrow transplantation, the recipient C/C genotype is associated with a significantly lower incidence of grade II–IV acute GVHD and a higher incidence of relapse, which predict worse survival outcomes for patients with high-risk disease [15].

Functional polymorphisms

IL-17 is the hallmark cytokine of Th17 cells and plays important roles in the host defense, the pathophysiology of autoimmune diseases and organ allograft rejection. Although several studies using mouse models showed a significant impact of IL-17 on the development of acute GVHD [2935], the results were not consistent. Espinoza et al. were the first to report an association of the rs2275913 SNP (G/A) in the promoter of the IL-17 gene with the development of acute GVHD [17, 36]. Notably, the rs2275913 SNP is located within a binding motif for nuclear factor activated T cells (NFAT), which is a critical regulator of the IL-17 promoter [37]. The same group demonstrated that the A allele of the IL-17 gene makes patients susceptible to acute GVHD because it correlates with more efficient IL-17 secretion through its higher affinity for NFAT than the G allele [17]. These findings suggest not only the functional relevance of the IL-17 promoter SNPs with the development of acute GVHD, but also the involvement of IL-17 in the development of acute GVHD, leading to a hypothesis that IL-17-producing cells can modify the function of host dendritic cells (DCs) through unknown mechanisms. The direct interaction between IL-17 and host DCs may be supported by the fact that DCs express IL-17 receptors [38]. A better understanding of the molecular mechanism by which this promoter SNP controls the production of IL-17 may therefore offer some novel therapeutic insights into the mechanisms underlying the development of other IL-17-related diseases, including rheumatoid arthritis, periodontal disease, multiple sclerosis, allergic rhinitis, psoriasis, inflammatory bowel disease and organ allograft rejection [39].

mHAs

McCarroll et al. [40] identified 1316 CNPs using genotyping arrays with higher SNPs density and copy number probes accompanied by newer algorithms. Among them, donor-negative and recipient-positive mismatch of the UGT2B17 CNP showed an association with acute GVHD [41]. This is consistent with a previous report [42] showing that the protein encoded by the UGT2B17 gene is a mHA that is selectively expressed in the liver, intestine and antigen-presenting cells, and that it plays a causative role in acute GVHD.

Cellular proteins encoded by the Y-chromosome can also operate as mHAs when male recipients receive SCT grafts from female donors [43, 44].

Conclusion

The determination of the non-HLA genotypes associated with GVHD prior to transplantation will provide patients an opportunity to receive optimal strategies in terms of the selection of the donor, type of graft, conditioning treatment and GVHD prophylaxis. However, several issues remain unresolved that need to be addressed before mainstream non-HLA genotyping can be implemented in clinical practice. First, the abundance of non-HLA gene polymorphisms identified should be validated by individual, multi-racial cohorts irrespective of whether CGS and GWAS approaches were used, because the study populations may critically impact on results, as has also been seen in HLA association studies [4, 45, 46]. Second, whether a polymorphic gene has a functional role and mHA nature should be determined to obtain a better understanding of the molecular mechanisms by which the gene polymorphism can influence the GVHD, offering novel therapeutic insights into GVHD, as well as other autoimmune diseases in which the polymorphic gene is involved. There is also a possibility that the gene polymorphism of interest may coordinate with other genes, and/or have close linkage with another gene with functional and/or immunogenic properties. Finally, systemic discovery of new genetic biomarkers using GWAS will add weight in the decade ahead, but informed consent and privacy protection remain issues that need specific attention, because GWAS create a large amount of individual-specific digital information that is easy to share across international borders [47].

Acknowledgments

This study was supported by grants from the Ministry of Health, Labor and Welfare of Japan, and the Ministry of Education, Culture, Sports and Technology of Japan. This work was supported in part by a Research on Allergic Disease and Immunology (H23-010) in a Health and Labor Science Grant from the Ministry of Health, Labor and Welfare of Japan. The grant sources played no role in the study design, data collection and analysis, the decision to publish or the preparation of the manuscript.

Conflict of interest

The authors declare no competing financial interests.

Copyright information

© The Japanese Society of Hematology 2013

Authors and Affiliations

  1. 1.Department of Hematology and OncologyKanazawa University HospitalKanazawaJapan