Genetic risk factors contribute to adverse outcome of hematopoietic stem cell transplantation (HSCT). Mismatching of the HLA complex most strongly determines outcomes, whereas non-HLA genetic polymorphisms are also having an impact. Although the majority of HSCTs are mismatched, only few studies have investigated the effects of non-HLA polymorphisms in the unrelated HSCT and HLA-mismatched setting. To understand these effects, we genotyped 41 previously studied single nucleotide polymorphisms (SNPs) in 2 independent, large cohorts of HSCT donor-recipient pairs (n = 460 and 462 pairs) from a homogeneous genetic background. The study population was chosen to pragmatically represent a large clinically homogeneous group (acute leukemia), allowing all degrees of HLA matching. The TNF-1031 donor-recipient genotype mismatch association with acute GVHD grade 4 was the only consistent association identified. Analysis of a subgroup of higher HLA matching showed consistent associations of the recipient IL2-330 GT genotype with risk of chronic GVHD, and the donor CTLA4-CT60 GG genotype with protection from acute GVHD. These associations are strong candidates for prediction of risk in a clinical setting. This study shows that non-HLA gene polymorphisms are of relevance for predicting HSCT outcome, even for HLA mismatched transplants.

Introduction

It is thought that a large proportion of risk for adverse outcomes after hematopoietic stem cell transplantation (HSCT) is genetic, attributed to HLA matching,1  killer-immunoglobulin-like receptor matching,2,3  minor histocompatibility antigens,4,5  and non-HLA gene polymorphisms.6 

Whereas the degree of HLA mismatching exerts the strongest genetic effect on risks, such as acute and chronic GVHD, relapse, and survival, non-HLA polymorphisms in immune response genes, such as cytokines, at least modify these risks, as shown in studies that have shown light on the pathobiology of HSCT,7,8  and the relation of cytokine gene polymorphisms,6,9,10  with gene expression and biologic effects.11,12,13,1415 

Non-HLA gene polymorphisms have been widely studied (a systematic search conducted revealed 192 studies over the last 2 decades). Most of these studies used a candidate gene approach, and only one study was a genome-wide association study.5  To minimize genetic confounding, most of these studies used either fully or largely HLA-matched related or unrelated HSCT cohorts. Limited availability of study subjects in the past made consideration of demographic or clinical risk factors in study cohort selection difficult, despite the existence of these risks being well established in the literature (eg, patient and donor age,16,17  female donor to male recipient,18  diagnosis and staging, prior chemotherapy, conditioning regimen,19  concurrent infections). Although more than 100 genetic markers in more than 60 candidate genes have been studied, consistency of results has been poor across studies, which has been attributed to differences in HSCT setting or stem cell source, ethnicity of the population, marker genotype distribution, and study quality and power. Only a limited number of associations underwent replication studies, and very few of these showed some consistency in different settings, such as polymorphisms in TNF, IL10, IL6, CTLA4.6 

HLA mismatching is common in daily unrelated donor HSCT practice, most commonly because of nonavailability of an HLA-matched donor. In the Japan Marrow Donor Program (JMDP), less than 10% of HSCT have a 12 of 12 allele HLA match, and approximately 30% have an 8 of 8 allele HLA match. Despite this, only a very small number of studies have deliberately used populations that represent the full spectrum of HLA matching.

It is an important clinical question whether non-HLA polymorphisms have an impact on HSCT outcome in an unrelated HSCT population despite the competing effects of HLA mismatching.

The aim of this study was to identify genetic polymorphisms influencing HSCT outcome in an unrelated donor, HLA-mismatched setting, pragmatically choosing a large diagnostic group (acute leukemia) with additional selection and correction for the most relevant confounding variables (see “Population”). We applied a study design aiming to comply with recommendations for more stringent genetic association study designs,20,21,22,2324  testing a panel of strong candidate SNP markers from previous studies. Key features include significance as well as effect size testing on 2 large, independent, clinically homogeneous study cohorts stemming from a population of homogeneous ethnic background.

Methods

Population

Donor and recipient HSCT pairs were selected from the JMDP registry of unrelated HSCT. This study was approved by the review boards of the JMDP and Tokai University Medical School, Isehara, Kanagawa, Japan. We chose pairs with a diagnosis of acute leukemia. These form the largest subgroup within HSCT. Cohorts represented 2 samplings of the same national pool, taken from 2 distinct timeframes (1993-2000, 2001-2005). Inclusion criteria were diagnosis (acute lymphoblastic leukemia; acute nonlymphoblastic leukemia), age (4-40 years), conditioning (myeloablative), and stem cell source (bone marrow). All transplants were T-cell replete and received GVHD prophylaxis with either cyclosporin A or tacrolimus with methotrexate and corticosteroids. Analysis of the source as well as the selected HSCT population showed that HLA mismatching, donor age, and GVHD prophylaxis regimen (cyclosporin A vs tacrolimus) were the only confounders remaining significant in multivariate analysis (data not shown here).

All donor-recipient pairs were HLA-typed retrospectively to allele level at 6 loci (HLA-A, HLA-B, HLA-C, HLA-DRB1, HLA-DQB1, and HLA-DPB1). The distribution of HLA matching of the confirmatory cohort was adjusted to that of the screening cohort by matching each sample of the screening cohort with a confirmatory cohort sample of the same HLA class or HLA class combination according to the previous literature25,26  and our own analyses of risk matches/mismatches within this study population (data not shown). Supplemental Table 1 (available on the Blood Web site; see the Supplemental Materials link at the top of the online article) shows the demographic and clinical characteristics of the selected cohorts. There was no statistically significant difference between the cohorts in the baseline demographic criteria. Supplemental Table 2A and B specify the degree of HLA matching and mismatching. For reasons of comparison, we have used the National Marrow Donor Program/Center for International Blood and Marrow Transplant Research classification of HLA matching.27  According to this classification, 357 HSCT pairs have an 8 of 8 (HLA A, B, C, DRB1) high-resolution allele match, 331 (35.9%) are partially matched (1 mismatch within these HLA loci), and 234 (25.4%) are mismatched (2 or more mismatches within these HLA loci). Considering the HLA DQ and DP loci also, only 78 HSCT pairs (8.5%) had a 12 of 12 allele match. In Japanese, HLA A, B, and C mismatches are associated with risk of acute GVHD. HLA C mismatches, however, have a protective effect on relapse (whereas HLA A, C, and B mismatches associate with a risk of death).25,26,28  More recent research has focused on specific allele mismatches, rather than mismatches in loci, aiming to identify nonpermissive mismatches for acute GVHD29  or protective mismatches against relapse,30  as well as risk HLA haplotypes for GVHD.31 

Gene and SNP marker selection

Selection of candidate markers was based on a search of the published literature on genetic associations with HSCT outcomes. As the TaqMan SNP genotyping platform was used, selection was limited to markers for which standard assays were available for this system.

For some genetic loci, the same markers that were associated in other populations were nonpolymorphic in Japanese (NOD2, TGFB1). The HapMap database (www.hapmap.org) was used to identify haploTag SNP for these loci.

The SNP markers included in this study are detailed in Table 1; the assay details are available in supplemental Methods.

Table 1

Selected candidate SNP markers of this study

Target gene SNP Target gene SNP 
CCL4 rs2634508 NOD2 rs1077861 
CD86 rs1129055  rs1861757 
CTLA4 rs231777  rs1861759 
 rs231775 (CTLA4–49)  rs6500328 
 rs3087243 (CTLA-CT60)  rs2111234 
FAS rs1800682 (FAS-670)  rs2111235 
FCGR2A rs1801274  rs7203344 
HLA-E rs1264457 (HLA-E R128G)  rs17313265 
 rs1800795 TGFB1 rs1800469 (TGFB1-509) 
HSP70/hom rs2075800  rs2241715 
IFNg rs2069705  rs2241716 
IL1A rs1800587 (IL1A-889)  rs4803455 
IL1B rs16944 (IL1B-511) TLR4 rs12377632 
IL2 rs2069762 (IL2-330)  rs1927907 
IL10 rs1800896 (IL10-1082) TNF rs361525 (TNF-238) 
 rs1800871 (IL10-819)  rs1799964 (TNF-1031) 
 rs1800872 (IL10–592)  rs1800629 (TNF-308) 
IL15RA rs2228059 (IL15RA N182T)  rs1799724 (TNF-857) 
IL23R rs6687620 TNFRSF1B rs1061622 (TNFR2 codon 196) 
MIF rs755622 VDR rs731236 
MTHFR rs1801133 (MTHFR C677T)   
Target gene SNP Target gene SNP 
CCL4 rs2634508 NOD2 rs1077861 
CD86 rs1129055  rs1861757 
CTLA4 rs231777  rs1861759 
 rs231775 (CTLA4–49)  rs6500328 
 rs3087243 (CTLA-CT60)  rs2111234 
FAS rs1800682 (FAS-670)  rs2111235 
FCGR2A rs1801274  rs7203344 
HLA-E rs1264457 (HLA-E R128G)  rs17313265 
 rs1800795 TGFB1 rs1800469 (TGFB1-509) 
HSP70/hom rs2075800  rs2241715 
IFNg rs2069705  rs2241716 
IL1A rs1800587 (IL1A-889)  rs4803455 
IL1B rs16944 (IL1B-511) TLR4 rs12377632 
IL2 rs2069762 (IL2-330)  rs1927907 
IL10 rs1800896 (IL10-1082) TNF rs361525 (TNF-238) 
 rs1800871 (IL10-819)  rs1799964 (TNF-1031) 
 rs1800872 (IL10–592)  rs1800629 (TNF-308) 
IL15RA rs2228059 (IL15RA N182T)  rs1799724 (TNF-857) 
IL23R rs6687620 TNFRSF1B rs1061622 (TNFR2 codon 196) 
MIF rs755622 VDR rs731236 
MTHFR rs1801133 (MTHFR C677T)   

Genotyping

TaqMan SNP genotyping assays (Applied Biosystems) were applied for 38 selected SNP according to the maker's instructions.

The IL10 promoter SNPs rs1800872 (-592A/C), rs1800871 (-819T/C), and rs1800896 (-1082A/G) were genotyped by PCR-SSO using Luminex Multi-Analyte Profiling system (xMAP; Luminex). Details of both genotyping methods can be found in supplemental Methods.

Statistical analysis

Genotype results were imported into SPSS Statistics Version 17.0 (SPSS Inc). Because little is known about effects of non-HLA polymorphisms in HLA-mismatched populations, we used 3 analytic approaches to identify significant associations: 2-sided Fisher exact test (95% confidence intervals [CIs]) with Bonferroni correction for significance testing, odds ratio (OR; 95% CIs) as a measure of effect size, and independent testing in a confirmatory cohort (without application of multiple testing correction). Variables were the 3 individual genotypes, and mismatch between donor and recipient genotypes. Outcomes were acute GVHD (0-4), acute GVHD grades 2 to 4, acute GVHD grades 3 to 4, acute GVHD grade 4, chronic GVHD, extensive chronic GVHD, relapse, death (overall, at 100 d/1 y/3 y), and survival (as log-rank test in Kaplan-Meier analysis). For the screening cohort, we considered as significant a P value of .05 with Bonferroni correction for the number of SNP markers tested. As the P value is not a good surrogate marker for effect size, and often small in HSCT-outcome association studies, we decided to separately include associations showing ORs of less than or equal to 0.5 and ≥ 2.0 (this follows observations of ORs of significant markers in previous studies).

Screening and confirmatory cohort data were analyzed on the overall cohort in the first instance. To reduce confounding by HLA mismatching, we conducted identical analyses on a subgroup with a higher degree of HLA matching (8 of 8 allele matching at the HLA A, B, C, DRB1 loci, with additional exclusion of combined HLA-DQB1 and DPB1 mismatches; allowing for either a HLA-DQB1 or a HLA-DPB1 mismatch only), similar to previous reports from JMDP,5  resulting in cohorts of 160 (discovery) and 166 (confirmatory) pairs.

For the screening cohort, we would genotype all 41 chosen SNP markers (Table 1) on both donor and recipient cohorts and conduct overall and subgroup analyses. Markers only that show a corrected P value of less than .05 and/or an OR of less than or equal to 0.5 and more than or equal to 2.0 in either the overall or the subgroup analyses would be selected for confirmatory typing. If a marker showed an association that was persisting when applying Bonferroni correction, we tested other associations of the same marker in the confirmatory cohort, even if these would not reach the multiple testing thresholds, to capture borderline significance or effect size of genotypes, building on the strength of testing in an independent confirmatory cohort.

Given the high degree of linkage between the CTLA4 as well as the IL10 SNPs in the study, unambiguous haplotypes could be determined directly without recourse to computational methods.

As the distribution of acute GVHD degrees of severity was significantly different between the screening and confirmation cohort, all associations with acute GVHD as outcome were reanalyzed after randomizing the study population into 2 different cohorts (using an online based tool for random assignment: http://www1.assumption.edu/users/avadum/applets/RandAssign/GroupGen.html).

Multivariate analysis was performed on the combined cohorts using STATA Version 11.0. OR of acute GVHD for the selected SNP in multivariate analysis was estimated by a multivariate logistic regression analysis with the adjustment for recipient and donor ages, underlying diagnosis, the use of total body irradiation, antithymoglobulin, female donor into male transplant, GVHD prophylaxis (tacrolimus vs cyclosporin A), relapse, and HLA mismatch to address possible confounding.

Results

Screening cohort

All transplants (n = 460 pairs).

In the screening cohort, involving 460 bone marrow transplants performed between 1993 and 2000, 41 single nucleotide SNP markers were typed in both patient and donor cohorts. Of these, 6 markers were excluded from analysis, for technical (multiple clusters: rs1927907, rs4803455) and statistical reasons (minor allele frequency < 5%: rs1800795, rs6687620, rs361525, rs1800629). All 35 markers included in the analysis were in Hardy-Weinberg equilibrium (defined as P > .05, with statistical correction for the number of tested markers).

Thirteen markers, plus the IL10 and CTLA4 haplotypes, showed an association with an HSCT outcome in the donor screening cohort (Table 2). By significance testing applying Bonferroni correction, only the marker IL10-1082 and the CTLA4 haplotype showed significant association, whereas 3 further markers were selected for confirmatory typing by their effect size (marker CTLA4 rs231775 also shows relevant effect size individually; marker CTLA4 rs231777, which showed no individual association, was included in the confirmatory cohort as part of the CTLA4 haplotype, not listed in Table 2). The recipient cohort (Table 3) revealed 15 markers, plus the CTLA4 haplotype, that were associated with a HSCT outcome. The IL2-330 SNP and the CTLA4 haplotype revealed significant associations above the multiple testing thresholds, whereas 5 SNP markers had ORs ≤ 0.5 and ≥ 2.0.

Table 2

Results of SNP genotyping on all donor samples

Gene Marker Discovery cohort (genotype and association) Confirmatory cohort (genotype and association) 
CTLA4 rs231775 AA aGVHD* (P = .0043, OR = 0.049,* CI = 0.028-0.083) NS 
  GG aGVHD (P = .0071, OR = 1.90, CI = 1.19-3.03)  
CTLA4 rs3087243 GG aGVHD (P = .0086, OR = 1.81, CI = 1.18-2.78) NS 
CTLA4 Haplotype CAA aGVHD (P = .0025, OR = 0.59, CI = 0.42-0.82) NS 
  CGG aGVHD* (P = .00057,* OR = 1.72, CI = 1.27-2.34)  
FAS rs1800682 CC aGVHD4* (P = .023, OR = 0.21,* CI = 0.37-0.96) NS 
IFNg rs2069705 CC ext cGVHD (P = .035, OR = 0.57, CI = 0.33-0.96) NT 
  CC relapse (P = .04, OR = 0.60, CI = 0.37-0.96)  
IL10 rs1800896 AA survival* (P = .001)* protective NS 
IL10 Haplotype CCA survival (P = .032) protective NT 
MTHFR rs1801133 CT cGVHD (P = .03, OR = 0.63, CI = 0.42-0.96) NT 
NOD2 rs17313265 CT survival (P = .012) risk NT 
  CC survival (P = .008) protective NT 
NOD2 rs2111235 TT aGVHD4* (P = .016, OR = 0.33,* CI = 0.14-0.80) NS 
NOD2 rs6500328 GG ext cGVHD* (P = .011, OR = 0.17,* CI = 0.023-0.78) NS 
TGFB1 rs1800469 CC aGVHD2-4 (P = .035, OR = 1.69, CI = 1.09-2.61) NT 
  CT aGVHD2-4 (P = .036, OR = 0.66, CI = 0.45-0.96) NT 
TGFB1 rs2241715 GG aGVHD2-4 (P = .047, OR = 1.64, CI = 1.06-2.53) NT 
  GT survival (P = .03) protective NT 
  GT ext cGVHD (P = .032, OR = 0.57, CI = 0.34-0.94) NT 
  GT aGVHD2-4 (P = .037, OR = 0.67, CI = 0.46-0.98) NT 
TNF rs1799964 TT relapse (P = .041, OR = 1.71, CI = 1.04-2.82) NT 
TNF rs1799724 CC survival (P = .014) protective NT 
Gene Marker Discovery cohort (genotype and association) Confirmatory cohort (genotype and association) 
CTLA4 rs231775 AA aGVHD* (P = .0043, OR = 0.049,* CI = 0.028-0.083) NS 
  GG aGVHD (P = .0071, OR = 1.90, CI = 1.19-3.03)  
CTLA4 rs3087243 GG aGVHD (P = .0086, OR = 1.81, CI = 1.18-2.78) NS 
CTLA4 Haplotype CAA aGVHD (P = .0025, OR = 0.59, CI = 0.42-0.82) NS 
  CGG aGVHD* (P = .00057,* OR = 1.72, CI = 1.27-2.34)  
FAS rs1800682 CC aGVHD4* (P = .023, OR = 0.21,* CI = 0.37-0.96) NS 
IFNg rs2069705 CC ext cGVHD (P = .035, OR = 0.57, CI = 0.33-0.96) NT 
  CC relapse (P = .04, OR = 0.60, CI = 0.37-0.96)  
IL10 rs1800896 AA survival* (P = .001)* protective NS 
IL10 Haplotype CCA survival (P = .032) protective NT 
MTHFR rs1801133 CT cGVHD (P = .03, OR = 0.63, CI = 0.42-0.96) NT 
NOD2 rs17313265 CT survival (P = .012) risk NT 
  CC survival (P = .008) protective NT 
NOD2 rs2111235 TT aGVHD4* (P = .016, OR = 0.33,* CI = 0.14-0.80) NS 
NOD2 rs6500328 GG ext cGVHD* (P = .011, OR = 0.17,* CI = 0.023-0.78) NS 
TGFB1 rs1800469 CC aGVHD2-4 (P = .035, OR = 1.69, CI = 1.09-2.61) NT 
  CT aGVHD2-4 (P = .036, OR = 0.66, CI = 0.45-0.96) NT 
TGFB1 rs2241715 GG aGVHD2-4 (P = .047, OR = 1.64, CI = 1.06-2.53) NT 
  GT survival (P = .03) protective NT 
  GT ext cGVHD (P = .032, OR = 0.57, CI = 0.34-0.94) NT 
  GT aGVHD2-4 (P = .037, OR = 0.67, CI = 0.46-0.98) NT 
TNF rs1799964 TT relapse (P = .041, OR = 1.71, CI = 1.04-2.82) NT 
TNF rs1799724 CC survival (P = .014) protective NT 

P values (2-sided Fisher exact test; survival, log rank test, Kaplan-Meier). Marker rs231777 had no individual association and is therefore not included in this table, but it was included into the confirmatory cohort as part of the CTLA4 haplotype.

aGVHD indicates acute GVHD; aGVHD4, acute GVHD grade 4; aGVHD2-4, acute GVHD grade 2-4; cGVHD, chronic GVHD; ext cGVHD, extensive chronic GVHD; mismatch, genotype mismatch between donor and recipient; NS, not significant; and NT, not tested.

*

Withstanding Bonferroni multiple testing corrections or have OR ≤ 0.5 or ≥ 2.

Table 3

Significant results of SNP genotyping on all recipient samples

Gene Marker Discovery cohort (genotype and association) Confirmatory cohort (genotype and association) 
CTLA4 rs231775 AA cGVHD (P = .046, OR = 1.83, CI = 1.02-3.28) NS 
CTLA4 rs231777 Mismatch aGVHD (P = .004, OR = 1.91, CI = 1.24-2.96) NS 
CTLA4 haplotype CAA cGVHD (P = .011, OR = 1.5, CI = 1.11-2.03) NS 
  CGG cGVHD* (P = .0013,* OR = 0.62, CI = 0.47-0.83) NS 
  CGG aGVHD2-4 (P = .019, OR = 0.70, CI = 0.52-0.94) NS 
  TAG aGVHD4* (P = .0071, OR = 3.71,* CI = 1.56-8.86) NS 
FAS rs1800682 CC relapse (P = .017, OR = 1.68, CI = 1.03-2.74) NS 
  CT relapse* (P = .0025, OR = 0.50,* CI = 0.33-0.78) NS 
  CT aGVHD (P = .009, OR = 1.79, CI = 1.15-2.77) NS 
  TT cGVHD (P = .024, OR = 1.75, CI = 1.03-2.82) NS 
  TT ext cGVHD (P = .014. OR = 1.74, CI = 1.03-2.94) NS 
HLA-E rs1264457 Mismatch survival (P = .023) risk NT 
IL1A rs1800578 Mismatch aGVHD2-4 (P = .026, OR = 1.69, CI = 1.11-2.56) NT 
IL1B rs16944 AA aGVHD (P = .048, OR = 0.63, CI = 0.39-0.99) NT 
  GG aGVHD (P = .032, OR = 1.75, CI = 1.08-2.82) NT 
IL15RA rs2228059 AC survival (P = .024) risk NT 
IL2 rs2069762 GG aGVHD4* (P = .0014,* OR = 4.51,* CI = 1.91-10.6) NS 
  GT survival (P = .0021) protective NS 
  TT survival (P = .0061) risk NS 
NOD2 rs17313265 CC aGVHD2-4 (P = .036, OR = 2.15, CI = 1.06-4.37) NS 
TGFB1 rs1800469 Mismatch aGVHD2-4 (P = .02, OR = 1.63, CI = 1.1-6.4) NT 
TGFB1 rs2241715 Mismatch aGVHD2-4 (P = .015, OR = 1.61, CI = 1.09-2.39) NT 
  Mismatch cGVHD (P = .035, OR = 1.58, CI = 1.04-2.41) NT 
TGFB1 rs2241716 AA ext cGVHD* (P = .0041, OR = 2.58,* CI = 1.36-4.87) NS 
TNF rs1799964 Mismatch aGVHD4*† (P = .022, OR = 2.53,*† CI = 1.16-5.53) Mismatch aGVHD4*† (P = .0053, OR = 3.40,*† CI = 1.48-7.81) 
  CC aGVHD4* (P = .041, OR = 4.92,* CI = 1.27-19.02) CC aGVHD4 trend (P = .06) 
TNF rs1799724 CC survival (P = .02) protective, NT 
  CT survival (P = .02) risk NT 
TNFRSF1B rs1061622 TT aGVHD4* (P = .023, OR = 4.69,* CI = 1.1-20.11) NS 
Gene Marker Discovery cohort (genotype and association) Confirmatory cohort (genotype and association) 
CTLA4 rs231775 AA cGVHD (P = .046, OR = 1.83, CI = 1.02-3.28) NS 
CTLA4 rs231777 Mismatch aGVHD (P = .004, OR = 1.91, CI = 1.24-2.96) NS 
CTLA4 haplotype CAA cGVHD (P = .011, OR = 1.5, CI = 1.11-2.03) NS 
  CGG cGVHD* (P = .0013,* OR = 0.62, CI = 0.47-0.83) NS 
  CGG aGVHD2-4 (P = .019, OR = 0.70, CI = 0.52-0.94) NS 
  TAG aGVHD4* (P = .0071, OR = 3.71,* CI = 1.56-8.86) NS 
FAS rs1800682 CC relapse (P = .017, OR = 1.68, CI = 1.03-2.74) NS 
  CT relapse* (P = .0025, OR = 0.50,* CI = 0.33-0.78) NS 
  CT aGVHD (P = .009, OR = 1.79, CI = 1.15-2.77) NS 
  TT cGVHD (P = .024, OR = 1.75, CI = 1.03-2.82) NS 
  TT ext cGVHD (P = .014. OR = 1.74, CI = 1.03-2.94) NS 
HLA-E rs1264457 Mismatch survival (P = .023) risk NT 
IL1A rs1800578 Mismatch aGVHD2-4 (P = .026, OR = 1.69, CI = 1.11-2.56) NT 
IL1B rs16944 AA aGVHD (P = .048, OR = 0.63, CI = 0.39-0.99) NT 
  GG aGVHD (P = .032, OR = 1.75, CI = 1.08-2.82) NT 
IL15RA rs2228059 AC survival (P = .024) risk NT 
IL2 rs2069762 GG aGVHD4* (P = .0014,* OR = 4.51,* CI = 1.91-10.6) NS 
  GT survival (P = .0021) protective NS 
  TT survival (P = .0061) risk NS 
NOD2 rs17313265 CC aGVHD2-4 (P = .036, OR = 2.15, CI = 1.06-4.37) NS 
TGFB1 rs1800469 Mismatch aGVHD2-4 (P = .02, OR = 1.63, CI = 1.1-6.4) NT 
TGFB1 rs2241715 Mismatch aGVHD2-4 (P = .015, OR = 1.61, CI = 1.09-2.39) NT 
  Mismatch cGVHD (P = .035, OR = 1.58, CI = 1.04-2.41) NT 
TGFB1 rs2241716 AA ext cGVHD* (P = .0041, OR = 2.58,* CI = 1.36-4.87) NS 
TNF rs1799964 Mismatch aGVHD4*† (P = .022, OR = 2.53,*† CI = 1.16-5.53) Mismatch aGVHD4*† (P = .0053, OR = 3.40,*† CI = 1.48-7.81) 
  CC aGVHD4* (P = .041, OR = 4.92,* CI = 1.27-19.02) CC aGVHD4 trend (P = .06) 
TNF rs1799724 CC survival (P = .02) protective, NT 
  CT survival (P = .02) risk NT 
TNFRSF1B rs1061622 TT aGVHD4* (P = .023, OR = 4.69,* CI = 1.1-20.11) NS 

The marker rs3087243 was not associated individually with chronic GVHD (cGVHD) or acute GVHD (aGVHD) and is not listed here, but it was included in the confirmatory cohort forming part of the CTLA4 haplotype.

NS indicates not significant; and NT, not tested. For other abbreviations please see Table 2.

*

Withstanding Bonferroni multiple testing corrections or have OR ≤ 0.5 or ≥ 2.

Consistent associations.

HLA-matched subgroup (n = 160 pairs).

When analyzing the HLA-matched subgroups of these cohorts, 7 markers and the CTLA4 and IL10 haplotypes in the donor cohort (Table 4) showed outcome associations, of which 5 markers and the CTLA4 haplotype were included for confirmatory typing. Only the CTLA4 haplotype had a P value significant when multiple testing correction was applied. In the HLA matched recipient subgroup, 3 markers showed an association with HSCT outcome, of which one was selected for the confirmation cohort by strength of OR (Table 5).

Table 4

Results of SNP genotyping on HLA-matched donor samples

Gene Marker Discovery cohort (genotype and association) Confirmatory cohort (genotype and association) 
CTLA4 rs231775 GG aGVHD* (P = .026, OR = 2.02,* CI = 1.09-3.75) NS 
CTLA4 rs3087243 GG aGVHD (P = .021, OR = 1.97, CI = 1.11-3.50) NS 
CTLA4 Haplotype CAA aGVHD (P = .012, OR = 0.55, CI = 0.35-0.87) NS 
  CGG aGVHD* (P = .00097,* OR = 2.06,* CI = 1.22-5.94) NS 
IFNg rs2069705 CC ext cGVHD* (P = .036, OR = 0.42,* CI = 0.20-0.93) NS 
  CT ext cGVHD* (P = .017, OR = 2.69,* CI = 1.22-5.94) NS 
IL10 rs1800896 AA aGVHD* (P = .038, OR = 0.21,* CI = 0.04-0.96) NS 
IL10 Haplotype CCG aGVHD* (P = .027, OR = 4.70, CI = 1.08-20.54) NS 
MTHFR rs1801133 TT aGVHD (P = .0016, OR = 12.13,* CI = 2.73-53.90) NT 
NOD2 rs17313265 CT relapse* (P = .013, OR = 2.68,* CI = 1.02-7.09) NS 
TNF rs1799724 CC survival (P = .006) protective NT 
Gene Marker Discovery cohort (genotype and association) Confirmatory cohort (genotype and association) 
CTLA4 rs231775 GG aGVHD* (P = .026, OR = 2.02,* CI = 1.09-3.75) NS 
CTLA4 rs3087243 GG aGVHD (P = .021, OR = 1.97, CI = 1.11-3.50) NS 
CTLA4 Haplotype CAA aGVHD (P = .012, OR = 0.55, CI = 0.35-0.87) NS 
  CGG aGVHD* (P = .00097,* OR = 2.06,* CI = 1.22-5.94) NS 
IFNg rs2069705 CC ext cGVHD* (P = .036, OR = 0.42,* CI = 0.20-0.93) NS 
  CT ext cGVHD* (P = .017, OR = 2.69,* CI = 1.22-5.94) NS 
IL10 rs1800896 AA aGVHD* (P = .038, OR = 0.21,* CI = 0.04-0.96) NS 
IL10 Haplotype CCG aGVHD* (P = .027, OR = 4.70, CI = 1.08-20.54) NS 
MTHFR rs1801133 TT aGVHD (P = .0016, OR = 12.13,* CI = 2.73-53.90) NT 
NOD2 rs17313265 CT relapse* (P = .013, OR = 2.68,* CI = 1.02-7.09) NS 
TNF rs1799724 CC survival (P = .006) protective NT 

NS indicates not significant; and NT, not tested. Explanation of other abbreviations found in Table 2.

*

Withstanding Bonferroni multiple testing corrections or have OR ≤ 0.5 or ≥ 2.

Table 5

Results of SNP genotyping on HLA-matched recipient samples

Gene Marker Discovery cohort (genotype and association) Confirmatory cohort (genotype and association) 
FAS rs1800682 CT aGVHD* (P = .0024, OR = 0.39,* CI = 0.22-0.71) NS 
IL1B rs16944 AA aGVHD (P = .043, OR = 0.51, CI = 0.27-0.97) NT 
IL2 rs2069762 GT survival (P = .037) protective NS 
  GT cGVHD (P = .039, OR = 1.97, CI = 1.05-3.71) GT cGVHD*† (P = .00041,*† OR = 3.24,*† CI = 1.69-6.20) 
  TT survival (P = .039) risk NS 
Gene Marker Discovery cohort (genotype and association) Confirmatory cohort (genotype and association) 
FAS rs1800682 CT aGVHD* (P = .0024, OR = 0.39,* CI = 0.22-0.71) NS 
IL1B rs16944 AA aGVHD (P = .043, OR = 0.51, CI = 0.27-0.97) NT 
IL2 rs2069762 GT survival (P = .037) protective NS 
  GT cGVHD (P = .039, OR = 1.97, CI = 1.05-3.71) GT cGVHD*† (P = .00041,*† OR = 3.24,*† CI = 1.69-6.20) 
  TT survival (P = .039) risk NS 

NS indicates not significant; and NT, not tested.

*

Withstanding Bonferroni multiple testing corrections or have OR ≤ 0.5 or ≥ 2.

Consistent associations.

Confirmatory cohort

All transplants (n = 462 pairs).

Seven markers for the donor cohort (CTLA4: rs231775, rs231777, rs3087243 [included for forming the CTLA4 haplotype, only rs231775 and rs3087243 showed an association in the screening cohort]; FAS: rs1800682; IL10: rs1800896; NOD2: rs2111235, rs6500328) and 10 markers for the recipient cohort (CTLA4: rs231775, rs231777, rs3087243 [part of CTLA4 haplotype, only rs231775 and rs231777 were associated in the screening cohort]; FAS: rs1800682; IL2: rs2069762; NOD2: 17313265; TGFB1: rs2241716; TNF: rs1799964; TNFRSF1B: rs1061622) were selected for typing in the confirmatory cohort. First, we were seeking to confirm associations from the screening cohorts that had significant P values after multiple testing correction (high significance); then, associations that had ORs ≤ 0.5 or ≥ 2.0 (large effect size); and third, associations within these selected markers that were consistent in both screening and confirmatory cohort (independent cohort confirmation), regardless of multiple testing correction or effect size.

There were no consistent findings in the overall donor confirmatory cohort (Table 2). In the overall recipient confirmatory cohort (Table 3), the donor-recipient genotype mismatch of the TNF-1031 SNP (rs1799964) was consistently associated in both screening and confirmatory cohorts with a higher risk of severe acute GVHD (grade 4). The CC genotype of the same marker was associated with acute GVHD grade 4 in the screening cohort and just escaped significance level in the confirmatory cohort (P = .06).

HLA-matched subgroups (166 pairs).

In the donor HLA-matched subgroup (Table 4), none of the markers typed in the confirmatory cohort showed any association. The HLA-matched recipient cohort (Table 5) revealed a consistent association between risk of chronic GVHD and the GT genotype of rs2069762 (IL2-330).

Table 6 summarizes the consistent associations of this study, composed of the IL2-330 and TNF-1031 SNP.

Table 6

SNP markers showing significant association in recipient screening and cohorts

Marker Genotype Cohort Outcome P Total Cases, all Controls, all Cases positive Cases negative Controls positive Controls negative OR OR (95% CI) 
TNF-1031 Mismatch Screening aGVHD4 .022 448 28 420 12 16 96 324 2.53 1.16-5.53 
rs1799964, recipients (all) Mismatch Confirmation aGVHD4 .0053 460 24 436 12 12 99 337 3.40 1.48-7.81 
IL2-330 GT Screening cGVHD .039 160 72 88 39 33 33 55 1.97 1.05-3.71 
rs2069762, recipients (HLA matched) GT Confirmation cGVHD .00041 166 75 92 40 35 23 68 3.24 1.70-6.20 
CTLA4-CT60 GG Random 1 aGVHD .022 159 58 101 20 38 54 47 0.46 0.27-0.78 
rs3087243, donors (HLA matched) GG Random 2 aGVHD .045 166 53 11 22 31 67 46 0.49 0.29-0.83 
Marker Genotype Cohort Outcome P Total Cases, all Controls, all Cases positive Cases negative Controls positive Controls negative OR OR (95% CI) 
TNF-1031 Mismatch Screening aGVHD4 .022 448 28 420 12 16 96 324 2.53 1.16-5.53 
rs1799964, recipients (all) Mismatch Confirmation aGVHD4 .0053 460 24 436 12 12 99 337 3.40 1.48-7.81 
IL2-330 GT Screening cGVHD .039 160 72 88 39 33 33 55 1.97 1.05-3.71 
rs2069762, recipients (HLA matched) GT Confirmation cGVHD .00041 166 75 92 40 35 23 68 3.24 1.70-6.20 
CTLA4-CT60 GG Random 1 aGVHD .022 159 58 101 20 38 54 47 0.46 0.27-0.78 
rs3087243, donors (HLA matched) GG Random 2 aGVHD .045 166 53 11 22 31 67 46 0.49 0.29-0.83 

Further analyses

To understand the mechanism of the associated genotype, we extended the analysis to all IL2-330 genotypes and chronic GVHD outcomes in the confirmatory cohort and found that GT also associated with extensive chronic GVHD (P = .00022, OR = 5.18, 95% CI, 2.37-11.39). The TT genotype exerts a protective effect against extensive chronic GVHD (P = .0029, OR = 0.3, 95% CI, 0.13-0.67). This finding is replicated when combining screening and confirmatory cohorts (GT and extensive chronic GVHD: P = .00055, OR = 2.90, 95% CI, 1.74-5.08; TT and extensive chronic GVHD: P = .001, OR = 0.40, 95% CI, 0.23-0.71), suggesting that the GG genotype is probably the higher risk genotype. We did not find a significant association with the GG genotype, which is probably because of limited statistical power of this low frequency genotype. Mirroring the analysis by MacMillan et al32  in our combined cohorts, the G allele showed a trend with risk of extensive chronic GVHD (P = .07), but not with acute GVHD.

The extended analysis of the TNF-1031 CC genotype in the confirmatory cohort showed that it was also associated with acute GVHD grade 2 to 4 (P = .029, OR = 3.41, 95% CI, 1.99-5.82). The TNF-1031 donor-recipient genotype mismatch was found to be a risk factor for acute GVHD grade 2 to 4 (P = .003, OR = 1.93, 95% CI, 1.13-3.30) and grade 3 or 4 (P = .002, OR = 2.21, 95% CI, 1.13-3.80) in the confirmatory cohort.

The stratification we applied in “matching” the degree of HLA mismatch of the confirmatory cohort to that of the screening cohort may have introduced bias (significantly different distribution of acute GVHD grades; supplemental Table 1). To address this, we randomly assigned samples to 2 cohorts, resolving any significant difference between time frames, and acute GVHD as an outcome measure. Reanalysis of the data for acute GVHD outcomes showed that the genotype mismatch of the TNF-1031 SNP as a risk factor for acute GVHD grade 4 would still hold up as significant (P = .005, OR = 3.26, 95% CI, 1.91-5.58; P = .021, OR = 2.60, 95% CI, 1.52-4.45). The CTLA4-CT60 (rs3087243) SNP showed a consistent association of the GG genotype as protective against acute GVHD (P = .022, OR = 0.46, 95% CI, 0.27-0.78; P = .045, OR = 0.49, 95% CI, 0.29-0.83) in the random cohort analysis of the HLA-matched subgroup.

Multivariate analyses

Multivariate analyses (Tables 7,Table 89) were performed on the combined (screening and confirmatory) cohorts and showed that the TNF-1031 donor-recipient genotype mismatch (acute GVHD grade 4), the CC genotype (acute GVHD grade 4), and the IL2-330 GT genotype (chronic GVHD) are independent risk factors, whereas the CTLA4-CT60 GG genotype is independently protective against acute GVHD.

Table 7

Multivariate analysis of the IL2–330 GT genotype as risk factor for chronic GVHD in the HLA-matched subgroup

Variable Univariate
 
Multivariate
 
OR (95% CI) P OR (95% CI) P 
Recipient age 1.008 (0.99-1.03) .481 1.008 (0.98-1.03) .528 
Donor age 1.024 (0.99-1.05) .106 1.020 (0.99-1.05) .195 
Female to male transplant 0.900 (0.52-1.57) .71 0.876 (0.48-1.60) .664 
Diagnosis ANLL vs ALL 1.087 (0.70-1.69) .711 1.022 (0.63-1.67) .929 
Total body irradiation 1.419 (0.72-2.80) .313 1.284 (0.62-2.67) .502 
Cyclosporine vs tacrolimus 1.024 (0.66-1.59) .916 0.996 (0.61-1.62) .987 
Relapse 0.526 (0.32-0.86) .011 0.573 (0.34-0.96) .033 
Genotype GT 2.507 (1.60-3.93) .000066 2.273 (1.42-3.63) .0006 
Variable Univariate
 
Multivariate
 
OR (95% CI) P OR (95% CI) P 
Recipient age 1.008 (0.99-1.03) .481 1.008 (0.98-1.03) .528 
Donor age 1.024 (0.99-1.05) .106 1.020 (0.99-1.05) .195 
Female to male transplant 0.900 (0.52-1.57) .71 0.876 (0.48-1.60) .664 
Diagnosis ANLL vs ALL 1.087 (0.70-1.69) .711 1.022 (0.63-1.67) .929 
Total body irradiation 1.419 (0.72-2.80) .313 1.284 (0.62-2.67) .502 
Cyclosporine vs tacrolimus 1.024 (0.66-1.59) .916 0.996 (0.61-1.62) .987 
Relapse 0.526 (0.32-0.86) .011 0.573 (0.34-0.96) .033 
Genotype GT 2.507 (1.60-3.93) .000066 2.273 (1.42-3.63) .0006 

The genotype is an independent risk factor.

Table 8

Multivariate analysis of the CTLA4-CT60 GG genotype for acute GVHD (grade 1-4 vs no GVHD) in the HLA-matched subgroup, confirming this genotype as an independent risk factor

Variable Univariate
 
Multivariate
 
OR (95% CI) P OR (95% CI) P 
Recipient age 1.017 (0.99-1.04) .146 1.020 (0.99-1.05) .121 
Donor age 0.995 (0.97-1.03) .763 0.997 (0.97-1.03) .854 
Female to male transplant 1.644 (0.93-2.89) .085 1.630 (0.89-2.97) .111 
Diagnosis ANLL vs ALL 1.280 (0.81-2.03) .296 1.129 (0.69-1.85) .631 
Total body irradiation 0.847 (0.43-1.68) .634 0.916 (0.45-1.86) .809 
Relapse 1.255 (0.77-2.06) .369 1.330 (0.80-2.24) .273 
Genotype GG 0.468 (0.29-0.75) .002 0.497 (0.31-0.80) .004 
Variable Univariate
 
Multivariate
 
OR (95% CI) P OR (95% CI) P 
Recipient age 1.017 (0.99-1.04) .146 1.020 (0.99-1.05) .121 
Donor age 0.995 (0.97-1.03) .763 0.997 (0.97-1.03) .854 
Female to male transplant 1.644 (0.93-2.89) .085 1.630 (0.89-2.97) .111 
Diagnosis ANLL vs ALL 1.280 (0.81-2.03) .296 1.129 (0.69-1.85) .631 
Total body irradiation 0.847 (0.43-1.68) .634 0.916 (0.45-1.86) .809 
Relapse 1.255 (0.77-2.06) .369 1.330 (0.80-2.24) .273 
Genotype GG 0.468 (0.29-0.75) .002 0.497 (0.31-0.80) .004 
Table 9

Multivariate analysis of TNF-1031 genotype mismatch and CC genotype as a risk factors* for acute GVHD grade 4 in the overall (HLA matched and mismatched) cohort

Variable Univariate
 
Multivariate
 
OR (95% CI) P OR (95% CI) P 
Recipient age 0.978 (0.95-1.01) .109 0.975 (0.94-1.01) .112 
Donor age 1.038 (1.00-1.08) .044 1.033 (0.99-1.07) .105 
Female to male transplant 0.610 (0.27-1.38) .235 0.582 (0.24-1.42) .236 
Diagnosis ANLL vs ALL 1.001 (0.57-1.76) .996 1.148 (0.60-2.18) .673 
Total body irradiation 0.909 (0.40-2.07) .819 0.992 (0.39-2.51) .987 
Antithymoglobulin 3.562 (0.99-12.73) .051 2.246 (0.45-11.15) .322 
Cyclosporine vs tacrolimus 1.336 (0.75-2.37) .321 1.516 (0.80-2.86) .198 
Relapse 0.115 (0.03-0.48) .003 0.154 (0.04-0.65) .011 
HLA match 0.465 (0.24-0.92) .027 0.765 (0.35-1.67) .502 
Genotype CC 4.336 (1.7-11.1) .002 3.888 (1.39-10.90) .010 
Genotype mismatch 2.905 (1.65-5.1) .00023 2.307 (1.18-4.52) .015 
Variable Univariate
 
Multivariate
 
OR (95% CI) P OR (95% CI) P 
Recipient age 0.978 (0.95-1.01) .109 0.975 (0.94-1.01) .112 
Donor age 1.038 (1.00-1.08) .044 1.033 (0.99-1.07) .105 
Female to male transplant 0.610 (0.27-1.38) .235 0.582 (0.24-1.42) .236 
Diagnosis ANLL vs ALL 1.001 (0.57-1.76) .996 1.148 (0.60-2.18) .673 
Total body irradiation 0.909 (0.40-2.07) .819 0.992 (0.39-2.51) .987 
Antithymoglobulin 3.562 (0.99-12.73) .051 2.246 (0.45-11.15) .322 
Cyclosporine vs tacrolimus 1.336 (0.75-2.37) .321 1.516 (0.80-2.86) .198 
Relapse 0.115 (0.03-0.48) .003 0.154 (0.04-0.65) .011 
HLA match 0.465 (0.24-0.92) .027 0.765 (0.35-1.67) .502 
Genotype CC 4.336 (1.7-11.1) .002 3.888 (1.39-10.90) .010 
Genotype mismatch 2.905 (1.65-5.1) .00023 2.307 (1.18-4.52) .015 
*

Both are independent risk factors, with competing effects from HLA matching and relapse.

Discussion

This study has identified 3 consistent non-HLA SNP associations with HSCT outcome: the TNF-1031 donor-recipient genotype mismatch with severe GVHD (grade 4, in the overall cohort), the recipient IL2-330 GT genotype with risk of chronic GVHD, and the CTLA4-CT60 GG genotype protective against acute GVHD (grade 1-4; the latter 2 associations were found in the HLA-matched subgroup only).

TNF-α is a cytokine that has been associated with severity of acute GVHD in several previous genetic, gene expression, and animal model studies. Teshima et al have demonstrated in an animal model that TNF is essential in the development of acute GVHD.13  Previous data from a Japanese population have shown that the TNF haplotype, including TNF-1031, was associated with severe GVHD,33  and the TNF-1031C allele was associated with higher TNF expression.34  A more recent study35  describes the C allele as a risk factor for grade 3 or 4 acute GVHD. Therefore, an association of the TNF-1031 CC genotype with severe acute GVHD, as seen in this study, albeit showing only a trend in the confirmation cohort, would be biologically meaningful and replicate previous findings. However, the TNF-1031 CC genotype displays strong linkage disequilibrium with HLA, in particular with HLA-B61.34  This may explain our finding of the strong association between donor-recipient genotype mismatch and acute GVHD grade 4 in the overall cohort only, but not in the HLA matched subgroup. Our study did not have the power to elucidate whether any particular TNF-1031 genotype mismatch combinations carry a higher risk. As the group affected with acute GVHD grade 4 is small (just > 5%), further studies should confirm this result independently. The finding that genotype mismatch was also associated with grade 2 to 4 as well as grade 3 or 4 acute GVHD (which are larger groups) in the confirmatory cohort gives further indication that the genotype mismatch is probably a risk factor for acute GVHD. Nevertheless, the strength and consistency of this association mean that it is potentially a strong discriminator for prediction of the most severe form of acute GVHD (grade 4), which could be exploited in clinical practice.

The IL2-330 (rs2069762) SNP has an almost identical genotype distribution between white and Japanese populations (white: TT, 0.536; GT, 0.464; GG, 0; Japanese [this study]: TT, 0.450; GT, 0.440; GG, 0.110). The G allele is the known high-expressing allele, and high levels of IL2 have been described to correlate with severity of acute GVHD.32,36  A previous study from North America on a cohort of similar time frame to our screening cohort32  reported an association between the recipient IL2-330 G allele and acute GVHD as well as a trend toward risk of chronic GVHD. In our study, we found an association of the GT genotype with risk of chronic GVHD. More detailed analysis showed that the low-frequency GG genotype is probably the highest risk genotype for chronic GVHD, whereas GT associated with risk, and TT with protection. Our findings therefore confirm those of the previous study, even across different ethnic populations, qualifying this marker as a predictor of chronic GVHD risk.

The effect of the CTLA4-CT60 polymorphism on HSCT outcomes was studied previously, in settings of HLA matched sibling donors37,38  and matched unrelated donors39  in white populations. In HLA-matched sibling transplants, the donor G allele was associated with increase of relapse and worse survival, whereas the AA genotype was linked to risk of acute GVHD. The findings in matched unrelated donor HSCT were similar, with the donor AA genotype associating with severe acute GVHD (grade 3 or 4), but risk of G allele or GG genotype with relapse or survival was not observed. Our findings are in accordance with these results, identifying the GG genotype as protective against acute GVHD (remarkably, the screening cohort result indicated a risk of the GG genotype with acute GVHD [Table 4], a finding completely reversed by the randomization). We could not establish any risk of the GG genotype with relapse or survival, or the AA genotype with acute GVHD. This may be explained by the fact that, in the Japanese population, the GG genotype is more prominent than in whites, whereas the AA genotype is more rare (HapMap data of genotypes: whites: AA, 0.208; AG, 0.513; GG, 0.283; Japanese: AA, 0.047; AG, 0.389; GG, 0.542). The risk of acute GVHD, relapse, or survival associated with this marker may therefore be lower in the Japanese population, compared with whites.

The results raise also some methodologic questions which are beyond the scope of this study: (1) By incorporating a measure of effect size into the statistical analysis, this study extends beyond previous approaches focusing on significance and correction for multiple testing. Our results suggest that this approach may be more sensitive; but because of limited power and small number of identified associations, no conclusions could be made about the impact on sensitivity and specificity, and statistical multiple testing burden. (2) Despite the effort to control variability of study population characteristics, reproducibility of associations remains low and appeared to be dependent on distribution of these characteristics among the cohorts. This may be the result of the overall small effect size of the associations, confounders in the study cohort, or both. A more comprehensive typing (full typing of all markers on both screening and confirmation cohort) and analysis would be required.

Clinical and population characteristics of study cohorts may explain some of the contradictory results observed in previous studies; therefore, careful design of study cohorts and control of confounders should receive more attention. The growing number of HSCTs may facilitate in the future the availability of larger, genetically and clinically more homogeneous study cohorts; however, the changing and expanding indications of HSCT are likely to prove a challenge.

In conclusion, this study demonstrates that non-HLA genetic association with HSCT outcomes does exist and can be detected, even in the HLA-mismatched setting. Such associations could be useful for application in future clinical practice in this clinically highly relevant population. These findings should be verified by larger studies also on populations of different ethnicities.

The online version of this article contains a data supplement.

The publication costs of this article were defrayed in part by page charge payment. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.

Acknowledgments

The authors thank the staff members of the transplantation centers, donor centers, and the JMDP Office for their generous cooperation; the Great Britain Sasakawa Foundation, which contributed to the laboratory costs of this project with a Butterfield Award; and the laboratory staff at the Division of Molecular Life Sciences at Tokai University for their kind support, including Mr Hayashi for technical advice and Ms Yamaguchi, Ms Matsushita, and Ms Higuchi for supporting the genotyping work.

This work was supported by the Research on Allergic Disease and Immunology (Health and Labor Science Research grants H20-014 and H23-010) and the Ministry of Health, Labor, and Welfare of Japan. C.H. was supported by a fellowship from the Kay Kendall Leukaemia Fund United Kingdom (grant 291,297).

Authorship

Contribution: C.H. designed and coordinated the project, carried out the experiments and univariate data analyses, and wrote the manuscript; A.O. designed the study and the experiment and provided technical advice; M.O., H.I., A.R.G., and K.A. designed the study; P.G.M. designed the study and experiment and inferred the CTLA4 haplotypes; K.K., K.H., and T.Y. performed the IL-10 SNP genotyping and haplotype inference; H.N. gave statistical advice and performed multivariate analyses; and Y.M. designed the study and acted as liaison to JMDP, providing clinical datasets and DNA samples.

Conflict-of-interest disclosure: The authors declare no competing financial interests.

Correspondence: Christian Harkensee, Institute of Cellular Medicine, University of Newcastle, Medical School, Framlington Place, Newcastle upon Tyne, NE2 4HH, United Kingdom; e-mail: christian.harkensee@ncl.ac.uk.

References

References
1
Hansen
JA
Petersdorf
EW
Lin
MT
et al. 
Genetics of allogeneic hematopoietic cell transplantation: role of HLA matching, functional variation in immune response genes.
Immunol Res
2008
41
1
56
78
2
Hsu
KC
Chida
S
Geraghty
DE
Dupont
B
The killer cell immunoglobulin-like receptor (KIR) genomic region: gene-order, haplotypes and allelic polymorphism.
Immunol Rev
2002
190
40
52
3
Yabe
T
Matsuo
K
Hirayasu
K
et al. 
Donor killer immunoglobulin-like receptor (KIR) genotype-patient cognate KIR ligand combination and antithymocyte globulin preadministration are critical factors in outcome of HLA-C-KIR ligand-mismatched T cell-replete unrelated bone marrow transplantation.
Biol Blood Marrow Transplant
2008
14
1
75
87
4
Kawase
T
Nanya
Y
Torikai
H
et al. 
Identification of human minor histocompatibility antigens based on genetic association with highly parallel genotyping of pooled DNA.
Blood
2008
110
6
3286
3294
5
Ogawa
S
Matsubara
A
Onizuka
M
et al. 
Exploration of the genetic basis of GVHD by genetic association studies.
Biol Blood Marrow Transplant
2008
15
1 Suppl
39
41
6
Hansen
JA
Chien
JW
Warren
EH
Zhao
LP
Martin
PJ
Defining genetic risk for graft-versus-host disease and mortality following allogeneic hematopoietic stem cell transplantation.
Curr Opin Hematol
2010
17
6
483
492
7
Choi
SW
Levine
JE
Ferrara
JL
Pathogenesis and management of graft-versus-host disease.
Immunol Allergy Clin North Am
2010
30
1
75
101
8
Billingham
RE
The biology of graft-versus-host reactions.
Harvey Lect
1966
62
21
78
9
Martín-Antonio
B
Granell
M
Urbano-Ispizua
Á
Genomic polymorphisms of the innate immune system and allogeneic stem cell transplantation.
Expert Rev Hematol
2010
3
4
411
427
10
Weissinger
EM
Dickinson
AM
Immunogenomics and proteomics in hematopoietic stem cell transplantation: predicting post-hematopoietic stem cell transplant complications.
Cancer Treat Res
2009
144
95
129
11
Ferrara
JL
Krenger
W
Graft-versus-host disease: the influence of type 1 and type 2 T cell cytokines.
Transfus Med Rev
1998
12
1
1
17
12
Socié
G
Graft-versus-host disease: proteomics comes of age.
Blood
2009
113
2
271
272
13
Teshima
T
Ordemann
R
Reddy
P
et al. 
Acute graft-versus-host disease does not require alloantigen expression on host epithelium.
Nat Med
2002
8
6
575
581
14
Buzzeo
MP
Yang
J
Casella
G
Reddy
V
A preliminary gene expression profile of acute graft-versus-host disease.
Cell Transplant
2008
17
5
489
494
15
Paczesny
S
Krijanovski
OI
Braun
TM
et al. 
A biomarker panel for acute graft-versus-host disease.
Blood
2009
113
2
273
278
16
Kollman
C
Howe
CW
Anasetti
C
et al. 
Donor characteristics as risk factors in recipients after transplantation of bone marrow from unrelated donors: the effect of donor age.
Blood
2001
98
7
2043
2051
17
Loren
AW
Bunin
GR
Boudreau
C
et al. 
Impact of donor and recipient sex and parity on outcomes of HLA-identical sibling allogeneic hematopoietic stem cell transplantation.
Biol Blood Marrow Transplant
2006
12
7
758
769
18
Randolph
SS
Gooley
TA
Warren
EH
Appelbaum
FR
Riddell
SR
Female donors contribute to a selective graft-versus-leukemia effect in male recipients of HLA-matched, related hematopoietic stem cell transplants.
Blood
2004
103
1
347
352
19
Pérez-Simón
JA
Diez-Campelo
M
Martino
R
et al. 
Influence of the intensity of the conditioning regimen on the characteristics of acute and chronic graft-versus-host disease after allogeneic transplantation.
Br J Haematol
2005
130
3
394
403
20
Colhoun
HM
McKeigue
PM
Davey Smith
G
Problems of reporting genetic associations with complex outcomes.
Lancet
2003
361
9360
865
872
21
Gambaro
G
Anglani
F
D'Angelo
A
Association studies of genetic polymorphisms and complex disease.
Lancet
2000
355
9200
308
311
22
Hirschhorn
JN
Lohmueller
K
Byrne
E
Hirschhorn
K
A comprehensive review of genetic association studies.
Genet Med
2002
4
2
45
61
23
Lander
ES
Schork
NJ
Genetic dissection of complex traits.
Science
1994
265
5181
2037
2048
24
Schork
NJ
Genetics of complex disease: approaches, problems, and solutions.
Am J Respir Crit Care Med
1997
156
4
S103
S109
25
Sasazuki
T
Juji
T
Morishima
Y
et al. 
Effect of matching of class I HLA alleles on clinical outcome after transplantation of hematopoietic stem cells from an unrelated donor: Japan Marrow Donor Program.
N Engl J Med
1998
339
17
1177
1185
26
Morishima
Y
Sasazuki
T
Inoko
H
et al. 
The clinical significance of human leukocyte antigen (HLA) allele compatibility in patients receiving a marrow transplant from serologically HLA-A, HLA-B, and HLA-DR matched unrelated donors.
Blood
2002
99
11
4200
4206
27
Weisdorf
D
Spellman
S
Haagenson
M
et al. 
Classification of HLA-matching for retrospective analysis of unrelated donor transplantation: revised definitions to predict survival.
Biol Blood Marrow Transplant
2008
14
7
748
758
28
Morishima
Y
Yabe
T
Matsuo
K
et al. 
Effects of HLA allele and killer immunoglobulin-like receptor ligand matching on clinical outcome in leukemia patients undergoing transplantation with T-cell-replete marrow from an unrelated donor.
Biol Blood Marrow Transplant
2007
13
3
315
328
29
Kawase
T
Morishima
Y
Matsuo
K
et al. 
High-risk HLA allele mismatch combinations responsible for severe acute graft versus host disease and implication for its molecular mechanism.
Blood
2007
110
7
2235
2241
30
Kawase
T
Matsuo
K
Kashiwase
K
et al. 
HLA mismatch combinations associated with decreased risk of relapse: implications for the molecular mechanism.
Blood
2009
113
12
2851
2858
31
Morishima
S
Ogawa
S
Matsubara
A
et al. 
Impact of highly conserved HLA haplotype on acute graft-versus-host disease.
Blood
2010
115
23
4664
4670
32
MacMillan
ML
Radloff
GA
Kiffmeyer
WR
DeFor
TE
Weisdorf
DJ
Davies
SM
High-producer interleukin-2 genotype increases risk for acute graft-versus-host disease after unrelated donor bone marrow transplantation.
Transplantation
2003
76
12
1758
1762
33
Ishikawa
Y
Kashiwase
K
Akaza
T
et al. 
Polymorphisms in TNFA and TNFR2 affect outcome of unrelated bone marrow transplantation.
Bone Marrow Transplant
2002
29
7
569
575
34
Higuchi
T
Seki
N
Kamizono
S
et al. 
Polymorphism of the 5′-flanking region of the human tumor necrosis factor (TNF)-alpha gene in Japanese.
Tissue Antigens
1998
51
6
605
612
35
Goyal
RK
Lin
Y
Schultz
KR
et al. 
Tumor necrosis factor-alpha gene polymorphisms are associated with severity of acute graft-versus-host disease following matched unrelated donor bone marrow transplantation in children: a Pediatric Blood and Marrow Transplant Consortium study.
Biol Blood Marrow Transplant
2010
16
7
927
936
36
Das
H
Imoto
S
Murayama
T
et al. 
Kinetic analysis of cytokine gene expression in patients with GVHD after donor lymphocyte infusion.
Bone Marrow Transplant
2001
27
4
373
380
37
Pérez-Garcia
A
De la Camara
R
Roman-Gomez
J
et al. 
CTLA-4 polymorphisms and clinical outcome after allogeneic stem cell transplantation from HLA-identical sibling donors.
Blood
2007
110
1
461
467
38
Murase
M
Nishida
T
Onizuka
M
et al. 
Cytotoxic T-lymphocyte antigen 4 haplotype correlates with relapse and survival after allogeneic hematopoietic SCT.
Bone Marrow Transplant
2011
46
11
1444
1449
39
Vannucchi
AM
Guidi
S
Guglielmelli
P
et al. 
Significance of CTLA-4 and CD14 genetic polymorphisms in clinical outcome after allogeneic stem cell transplantation.
Bone Marrow Transplant
2007
40
10
1001
1002