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. Author manuscript; available in PMC: 2010 Oct 18.
Published in final edited form as: Gastroenterology. 2008 Jun 3;135(3):830–84010. doi: 10.1053/j.gastro.2008.05.080

Genetic variants in Major Histocompatibility Complex-linked genes Associate with Pediatric Liver Transplant Rejection

Rakesh Sindhi 1, Brandon W Higgs 1, Daniel E Weeks 1, Chethan AshokKumar 1, Ronald Jaffe 1, Cecilia Kim 1, Patrick Wilson 1, Nydia Chien 1, Joseph Glessner 1, Anjan Talukdar 1, George Mazariegos 1, M Michael Barmada 1, Edward Frackleton 1, Nancy Petro 1, Andrew Eckert 1, Hakon Hakonarson 1, Robert Ferrell 1
PMCID: PMC2956436  NIHMSID: NIHMS69061  PMID: 18639552

Abstract

Background/Aims

Limited access to large samples and independent replication cohorts precludes genome-wide association (GWA) studies of rare but complex traits. To localize candidate genes with family-based GWA, a novel exploratory analysis was first tested on 1,774 major histocompatibility complex single nucleotide polymorphisms (SNPs) in 240 DNA samples from 80 children with primary liver transplantation (LTx), and their biological parents.

Methods/Results

Initially, 57 SNPs with large differences (p<0.05) in minor allele frequencies were selected, when parents of children with early rejection (Rejectors) were compared with parents of Non-Rejectors. In hypothesis-testing of selected SNPs, the gamete competition statistic identified the minor allele G (ancestral allele T) of the SNP rs9296068, near HLA-DOA, as being significantly different (p=0.018) in parent-to-child transmission between outcome groups. Subsequent simple association testing confirmed over- and under-transmission of rs9296068 based on 1) the most significant differences between outcome groups, of 1,774 SNPs tested (p=0.002), and 2) allele (G) frequencies that were greater among Rejectors (51.4 vs. 36.8%, p=0.015), and lower among Non-Rejectors (26.8 vs. 36.8%, p=0.074), compared with 400 normal control Caucasian children. In early functional validation, a) Rejectors demonstrated significant repression of the first HLA-DOA exon closest to rs9296068, and b) Rejectors with the risk allele showed 3-fold greater intragraft content of B-lymphocytes, whose antigen-presenting function is inhibited selectively by HLA-DOA, compared with Rejectors without the allele.

Conclusions

The minor allele of the SNP rs9296068 is significantly associated with LTx rejection, and with enhanced B-lymphocyte participation in rejection, likely due to a dysfunctional HLA-DOA gene product.

Introduction

In children, liver transplantation (LTx) is usually performed for multiple congenital liver diseases, and results in highly variable outcomes (1). Acute cellular rejection (ACR) occurs in 50% and post-LTx lymphoma-like malignancy affects 2-10% (2). Genetic variants, exemplified most commonly by single nucleotide polymorphisms (SNPs) are a significant basis for individual variation (3). However, the majority of the >10 million catalogued SNPs do not alter gene function (4). Also, promising associations involving discrete SNPs are rarely reproduced (5-7). Population stratification, or over-representation of one ethnicity within an outcome group may allow a SNP representing this ethnicity to be viewed as the outcome-specific SNP (8). Family-based association studies can minimize stratification (9). In this design, parental genotype serves as the control, and transmission frequency of a SNP from heterozygous parents to affected offspring is compared with the expected 50% transmission frequency. Significant deviations reflect transmission disequilibrium, and are more likely to represent disease-specific variation than variations due to ethnicity. The known location of such a SNP is then used to identify a potential candidate gene, and a causal variant in proximity. Increasingly, genome-wide association (GWA) studies are being conducted, recognizing that most disease traits are complex, and likely originate from an interaction between multiple causal variants within multiple genes, and the environment.

Several limitations preclude application of GWA in transplantation, especially among pediatric LTx recipients. First, simultaneous testing of large numbers of SNPs necessitates stringent multiple-testing correction. Under these conditions, statistical power requirements mandate a large subject sample, or a two-step study in which candidate SNPs identified in a screening sample are replicated in a second step. Accruing a homogeneous validation cohort can take several years, because approximately 550 pediatric LTx are performed annually in the United States, and are distributed among >50 transplant centers (10). Secondly, the numbers of candidate SNPs in an association study may not exceed false-discovery thresholds. From such a limited list of candidates, any true-positive association may at best account for large effects.

We report for the first time, a novel, multi-step approach to candidate gene localization, which incorporates preliminary functional validation in the same test cohort. First, a two-tier, family-based association method identifies the candidate gene or locus. Next, transmission distortion in that locus is confirmed by allele frequency comparisons with a large control group. Because SNPs within non-coding regions can influence gene expression and splicing at distances of up to 100 kb, differential regulation and alternative splice variants of candidate genes is evaluated with probes specific to exons of whole gene transcripts in the first of two preliminary functional validation tests (11, 12). In the second, the candidate is characterized in diseased tissue with immunohistochemistry. Because our sample size is small, and consists of 80 case-parent-parent trios, our association method is based on the following biologic assumptions: A) If a SNP is strongly associated with an inherited trait, it should demonstrate differences in parental allele frequencies (PAF) between the two groups, B) In family-based association testing, a genetic variant that is associated with rejection/non-rejection should show over-transmission in one outcome group and under-transmission in the other in the gamete competition test (GC). The GC statistic evaluates transmission disequilibrium using full pedigree data, similar to the well-known Transmission Disequilibrium Test (TDT) (8), but is based on a likelihood ratio test (13). The GC statistic also handles missing data and allows haplotype-based analysis. C) In a confirmatory step, potential candidates should also demonstrate i) significant differences in allele frequency when the two outcome groups are compared with each other, and ii) evidence of overtransmission in one group and undertransmission in the other when compared individually, with a large cohort of 400 normal Caucasian children.

We asked whether rejection/non-rejection outcomes are associated with genetic variants in the major histocompatibility complex (MHC) region. The 1,774 MHC-SNPs evaluated here are a subset of 550,000 genome-wide SNPs recently characterized in our test population. MHC-SNPs have been analyzed separately at first, to explore the utility of our statistical method, which is based in part on screening/testing approaches for quantitative traits proposed by others, by applying it to a candidate region with known impact in organ transplantation (14-17). The results show that the minor allele G at the SNP locus rs9296068, which is significantly associated with rejection outcomes, localizes to the 5′ UTR (untranslated) region of the HLA-DOA gene. Differential regulation of HLA-DOA, which is selectively expressed in B-lymphocytes, is suggested by associated repression of the first HLA-DOA exon, and significantly higher B-lymphocyte content in allograft biopsies from Rejectors (18, 19).

Methods

Patient Population

All studies were performed with approval from the University of Pittsburgh’s Institutional Review Board. DNA was extracted from 3 ml whole blood samples from 80 primary pediatric LTx recipients ages 0-22 years, and their biological parents (240 DNA samples). All children received previously described Tacrolimus monotherapy after steroid-free induction with rabbit, anti-human thymocyte globulin (rATG, Genzyme, Cambridge, MA) (20). Children who experienced biopsy-proven ACR within the first 60 days after LTx were termed Rejectors. Normal controls consisted of 400 disease-free Caucasian children with no prior or ongoing use of imunosuppressants, or transplantation. In addition, all 400 samples were selected for the absence of large copy number variants that could suggest a disease association. This normal control population was recruited at the Center for Applied Genomics at the Children’s Hospital of Philadelphia (CAG-CHOP).

Genotyping

was performed with 550,000 genome-wide SNP loci with the HumHap550k SNP bead array (Illumina, San Diego, CA.). Analysis from this experiment was restricted to 1,813 SNPs covering 168 MHC genes on chromosome 6p, of which 1,774 passed our quality control criteria.

DNA extracted by the Gentra Purigene system (Minneapolis, MN) was activated, and SNPs were characterized using manufacturer’s protocol. The Illumina Beadstation GX software was used to extract genotype calls (Illumina, San Diego, CA.) (21).

Statistical Methods

A total of 1,813 SNPs from the MHC region of the HumHap550k SNP array (Illumina, San Diego, CA.) were identified for analysis. Genotype data from the array were merged with pedigree and phenotype data and quality controlled for the following: Mendelian errors (recoded to missing), Hardy-Weinberg equilibrium (SNPs with deviations at p<.001 removed), missing rate across patients (>10% removed), minimal minor allele frequency (SNPs with MAF <1% removed), and low genotyping rate for an individual (<10% removed in the simple association test) using the PLINK v0.99r software package (22). This filtering reduced the number of SNPs to 1,774 total. A two-sample proportions statistic (two-sided) was used to determine PAF differences (p-value cutoff <0.05) between parents of Rejectors and Non-Rejectors. This screening step yielded a subset of MHC-SNPs for subsequent hypothesis testing using the Gamete Competition (GC) statistic, as implemented in the software package Mendel v7.0.0 (23). In this approach, a segregation parameter τ is estimated by maximum likelihood from the family data, and a likelihood ratio test is then applied. For a two-allele locus with alleles 1 and 2, the probability that a heterozygous parent with genotype 1/2 transmits allele 1 is defined as Pr (1/2 -> 1)= τ1/( τ1+ τ2); the null hypothesis of Mendelian transmission corresponds to τ1 = τ2 = 1 (14). The transmission parameter τk is set to 1 for the most frequent allele k, while the remaining τk values (for all k not equal to the most frequent allele) are estimated by maximum likelihood. In our application, we assumed symmetric transmission: that is, an allele that is over-transmitted to Rejectors is assumed to be similarly under-transmitted to Non-Rejectors. Results are summarized as the p-value and chi-squared statistic (with 95% confidence bounds) for the PAF comparison, and the estimated segregation parameter (τ), the allele frequency, and the p-value of the GC statistic (see Appendix 1). Note that this screening/testing approach markedly reduces multiple testing problems because the PAF test (which only uses parental genotypes) is independent of the gamete competition test (which depends on how often specific alleles are transmitted to the children). Thus, since the PAF test alone is used for SNP selection, we only have to adjust for the actual number of GC tests conducted on the much smaller number of selected SNPs.

Confirmatory association testing with 400 normal Caucasian controls

Comparisons of MAF for significant MHC-SNPs were conducted, between Rejectors and normal controls, and between Non-Rejectors and normal controls (chi-square test).

Validating candidacy of the HLA-DOA locus with differential gene splicing patterns

The Affymetrix Human Exon 1.0 ST array was used to measure differential splicing patterns in archived RNA isolated from 29 of 80 children. Probe summaries for both the genes and exons were computed using the Affymetrix Power Tools (APT) software and ‘rma-sketch’ normalization method. The gene-level normalized intensities (NI) were computed with the MiDAS algorithm and both the splicing index (SI) (24) and Student’s t-test p-values (two-sided) were computed on the NI values in R (25). Principal components analysis (PCA) was calculated separately on exon-level and gene-level intensities and was used to remove 3 outlier samples, for a remaining total of 26 samples-11 Rejectors and 15 Non-Rejectors. To remove low expressed gene-level probes, those with values less than 3.5 (log2 scale) in >50% of the samples in either group were filtered out leaving 17,242 of the original 22,011 probes. Those gene-level probes that were highly differentially expressed between groups were also removed using a fold change threshold of log2 (10). This step accounts for the tendency for the gene-level probe set intensities in each group to be “disproportionately affected by background noise or saturation” (Affymetrix Technical notes). Exon-level probes were filtered based on APT’s detection above background (DABG) p-value greater than 0.05 in n-1 samples leaving 218,402 of the original 287,329 exon-level probes.

After gene and exon probe filtering, 7 gene-level probes (and 67 corresponding exon-level probes for the genes) within a window size of 200 kb that included the HLA-DOA gene on chromosome 6 were extracted and examined for differential splicing (positions 33,000,000-33,200,000). This was conducted to restrict the analysis to only the immediate region surrounding the HLA-DOA gene.

Relating intragraft content of B-lymphocytes, to rs9296068

Because the HLA-DOA gene inhibits class II antigen presentation selectively in B-cells, we asked whether B-cells were present in rejecting allograft biopsies, and whether the B-cell content of allograft biopsies varied with the presence or absence of the risk allele of rs9296068. Slides were re-cut from stored tissue blocks for 36 of 80 children, with 4μm thick tissue sections, stained in batches on a Ventana immunostainer using mouse monoclonal anti CD79a (DAKO M7050 at 1:100, Ventana CCI mild, 32 minutes at 32C,iView DAB detection), as well as their positive and negative biological staining controls for each batch. Hematoxylin counterstain was applied after DAB detection. The surface marker CD79a identifies cells of B-cell/plamacytoid lineage.

Cell counting was done blinded to outcome, and prior to histologic re-review of the tissues. Duplicate counts were done on each 10th case to assess variance. Portal and lobular regions of allografts were optically scored separately, at a magnification of ×400 and ×200, respectively. B-cell counts were expressed as total number per portal area, and total number per lobule (Figure 3).

Figure 3.

Figure 3

a). Significant correlation exists between B-lymphocyte content in liver grafts with ACR, and numbers of risk allele G at rs9296068 (r2=0.194, p=0.021). Accompanying micrographs show ACR, with portal areas containing brown, horseradish-peroxidase-stained CD79a+ B-lymphocyte/plasmacytoid cells. B-lymphocyte content is lowest, when the risk allele is absent (panel b), higher in heterozygotes (panel c), and highest when the risk allele is homozygous (panel d).

Results

Demographics

Early ACR occurred at mean±SD 32.5±4.2 days after LTx in 37 children who were termed Rejectors. Rejectors and Non-Rejectors (n=43) were similar with respect to age (median±SEM 6±1.1 vs 4.6±0.9 years, p=NS), male: female gender distribution (16:21 vs 21:22, p=NS), and etiology of liver failure requiring LTx (Table 1). The racial distribution in the Rejector and Non-Rejector groups was (Caucasian: African-American: Other=31:2:4 vs 42:0:1, respectively). Also, there were no differences between Rejectors and Non-Rejectors, in donor-recipient matching at the HLA-A, HLA-B, and HLA-DR loci (1.4±1.2 vs 1.8±1.2 antigens, p=NS), or disease severity as reflected in the Pediatric End-Stage Liver Disease score (PELD, 25.5±13.2 vs 24±14.2, P=NS). The sample size was too small to evaluate the effect of disease, age at transplant, and immunosuppression on rejection outcomes, or whether the highly associated SNP(s) were independent predictors of rejection outcome.

Table 1.

Etiology of liver disease leading to LTx in 80 children.

Etilogy of liver disease Rejectors Non-
Rejectors
Allagilles 1 1
Autoimmune Hepatitis 3 0
Biliary Atresia 8 13
BRIC: Benign Recurrent Intrahepatic
Cholestasis
0 1
Budd-Chiari 0 1
Bylers Disease PFIC type I 1 0
Carolis Disease 1 0
Congenital Hepatic Fibrosis 1 2
Crigler-Najjar 1 5
Cystic Fibrosis 1 1
Fulminant Hepatic Failure 2 2
Giant Cell Hepatitis 0 1
Glycogen Storge Disease 1 0
Hepatic Fibrosis 1 0
Hepatoblastoma 1 1
Hepatocellular Carcinoma 0 1
Methylmalonic Acidemia 1 0
Maple Syrup Urine Disease 7 8
Ornithin Transcarbamylase Deficiency 1 2
Primary Sclerosing Cholangitis 2 1
Secondary Biliary Cirrhosis 0 1
Paucity of Bile Ducts 1 0
Tyrosenemia 1 1
Cirrhosis-unknown 2 1
Total 37 43

Fifty-seven SNPs passed our screening test due to large differences in MAF, when parents of Rejectors were compared with parents of Non-Rejectors (Appendix 1). When the GC statistic was applied to these 57 SNPs, only one SNP, rs9296068, in the 5′ flanking UTR of HLA-DOA demonstrated differences between groups with p<0.05 in parent-to-child transmission (p=0.0183, Table 2). Specifically, the minor allele G was transmitted more frequently to Rejectors, and less so to Non-Rejectors from biological parents. The physical position of the implicated SNP is 33096673 (Build 35). Figure 1 summarizes the results of the PAF comparison for the entire set of 1,774 MHC SNPs (upper panel), and the results of the GC test applied to the 57 selected SNPs for Rejectors and Non-Rejectors (lower panel).

Table 2.

Only one SNP, rs9296068 near the HLA-DOA gene, met criteria for selection and hypothesis testing in our two-tier approach. This SNP demonstrated a large difference (p=0.041) in MAF when parents of Rejectors were compared with parents of Non-Rejectors, as well as significant differences in parent-to-child transmission between Rejectors and Non-Rejectors, on the GC test (p=0.0183). Transmission data show more parents (n=19) transmitting the minor allele of rs9296068 to their Rejector offspring than parents who did not (n=12). The reverse was true among Non-Rejectors, whose parents were less likely to transmit this risk allele (7 transmissions vs 17 non-transmissions).

HLA-DOA/ SNP=rs9296068 (physical position=33,096,673)
Rejector vs. Non-Rejector MAF p value 0.041
Rejector vs. Non-Rejector GC p value 0.018
GC transmission parameter (τ2) 1.9
Allele 2
Rejector parents
 MAF 46.3%
 Number transmitted 19
 Number non-transmitted 12
Non-Rejector parents
 MAF 33.8%
 Number transmitted 7
 Number non-transmitted 17

MAF=minor allele frequency

For the GC statistic, under the null hypothesis of Mendelian segregation, τk=1 for all k alleles (11)

Figure 1.

Figure 1

Upper panel shows −log10(p-values) for comparison of minor allele frequencies of 1,776 SNPs in parents of Rejectors, and parents of Non-Rejectors. Fifty seven SNPs show large differences (p<0.05, −log10(p-value)>1.3) in allele frequencies in this comparison and are shown in the lower panel. Only one of these 57 SNPs (lower panel) also shows significant differences in parent-to-child transmission when Rejectors were compared with Non-Rejectors in the gamete competition statistic. This SNP rs9296068, marked by the red square is located in the HLA-DOA gene.

In the confirmatory association testing step, 77 SNPs showed significant differences in allele frequencies when Rejectors were compared directly with Non-Rejectors (p≤0.05). Among these 77 SNPs, additional between-group comparisons showed 39 SNPs to be significantly different among Rejectors, and 19 SNPs to be significantly different among Non-Rejectors, when each group was compared separately with 400 normal controls (Appendix 2). In direct comparisons, the differences between Rejectors and Non-Rejectors were most significant (p=0.002) for the SNP rs9296068 (Table 3). When compared with normal controls, the minor allele (G) of rs9296068 was more commonly seen among Rejectors (36.7% vs 51.4%, p=0.015), but less commonly among Non-Rejectors (36.7 % vs 26.8%, p=0.074). Only one other SNP rs9276994 shows similar differences in distribution, when Rejectors are compared with Non-Rejectors (48.6% vs 28%, p=0.009), and when normal controls are compared either with Rejectors (37.7% vs 48.6 %, p=0.074) or with Non-Rejectors (37.7% vs 28%, p=0.083) (Table 4). In all, five of 14 top-ranked discriminatory SNPs localized to the 5′ flanking UTR of HLA-DOA (Table 4).

Table 3.

Confirmatory association testing shows that MAF for rs9296068 are greater among Rejectors, and less among Non-Rejectors, compared with a large cohort of 400 normal Caucasian children. Together, these results confirm parent-to-child over-transmission among Rejectors, and under-transmission among Non-Rejectors, observed in the GC test.

Rejector vs. Controls MAF in Rejector children 51.4%
MAF in Controls 36.8%
x 2 5.90
P value 0.015
Odds ratio 1.82
Non-Rejector vs.
Controls
MAF in Non-Rejector children 26.8%
MAF in Controls 36.8%
x 2 3.18
p value 0.074
Odds ratio 0.63

MAF=minor allele frequency

*

MAF differences are based on the samples used. For the unrelated case/control association shown in the table above, children are used to calculate allele frequencies. For the GC test in Table 2, trio information is used, resulting in minor differences in allele frequency.

Table 4.

Results of confirmatory association testing for SNPs, ordered by physicial position, which showed the most significant differences in MAF (p≤0.010) between Rejectors and Non-Rejectors (last column). Of 14 such SNPs, five are near HLA-DOA. Among them, rs9296068 and rs9276994 show MAF, which are greater among Rejectors (R), and less among Non-rejectors (NR), compared with 400 normal control Caucasian children (NC). Only rs9296068 shows differences in PAF between outcome groups, satisfying selection criteria for candidacy, while rs9276994 fails the PAF test.

Allele Frequency Chi-square test p-values
SNP Physical
location
Closest
Gene
R NR NC R vs NC NR vs
NC
R vs
NR
rs2517904 29,976,963 HCG2P7 2.9% 15.9% 7.5% 0.147 0.009 0.007
rs3134879 30,123,884 ZNRD1 26.6% 48.7% 41.1% 0.023 0.192 0.007
rs9366752 30,132,656 ZNRD1 34.3% 15.9% 20.0% 0.005 0.368 0.008
rs9261441 30,199,737 TRIM31 15.7% 3.7% 13.6% 0.623 0.01 0.01
rs1345229 30,290,374 TRIM26 14.3% 2.4% 11.9% 0.553 0.009 0.007
rs1264583 30,401,462 TRIM39 14.3% 2.4% 5.0% 0.001 0.3 0.007
rs1264581 30,405,484 TRIM39 16.2% 3.7% 5.3% 0.000 0.524 0.009
rs3094097 30,741,854 DHX16 14.3% 2.4% 9.8% 0.228 0.028 0.007
rs602875 32,681,607 HLA-DRB1 42.9% 22.0% 23.8% 0.000 0.707 0.006
rs6457699 33,089,625 HLA-DOA 54.3% 31.7% 46.8% 0.226 0.009 0.005
rs9276994 33092233 HLA-DOA 48.6% 28.1% 37.8% 0.075 0.083 0.009
rs6933994 33095098 HLA-DOA 57.1% 36.3% 46.0% 0.614 0.002 0.01
rs9296068 33,096,673 HLA-DOA 51.4% 26.8% 36.8% 0.015 0.074 0.002
rs9277015 33,101,244 HLA-DOA 44.3% 24.4% 37.0% 0.228 0.023 0.01

The first HLA-DOA exon is repressed in Rejectors

Following probe filtering (explained above) and retention of only those genes with at least one exon with p<0.05, two genes remained, HLA-DOA and HLA-DPA1 (Appendix 3). The first HLA-DOA exon between physical positions 33,085,305-33,085,362 was repressed among Rejectors, as suggested by −1.53-fold decreased expression, compared with Non-Rejectors (Figure 2). This repressed exon lies immediately adjacent to the 5′ flanking UTR of HLA-DOA, which contains the risk allele rs9296068 at position 33,096,673, and is ≈11.3 kb removed from the risk allele. In contrast, ≈47.8 kb, and three HLA-DPA exon transcripts separate rs9296068 from the discriminatory HLA-DPA exon at position 33,144,437-33,144,544, whose expression is −1.30-fold lower among Rejectors, compared with Non-Rejectors.

Figure 2.

Figure 2

Splicing index values, defined as the fold change between mean gene-level normalized exon intensities in the Rejector and Non-Rejector groups and 95% confidence intervals for the 10 exons that map to the HLA-DOA gene. The physical position ranges of each exon are represented on the x-axis and any exon point with a significant p-value (p<.05) is shaded red. Significant negative fold changes represent exon skipping or repression, while significant positive fold changes represent exon enrichment for the gene.

Intragraft B-cell content is higher in Rejectors with the risk allele of rs9296068 (Figure 3)

The risk allele (G) of rs9296068 was present in seven of 10 liver allograft biopsies from Non-Rejectors (allele frequency=0.4), and 19 of 26 Rejectors (allele frequency=0.5). B-cell content (median±SEM) was low at 1.1 cell per portal area in Non-Rejectors. Among Rejectors, the risk allele (G) was absent in seven, heterozygous in 12, and homozygous in seven. B-cell content in respective allograft biopsies from these Rejectors was 4±2.6 cells, 11±3.3 cells, and 16±4.7 cell per portal area, and showed significant correlation with the risk allele (r2=0.194, p=0.021, Figure 3). Also, differences between B-cell content were significant when Rejectors without the risk allele (n=7, 4±2.6 B-cells/portal area) were compared with Rejectors who were either homozygous or heterozygous for the risk allele of rs9296068 (n=17, 11.54±2.4 cells/portal area, p=0.022). The lobular areas contained an average of 0-3 B-cells per lobule in both Rejectors and Non-Rejectors, and showed no differences.

Subanalysis in Caucasian children to evaluate population stratification

The HapMap database shows rs9296068 (G) allele frequencies of 31% in Caucasians (CEU), and 67.8% in Yoruba (YRI) populations. To avoid false positive association in case-control comparisons, trios for two African-Americans and all six Non-Caucasians were excluded, five new trios from Caucasians children with LTx added, and both, the PAF comparison and simple case/control association were recalculated for 35 Rejectors, and 42 Non-Rejectors. Four SNPs adjacent to HLA-DOA remain discriminatory (p<0.05) in comparison of Rejectors with Non-Rejectors. Among them, rs6457699, rs9276994, and rs9296068 are ranked 3, 8 and 9 among the top ten SNPs, with all showing greater MAF among Rejectors and less among Non-Rejectors, compared with 400 normal Caucasian children (Appendix 4). In the PAF test, higher MAF among parents of Rejectors approached significance for rs6457699 (p=0.055) and rs9276994 (p=0.077) but not for rs9296068 (40 vs 34.7%, p=0.43). This observation suggests that the Rejector group is relatively underpowered to detect MAF differences for the rs9296068 SNP, even though the GC test confirms significant differences in parent-to child transmission between groups for its risk allele (p=0.004). Finally, both rs6457699, and rs9276994 are situated ≈4kb and ≈6kb upstream of the first HLA-DOA exon, and the GC test was significant for rs6457699 (p=0.04), implicating HLA-DOA once again (Appendix 4).

The GC test, unlike a case/control association, is based on distortions in allele transmission from parent to child, and so should be less sensitive to population substructure. It is of interest to assay whether or not transmission distortion occurs at the SNP of interest in the HapMap non-disease reference population (26). Therefore, the GC statistic was calculated for both alleles of rs9296068 for 30 YRI families (90 individuals), and 20 CEU families (90 individuals) using genotype and pedigree files from the Hapmap database. In both populations, the risk allele failed to show preferential transmission compared with its complementary allele, as suggested by GC p-values >0.05. Therefore, the null hypothesis of Mendelian transmission cannot be rejected. This sub-analysis supports our conclusions from GC testing of 72 Caucasian and 8 Non-Caucasian trios.

Discussion

Our multi-step approach identifies the HLA-DOA gene, and the B-lymphocyte in which it is exclusively expressed, as plausible candidates contributing to pediatric LTx rejection. Adding early functional validation to family-based association in the same dataset is especially useful, because it obviates the need for immediate replication in an independent cohort, whose accrual may take several years in the case of rare disease traits. This novel approach was motivated by failure when we first performed genome-wide association with the unmodified TDT applied to all 550,000 SNPs (on-going study and data not shown). All SNPs showing significant p-values failed to remain significant after Bonferroni correction for multiple hypothesis testing.

Because SNP reduction with PAF comparisons and the GC test are independent, the combined p-value for r9296068 is a multiple of values from both procedures (0.041*0.0183=0.00075). However, this would not be significant after multiple-testing correction for 1,774 SNPs. Therefore, transmission characteristics of rs9296068 were confirmed by showing that allele frequencies in Rejectors and Non-Rejectors were respectively, significantly greater (51.4 vs 36.8%, p=0.015), and less (26.8 vs 36.8%, p=0.074) than those in the normal control population of 400 Caucasian children (Table 3). Finally, in direct comparisons of allele frequencies between Rejectors and Non-Rejectors, the 5′ flanking UTR of HLA-DOA was represented by five SNPs among 14 top-ranked SNPs (p≤0.01) (Table 4), of which rs9296068 achieved the highest p-value (0.002), and another, rs9276994, also showed evidence of over-transmission in Rejectors (p=0.074), and under-transmission in Non-Rejectors (p=0.082), even though parental allele frequencies were similar. Significantly, all five highly-ranked SNPs, beginning with rs6457699 and ending with rs9277015, were present upstream, in an ≈11.6 kb segment, at a distance of ≈4-15 kb from the first HLA-DOA exon (Figures 2 and 3). Promoter function has been predicted for a highly conserved ≈10kb region immediately upstream of the first HLA-DOA exon, with Caucasians demonstrating a linkage disequilibrium (LD) block encompassing the rs9296068 locus (Figure 4) (27). Because 3 of 5 discriminatory SNPs localize to this putative promoter, altered transcription factor binding, and differential regulation of HLA-DOA gene expression can be postulated. Significant repression of the first HLA DOA exon among Rejectors in our study supports this view. Decreased HLA-DOA gene expression is also seen with increasing numbers of the risk allele of rs9296068 for both Caucasian and Yoruba populations in public databases (28).

Figure 4.

Figure 4

The HLA-DOA gene is transcribed from the minus strand. The upstream 5′ flanking UTR region defined by five discriminatory SNPs in simple association testing of Rejectors vs Non-Rejectors lies between rs9296068 to the right and rs6457699 to the left, and shows marked linkage disequilibrium. Rs6457699 lies ≈4kb from the first HLA-DOA exon, on the left. Rs9296068 is associated with allele-dependent decrease in HLA-DOA expresion among CEU and YRI in public databases (Source: WGAViewer).

We interpret our observed associations as suggestive of a causal role for the HLA-DOA gene, and for the B-lymphocyte, rather than a causal role for the SNP itself; however causality remains unproven until definitive studies identify a true causal variant, and the mechanism by which it might alter HLA-DOA gene expression and B-cell function. For the association itself, all statistical tests used sequentially in the current study are necessary because neither simple association testing nor family-based association testing generates, by itself, a list of SNPs larger than the expected false positive prediction (p=0.05 times 1,774 SNPs=89 false-positives). The HLA-DOA gene, and its adjacent region, is of interest for several reasons. Compared with one of its 3′ neighbors, HLA-DPB1, which is highly polymorphic, and can influence immunological outcomes in bone-marrow, corneal and renal transplantation, the HLA-DOA gene is relatively non-polymorphic, and inhibits class II antigen presentation in mature B-cells; but its role in organ transplantation is unknown (29-31, 19, 20). Our findings lead us to speculate that a missing exon transcript may produce a dysfunctional HLA-DOA gene product, which facilitates rejection by failing to inhibit antigen presentation by B-lymphocytes. The resulting increased B-lymphocyte participation in the rejection process is seen as nearly three-fold higher intragraft B-lymphocyte content in rejecting liver grafts in our study, when the minor allele G of rs9296068 was present, compared with rejecting allografts from children without this allele. Among pediatric LTx, prior supportive evidence also includes greater resistance of activated B-lymphocytes to immunosuppression, as well as a relative excess of B-lymphocytes during the risk period for early rejection (18, 32). B-lymphocyte-rich infiltrates, as well as B-lymphocyte-specific gene expression products have already been demonstrated in renal allografts with steroid-resistant acute cellular rejection (33). While our observations are preliminary, they suggest that the HLA-DOA gene and its vicinity be mapped further to identify novel causal variants.

We acknowledge several limitations. The heterogeneous diagnoses precipitating LTx are potential sources of stratification, although no single disease dominated either outcome group. For example, all 5 children with PSC carried the risk allele, with four experiencing rejection, despite statistically similar proportions of PSC in either group (4/37 Rejectors vs 1/43 Non-Rejectors, p=NS). Second, our SNP reduction step which relies on PAF comparisons, is biased by inclusion of eight Non-Caucasians trios, seven in the Rejector group. In accepting rs9296068 as a candidate, an illustrative subanalysis shows that our conclusions would be unchanged if an adequately powered Caucasian sample was available (Appendix 5). For these reasons, we have also relied on functional studies, coupled with allele-specific decrease in HLA-DOA expression in public databases for both CEU and YRI, to suggest biological relevance for the risk allele. We hope to relate differences in HLA-DOA exon repression to allelic variations at rs9296068 in a larger future sample. The small numbers of Rejectors (n=11) in whom HLA-DOA exon repression was shown, could not be divided further for adequately powered correlations with allelic variants in this study.

We conclude that our combination of methods can identify biologically relevant associations in small populations. We propose to validate our conclusions and address the primary power limitations of this pilot study by extending it to multicenter LTx populations.

Acknowledgments

Support: 5RO1AI073895-01, Children’s Hospital of Pittsburgh Research Foundation, and Hillman Foundation of Pittsburgh.

Special thanks: Timothy Billiar and Roger Oxendale.

Appendix 1

Appendix 1. p-values for parental allele frequency comparison, and for the GC statistic comparing prent-to-child transmission of SNPs between Rejectors and Non-Rejectors.

The minor allele for each snp is identified in the allele column, and the minor allele frequencies (MAF)s in both the parents and offspring for each group (NR and R) are provided for this allele.

For each SNP in the GC model, the transmission parameter tau k is set to 1 for the most frequent allele k, while the remaining tauk values (for all k not equal to the most frequent allele) are estimated by maximum likelihood.

SNP Closest
Gene
Distance to
gene
Position SNP type Parental allele
frequency
comparison, p-
value
Lower
conf.
Interval
Higher
conf.
Interval
Rejector
Parents MAF
Non-Rejector
Parents MAF
Rejector MAF Non-Rejector
MAF
Rejector vs.
Non-Rejector
GC p value
tauk Allele
frequency
in group k
Allele distance to exon boundary
rs4713213 OR5V1 0 29446941 INTRONIC 0.046 0.0027 0.2463 50.8% 38.3% 44.4% 40.2% 0.285 0.7749 44.0% 1 −9
rs4598109 OR5V1 0 29452683 INTRONIC 0.028 0.0146 0.2546 46.2% 32.7% 38.6% 35.7% 0.144 0.7032 38.8% 1 −9
rs238883 OR5V1 0 29454205 INTRONIC 0.033 −0.2547 −0.0115 38.6% 52.0% 43.1% 46.4% 0.097 1.5377 46.0% 2 −9
rs238882 OR5V1 0 29454342 INTRONIC 0.012 0.0324 0.2711 48.5% 33.3% 41.7% 35.7% 0.228 0.7473 40.7% 1 −9
rs238872 OR5V1 0 29459852 INTRONIC 0.040 0.0066 0.251 53.8% 40.9% 50.0% 46.4% 0.180 0.7316 47.2% 1 −9
rs3094556 OR5V1 0 29461387 INTRONIC 0.004 0.0571 0.2963 58.7% 41.0% 55.6% 46.4% 0.290 0.7794 49.7% 2 −9
rs3094551 OR5V1 0 29462778 INTRONIC 0.010 −0.2759 −0.0379 36.2% 51.9% 40.0% 46.4% 0.303 1.2708 44.4% 1 −9
rs3094550 OR5V1 0 29462788 INTRONIC 0.009 −0.28 −0.0399 36.6% 52.6% 40.0% 47.6% 0.382 1.2278 45.2% 2 −9
rs2517817 HLAH_HUMAN 671 29967496 DOWNSTREAM 0.032 −0.1501 −0.009 4.6% 12.5% 2.9% 13.8% 0.273 0.6088 10.0% 1 −9
rs7758512 Q6ZU40_HUMAN 0 30078568 INTRONIC 0.034 0.0049 0.1686 15.9% 7.2% 14.7% 12.2% 0.374 0.7223 12.1% 2 −9
rs9261129 Q6ZU40_HUMAN 0 30087558 INTRONIC 0.042 0.0024 0.1605 14.4% 6.3% 14.3% 11.9% 0.405 0.735 11.8% 2 −9
rs9261277 ZNRD1 0 30139070 INTRONIC 0.044 0.0014 0.16 15.2% 7.1% 14.3% 10.5% 0.631 0.8399 11.5% 2 −9
rs1264701 TRIM31 −4318 30174337 DOWNSTREAM 0.027 −0.2051 −0.0144 13.1% 24.1% 9.7% 22.1% 0.514 0.816 19.2% 1 −9
rs3734838 TRIM31 0 30188210 NON_SYNONYMOUS_CODING 0.042 0.0005 0.1417 11.5% 4.4% 10.0% 2.3% 0.719 1.1603 8.3% 1 −9
rs9261441 TRIM31 10891 30199737 INTERGENIC 0.012 0.019 0.1779 16.2% 6.3% 15.3% 3.6% 0.372 1.3678 10.8% 1 −9
rs2022065 TRIM10 0 30229439 3PRIME_UTR 0.045 0.0021 0.224 34.1% 22.8% 35.7% 23.2% 0.638 1.1264 28.2% 1 88
rs1345229 TRIM26 1191 30290374 UPSTREAM 0.008 0.0226 0.1713 14.2% 4.5% 13.9% 2.4% 0.341 1.4499 9.2% 1 −9
rs9357097 TRIM39 −9500 30393100 INTERGENIC 0.015 −0.2417 −0.0275 19.2% 32.7% 16.7% 32.1% 0.480 0.8097 27.2% 1 −9
rs2516649 GNL1 −16814 30604861 INTERGENIC 0.040 −0.2333 −0.0069 25.0% 37.0% 23.6% 35.7% 0.994 0.9958 31.2% 2 −9
rs2844713 GNL1 0 30627237 INTRONIC 0.043 −0.2307 −0.0052 26.8% 38.6% 27.8% 36.0% 0.476 1.1975 33.2% 1 −9
rs4248154 NM_001010909 44941 31110595 INTERGENIC 0.017 −0.1853 −0.02 8.1% 18.4% 11.1% 20.2% 0.522 0.7948 14.1% 1 −9
rs2523849 C6orf15 −53952 31133030 INTERGENIC 0.031 0.0079 0.1963 22.4% 12.2% 24.3% 13.1% 0.734 1.1123 17.6% 2 −9
rs2428514 C6orf15 −51487 31135495 INTERGENIC 0.044 0.0015 0.1804 19.9% 10.8% 20.0% 12.2% 0.910 0.9627 15.6% 1 −9
rs2517403 C6orf15 −11994 31174988 INTERGENIC 0.048 0.0013 0.2352 41.0% 29.2% 42.9% 34.5% 0.669 0.9029 35.3% 2 −9
rs2844635 C6orf15 −3522 31183460 DOWNSTREAM 0.040 0.0055 0.2384 41.0% 28.9% 42.9% 35.0% 0.603 0.8816 35.1% 2 −9
rs9295957 Q6H1K9_HUMAN 11917 31265572 INTERGENIC 0.046 −0.1814 −0.0039 10.6% 19.9% 10.6% 17.1% 0.498 1.2478 15.6% 1 −9
rs7745906 1C07_HUMAN −32518 31311987 INTERGENIC 0.037 −0.1749 −0.0076 8.8% 18.0% 7.4% 18.6% 0.960 1.0194 14.2% 1 −9
rs2074488 1C07_HUMAN 524 31348410 UPSTREAM 0.038 −0.156 −0.0066 6.0% 14.1% 8.6% 14.0% 0.386 1.4316 10.6% 1 −9
rs9366778 1C07_HUMAN 29266 31377152 INTERGENIC 0.039 −0.2425 −0.0071 33.1% 45.6% 34.7% 41.7% 0.446 1.2061 40.3% 1 −9
rs406936 NP_008860.4 0 32041140 INTRONIC 0.048 −0.1643 −0.0031 8.1% 16.5% 5.6% 15.0% 0.780 0.9085 12.5% 1 −9
rs454212 NP_008860.4 0 32042351 INTRONIC 0.028 −0.1715 −0.0123 6.4% 15.5% 6.1% 12.2% 0.948 1.0266 11.3% 1 −114
rs387608 STK19 0 32049536 INTRONIC 0.048 −0.1643 −0.0031 8.1% 16.5% 5.6% 15.0% 0.780 0.9085 12.5% 1 −9
rs2269429 TNXB 0 32137161 NON_SYNONYMOUS_CODING 0.044 −0.1475 −0.0044 5.2% 12.8% 5.6% 9.8% 0.400 1.3939 9.3% 1 −9
rs204899 TNXB 0 32165605 INTRONIC 0.012 −0.1571 −0.0214 3.7% 12.7% 2.8% 8.8% 0.657 1.1994 8.6% 1 −9
rs3115553 C6orf10 −14648 32353805 INTERGENIC 0.049 0.0004 0.2025 26.8% 16.7% 25.7% 23.2% 0.298 0.7368 21.9% 1 −9
rs9268384 C6orf10 0 32444564 NON_SYNONYMOUS_CODING 0.045 −0.2416 −0.004 33.8% 46.1% 35.7% 43.9% 0.962 0.9873 40.3% 2 5
rs4424066 C6orf10 2096 32462406 UPSTREAM 0.039 −0.2411 −0.0078 30.6% 43.0% 26.4% 37.8% 0.798 1.0642 37.2% 2 −9
rs3817973 BTNL2 −635 32469089 DOWNSTREAM 0.022 −0.2518 −0.0207 29.4% 43.0% 25.7% 36.9% 0.707 1.0954 37.0% 1 −9
rs3793126 BTNL2 0 32479597 INTRONIC 0.044 −0.2128 −0.0048 17.7% 28.6% 18.1% 25.6% 0.727 1.1156 23.8% 2 −9
rs86567 HLA-DOA 0 33084737 INTRONIC 0.037 −0.2434 −0.0089 31.6% 44.2% 31.9% 48.8% 0.292 0.7825 37.8% 2 −9
rs6457699 HLA-DOA 4258 33089625 UPSTREAM 0.031 0.0123 0.2547 53.7% 40.4% 52.9% 30.5% 0.072 1.5742 45.9% 1 −9
rs6933994 HLA-DOA 9731 33095098 INTERGENIC 0.042 0.0053 0.2485 58.1% 45.4% 55.7% 36.3% 0.173 0.7236 49.2% 1 −9
rs6457702 HLA-DOA 10660 33096027 INTERGENIC 0.009 −0.2802 −0.0399 33.3% 49.3% 37.5% 52.5% 0.757 0.9284 42.4% 1 −9
rs9296068 HLA-DOA 11306 33096673 INTERGENIC 0.041 0.0053 0.2447 46.3% 33.8% 50.0% 26.8% 0.018 1.8513 38.9% 2 −9
rs986521 COL11A2 0 33244123 INTRONIC 0.038 −0.2075 −0.0074 16.2% 26.9% 15.7% 30.0% 0.243 0.7138 21.8% 2 −151
rs9277932 COL11A2 0 33249231 INTRONIC 0.028 −0.25 −0.0154 30.9% 44.2% 35.3% 45.1% 0.813 1.0611 38.0% 1 −26
rs2855425 COL11A2 0 33252351 INTRONIC 0.040 −0.221 −0.0067 20.9% 32.3% 18.6% 32.9% 0.336 0.7725 26.6% 2 −125
rs6531 RXRB 0 33271429 SYNONYMOUS_CODING 0.036 −0.2241 −0.0088 20.6% 32.2% 18.6% 32.9% 0.342 0.776 26.4% 2 28
rs211474 DAXX 29822 33428591 INTERGENIC 0.045 0.0029 0.2401 46.3% 34.2% 43.1% 32.1% 0.926 1.0226 39.5% 1 −9
rs211455 KIFC1 −31102 33436496 INTERGENIC 0.019 0.023 0.2572 45.7% 31.7% 38.9% 29.1% 0.824 0.9483 37.8% 1 −9
rs211452 KIFC1 −28639 33438959 INTERGENIC 0.020 0.0223 0.263 52.2% 38.0% 43.1% 34.9% 0.624 0.8897 43.7% 2 −9
rs211457 KIFC1 0 33473618 INTRONIC 0.025 −0.1556 −0.0122 5.1% 13.5% 5.6% 14.6% 0.580 0.7843 9.5% 1 −166
rs3116713 PHF1 0 33490266 NON_SYNONYMOUS_CODING 0.025 −0.1445 −0.0116 3.7% 11.5% 4.2% 12.2% 0.537 0.7515 7.9% 2 33
rs211456 ZBTB9 0 33497359 INTRONIC 0.041 0.006 0.2481 54.5% 41.8% 47.2% 39.5% 0.718 0.9181 46.7% 1 −9
rs396746 NP_997380.1 0 33665023 INTRONIC 0.032 −0.1845 −0.0101 10.1% 19.9% 13.9% 20.7% 0.709 1.1293 15.1% 1 −9
rs169737 ITPR3 −12767 33684555 INTERGENIC 0.024 −0.2185 −0.0165 16.2% 27.9% 21.4% 25.6% 0.269 1.3651 22.0% 1 −9
rs12529825 ITPR3 0 33725381 INTRONIC 0.012 −0.1571 −0.0214 3.7% 12.7% 5.6% 14.6% 0.683 0.8395 8.5% 2 −9

Appendix 2

Appendix 2.

List of 77 SNPs with significant differences in allele frequencies between Rejectors (R, n=37) and Non-Rejectors (NR, n=43), between Rejectors and 400 normal control Caucasian children, and Non-Rejectors vs 400 normal control Caucasian children. When compared with normal controls, only rs9296068 shows allele frequencies which are greater in Rejectors, and less among Non-Rejectors.

rs926068 also shows the greatest differences in allele frequencies between Rejectors and Non-Rejectors, and is one of five SNPs representing the HLA-DOA gene for which allele frequency differences between groups (R vs NR) are≤0.01.

Allele frequency Rejector vs Non-Rejectors
Chi-sq
Rejectors vs normal controls
Chi-sq
Rejectors vs Normal Controls
Chi-sq
SNP Closest Gene Distance to
gene
SNP type Position Rejectors Non-Rejectors Normal Control SNP rank p-value odds ratio p-value odds ratio p-value odds ratio
rs9296068 HLA-DOA 11306 INTERGENIC 33096673 51.40% 26.80% 36.70% 1 0.002 2.888 0.0152 1.822 0.074 0.6311
rs6457699 HLA-DOA 4258 UPSTREAM 33089625 54.30% 31.70% 46.70% 2 0.005 2.558 0.226 1.353 0.009 0.5288
rs602875 HLA-DRB1 16048 INTERGENIC 32681607 42.90% 21.90% 23.80% 3 0.006 2.667 0.0004 2.401 0.707 0.9003
rs1264583 HLAH_HUMAN 10138 INTERGENIC 30401462 14.30% 2.40% 5% 4 0.007 6.667 0.001 3.167 0.299 0.475
rs3094097 Q6ZU40_HUMAN 0 INTRONIC 30741854 14.30% 2.40% 9.70% 5 0.007 6.667 0.227 1.543 0.028 0.2314
rs1345229 TRIM26 1191 UPSTREAM 30290374 14.30% 2.40% 11.90% 6 0.007 6.667 0.553 1.237 0.009 0.1855
rs3134879 TRIM39 −1138 UPSTREAM 30123884 26.60% 48.70% 41.10% 7 0.007 0.3807 0.023 0.519 0.192 1.363
rs2517904 DHX16 0 INTRONIC 29976963 2.90% 15.80% 7.50% 8 0.007 0.1561 0.147 0.3618 0.009 2.317
rs9366752 C6orf12 0 3PRIME_UTR 30132656 34.30% 15.80% 20% 9 0.008 2.769 0.005 2.087 0.368 0.7536
rs1264581 TRIM39 0 SYNONYMOUS_CODING 30405484 16.20% 3.70% 5.30% 10 0.009 5.082 0.0003 3.455 0.524 0.6799
rs9276994 HLA-DOA 6866 INTERGENIC 33092233 48.60% 28.10% 37.70% 11 0.009 2.423 0.075 1.557 0.083 0.6428
rs9277015 HLA-DOA 15877 INTERGENIC 33101244 44.30% 24.40% 37% 12 0.009 2.464 0.227 1.353 0.023 0.5493
rs6933994 TRIM31 10891 INTERGENIC 33095098 57.10% 36.30% 46% 13 0.01 2.345 0.614 0.8808 0.002 2.065
rs9261441 HLA-DOA 9731 INTERGENIC 30199737 15.70% 3.70% 13.60% 14 0.01 4.91 0.623 1.184 0.01 0.2412
rs2394255 HLA-A 9079 INTERGENIC 30057800 58.60% 37.80% 48.60% 15 0.012 2.326 0.11 1.494 0.062 0.6423
rs532098 HCG9 3625 DOWNSTREAM 32686030 30.90% 51.20% 45.60% 16 0.012 0.4255 0.019 0.5327 0.332 1.252
rs9468829 NP_003888.2 36906 INTERGENIC 30857212 21.40% 7.30% 12.10% 17 0.012 3.455 0.024 1.994 0.204 0.5773
rs16896742 HLA-DRB1 20471 INTERGENIC 30030719 46.90% 26.80% 34.20% 18 0.012 2.406 0.042 1.695 0.177 0.7043
rs2516684 RPP21 48325 INTERGENIC 30470974 17.10% 4.90% 13.10% 19 0.014 4.034 0.345 1.369 0.031 0.3394
rs12206499 HCG9 −5765 INTERGENIC 30045106 37.10% 19.50% 25.70% 20 0.015 2.438 0.0377 1.709 0.219 0.7011
rs6904029 HCG9 −809 UPSTREAM 30051046 37.10% 19.50% 25.70% 21 0.015 2.438 0.039 1.704 0.215 0.699
rs3823355 HCG9 0 NON_SYNONYMOUS_CODING 30050062 37.10% 19.50% 25.90% 22 0.015 2.438 0.041 1.693 0.207 0.6945
rs6933546 HLAH_HUMAN 671 DOWNSTREAM 33103992 42.90% 24.40% 36.60% 23 0.016 2.325 0.301 1.298 0.027 0.5582
rs2517817 HLA-DOA 18625 INTERGENIC 29967496 2.90% 14.50% 7.90% 24 0.016 0.1791 0.138 0.3548 0.048 1.982
rs3869070 Q6ZU40_HUMAN 0 INTRONIC 30131847 55.90% 36.60% 44.70% 25 0.018 2.196 0.077 1.564 0.156 0.7123
rs2647044 HLA-G 23348 INTERGENIC 32775888 22.70% 8.70% 9.90% 26 0.019 3.067 0.001 2.655 0.726 0.8655
rs2975033 BAT2 0 INTRONIC 29930240 35.70% 18.70% 25.60% 27 0.019 2.407 0.066 1.612 0.176 0.6698
rs9267522 BAT2 0 NON_SYNONYMOUS_CODING 31711749 27.10% 12.20% 13% 28 0.019 2.682 0.001 2.493 0.836 0.9295
rs3117583 BAT3 0 INTRONIC 31727555 27.10% 12.20% 13% 29 0.019 2.682 0.001 2.493 0.836 0.9295
rs3130618 BAT4 0 NON_SYNONYMOUS_CODING 31740113 27.10% 12.20% 13% 30 0.019 2.682 0.001 2.493 0.836 0.9295
rs3115663 HB25_human 21592 INTERGENIC 31709822 27.10% 12.20% 13.10% 31 0.019 2.682 0.001 2.466 0.812 0.9193
rs4711207 Q6ZU40_HUMAN 0 INTRONIC 30113733 34.40% 17.50% 22.80% 32 0.02 2.469 0.036 1.776 0.28 0.7193
rs2040450 RPP21 19669 INTERGENIC 30442318 16.20% 4.90% 12.70% 33 0.022 3.763 0.42 1.321 0.037 0.3509
rs4259245 ITPR3 0 INTRONIC 33732199 27.10% 45.10% 35.70% 34 0.022 0.4531 0.148 0.6695 0.093 1.478
rs2107202 TRIM40 0 INTRONIC 30213722 20 36.60% 25.90% 35 0.025 0.4333 0.279 0.7162 0.037 1.653
rs915664 DDR1 −54188 INTRONIC 30902596 35.70% 19.50% 30.60% 36 0.025 2.292 0.377 1.259 0.036 0.5492
rs3129763 HA25_HUMAN −14209 INTERGENIC 32698903 38.60% 21.90% 22.90% 37 0.025 2.233 0.003 2.11 0.84 0.9452
rs3893464 HCG9 −7642 INTERGENIC 30043229 37.10% 54.90% 50.60% 38 0.029 0.4859 0.03 0.5763 0.463 0.843
rs9261301 RNF39 0 INTRONIC 30149538 52.90% 35.40% 44.40% 39 0.03 2.049 0.171 1.405 0.117 0.6859
rs9267546 LY6G6D −1245 UPSTREAM 31781415 17.60% 6.20% 9.30% 40 0.03 3.214 0.026 2.102 0.371 0.6541
rs387608 HCG9 0 INTRONIC 32049536 5.70% 17.10% 15% 41 0.031 0.2944 0.033 0.3434 0.618 1.167
rs406936 TRIM39 −9500 INTERGENIC 32041140 5.70% 17.10% 14.70% 42 0.031 0.2944 0.037 0.3503 0.574 1.19
rs9357097 NP_008860.4 0 INTRONIC 30393100 17.10% 32.50% 30.90% 43 0.031 0.4297 0.0155 0.4615 0.776 1.074
rs2394250 STK19 0 INTRONIC 30051635 51.40% 34.10% 41.60% 44 0.031 2.042 0.111 1.485 0.189 0.7272
rs2257914 TRIM40 0 5PRIME_UTR 30228542 10% 23.20% 17.50% 45 0.032 0.3684 0.108 0.5238 0.203 1.422
rs2021723 TRIM10 0 3PRIME_UTR 30211902 10% 23.20% 17.30% 46 0.032 0.3684 0.119 0.533 0.182 1.447
rs2844776 TRIM26 0 INTRONIC 30279806 15.70% 30.50% 20.10% 47 0.033 0.4251 0.374 0.74 0.028 1.741
rs2395175 HLA-DRA −2621 UPSTREAM 32513004 4.30% 14.60% 14.20% 48 0.033 0.2612 0.02 0.2714 0.907 1.039
rs2187668 HA25_HUMAN 0 INTRONIC 32713862 20.60% 8.50% 8.60% 49 0.034 2.778 0.0013 2.747 0.978 0.9888
rs9267911 TRIM31 0 INTRONIC 32313088 58.60% 41.50% 47.30% 50 0.035 1.996 0.069 1.578 0.317 0.7908
rs2523990 NOTCH4 13266 INTERGENIC 30185208 58.60% 41.50% 47.40% 51 0.035 1.996 0.0722 1.57 0.307 0.7868
rs12212092 HCG9 −9631 INTERGENIC 30236421 12.90% 3.70% 6.30% 52 0.036 3.885 0.037 2.19 0.338 0.5635
rs6457109 TRIM10 0 NON_SYNONYMOUS_CODING 30041240 18.60% 7.30% 9.90% 53 0.036 2.889 0.0233 2.082 0.455 0.7205
rs9277027 HLAH_HUMAN −5770 INTERGENIC 33106216 30% 15.80% 30.40% 54 0.037 2.275 0.948 0.9824 0.006 0.4319
rs2523809 HLA-DOA 20849 INTERGENIC 29957598 8.60% 20.70% 11.80% 55 0.037 0.3585 0.424 0.7041 0.019 1.964
rs375912 NR_002139.1 −14455 INTERGENIC 33124706 32.90% 18.30% 36.50% 56 0.039 2.186 0.543 0.8514 0.001 0.3895
rs2517930 HLA-DPA1 −15618 INTERGENIC 29853054 37.10% 21.90% 30.80% 57 0.039 2.101 0.271 1.329 0.097 0.6325
rs4713411 NM_001010909 29501 INTERGENIC 31095155 28.10% 44.90% 43.40% 58 0.04 0.4807 0.018 0.5114 0.796 1.064
rs1264567 TRIM40 −11178 INTERGENIC 30474079 20% 8.50% 18.90% 59 0.041 2.679 0.818 1.075 0.02 0.4011
rs213213 RPP21 51430 INTERGENIC 33291708 21.40% 36.60% 26.70% 60 0.041 0.4727 0.332 0.7468 0.058 1.58
rs1419675 RING1 3232 DOWNSTREAM 30200686 21.40% 36.60% 25.90% 61 0.041 0.4727 0.413 0.7813 0.037 1.653
rs6910071 C6orf10 0 INTRONIC 32390832 7.14% 18.30% 19.10% 62 0.043 0.3436 0.0126 0.3253 0.855 0.9467
rs86567 HLA-DOA 0 INTRONIC 33084737 31.40% 47.60% 38.10% 63 0.043 0.5053 0.267 0.7439 0.095 1.472
rs3734838 RNF39 12015 INTERGENIC 30188210 10.30% 2.40% 8.50% 64 0.044 4.59 0.622 1.229 0.052 0.2676
rs6909253 TRIM31 −6114 INTERGENIC 30163622 52.90% 36.60% 37.30% 65 0.044 1.943 0.01 1.889 0.906 0.9719
rs9261394 TRIM31 0 NON_SYNONYMOUS_CODING 30172541 52.90% 36.60% 38% 66 0.044 1.943 0.015 1.829 0.801 0.9413
rs1003581 GABBR1 0 INTRONIC 29648183 9.10% 21.20% 19.90% 67 0.045 0.3706 0.032 0.4019 0.778 1.085
rs594223 C6orf125 0 INTRONIC 33775943 21.40% 9.80% 17.90% 68 0.045 2.523 0.46 1.253 0.063 0.4967
rs9468692 RNF39 1571 UPSTREAM 30227869 14.30% 4.90% 7.10% 69 0.046 3.25 0.032 2.173 0.445 0.6685
rs1150735 TRIM10 0 3PRIME_UTR 30153178 27.10% 42.70% 40% 70 0.046 0.5003 0.034 0.5588 0.637 1.117
rs1052486 BAT3 0 NON_SYNONYMOUS_CODING 31718665 40% 56.40% 43.70% 71 0.046 0.5152 0.008 1.934 0.987 0.9961
rs1264701 TRIM31 −4318 DOWNSTREAM 30174337 10% 21.90% 22.40% 72 0.048 0.3951 0.015 0.3842 0.921 0.9726
rs1077393 BAT3 0 INTRONIC 31718508 40% 56.10% 44.10% 73 0.048 0.5217 0.01 1.899 0.969 0.991
rs986521 COL11A2 0 INTRONIC 33244123 15.70% 29.30% 20.10% 74 0.048 0.4506 0.374 0.74 0.053 1.642
rs9262138 DHX16 0 NON_SYNONYMOUS_CODING 30735846 10% 2.40% 5.90% 75 0.049 4.444 0.17 1.78 0.196 0.4005
rs9267665 ZBTB12 1087 UPSTREAM 31978835 10% 2.40% 4.30% 76 0.049 4.444 0.029 2.503 0.43 0.5632
rs7745906 1C07_HUMAN −32518 INTERGENIC 31311987 7.35% 18.30% 13% 77 0.05 0.3545 0.177 0.5311 0.182 1.498

Appendix 3

Appendix 3.

Summary statistics for differentially expressed exons between Rejectors and Non-rejectors

Exon ID Transcript ID Exon fold change Exon p-value Transcript fold change Transcript p-value Transcript/SNP name Exon start/SNP location Exon stop
2950312 2950307 1.063 0.555 −1.083 0.326 HLA-DOA 33,081,985 33,082,504
2950313 2950307 1.122 0.397 −1.083 0.326 HLA-DOA 33,082,838 33,082,870
2950314 2950307 1.069 0.372 −1.083 0.326 HLA-DOA 33,082,939 33,082,970
2950317 2950307 −1.065 0.638 −1.083 0.326 HLA-DOA 33,083,111 33,083,291
2950322 2950307 −1.060 0.395 −1.083 0.326 HLA-DOA 33,083,777 33,083,802
2950323 2950307 −1.011 0.905 −1.083 0.326 HLA-DOA 33,083,818 33,083,847
2950324 2950307 1.017 0.84 −1.083 0.326 HLA-DOA 33,083,857 33,083,987
2950325 2950307 1.127 0.383 −1.083 0.326 HLA-DOA 33,084,068 33,084,099
2950326 2950307 −1.048 0.748 −1.083 0.326 HLA-DOA 33,085,222 33,085,260
2950327 2950307 −1.532 0.0153 −1.083 0.326 HLA-DOA 33,085,305 33,085,362
untranslated rs6457699 33,089,625
untranslated rs9276994 33,092,233
untranslated rs6933994 33,095,098
untranslated rs9296068 33,096,673
untranslated rs9277015 33,101,244
2950331 2950329 1.129 0.545 −1.166 0.419 HLA-DPA1 33,140,788 33,140,818
2950332 2950329 −1.161 0.517 −1.166 0.419 HLA-DPA1 33,140,836 33,140,861
2950333 2950329 −1.246 0.204 −1.166 0.419 HLA-DPA1 33,140,925 33,141,014
2950338 2950329 −1.302 0.0128 −1.166 0.419 HLA-DPA1 33,144,437 33,144,544
2950340 2950329 −1.114 0.31 −1.166 0.419 HLA-DPA1 33,144,774 33,144,804
2950341 2950329 −1.014 0.875 −1.166 0.419 HLA-DPA1 33,144,844 33,144,876
2950342 2950329 1.030 0.792 −1.166 0.419 HLA-DPA1 33,144,929 33,144,963
2950343 2950329 −1.114 0.479 −1.166 0.419 HLA-DPA1 33,144,969 33,144,999
2950345 2950329 1.057 0.565 −1.166 0.419 HLA-DPA1 33,145,413 33,145,477
2950346 2950329 1.346 0.113 −1.166 0.419 HLA-DPA1 33,145,573 33,145,641
2950348 2950329 1.035 0.723 −1.166 0.419 HLA-DPA1 33,149,238 33,149,262

Exon fold change, or splicing index, is calculated as the ratio of mean gene-level normalized intensities between rejectors and non-rejectors. Negative values indicate exon skipping or repression, whereas positive values indicate exon enrichment. The p-values are calculated using a Student’s two-sample t -test on gene-level normalized intensities. Orange cells indicate p<.05.

Transcript fold change is calculated as the ratio of the mean gene-level intensities between rejectors and non-rejectors. All exons within a transcript have identical gene-level intensities, but different exon-level intensities. The p-values are calculated using a Student’s two-sample t -test on gene-level intensities.

Appendix 4

Appendix 4.

Top-ranked SNPs with p<0.01 from simple association testing with Rejectors (n=35) vs Non-Rejectors (n=42), all of whom are Caucasians

MAF MAF MAF REJ vs. NONREJ REJ vs. CONTROLS NONREJ vs. CONTROLS
SNP rank physical position type Closest gene Distance to gene Rejectors Controls Non-Rejectors P-VALUE OR L95 U95 Chi-Sq P-value OR L95 U95 Chi-Sq P-value OR L95 U95
rs2975033 4 29930240 INTERGENIC HLA-G 23348 36.36 25.62 14.86 0.0034 3.273 1.451 7.382 0.05727 1.659 0.9801 2.807 0.04007 0.5068 0.262 0.9804
rs12206499 10 30045106 INTERGENIC HCG9 −5765 36.36 25.69 16.22 0.0065 2.952 1.332 6.544 0.05914 1.653 0.9765 2.797 0.07133 0.5598 0.2957 1.06
rs3823355 11 30050062 UPSTREAM HCG9 −809 36.36 25.87 16.22 0.0065 2.952 1.332 6.544 0.06405 1.637 0.9675 2.77 0.06659 0.5545 0.2929 1.049
rs6904029 12 30051046 NON_SYNONYMOUS_CODING HCG9 0 36.36 25.75 16.22 0.0065 2.952 1.332 6.544 0.06059 1.648 0.9738 2.788 0.06976 0.5581 0.2948 1.056
rs2394255 2 30057800 DOWNSTREAM HCG9 3625 59.09 48.62 33.78 0.0027 2.831 1.423 5.631 0.1021 1.526 0.9166 2.542 0.01447 0.5391 0.3266 0.8901
rs3869070 6 30131847 INTRONIC Q6ZU40_HUMAN 0 56.25 44.75 32.43 0.0049 2.679 1.339 5.358 0.0755 1.587 0.9502 2.652 0.04098 0.5926 0.3572 0.9832
rs9366752 1 30132656 3PRIME_UTR C6orf12 0 33.33 20 12.16 0.0026 3.611 1.521 8.575 0.01061 2 1.165 3.433 0.1024 0.5538 0.27 1.136
rs6909253 15 30163622 INTERGENIC RNF39 12015 54.55 37.25 32.43 0.0083 2.5 1.258 4.968 0.005529 2.021 1.22 3.35 0.4111 0.8086 0.4868 1.343
rs9261394 16 30172541 INTERGENIC TRIM31 −6114 54.55 38 32.43 0.0083 2.5 1.258 4.968 0.008155 1.958 1.181 3.245 0.344 0.7832 0.4716 1.301
rs2523990 13 30185208 INTRONIC TRIM31 0 60.61 47.38 37.84 0.0071 2.527 1.278 4.997 0.0387 1.709 1.023 2.854 0.1156 0.6762 0.4143 1.104
rs1345229 18 30290374 UPSTREAM TRIM26 1191 15.15 11.87 2.703 0.0086 6.429 1.354 30.53 0.4332 1.325 0.654 2.685 0.01625 0.2061 0.04976 0.8539
rs9357097 7 30393100 INTERGENIC TRIM39 −9500 15.15 30.95 36.11 0.0051 0.3159 0.1382 0.7224 0.006962 0.3984 0.1999 0.7937 0.3663 1.261 0.7619 2.087
rs1264583 19 30401462 UPSTREAM TRIM39 −1138 12.12 5 1.351 0.0095 10.07 1.224 82.82 0.01509 2.621 1.172 5.86 0.1556 0.2603 0.03527 1.921
rs1264581 5 30405484 SYNONYMOUS_CODING TRIM39 0 14.06 5.29 1.351 0.0041 11.95 1.47 97.1 0.004299 2.93 1.356 6.329 0.1354 0.2453 0.03327 1.808
rs3095150 17 31040511 INTERGENIC DPCR1 10534 45.45 42.8 24.32 0.0086 2.593 1.263 5.32 0.6759 1.114 0.6723 1.844 0.002013 0.4295 0.248 0.744
rs6457699 3 33089625 UPSTREAM HLA-DOA 4258 53.12 46.75 28.38 0.0031 2.86 1.414 5.786 0.3256 1.291 0.775 2.15 0.002381 0.4513 0.2672 0.7623
rs9276994 8 33092233 INTERGENIC HLA-DOA 6866 46.88 37.75 24.32 0.0055 2.745 1.332 5.658 0.1487 1.455 0.8726 2.426 0.02181 0.53 0.3058 0.9186
rs6933994 14 33095098 INTERGENIC HLA-DOA 9731 56.25 45.99 33.33 0.0072 2.571 1.282 5.156 0.7293 0.9134 0.5468 1.526 0.0007677 2.349 1.411 3.909
rs9296068 9 33096673 INTERGENIC HLA-DOA 11306 46.88 36.75 24.32 0.0055 2.745 1.332 5.658 0.1074 1.519 0.9105 2.533 0.0328 0.5532 0.3191 0.959

Parental Allele test and Gamete Competition (GC) test for the same snps as above

The 5′UTR flanking region of HLA-DOA is represented by 4 SNPs, of which rs6457699 lies roughly 4kb from the first HLA-DOA exon, and also shows differences in parental allele comparisons, which approach significance at p=0.055 (yellow cell).

rs9296068 is more frequent in parents of Rejectors, compared with parents of Non-Rejectors. However, differences are not statistically significant, due to reduced power in the Rejector group, and among Rejector parents, as a result of removing seven non-Caucasians, and adding 5 caucasian trios.

Appendix 5

Parental Allele test MAF-Parents MAF-Parents GC test
SNP rank physical position type Closest gene Distance to gene Chi-Sq p-value LCI UCI Rejectors Non-Rejectors P-VALUE
rs2975033 4 29930240 INTERGENIC HLA-G 23348 0.08 −0.01 0.21 30.95 21.05 0.075
rs12206499 10 30045106 INTERGENIC HCG9 −5765 0.22 −0.04 0.19 31.75 24.34 0.0126
rs3823355 11 30050062 UPSTREAM HCG9 −809 0.19 −0.04 0.19 32.03 24.34 0.026
rs6904029 12 30051046 NON_SYNONYMOUS_CODING HCG9 0 0.22 −0.04 0.19 31.75 24.34 0.026
rs2394255 2 30057800 DOWNSTREAM HCG9 3625 0.42 −0.07 0.18 47.62 42.11 0.004
rs3869070 6 30131847 INTRONIC Q6ZU40_HUMAN 0 0.46 −0.07 0.18 45.16 40.00 0.014
rs9366752 1 30132656 3PRIME_UTR C6orf12 0 0.42 −0.06 0.16 26.98 22.08 0.006
rs6909253 15 30163622 INTERGENIC RNF39 12015 0.16 −0.03 0.21 45.24 36.18 0.041
rs9261394 16 30172541 INTERGENIC TRIM31 −6114 0.19 −0.04 0.21 45.97 37.33 0.039
rs2523990 13 30185208 INTRONIC TRIM31 0 0.10 −0.02 0.23 54.10 43.33 0.076
rs1345229 18 30290374 UPSTREAM TRIM26 1191 0.01 0.02 0.18 14.52 4.61 0.35
rs9357097 7 30393100 INTERGENIC TRIM39 −9500 0.00 −0.29 −0.08 14.17 32.89 0.734
rs1264583 19 30401462 UPSTREAM TRIM39 −1138 0.26 −0.03 0.11 8.73 4.67 0.138
rs1264581 5 30405484 SYNONYMOUS_CODING TRIM39 0 0.25 −0.03 0.11 9.68 5.33 0.0959
rs3095150 17 31040511 INTERGENIC DPCR1 10534 0.35 −0.06 0.18 39.52 33.33 0.008
rs6457699 3 33089625 UPSTREAM HLA-DOA 4258 0.06 0.00 0.25 52.42 40.13 0.045
rs9276994 8 33092233 INTERGENIC HLA-DOA 6866 0.08 −0.01 0.23 44.44 33.33 0.063
rs6933994 14 33095098 INTERGENIC HLA-DOA 9731 0.12 −0.02 0.23 55.56 45.27 0.074
rs9296068 9 33096673 INTERGENIC HLA-DOA 11306 0.40 −0.07 0.18 40.32 34.67 0.004

Footnotes

Presented in part at the American Transplant Congress, May 7, 2007, San Francisco, CA.

Conflict of interest: None. Study subjects informed.

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