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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Gastroenterology. Author manuscript; available in PMC Oct 18, 2010.
Published in final edited form as:
PMCID: PMC2956436
NIHMSID: NIHMS69061
Genetic variants in Major Histocompatibility Complex-linked genes Associate with Pediatric Liver Transplant Rejection
Rakesh Sindhi, MD, Brandon W. Higgs, PhD, Daniel E. Weeks, PhD, Chethan AshokKumar, PhD, Ronald Jaffe, MB.BCh, Cecilia Kim, MS, Patrick Wilson, BS, Nydia Chien, MSN, Joseph Glessner, BS, Anjan Talukdar, MD, George Mazariegos, MD, M. Michael Barmada, PhD, Edward Frackleton, BA, Nancy Petro, BS, Andrew Eckert, MS, Hakon Hakonarson, MD, PhD, and Robert Ferrell, PhD
Hillman Center for Pediatric Transplantation, Children’s Hospital of Pittsburgh, Pittsburgh, Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, and the Department of Human Genetics and Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh.
Address correspondence to: Rakesh Sindhi, MD, FACS. Hillman Center for Pediatric Transplantation Children’s Hospital of Pittsburgh 3705 Fifth Avenue Pittsburgh, PA 15213. Phone/Fax: (412-692-6110/6116 ; Rakesh.Sindhi/at/chp.edu
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.
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).
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 (more ...)
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
Table 1
Etiology of liver disease leading to LTx in 80 children.
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
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, (more ...)
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 (more ...)
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
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 (more ...)
Table 4
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 (more ...)
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 (more ...)
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.
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 (Figures22 and and3).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 (more ...)
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.
SNPClosest
Gene
Distance to
gene
PositionSNP typeParental allele
frequency
comparison, p-
value
Lower
conf.
Interval
Higher
conf.
Interval
Rejector
Parents MAF
Non-Rejector
Parents MAF
Rejector MAFNon-Rejector
MAF
Rejector vs.
Non-Rejector
GC p value
taukAllele
frequency
in group k
Alleledistance to exon boundary
rs4713213OR5V1029446941INTRONIC0.0460.00270.246350.8%38.3%44.4%40.2%0.2850.774944.0%1−9
rs4598109OR5V1029452683INTRONIC0.0280.01460.254646.2%32.7%38.6%35.7%0.1440.703238.8%1−9
rs238883OR5V1029454205INTRONIC0.033−0.2547−0.011538.6%52.0%43.1%46.4%0.0971.537746.0%2−9
rs238882OR5V1029454342INTRONIC0.0120.03240.271148.5%33.3%41.7%35.7%0.2280.747340.7%1−9
rs238872OR5V1029459852INTRONIC0.0400.00660.25153.8%40.9%50.0%46.4%0.1800.731647.2%1−9
rs3094556OR5V1029461387INTRONIC0.0040.05710.296358.7%41.0%55.6%46.4%0.2900.779449.7%2−9
rs3094551OR5V1029462778INTRONIC0.010−0.2759−0.037936.2%51.9%40.0%46.4%0.3031.270844.4%1−9
rs3094550OR5V1029462788INTRONIC0.009−0.28−0.039936.6%52.6%40.0%47.6%0.3821.227845.2%2−9
rs2517817HLAH_HUMAN67129967496DOWNSTREAM0.032−0.1501−0.0094.6%12.5%2.9%13.8%0.2730.608810.0%1−9
rs7758512Q6ZU40_HUMAN030078568INTRONIC0.0340.00490.168615.9%7.2%14.7%12.2%0.3740.722312.1%2−9
rs9261129Q6ZU40_HUMAN030087558INTRONIC0.0420.00240.160514.4%6.3%14.3%11.9%0.4050.73511.8%2−9
rs9261277ZNRD1030139070INTRONIC0.0440.00140.1615.2%7.1%14.3%10.5%0.6310.839911.5%2−9
rs1264701TRIM31−431830174337DOWNSTREAM0.027−0.2051−0.014413.1%24.1%9.7%22.1%0.5140.81619.2%1−9
rs3734838TRIM31030188210NON_SYNONYMOUS_CODING0.0420.00050.141711.5%4.4%10.0%2.3%0.7191.16038.3%1−9
rs9261441TRIM311089130199737INTERGENIC0.0120.0190.177916.2%6.3%15.3%3.6%0.3721.367810.8%1−9
rs2022065TRIM100302294393PRIME_UTR0.0450.00210.22434.1%22.8%35.7%23.2%0.6381.126428.2%188
rs1345229TRIM26119130290374UPSTREAM0.0080.02260.171314.2%4.5%13.9%2.4%0.3411.44999.2%1−9
rs9357097TRIM39−950030393100INTERGENIC0.015−0.2417−0.027519.2%32.7%16.7%32.1%0.4800.809727.2%1−9
rs2516649GNL1−1681430604861INTERGENIC0.040−0.2333−0.006925.0%37.0%23.6%35.7%0.9940.995831.2%2−9
rs2844713GNL1030627237INTRONIC0.043−0.2307−0.005226.8%38.6%27.8%36.0%0.4761.197533.2%1−9
rs4248154NM_0010109094494131110595INTERGENIC0.017−0.1853−0.028.1%18.4%11.1%20.2%0.5220.794814.1%1−9
rs2523849C6orf15−5395231133030INTERGENIC0.0310.00790.196322.4%12.2%24.3%13.1%0.7341.112317.6%2−9
rs2428514C6orf15−5148731135495INTERGENIC0.0440.00150.180419.9%10.8%20.0%12.2%0.9100.962715.6%1−9
rs2517403C6orf15−1199431174988INTERGENIC0.0480.00130.235241.0%29.2%42.9%34.5%0.6690.902935.3%2−9
rs2844635C6orf15−352231183460DOWNSTREAM0.0400.00550.238441.0%28.9%42.9%35.0%0.6030.881635.1%2−9
rs9295957Q6H1K9_HUMAN1191731265572INTERGENIC0.046−0.1814−0.003910.6%19.9%10.6%17.1%0.4981.247815.6%1−9
rs77459061C07_HUMAN−3251831311987INTERGENIC0.037−0.1749−0.00768.8%18.0%7.4%18.6%0.9601.019414.2%1−9
rs20744881C07_HUMAN52431348410UPSTREAM0.038−0.156−0.00666.0%14.1%8.6%14.0%0.3861.431610.6%1−9
rs93667781C07_HUMAN2926631377152INTERGENIC0.039−0.2425−0.007133.1%45.6%34.7%41.7%0.4461.206140.3%1−9
rs406936NP_008860.4032041140INTRONIC0.048−0.1643−0.00318.1%16.5%5.6%15.0%0.7800.908512.5%1−9
rs454212NP_008860.4032042351INTRONIC0.028−0.1715−0.01236.4%15.5%6.1%12.2%0.9481.026611.3%1−114
rs387608STK19032049536INTRONIC0.048−0.1643−0.00318.1%16.5%5.6%15.0%0.7800.908512.5%1−9
rs2269429TNXB032137161NON_SYNONYMOUS_CODING0.044−0.1475−0.00445.2%12.8%5.6%9.8%0.4001.39399.3%1−9
rs204899TNXB032165605INTRONIC0.012−0.1571−0.02143.7%12.7%2.8%8.8%0.6571.19948.6%1−9
rs3115553C6orf10−1464832353805INTERGENIC0.0490.00040.202526.8%16.7%25.7%23.2%0.2980.736821.9%1−9
rs9268384C6orf10032444564NON_SYNONYMOUS_CODING0.045−0.2416−0.00433.8%46.1%35.7%43.9%0.9620.987340.3%25
rs4424066C6orf10209632462406UPSTREAM0.039−0.2411−0.007830.6%43.0%26.4%37.8%0.7981.064237.2%2−9
rs3817973BTNL2−63532469089DOWNSTREAM0.022−0.2518−0.020729.4%43.0%25.7%36.9%0.7071.095437.0%1−9
rs3793126BTNL2032479597INTRONIC0.044−0.2128−0.004817.7%28.6%18.1%25.6%0.7271.115623.8%2−9
rs86567HLA-DOA033084737INTRONIC0.037−0.2434−0.008931.6%44.2%31.9%48.8%0.2920.782537.8%2−9
rs6457699HLA-DOA425833089625UPSTREAM0.0310.01230.254753.7%40.4%52.9%30.5%0.0721.574245.9%1−9
rs6933994HLA-DOA973133095098INTERGENIC0.0420.00530.248558.1%45.4%55.7%36.3%0.1730.723649.2%1−9
rs6457702HLA-DOA1066033096027INTERGENIC0.009−0.2802−0.039933.3%49.3%37.5%52.5%0.7570.928442.4%1−9
rs9296068HLA-DOA1130633096673INTERGENIC0.0410.00530.244746.3%33.8%50.0%26.8%0.0181.851338.9%2−9
rs986521COL11A2033244123INTRONIC0.038−0.2075−0.007416.2%26.9%15.7%30.0%0.2430.713821.8%2−151
rs9277932COL11A2033249231INTRONIC0.028−0.25−0.015430.9%44.2%35.3%45.1%0.8131.061138.0%1−26
rs2855425COL11A2033252351INTRONIC0.040−0.221−0.006720.9%32.3%18.6%32.9%0.3360.772526.6%2−125
rs6531RXRB033271429SYNONYMOUS_CODING0.036−0.2241−0.008820.6%32.2%18.6%32.9%0.3420.77626.4%228
rs211474DAXX2982233428591INTERGENIC0.0450.00290.240146.3%34.2%43.1%32.1%0.9261.022639.5%1−9
rs211455KIFC1−3110233436496INTERGENIC0.0190.0230.257245.7%31.7%38.9%29.1%0.8240.948337.8%1−9
rs211452KIFC1−2863933438959INTERGENIC0.0200.02230.26352.2%38.0%43.1%34.9%0.6240.889743.7%2−9
rs211457KIFC1033473618INTRONIC0.025−0.1556−0.01225.1%13.5%5.6%14.6%0.5800.78439.5%1−166
rs3116713PHF1033490266NON_SYNONYMOUS_CODING0.025−0.1445−0.01163.7%11.5%4.2%12.2%0.5370.75157.9%233
rs211456ZBTB9033497359INTRONIC0.0410.0060.248154.5%41.8%47.2%39.5%0.7180.918146.7%1−9
rs396746NP_997380.1033665023INTRONIC0.032−0.1845−0.010110.1%19.9%13.9%20.7%0.7091.129315.1%1−9
rs169737ITPR3−1276733684555INTERGENIC0.024−0.2185−0.016516.2%27.9%21.4%25.6%0.2691.365122.0%1−9
rs12529825ITPR3033725381INTRONIC0.012−0.1571−0.02143.7%12.7%5.6%14.6%0.6830.83958.5%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 frequencyRejector vs Non-Rejectors
Chi-sq
Rejectors vs normal controls
Chi-sq
Rejectors vs Normal Controls
Chi-sq
SNPClosest GeneDistance to
gene
SNP typePositionRejectorsNon-RejectorsNormal ControlSNP rankp-valueodds ratiop-valueodds ratiop-valueodds ratio
rs9296068HLA-DOA11306INTERGENIC3309667351.40%26.80%36.70%10.0022.8880.01521.8220.0740.6311
rs6457699HLA-DOA4258UPSTREAM3308962554.30%31.70%46.70%20.0052.5580.2261.3530.0090.5288
rs602875HLA-DRB116048INTERGENIC3268160742.90%21.90%23.80%30.0062.6670.00042.4010.7070.9003
rs1264583HLAH_HUMAN10138INTERGENIC3040146214.30%2.40%5%40.0076.6670.0013.1670.2990.475
rs3094097Q6ZU40_HUMAN0INTRONIC3074185414.30%2.40%9.70%50.0076.6670.2271.5430.0280.2314
rs1345229TRIM261191UPSTREAM3029037414.30%2.40%11.90%60.0076.6670.5531.2370.0090.1855
rs3134879TRIM39−1138UPSTREAM3012388426.60%48.70%41.10%70.0070.38070.0230.5190.1921.363
rs2517904DHX160INTRONIC299769632.90%15.80%7.50%80.0070.15610.1470.36180.0092.317
rs9366752C6orf1203PRIME_UTR3013265634.30%15.80%20%90.0082.7690.0052.0870.3680.7536
rs1264581TRIM390SYNONYMOUS_CODING3040548416.20%3.70%5.30%100.0095.0820.00033.4550.5240.6799
rs9276994HLA-DOA6866INTERGENIC3309223348.60%28.10%37.70%110.0092.4230.0751.5570.0830.6428
rs9277015HLA-DOA15877INTERGENIC3310124444.30%24.40%37%120.0092.4640.2271.3530.0230.5493
rs6933994TRIM3110891INTERGENIC3309509857.10%36.30%46%130.012.3450.6140.88080.0022.065
rs9261441HLA-DOA9731INTERGENIC3019973715.70%3.70%13.60%140.014.910.6231.1840.010.2412
rs2394255HLA-A9079INTERGENIC3005780058.60%37.80%48.60%150.0122.3260.111.4940.0620.6423
rs532098HCG93625DOWNSTREAM3268603030.90%51.20%45.60%160.0120.42550.0190.53270.3321.252
rs9468829NP_003888.236906INTERGENIC3085721221.40%7.30%12.10%170.0123.4550.0241.9940.2040.5773
rs16896742HLA-DRB120471INTERGENIC3003071946.90%26.80%34.20%180.0122.4060.0421.6950.1770.7043
rs2516684RPP2148325INTERGENIC3047097417.10%4.90%13.10%190.0144.0340.3451.3690.0310.3394
rs12206499HCG9−5765INTERGENIC3004510637.10%19.50%25.70%200.0152.4380.03771.7090.2190.7011
rs6904029HCG9−809UPSTREAM3005104637.10%19.50%25.70%210.0152.4380.0391.7040.2150.699
rs3823355HCG90NON_SYNONYMOUS_CODING3005006237.10%19.50%25.90%220.0152.4380.0411.6930.2070.6945
rs6933546HLAH_HUMAN671DOWNSTREAM3310399242.90%24.40%36.60%230.0162.3250.3011.2980.0270.5582
rs2517817HLA-DOA18625INTERGENIC299674962.90%14.50%7.90%240.0160.17910.1380.35480.0481.982
rs3869070Q6ZU40_HUMAN0INTRONIC3013184755.90%36.60%44.70%250.0182.1960.0771.5640.1560.7123
rs2647044HLA-G23348INTERGENIC3277588822.70%8.70%9.90%260.0193.0670.0012.6550.7260.8655
rs2975033BAT20INTRONIC2993024035.70%18.70%25.60%270.0192.4070.0661.6120.1760.6698
rs9267522BAT20NON_SYNONYMOUS_CODING3171174927.10%12.20%13%280.0192.6820.0012.4930.8360.9295
rs3117583BAT30INTRONIC3172755527.10%12.20%13%290.0192.6820.0012.4930.8360.9295
rs3130618BAT40NON_SYNONYMOUS_CODING3174011327.10%12.20%13%300.0192.6820.0012.4930.8360.9295
rs3115663HB25_human21592INTERGENIC3170982227.10%12.20%13.10%310.0192.6820.0012.4660.8120.9193
rs4711207Q6ZU40_HUMAN0INTRONIC3011373334.40%17.50%22.80%320.022.4690.0361.7760.280.7193
rs2040450RPP2119669INTERGENIC3044231816.20%4.90%12.70%330.0223.7630.421.3210.0370.3509
rs4259245ITPR30INTRONIC3373219927.10%45.10%35.70%340.0220.45310.1480.66950.0931.478
rs2107202TRIM400INTRONIC302137222036.60%25.90%350.0250.43330.2790.71620.0371.653
rs915664DDR1−54188INTRONIC3090259635.70%19.50%30.60%360.0252.2920.3771.2590.0360.5492
rs3129763HA25_HUMAN−14209INTERGENIC3269890338.60%21.90%22.90%370.0252.2330.0032.110.840.9452
rs3893464HCG9−7642INTERGENIC3004322937.10%54.90%50.60%380.0290.48590.030.57630.4630.843
rs9261301RNF390INTRONIC3014953852.90%35.40%44.40%390.032.0490.1711.4050.1170.6859
rs9267546LY6G6D−1245UPSTREAM3178141517.60%6.20%9.30%400.033.2140.0262.1020.3710.6541
rs387608HCG90INTRONIC320495365.70%17.10%15%410.0310.29440.0330.34340.6181.167
rs406936TRIM39−9500INTERGENIC320411405.70%17.10%14.70%420.0310.29440.0370.35030.5741.19
rs9357097NP_008860.40INTRONIC3039310017.10%32.50%30.90%430.0310.42970.01550.46150.7761.074
rs2394250STK190INTRONIC3005163551.40%34.10%41.60%440.0312.0420.1111.4850.1890.7272
rs2257914TRIM4005PRIME_UTR3022854210%23.20%17.50%450.0320.36840.1080.52380.2031.422
rs2021723TRIM1003PRIME_UTR3021190210%23.20%17.30%460.0320.36840.1190.5330.1821.447
rs2844776TRIM260INTRONIC3027980615.70%30.50%20.10%470.0330.42510.3740.740.0281.741
rs2395175HLA-DRA−2621UPSTREAM325130044.30%14.60%14.20%480.0330.26120.020.27140.9071.039
rs2187668HA25_HUMAN0INTRONIC3271386220.60%8.50%8.60%490.0342.7780.00132.7470.9780.9888
rs9267911TRIM310INTRONIC3231308858.60%41.50%47.30%500.0351.9960.0691.5780.3170.7908
rs2523990NOTCH413266INTERGENIC3018520858.60%41.50%47.40%510.0351.9960.07221.570.3070.7868
rs12212092HCG9−9631INTERGENIC3023642112.90%3.70%6.30%520.0363.8850.0372.190.3380.5635
rs6457109TRIM100NON_SYNONYMOUS_CODING3004124018.60%7.30%9.90%530.0362.8890.02332.0820.4550.7205
rs9277027HLAH_HUMAN−5770INTERGENIC3310621630%15.80%30.40%540.0372.2750.9480.98240.0060.4319
rs2523809HLA-DOA20849INTERGENIC299575988.60%20.70%11.80%550.0370.35850.4240.70410.0191.964
rs375912NR_002139.1−14455INTERGENIC3312470632.90%18.30%36.50%560.0392.1860.5430.85140.0010.3895
rs2517930HLA-DPA1−15618INTERGENIC2985305437.10%21.90%30.80%570.0392.1010.2711.3290.0970.6325
rs4713411NM_00101090929501INTERGENIC3109515528.10%44.90%43.40%580.040.48070.0180.51140.7961.064
rs1264567TRIM40−11178INTERGENIC3047407920%8.50%18.90%590.0412.6790.8181.0750.020.4011
rs213213RPP2151430INTERGENIC3329170821.40%36.60%26.70%600.0410.47270.3320.74680.0581.58
rs1419675RING13232DOWNSTREAM3020068621.40%36.60%25.90%610.0410.47270.4130.78130.0371.653
rs6910071C6orf100INTRONIC323908327.14%18.30%19.10%620.0430.34360.01260.32530.8550.9467
rs86567HLA-DOA0INTRONIC3308473731.40%47.60%38.10%630.0430.50530.2670.74390.0951.472
rs3734838RNF3912015INTERGENIC3018821010.30%2.40%8.50%640.0444.590.6221.2290.0520.2676
rs6909253TRIM31−6114INTERGENIC3016362252.90%36.60%37.30%650.0441.9430.011.8890.9060.9719
rs9261394TRIM310NON_SYNONYMOUS_CODING3017254152.90%36.60%38%660.0441.9430.0151.8290.8010.9413
rs1003581GABBR10INTRONIC296481839.10%21.20%19.90%670.0450.37060.0320.40190.7781.085
rs594223C6orf1250INTRONIC3377594321.40%9.80%17.90%680.0452.5230.461.2530.0630.4967
rs9468692RNF391571UPSTREAM3022786914.30%4.90%7.10%690.0463.250.0322.1730.4450.6685
rs1150735TRIM1003PRIME_UTR3015317827.10%42.70%40%700.0460.50030.0340.55880.6371.117
rs1052486BAT30NON_SYNONYMOUS_CODING3171866540%56.40%43.70%710.0460.51520.0081.9340.9870.9961
rs1264701TRIM31−4318DOWNSTREAM3017433710%21.90%22.40%720.0480.39510.0150.38420.9210.9726
rs1077393BAT30INTRONIC3171850840%56.10%44.10%730.0480.52170.011.8990.9690.991
rs986521COL11A20INTRONIC3324412315.70%29.30%20.10%740.0480.45060.3740.740.0531.642
rs9262138DHX160NON_SYNONYMOUS_CODING3073584610%2.40%5.90%750.0494.4440.171.780.1960.4005
rs9267665ZBTB121087UPSTREAM3197883510%2.40%4.30%760.0494.4440.0292.5030.430.5632
rs77459061C07_HUMAN−32518INTERGENIC313119877.35%18.30%13%770.050.35450.1770.53110.1821.498
Appendix 3
Appendix 3
Summary statistics for differentially expressed exons between Rejectors and Non-rejectors
Exon IDTranscript IDExon fold changeExon p-valueTranscript fold changeTranscript p-valueTranscript/SNP nameExon start/SNP locationExon stop
295031229503071.0630.555−1.0830.326HLA-DOA33,081,98533,082,504
295031329503071.1220.397−1.0830.326HLA-DOA33,082,83833,082,870
295031429503071.0690.372−1.0830.326HLA-DOA33,082,93933,082,970
29503172950307−1.0650.638−1.0830.326HLA-DOA33,083,11133,083,291
29503222950307−1.0600.395−1.0830.326HLA-DOA33,083,77733,083,802
29503232950307−1.0110.905−1.0830.326HLA-DOA33,083,81833,083,847
295032429503071.0170.84−1.0830.326HLA-DOA33,083,85733,083,987
295032529503071.1270.383−1.0830.326HLA-DOA33,084,06833,084,099
29503262950307−1.0480.748−1.0830.326HLA-DOA33,085,22233,085,260
29503272950307−1.5320.0153−1.0830.326HLA-DOA33,085,30533,085,362
untranslatedrs645769933,089,625
untranslatedrs927699433,092,233
untranslatedrs693399433,095,098
untranslatedrs929606833,096,673
untranslatedrs927701533,101,244
295033129503291.1290.545−1.1660.419HLA-DPA133,140,78833,140,818
29503322950329−1.1610.517−1.1660.419HLA-DPA133,140,83633,140,861
29503332950329−1.2460.204−1.1660.419HLA-DPA133,140,92533,141,014
29503382950329−1.3020.0128−1.1660.419HLA-DPA133,144,43733,144,544
29503402950329−1.1140.31−1.1660.419HLA-DPA133,144,77433,144,804
29503412950329−1.0140.875−1.1660.419HLA-DPA133,144,84433,144,876
295034229503291.0300.792−1.1660.419HLA-DPA133,144,92933,144,963
29503432950329−1.1140.479−1.1660.419HLA-DPA133,144,96933,144,999
295034529503291.0570.565−1.1660.419HLA-DPA133,145,41333,145,477
295034629503291.3460.113−1.1660.419HLA-DPA133,145,57333,145,641
295034829503291.0350.723−1.1660.419HLA-DPA133,149,23833,149,262
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
MAFMAFMAFREJ vs. NONREJREJ vs. CONTROLSNONREJ vs. CONTROLS
SNPrankphysical positiontypeClosest geneDistance to geneRejectorsControlsNon-RejectorsP-VALUEORL95U95Chi-Sq P-valueORL95U95Chi-Sq P-valueORL95U95
rs2975033429930240INTERGENICHLA-G2334836.3625.6214.860.00343.2731.4517.3820.057271.6590.98012.8070.040070.50680.2620.9804
rs122064991030045106INTERGENICHCG9−576536.3625.6916.220.00652.9521.3326.5440.059141.6530.97652.7970.071330.55980.29571.06
rs38233551130050062UPSTREAMHCG9−80936.3625.8716.220.00652.9521.3326.5440.064051.6370.96752.770.066590.55450.29291.049
rs69040291230051046NON_SYNONYMOUS_CODINGHCG9036.3625.7516.220.00652.9521.3326.5440.060591.6480.97382.7880.069760.55810.29481.056
rs2394255230057800DOWNSTREAMHCG9362559.0948.6233.780.00272.8311.4235.6310.10211.5260.91662.5420.014470.53910.32660.8901
rs3869070630131847INTRONICQ6ZU40_HUMAN056.2544.7532.430.00492.6791.3395.3580.07551.5870.95022.6520.040980.59260.35720.9832
rs93667521301326563PRIME_UTRC6orf12033.332012.160.00263.6111.5218.5750.0106121.1653.4330.10240.55380.271.136
rs69092531530163622INTERGENICRNF391201554.5537.2532.430.00832.51.2584.9680.0055292.0211.223.350.41110.80860.48681.343
rs92613941630172541INTERGENICTRIM31−611454.553832.430.00832.51.2584.9680.0081551.9581.1813.2450.3440.78320.47161.301
rs25239901330185208INTRONICTRIM31060.6147.3837.840.00712.5271.2784.9970.03871.7091.0232.8540.11560.67620.41431.104
rs13452291830290374UPSTREAMTRIM26119115.1511.872.7030.00866.4291.35430.530.43321.3250.6542.6850.016250.20610.049760.8539
rs9357097730393100INTERGENICTRIM39−950015.1530.9536.110.00510.31590.13820.72240.0069620.39840.19990.79370.36631.2610.76192.087
rs12645831930401462UPSTREAMTRIM39−113812.1251.3510.009510.071.22482.820.015092.6211.1725.860.15560.26030.035271.921
rs1264581530405484SYNONYMOUS_CODINGTRIM39014.065.291.3510.004111.951.4797.10.0042992.931.3566.3290.13540.24530.033271.808
rs30951501731040511INTERGENICDPCR11053445.4542.824.320.00862.5931.2635.320.67591.1140.67231.8440.0020130.42950.2480.744
rs6457699333089625UPSTREAMHLA-DOA425853.1246.7528.380.00312.861.4145.7860.32561.2910.7752.150.0023810.45130.26720.7623
rs9276994833092233INTERGENICHLA-DOA686646.8837.7524.320.00552.7451.3325.6580.14871.4550.87262.4260.021810.530.30580.9186
rs69339941433095098INTERGENICHLA-DOA973156.2545.9933.330.00722.5711.2825.1560.72930.91340.54681.5260.00076772.3491.4113.909
rs9296068933096673INTERGENICHLA-DOA1130646.8836.7524.320.00552.7451.3325.6580.10741.5190.91052.5330.03280.55320.31910.959
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 testMAF-ParentsMAF-ParentsGC test
SNPrankphysical positiontypeClosest geneDistance to geneChi-Sq p-valueLCIUCIRejectorsNon-RejectorsP-VALUE
rs2975033429930240INTERGENICHLA-G233480.08−0.010.2130.9521.050.075
rs122064991030045106INTERGENICHCG9−57650.22−0.040.1931.7524.340.0126
rs38233551130050062UPSTREAMHCG9−8090.19−0.040.1932.0324.340.026
rs69040291230051046NON_SYNONYMOUS_CODINGHCG900.22−0.040.1931.7524.340.026
rs2394255230057800DOWNSTREAMHCG936250.42−0.070.1847.6242.110.004
rs3869070630131847INTRONICQ6ZU40_HUMAN00.46−0.070.1845.1640.000.014
rs93667521301326563PRIME_UTRC6orf1200.42−0.060.1626.9822.080.006
rs69092531530163622INTERGENICRNF39120150.16−0.030.2145.2436.180.041
rs92613941630172541INTERGENICTRIM31−61140.19−0.040.2145.9737.330.039
rs25239901330185208INTRONICTRIM3100.10−0.020.2354.1043.330.076
rs13452291830290374UPSTREAMTRIM2611910.010.020.1814.524.610.35
rs9357097730393100INTERGENICTRIM39−95000.00−0.29−0.0814.1732.890.734
rs12645831930401462UPSTREAMTRIM39−11380.26−0.030.118.734.670.138
rs1264581530405484SYNONYMOUS_CODINGTRIM3900.25−0.030.119.685.330.0959
rs30951501731040511INTERGENICDPCR1105340.35−0.060.1839.5233.330.008
rs6457699333089625UPSTREAMHLA-DOA42580.060.000.2552.4240.130.045
rs9276994833092233INTERGENICHLA-DOA68660.08−0.010.2344.4433.330.063
rs69339941433095098INTERGENICHLA-DOA97310.12−0.020.2355.5645.270.074
rs9296068933096673INTERGENICHLA-DOA113060.40−0.070.1840.3234.670.004
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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