Candidate genetic associations with acute GVHD (aGVHD) were evaluated with the use of genotyped and imputed singlenucleotide polymorphism data from genome-wide scans of 1298 allogeneic hematopoietic cell transplantation (HCT) donors and recipients. Of 40 previously reported candidate SNPs, 6 were successfully genotyped, and 10 were imputed and passed criteria for analysis. Patient and donor genotypes were assessed for association with grades IIb-IV and III-IV aGVHD, stratified by donor type, in univariate and multivariate allelic, recessive and dominant models. Use of imputed genotypes to replicate previous IL10 associations was validated. Similar to previous publications, the IL6 donor genotype for rs1800795 was associated with a 20%-50% increased risk for grade IIb-IV aGVHD after unrelated HCT in the allelic (adjusted P ‫؍‬ .011) and recessive (adjusted P ‫؍‬ .0013) models. The donor genotype was associated with a 60% increase in risk for grade III-IV aGVHD after related HCT (adjusted P ‫؍‬ .028). Other associations were found for IL2, CTLA4, HPSE, and MTHFR but were inconsistent with original publications. These results illustrate the advantages of using imputed single-nucleotide polymorphism data in genetic analyses and demonstrate the importance of validation in genetic association studies.

The outcome of allogeneic hematopoietic cell transplantation is influenced by donor/recipient genetic disparity at loci both inside and outside the MHC on chromosome 6p. Although disparity at loci within the MHC is the most important risk factor for the development of severe GVHD, disparity at loci outside the MHC that encode minor histocompatibility (H) antigens can elicit GVHD and GVL activity in donor/recipient pairs who are otherwise genetically identical across the MHC. Minor H antigens are created by sequence and structural variations within the genome. The enormous variation that characterizes the human genome suggests that the total number of minor H loci is probably large and ensures that all donor/ recipient pairs, despite selection for identity at the MHC, will be mismatched for many minor H antigens. In addition to mismatch at minor H loci, unrelated donor/ recipient pairs exhibit genetic disparity at numerous loci within the MHC, particularly HLA-DP, despite selection for identity at HLA-A, -B, -C, and -DRB1. Disparity at HLA-DP exists in 80% of unrelated pairs and clearly influences the outcome of unrelated hematopoietic cell transplantation; the magnitude of this effect probably exceeds that associated with disparity at any locus outside the MHC. (Blood. 2012;120(14):2796-2806) IntroductionGenetic nonidentity between donor and recipient is the key to the therapeutic efficacy of allogeneic hematopoietic cell transplantation (HCT) for malignant disease, but it is also the root of GVHD, its primary limitation. Pioneering studies in the late 1960s and early 1970s led to the critical discovery that donor/recipient genetic nonidentity at the MHC on chromosome 6p is the single most important risk factor for the development of severe GVHD. 1 The subsequent implementation of donor selection procedures according to donor/recipient MHC matching established with serologic assays and mixed lymphocyte culture revolutionized the nascent field of allogeneic marrow transplantation and enabled rapid growth during the subsequent decade in the annual number of transplantations performed, as well as considerable improvement in the likelihood of a successful transplantation outcome. Nonetheless, clinically significant GVHD still developed in a sizeable fraction of recipients of bone marrow grafts from sibling donors with whom they were genotypically identical throughout the MHC region on both copies of chromosome 6p. This observation suggested that genetic loci outside the MHC, encoding putative histocompatibility determinants that were collectively referred to as minor histocompatibility (H) antigens, could also influence a recipient's likelihood of developing GVHD or benefitting from GVL activity. 1,2 The intervening years have witnessed steady progress in elucidating the nature of minor H antigens and the genes that encode them and have seen the identification and characterization of other complex genetic loci that also influence histocompatibility in the allogeneic HCT setting. Here, we review the manner in which g...

Recent advances in genotyping technologies have enabled genomewide association studies (GWAS) of many complex traits including autoimmune disease, infectious disease, cancer and heart disease. To facilitate interpretations and establish biological basis, it could be advantageous to identify alleles of functional genes, beyond just single nucleotide polymorphisms (SNPs) within or nearby genes. Leslie et al (2008) have proposed an Identity-by-Decent method (IBD-based) for predicting human leukocyte antigen (HLA) alleles (multiallelic and highly polymorphic) with SNP data, and predictions have achieved a satisfactory accuracy on the order of 97%. Building upon their success, we introduce a complementary method for predicting highly polymorphic alleles using unphased SNP data as the training data set. Due to its generality and flexibility, the new method is readily applicable to large population studies. Applying it to HLA genes in a cohort of 630 healthy individuals as a training set, we constructed predictive models for HLA-A, B, C, DRB1 and DQB1. Then, we performed a validation study with another cohort of 630 healthy individuals, and the predictive models achieved predictive accuracies for HLA alleles defined at intermediate or high resolution ranging as high as (100%, 97%) for HLA-A, (98%, 96%) for B, (98%, 98%) for C, (97%, 96%) for DRB1 and (98%, 95%) for DQB1, respectively. These preliminary results suggest the feasibility of predicting other polymorphic genetic alleles, since HLA loci are almost certainly among most polymorphic genes.

Head and neck squamous cell carcinoma (HNSCC) is characterized by significant genomic instability that could lead to clonal diversity. Intratumor clonal heterogeneity has been proposed as a major attribute underlying tumor evolution, progression, and resistance to chemotherapy and radiation. Understanding genetic heterogeneity could lead to treatments specific to resistant and metastatic tumor cells. To characterize the degree of intratumor genetic heterogeneity within a single tumor, we performed whole-genome sequencing on three separate regions of an human papillomavirus (HPV)-positive oropharyngeal squamous cell carcinoma and two separate regions from one corresponding cervical lymph node metastasis. This approach achieved coverage of approximately 97.9% of the genome across all samples. In total, 5701 somatic point mutations (SPMs) and 4347 small somatic insertions and deletions (indels)were detected in at least one sample. Ninety-two percent of SPMs and 77% of indels were validated in a second set of samples adjacent to the discovery set. All five tumor samples shared 41% of SPMs, 57% of the 1805 genes with SPMs, and 34 of 55 cancer genes. The distribution of SPMs allowed phylogenetic reconstruction of this tumor's evolutionary pathway and showed that the metastatic samples arose as a late event. The degree of intratumor heterogeneity showed that a single biopsy may not represent the entire mutational landscape of HNSCC tumors. This approach may be used to further characterize intratumor heterogeneity in more patients, and their sample-to-sample variations could reveal the evolutionary process of cancer cells, facilitate our understanding of tumorigenesis, and enable the development of novel targeted therapies.

BackgroundNumerous immune-mediated diseases have been associated with the class I and II HLA genes located within the major histocompatibility complex (MHC) consisting of highly polymorphic alleles encoded by the HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1 loci. Genotyping for HLA alleles is complex and relatively expensive. Recent studies have demonstrated the feasibility of predicting HLA alleles, using MHC SNPs inside and outside of HLA that are typically included in SNP arrays and are commonly available in genome-wide association studies (GWAS). We have recently described a novel method that is complementary to the previous methods, for accurately predicting HLA alleles using unphased flanking SNPs genotypes. In this manuscript, we address several practical issues relevant to the application of this methodology.ResultsApplying this new methodology to three large independent study cohorts, we have evaluated the performance of the predictive models in ethnically diverse populations. Specifically, we have found that utilizing imputed in addition to genotyped SNPs generally yields comparable if not better performance in prediction accuracies. Our evaluation also supports the idea that predictive models trained on one population are transferable to other populations of the same ethnicity. Further, when the training set includes multi-ethnic populations, the resulting models are reliable and perform well for the same subpopulations across all HLA genes. In contrast, the predictive models built from single ethnic populations have superior performance within the same ethnic population, but are not likely to perform well in other ethnic populations.ConclusionsThe empirical explorations reported here provide further evidence in support of the application of this approach for predicting HLA alleles with GWAS-derived SNP data. Utilizing all available samples, we have built "state of the art" predictive models for HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1. The HLA allele predictive models, along with the program used to carry out the prediction, are available on our website.