Assessing the utilization of high-resolution 2-field HLA typing in solid organ transplantation.

HLA typing in solid organ transplantation (SOT) is necessary for determining HLA-matching status between donor-recipient pairs and assessing patients\u27 anti-HLA antibody profiles. Histocompatibility has traditionally been evaluated based on serologically defined HLA antigens. The evolution of HLA typing and antibody identification technologies, however, has revealed many limitations with using serologic equivalents for assessing compatibility in SOT. The significant improvements to HLA typing introduced by next-generation sequencing (NGS) require an assessment of the impact of this technology on SOT. We have assessed the role of high-resolution 2-field HLA typing (HR-2F) in SOT by retrospectively evaluating NGS-typed pre- and post-SOT cases. HR-2F typing was highly instructive or necessary in 41% (156/385) of the cases. Several pre- and posttransplant scenarios were identified as being better served by HR-2F typing. Five different categories are presented with specific case examples. The experience of another center (Temple University Hospital) is also included, whereby 21% of the cases required HR-2F typing by Sanger sequencing, as supported by other legacy methods, to properly address posttransplant anti-HLA antibody issues

Arginine at positions 13 or 70-71 in pocket 4 of HLA-DRB1 alleles is associated with susceptibility to tuberculoid leprosy

Evaluation of human histocompatibility leukocyte antigen (HLA) class II genes in 54 cases of tuberculoid leprosy (TL) and 44 controls has shown a positive association with HLA-DRB1 alleles that contain Arg13 or Arg70-Arg71. Among TL patients, 87% carry specific alleles of DRB1 Arg13 or Arg70-Arg71 as compared to 43% among controls (p = 5 x 10(-6)) conferring a relative risk of 8.8. Thus, susceptibility to TL involves three critical amino acid positions of the beta chain, the side chains of which, when modeled on the DR1 crystal structure, line a pocket (pocket 4) accommodating the side chain of a bound peptide. This study suggests that disease susceptibility may be determined by the independent contribution of polymorphic residues participating in the formation of a functional arrangement (i.e., pocket) within the binding cleft of an HLA molecule

Aneurysmal Lesions of Patients with Abdominal Aortic Aneurysm Contain Clonally Expanded T Cells

Abdominal aortic aneurysm (AAA) is a common disease with often life-threatening consequences. This vascular disorder is responsible for 1-2% of all deaths in men aged 65 years or older. Autoimmunity may be responsible for the pathogenesis of AAA. Although it is well documented that infiltrating T cells are essentially always present in AAA lesions, little is known about their role in the initiation and/or progression of the disease. To determine whether T cells infiltrating AAA lesions contain clonally expanded populations of T cells, we amplified beta-chain TCR transcripts by the nonpalindromic adaptor-PCR/Vbeta-specific PCR and/or Vbeta-specific PCR, followed by cloning and sequencing. We report in this article that aortic abdominal aneurysmal lesions from 8 of 10 patients with AAA contained oligoclonal populations of T cells. Multiple identical copies of beta-chain TCR transcripts were identified in these patients. These clonal expansions are statistically significant. These results demonstrate that alphabeta TCR(+) T lymphocytes infiltrating aneurysmal lesions of patients with AAA have undergone proliferation and clonal expansion in vivo at the site of the aneurysmal lesion, in response to unidentified self- or nonself Ags. This evidence supports the hypothesis that AAA is a specific Ag-driven T cell disease

Clonally Expanded Alpha-Chain T-Cell Receptor (TCR) Transcripts are Present in Aneurysmal Lesions of Patients With Abdominal Aortic Aneurysm (AAA)

Abdominal aortic aneurysm (AAA) is a life-threatening immunological disease responsible for 1 to 2% of all deaths in 65 year old or older individuals. Although mononuclear cell infiltrates have been demonstrated in AAA lesions and autoimmunity may be responsible for the initiation and account for the propagation of the disease, the information available about the pathogenesis of AAA is limited. To examine whether AAA lesions from patients with AAA contain clonally expanded α-chain TCR transcripts, we amplified by the non-palindromic adaptor-PCR (NPA-PCR)/Vα-specific PCR and/or the Vα-specific PCR these α-chain TCR transcripts. The amplified transcripts were cloned and sequenced. Substantial proportions of identical α-chain TCR transcripts were identified in AAA lesions of 4 of 5 patients, demonstrating that clonally expanded T cells are present in these AAA lesions. These results were statistically significant by the bimodal distribution. Three of 5 of these patients were typed by DNA-based HLA-typing and all three expressed DRB1 alleles containing the DRβGln70 amino acid residue that has been demonstrated to be associated with AAA. All three patients exhibited clonally expanded T cells in AAA lesions. Four of the 5 patients with AAA who exhibited clonal expansions of α-chain TCR transcripts, also exhibited clonal expansions of β-chain TCR transcripts in AAA lesions, as we have demonstrated previously (J Immunol 192:4897, 2014). αβ TCR-expressing T cells infiltrating AAA lesions contain T-cell clones which have undergone proliferation and clonal expansion in vivo in response to as yet unidentified specific antigens that may be self or nonself. These results provide additional evidence supporting the hypothesis that AAA is a specific antigen-driven T-cell autoimmune disease

From Disease Association to Risk Assessment: An Optimistic View from Genome-Wide Association Studies on Type 1 Diabetes

Genome-wide association studies (GWAS) have been fruitful in identifying disease susceptibility loci for common and complex diseases. A remaining question is whether we can quantify individual disease risk based on genotype data, in order to facilitate personalized prevention and treatment for complex diseases. Previous studies have typically failed to achieve satisfactory performance, primarily due to the use of only a limited number of confirmed susceptibility loci. Here we propose that sophisticated machine-learning approaches with a large ensemble of markers may improve the performance of disease risk assessment. We applied a Support Vector Machine (SVM) algorithm on a GWAS dataset generated on the Affymetrix genotyping platform for type 1 diabetes (T1D) and optimized a risk assessment model with hundreds of markers. We subsequently tested this model on an independent Illumina-genotyped dataset with imputed genotypes (1,008 cases and 1,000 controls), as well as a separate Affymetrix-genotyped dataset (1,529 cases and 1,458 controls), resulting in area under ROC curve (AUC) of ∼0.84 in both datasets. In contrast, poor performance was achieved when limited to dozens of known susceptibility loci in the SVM model or logistic regression model. Our study suggests that improved disease risk assessment can be achieved by using algorithms that take into account interactions between a large ensemble of markers. We are optimistic that genotype-based disease risk assessment may be feasible for diseases where a notable proportion of the risk has already been captured by SNP arrays

A Genome-Wide Meta-Analysis of Six Type 1 Diabetes Cohorts Identifies Multiple Associated Loci

Diabetes impacts approximately 200 million people worldwide, of whom approximately 10% are affected by type 1 diabetes (T1D). The application of genome-wide association studies (GWAS) has robustly revealed dozens of genetic contributors to the pathogenesis of T1D, with the most recent meta-analysis identifying in excess of 40 loci. To identify additional genetic loci for T1D susceptibility, we examined associations in the largest meta-analysis to date between the disease and ∼2.54 million SNPs in a combined cohort of 9,934 cases and 16,956 controls. Targeted follow-up of 53 SNPs in 1,120 affected trios uncovered three new loci associated with T1D that reached genome-wide significance. The most significantly associated SNP (rs539514, P = 5.66×10−11) resides in an intronic region of the LMO7 (LIM domain only 7) gene on 13q22. The second most significantly associated SNP (rs478222, P = 3.50×10−9) resides in an intronic region of the EFR3B (protein EFR3 homolog B) gene on 2p23; however, the region of linkage disequilibrium is approximately 800 kb and harbors additional multiple genes, including NCOA1, C2orf79, CENPO, ADCY3, DNAJC27, POMC, and DNMT3A. The third most significantly associated SNP (rs924043, P = 8.06×10−9) lies in an intergenic region on 6q27, where the region of association is approximately 900 kb and harbors multiple genes including WDR27, C6orf120, PHF10, TCTE3, C6orf208, LOC154449, DLL1, FAM120B, PSMB1, TBP, and PCD2. These latest associated regions add to the growing repertoire of gene networks predisposing to T1D

Microtubule Actin Crosslinking Factor 1 Regulates the Balbiani Body and Animal-Vegetal Polarity of the Zebrafish Oocyte

Although of fundamental importance in developmental biology, the genetic basis for the symmetry breaking events that polarize the vertebrate oocyte and egg are largely unknown. In vertebrates, the first morphological asymmetry in the oocyte is the Balbiani body, a highly conserved, transient structure found in vertebrates and invertebrates including Drosophila, Xenopus, human, and mouse. We report the identification of the zebrafish magellan (mgn) mutant, which exhibits a novel enlarged Balbiani body phenotype and a disruption of oocyte polarity. To determine the molecular identity of the mgn gene, we positionally cloned the gene, employing a novel DNA capture method to target region-specific genomic DNA of 600 kb for massively parallel sequencing. Using this technique, we were able to enrich for the genomic region linked to our mutation within one week and then identify the mutation in mgn using massively parallel sequencing. This is one of the first successful uses of genomic DNA enrichment combined with massively parallel sequencing to determine the molecular identity of a gene associated with a mutant phenotype. We anticipate that the combination of these technologies will have wide applicability for the efficient identification of mutant genes in all organisms. We identified the mutation in mgn as a deletion in the coding sequence of the zebrafish microtubule actin crosslinking factor 1 (macf1) gene. macf1 is a member of the highly conserved spectraplakin family of cytoskeletal linker proteins, which play diverse roles in polarized cells such as neurons, muscle cells, and epithelial cells. In mgn mutants, the oocyte nucleus is mislocalized; and the Balbiani body, localized mRNAs, and organelles are absent from the periphery of the oocyte, consistent with a function for macf1 in nuclear anchoring and cortical localization. These data provide the first evidence for a role for spectraplakins in polarization of the vertebrate oocyte and egg

Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Genome-wide association studies (GWASs) have identified hundreds of susceptibility genes, including shared associations across clinically distinct autoimmune diseases. We performed an inverse χ(2) meta-analysis across ten pediatric-age-of-onset autoimmune diseases (pAIDs) in a case-control study including more than 6,035 cases and 10,718 shared population-based controls. We identified 27 genome-wide significant loci associated with one or more pAIDs, mapping to in silico-replicated autoimmune-associated genes (including IL2RA) and new candidate loci with established immunoregulatory functions such as ADGRL2, TENM3, ANKRD30A, ADCY7 and CD40LG. The pAID-associated single-nucleotide polymorphisms (SNPs) were functionally enriched for deoxyribonuclease (DNase)-hypersensitivity sites, expression quantitative trait loci (eQTLs), microRNA (miRNA)-binding sites and coding variants. We also identified biologically correlated, pAID-associated candidate gene sets on the basis of immune cell expression profiling and found evidence of genetic sharing. Network and protein-interaction analyses demonstrated converging roles for the signaling pathways of type 1, 2 and 17 helper T cells (TH1, TH2 and TH17), JAK-STAT, interferon and interleukin in multiple autoimmune diseases