Interaction between maternal killer immunoglobulin-like receptors and offspring HLAs and susceptibility of childhood ALL.

Acute lymphoblastic leukemia (ALL) in children is associated with a distinct neonatal cytokine profile. The basis of this neonatal immune phenotype is unknown but potentially related to maternal-fetal immune receptor interactions. We conducted a case-control study of 226 case child-mother pairs and 404 control child-mother pairs to evaluate the role of interaction between HLA genotypes in the offspring and maternal killer immunoglobulin-like receptor (KIR) genotypes in the etiology of childhood ALL, while considering potential mediation by neonatal cytokines and the immune-modulating enzyme arginase-II (ARG-II). We observed different associations between offspring HLA-maternal KIR activating profiles and the risk of ALL in different predicted genetic ancestry groups. For instance, in Latino subjects who experience the highest risk of childhood leukemia, activating profiles were significantly associated with a lower risk of childhood ALL (odds ratio [OR] = 0.59; 95% confidence interval [CI], 0.49-0.71) and a higher level of ARG-II at birth (coefficient = 0.13; 95% CI, 0.04-0.22). HLA-KIR activating profiles were also associated with a lower risk of ALL in non-Latino Asians (OR = 0.63; 95% CI, 0.38-1.01), although they had a lower tumor necrosis factor-α level (coefficient = -0.27; 95% CI, -0.49 to -0.06). Among non-Latino White subjects, no significant association was observed between offspring HLA-maternal KIR interaction and ALL risk or cytokine levels. The current study reports the association between offspring HLA-maternal KIR interaction and the development of childhood ALL with variation by predicted genetic ancestry. We also observed some associations between activating profiles and immune factors related to cytokine control; however, cytokines did not demonstrate causal mediation of the activating profiles on ALL risk.

Breastmilk, Stool, and Meconium: Bacterial Communities in South Africa.

Human milk optimizes gut microbial richness and diversity, and is critical for proper immune development. Research has shown differing microbial composition based on geographic location, providing evidence that diverse biospecimen data is needed when studying human bacterial communities. Yet, limited research describes human milk and infant gut microbial communities in Africa. Our study uses breastmilk, stool, and meconium samples from a South African birth cohort to describe the microbial diversity, identify distinct taxonomic units, and determine correlations between bacterial abundance in breastmilk and stool samples. Mother-infant dyads (N = 20) were identified from a longitudinal birth cohort in the Vhembe district of Limpopo Province, South Africa. Breastmilk, meconium, and stool samples were analyzed using 16S ribosomal RNA sequencing of the V4-V5 gene region using the MiSeq platform for identification and relative quantification of bacterial taxa. A non-metric multidimensional scaling using Bray-Curtis distances of sample Z-scores showed that meconium, stool, and breastmilk microbial communities are distinct with varying genus. Breastmilk was mostly comprised of Streptococcus, Staphylococcus, Veillonella, and Corynebacterium. Stool samples showed the highest levels of Bifidobacterium, Faecalibacterium, Bacteroides, and Streptococcus. Alpha diversity measures found that stool samples have the highest Shannon index score compared to breastmilk and meconium. The abundance of Bifidobacterium (r = 0.57), Blautia (r = 0.59), and Haemophilus (r = 0.69) was correlated (p < 0.1) between breastmilk and stool samples. Despite the importance of breastmilk in seeding the infant gut microbiome, we found evidence of distinct bacterial communities between breastmilk and stool samples from South African mother-infant dyads.

Bridging ImmunoGenomic Data Analysis Workflow Gaps (BIGDAWG): An integrated case-control analysis pipeline.

Bridging ImmunoGenomic Data-Analysis Workflow Gaps (BIGDAWG) is an integrated data-analysis pipeline designed for the standardized analysis of highly-polymorphic genetic data, specifically for the HLA and KIR genetic systems. Most modern genetic analysis programs are designed for the analysis of single nucleotide polymorphisms, but the highly polymorphic nature of HLA and KIR data require specialized methods of data analysis. BIGDAWG performs case-control data analyses of highly polymorphic genotype data characteristic of the HLA and KIR loci. BIGDAWG performs tests for Hardy-Weinberg equilibrium, calculates allele frequencies and bins low-frequency alleles for k×2 and 2×2 chi-squared tests, and calculates odds ratios, confidence intervals and p-values for each allele. When multi-locus genotype data are available, BIGDAWG estimates user-specified haplotypes and performs the same binning and statistical calculations for each haplotype. For the HLA loci, BIGDAWG performs the same analyses at the individual amino-acid level. Finally, BIGDAWG generates figures and tables for each of these comparisons. BIGDAWG obviates the error-prone reformatting needed to traffic data between multiple programs, and streamlines and standardizes the data-analysis process for case-control studies of highly polymorphic data. BIGDAWG has been implemented as the bigdawg R package and as a free web application at bigdawg.immunogenomics.org.

Proceedings: human leukocyte antigen haplo-homozygous induced pluripotent stem cell haplobank modeled after the california population: evaluating matching in a multiethnic and admixed population.

The development of a California-based induced pluripotent stem cell (iPSC) bank based on human leukocyte antigen (HLA) haplotype matching represents a significant challenge and a valuable opportunity for the advancement of regenerative medicine. However, previously published models of iPSC banks have neither addressed the admixed nature of populations like that of California nor evaluated the benefit to the population as a whole. We developed a new model for evaluating an iPSC haplobank based on demographic and immunogenetic characteristics reflecting California. The model evaluates haplolines or cell lines from donors homozygous for a single HLA-A, HLA-B, HLA-DRB1 haplotype. We generated estimates of the percentage of the population matched under various combinations of haplolines derived from six ancestries (black/African American, American Indian, Asian/Pacific Islander, Hispanic, and white/not Hispanic) and data available from the U.S. Census Bureau, the California Institute for Regenerative Medicine, and the National Marrow Donor Program. The model included both cis (haplotype-level) and trans (genotype-level) matching between a modeled iPSC haplobank and the recipient population following resampling simulations. We showed that serving a majority (>50%) of a simulated California population through cis matching would require the creation, redundant storage, and maintenance of almost 207 different haplolines representing the top 60 most frequent haplotypes from each ancestry group. Allowances for trans matching reduced the haplobank to fewer than 141 haplolines found among the top 40 most frequent haplotypes. Finally, we showed that a model optimized, custom haplobank was able to serve a majority of the California population with fewer than 80 haplolines.

High-resolution HLA-A, HLA-B, and HLA-DRB1 haplotype frequencies from the French Bone Marrow Donor Registry.

We have estimated human leukocyte antigen (HLA) haplotype frequencies using the maximum likelihood mode, which accommodates typing ambiguities. The results of the frequency distribution of the 7015 haplotypes obtained are presented here. These include a total of 114 HLA-A, 185 HLA-B, and 76 HLA-DRB1 unique alleles at each locus. Across all populations, although the most common individual HLA alleles were HLA-A(∗)02:01 (29.0%), HLA-B(∗)07:02 (11.4%), and HLA-DRB1(∗)07:01 (15.9%), the most frequent haplotype was found to be HLA-A(∗)01:01∼B(∗)08:01∼DRB1(∗)03:01.

Comparison of high-resolution human leukocyte antigen haplotype frequencies in different ethnic groups: Consequences of sampling fluctuation and haplotype frequency distribution tail truncation.

High-resolution haplotype frequency estimations and descriptive metrics are becoming increasingly popular for accurately describing human leukocyte antigen diversity. In this study, we compared sample sets of publically available haplotype frequencies from different populations to characterize the consequences of unequal sample size on haplotype frequency estimation. We found that for low samples sizes (a few thousand), haplotype frequencies were overestimated, affecting all descriptive metrics of the underlying distribution, such as most frequent haplotype, the number of haplotypes, and the mean/median frequency. This overestimation was a result of random sample fluctuation and truncation of the tail end of the frequency distribution that comprises the least frequent haplotypes. Finally, we simulated balanced datasets through resampling and contrasted the disparities of descriptive metrics among equal and unequal datasets. This simulation resulted in the global description of the most frequent human leukocyte antigen haplotypes worldwide.

HLA class II genotypes are not associated with age related macular degeneration in a case-control, population-based study.

Multiple lines of evidence support an immunologic basis and genetic disposition for the development of age-related macular degeneration (AMD). Comprehensive human leukocyte antigens (HLA) class II typing at four loci (DRB1, DQA1, DQB1, and DPB1) was assessed using next generation sequencing methods and tested for association with age-related macular degeneration (AMD) in a case-control study of 456 AMD cases and 499 controls from the population-based Study of Osteoporotic Fractures (SOF) cohort. No statistically significant associations were identified for any of the class II loci and a previously identified association between DRB1*13:01 was not replicated in this dataset. These results reported here suggest that common HLA class II genetic variation does not contribute to AMD disease risk.

Interferon-beta affects mitochondrial activity in CD4+ lymphocytes: Implications for mechanism of action in multiple sclerosis.

BACKGROUND: Whereas cellular immune function depends on energy supply and mitochondrial function, little is known on the impact of immunotherapies on cellular energy metabolism. OBJECTIVE: The objective of this paper is to assess the effects of interferon-beta (IFN-ß) on mitochondrial function of CD4(+) T cells. METHODS: Intracellular adenosine triphosphate (iATP) in phytohemagglutinin (PHA)-stimulated CD4(+) cells of multiple sclerosis (MS) patients treated with IFN-ß and controls were analyzed in a luciferase-based assay. Mitochondrial-transmembrane potential (ΔΨm) in IFN-ß-treated peripheral blood mononuclear cells (PBMCs) was investigated by flow cytometry. Expression of genes involved in mitochondrial oxidative phosphorylation (OXPHOS) in CD4(+) cells of IFN-ß-treated individuals and correlations between genetic variants in the key metabolism regulator PGC-1α and IFN-ß response in MS were analyzed. RESULTS: IFN-ß-treated MS patients exhibited a dose-dependent reduction of iATP levels in CD4(+) T cells compared to controls (p < 0.001). Mitochondrial effects were reflected by depolarization of ΔΨm. Expression data revealed changes in the transcription of OXPHOS-genes. iATP levels in IFN-ß-responders were reduced compared to non-responders (p < 0.05), and the major T allele of the SNP rs7665116 of PGC-1α correlated with iATP-levels. CONCLUSION: Reduced iATP-synthesis ex vivo and differential expression of OXPHOS-genes in CD4(+) T cells point to unknown IFN-ß effects on mitochondrial energy metabolism, adding to potential pleiotropic mechanisms of action.

DNA storage under high temperature conditions does not affect performance in human leukocyte antigen genotyping via next-generation sequencing (DNA integrity maintained in extreme conditions).

BACKGROUND: Stable dry-state storage of DNA is desirable to minimize required storage space and to reduce electrical and shipping costs. DNA purified from various commercially available dry-state stabilization matrices has been used successfully in downstream molecular applications (e.g., quantitative polymerase chain reaction [qPCR], microarray, and sequence-based genotyping). However, standard DNA storage conditions still include freezing of DNA eluted in aqueous buffers or nuclease-free water. Broad implementation of dry-state, long-term DNA storage requires enhancement of such dry-state DNA stabilization products to control for temperature fluctuations at specimen collection, transit, and storage. This study tested the integrity of genomic DNA subjected to long-term storage on GenTegra(™) DNA stabilization matrices (GenTegra LLC, Pleasanton, CA) at extreme conditions, as defined by a 4-year storage period at ambient temperature with an initial incubation for 7 months at 37°C, 56°C, or ambient temperature. Subsequently, purified DNA performance and integrity were measured by qPCR and next-generation sequencing (NGS)-based human leokocyte antigen (HLA) genotyping. RESULTS: High molecular weight genomic DNA samples were recovered from the GenTegra product matrix and exhibited integrity comparable to a highly characterized commercial standard under assessment by qPCR. Samples were genotyped for classical HLA loci using next generation sequencing-based methodolgy on the Roche 454 GS Junior instrument. Amplification efficiency, sequence coverage, and sequence quality were all comparable with those produced from a cell line DNA sequenced as a control. No significant differences were observed in the mean, median, or mode quality scores between samples and controls (p≥0.4). CONCLUSIONS: Next generation HLA genotyping was chosen to test the integrity of GenTegra-treated genomic DNA due to the requirment for long sequence reads to genotype the highly polymorphic classical HLA genes. Experimental results demonstrate the efficacy of the GenTegra product as a suitable genomic DNA preservation tool for collection and long-term biobanking of DNA at fluctuating and high temperatures.

Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data.

BACKGROUND: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. METHODS: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. RESULTS: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). CONCLUSIONS: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics.

Multiple sclerosis pharmacogenomics: maximizing efficacy of therapy.

Genetic polymorphisms and variable expression of drug receptors, metabolizing enzymes, and transporters have been linked to interindividual differences in efficacy and toxicity of many Food and Drug Administration-approved therapeutic agents. In multiple sclerosis, the combination of heterogeneity of disease pathology and significant variation in clinical response to disease-modifying agents necessitates the definition of biomarkers that can a priori predict therapeutic response and define appropriate therapeutic regimens. Pharmacogenomic studies will directly address the question of heterogeneity by analysis of the correlation between different genomic variants and clinical responses to therapy. These studies will include longitudinal designs, maximize clinical response variables, include whole-genome technologies, use large patient cohorts, and require the development of novel mathematical algorithms designed to integrate the wealth of disparate data to identify modest genetic effects and interactions.

Abrogation of T cell quiescence characterizes patients at high risk for multiple sclerosis after the initial neurological event.

Clinically isolated syndrome (CIS) refers to the earliest clinical manifestation of multiple sclerosis (MS). Currently there are no prognostic biological markers that accurately predict conversion of CIS to clinically definite MS (CDMS). Furthermore, the earliest molecular events in MS are still unknown. We used microarrays to study gene expression in naïve CD4(+) T cells from 37 CIS patients at time of diagnosis and after 1 year. Supervised machine-learning methods were used to build predictive models of disease conversion. We identified 975 genes whose expression segregated CIS patients into four distinct subgroups. A subset of 108 genes further discriminated patients in one of these (group 1) from other CIS patients. Remarkably, 92% of patients in group 1 converted to CDMS within 9 months. Consistent down-regulation of TOB1, a critical regulator of cell proliferation, was characteristic of group 1 patients. Decreased TOB1 expression at the RNA and protein levels also was confirmed in experimental autoimmune encephalomyelitis. Finally, a genetic association was observed between TOB1 variation and MS progression in an independent cohort. These results indicate that CIS patients at high risk of conversion have impaired regulation of T cell quiescence, possibly resulting in earlier activation of pathogenic CD4(+) cells.

Met, the hepatocyte growth factor receptor, localizes to the nucleus in cells at low density.

Some breast cancer cases in our previous immunohistochemical studies show Met expression in the nucleus. Given nuclear localization of other receptor tyrosine kinases, we proceeded to investigate Met. Nuclear Met is seen in numerous cell lines and in germinal regions of many tissues using four unique antibodies. Cell fractionation reveals a 60-kDa band recognized by COOH-terminal Met antibodies that is present independent of hepatocyte growth factor treatment. Green fluorescent protein (GFP) fusion proteins of the cytoplasmic domain of Met transfected into HEK293 cells are found in the nucleus whereas the full-length Met-GFP fusion is membranous. Further deletions of the Met-GFP fusions identify a region of the juxtamembrane domain required for nuclear translocation. In a CaCo2 cell line model for epithelial maturation, we find that Met is initially nuclear, and then becomes membranous, after confluence. This work suggests processing of the Met receptor, analogous to ErbB4, resulting in the release of the cytoplasmic domain and its translocation to the nucleus in cells at low density.

Direct interaction of the C-terminal domain of alpha-catenin and F-actin is necessary for stabilized cell-cell adhesion.

Alpha-catenin functions to anchor adherens junctions to the filamentous actin (F-actin) cytoskeleton, through direct and indirect binding mechanisms. When truncated at amino acid 865, alpha-catenin exhibited a markedly reduced F-actin binding affinity compared to wild-type. Expression of the truncated mutant in the alpha-catenin deficient colon carcinoma cell line, Clone A, could not restore an adhesive phenotype when compared. Furthermore, the truncated alpha-catenin fusion protein failed to concentrate at sites of cell-cell contact, to promote morphological changes associated with epithelial monolayers, and to stimulate resistance to shearing forces in a hanging drop aggregation assay. Subsequent attempts to isolate single residues governing the direct F-actin interaction, using neutralizing charge or reverse charge mutations of basic residues within a homology modeled alpha-catenin C-terminal 5-helix bundle, had no effect on F-actin cosedimentation. We conclude that direct attachment of alpha-catenin to F-actin is required to promote cadherin-mediated contact formation and strong cell-cell adhesive states.