Image_2_HLA-associated outcomes in peanut oral immunotherapy trials identify mechanistic and clinical determinants of therapeutic success.pdf

RationalePrevious studies identified an interaction between HLA and oral peanut exposure. HLA-DQA1*01:02 had a protective role with the induction of Ara h 2 epitope-specific IgG4 associated with peanut consumption during the LEAP clinical trial for prevention of peanut allergy, while it was a risk allele for peanut allergy in the peanut avoidance group. We have now evaluated this gene-environment interaction in two subsequent peanut oral immunotherapy (OIT) trials - IMPACT and POISED - to better understand the potential for the HLA-DQA1*01:02 allele as an indicator of higher likelihood of desensitization, sustained unresponsiveness, and peanut allergy remission.MethodsWe determined HLA-DQA1*01:02 carrier status using genome sequencing from POISED (N=118, age: 7-55yr) and IMPACT (N=126, age: 12-ResultsWhile not quite statistically significant, a higher proportion of HLA-DQA1*01:02 carriers receiving OIT in IMPACT were desensitized (93%) compared to non-carriers (78%); odds ratio (OR)=5.74 (p=0.06). In this sample we also observed that a higher proportion of carriers achieved remission (35%) compared to non-carriers (22%); OR=1.26 (p=0.80). In POISED, carriers more frequently attained continued desensitization (80% versus 61% among non-carriers; OR=1.28, p=0.86) and achieved SU (52% versus 31%; OR=2.32, p=0.19). psIgG4 associations with HLA-DQA1*01:02 in the OIT arm of IMPACT which included younger study subjects recapitulated patterns noted in LEAP, but no associations of note were observed in the older POISED study subjects.ConclusionsFindings across three clinical trials show a pattern of a gene environment interaction between HLA and oral peanut exposure. Age, and prior sensitization contribute additional determinants of outcomes, consistent with a mechanism of restricted antigen recognition fundamental to driving protective immune responses to OIT.</p

High-Throughput Sequencing in Respiratory, Critical Care, and Sleep Medicine Research An Official American Thoracic Society Workshop Report

High-throughput, “next-generation” sequencing methods are now being broadly applied across all fields of biomedical research, including respiratory disease, critical care, and sleep medicine. Although there are numerous review articles and best practice guidelines related to sequencing methods and data analysis, there are fewer resources summarizing issues related to study design and interpretation, especially as applied to common, complex, nonmalignant diseases. To address these gaps, a single-day workshop was held at the American Thoracic Society meeting in May 2017, led by the American Thoracic Society Section on Genetics and Genomics. The aim of this workshop was to review the design, analysis, interpretation, and functional follow-up of high-throughput sequencing studies in respiratory, critical care, and sleep medicine research. This workshop brought together experts in multiple fields, including genetic epidemiology, biobanking bioinformatics, and research ethics, along with physician-scientists with expertise in a range of relevant diseases. The workshop focused on application of DNA and RNA sequencing research in common chronic diseases and did not cover sequencing studies in lung cancer, monogenic diseases (e.g., cystic fibrosis), or microbiome sequencing. Participants reviewed and discussed study design, data analysis and presentation, interpretation, functional follow-up, and reporting of results. This report summarizes the main conclusions of the workshop, specifically addressing the application of these methods in respiratory, critical care, and sleep medicine research. This workshop report may serve as a resource for our research community as well as for journal editors and reviewers of sequencing-based manuscript submissions in our research field

Image_1_HLA-associated outcomes in peanut oral immunotherapy trials identify mechanistic and clinical determinants of therapeutic success.pdf

RationalePrevious studies identified an interaction between HLA and oral peanut exposure. HLA-DQA1*01:02 had a protective role with the induction of Ara h 2 epitope-specific IgG4 associated with peanut consumption during the LEAP clinical trial for prevention of peanut allergy, while it was a risk allele for peanut allergy in the peanut avoidance group. We have now evaluated this gene-environment interaction in two subsequent peanut oral immunotherapy (OIT) trials - IMPACT and POISED - to better understand the potential for the HLA-DQA1*01:02 allele as an indicator of higher likelihood of desensitization, sustained unresponsiveness, and peanut allergy remission.MethodsWe determined HLA-DQA1*01:02 carrier status using genome sequencing from POISED (N=118, age: 7-55yr) and IMPACT (N=126, age: 12-ResultsWhile not quite statistically significant, a higher proportion of HLA-DQA1*01:02 carriers receiving OIT in IMPACT were desensitized (93%) compared to non-carriers (78%); odds ratio (OR)=5.74 (p=0.06). In this sample we also observed that a higher proportion of carriers achieved remission (35%) compared to non-carriers (22%); OR=1.26 (p=0.80). In POISED, carriers more frequently attained continued desensitization (80% versus 61% among non-carriers; OR=1.28, p=0.86) and achieved SU (52% versus 31%; OR=2.32, p=0.19). psIgG4 associations with HLA-DQA1*01:02 in the OIT arm of IMPACT which included younger study subjects recapitulated patterns noted in LEAP, but no associations of note were observed in the older POISED study subjects.ConclusionsFindings across three clinical trials show a pattern of a gene environment interaction between HLA and oral peanut exposure. Age, and prior sensitization contribute additional determinants of outcomes, consistent with a mechanism of restricted antigen recognition fundamental to driving protective immune responses to OIT.</p

Additional file 2 of African-specific alleles modify risk for asthma at the 17q12-q21 locus in African Americans

Additional file 2. Region-wide eQTL results in airway epithelial cells from 189 African American children in the URECA cohort

Additional file 1 of African-specific alleles modify risk for asthma at the 17q12-q21 locus in African Americans

Additional file 1. Contains Supplementary Methods, Supplementary Tables (Table S1-10), and Supplementary Figures (Fig. S1-14), and corresponding references. Supplementary Methods. Descriptions of Populations. Building Consensus Sequences in the Critical Region. Table S1. Characteristics of the APIC and URECA Cohorts. Table S2. Predicted Haplotypes in CREW. Table S3. Haplotype Frequencies in Whole Genome Sequences. Table S4. Worldwide Frequencies of African-specific SNPs. Table S5. cis-eQTL Results for SNPs in or near GSDMA. Table S6. ENCODE Cell Lines and DNAse Clustering at pcHi-C Region. Table S7. pcHi-C Target Genes for African-specific Variants in Airway Epithelial Cells. Table S8. pcHi-C Target Genes for African-specific Variants in Airway Immune Cells. Table S9. Quantitative Trait Association Results in the APIC and URECA Cohorts. Table S10. African American Adult Asthmatics by Severity and Genotype. Figure S1. Overview of Study Design. Figure S2. ChromoPainter Analysis. Figure S3. ChromoPainter Visualization of Haplotype Breakpoints. Figure S4. ChromoPainter Display of the 17q12-q21 Region in Haplotype 4 Homozygotes. Figure S5. Ancestry PCA plots for APIC and URECA Children. Figure S6. eQTL Box Plots of rs28623237 Genotype and GSDMA Expression in CAAPA2. Figure S7. LD Plot of African-specific Variants and SNPs in or near GSDMA. Figure S8. eQTL Box Plots of rs113282230 Genotype and GSDMA Expression Conditioned on GSDMA SNPs. Figure S9. eQTL Violin Plots of rs235480 and rs1132828830 Genotypes on GSDMA and GSDMB Expression. Figure S10. LD Plot of the African-specific Variants and SNPs in the Core Region of The 17q12-q21 Locus. Figure S11. Chromatin Annotations in the Region Encoding the African-specific SNPs in ENCODE Cell Lines. Figure S12. eGenes for rs113282230 in Immune Cells. Figure S13. pcHi-C Data for rs113282230 in Immune Cells. Figure S14. Rs113282230 Genotype Effect on Asthma Prevalence by rs2305480 AA And GG Genotypes in APIC and URECA