DOI: 10.5061/dryad.w3r2280nw
title: Data from: Integrative genomic analysis in African American children with asthma finds 3 novel loci associated with lung function

description: Bronchodilator drugs are commonly prescribed for treatment and management
 of obstructive lung function present
 with diseases such as asthma. Administration of
 bronchodilator medication can partially or fully restore lung
 function as measured by pulmonary function tests. The genetics of baseline
 lung function measures taken prior to bronchodilator medication has
 been extensively studied, and the
 genetics of the bronchodilator response itself has received some
 attention. However, few studies have focused on the
 genetics of post-bronchodilator lung function. To address this
 gap, we analyzed lung function phenotypes in 1,103
 subjects from the Study of African Americans, Asthma, Genes, and
 Environment (SAGE), a pediatric asthma case-control cohort, using an
 integrative genomic analysis approach that
 combined genotype, locus-specific genetic
 ancestry, and functional annotation
 information. We integrated genome-wide
 association study (GWAS) results with an admixture
 mapping scan of three pulmonary function tests
 (FEV1, FVC, and
 FEV1/FVC) taken before and after albuterol bronchodilator administration on the same subjects, yielding six traits. We identified 18 GWAS loci, and 5 additional loci from admixture mapping, spanning several known and novel lung function candidate genes. Most loci identified via admixture mapping exhibited wide variation in minor allele frequency across genotyped global populations. Functional fine-mapping revealed an enrichment of epigenetic annotations from peripheral blood mononuclear cells, fetal lung tissue, and lung fibroblasts. Our results point to three novel potential genetic drivers of pre- and post-bronchodilator lung function: ADAMTS1, RAD54B, and EGLN3. 
description: <strong>Cohort</strong> 
 Subset of the SAGE II cohort (<strong>S</strong>tudy
 of <strong>A</strong>frican Americans, Asthma,
 <strong>G</strong>enes, and<strong>
 E</strong>nvironments),  described in full elsewhere (Borrell et
 al., 2013; Nishimura et al., 2013; Thakur et al., 2013; Mak et al.,
 2018)  Selected participants are self-identified as
 US-born, non-Hispanic African American and self-reported that all four
 grandparents were also US-born, non-Hispanic African Americans.
 Selected participants had pre- or pre- and post-bronchodilator
 spirometry measurements available (FEV1, FVC, FEV1/FVC), and full
 covariate data (age, sex, BMI, asthma status, maternal educational
 attainment) Final cohort: 1,103 individuals (831
 cases) <strong>Genotyping, Ancestry
 Inference, and Quality Control</strong> 
 DNA isolated from whole blood and extracted using Wizard®
 Genomic DNA Purification kits (Promega, Fitchburg, WI).
 Genotyping performed with Affymetrix Axion LAT1 array
 Imputation was performed via the Michigan Imputation Server with the 1000 Genomes Project reference panel QC performed in PLINK v1.9 (Filters for retention: biallelic SNP, genotype missingness &lt; 5%, MAF &gt; 1%, no deviation from HWE [p &gt; 0.001]) Local ancestry was called with RFMix for 454,322 genotyped SNPs that were successfully phased Final genotyped set: 660,802 markers Final imputed set: 15,954,804 markers <strong>Genetic Association Analyses</strong> Genetic Relatedness Matrices (GRMs) were constructed with the GENESIS pipeline Genotype association testing executed with the MLMA-LOCO algorithm from GCTA, correcting for age (continuous), sex (male, female), obesity status (obese, overweight, normal), maternal educational attainment (years of) and the first 3 principle components, as well as asthma status for pre-bronchodilator measurements. Admixture mapping analysis were performed with linear regression models in R after regressing phenotypes onto ancestral allele counts (0, 1, or 2 African ancestral alleles) for each SNP, including age, sex, obesity status, maternal education, and global African ancestry proportion as covariates, with asthma status as an additional covariate for pre-bronchodilator measurements. <b>Fine-mapping</b> Functional fine-mapping was performed with PAINTOR according to the recommended approach, using a subset of lung- and blood-related duncation annotations from the Roadmap project and ENCODE consortium. The top 5 minimally correlated annotations were selected for the final PAINTOR model at each locus. Fine-mapping was performed on the GWAS summary statistics within the regions identified by admixture mapping.
description: Full code used to produce the datasets is available here: https://github.com/asthmacollaboratory/sage-lungfunction <strong>gwas.*.mlma</strong> - file per phenotype (6 total) of GWAS results, corrected for age, sex, obesity status, maternal education, height, PCs 1-3, and, for pre-bronchodilator phenotypes, asthma status <b>admixmap.*.SAGE_ALLCHR.txt</b> - file per phenotype (6 total) of admixture mapping analysis results, corrected for age, sex, obesity status, maternal education, height, global African ancestry, and, for pre-bronchodilator phenotypes, asthma status <strong>*.paintor.results</strong> - file per locus (5 total) of posterior probabilities at each SNP <strong>*.annotations.pval</strong> file per locus (5 total) of p-values of annotations tested used at each locus <strong>*.annotations.top</strong> file per locus (5 total) for the top 5 annotations used per locus, visible in the CANVIS figures