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Data from: Integrative genomic analysis in African American children with asthma finds 3 novel loci associated with lung function

Citation

Goddard, Pagé et al. (2020), Data from: Integrative genomic analysis in African American children with asthma finds 3 novel loci associated with lung function, Dryad, Dataset, https://doi.org/10.5061/dryad.w3r2280nw

Abstract

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. 

Methods

Cohort

  • Subset of the SAGE II cohort (Study of African Americans, Asthma, Genes, and Environments),  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)

Genotyping, Ancestry Inference, and Quality Control

  • 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 < 5%, MAF > 1%, no deviation from HWE [p > 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

Genetic Association Analyses

  • 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.

Fine-mapping

  • 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.

Usage Notes

Full code used to produce the datasets is available here: https://github.com/asthmacollaboratory/sage-lungfunction

gwas.*.mlma - 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

admixmap.*.SAGE_ALLCHR.txt - 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

*.paintor.results - file per locus (5 total) of posterior probabilities at each SNP

*.annotations.pval file per locus (5 total) of p-values of annotations tested used at each locus

*.annotations.top file per locus (5 total) for the top 5 annotations used per locus, visible in the CANVIS figures

Funding

National Heart, Lung, and Blood Institute, Award: R01HL117004

National Heart, Lung, and Blood Institute, Award: R01HL128439

National Heart, Lung, and Blood Institute, Award: R01HL135156

National Heart, Lung, and Blood Institute, Award: X01HL134589

National Heart, Lung, and Blood Institute, Award: R01HL141992

National Heart, Lung, and Blood Institute, Award: R01HL104608

National Heart, Lung, and Blood Institute, Award: R01HL141845

National Heart, Lung, and Blood Institute, Award: U01HL138626

National Human Genome Research Institute, Award: U01HG007419

National Human Genome Research Institute, Award: U01HG009080

National Institute of Environmental Health Sciences, Award: R01ES015794

National Institute of Environmental Health Sciences, Award: R21ES24844

Eunice Kennedy Shriver National Institute of Child Health and Human Development, Award: R01HD085993

National Institute on Minority Health and Health Disparities, Award: P60MD006902

National Institute on Minority Health and Health Disparities, Award: R01MD010443

National Institute on Minority Health and Health Disparities, Award: RL5GM118984

National Institute on Minority Health and Health Disparities, Award: R56MD013312

Tobacco-Related Disease Research Program, Award: 24RT-0025

Tobacco-Related Disease Research Program, Award: 27IR-0030

National Institute of General Medical Sciences, Award: TL4GM118986

National Institute of General Medical Sciences, Award: 1UL1GM118985

National Human Genome Research Institute, Award: T32HG000044

National Heart, Lung, and Blood Institute, Award: R01HL135156-S1

Gordon and Betty Moore Foundation, Award: GBMF3834

Alfred P. Sloan Foundation, Award: 2013-10-27

National Institute of General Medical Sciences, Award: T32GM007546

National Institutes of Health, Award: T34GM008574

National Heart, Lung, and Blood Institute, Award: R01HL117004-S1

National Institute of General Medical Sciences, Award: K12GM081266

National Heart, Lung, and Blood Institute, Award: K01HL140218