Genetic and non-genetic factors affecting the expression of COVID-19-relevant genes in the large airway epithelium. - Kasela, Silva; Ortega, Victor E; Martorella, Molly; Garudadri, Suresh; Nguyen, Jenna; Ampleford, Elizabeth; Pasanen, Anu; Nerella, Srilaxmi; Buschur, Kristina L; Barjaktarevic, Igor Z; Barr, R Graham; Bleecker, Eugene R; et al. (Genome Med, 2021)
BACKGROUND: The large airway epithelial barrier provides one of the first lines of defense against respiratory viruses, including SARS-CoV-2 that causes COVID-19. Substantial inter-individual variability in individual disease courses is hypothesized to be partially mediated by the differential regulation of the genes that interact with the SARS-CoV-2 virus or are involved in the subsequent host response. Here, we comprehensively investigated non-genetic and genetic factors influencing COVID-19-relevant bronchial epithelial gene expression. METHODS: We analyzed RNA-sequencing data from bronchial epithelial brushings obtained from uninfected individuals. We related ACE2 gene expression to host and environmental factors in the SPIROMICS cohort of smokers with and without chronic obstructive pulmonary disease (COPD) and replicated these associations in two asthma cohorts, SARP and MAST. To identify airway biology beyond ACE2 binding that may contribute to increased susceptibility, we used gene set enrichment analyses to determine if gene expression changes indicative of a suppressed airway immune response observed early in SARS-CoV-2 infection are also observed in association with host factors. To identify host genetic variants affecting COVID-19 susceptibility in SPIROMICS, we performed expression quantitative trait (eQTL) mapping and investigated the phenotypic associations of the eQTL variants. RESULTS: We found that ACE2 expression was higher in relation to active smoking, obesity, and hypertension that are known risk factors of COVID-19 severity, while an association with interferon-related inflammation was driven by the truncated, non-binding ACE2 isoform. We discovered that expression patterns of a suppressed airway immune response to early SARS-CoV-2 infection, compared to other viruses, are similar to patterns associated with obesity, hypertension, and cardiovascular disease, which may thus contribute to a COVID-19-susceptible airway environment. eQTL mapping identified regulatory variants for genes implicated in COVID-19, some of which had pheWAS evidence for their potential role in respiratory infections. CONCLUSIONS: These data provide evidence that clinically relevant variation in the expression of COVID-19-related genes is associated with host factors, environmental exposures, and likely host genetic variation.
Keywords: Adult; Aged; Aged, 80 and over; Angiotensin-Converting Enzyme 2; Asthma; Bronchi; Cardiovascular Diseases; COVID-19; Gene Expression; Genetic Variation; Humans; Middle Aged; Obesity; Pulmonary Disease, Chronic Obstructive; Quantitative Trait Loci; Respiratory Mucosa; Risk Factors; SARS-CoV-2; Smoking

Whole exome sequencing analysis in severe chronic obstructive pulmonary disease. - Qiao, Dandi; Ameli, Asher; Prokopenko, Dmitry; Chen, Han; Kho, Alvin T; Parker, Margaret M; Morrow, Jarrett; Hobbs, Brian D; Liu, Yanhong; Beaty, Terri H; Crapo, James D; Barnes, Kathleen C; et al. (Hum Mol Genet, 2018)
Chronic obstructive pulmonary disease (COPD), one of the leading causes of death worldwide, is substantially influenced by genetic factors. Alpha-1 antitrypsin deficiency demonstrates that rare coding variants of large effect can influence COPD susceptibility. To identify additional rare coding variants in patients with severe COPD, we conducted whole exome sequencing analysis in 2543 subjects from two family-based studies (Boston Early-Onset COPD Study and International COPD Genetics Network) and one case-control study (COPDGene). Applying a gene-based segregation test in the family-based data, we identified significant segregation of rare loss of function variants in TBC1D10A and RFPL1 (P-value < 2x10-6), but were unable to find similar variants in the case-control study. In single-variant, gene-based and pathway association analyses, we were unable to find significant findings that replicated or were significant in meta-analysis. However, we found that the top results in the two datasets were in proximity to each other in the protein-protein interaction network (P-value = 0.014), suggesting enrichment of these results for similar biological processes. A network of these association results and their neighbors was significantly enriched in the transforming growth factor beta-receptor binding and cilia-related pathways. Finally, in a more detailed examination of candidate genes, we identified individuals with putative high-risk variants, including patients harboring homozygous mutations in genes associated with cutis laxa and Niemann-Pick Disease Type C. Our results likely reflect heterogeneity of genetic risk for COPD along with limitations of statistical power and functional annotation, and highlight the potential of network analysis to gain insight into genetic association studies.
Keywords: Adolescent; Adult; Aged; Case-Control Studies; DNA Mutational Analysis; Female; Genetic Association Studies; Genetic Predisposition to Disease; Humans; Male; Middle Aged; Mutation; Polymorphism, Single Nucleotide; Pulmonary Disease, Chronic Obstructive; Whole Exome Sequencing; Young Adult

Gene-based segregation method for identifying rare variants in family-based sequencing studies. - Qiao, Dandi; Lange, Christoph; Laird, Nan M; Won, Sungho; Hersh, Craig P; Morrow, Jarrett; Hobbs, Brian D; Lutz, Sharon M; Ruczinski, Ingo; Beaty, Terri H; Silverman, Edwin K; Cho, Michael H (Genet Epidemiol, 2017)
Whole-exome sequencing using family data has identified rare coding variants in Mendelian diseases or complex diseases with Mendelian subtypes, using filters based on variant novelty, functionality, and segregation with the phenotype within families. However, formal statistical approaches are limited. We propose a gene-based segregation test (GESE) that quantifies the uncertainty of the filtering approach. It is constructed using the probability of segregation events under the null hypothesis of Mendelian transmission. This test takes into account different degrees of relatedness in families, the number of functional rare variants in the gene, and their minor allele frequencies in the corresponding population. In addition, a weighted version of this test allows incorporating additional subject phenotypes to improve statistical power. We show via simulations that the GESE and weighted GESE tests maintain appropriate type I error rate, and have greater power than several commonly used region-based methods. We apply our method to whole-exome sequencing data from 49 extended pedigrees with severe, early-onset chronic obstructive pulmonary disease (COPD) in the Boston Early-Onset COPD study (BEOCOPD) and identify several promising candidate genes. Our proposed methods show great potential for identifying rare coding variants of large effect and high penetrance for family-based sequencing data. The proposed tests are implemented in an R package that is available on CRAN (https://cran.r-project.org/web/packages/GESE/).
Keywords: Age of Onset; Boston; Computer Simulation; Databases, Genetic; Family; Genetic Variation; Genome, Human; Humans; Models, Genetic; Penetrance; Pulmonary Disease, Chronic Obstructive; Reference Standards; Sequence Analysis, DNA

Exome Sequencing Analysis in Severe, Early-Onset Chronic Obstructive Pulmonary Disease. - Qiao, Dandi; Lange, Christoph; Beaty, Terri H; Crapo, James D; Barnes, Kathleen C; Bamshad, Michael; Hersh, Craig P; Morrow, Jarrett; Pinto-Plata, Victor M; Marchetti, Nathaniel; Bueno, Raphael; Celli, Bartolome R; et al. (Am J Respir Crit Care Med, 2016)
RATIONALE: Genomic regions identified by genome-wide association studies explain only a small fraction of heritability for chronic obstructive pulmonary disease (COPD). Alpha-1 antitrypsin deficiency shows that rare coding variants of large effect also influence COPD susceptibility. We hypothesized that exome sequencing in families identified through a proband with severe, early-onset COPD would identify additional rare genetic determinants of large effect. OBJECTIVES: To identify rare genetic determinants of severe COPD. METHODS: We applied filtering approaches to identify potential causal variants for COPD in whole exomes from 347 subjects in 49 extended pedigrees from the Boston Early-Onset COPD Study. We assessed the power of this approach under different levels of genetic heterogeneity using simulations. We tested genes identified in these families using gene-based association tests in exomes of 204 cases with severe COPD and 195 resistant smokers from the COPDGene study. In addition, we examined previously described loci associated with COPD using these datasets. MEASUREMENTS AND MAIN RESULTS: We identified 69 genes with predicted deleterious nonsynonymous, stop, or splice variants that segregated with severe COPD in at least two pedigrees. Four genes (DNAH8, ALCAM, RARS, and GBF1) also demonstrated an increase in rare nonsynonymous, stop, and/or splice mutations in cases compared with resistant smokers from the COPDGene study; however, these results were not statistically significant. We demonstrate the limitations of the power of this approach under genetic heterogeneity through simulation. CONCLUSIONS: Rare deleterious coding variants may increase risk for COPD, but multiple genes likely contribute to COPD susceptibility.
Keywords: Adult; alpha 1-Antitrypsin Deficiency; Boston; Exome; Female; Genetic Predisposition to Disease; Genome-Wide Association Study; Humans; Male; Middle Aged; Pulmonary Disease, Chronic Obstructive; Severity of Illness Index

PRIMUS: rapid reconstruction of pedigrees from genome-wide estimates of identity by descent. - Staples, Jeffrey; Qiao, Dandi; Cho, Michael H; Silverman, Edwin K; Nickerson, Deborah A; Below, Jennifer E (Am J Hum Genet, 2014)
Understanding and correctly utilizing relatedness among samples is essential for genetic analysis; however, managing sample records and pedigrees can often be error prone and incomplete. Data sets ascertained by random sampling often harbor cryptic relatedness that can be leveraged in genetic analyses for maximizing power. We have developed a method that uses genome-wide estimates of pairwise identity by descent to identify families and quickly reconstruct and score all possible pedigrees that fit the genetic data by using up to third-degree relatives, and we have included it in the software package PRIMUS (Pedigree Reconstruction and Identification of the Maximally Unrelated Set). Here, we validate its performance on simulated, clinical, and HapMap pedigrees. Among these samples, we demonstrate that PRIMUS can verify reported pedigree structures and identify cryptic relationships. Finally, we show that PRIMUS reconstructed pedigrees, all of which were previously unknown, for 203 families from a cohort collected in Starr County, TX (1,890 samples).
Keywords: Base Sequence; Computer Simulation; Exome; Gene Frequency; Genetics, Population; Humans; Molecular Sequence Data; Pedigree; Pulmonary Disease, Chronic Obstructive; Sequence Analysis, DNA; Software; Texas