Background: Shorter telomeres and COPD are both associated with accelerated cellular aging. Previously, telomere length has been demonstrated to be associated with reduced lung function and an increased risk of COPD. Computational modeling has allowed for large-scale telomere length estimation using whole genome sequencing data from the NHLBI TOPMed consortium. We hypothesized that shorter calculated telomere length would associate with COPD affection status and COPD severity (based on Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage), and that these relationships would be modified by sex and smoking status.

Methods: Using generalized linear mixed effects model and linear mixed effects model, we tested the relationship between telomere length and spirometry-defined moderate-to-severe COPD (GOLD grades 2,3, and 4) status, GOLD levels, and forced expiratory volume in 1 second (FEV1) percent predicted using the COPDGene study. Models were adjusted for sex, age at blood draw, age2, current smoking status, smoking intensity (log pack-years), and top 10 genetic ancestry principal components. We also tested the interaction effects between telomere length and sex, age, and smoking intensity on the risk for moderate-to-severe COPD. Linear regression model was evaluated for quantitative CT scan percent emphysema. Replications were conducted using the ECLIPSE and LTRC datasets.

Results: We observed significant association between shorter telomere length and higher risk of COPD in the COPDGene cohort (P<0.0001; 95% CI: 0.67 – 0.80). The result was replicated using the LTRC cohort (P=0.041; 95% CI: 0.46-0.98). We also observed a progressive shortening of telomere by GOLD grade in the COPDGene cohort (P<0.0001; 95% CI: 0.75-0.86), which showed a similar, but non-significant, trend in the LTRC and ECLIPSE data (P=0.25 and 0.06 respectively). However, we did not observe significant effect modification by sex, age or pack-years of smoking on the association of telomere length on COPD status. There was significant association between telomere length and percent emphysema in the COPDGene study (p-value = 3.37e-04).

Conclusion: Shorter telomere length associates with the risk of moderate-to-severe COPD and demonstrates shortening with increasing COPD severity. Decelerating telomere attrition may represent an important therapeutic target for mitigating COPD progression in smokers.

Asthma disparities by race and ethnicity in the U.S. may be influenced by differences in asthma drug response: African American and Puerto Rican children have lower drug response to bronchodilators, the most commonly used asthma rescue therapy. In this talk, we will present results from whole genome sequencing association analyses for bronchodilator response (BDR) among 6385 minority children from the Asthma Translational Genomics Collaboration (ATGC) that is part of the NHLBI’s TOPMed program. Genome-wide association analyses for BDR were conducted with TOPMed Freeze 8 data for each cohort and racial/ethnic group using linear mixed models, while adjusting for sex, age, BMI and four principal components. Racial/ethnic-specific and overall meta-analyses were performed using METASOFT under a fixed-effects model. Among common variants (MAF>0.01), the top association in 4562 African American children was nearest IZUMO3, in 1154 Puerto Rican children was nearest DNAH5, and in 669 Mexican children was nearest ZNF311. Across all racial-ethnic groups, the top variant was nearest SFXN4. We previously developed the app Reducing Associations by Linking Genes And omics Results (REALGAR) that provides insights helpful for prioritizing and designing functional validation studies for genetic associations using publicly available omics data. Using REALGAR, we found that 1) SFXN4 had decreased expression (q=3.8e-4) in whole blood of 318 people with severe asthma versus 87 healthy controls (GSE69683), 2) ZNF311 had increased expression (q=5.3e-7) and 3) DNAH5 and decreased expression (q=5.5e-25) in airway smooth muscle exposed to 100nM budesonide for 18hr (SRP098649). Thus, cell-specific omics suggests potential disease mechanisms of BDR associations and are useful to prioritize associated genes and facilitate the design of validation experiments.

Coronavirus disease 2019 (COVID-19), the clinical syndrome caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, has led to a global crisis. As a respiratory virus, SARS-CoV-2 is hypothesized to gain entry into humans via the airway epithelium, where it initiates a host response that leads to the subsequent clinical syndrome. However, the particular host and environmental factors that determine individual disease courses are poorly understood. Here, we analyzed RNA-sequencing data from bronchial epithelial brushings obtained from uninfected individuals in the SPIROMICS, SARP, and MAST cohorts, to investigate how non-genetic and genetic factors affect the regulation of host genes implicated in COVID-19.
We found that expression of ACE2, the receptor of the SARS-CoV-2 Spike protein, was higher in relation to known risk factors of severe COVID-19, such as active smoking, obesity, and hypertension, potentially facilitating SARS-CoV-2 entry into host cells. In contrast, a truncated, non-binding ACE2 isoform drove an association between interferon-related inflammation and ACE2 expression. We also discovered that expression patterns of a suppressed airway immune response to early SARS-CoV-2 infection, compared to other viruses, were similar to patterns associated with obesity, hypertension, and cardiovascular disease, which may thus contribute to a COVID-19-susceptible airway environment.
To identify host genetic variants affecting COVID-19 susceptibility, we next performed expression quantitative trait (eQTL) mapping in SPIROMICS (WGS data from the TOPMed project) focusing on 496 genes implicated in SARS-CoV-2. Although the key genes, ACE2 and TMPRSS2, did not have eQTLs in bronchial epithelium, we discovered 108 COVID-19-related genes with significant eQTLs (FDR < 0.05). Querying PheWAS results and using colocalization analysis, we further identified 12 loci where the eQTL signal and immune- or respiratory-related trait likely shared a genetic cause. These respiratory infectivity-altering variants are plausible host genetic risk factors for COVID-19. For example, ERMP1 has an eQTL colocalizing with an asthma association in the UK Biobank. ERMP1 interacts with the SARS-CoV-2 protein Orf9c, and studies suggest that severe asthma is a risk factor for COVID-19 hospitalization and death.
Altogether, our findings of genetic and non-genetic factors affecting the expression of COVID-19-related genes in bronchial epithelium provide essential insights for understanding inter-individual variation of COVID-19 and developing therapeutic targets.