Genetic overlap study between idiopathic pulmonary fibrosis and COVID-19

Background/Objectives: Genetic factors influence COVID-19 susceptibility and outcomes, including the development of pulmonary fibrosis (i.e. lung scarring). Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease and the most common cause of pulmonary fibrosis in the general population. Genome-wide association studies (GWAS) of COVID-19 and IPF revealed genes associated with both diseases, suggesting these share genetic risk factors. Here we performed a genetic overlap study between COVID-19 and IPF. Method(s): Summary statistics from an IPF 5-way meta-GWAS and from the COVID-19 Host Genetics initiative GWAS metaanalysis (v6) were used. We performed genetic correlation analyses and assessed individual genetic signals to identify those variants shared between both traits. We conducted colocalisation analyses to determine whether the same causal variant was driving both traits. Finally, the association of overlapping variants with gene expression was assessed and a phenome-wide association study was performed. Result(s): There was a positive genetic correlation between severe COVID-19 and IPF. We found four genetic loci with likely shared causal variants between both traits, including one novel risk locus at 7q22.1 that colocalised with decreased ZKSCAN1 and TRIM4 expression in blood. The other three loci colocalised with MUC5B, ATP11A and DPP9 expression. The locus associated with increased ATP11A expression was also associated with higher Hb1AC levels, a biomarker used in diabetes. Conclusion(s): Results suggest there are shared biological processes driving IPF and severe COVID-19 phenotypes.

Inflammation profiling and recovery clusters five months post-hospitalisation for COVID-19

Background Understanding the underlying mechanisms of post-COVID sequelae (Long COVID) is urgently needed to guide interventions. Aim To compare the inflammation profiles of four recovery clusters post-hospitalisation. Methods Post-Hospitalisation COVID-19 (PHOSP-COVID) is a prospective, multi-centre study across UK. Four recovery clusters previously identified using clinical data (symptoms, mental health, cognitive impairment, and physical function) at 5 months post-discharge were used based on severity of on-going health impairments: very severe, severe, moderate (cognitive), and mild. Inflammatory profiling performed from plasma samples using the Olink Explore 384 inflammation panel. Multinomial logistic regression for each protein was undertaken comparing the mild cluster with each of the remaining clusters with FDR of 0.1 to adjust p values. Results 626 participants (clusters: very severe n=111, severe n=173, moderate/cognitive n=73 and mild n=269). Proteomic results from 296 proteins were included. After adjustment for age, BMI, and comorbidity count, 13 proteins were significantly elevated in the very severe cluster, and 2 proteins in the moderate/cognitive cluster, compared to the mild cluster (Figure 1). Conclusion Inflammatory mediators consistent with persistent lung and systemic inflammation were associated with the severity of ongoing health impairments highlighting potential therapeutic pathways to be tested.

Characteristics and risk factors for persistent breathlessness after hospitalisation for COVID-19

Background: Persisting breathlessness after COVID-19 infection is common and debilitating. We aimed to characterise and identify risk factors for patients with persistent breathlessness following COVID-19 hospitalisation. Method(s): PHOSP-COVID is a multi-centre prospective cohort study of UK adults hospitalised for COVID-19. Clinical data were collected during hospitalisation and at a research visit. Breathlessness was measured by a numeric rating scale of 0-10. We defined post-COVID breathlessness as an increase in score of 1 or more compared to the preCOVID-19 level. Multivariable logistic regression was used to identify risk factors. Result(s): We included 1,226 participants (37% female, median age 59 years, 22% mechanically ventilated). At a median five months after discharge, 50% reported post-COVID breathlessness. Risk factors for post-COVID breathlessness were socio-economic deprivation (adjusted odds ratio, 1.67;95% confidence interval, 1.14-2.44), pre-existing depression/anxiety (1.58;1.06-2.35), female sex (1.56;1.21-2.00) and admission duration (1.01;1.00- 1.02). Black ethnicity (0.56;0.35-0.89) and older age groups (0.31;0.14-0.66) were less likely to report post-COVID breathlessness. Post-COVID breathlessness was associated with worse performance on the shuttle walk test and forced vital capacity, but not with obstructive airflow limitation. Conclusion(s): Half of this national cohort of patients hospitalised for COVID-19 experienced persistent breathlessness at follow up. The risk factors identified for post-COVID breathlessness should inform mechanistic work to understand causal processes and develop future interventions to improve outcomes in this growing population.

Genetic overlap study between acute respiratory distress syndrome and idiopathic pulmonary fibrosis

Introduction and ObjectiveAcute respiratory distress syndrome (ARDS) is a critical lung condition induced by a systemic inflammatory response. A subset of ARDS patients can also develop pulmonary fibrosis (i.e. lung scarring). Idiopathic pulmonary fibrosis (IPF) is the most common cause of pulmonary fibrosis in the general population. Genome-wide association studies (GWAS) of IPF and post-sepsis ARDS suggest that these phenotypes could share genetic risk factors. Here we performed the first genetic overlap study between IPF and ARDS to identify shared genetic risk loci that might be informative about development of lung fibrosis after ARDS.MethodsWe used summary statistics from large meta-GWASs of IPF risk (4,125 cases, 20,464 controls) and post-sepsis ARDS (716 cases, 4,399 controls), as well as individual-level data from a subset of individuals from the ARDS GWAS (321 cases, 3,249 controls). We performed polygenic risk score (PRS) analyses to assess if IPF GWAS variants could be used to predict ARDS risk. We constructed PRSs as the weighted sum of variants reaching different p-value thresholds in the IPF meta-GWAS, and tested their association with ARDS risk, whilst adjusting for age, sex and population stratification. We also assessed individual genetic signals to identify variants shared between both traits. We conducted colocalisation analyses to determine whether the same causal variant was driving both phenotypes, and studied the association of overlapping variants with gene expression.ResultsThe PRS calculated from IPF variants that passed the best p-value threshold (i.e. p=0.0011) predicted ARDS risk (p=4.07x10-04, OR[95%CI]=1.24[1.10, 1.39]). We also found that the ARDS protective allele at HLA-DQA2 was associated with IPF risk (p=1.28x10-04) and that the IPF risk allele at ATP11A conferred protection from post-sepsis ARDS (p=0.003). The latter was associated with protection from severe COVID-19 in previous studies. Colocalisation analyses were inconclusive, likely due to the limited ARDS sample size.ConclusionsOur risk score analyses suggest that there may be shared biological processes underlying IPF and ARDS risk. However, we note opposite directions of effect on IPF and ARDS risk for some loci. Further studies are needed to assess if these results are also informative about fibrotic sequelae of ARDS.Please refer to page A208 for declarations of interest related to this .

Extended cohort for e-health, environment and DNA (exceed) COVID-19 focus

Background: New data collection in established longitudinal population studies provides an opportunity for studying the risk factors and sequelae of the novel coronavirus disease 2019 (COVID-19), plus the indirect impacts of the COVID-19 pandemic on wellbeing. The Extended Cohort for E-health, Environment and DNA (EXCEED) cohort is a population-based cohort (N>11,000), recruited from 2013 in Leicester, Leicestershire and Rutland. EXCEED includes consent for electronic healthcare record (EHR) linkage, spirometry, genomic data, and questionnaire data.

Prognostic value of the initial chest computerised tomography scan at one year following infection in an ethnically diverse cohort of patients admitted to hospital for COVID-19

P130 Figure 1Features of COVID-19 on the CT were very common in hospitalised patients and were related to all-cause mortality one year following hospitalisation[Figure omitted. See PDF]ConclusionEvidence of COVID-19 pneumonia on CTT is more common and severe in patients from ethnic minority groups and is independently associated with worse prognosis following hospitalisation.