Genetic Determinants of the Acute Respiratory Distress Syndrome.

Acute respiratory distress syndrome (ARDS) is a life-threatening lung condition that arises from multiple causes, including sepsis, pneumonia, trauma, and severe coronavirus disease 2019 (COVID-19). Given the heterogeneity of causes and the lack of specific therapeutic options, it is crucial to understand the genetic and molecular mechanisms that underlie this condition. The identification of genetic risks and pharmacogenetic loci, which are involved in determining drug responses, could help enhance early patient diagnosis, assist in risk stratification of patients, and reveal novel targets for pharmacological interventions, including possibilities for drug repositioning. Here, we highlight the basis and importance of the most common genetic approaches to understanding the pathogenesis of ARDS and its critical triggers. We summarize the findings of screening common genetic variation via genome-wide association studies and analyses based on other approaches, such as polygenic risk scores, multi-trait analyses, or Mendelian randomization studies. We also provide an overview of results from rare genetic variation studies using Next-Generation Sequencing techniques and their links with inborn errors of immunity. Lastly, we discuss the genetic overlap between severe COVID-19 and ARDS by other causes.

Residual Lung Abnormalities Following COVID-19 Hospitalization: Interim Analysis of the UKILD Post-COVID Study.

RATIONALE: Shared symptoms and genetic architecture between COVID-19 and lung fibrosis suggests SARS-CoV-2 infection may lead to progressive lung damage. OBJECTIVES: The UKILD Post-COVID study interim analysis was planned to estimate the prevalence of residual lung abnormalities in people hospitalized with COVID-19 based on risk strata. METHODS: The Post-HOSPitalisation COVID Study (PHOSP-COVID) was used for capture of routine and research follow-up within 240 days from discharge. Thoracic CTs linked by PHOSP-COVID identifiers were scored for percentage of residual lung abnormalities (ground glass opacities and reticulations). Risk factors in linked CT were estimated with Bayesian binomial regression and risk strata were generated. Numbers within strata were used to estimate post-hospitalization prevalence using Bayesian binomial distributions. Sensitivity analysis was restricted to participants with protocol driven research follow-up. MEASUREMENTS AND MAIN RESULTS: The interim cohort comprised 3700 people. Of 209 subjects with linked CTs (median 119 days, interquartile range 83-155), 166 people (79.4%) had >10% involvement of residual lung abnormalities. Risk factors included abnormal chest X-ray (RR 1·21 95%CrI 1·05; 1·40), percent predicted DLco<80% (RR 1·25 95%CrI 1·00; 1·56) and severe admission requiring ventilation support (RR 1·27 95%CrI 1·07; 1·55). In the remaining 3491 people, moderate to very-high risk of residual lung abnormalities was classified in 7·8%, post-hospitalization prevalence was estimated at 8.5% (95%CrI 7.6%; 9.5%) rising to 11.7% (95%CrI 10.3%; 13.1%) in sensitivity analysis. CONCLUSIONS: Residual lung abnormalities were estimated in up to 11% of people discharged following COVID-19 related hospitalization. Health services should monitor at-risk individuals to elucidate long-term functional implications. This article is open access and distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

Leveraging global multi-ancestry meta-analysis in the study of idiopathic pulmonary fibrosis genetics.

The research of rare and devastating orphan diseases, such as idiopathic pulmonary fibrosis (IPF) has been limited by the rarity of the disease itself. The prognosis is poor-the prevalence of IPF is only approximately four times the incidence, limiting the recruitment of patients to trials and studies of the underlying biology. Global biobanking efforts can dramatically alter the future of IPF research. We describe a large-scale meta-analysis of IPF, with 8,492 patients and 1,355,819 population controls from 13 biobanks around the globe. Finally, we combine this meta-analysis with the largest available meta-analysis of IPF, reaching 11,160 patients and 1,364,410 population controls. We identify seven novel genome-wide significant loci, only one of which would have been identified if the analysis had been limited to European ancestry individuals. We observe notable pleiotropy across IPF susceptibility and severe COVID-19 infection and note an unexplained sex-heterogeneity effect at the strongest IPF locus MUC5B.