Genetic Risk and Chronic Obstructive Pulmonary Disease Independently Predict the Risk of Incident Severe COVID-19.

Rationale: Both genetic variants and chronic obstructive pulmonary disease (COPD) contribute to the risk of incident severe coronavirus disease (COVID-19). Whether genetic risk of incident severe COVID-19 is the same regardless of preexisting COPD is unknown. Objectives: In this study, we aimed to investigate the potential interaction between genetic risk and COPD in relation to severe COVID-19. Methods: We constructed a polygenic risk score for severe COVID-19 by using 112 single-nucleotide polymorphisms in 430,582 participants from the UK Biobank study. We examined the associations of genetic risk and COPD with severe COVID-19 by using logistic regression models. Results: Of 430,582 participants, 712 developed severe COVID-19 as of February 22, 2021, of whom 19.8% had preexisting COPD. Compared with participants at low genetic risk, those at intermediate genetic risk (odds ratio [OR], 1.34; 95% confidence interval [CI], 1.09-1.66) and high genetic risk (OR, 1.50; 95% CI, 1.18-1.92) had higher risk of severe COVID-19 (P for trend = 0.001), and the association was independent of COPD (P for interaction = 0.76). COPD was associated with a higher risk of incident severe COVID-19 (OR, 1.37; 95% CI, 1.12-1.67; P = 0.002). Participants at high genetic risk and with COPD had a higher risk of severe COVID-19 (OR, 2.05; 95% CI, 1.35-3.04; P < 0.001) than those at low genetic risk and without COPD. Conclusions: The polygenic risk score, which combines multiple risk alleles, can be effectively used in screening for high-risk populations of severe COVID-19. High genetic risk correlates with a higher risk of severe COVID-19, regardless of preexisting COPD.

Systematic review of the registered clinical trials for coronavirus disease 2019 (COVID-19).

BACKGROUND: Since the outbreak of coronavirus disease 2019 (COVID-19), many researchers in China have performed related clinical research. However, systematic reviews of the registered clinical trials are still lacking. Therefore, we conducted a systematic review of clinical trials for COVID-19 to summarize their characteristics. METHODS: This study is based on the PRISMA recommendations in the Cochrane handbook. The Chinese Clinical Registration Center and the ClinicalTrials.gov databases were searched to identify registered clinical trials related to COVID-19. The retrieval inception date was February 9, 2020. Two researchers independently selected the literature based on the inclusion and exclusion criteria, extracted data, and evaluated the risk of bias. RESULTS: A total of 75 registered clinical trials (63 interventional studies and 12 observational studies) for COVID-19 were identified. The majority of clinical trials were sponsored by Chinese hospitals. Only 11 trials have begun to recruit patients, and none of the registered clinical trials have been completed; 34 trials were early clinical exploratory trials or in the pre-experiment stage, 13 trials were phase III, and four trials were phase IV. The intervention methods included traditional Chinese medicine in 26 trials, Western medicine in 30 trials, and integrated traditional Chinese medicine and Western medicine in 19 trials. The subjects were primarily non-critical adult patients (≥ 18 years old). The median sample size of the trials was 100 (IQR: 60-200), and the median length of the trial periods was 179 d (IQR: 94-366 d). The main outcomes were clinical observation and examinations. Overall, the methodological quality of both the interventional trials and observational studies was low. CONCLUSIONS: Intensive clinical trials on the treatment of COVID-19 using traditional Chinese medicine and Western medicine are ongoing or will be performed in China. However, based on the uncertain methodological quality, small sample size, and long trial duration, we will not be able to obtain reliable, high-quality clinical evidence regarding the treatment of COVID-19 in the near future. Improving the quality of study design, prioritizing promising drugs, and using different designs and statistical methods are worth advocating and recommending for clinical trials of COVID-19 in the future.