Genetic predisposition to blood cell indices in relation to severe COVID-19.
Yao YaoHongfei SongFanshuang ZhangJibin LiuDong WangQuan-Sheng FengShuquan RaoCen JiangPublished in: Journal of medical virology (2022)
Despite considerable variation in disease manifestations observed among coronavirus disease 2019 (COVID-19) patients infected with severe acute respiratory syndrome coronavirus 2, the risk factors predicting disease severity remain elusive. Recent studies suggest that peripheral blood cells play a pivotal role in COVID-19 pathogenesis. Here, we applied two-sample Mendelian randomization (MR) analyses to evaluate the potential causal contributions of blood cell indices variation to COVID-19 severity, using single-nucleotide polymorphisms (SNPs) as instrumental variables for 17 indices from the UK Biobank and INTERVAL genome-wide association studies (N = 173 480). Data on the associations between the SNPs and very severe respiratory confirmed COVID-19 were obtained from the COVID-19 host genetics initiative (N = 8779/1 001 875). We observed significant negative association between hematocrit (HCT; odds ratio, OR = 0.775, 95% confidence interval, CI = 0.635-0.915, p = 3.48E-04) or red blood cell count (OR = 0.830, 95% CI = 0.728-0.932, p = 2.19E-03) and very severe respiratory confirmed COVID-19, as well as nominal negative association of hemoglobin concentration (OR = 0.808, 95% CI = 0.673-0.943, p = 3.95E-03) with very severe respiratory confirmed COVID-19 (no effect survived multiple correction). In conclusion, the MR study supports a protective effect of high HCT and red blood cell count from very severe respiratory confirmed COVID-19, suggesting potential strategies to ameliorate/treat clinical conditions in very severe respiratory confirmed COVID-19.
Keyphrases
- coronavirus disease
- sars cov
- respiratory syndrome coronavirus
- red blood cell
- peripheral blood
- risk factors
- magnetic resonance imaging
- magnetic resonance
- genome wide
- dna methylation
- stem cells
- computed tomography
- machine learning
- drug induced
- signaling pathway
- risk assessment
- quality improvement
- cell cycle arrest
- contrast enhanced
- oxidative stress
- cell therapy
- bone marrow
- big data
- respiratory tract
- climate change
- pi k akt
- copy number