Systematic review of host genetic association with Covid-19 prognosis and susceptibility: What have we learned in 2020?
João Locke Ferreira de AraújoDiego Menezes BonfimJulia Maria Saraiva-DuarteLuciana de Lima FerreiraRenato Santana de AguiarRenan Pedra de SouzaPublished in: Reviews in medical virology (2021)
Biomarker identification may provide strategic opportunities to understand disease pathophysiology, predict outcomes, improve human health, and reduce healthcare costs. The highly heterogeneous Covid-19 clinical manifestation suggests a complex interaction of several different human, viral and environmental factors. Here, we systematically reviewed genetic association studies evaluating Covid-19 severity or susceptibility to SARS-CoV-2 infection following PRISMA recommendations. Our research comprised papers published until December 31st , 2020, in PubMed and BioRXiv databases focusing on genetic association studies with Covid-19 prognosis or susceptibility. We found 20 eligible genetic association studies, of which 11 assessed Covid-19 outcome and 14 evaluated infection susceptibility (five analyzed both effects). Q-genie assessment indicated moderate quality. Five large-scale association studies (GWAS, whole-genome, or exome sequencing) were reported with no consistent replication to date. Promising hits were found on the 3p21.31 region and ABO locus. Candidate gene studies examined ACE1, ACE2, TMPRSS2, IFITM3, APOE, Furin, IFNL3, IFNL4, HLA, TNF-ɑ genes, and ABO system. The most evaluated single locus was the ABO, and the most sampled region was the HLA with three and five candidate gene studies, respectively. Meta-analysis could not be performed. Available data showed the need for further reports to replicate claimed associations.
Keyphrases
- coronavirus disease
- sars cov
- systematic review
- case control
- genome wide
- meta analyses
- copy number
- healthcare
- human health
- respiratory syndrome coronavirus
- rheumatoid arthritis
- endothelial cells
- gene expression
- machine learning
- clinical practice
- cognitive decline
- climate change
- metabolic syndrome
- transcription factor
- electronic health record
- drug induced
- social media
- health insurance
- angiotensin converting enzyme
- data analysis