Rare Variants in Inborn Errors of Immunity Genes Associated with Covid-19 Severity (preprint)

Covid-19 is a contagious disease caused by SARS-CoV-2, a novel severe acute respiratory syndrome coronavirus. Common variants and networks underlying host genetic mechanisms have been extensively studied to identify disease-associated genetic factors. However, there are few studies about the rare variants, typically inborn errors of immunity, in understanding the host genetics behind Covid-19 infection, especially in the Chinese population. To fill this gap, we investigate likely-deleterious missense and high-confidence predicted loss-of-function variants by (a) performing gene- and pathway-level association analyses, (b) examining known genes involved in type I interferon signaling and others previously reported in Covid-19 disease, and (c) identifying candidate genes with accumulating mutations and their potential protein-protein interactions with known genes. Based on our analyses, several putative genes and pathways are uncovered and worth further investigation, for example, genes IL12RB1, TBK1, and TLR3, and pathways Tuberculosis (hsa:05152), Primary Immunodeficiency (hsa:05340), and Influenza A (hsa:05164). These regions generally play an essential role in regulating antiviral innate immunity responses to foreign pathogens and in responding to many inflammatory diseases. We believe that to some extent, as an acute inflammatory disease, Covid-19 is also affected by these inborn errors of immunity. We hope that the identification of these rare genetic factors will provide new insights into the genetic architecture of Covid-19.

A Chinese host genetic study discovered type I interferons and causality of cholesterol levels and WBC counts on COVID-19 severity (preprint)

As of early May 2021, the ongoing pandemic COVID-19 has caused over 160 million of infections and over 3 million deaths worldwide. Many risk factors, such as age, gender, and comorbidities, have been studied to explain the variable symptoms of infected patients. However, these effects may not fully account for the diversity in disease severity. Here, we present a comprehensive analysis of a broad range of patients laboratory and clinical assessments to investigate the genetic contributions to COVID-19 severity. By performing GWAS analysis, we discovered several concrete associations for laboratory features. Based on these findings, we performed Mendelian randomization (MR) analysis to investigate the causality of laboratory traits on disease severity. From the MR study, we identified two causal traits, cholesterol levels and WBC counts. The functional gene related to cholesterol levels is ApoE and people with particular ApoE genotype are more likely to have higher cholesterol levels, facilitating the process that SARS-CoV-2 binds on its receptor ACE2 and aggravating COVID-19 disease. The functional gene related to WBC counts is MHC system that plays a central role in the immune system. The host immune response to the SARS-CoV-2 infection greatly affects the patients severity status and clinical outcome. Additionally, our gene-based and GSEA analysis revealed interferon pathways, including type I interferon receptor binding, regulation of IFNA signaling, and SARS coronavirus and innate immunity. We hope that our work will make a contribution in studying the genetic mechanisms of disease illness and serve as useful reference for the clinical diagnosis and treatment of COVID-19.

The Trans-omics Landscape of COVID-19 (preprint)

The outbreak of coronavirus disease 2019 (COVID-19) has been causing a global health emergency. Although previous studies investigated COVID-19 at different omics levels, the molecular hallmarks of COVID-19, especially in those patients without comorbidities, have not been fully investigated. Here, we presented a trans-omics landscape for COVID-19 based on integrative analysis of genomic, transcriptomic, proteomic, metabolomic and lipidomic profiles from blood samples of 231 COVID-19 patients, ranging from asymptomatic to critically ill, importantly excluding those with any comorbidities. Notably, we found neutrophils heterogeneity existed between asymptomatic and critically ill patients. Expression discordance of inflammatory cytokines at mRNA and protein levels in asymptomatic patients could possibly be explained by post-transcriptional regulation by RNA binding proteins (RBPs) and microRNAs. Neutrophils over-activation, induced arginine depletion, and tryptophan metabolites accumulation contributed to T/NK cell dysfunction in critical patients. Anti-virus interferons were gradually suppressed along with disease severity. Overall, our study systematically revealed multi-omics characteristics of COVID-19, and the data we generated could hopefully help illuminate COVID-19 pathogenesis and provide valuable clues about potential therapeutic strategies for COVID-19.

The Trans-omics Landscape of COVID-19 (preprint)

System-wide molecular characteristics of COVID-19, especially in those patients without comorbidities, have not been fully investigated. We compared extensive molecular profiles of blood samples from 231 COVID-19 patients, ranging from asymptomatic to critically ill, importantly excluding those with any comorbidities. Amongst the major findings, asymptomatic patients were characterized by highly activated anti-virus interferon, T/natural killer (NK) cell activation, and transcriptional upregulation of inflammatory cytokine mRNAs. However, given very abundant RNA binding proteins (RBPs), these cytokine mRNAs could be effectively destabilized hence preserving normal cytokine levels. In contrast, in critically ill patients, cytokine storm due to RBPs inhibition and tryptophan metabolites accumulation contributed to T/NK cell dysfunction. A machine-learning model was constructed which accurately stratified the COVID-19 severities based on their multi-omics features. Overall, our analysis provides insights into COVID-19 pathogenesis and identifies targets for intervening in treatment.

Initial Study of Human Genetic Contribution to COVID-19 Severity and Susceptibility (preprint)

The COVID-19 pandemic has accounted for more than five million infections and hundreds of thousand deaths worldwide in the past six months. The patients demonstrate a great diversity in clinical and laboratory manifestations and disease severity. Nonetheless, little is known about the host genetic contribution to the observed inter-individual phenotypic variability. Here, we report the first host genetic study in China by deeply sequencing and analyzing 332 COVID-19 patients categorized by varying levels of severity from the Shenzhen Third Peoples Hospital. Upon a total of 22.2 million genetic variants, we conducted both single-variant and gene-based association tests among five severity groups including asymptomatic, mild, moderate, severe and critical ill patients after the correction of potential confounding factors. The most significant gene locus associated with severity is located in TMEM189-UBE2V1 involved in the IL-1 signaling pathway. The p.Val197Met missense variant that affects the stability of the TMPRSS2 protein displays a decreasing allele frequency among the severe patients compared to the mild and the general population. We also identified that the HLA-A*11:01, B*51:01 and C*14:02 alleles significantly predispose the worst outcome of the patients. This initial study of Chinese patients provides a comprehensive view of the genetic difference among the COVID-19 patient groups and highlighted genes and variants that may help guide targeted efforts in containing the outbreak. Limitations and advantages of the study were also reviewed to guide future international efforts on elucidating the genetic architecture of host-pathogen interaction for COVID-19 and other infectious and complex diseases.