Genetic variants in the NF-κB signaling pathway (NFKB1, NFKBIA, NFKBIZ) and risk of critical outcome among COVID-19 patients.

The NF-κB signaling pathway is a key regulator of inflammation in the response to SARS-CoV-2 infection. This pathway has been implicated in the hyperinflammatory state that characterizes the severe forms of COVID-19. The genetic variation of the NF-κB components might thus explain the predisposition to critical outcomes of this viral disease. We aimed to study the role of the common NFKB1 rs28362491, NFKBIA rs696 and NFKBIZ rs3217713 variants in the risk of developing severe COVID-19 with ICU admission. A total of 470 Spanish patients requiring respiratory support in the ICU were studied (99 deceased and 371 survivors). Compared to healthy population controls (N = 300), the NFKBIA rs696 GG genotype was increased in the patients (p = 0.045; OR = 1.37). The NFKBIZ rs3217713 insertion homozygosis was associated with a significant risk of death (p = 0.02; OR = 1.76) and was also related to increased D-dimer values (p = 0.0078, OR = 1.96). This gene has been implicated in sepsis in mice and rats. Moreover, we found a trend toward lower expression of the NFKBIZ transcript in total blood from II patients. In conclusion, variants in the NF-κB genes might be associated with the risk of developing severe COVID-19, with a significant effect of the NFKBIZ gene on mortality. Our results were based on a limited number of patients and require validation in larger cohorts from other populations.

Systematic comparison of published host gene expression signatures for bacterial/viral discrimination.

BACKGROUND: Measuring host gene expression is a promising diagnostic strategy to discriminate bacterial and viral infections. Multiple signatures of varying size, complexity, and target populations have been described. However, there is little information to indicate how the performance of various published signatures compare to one another. METHODS: This systematic comparison of host gene expression signatures evaluated the performance of 28 signatures, validating them in 4589 subjects from 51 publicly available datasets. Thirteen COVID-specific datasets with 1416 subjects were included in a separate analysis. Individual signature performance was evaluated using the area under the receiving operating characteristic curve (AUC) value. Overall signature performance was evaluated using median AUCs and accuracies. RESULTS: Signature performance varied widely, with median AUCs ranging from 0.55 to 0.96 for bacterial classification and 0.69-0.97 for viral classification. Signature size varied (1-398 genes), with smaller signatures generally performing more poorly (P < 0.04). Viral infection was easier to diagnose than bacterial infection (84% vs. 79% overall accuracy, respectively; P < .001). Host gene expression classifiers performed more poorly in some pediatric populations (3 months-1 year and 2-11 years) compared to the adult population for both bacterial infection (73% and 70% vs. 82%, respectively; P < .001) and viral infection (80% and 79% vs. 88%, respectively; P < .001). We did not observe classification differences based on illness severity as defined by ICU admission for bacterial or viral infections. The median AUC across all signatures for COVID-19 classification was 0.80 compared to 0.83 for viral classification in the same datasets. CONCLUSIONS: In this systematic comparison of 28 host gene expression signatures, we observed differences based on a signature's size and characteristics of the validation population, including age and infection type. However, populations used for signature discovery did not impact performance, underscoring the redundancy among many of these signatures. Furthermore, differential performance in specific populations may only be observable through this type of large-scale validation.

A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program.

The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n = 35) or hospitalization (n = 42) due to severe COVID-19 using genome-wide association summary data from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (nrs495828 = 53 and nrs505922 = 59); strongest association with venous embolism, odds ratio (ORrs495828 1.33 (p = 1.32 x 10-199), and thrombosis ORrs505922 1.33, p = 2.2 x10-265. Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p = 4.12 × 10-191; CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p = 2.26× 10-12. The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p = 6.48 x10-23, lupus OR 0.84, p = 3.97 x 10-06. PheWAS stratified by ancestry demonstrated differences in genotype-phenotype associations. LMNA (rs581342) associated with neutropenia OR 1.29 p = 4.1 x 10-13 among Veterans of African and Hispanic ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets.

dbGSRV: A manually curated database of genetic susceptibility to respiratory virus.

Human genetics has been proposed to play an essential role in inter-individual differences in respiratory virus infection occurrence and outcomes. To systematically understand human genetic contributions to respiratory virus infection, we developed the database dbGSRV, a manually curated database that integrated the host genetic susceptibility and severity studies of respiratory viruses scattered over literatures in PubMed. At present, dbGSRV contains 1932 records of genetic association studies relating 1010 unique variants and seven respiratory viruses, manually curated from 168 published articles. Users can access the records by quick searching, batch searching, advanced searching and browsing. Reference information, infection status, population information, mutation information and disease relationship are provided for each record, as well as hyperlinks to public databases in convenient of users accessing more information. In addition, a visual overview of the topological network relationship between respiratory viruses and associated genes is provided. Therefore, dbGSRV offers a convenient resource for researchers to browse and retrieve genetic associations with respiratory viruses, which may inspire future studies and provide new insights in our understanding and treatment of respiratory virus infection. Database URL: http://www.ehbio.com/dbGSRV/front/.

The 90 plus: longevity and COVID-19 survival.

The world population is getting older and studies aiming to enhance our comprehension of the underlying mechanisms responsible for health span are of utmost interest for longevity and as a measure for health care. In this review, we summarized previous genetic association studies (GWAS) and next-generation sequencing (NGS) of elderly cohorts. We also present the updated hypothesis for the aging process, together with the factors associated with healthy aging. We discuss the relevance of studying older individuals and build databanks to characterize the presence and resistance against late-onset disorders. The identification of about 2 million novel variants in our cohort of more than 1000 elderly Brazilians illustrates the importance of studying highly admixed populations of non-European ancestry. Finally, the ascertainment of nonagenarians and particularly of centenarians who were recovered from COVID-19 or remained asymptomatic opens new avenues of research aiming to enhance our comprehension of biological mechanisms associated with resistance against pathogens.

APOE ε4 associates with increased risk of severe COVID-19, cerebral microhaemorrhages and post-COVID mental fatigue: a Finnish biobank, autopsy and clinical study.

Apolipoprotein E ε4 allele (APOE4) has been shown to associate with increased susceptibility to SARS-CoV-2 infection and COVID-19 mortality in some previous genetic studies, but information on the role of APOE4 on the underlying pathology and parallel clinical manifestations is scarce. Here we studied the genetic association between APOE and COVID-19 in Finnish biobank, autopsy and prospective clinical cohort datasets. In line with previous work, our data on 2611 cases showed that APOE4 carriership associates with severe COVID-19 in intensive care patients compared with non-infected population controls after matching for age, sex and cardiovascular disease status. Histopathological examination of brain autopsy material of 21 COVID-19 cases provided evidence that perivascular microhaemorrhages are more prevalent in APOE4 carriers. Finally, our analysis of post-COVID fatigue in a prospective clinical cohort of 156 subjects revealed that APOE4 carriership independently associates with higher mental fatigue compared to non-carriers at six months after initial illness. In conclusion, the present data on Finns suggests that APOE4 is a risk factor for severe COVID-19 and post-COVID mental fatigue and provides the first indication that some of this effect could be mediated via increased cerebrovascular damage. Further studies in larger cohorts and animal models are warranted.

Mapping the proteo-genomic convergence of human diseases.

Characterization of the genetic regulation of proteins is essential for understanding disease etiology and developing therapies. We identified 10,674 genetic associations for 3892 plasma proteins to create a cis-anchored gene-protein-disease map of 1859 connections that highlights strong cross-disease biological convergence. This proteo-genomic map provides a framework to connect etiologically related diseases, to provide biological context for new or emerging disorders, and to integrate different biological domains to establish mechanisms for known gene-disease links. Our results identify proteo-genomic connections within and between diseases and establish the value of cis-protein variants for annotation of likely causal disease genes at loci identified in genome-wide association studies, thereby addressing a major barrier to experimental validation and clinical translation of genetic discoveries.

Aging whole blood transcriptome reveals candidate genes for SARS-CoV-2-related vascular and immune alterations.

The risk of severe COVID-19 increases with age as older patients are at highest risk. Thus, there is an urgent need to identify how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) interacts with blood components during aging. We investigated the whole blood transcriptome from the Genotype-Tissue Expression (GTEx) database to explore differentially expressed genes (DEGs) translated into proteins interacting with viral proteins during aging. From 22 DEGs in aged blood, FASLG, CTSW, CTSE, VCAM1, and BAG3 were associated with immune response, inflammation, cell component and adhesion, and platelet activation/aggregation. Males and females older than 50 years old overexpress FASLG, possibly inducing a hyperinflammatory cascade. The expression of cathepsins (CTSW and CTSE) and the anti-apoptotic co-chaperone molecule BAG3 also increased throughout aging in both genders. By exploring single-cell RNA-sequencing data from peripheral blood of SARS-CoV-2-infected patients, we found FASLG and CTSW expressed in natural killer cells and CD8 + T lymphocytes, whereas BAG3 was expressed mainly in CD4 + T cells, naive T cells, and CD14 + monocytes. In addition, T cell exhaustion was associated with increased expression of CCL4L2 and DUSP4 over blood aging. LAG3, PDCD1, TIGIT, VCAM1, HLA-DRA, and TOX also increased in individuals aged 60-69 years old; conversely, the RGS2 gene decreased with aging. We further identified a distinct gene expression profile associated with type I interferon signaling following blood aging. These results revealed changes in blood molecules potentially related to SARS-CoV-2 infection throughout aging, emphasizing them as therapeutic candidates for aggressive clinical manifestation of COVID-19. KEY MESSAGES: • Prediction of host-viral interactions in the whole blood transcriptome during aging. • Expression levels of FASLG, CTSW, CTSE, VCAM1, and BAG3 increase in aged blood. • Blood interactome reveals targets involved with immune response, inflammation, and blood clots. • SARS-CoV-2-infected patients with high viral load showed FASLG overexpression. • Gene expression profile associated with T cell exhaustion and type I interferon signaling were affected with blood aging.

Medical Significance of Uterine Corpus Endometrial Carcinoma Patients Infected With SARS-CoV-2 and Pharmacological Characteristics of Plumbagin.

Background: Clinically, evidence shows that uterine corpus endometrial carcinoma (UCEC) patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may have a higher death-rate. However, current anti-UCEC/coronavirus disease 2019 (COVID-19) treatment is lacking. Plumbagin (PLB), a pharmacologically active alkaloid, is an emerging anti-cancer inhibitor. Accordingly, the current report was designed to identify and characterize the anti-UCEC function and mechanism of PLB in the treatment of patients infected with SARS-CoV-2 via integrated in silico analysis. Methods: The clinical analyses of UCEC and COVID-19 in patients were conducted using online-accessible tools. Meanwhile, in silico methods including network pharmacology and biological molecular docking aimed to screen and characterize the anti-UCEC/COVID-19 functions, bio targets, and mechanisms of the action of PLB. Results: The bioinformatics data uncovered the clinical characteristics of UCEC patients infected with SARS-CoV-2, including specific genes, health risk, survival rate, and prognostic index. Network pharmacology findings disclosed that PLB-exerted anti-UCEC/COVID-19 effects were achieved through anti-proliferation, inducing cytotoxicity and apoptosis, anti-inflammation, immunomodulation, and modulation of some of the key molecular pathways associated with anti-inflammatory and immunomodulating actions. Following molecular docking analysis, in silico investigation helped identify the anti-UCEC/COVID-19 pharmacological bio targets of PLB, including mitogen-activated protein kinase 3 (MAPK3), tumor necrosis factor (TNF), and urokinase-type plasminogen activator (PLAU). Conclusions: Based on the present bioinformatic and in silico findings, the clinical characterization of UCEC/COVID-19 patients was revealed. The candidate, core bio targets, and molecular pathways of PLB action in the potential treatment of UCEC/COVID-19 were identified accordingly.

Polymorphisms of ACE (I/D) and ACE2 receptor gene (Rs2106809, Rs2285666) are not related to the clinical course of COVID-19: A case study.

Coronavirus disease 2019 (COVID-19) is an infectious disease, and the reason behind the currently ongoing pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Angiotensin-converting enzyme (ACE2) has been recognized as the specific receptor of the SARS-CoV-2 virus. Although the possible effect of ACE2 gene polymorphism remains unknown, human ACE2 receptor expression influences SARS-CoV-2 susceptibility and COVID-19 disease outcome. In this study, we aimed to investigate the relationship between ACE gene I/D polymorphism, ACE2 receptor gene polymorphism, and COVID-19 severity. ACE gene insertion/deletion (I/D) polymorphism and ACE2 receptor gene rs2106809 and rs2285666 polymorphisms were determined using polymerase chain reaction (PCR) and PCR-based restriction fragment length polymorphism methods, respectively, in 155 COVID-19 patients who were divided into three groups (mild, moderate, and severe) according to clinical symptoms. However, the distribution of genotype and allele frequencies of ACE gene I/D, ACE2 receptor gene rs2106809, and rs2285666 polymorphisms were not statistically significant in all groups. In conclusion, in the study population, ACE gene I/D, ACE2 receptor gene rs2106809, and rs2285666 polymorphisms were not associated with the severity of COVID-19 infection. Although ACE2 receptor gene expression may affect the susceptibility to COVID-19, there is no existing evidence that the ACE or ACE2 gene polymorphisms are directly associated with COVID-19 severity. Interindividual differences in COVID-19 severity might be related to epigenetic mechanisms of ACE2 receptor gene expression or variations in other genes suggested to play a critical role in COVID-19 pathogenesis such as pro-inflammatory cytokines and coagulation indicators.

Correlation between interleukin gene polymorphisms and current prevalence and mortality rates due to novel coronavirus disease 2019 (COVID-2019) in 23 countries.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) infection may rely on a potential genetic background for the variations in the inflammatory response. We aimed to investigate the possible correlation between polymorphisms in the IL-6 gene at rs1800796/rs1800795, in IL-6R at rs2228145, in IL-10 at rs1800896 and rs1800871, in IL-17 at rs2275913 and rs763780 loci, and COVID-19 prevalence and mortality rates among populations of 23 countries. METHODS: We searched the literature for polymorphisms in China, Japan, India, Spain, Mexico, Sweden, Turkey, Brazil, Russia, Poland, Italy, South Africa, Netherlands, Greece, Germany, UK, Iran, Finland, Czechia, Tunisia, Norway, Egypt, Croatia. We recorded the prevalence and mortality rates (per million) caused by the Coronavirus infection recorded on 7th September 2020 and 6th December 2020. RESULTS: There was a significant positive correlation between the frequency of AG genotype of rs1800896 and prevalence recorded on 6th December 2020 (r: 0.53, r2 : 0.28, p < .05). There was a significant negative correlation between the mortality rates recorded on 7th September, and the AG genotype of rs2275913 (r: -0.51, r2 : 0.26, p < .05). There was a significant positive correlation between the prevalence recorded on 6th December, and TT genotype at rs763780 (r: 0.65, r2 :0.42, p < .05) while a negative correlation between prevalence and TC genotype at rs763780 (r: -0.66, r2 : 0.43, p < .05). Also, a significant negative correlation was found between mortality rates recorded on 6th December 2020 and CC genotype at rs763780 (r: -0.56, r2 : 0.31, p < .05). CONCLUSION: The variations in prevalence of COVID-19 and its mortality rates among countries may be explained by the polymorphisms at rs1800896 in IL-10, rs2275913 in IL-17A, and rs763780 loci in the IL-17F gene.

Human Ace D/I Polymorphism Could Affect the Clinicobiological Course of COVID-19.

INTRODUCTION: The coronavirus disease 2019 (COVID-19), that is caused by severe acute respiratory syndrome corona virus 2 (SARS-CoV-2), has spread rapidly worldwide since December 2019. The SARS-CoV-2 virus has a great affinity for the angiotensin-converting enzyme-2 (ACE-2) receptor, which is an essential element of the renin-angiotensin system (RAS). This study is aimed at assessing the impact of the angiotensin-converting enzyme (ACE) gene insertion (I)/deletion (D) polymorphisms, on the susceptibility and clinical outcomes of the COVID-19 immunoinflammatory syndrome. Patients and Methods. A total of 112 patients diagnosed with COVID-19 between 1 and 15 May 2020 were enrolled in the study. ACE gene allele frequencies were compared to the previously reported Turkish population comprised of 300 people. RESULTS: The most common genotype in the patients and control group was DI with 53% and II with 42%, respectively. The difference in the presence of the D allele between the patient and control groups was statistically significant (67% vs. 42%, respectively, p < 0.0001). Severe pneumonia was observed more in patients with DI allele (31%) than DD (8%) and II (0%) (p = 0.021). The mortality rate, time to defervescence, and the hospitalization duration were not different between the genotype groups. CONCLUSION: Genotype DI of ACE I/D polymorphism is associated with the infectious rate particularly severe pneumonia in this study conducted in the Turkish population. Therefore, ACE D/I polymorphism could affect the clinical course of COVID-19.

A Global Effort to Define the Human Genetics of Protective Immunity to SARS-CoV-2 Infection.

SARS-CoV-2 infection displays immense inter-individual clinical variability, ranging from silent infection to lethal disease. The role of human genetics in determining clinical response to the virus remains unclear. Studies of outliers-individuals remaining uninfected despite viral exposure and healthy young patients with life-threatening disease-present a unique opportunity to reveal human genetic determinants of infection and disease.

Rare loss-of-function variants in type I IFN immunity genes are not associated with severe COVID-19.

A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,864 COVID-19 cases (713 with severe and 1,151 with mild disease) and 15,033 ancestry-matched population controls across 4 independent COVID-19 biobanks. We tested whether rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only 1 rare pLOF mutation across these genes among 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We found no evidence of association of rare LOF variants in the 13 candidate genes with severe COVID-19 outcomes.

Association between the HLA genotype and the severity of COVID-19 infection among South Asians.

Regional variations are found in the incidence and severity of the COVID-19 infection. Human leukocyte antigen (HLA) polymorphism is one of the genetic factors that might have an impact on the outcome of the disease. This study explored the association between the HLA genotype and the severity of COVID-19 among patients from South Asia. Blood samples from 95 Asians (Bangladeshis, Indians, and Pakistanis) with COVID-19 were collected. The patients were divided according to the severity of their infection: mild (N = 64), severe (N = 31), and fatal (N = 20). DNA was extracted from all samples, and HLA genotyping was performed for both class I (A, B, and C) and class II (DRB1, DQA1, and DQB1) using the PCR-rSSO (polymerase chain reaction-reverse sequence-specific oligonucleotide) molecular method. The frequency of HLA-B*51 was significantly higher among patients in the fatal group than among those in the mild infection group (15% vs. 4.7%, p = 0.027). Additionally, the frequency of HLA-B*35 was significantly higher in the mild infection group than in the fatal group (21.1% vs. 7.5%, p = 0.050 [a borderline p-value]). In terms of HLA class II, DRB1*13 was significantly observed in the fatal group than in the mild infection group (17.5% vs. 11.3%, p = 0.049). However, the p-value for all alleles became insignificant after a statistical correction for the p-values (pc = 0.216, pc = 0.4, and pc = 0.49, respectively). Compared with all published data, this study highlights that the association between the HLA system and the COVID-19 outcome might be ethnic-dependent. Genetic variation between populations must be examined on a wider scale to assess infection prognosis and vaccine effectiveness.

MHC Haplotyping of SARS-CoV-2 Patients: HLA Subtypes Are Not Associated with the Presence and Severity of COVID-19 in the Israeli Population.

HLA haplotypes were found to be associated with increased risk for viral infections or disease severity in various diseases, including SARS. Several genetic variants are associated with COVID-19 severity. Studies have proposed associations, based on a very small sample and a large number of tested HLA alleles, but no clear association between HLA and COVID-19 incidence or severity has been reported. We conducted a large-scale HLA analysis of Israeli individuals who tested positive for SARS-CoV-2 infection by PCR. Overall, 72,912 individuals with known HLA haplotypes were included in the study, of whom 6413 (8.8%) were found to have SARS-CoV-2 by PCR. A total of 20,937 subjects were of Ashkenazi origin (at least 2/4 grandparents). One hundred eighty-one patients (2.8% of the infected) were hospitalized due to the disease. None of the 66 most common HLA loci (within the five HLA subgroups: A, B, C, DQB1, DRB1) was found to be associated with SARS-CoV-2 infection or hospitalization in the general Israeli population. Similarly, no association was detected in the Ashkenazi Jewish subset. Moreover, no association was found between heterozygosity in any of the HLA loci and either infection or hospitalization. We conclude that HLA haplotypes are not a major risk/protecting factor among the Israeli population for SARS-CoV-2 infection or severity. Our results suggest that if any HLA association exists with the disease it is very weak, and of limited effect on the pandemic.

HLA-A*11:01:01:01, HLA-C*12:02:02:01-HLA-B*52:01:02:02, Age and Sex Are Associated With Severity of Japanese COVID-19 With Respiratory Failure.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing coronavirus disease 2019 (COVID-19) was announced as an outbreak by the World Health Organization (WHO) in January 2020 and as a pandemic in March 2020. The majority of infected individuals have experienced no or only mild symptoms, ranging from fully asymptomatic cases to mild pneumonic disease. However, a minority of infected individuals develop severe respiratory symptoms. The objective of this study was to identify susceptible HLA alleles and clinical markers that can be used in risk prediction model for the early identification of severe COVID-19 among hospitalized COVID-19 patients. A total of 137 patients with mild COVID-19 (mCOVID-19) and 53 patients with severe COVID-19 (sCOVID-19) were recruited from the Center Hospital of the National Center for Global Health and Medicine (NCGM), Tokyo, Japan for the period of February-August 2020. High-resolution sequencing-based typing for eight HLA genes was performed using next-generation sequencing. In the HLA association studies, HLA-A*11:01:01:01 [Pc = 0.013, OR = 2.26 (1.27-3.91)] and HLA-C*12:02:02:01-HLA-B*52:01:01:02 [Pc = 0.020, OR = 2.25 (1.24-3.92)] were found to be significantly associated with the severity of COVID-19. After multivariate analysis controlling for other confounding factors and comorbidities, HLA-A*11:01:01:01 [P = 3.34E-03, OR = 3.41 (1.50-7.73)], age at diagnosis [P = 1.29E-02, OR = 1.04 (1.01-1.07)] and sex at birth [P = 8.88E-03, OR = 2.92 (1.31-6.54)] remained significant. The area under the curve of the risk prediction model utilizing HLA-A*11:01:01:01, age at diagnosis, and sex at birth was 0.772, with sensitivity of 0.715 and specificity of 0.717. To the best of our knowledge, this is the first article that describes associations of HLA alleles with COVID-19 at the 4-field (highest) resolution level. Early identification of potential sCOVID-19 could help clinicians prioritize medical utility and significantly decrease mortality from COVID-19.