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Butler-Laporte, Guillaume, Povysil, Gundula, Kosmicki, Jack, Cirulli, Elizabeth, Drivas, Theodore, Furini, Simone, Saad, Chadi, Schmidt, Axel, Olszewski, Pawel, Korotko, Urszula, Quinodoz, Mathieu, Çelik, Elifnaz, Kundu, Kousik, Walter, Klaudia, Jung, Junghyung, Stockwell, Amy, Sloofman, Laura, Charney, Alexander, Jordan, Daniel, Beckmann, Noam, Przychodzen, Bartlomiej, Chang, Timothy, Pottinger, Tess, Shang, Ning, Brand, Fabian, Fava, Francesca, Mari, Francesca, Chwialkowska, Karolina, Niemira, Magdalena, Pula, Szymon, Baillie, Kenneth, Stuckey, Alex, Ganna, Andrea, Karczewski, Konrad, Veerapen, Kumar, Bourgey, Mathieu, Bourque, Guillaume, Eveleigh, Robert J. M.; Forgetta, Vincenzo, Morrison, David, Langlais, David, Lathrop, Mark, Mooser, Vincent, Nakanishi, Tomoko, Frithiof, Robert, Hultström, Michael, Lipcsey, Miklos, Marincevic-Zuniga, Yanara, Nordlund, Jessica, Schiabor Barrett, Kelly, Lee, William, Bolze, Alexandre, White, Simon, Riffle, Stephen, Tanudjaja, Francisco, Sandoval, Efren, Neveux, Iva, Dabe, Shaun, Casadei, Nicolas, Motameny, Susanne, Alaamery, Manal, Massadeh, Salam, Aljawini, Nora, Almutairi, Mansour, Arabi, Yaseen, Alqahtan, Saleh, Al Harthi, Fawz, Almutairi, Amal, Alqubaishi, Fatima, Alotaibi, Sarah, Binowayn, Albandari, Alsolm, Ebtehal, Bardisy, Hadeel El, Fawzy, Mohammad, Geschwind, Daniel, Arteaga, Stephanie, Stephens, Alexis, Butte, Manish, Boutros, Paul, Yamaguchi, Takafumi, Tao, Shu, Eng, Stefan, Sanders, Timothy, Tung, Paul, Broudy, Michael, Pan, Yu, Gonzalez, Alfredo, Chavan, Nikhil, Johnson, Ruth, Pasaniuc, Bogdan, Yaspan, Brian, Smieszek, Sandra, Rivolta, Carlo, Bibert, Stephanie, Bochud, Pierre-Yves, Dabrowski, Maciej, Zawadzki, Pawel, Sypniewski, Mateusz, Kaja, Elżbieta, Chariyavilaskul, Pajaree, Nilaratanakul, Voraphoj, Hirankarn, Nattiya, Shotelersuk, Vorasuk, Pongpanich, Monnat, Phokaew, Chureerat, Chetruengchai, Wanna, Kawai, Yosuke, Hasegawa, Takanori, Naito, Tatsuhiko, Namkoong, Ho, Edahiro, Ryuya, Kimura, Akinori, Ogawa, Seishi, Kanai, Takanori, Fukunaga, Koichi, Okada, Yukinori, Imoto, Seiya, Miyano, Satoru, Mangul, Serghei, Abedalthagafi, Malak, Zeberg, Hugo, Grzymski, Joseph, Washington, Nicole, Ossowski, Stephan, Ludwig, Kerstin, Schulte, Eva, Riess, Olaf, Moniuszko, Marcin, Kwasniewski, Miroslaw, Mbarek, Hamdi, Ismail, Said, Verma, Anurag, Goldstein, David, Kiryluk, Krzysztof, Renieri, Alessandra, Ferreira, Manuel, Richards, Brent, Initiative, Covid- Host Genetics, De, C. O. I. Host Genetics Group, Study, Gen-Covid Multicenter, Gen, Omicc Consortium, Japan, Covid-Task Force, Regeneron Genetics, Center.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-332108

ABSTRACT

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,048 severe disease cases and 571,009 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p=5.41×10 -7 ). These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

2.
J Epidemiol Glob Health ; 12(1): 85-91, 2022 03.
Article in English | MEDLINE | ID: covidwho-1605573

ABSTRACT

BACKGROUND: Disease severity among patients infected with SARS-CoV-2 varies remarkably. Preliminary studies reported that the ABO blood group system confers differential viral susceptibility and disease severity caused by SARS-CoV-2. Thus, differences in ABO blood group phenotypes may partly explain the observed heterogeneity in COVID-19 severity patterns, and could help identify individuals at increased risk. Herein, we explored the association between ABO blood group phenotypes and COVID-19 susceptibility and severity in a Saudi Arabian cohort. METHODS: In this retrospective cohort study, we performed ABO typing on a total of 373 Saudi patients infected with SARS-CoV-2 and conducted association analysis between ABO blood group phenotype and COVID-19 infection severity. We then performed gender-stratified analysis by dividing the participating patients into two groups by gender, and classified them according to age. RESULTS: The frequencies of blood group phenotypes A, B, AB and O were 27.3, 23.6, 5.4 and 43.7%, respectively. We found that blood group phenotype O was associated with a lower risk of testing positive for COVID-19 infection (OR 0.76 95% CI 0.62-0.95, p = 0.0113), while blood group phenotype B was associated with higher odds of testing positive (OR 1.51 95% CI 1.17-1.93, p = 0.0009). However, blood group phenotype B was associated with increased risk in the mild and moderate group but not the severe COVID-19 infection group. Blood group phenotype O was protective in all severity groups. CONCLUSION: Our findings provide evidence that blood group phenotype B is a risk for COVID-19 disease while blood group phenotype O is protective from COVID-19 infection. However, further studies are necessary to validate these associations in a larger sample size and among individuals of different ethnic groups.


Subject(s)
ABO Blood-Group System , COVID-19 , ABO Blood-Group System/genetics , COVID-19/epidemiology , Humans , Phenotype , Retrospective Studies , SARS-CoV-2 , Saudi Arabia/epidemiology , Severity of Illness Index
3.
Clin Immunol ; 234: 108911, 2022 01.
Article in English | MEDLINE | ID: covidwho-1588089

ABSTRACT

BACKGROUND: Natural killer (NK) cells play an essential role against viruses. NK cells express killer cell immunoglobulin-like receptors (KIRs) which regulate their activity and function. The polymorphisms in KIR haplotypes confer differential viral susceptibility and disease severity caused by infections. We investigated the association between KIR genes and COVID-19 disease severity. METHODS: 424 COVID-19 positive patients were divided according to their disease severity into mild, moderate and severe. KIR genes were genotyped using next generation sequencing (NGS). Association between KIR genes and COVID-19 disease severity was conducted and significant correlations were reported. RESULTS: In the COVID-19 patients, KIR Bx genotype was more common than AA genotype. The Bx genotype was found more frequently in patients with mild disease, while in severe disease the AA genotype was more common than the Bx genotype. The KIR2DS4 gene carried the highest risk for severe COVID-19 infection (OR 8.48, pc= 0.0084) followed by KIR3DL1 (OR 7.61, pc= 0.0192). CONCLUSIONS: Our findings suggest that KIR2DS4 and KIR3DL1 genes carry risk for severe COVID-19 disease.


Subject(s)
COVID-19/genetics , Genetic Predisposition to Disease/genetics , Polymorphism, Genetic/genetics , Receptors, KIR/genetics , Adult , COVID-19/metabolism , Female , Gene Frequency/genetics , Genotype , Humans , Killer Cells, Natural/metabolism , Male , Middle Aged , SARS-CoV-2/pathogenicity
4.
J Clin Invest ; 131(14)2021 07 15.
Article in English | MEDLINE | ID: covidwho-1365266

ABSTRACT

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.


Subject(s)
COVID-19/genetics , COVID-19/immunology , Interferon Type I/genetics , Interferon Type I/immunology , Loss of Function Mutation , SARS-CoV-2 , Adolescent , Adult , Aged , Aged, 80 and over , Case-Control Studies , Child , Child, Preschool , Cohort Studies , Female , Genetic Association Studies , Genetic Predisposition to Disease , Humans , Infant , Infant, Newborn , Interferon Regulatory Factor-7/genetics , Male , Middle Aged , Severity of Illness Index , Toll-Like Receptor 3/genetics , Whole Exome Sequencing , Whole Genome Sequencing , Young Adult
5.
J Multidiscip Healthc ; 14: 2017-2033, 2021.
Article in English | MEDLINE | ID: covidwho-1346356

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in Wuhan, China, in late 2019 and created a global pandemic that overwhelmed healthcare systems. COVID-19, as of July 3, 2021, yielded 182 million confirmed cases and 3.9 million deaths globally according to the World Health Organization. Several patients who were initially diagnosed with mild or moderate COVID-19 later deteriorated and were reclassified to severe disease type. OBJECTIVE: The aim is to create a predictive model for COVID-19 ventilatory support and mortality early on from baseline (at the time of diagnosis) and routinely collected data of each patient (CXR, CBC, demographics, and patient history). METHODS: Four common machine learning algorithms, three data balancing techniques, and feature selection are used to build and validate predictive models for COVID-19 mechanical requirement and mortality. Baseline CXR, CBC, demographic, and clinical data were retrospectively collected from April 2, 2020, till June 18, 2020, for 5739 patients with confirmed PCR COVID-19 at King Abdulaziz Medical City in Riyadh. However, of those patients, only 1508 and 1513 have met the inclusion criteria for ventilatory support and mortalilty endpoints, respectively. RESULTS: In an independent test set, ventilation requirement predictive model with top 20 features selected with reliefF algorithm from baseline radiological, laboratory, and clinical data using support vector machines and random undersampling technique attained an AUC of 0.87 and a balanced accuracy of 0.81. For mortality endpoint, the top model yielded an AUC of 0.83 and a balanced accuracy of 0.80 using all features with balanced random forest. This indicates that with only routinely collected data our models can predict the outcome with good performance. The predictive ability of combined data consistently outperformed each data set individually for intubation and mortality. For the ventilator support, chest X-ray severity annotations alone performed better than comorbidity, complete blood count, age, or gender with an AUC of 0.85 and balanced accuracy of 0.79. For mortality, comorbidity alone achieved an AUC of 0.80 and a balanced accuracy of 0.72, which is higher than models that use either chest radiograph, laboratory, or demographic features only. CONCLUSION: The experimental results demonstrate the practicality of the proposed COVID-19 predictive tool for hospital resource planning and patients' prioritization in the current COVID-19 pandemic crisis.

6.
J Clin Invest ; 131(14)2021 07 15.
Article in English | MEDLINE | ID: covidwho-1247462

ABSTRACT

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.


Subject(s)
COVID-19/genetics , COVID-19/immunology , Interferon Type I/genetics , Interferon Type I/immunology , Loss of Function Mutation , SARS-CoV-2 , Adolescent , Adult , Aged , Aged, 80 and over , Case-Control Studies , Child , Child, Preschool , Cohort Studies , Female , Genetic Association Studies , Genetic Predisposition to Disease , Humans , Infant , Infant, Newborn , Interferon Regulatory Factor-7/genetics , Male , Middle Aged , Severity of Illness Index , Toll-Like Receptor 3/genetics , Whole Exome Sequencing , Whole Genome Sequencing , Young Adult
7.
Pharmaceutics ; 13(4)2021 Apr 06.
Article in English | MEDLINE | ID: covidwho-1178386

ABSTRACT

Sialic acid that presents on the surface of lung epithelial cells is considered as one of the main binding targets for many respiratory viruses, including influenza and the current coronavirus (SARS-CoV-2) through the viral surface protein hemagglutinin. Gold nanoparticles (Au NPs) are extensively used in the diagnostic field owing to a phenomenon known as 'surface plasmonic resonance' in which the scattered light is absorbed by these NPs and can be detected via UV-Vis spectrophotometry. Consequently, sialic acid conjugated Au NPs (SA-Au NPs) were utilized for their plasmonic effect against SARS-CoV-2, influenza B virus, and Middle-East respiratory syndrome-related coronavirus (MERS) in patients' swab samples. The SA-Au NPs system was prepared by a one-pot synthesis method, through which the NPs solution color changed from pale yellow to dark red wine color, indicting its successful preparation. In addition, the SA-Au NPs had an average particle size of 30 ± 1 nm, negative zeta potential (-30 ± 0.3 mV), and a UV absorbance of 525 nm. These NPs have proven their ability to change the color of the NPs solutions and patients' swabs that contain SARS-CoV-2, influenza B, and MERS viruses, suggesting a rapid and straightforward detection tool that would reduce the spread of these viral infections and accelerate the therapeutic intervention.

8.
Genomics ; 113(4): 1733-1741, 2021 07.
Article in English | MEDLINE | ID: covidwho-1171554

ABSTRACT

Interferon-induced membrane proteins (IFITM) 3 gene variants are known risk factor for severe viral diseases. We examined whether IFITM3 variant may underlie the heterogeneous clinical outcomes of SARS-CoV-2 infection-induced COVID-19 in large Arab population. We genotyped 880 Saudi patients; 93.8% were PCR-confirmed SARS-CoV-2 infection, encompassing most COVID-19 phenotypes. Mortality at 90 days was 9.1%. IFITM3-SNP, rs12252-G allele was associated with hospital admission (OR = 1.65 [95% CI; 1.01-2.70], P = 0.04]) and mortality (OR = 2.2 [95% CI; 1.16-4.20], P = 0.01). Patients less than 60 years old had a lower survival probability if they harbor this allele (log-rank test P = 0.002). Plasma levels of IFNγ were significantly lower in a subset of patients with AG/GG genotypes than patients with AA genotype (P = 0.00016). Early identification of these individuals at higher risk of death may inform precision public health response.


Subject(s)
COVID-19/genetics , Genetic Predisposition to Disease , Membrane Proteins/genetics , RNA-Binding Proteins/genetics , SARS-CoV-2/genetics , Adult , Aged , Aged, 80 and over , COVID-19/mortality , COVID-19/virology , Female , Genetic Association Studies , Genotype , Humans , Interferons/genetics , Male , Middle Aged , Polymorphism, Single Nucleotide/genetics , SARS-CoV-2/pathogenicity
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