Genome‐wide association analysis of COVID‐19 mortality risk in SARS‐CoV‐2 genomes identifies mutation in the SARS‐CoV‐2 spike protein that colocalizes with P.1 of the Brazilian strain

SARS‐CoV‐2 mortality has been extensively studied in relation to host susceptibility. How sequence variations in the SARS‐CoV‐2 genome affect pathogenicity is poorly understood. Starting in October 2020, using the methodology of genome‐wide association studies (GWAS), we looked at the association be...

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Veröffentlicht in:Genetic epidemiology 2021-10, Vol.45 (7), p.685-693
Hauptverfasser: Hahn, Georg, Wu, Chloe M., Lee, Sanghun, Lutz, Sharon M., Khurana, Surender, Baden, Lindsey R., Haneuse, Sebastien, Qiao, Dandi, Hecker, Julian, DeMeo, Dawn L., Tanzi, Rudolph E., Choudhary, Manish C., Etemad, Behzad, Mohammadi, Abbas, Esmaeilzadeh, Elmira, Cho, Michael H., Li, Jonathan Z., Randolph, Adrienne G., Laird, Nan M., Weiss, Scott T., Silverman, Edwin K., Ribbeck, Katharina, Lange, Christoph
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container_end_page 693
container_issue 7
container_start_page 685
container_title Genetic epidemiology
container_volume 45
creator Hahn, Georg
Wu, Chloe M.
Lee, Sanghun
Lutz, Sharon M.
Khurana, Surender
Baden, Lindsey R.
Haneuse, Sebastien
Qiao, Dandi
Hecker, Julian
DeMeo, Dawn L.
Tanzi, Rudolph E.
Choudhary, Manish C.
Etemad, Behzad
Mohammadi, Abbas
Esmaeilzadeh, Elmira
Cho, Michael H.
Li, Jonathan Z.
Randolph, Adrienne G.
Laird, Nan M.
Weiss, Scott T.
Silverman, Edwin K.
Ribbeck, Katharina
Lange, Christoph
description SARS‐CoV‐2 mortality has been extensively studied in relation to host susceptibility. How sequence variations in the SARS‐CoV‐2 genome affect pathogenicity is poorly understood. Starting in October 2020, using the methodology of genome‐wide association studies (GWAS), we looked at the association between whole‐genome sequencing (WGS) data of the virus and COVID‐19 mortality as a potential method of early identification of highly pathogenic strains to target for containment. Although continuously updating our analysis, in December 2020, we analyzed 7548 single‐stranded SARS‐CoV‐2 genomes of COVID‐19 patients in the GISAID database and associated variants with mortality using a logistic regression. In total, evaluating 29,891 sequenced loci of the viral genome for association with patient/host mortality, two loci, at 12,053 and 25,088 bp, achieved genome‐wide significance (p values of 4.09e−09 and 4.41e−23, respectively), though only 25,088 bp remained significant in follow‐up analyses. Our association findings were exclusively driven by the samples that were submitted from Brazil (p value of 4.90e−13 for 25,088 bp). The mutation frequency of 25,088 bp in the Brazilian samples on GISAID has rapidly increased from about 0.4 in October/December 2020 to 0.77 in March 2021. Although GWAS methodology is suitable for samples in which mutation frequencies varies between geographical regions, it cannot account for mutation frequencies that change rapidly overtime, rendering a GWAS follow‐up analysis of the GISAID samples that have been submitted after December 2020 as invalid. The locus at 25,088 bp is located in the P.1 strain, which later (April 2021) became one of the distinguishing loci (precisely, substitution V1176F) of the Brazilian strain as defined by the Centers for Disease Control. Specifically, the mutations at 25,088 bp occur in the S2 subunit of the SARS‐CoV‐2 spike protein, which plays a key role in viral entry of target host cells. Since the mutations alter amino acid coding sequences, they potentially imposing structural changes that could enhance viral infectivity and symptom severity. Our analysis suggests that GWAS methodology can provide suitable analysis tools for the real‐time detection of new more transmissible and pathogenic viral strains in databases such as GISAID, though new approaches are needed to accommodate rapidly changing mutation frequencies over time, in the presence of simultaneously changing case/control ratios. Improvements of
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How sequence variations in the SARS‐CoV‐2 genome affect pathogenicity is poorly understood. Starting in October 2020, using the methodology of genome‐wide association studies (GWAS), we looked at the association between whole‐genome sequencing (WGS) data of the virus and COVID‐19 mortality as a potential method of early identification of highly pathogenic strains to target for containment. Although continuously updating our analysis, in December 2020, we analyzed 7548 single‐stranded SARS‐CoV‐2 genomes of COVID‐19 patients in the GISAID database and associated variants with mortality using a logistic regression. In total, evaluating 29,891 sequenced loci of the viral genome for association with patient/host mortality, two loci, at 12,053 and 25,088 bp, achieved genome‐wide significance (p values of 4.09e−09 and 4.41e−23, respectively), though only 25,088 bp remained significant in follow‐up analyses. Our association findings were exclusively driven by the samples that were submitted from Brazil (p value of 4.90e−13 for 25,088 bp). The mutation frequency of 25,088 bp in the Brazilian samples on GISAID has rapidly increased from about 0.4 in October/December 2020 to 0.77 in March 2021. Although GWAS methodology is suitable for samples in which mutation frequencies varies between geographical regions, it cannot account for mutation frequencies that change rapidly overtime, rendering a GWAS follow‐up analysis of the GISAID samples that have been submitted after December 2020 as invalid. The locus at 25,088 bp is located in the P.1 strain, which later (April 2021) became one of the distinguishing loci (precisely, substitution V1176F) of the Brazilian strain as defined by the Centers for Disease Control. Specifically, the mutations at 25,088 bp occur in the S2 subunit of the SARS‐CoV‐2 spike protein, which plays a key role in viral entry of target host cells. Since the mutations alter amino acid coding sequences, they potentially imposing structural changes that could enhance viral infectivity and symptom severity. Our analysis suggests that GWAS methodology can provide suitable analysis tools for the real‐time detection of new more transmissible and pathogenic viral strains in databases such as GISAID, though new approaches are needed to accommodate rapidly changing mutation frequencies over time, in the presence of simultaneously changing case/control ratios. 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How sequence variations in the SARS‐CoV‐2 genome affect pathogenicity is poorly understood. Starting in October 2020, using the methodology of genome‐wide association studies (GWAS), we looked at the association between whole‐genome sequencing (WGS) data of the virus and COVID‐19 mortality as a potential method of early identification of highly pathogenic strains to target for containment. Although continuously updating our analysis, in December 2020, we analyzed 7548 single‐stranded SARS‐CoV‐2 genomes of COVID‐19 patients in the GISAID database and associated variants with mortality using a logistic regression. In total, evaluating 29,891 sequenced loci of the viral genome for association with patient/host mortality, two loci, at 12,053 and 25,088 bp, achieved genome‐wide significance (p values of 4.09e−09 and 4.41e−23, respectively), though only 25,088 bp remained significant in follow‐up analyses. Our association findings were exclusively driven by the samples that were submitted from Brazil (p value of 4.90e−13 for 25,088 bp). The mutation frequency of 25,088 bp in the Brazilian samples on GISAID has rapidly increased from about 0.4 in October/December 2020 to 0.77 in March 2021. Although GWAS methodology is suitable for samples in which mutation frequencies varies between geographical regions, it cannot account for mutation frequencies that change rapidly overtime, rendering a GWAS follow‐up analysis of the GISAID samples that have been submitted after December 2020 as invalid. The locus at 25,088 bp is located in the P.1 strain, which later (April 2021) became one of the distinguishing loci (precisely, substitution V1176F) of the Brazilian strain as defined by the Centers for Disease Control. Specifically, the mutations at 25,088 bp occur in the S2 subunit of the SARS‐CoV‐2 spike protein, which plays a key role in viral entry of target host cells. Since the mutations alter amino acid coding sequences, they potentially imposing structural changes that could enhance viral infectivity and symptom severity. Our analysis suggests that GWAS methodology can provide suitable analysis tools for the real‐time detection of new more transmissible and pathogenic viral strains in databases such as GISAID, though new approaches are needed to accommodate rapidly changing mutation frequencies over time, in the presence of simultaneously changing case/control ratios. Improvements of the associated metadata/patient information in terms of quality and availability will also be important to fully utilize the potential of GWAS methodology in this field.</description><subject>Association analysis</subject><subject>Brazil</subject><subject>COVID-19</subject><subject>Genome-Wide Association Study</subject><subject>Genomes</subject><subject>GISAID database</subject><subject>Humans</subject><subject>Infectivity</subject><subject>logistic regression</subject><subject>Mortality</subject><subject>Mutation</subject><subject>Nucleotide sequence</subject><subject>Pathogenicity</subject><subject>Phylogeny</subject><subject>SARS-CoV-2</subject><subject>Severe acute respiratory syndrome coronavirus 2</subject><subject>Spike Glycoprotein, Coronavirus - genetics</subject><subject>Spike protein</subject><subject>Strains (organisms)</subject><subject>Whole genome sequencing</subject><issn>0741-0395</issn><issn>1098-2272</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9ks9uEzEQxi0EoiFw4QGQJS4IKcH2ev9dkEooIVKlVhR6tbwbbzLt7nqxvUTpiUfgnXgTnoTZbKmgB3ywLc1vvhl7PkKeczbnjIk3G9PBXAgp-AMy4SzPZkKk4iGZsFTyGYvy-Ig88f6KMc5lHj8mR5HkcZ6IdEJ-Lk1rG_Pr-48drA3V3tsSdADbUt3qeu_BU1vRxdnl6j1CPKeNdUHXEPbUgb-m0NKL408XGFvYS9wF3RwUPUW9NkAFeG36MGoiHbbmfobv4NrQztlgDoAOtLS1LbHMDWbvIGzp-ZwPjQzZ75y-gRp0S31wGtqn5FGla2-e3Z5T8uXDyefFx9np2XK1OD6dlTJN-MwUMop0EZmiWFdZlWa5jsqYxRhkWSSjuEo5_pvRfG2qOI0LlpV5LoypcDFMnpK3o27XF41Zl_g8p2vVOWi02yurQf0baWGrNvabyqRIUiw-Ja9uBZz92hsfVAO-NHWtW2N7r0QspUxEJmJEX95Dr2zvcCIDleLYE5bkSL0eqdJZ752p7prhTA3eUIM31MEbCL_4u_079I8ZEOAjsIPa7P8jpZYn56tR9DeKyczA</recordid><startdate>202110</startdate><enddate>202110</enddate><creator>Hahn, Georg</creator><creator>Wu, Chloe M.</creator><creator>Lee, Sanghun</creator><creator>Lutz, Sharon M.</creator><creator>Khurana, Surender</creator><creator>Baden, Lindsey R.</creator><creator>Haneuse, Sebastien</creator><creator>Qiao, Dandi</creator><creator>Hecker, Julian</creator><creator>DeMeo, Dawn L.</creator><creator>Tanzi, Rudolph E.</creator><creator>Choudhary, Manish C.</creator><creator>Etemad, Behzad</creator><creator>Mohammadi, Abbas</creator><creator>Esmaeilzadeh, Elmira</creator><creator>Cho, Michael H.</creator><creator>Li, Jonathan Z.</creator><creator>Randolph, Adrienne G.</creator><creator>Laird, Nan M.</creator><creator>Weiss, Scott T.</creator><creator>Silverman, Edwin K.</creator><creator>Ribbeck, Katharina</creator><creator>Lange, Christoph</creator><general>Wiley Subscription Services, Inc</general><general>John Wiley and Sons Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QP</scope><scope>7QR</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-6008-2720</orcidid></search><sort><creationdate>202110</creationdate><title>Genome‐wide association analysis of COVID‐19 mortality risk in SARS‐CoV‐2 genomes identifies mutation in the SARS‐CoV‐2 spike protein that colocalizes with P.1 of the Brazilian strain</title><author>Hahn, Georg ; Wu, Chloe M. ; Lee, Sanghun ; Lutz, Sharon M. ; Khurana, Surender ; Baden, Lindsey R. ; Haneuse, Sebastien ; Qiao, Dandi ; Hecker, Julian ; DeMeo, Dawn L. ; Tanzi, Rudolph E. ; Choudhary, Manish C. ; Etemad, Behzad ; Mohammadi, Abbas ; Esmaeilzadeh, Elmira ; Cho, Michael H. ; Li, Jonathan Z. ; Randolph, Adrienne G. ; Laird, Nan M. ; Weiss, Scott T. ; Silverman, Edwin K. ; Ribbeck, Katharina ; Lange, Christoph</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4761-eb433ab3ebbdf8f789a3c505476083435f71272ea1def575b08c992eeffff0b43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Association analysis</topic><topic>Brazil</topic><topic>COVID-19</topic><topic>Genome-Wide Association Study</topic><topic>Genomes</topic><topic>GISAID database</topic><topic>Humans</topic><topic>Infectivity</topic><topic>logistic regression</topic><topic>Mortality</topic><topic>Mutation</topic><topic>Nucleotide sequence</topic><topic>Pathogenicity</topic><topic>Phylogeny</topic><topic>SARS-CoV-2</topic><topic>Severe acute respiratory syndrome coronavirus 2</topic><topic>Spike Glycoprotein, Coronavirus - genetics</topic><topic>Spike protein</topic><topic>Strains (organisms)</topic><topic>Whole genome sequencing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hahn, Georg</creatorcontrib><creatorcontrib>Wu, Chloe M.</creatorcontrib><creatorcontrib>Lee, Sanghun</creatorcontrib><creatorcontrib>Lutz, Sharon M.</creatorcontrib><creatorcontrib>Khurana, Surender</creatorcontrib><creatorcontrib>Baden, Lindsey R.</creatorcontrib><creatorcontrib>Haneuse, Sebastien</creatorcontrib><creatorcontrib>Qiao, Dandi</creatorcontrib><creatorcontrib>Hecker, Julian</creatorcontrib><creatorcontrib>DeMeo, Dawn L.</creatorcontrib><creatorcontrib>Tanzi, Rudolph E.</creatorcontrib><creatorcontrib>Choudhary, Manish C.</creatorcontrib><creatorcontrib>Etemad, Behzad</creatorcontrib><creatorcontrib>Mohammadi, Abbas</creatorcontrib><creatorcontrib>Esmaeilzadeh, Elmira</creatorcontrib><creatorcontrib>Cho, Michael H.</creatorcontrib><creatorcontrib>Li, Jonathan Z.</creatorcontrib><creatorcontrib>Randolph, Adrienne G.</creatorcontrib><creatorcontrib>Laird, Nan M.</creatorcontrib><creatorcontrib>Weiss, Scott T.</creatorcontrib><creatorcontrib>Silverman, Edwin K.</creatorcontrib><creatorcontrib>Ribbeck, Katharina</creatorcontrib><creatorcontrib>Lange, Christoph</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Calcium &amp; 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How sequence variations in the SARS‐CoV‐2 genome affect pathogenicity is poorly understood. Starting in October 2020, using the methodology of genome‐wide association studies (GWAS), we looked at the association between whole‐genome sequencing (WGS) data of the virus and COVID‐19 mortality as a potential method of early identification of highly pathogenic strains to target for containment. Although continuously updating our analysis, in December 2020, we analyzed 7548 single‐stranded SARS‐CoV‐2 genomes of COVID‐19 patients in the GISAID database and associated variants with mortality using a logistic regression. In total, evaluating 29,891 sequenced loci of the viral genome for association with patient/host mortality, two loci, at 12,053 and 25,088 bp, achieved genome‐wide significance (p values of 4.09e−09 and 4.41e−23, respectively), though only 25,088 bp remained significant in follow‐up analyses. Our association findings were exclusively driven by the samples that were submitted from Brazil (p value of 4.90e−13 for 25,088 bp). The mutation frequency of 25,088 bp in the Brazilian samples on GISAID has rapidly increased from about 0.4 in October/December 2020 to 0.77 in March 2021. Although GWAS methodology is suitable for samples in which mutation frequencies varies between geographical regions, it cannot account for mutation frequencies that change rapidly overtime, rendering a GWAS follow‐up analysis of the GISAID samples that have been submitted after December 2020 as invalid. The locus at 25,088 bp is located in the P.1 strain, which later (April 2021) became one of the distinguishing loci (precisely, substitution V1176F) of the Brazilian strain as defined by the Centers for Disease Control. Specifically, the mutations at 25,088 bp occur in the S2 subunit of the SARS‐CoV‐2 spike protein, which plays a key role in viral entry of target host cells. Since the mutations alter amino acid coding sequences, they potentially imposing structural changes that could enhance viral infectivity and symptom severity. Our analysis suggests that GWAS methodology can provide suitable analysis tools for the real‐time detection of new more transmissible and pathogenic viral strains in databases such as GISAID, though new approaches are needed to accommodate rapidly changing mutation frequencies over time, in the presence of simultaneously changing case/control ratios. Improvements of the associated metadata/patient information in terms of quality and availability will also be important to fully utilize the potential of GWAS methodology in this field.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>34159627</pmid><doi>10.1002/gepi.22421</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0001-6008-2720</orcidid><oa>free_for_read</oa></addata></record>
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1098-2272
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source MEDLINE; Wiley Online Library Journals Frontfile Complete
subjects Association analysis
Brazil
COVID-19
Genome-Wide Association Study
Genomes
GISAID database
Humans
Infectivity
logistic regression
Mortality
Mutation
Nucleotide sequence
Pathogenicity
Phylogeny
SARS-CoV-2
Severe acute respiratory syndrome coronavirus 2
Spike Glycoprotein, Coronavirus - genetics
Spike protein
Strains (organisms)
Whole genome sequencing
title Genome‐wide association analysis of COVID‐19 mortality risk in SARS‐CoV‐2 genomes identifies mutation in the SARS‐CoV‐2 spike protein that colocalizes with P.1 of the Brazilian strain
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