key: cord-0758558-qu9spfcd
authors: Horowitz, J. E.; Kosmicki, J. A.; Damask, A.; Sharma, D.; Roberts, G. H. L.; Justice, A. A. E.; Banerjee, N.; Coignet, M. V.; Yadav, A.; Leader, J. B.; Marcketta, A.; Park, D. S.; Lanche, R.; Maxwell, E.; Knight, S. C.; Bai, X.; Guturu, H.; Sun, D.; Baltzell, A.; Kury, F. S. P.; Backman, J. D.; Girshick, A. R.; O'Dushlaine, C.; McCurdy, S. R.; Partha, R.; Mansfield, A. J.; Turissini, D. A.; Li, A. H.; Zhang, M.; Mbatchou, J.; Watanabe, K.; Gurski, L.; McCarthy, S. E.; Verma, A.; Sirugo, G.; Regeneron Genetics Center,; Ritchie, M. D.; Jones, M.; Balasubramanian, S.; Salerno, W. J.; Shuldiner,
title: Common genetic variants identify therapeutic targets for COVID-19 and individuals at high risk of severe disease
date: 2020-12-16
journal: medRxiv
DOI: 10.1101/2020.12.14.20248176
sha: 052637eb79f9186719296699c7787f3e69bdd98b
doc_id: 758558
cord_uid: qu9spfcd

The need to identify and effectively treat COVID-19 cases at highest risk for severe disease is critical. We identified seven common genetic variants (three novel) that modulate COVID-19 susceptibility and severity, implicating IFNAR2, CCHCR1, TCF19, SLC6A20 and the hyaluronan pathway as potential therapeutic targets. A high genetic burden was strongly associated with increased risk of hospitalization and severe disease among COVID-19 cases, especially among individuals with few known risk factors.

). In contrast, for IFNAR2, our analysis suggests that 126 severe COVID-19 is associated with lower expression in immune cells and lung tissue 127 (Supplementary Table 11) , consistent with the deficient interferon response observed in severe 128 COVID-19 patients [29] . Collectively, these analyses identified four specific putative effector 129 genes in COVID-19 risk loci (IFNAR2, CCHCR1, TCF19 and SLC6A20), though functional 130 studies are required to confirm these predictions. 131 132 Co-localization analyses did not identify any likely target genes for the three new risk variants. 133

However, we note that two of these (rs12461764 and rs79833209) are near genes related to The second aim of this study was to determine if genetics can help identify individuals at high risk 144 of severe disease, who may be prioritized for prophylactic or therapeutic interventions. 145 GRS (top 10%) was associated with a 2.0-fold increased risk of hospitalization (95% CI 1.66-2.55, 152

P=3x10 -11 ; Supplementary Figure 4A ) and 1.8-fold increased risk of severe disease (95% CI 153 1.40-2.41, P=10 -5 ; Figure 3A) . A consistent pattern was observed in other ancestries, though 154 sample sizes were considerably smaller (Supplementary Tables 12 and 13) . Lastly, we compared 155 the effect of the GRS between individuals with and without established risk factors for severe 156 COVID-19. We found that a high GRS (top 10%) was strongly associated with risk of severe 157 disease among individuals with one (OR=3.26, 95% CI 2.03-5.23, P=10 -6 ) or two (OR=2.19, 95% 158 CI 1.29-3.72, P=0.004) established risk factors (Figure 3B and 3C; Supplementary Table 14) . 159

In contrast, there was a much weaker association between a high GRS and risk of severe disease 160 among individuals with many (three or more) risk factors (OR=1. 26 Table 14) . Collectively, these results demonstrate that a GRS calculated 164 using variants associated with disease risk and severity can be used to identify COVID-19 cases 165 at high risk of developing poor disease outcomes. This is important as many of these individuals 166 might not be prioritized for prophylactic or therapeutic interventions according to current 167 guidelines [35] . 168

In summary, we confirmed four common variant associations with COVID-19 susceptibility and 170 further show that they modulate disease severity and are likely to influence the function of 171 All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 16, 2020. ; https://doi.org/10.1101/2020.12.14.20248176 doi: medRxiv preprint can be used to identify individuals at high risk of poor disease outcomes. Collectively, our analyses 175 point to potential novel therapies and help identify patients at high risk of severe COVID-19. 176 All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. ICU admittance with ventilation, septic shock, respiratory failure, and organ failure due to 198 COVID-19. Binary responses were encoded as 0 for "No" and 1 for "Yes". Three symptom questions related to shortness of breath, fever, and nausea/vomiting symptoms were encoded as a 200 unit-scaled variable based on the following mapping: 0="None", 0.2="Very mild", 0. Server. Prior to imputation, we retained variants that had a MAF >= 0.1%, missingness < 1% and 216 HWE p-value > 10 -15 . Following imputation, data from the OMNI and GSA datasets were merged 217 for subsequent association analyses, which included an OMNI/GSA batch covariate, in addition 218 to other covariates described below. 219 220 221 All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 

All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 16, 2020. ; https://doi.org/10.1101/2020.12.14.20248176 doi: medRxiv preprint with only negative qPCR or serology test results for SARS-CoV-2 and no COVID-19-related 248 ICD10 code (U07), hospitalization or death; and (iii) unknown -those with no qPCR or serology 249 test results and no COVID-19-related ICD10 code (U07), hospitalization or death. We then used 250 these broad COVID-19 disease categories, in addition to hospitalization and disease severity 251 information, to create seven COVID-19-related phenotypes for genetic association analyses, as 252 detailed in Supplementary Table 3 . For association analysis in the AncestryDNA study, we 253 excluded from the COVID-19 unknown group individuals who had (i) a first-degree relative who 254 was COVID-19 positive; or (ii) flu-like symptoms. 255 256

Association analyses in each study were performed using the genomewide Firth logistic regression 258 test implemented in REGENIE [40] . In this implementation, Firth's approach is applied when the 259 p-value from standard logistic regression score test is below 0.05. We included in step 1 of 260 REGENIE (i.e. prediction of individual trait values based on the genetic data) directly genotyped 261 variants with a minor allele frequency (MAF) >1%, <10% missingness, Hardy-Weinberg 262 equilibrium test P-value>10 -15 and linkage-disequilibrium (LD) pruning (1000 variant windows, 263 100 variant sliding windows and r 2 <0.9). The association model used in step 2 of REGENIE 264 included as covariates age, age 2 , sex, age-by-sex, and the first 10 ancestry-informative principal 265 components (PCs) derived from the analysis of a stricter set of LD-pruned (50 variant windows, 5 266 All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 16, 2020. ; https://doi.org/10.1101/2020.12.14.20248176 doi: medRxiv preprint variant sliding windows and r 2 <0.5) common variants from the array (imputed for the GHS study) 267 data. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 16, 2020. ; https://doi.org/10.1101/2020.12.14.20248176 doi: medRxiv preprint susceptibility in previous GWAS and that we (i) independently replicated; and (ii) found to be 290 associated with COVID-19 severity. We used as weights the effect (beta) reported in previous 291 All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 16, 2020. interests. 319 320 All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 16, 2020. ; https://doi.org/10.1101/2020.12.14.20248176 doi: medRxiv preprint All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 16, 2020. ; https://doi.org/10.1101/2020.12.14.20248176 doi: medRxiv preprint All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 16, 2020. ; https://doi.org/10.1101/2020.12.14.20248176 doi: medRxiv preprint All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 16, 2020. ; https://doi.org/10.1101/2020.12.14.20248176 doi: medRxiv preprint (C) Association between high genetic risk (top 10% of GRS vs. all other COVID-19 cases) and 354 severe disease, after stratifying by the number of pre-existing clinical risk factors. The association 355 was tested in the UK Biobank and AncestryDNA studies, with results combined using inverse-356 variance meta-analysis. 357 358 All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 16, 2020. ; https://doi.org/10.1101/2020.12.14.20248176 doi: medRxiv preprint All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 16, 2020. ; https://doi.org/10.1101/2020.12.14.20248176 doi: medRxiv preprint All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Loci. medRxiv, 2020. 548 All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 16, 2020. ; https://doi.org/10.1101/2020.12.14.20248176 doi: medRxiv preprint 

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