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[Preprint]. 2021 Mar 12:2021.03.07.21252875.
doi: 10.1101/2021.03.07.21252875.

Age-dependent impact of the major common genetic risk factor for COVID-19 on severity and mortality

Affiliations

Age-dependent impact of the major common genetic risk factor for COVID-19 on severity and mortality

Tomoko Nakanishi et al. medRxiv. .

Update in

  • Age-dependent impact of the major common genetic risk factor for COVID-19 on severity and mortality.
    Nakanishi T, Pigazzini S, Degenhardt F, Cordioli M, Butler-Laporte G, Maya-Miles D, Bujanda L, Bouysran Y, Niemi ME, Palom A, Ellinghaus D, Khan A, Martínez-Bueno M, Rolker S, Amitrano S, Roade Tato L, Fava F; FinnGen; COVID-19 Host Genetics Initiative (HGI); Spinner CD, Prati D, Bernardo D, Garcia F, Darcis G, Fernández-Cadenas I, Holter JC, Banales JM, Frithiof R, Kiryluk K, Duga S, Asselta R, Pereira AC, Romero-Gómez M, Nafría-Jiménez B, Hov JR, Migeotte I, Renieri A, Planas AM, Ludwig KU, Buti M, Rahmouni S, Alarcón-Riquelme ME, Schulte EC, Franke A, Karlsen TH, Valenti L, Zeberg H, Richards JB, Ganna A. Nakanishi T, et al. J Clin Invest. 2021 Dec 1;131(23):e152386. doi: 10.1172/JCI152386. J Clin Invest. 2021. PMID: 34597274 Free PMC article. Clinical Trial.

Abstract

Background: There is considerable variability in COVID-19 outcomes amongst younger adults-and some of this variation may be due to genetic predisposition. We characterized the clinical implications of the major genetic risk factor for COVID-19 severity, and its age-dependent effect, using individual-level data in a large international multi-centre consortium.

Method: The major common COVID-19 genetic risk factor is a chromosome 3 locus, tagged by the marker rs10490770. We combined individual level data for 13,424 COVID-19 positive patients (N=6,689 hospitalized) from 17 cohorts in nine countries to assess the association of this genetic marker with mortality, COVID-19-related complications and laboratory values. We next examined if the magnitude of these associations varied by age and were independent from known clinical COVID-19 risk factors.

Findings: We found that rs10490770 risk allele carriers experienced an increased risk of all-cause mortality (hazard ratio [HR] 1·4, 95% confidence interval [CI] 1·2-1·6) and COVID-19 related mortality (HR 1·5, 95%CI 1·3-1·8). Risk allele carriers had increased odds of several COVID-19 complications: severe respiratory failure (odds ratio [OR] 2·0, 95%CI 1·6-2·6), venous thromboembolism (OR 1·7, 95%CI 1·2-2·4), and hepatic injury (OR 1·6, 95%CI 1·2-2·0). Risk allele carriers ≤ 60 years had higher odds of death or severe respiratory failure (OR 2·6, 95%CI 1·8-3·9) compared to those > 60 years OR 1·5 (95%CI 1·3-1·9, interaction p-value=0·04). Amongst individuals ≤ 60 years who died or experienced severe respiratory COVID-19 outcome, we found that 31·8% (95%CI 27·6-36·2) were risk variant carriers, compared to 13·9% (95%CI 12·6-15·2%) of those not experiencing these outcomes. Prediction of death or severe respiratory failure among those ≤ 60 years improved when including the risk allele (AUC 0·82 vs 0·84, p=0·016) and the prediction ability of rs10490770 risk allele was similar to, or better than, most established clinical risk factors.

Interpretation: The major common COVID-19 risk locus on chromosome 3 is associated with increased risks of morbidity and mortality-and these are more pronounced amongst individuals ≤ 60 years. The effect on COVID-19 severity was similar to, or larger than most established risk factors, suggesting potential implications for clinical risk management.

Funding: Funding was obtained by each of the participating cohorts individually.

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Conflict of interest statement

Declaration of interests

JBR has served as an advisor to GlaxoSmithKline and Deerfield Capital. DP has served as an advisory board, and has received travel/research grants, speaking and teaching fees for Macopharma, Ortho Clinical Diagnostics, Grifols, Terumo, Immucor, Diamed, and Diatech Pharmacogenetics. THK has served an advisor to Novartis, Gilead, Intercept and Engitix. LV declares following; speaking fees: MSD, Gilead, AlfaSigma, AbbVie, Consulting: Gilead, Pfizer, Astra Zeneca, Novo Nordisk, Intercept pharmaceuticals, Diatech Pharmacogenetics, IONIS; Research grants: Gilead. All other authors declare that there are no conflicts of interest.

Figures

Figure 1:
Figure 1:. Associations with mortality
The results described here were restricted to 9,248 COVID-19 patients of European ancestry with available follow-up and cause of death information. (A) Kaplan-Meier curves stratified by rs10490770 risk allele carrier status. (Carriers: N=1,400 vs non-carriers: N=7,848). Hazard ratios (HR) were calculated by adjusting for age, sex, genetic PCs 1 to 5 as fixed effects, and groups indicating participating studies as random effects. (B) Cumulative incidence curves for COVID-19 related death and COVID-19 unrelated death amongst the same individuals as (A).
Figure 2:
Figure 2:. Associations between rs10490770 risk allele carrier status and COVID-19 severity and complications.
The results described here were restricted to COVID-19 patients of European ancestry. Logistic regressions were fit to assess the associations of rs10490770 risk allele carrier status with COVID-19 severity and complications, adjusting for age, sex, genetic PCs 1 to 5 as fixed effects, and groups indicating participating studies as random effects. Red: All participants (N=11,658) Blue: Hospitalized participants only (N=5,601) The case counts demonstrated here are from the data in all individuals.
Figure 3:
Figure 3:. Influence of age and clinical risk factors for the effect of rs10490770 risk allele carrier status on death or severe respiratory failure.
(A) Age distribution in COVID-19 patients of European ancestry who died or experienced severe respiratory failure (N=1,925). Median (IQR) age was 67 (63-78) years in carriers (N=438) and 72 (59-76) years in non-carriers (N=1,442). (B) Logistic regressions between rs10490770 risk allele carrier status and death or severe respiratory failure. Regressions were performed within subgroups stratified by age (age ≤ 60 years and age > 60 years) (Cases / Controls = 1,925 / 7,055) or by the number of established risk factors (0, 1, or ≥2); BMI≥30, smoking, cancer, chronic kidney disease, chronic obstructive pulmonary disease (COPD), chronic heart failure, transplantation, and diabetes mellitus (Cases / Controls = 834 / 6,454).
Figure 4:
Figure 4:. Multivariate regression models and risk prediction estimates of COVID19 death or severe respiratory failure
Multivariate regression analyses for death or severe respiratory failure were restricted to European-ancestry individuals with complete information of demographic variables (green), comorbidities (blue) and rs10490770 risk allele status (red). (N=7,288 for all and N = 2,476 for Age ≤ 60), CKD: chronic kidney disease, COPD: chronic obstructive pulmonary disease, CHF: chronic heart failure, DM: diabetes mellitus. (A) Forest plots comparing odds ratios from multivariate regression models. The size of each dot represents the frequency of the risk factors. (B) Comparison of AUCs of predictions for COVID-19 outcomes. rs10490770 risk allele and non-genetic clinical risk factors were included separately in addition to age and sex in multivariate regression models

References

    1. McKee M, Stuckler D. If the world fails to protect the economy, COVID-19 will damage health not just now but also in the future. Nat. Med. 2020; 26: 640–2. - PubMed
    1. Buitrago-Garcia D, Egli-Gany D, Counotte MJ, et al. Occurrence and transmission potential of asymptomatic and presymptomatic SARSCoV-2 infections: A living systematic review and meta-analysis. PLoS Med. 2020; 17: e1003346. - PMC - PubMed
    1. Dooling K, Marin M, Wallace M, et al. The Advisory Committee on Immunization Practices’ Updated Interim Recommendation for Allocation of COVID-19 Vaccine — United States, December 2020. MMWR Morb Mortal Wkly Rep 2021; 69: 1657–60. - PMC - PubMed
    1. O’Driscoll M, Dos Santos GR, Wang L, et al. Age-specific mortality and immunity patterns of SARS-CoV-2. Nature 2020; 590: 140–5. - PubMed
    1. Williamson EJ, Walker AJ, Bhaskaran K, et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature 2020; 584: 430–6. - PMC - PubMed

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