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. 2024 Oct 3:13:RP93666.
doi: 10.7554/eLife.93666.

Novel risk loci for COVID-19 hospitalization among admixed American populations

Silvia Diz-de Almeida #  1   2   3   4 , Raquel Cruz #  1   2   3   4 , Andre D Luchessi  5 , José M Lorenzo-Salazar  6 , Miguel López de Heredia  3 , Inés Quintela  7 , Rafaela González-Montelongo  6 , Vivian Nogueira Silbiger  5 , Marta Sevilla Porras  3   8 , Jair Antonio Tenorio Castaño  1   3   8 , Julian Nevado  1   3   8 , Jose María Aguado  9   10   11 , Carlos Aguilar  12 , Sergio Aguilera-Albesa  2   13 , Virginia Almadana  14 , Berta Almoguera  3   15 , Nuria Alvarez  16 , Álvaro Andreu-Bernabeu  17   18 , Eunate Arana-Arri  19   20 , Celso Arango  17   18   21 , María J Arranz  22 , Maria-Jesus Artiga  23 , Raúl C Baptista-Rosas  24   25   26 , María Barreda-Sánchez  27   28 , Moncef Belhassen-Garcia  29 , Joao F Bezerra  30 , Marcos A C Bezerra  31 , Lucía Boix-Palop  32 , María Brion  33   34 , Ramón Brugada  34   35   36   37 , Matilde Bustos  38 , Enrique J Calderón  38   39   40 , Cristina Carbonell  41   42 , Luis Castano  3   19   43   44   45 , Jose E Castelao  46 , Rosa Conde-Vicente  47 , M Lourdes Cordero-Lorenzana  48 , Jose L Cortes-Sanchez  49   50 , Marta Corton  3   15 , M Teresa Darnaude  51 , Alba De Martino-Rodríguez  52   53 , Victor Del Campo-Pérez  54 , Aranzazu Diaz de Bustamante  51 , Elena Domínguez-Garrido  55 , Rocío Eirós  56 , María Carmen Fariñas  57   58   59 , María J Fernandez-Nestosa  60 , Uxía Fernández-Robelo  61 , Amanda Fernández-Rodríguez  11   62 , Tania Fernández-Villa  40   63 , Manuela Gago-Dominguez  7   64 , Belén Gil-Fournier  65 , Javier Gómez-Arrue  52   53 , Beatriz González Álvarez  52   53 , Fernan Gonzalez Bernaldo de Quirós  66 , Anna González-Neira  16 , Javier González-Peñas  17   18   21 , Juan F Gutiérrez-Bautista  67 , María José Herrero  68   69 , Antonio Herrero-Gonzalez  70 , María A Jimenez-Sousa  11   62 , María Claudia Lattig  71   72 , Anabel Liger Borja  73 , Rosario Lopez-Rodriguez  3   15   74 , Esther Mancebo  75   76 , Caridad Martín-López  73 , Vicente Martín  40   63 , Oscar Martinez-Nieto  72   77 , Iciar Martinez-Lopez  78   79 , Michel F Martinez-Resendez  49 , Angel Martinez-Perez  80 , Juliana F Mazzeu  81   82   83 , Eleuterio Merayo Macías  84 , Pablo Minguez  3   15 , Victor Moreno Cuerda  85   86 , Silviene F Oliveira  83   87   88   89 , Eva Ortega-Paino  23 , Mara Parellada  17   18   21 , Estela Paz-Artal  75   76   90 , Ney P C Santos  91 , Patricia Pérez-Matute  92 , Patricia Perez  93 , M Elena Pérez-Tomás  28 , Teresa Perucho  94 , Mellina Pinsach-Abuin  34   35 , Guillermo Pita  16 , Ericka N Pompa-Mera  95   96 , Gloria L Porras-Hurtado  97 , Aurora Pujol  3   98   99 , Soraya Ramiro León  65 , Salvador Resino  11   62 , Marianne R Fernandes  91   100 , Emilio Rodríguez-Ruiz  64   101 , Fernando Rodriguez-Artalejo  40   102   103   104 , José A Rodriguez-Garcia  105 , Francisco Ruiz-Cabello  64   106   107 , Javier Ruiz-Hornillos  108   109   110 , Pablo Ryan  11   111   112   113 , José Manuel Soria  80 , Juan Carlos Souto  114 , Eduardo Tamayo  115   116 , Alvaro Tamayo-Velasco  117 , Juan Carlos Taracido-Fernandez  70 , Alejandro Teper  118 , Lilian Torres-Tobar  119 , Miguel Urioste  120 , Juan Valencia-Ramos  121 , Zuleima Yáñez  122 , Ruth Zarate  123 , Itziar de Rojas  124   125 , Agustín Ruiz  124   125 , Pascual Sánchez  126 , Luis Miguel Real  127 ; SCOURGE Cohort Group; Encarna Guillen-Navarro  28   128   129   130 , Carmen Ayuso  3   15 , Esteban Parra  131 , José A Riancho  3   57   58   59 , Augusto Rojas-Martinez  132 , Carlos Flores  6   133   134   135 , Pablo Lapunzina  1   3   8 , Ángel Carracedo  3   4   7   64
Affiliations

Novel risk loci for COVID-19 hospitalization among admixed American populations

Silvia Diz-de Almeida et al. Elife. .

Abstract

The genetic basis of severe COVID-19 has been thoroughly studied, and many genetic risk factors shared between populations have been identified. However, reduced sample sizes from non-European groups have limited the discovery of population-specific common risk loci. In this second study nested in the SCOURGE consortium, we conducted a genome-wide association study (GWAS) for COVID-19 hospitalization in admixed Americans, comprising a total of 4702 hospitalized cases recruited by SCOURGE and seven other participating studies in the COVID-19 Host Genetic Initiative. We identified four genome-wide significant associations, two of which constitute novel loci and were first discovered in Latin American populations (BAZ2B and DDIAS). A trans-ethnic meta-analysis revealed another novel cross-population risk locus in CREBBP. Finally, we assessed the performance of a cross-ancestry polygenic risk score in the SCOURGE admixed American cohort. This study constitutes the largest GWAS for COVID-19 hospitalization in admixed Latin Americans conducted to date. This allowed to reveal novel risk loci and emphasize the need of considering the diversity of populations in genomic research.

Keywords: COVID-19; GWAS; SNP; genetics; genomics; none.

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Conflict of interest statement

SD, RC, AL, JL, Md, IQ, RG, VN, MP, JT, JN, JA, CA, SA, VA, BA, NA, ÁA, EA, CA, MA, MA, RB, MB, MB, JB, MB, LB, MB, RB, MB, EC, CC, LC, JC, RC, MC, JC, MC, MD, AD, Vd, Ad, ED, RE, MF, MF, UF, AF, TF, MG, BG, JG, BÁ, FB, AG, JG, JG, MH, AH, MJ, ML, AB, RL, EM, CM, VM, OM, IM, MM, AM, JM, EM, PM, VC, SO, EO, MP, EP, NS, PP, PP, MP, TP, MP, GP, EP, GP, AP, SL, SR, MF, ER, FR, JR, FR, JR, PR, JS, JS, ET, AT, JT, AT, LT, MU, JV, ZY, RZ, Id, AR, PS, LR, EG, CA, EP, JR, AR, CF, PL, ÁC No competing interests declared

Figures

Figure 1.
Figure 1.. Flow chart of this study.
Stage I of the study involved a meta-analysis of the Latin American genome-wide association studies (GWAS) from SCOURGE and the COVID-19 Host Genetics Initiative. The resulting meta-analysis was leveraged to prioritize genes by using a transcriptome-wide association study (TWAS), Bayesian fine-mapping and functional annotations, and to assess the generalizability of polygenic risk score (PGS) cross-population models in Latin Americans. Stage II involved two additional cross-population GWAS meta-analyses to further investigate the replicability of findings.
Figure 1—figure supplement 1.
Figure 1—figure supplement 1.. Global genetic inferred ancestry (GIA) composition in the SCOURGE Latin American cohort.
European (EUR), African (AFR), and Native American (AMR) GIA was derived with ADMIXTURE from a reference panel composed of Aymaran, Mayan, Nahuan, and Quechuan individuals of Native American genetic ancestry and randomly selected samples from the EUR and AFR 1KGP populations. The colors represent the different geographical sampling regions from which the admixed American individuals from SCOURGE were recruited.
Figure 2.
Figure 2.. Manhattan plot for the admixed AMR genome-wide association studies (GWAS) meta-analysis.
Probability thresholds at p=5 × 10–8 and p=5 × 10–5 are indicated by the horizontal lines. Genome-wide significant associations with COVID-19 hospitalizations were found on chromosome 2 (within BAZ2B), chromosome 3 (within LZTFL1), chromosome 6 (within FOXP4), and chromosome 11 (within DDIAS).
Figure 2—figure supplement 1.
Figure 2—figure supplement 1.. Quantile–quantile plot for the AMR genome-wide association studies (GWAS) meta-analysis.
A lambda inflation factor of 1.015 was obtained.
Figure 3.
Figure 3.. New loci associated with COVID-19 hospitalization in Admixed american populations.
(A) Regional association plots for rs1003835 at chromosome 2 and rs77599934 at chromosome 11. (B) Allele frequency distribution across the 1000 Genomes Project populations for the lead variants rs1003835 and rs77599934. Retrieved from The Geography of Genetic Variants Web or GGV.
Figure 3—figure supplement 1.
Figure 3—figure supplement 1.. Regional association plots for the fine mapped loci in chromosomes 2 (A) and 16 (B).
Colored in red, the variants allocated to the credible set at the 95% confidence according to the Bayesian fine mapping. In blue, the sentinel variant.
Figure 4.
Figure 4.. Summary of the results from gene prioritization strategies used for genetic associations in AMR populations.
Genome-wide association studies (GWAS) catalog association for BAZ2B-AS was with FEV/FCV ratio. Literature-based evidence is further explored in ‘Discussion’.
Figure 4—figure supplement 1.
Figure 4—figure supplement 1.. Gene‒tissue pairs for which either rs1003835 or rs60606421 are significant expression quantitative trait loci (eQTL) at false discovery rate (FDR) < 0.05 (data retrieved from https://gtexportal.org/home/snp/).
rs1003835 (chromosome 2) maps to BAZ2B, LY75, and PLA2R1 genes. As for the lead variant of chromosome 11, rs77599934, since it was not an eQTL, we used an LD proxy variant (rs60606421). DDIAS and PRCP genes map closely to this variant. NES and p-values correspond to the normalized effect size (and direction) of eQTL-gene associations and the p-value for the tissue, respectively.
Figure 5.
Figure 5.. Forest plot showing effect sizes and the corresponding confidence intervals for the sentinel variants identified in the AMR meta-analysis across populations.
All beta values with their corresponding CIs were retrieved from the B2 population-specific meta-analysis from the HGI v7 release, except for AMR, for which the beta value and IC from the HGIAMR-SCOURGE meta-analysis are represented.
Figure 6.
Figure 6.. Polygenic risk distribution for COVID-19 hospitalization.
(A) Polygenic risk stratified by polygenic risk score (PGS) deciles comparing each risk group against the lowest risk group (OR–95% CI). (B) Distribution of the PGS in each of the severity scale classes. 0, asymptomatic; 1, mild disease; 2, moderate disease; 3, severe disease; 4, critical disease.
See this image and copyright information in PMC

Update of

  • doi: 10.1101/2023.08.11.23293871
  • doi: 10.7554/eLife.93666.1
  • doi: 10.7554/eLife.93666.2

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