Journal of Personalized Medicine Article Genomic Characterization of Host Factors Related to SARS-CoV-2 Infection in People with Dementia and Control Populations: The GR@ACE/DEGESCO Study Itziar de Rojas 1,2 , Isabel Hernández 1,2 , Laura Montrreal 1 , Inés Quintela 3 , Miguel Calero 2,4,5 , Jose Luís Royo 6 , Raquel Huerto Vilas 7,8 , Antonio González-Pérez 9 , Emilio Franco-Macías 10 , Juan Macías 11 , Manuel Menéndez-González 12,13,14 , Ana Frank-García 2,15,16 , Mónica Diez-Fairen 17,18 , Carmen Lage 2,19 , Sebastián García-Madrona 20 , Nuria Aguilera 1 , Pablo García-González 1,2 , Raquel Puerta 1 , Oscar Sotolongo-Grau 1 , Silvia Alonso-Lana 1 , Alberto Rábano 2,5,21 , Alfonso Arias Pastor 7,8 , Ana Belén Pastor 5,21 , Anaïs Corma-Gómez 11 , Angel Martín Montes 2,15,16 , Carmen Martínez Rodríguez 13,22 , Dolores Buiza-Rueda 2,23 , Maria Teresa Periñán 2,23 , Eloy Rodriguez-Rodriguez 2,19 , Ignacio Alvarez 17,18 , Irene Rosas Allende 13,24 , Juan A. Pineda 11 , María Bernal Sánchez-Arjona 10 , Marta Fernández-Fuertes 11 , Silvia Mendoza 25 , Teodoro del Ser 26 , GR@ACE/DEGESCO Consortium † , Guillermo Garcia-Ribas 20 , Pascual Sánchez-Juan 2,19 , Pau Pastor 17,18 , María J. Bullido 2,27,28,29 , Victoria Álvarez 13,24 , Luis M. Real 11 , Pablo Mir 2,23 , Gerard Piñol-Ripoll 7,8 , Jose María García-Alberca 2,25 , Miguel Medina 2,5 , Adelina Orellana 1,2 , Chris R. Butler 1,30,31 , Marta Marquié 1,2 , María Eugenia Sáez 9 , Ángel Carracedo 3,32 , Lluís Tárraga 1,2 , Mercè Boada 1,2 and Agustín Ruiz 1,2, *  1 Research Center and Memory Clinic, Ace Alzheimer Center Barcelona—Universitat Internacional de  Catalunya, 08017 Barcelona, Spain; iderojas@fundacioace.org (I.d.R.); ihernandez@fundacioace.org (I.H.); Citation: de Rojas, I.; Hernández, I.; lmontrreal@fundacioace.org (L.M.); naguilera@fundacioace.org (N.A.); pgarcia@fundacioace.org (P.G.-G.); Montrreal, L.; Quintela, I.; Calero, M.; rpuerta@fundacioace.org (R.P.); osotolongo@fundacioace.org (O.S.-G.); salonso@fundacioace.org (S.A.-L.); Royo, J.L.; Huerto Vilas, R.; González- aorellana@fundacioace.org (A.O.); christopher.butler@imperial.ac.uk (C.R.B.); Pérez, A.; Franco-Macías, E.; Macías, mmarquie@fundacioace.org (M.M.); ltarraga@fundacioace.org (L.T.); mboada@fundacioace.org (M.B.) 2 CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of J.; et al. Genomic Characterization of Host Factors Related to SARS-CoV-2 Health Carlos III, 28220 Madrid, Spain; mcalero@isciii.es (M.C.); afrankg@gmail.com (A.F.-G.); Infection in People with Dementia clage@idival.org (C.L.); arabano@fundacioncien.es (A.R.); angel.mar.mon@hotmail.com (A.M.M.); and Control Populations: The buizarueda@gmail.com (D.B.-R.); teresaperinantocino@gmail.com (M.T.P.); eloymrod@gmail.com (E.R.-R.); GR@ACE/DEGESCO Study. J. Pers. pascualjesus.sanchez@scsalud.es (P.S.-J.); mjbullido@cbm.csic.es (M.J.B.); pmir@us.es (P.M.); Med. 2021, 11, 1318. https://doi.org/ jmgalberca@ianec.com (J.M.G.-A.); mmedina@ciberned.es (M.M.) 3 Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII), Universidade de 10.3390/jpm11121318 Santiago de Compostela, 15705 Santiago de Compostela, Spain; ines.quintela@usc.es (I.Q.); angel.carracedo@usc.es (Á.C.) Academic Editor: Rosanna Asselta 4 UFIEC, Instituto de Salud Carlos III, 28220 Madrid, Spain 5 CIEN Foundation/Queen Sofia Foundation Alzheimer Center, 28220 Madrid, Spain; Received: 25 October 2021 abpastor@fundacioncien.es Accepted: 4 December 2021 6 Depatamento de Especialidades Quirúrgicas, Bioquímica e Inmunología, Facultad de Medicina, Published: 7 December 2021 Universidad de Málaga, 29016 Málaga, Spain; jlroyo@uma.es 7 Unitat Trastorns Cognitius, Hospital Universitari Santa Maria de Lleida, 25198 Lleida, Spain; Publisher’s Note: MDPI stays neutral rhuerto@gss.cat (R.H.V.); aarias@gss.cat (A.A.P.); gerard_437302@hotmail.com (G.P.-R.) with regard to jurisdictional claims in 8 Institut de Recerca Biomedica de Lleida (IRBLLeida), 25198 Lleida, Spain 9 CAEBI, Centro Andaluz de Estudios Bioinformáticos, 41013 Sevilla, Spain; agonzalez@caebi.es (A.G.-P.); published maps and institutional affil- iations. mesaez@caebi.es (M.E.S.) 10 Unidad de Demencias, Servicio de Neurología y Neurofisiología, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain; efranco17@gmail.com (E.F.-M.); bernalsanchezarjona@gmail.com (M.B.S.-A.) 11 Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital Universitario de Valme, 41013 Sevilla, Copyright: © 2021 by the authors. Spain; juan.macias.sanchez@gmail.com (J.M.); anais.corgo@gmail.com (A.C.-G.); Licensee MDPI, Basel, Switzerland. japineda@telefonica.net (J.A.P.); martaffuertes@gmail.com (M.F.-F.); lmreal67b@gmail.com (L.M.R.) 12 Servicio de Neurología, Hospital Universitario Central de Asturias, 33011 Oviedo, Spain; This article is an open access article distributed under the terms and manuelmenendez@gmail.com 13 Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), 33011 Asturias, Spain; conditions of the Creative Commons carmenmartrod@gmail.com (C.M.R.); irene.roa81@gmail.com (I.R.A.); victoria.alvarez@sespa.es (V.Á.) Attribution (CC BY) license (https:// 14 Departamento de Medicina, Universidad de Oviedo, 33011 Oviedo, Spain creativecommons.org/licenses/by/ 15 Department of Neurology, University Hospital La Paz-Universidad Autónoma-Madrid, 28046 Madrid, Spain 4.0/). J. Pers. Med. 2021, 11, 1318. https://doi.org/10.3390/jpm11121318 https://www.mdpi.com/journal/jpm J. Pers. Med. 2021, 11, 1318 2 of 11 16 University Hospital La Paz Research Institute (IdiPaz), 28029 Madrid, Spain 17 Fundació Docència i Recerca MútuaTerrassa, 08221 Terrassa, Spain; monicadifa@gmail.com (M.D.-F.); ignacio.alvafer@gmail.com (I.A.); pastorpau@gmail.com (P.P.) 18 Memory Disorders Unit, Department of Neurology, Hospital Universitari Mutua de Terrassa, 08221 Terrassa, Spain 19 Neurology Service, Marqués de Valdecilla University Hospital (University of Cantabria and IDIVAL), 39008 Santander, Spain 20 Hospital Universitario Ramon y Cajal, IRYCIS, 28034 Madrid, Spain; sebastian.garcia@salud.madrid.org (S.G.-M.); ggribas@salud.madrid.org (G.G.-R.) 21 Banco de Tejidos de la Fundación CIEN, 28034 Madrid, Spain 22 Hospital de Cabueñes, 33394 Gijón, Spain 23 Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain 24 Laboratorio de Genética, Hospital Universitario Central de Asturias, 33011 Oviedo, Spain 25 Alzheimer Research Center & Memory Clinic, Andalusian Institute for Neuroscience, 29012 Málaga, Spain; silviamendoza@gmail.com 26 Department of Neurology/CIEN Foundation/Queen Sofia Foundation Alzheimer Center, 28220 Madrid, Spain; tdelser@fundacioncien.es 27 Centro de Biología Molecular Severo Ochoa (UAM-CSIC), 28049 Madrid, Spain 28 Instituto de Investigacion Sanitaria ‘Hospital la Paz’ (IdIPaz), 28029 Madrid, Spain 29 Universidad Autónoma de Madrid, 28049 Madrid, Spain 30 Department of Brain Sciences, Imperial College, London SW7 2BX, UK 31 Department of Neurology, Pontificia Universidad Católica, Santiago 340, Chile 32 Fundación Pública Galega de Medicina Xenómica-CIBERER-IDIS, 15705 Santiago de Compostela, Spain * Correspondence: aruiz@fundacioace.org; Tel.: +34-93-444-73-18; Fax: +34-93-410-17-01 † GR@ACE/DEGESCO Consortium, 08017 Barcelona, Spain. Abstract: Emerging studies have suggested several chromosomal regions as potential host genetic factors involved in the susceptibility to SARS-CoV-2 infection and disease outcome. We nested a COVID-19 genome-wide association study using the GR@ACE/DEGESCO study, searching for susceptibility factors associated with COVID-19 disease. To this end, we compared 221 COVID-19 confirmed cases with 17,035 individuals in whom the COVID-19 disease status was unknown. Then, we performed a meta-analysis with the publicly available data from the COVID-19 Host Genetics Initiative. Because the APOE locus has been suggested as a potential modifier of COVID-19 disease, we added sensitivity analyses stratifying by dementia status or by disease severity. We confirmed the existence of the 3p21.31 region (LZTFL1, SLC6A20) implicated in the susceptibility to SARS-CoV-2 infection and TYK2 gene might be involved in COVID-19 severity. Nevertheless, no statistically significant association was observed in the COVID-19 fatal outcome or in the stratified analyses (dementia-only and non-dementia strata) for the APOE locus not supporting its involvement in SARS-CoV-2 pathobiology or COVID-19 prognosis. Keywords: SARS-CoV-2; COVID-19; GWAS; GR@ACE/DEGESCO; dementia; APOE 1. Introduction The coronavirus disease [1] 2019 (COVID-19) has provoked a global crisis. This respi- ratory infection is caused by the severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2) discovered in Wuhan, China, in late 2019. Due to the rapid evolution to a pandemic, insights into how to better understand and combat COVID-19 are desperately needed. Compared to clinical [2–4] or epidemiological [5] characteristics of the disease, the role of host genetic factors affecting the susceptibility and severity of the COVID-19 disease has been poorly studied to date. Given the importance and urgency of understanding such factors, the ‘COVID-19 Host Genetics Initiative [3]’ (COVID-19 HGI) was launched. This initiative brings together the human genetics scientific worldwide community to generate, share, and analyze data relating to the genetic determinants of COVID-19 susceptibility and severity outcomes. Emerging studies include those from Ellinghaus et al. [6], who conducted a genome-wide association study (GWAS) of COVID-19 cases and identified two J. Pers. Med. 2021, 11, 1318 3 of 11 loci that achieved genome-wide significance: the blood type ABO locus on chromosome (chr) 9, and a cluster of immune functions genes on chr 3 (candidate gene SLC6A20). Additionally, Pairo-Castineira et al. [7] reported a genome wide significant association in a gene cluster encoding antiviral restriction enzyme activators (OAS) and near the TYK2, DPP9, and IFNAR2 genes. Torre-Fuentes et al. [8], through whole-exome sequencing, showed an association of exonic variants in the ACE2, TMPRSS2, and FURIN genes in relation to the presence or absence of SARS-CoV-2 infection. Roberts et al. [9] identified three novel loci; near IVNS1ABP/SWT1, a gene involved in influenza virus replication associated only in males, and two genes with established roles in viral replication or immunity (SMRR1 and the immunoglobulin lambda locus). Furthermore, an independent study using the UK Biobank [10] cohort recently suggested [11] that APOE ε4ε4 genotype increases the risks of severe SARS-CoV-2 infection, independent of preexisting dementia, cardiovascular disease, and type-2 diabetes. A population survey of older people in Madrid (Vallecas Project) [12] also reported a significant association of the APOE ε4 allele with the incidence of SARS-CoV-2 infection. To validate emerging genetic associations relevant to COVID-19 susceptibility and severity outcomes from these recent studies, further investigation in independent datasets is needed. To investigate host factors influencing SARS-CoV-2 infection and disease outcome, we took advantage of the GR@ACE/DEGESCO cohort investigating Alzheimer’s disease (AD) and related dementias. This dataset presents the largest case-control GWAS study conducted in the Spanish population to date [13,14]. To identify subjects included in our study who were infected by the coronavirus, we prospectively requested data from all physicians monitoring the subjects included in the GR@ACE/DEGESCO dataset. The main objective of this manuscript is to communicate the novel resource to the scientific community and also to provide independent replication in candidate SNPs previously reported in the literature to date. For that purpose, the data received were organized to design nested case-control studies. Candidate SNPs observed in previous studies were evaluated. Using this approach, we were able to confirm two loci previously proposed, but no evidence was obtained about the role of APOE isoforms in the COVID-19 incidence or fatal outcome. 2. Methods 2.1. Study Participants To conduct this research, we used genetic data obtained from 17,256 subjects included in the GR@ACE/DEGESCO GWAS which also includes the Vallecas project cohort [12]. Clinical definitions and methods used for genotyping and quality controls applied have been published elsewhere [13,14]. From April to October 2020, information on SARS- CoV-2 infection and COVID-19 disease outcome was collected prospectively by clinicians following up the effect of the pandemic in individuals included in the GR@ACE study. Specifically, we started monitoring the Fundació ACE patients by regular teleconferences with patients and families [15]. Briefly, we designed a telematic COVID-19 survey intended to assess exposure, risk factors, symptomatology, and demographic information associated with COVID-19 susceptibility and severity. Data obtained from these self-reported surveys were followed up by our professionals. Information retrieved from patients and families was validated against the clinical history obtained from general practitioners and hospital records. Only individuals having confirmatory evidence of COVID-19 disease in their clinical records were endorsed as COVID-19 cases for this study. Fatalities associated with SARS-CoV-2 infection were also confirmed with patient relatives. Using the information retrieved, we constructed two phenotypes: the first, in which individuals who reported a positive COVID-19 test were compared to those who reported a negative test or were without information (e.g., population), was intended to assess the susceptibility to SARS- CoV-2 infection; the other, in which people who died with COVID-19 were compared to those who were infected but survived the disease, was intended to assess the disease severity. Similarly, participants from the Vallecas Project cohort were contacted by a phone J. Pers. Med. 2021, 11, 1318 4 of 11 call at the end of April 2020, and received a survey to explore the incidence, clinical features, and severity of COVID-19. 2.2. Meta-Analyses We used the data freeze 4 (20 October 2020) from the COVID-19 Host Genetics Initia- tive (HGI) (https://www.covid19hg.org/, accessed date: 1 October 2021) and conducted a meta-analysis. We downloaded the phenotypes for COVID-19 vs. Population (GRCh38 leave out 23 and Me, Susceptibility analysis C2) “ALL” population from 36 studies with 30,937 cases and 1,471,815 controls and the “EUR” population from 22 studies with 14,134 cases and 1,284,876 controls. Cases were individuals with laboratory confirmation of SARS-CoV-2 infection (RNA and/or serology based), physician confirmed or self-reported COVID-19 positive (e.g., by questionnaire). Controls were everybody who was not a case, e.g., population. 2.3. Sample Processing, Genotyping, Quality Control, and Imputation DNA was extracted from peripheral blood according to standard procedures using the Chemagic system (Perkin Elmer). Samples reaching DNA concentrations of >10 ng/µL and presenting high integrity were included for genotyping. Cases and controls were randomized across sample plates to avoid batch effects. For genotyping, we used the Axiom 815K Spanish biobank array (Thermo Fisher) at the Spanish National Centre for Genotyping (CeGEN, Santiago de Compostela, Spain). Details on genotyping and quality-control procedures are provided in previous publica- tions [13,14]. Briefly, individuals with low-quality samples, excess of heterozygosity, sex discrepancies, and familial relations between samples (PI-HAT > 0.1875) were excluded from the analysis. A principal component analysis (PCA) was performed and population outliers were removed. Variants with call rate below 95% or deviation from the Hardy– Weinberg equilibrium (p ≤ 1 × 10−6 ) were also removed from the analysis. To maximize genetic coverage, we performed single-nucleotide polymorphism (SNP) imputation on genome build GRCh38 using the Trans-Omics for Precision Medicine (TOPMed) imputa- tion server [16–18]. Low imputation quality variants (R2 < 0.30) were excluded. After QC steps, we tested 14,212,906 genetic variants for association with COVID-19 disease. 2.4. Targeted Phenotypes and Statistical Analyses The primary analysis focuses on SARS-CoV-2 infection susceptibility. Individuals with a positive test for infection or suspected COVID-19 were included as cases and individuals with unknown SARS-CoV-2 infection status were used as controls for the subsequent genome-wide association studies (Table 1). The inevitable presence of individuals in the control group who may exhibit the critical illness phenotype if exposed to SARS-CoV-2 is expected to bias any associations towards the null. For that reason, any estimate on SARS-CoV-2 susceptibility must be considered highly conservative. Because COVID-19 is highly dynamic in the Spanish population, we plan to update GWAS information every six months. Periodic data releases will be uploaded to the GR@ACE/DEGESCO website and will be publicly available to registered users. The APOE locus is the most important genetic risk factor for AD [19,20]. Beyond its involvement in dementia causality, the locus is also involved in a number of cardiovascular phenotypes [21] and human longevity [22,23] of special interest for dementia studies like GR@ACE/DEGESCO. Because the APOE locus has been suggested as a potential modifier of COVID-19, we decided to add stratified analyses by using dementia-only and non-dementia strata. Meta-analysis of both strata was performed to assess heterogeneity. In addition, point estimates were obtained using only infected populations (survival analysis). For fatal COVID-19 disease outcome, the population was restricted only to those subjects with confirmed SARS-CoV-2 infection. Then, the case status was dichotomized as COVID-19 exitus and non-exitus. GWAS were performed separately for both phenotypes (SARS-CoV-2 susceptibility and fatal COVID-19 disease outcome). Logistic regression J. Pers. Med. 2021, 11, 1318 5 of 11 unadjusted models were fitted using Plink (v2.00a). To maximize the statistical power and because of the difference between the cases/control sample sizes, we decided to conduct the primary analyses in selected candidate SNPs without any covariate in the model. Later, we applied linear mixed models (LMM) to the significant signals to see if the effect is altered by the impact of the covariates using lme4 package in R. APOE locus involvement in fatal COVID-19 disease outcome was also evaluated. Because of the strong association of APOE with Alzheimer’s disease and longevity, its involvement was adjusted for age and dementia status. Subsequently, we performed two fixed-effects inverse-variance–weighted meta-analyses with METAL [24] on the summary statistics of the GR@ACE/DEGESCO study and the COVID-19 HGI (ALL and EUR populations) to maximize the statistical power. We selected 30 variants in 17 genome-wide candidate regions from five recent publications described in Table S1. Table 1. Demographics of the GWAS models in GR@ACE/DEGESCO cohort. Whole Study Cases with Population Total COVID-19 Participants (n) 221 17,035 17,256 Gender (% Female) 69.68 58.78 58.92 Age, years (SD) 71.08 (17.55) 70.45 (16.49) 70.46 (16.51) APOE4 carriers (%) 34.39 30.13 30.19 Dementia (%) 57.92 45.79 45.95 Dementia individuals Cases with COVID-19 Population Total Participants (n) 128 7801 7929 Gender (% Female) 78.12 68.43 68.58 Age, years (SD) 75.4 (17.29) 72.86 (14.94) 72.93 (15.01) APOE4 carriers (%) 42.19 41.35 41.37 Non-Dementia individuals Cases with COVID-19 Population Total Participants (n) 93 9223 9316 Gender (% Female) 58.06 50.61 50.69 Age, years (SD) 65.16 (16.21) 69.05 (17.17) 69 (17.16) APOE4 carriers (%) 23.66 20.64 20.67 Individuals with COVID-19 Cases with COVID-19 Population Total Participants (n) 55 166 221 Gender (% Female) 61.82 72.29 69.68 Age, years (SD) 83.44 (7.83) 76.68 (15.35) 78.42 (14.11) APOE4 carriers (%) 36.36 33.73 34.39 Dementia (%) 87.27 50.60 59.73 J. Pers. Med. 2021, 11, 1318 6 of 11 3. Results We obtained point-effects for the entire human genome by measuring the effect of each SNP variant studied on susceptibility to SARS-CoV-2 infection and COVID-19 disease survival in the GR@ACE/DEGESCO cohort (Table 1). Genomic inflation factors (λ) of the models ranged between 0.995 and 1.017 (Table S1). These calculations suggest no gross bias or stratification issues in any comparison conducted. Because of the small number of individuals with SARS-CoV-2 infection in our study (n = 221), we were unable to identify any GWAS significant signal using GR@ACE/DEGESCO data alone. GWAS summary statistics for the entire genome are available and can be incorporated into ongoing international efforts. On the basis of previously published GWAS results related to COVID-19 host suscep- tibility analyses [6–9,25], we selected thirty lead SNPs for independent replication in the GR@ACE/DEGESCO data (Table S1). Importantly, 9 of 30 SNPs were validated in at least one GWAS comparison. Interestingly, despite the small sample size, we observed a fully independent replication in chr3 locus near the LZTFL1 (rs71325088 COVID-19 fatal outcome analysis; OR = 3.03 (1.24–7.45), p-value = 0.015) and SLC6A20 genes (rs11385942 COVID-19 fatal outcome analysis; OR = 2.34 (1.03–5.35), p-value = 0.043). This result provides inde- pendent evidence of the role of this specific SNP in COVID-19 fatal outcome. In the case of TYK2 gene in chr19 (rs74956615), we observed a compatible point effect, direction and statistical significance for susceptibility (OR = 1.70 (1.13–2.55), p-value = 0.011), COVID-19 fatal outcome (OR = 4.96 (2.02–12.20), p-value = 4.85 × 10−4 ), an improvement in the meta-analysis (EUR, OR = 1.11 (1.04–1.19), p-value = 1.63 × 10−3 ; All, OR = 1.11 (1.04–1.19), p-value = 9.92 × 10−4 , Supplementary Table S2) and confirmation in the linear mixed models (p-value = 5.5 × 10−4 , Supplementary Table S3). In addition, three candidate SNPs previously reported displayed compatible effect size and direction (rs9380142-HLA-G, rs3131294-NOTCH4, and rs10735079-OAS3) in our datasets. Seven markers in the SMRR1, IVNS1ABP/SWT1, CCHCR1, OAS1, TYK2, and IFNAR2 genomic regions have the same effect size direction, but remained non-significant. This result is suggesting a lack of power for detecting them in the COVID-19 fatal outcome analysis. Finally, the meta-analysis revealed slight improvements in TYK2 and IFNAR2 genes and slight reductions of significance in HLA-G and ABO genes with susceptibility to SARS-CoV-2 infection (Supplementary Table S2). In contrast, we were not be able to observe any evidence of statistically significant association, a compatible point effect, nor consistent effect direction in the COVID-19 fatal outcome analysis adjusted by age and dementia status for the APOE locus (rs429358, OR = 0.81 (0.44–1.48), p-value = 0.486; rs7412, OR = 1.02 (0.37–2.82), p-value = 0.967; Figure 1, Table S1), in the stratified analyses using dementia-only (rs429358, OR = 0.99 (0.74–1.33), p-value = 0.971; rs7412, OR = 1.07 (0.57–2.00), p-value = 0.838) or in non- dementia strata (rs429358, OR = 1.08 (0.68–1.70), p-value = 0.747; rs7412, OR = 1.29 (0.75–2.22), p-value = 0.365). Further meta-analysis of dementia and non-dementia groups indicated an absence of heterogeneity among strata. Furthermore, HGI consortium [25] data alone and a susceptibility meta-analysis with both HGI and GR@ACE/DEGESCO con- firmed our findings (meta-analysis EUR, rs429358, OR = 1.03 (0.99–1.07), p-value = 0.199; rs7412, OR = 0.99 (0.94–1.04), p-value = 0.574, Supplementary Table S2). J. Pers. Med. 2021, 11, x FOR PEER REVIEW 7 of 11 J. Pers. Med. 2021, 11, 1318 7 of 11 Figure 1. Forest plot comparing estimates for rs429358 APOE ε4 locus in different analysis. Manhattan Figure 1. Forest plot comparing estimates for rs429358 APOE ε4 locus in different analysis. Manhat- plot for chr19 tan plot for chr19 for for fatal fatal outcome outcome analysis analysis results resultsin inGR@ACE/DEGESCO GR@ACE/DEGESCO population population (exitus (exitusvs. vs.non- exitus adjusted non-exitus adjusted by by age ageand anddementia dementiastatus; status;total totalsample samplesize size==221). 221).Pink Pinkdots dotscorrespond correspondtotoSNPs SNPsconfiguring commonAPOE configuringcommon APOEhaplogenotypes haplogenotypes(ε2/ε3/ε4). (ε2/ε3/ε4). 4. Discussion 4. Discussion Our data strengthen the evidence for an association with SARS-CoV-2 susceptibility Our data strengthen the evidence for an association with SARS-CoV-2 susceptibility at the chr3p21.31 gene cluster, first identified by Ellinghaus et al. [6] and recently validated at the chr3p21.31 gene cluster, first identified by Ellinghaus et al. [6] and recently validated by others [26,27]. In particular, SLC6A20 can be linked to the association via eQTLs within by others [26,27]. In particular, SLC6A20 can be linked to the association via eQTLs within breast epithelium and esophagus muscularis mucosa according to GTEx [28], suggesting breast epithelium and esophagus muscularis mucosa according to GTEx [28], suggesting increased expression of SLC6A20 correlates with increased risk of severe outcomes. Fur- increased expression of SLC6A20 correlates with increased risk of severe outcomes. Fur- ther, SLC6A20 can form a complex with angiotensin converting enzyme 2 (ACE2), the ther,cell SLC6A20 surfacecan form afor receptor complex with angiotensin SARS-CoV-2 viral entryconverting [29]. Thus, enzyme 2 (ACE2), it is possible thatthe cell increased surface receptor SLC6A20 for SARS-CoV-2 expression viral entry leads to increased ACE2[29]. Thus, protein it and levels is possible that uptake. greater viral increasedOther SLC6A20 expression leads to increased ACE2 protein levels and candidates from the region such as LZFTL1 (CCR9, CXCR6, XCR1, FYCO1) have greater viral uptake. been im- Other candidates plicated from thefunctions in respiratory region such as LZFTL1 and/or (CCR9, system in the immune CXCR6,that XCR1, FYCO1) should have be considered beenandimplicated in investigated.respiratory functions and/or in the immune system that should be con- sidered and investigated. A potential causal role for TYK2 was also statistically significant in our analysis. These A potential findings supportcausaltherole for reported results TYK2 was by also statistically et Pairo-Castineira significant in ourcritical al. [7] in which analysis. illness These findings support the results reported by Pairo-Castineira et al. [7] in in COVID-19 is related to host-driven inflammatory lung injury, which is a key mechanismwhich critical illness in COVID-19 of late is related COVID-19 and life-threatening to host-driven inflammatory lung injury, which is a key disease. mechanism of late and life-threatening COVID-19 The GR@ACE/DEGESCO dementia configuration disease. allows us to study, in a different population, the APOE effect suggested by previous studies with the UK Biobank [10] on J. Pers. Med. 2021, 11, 1318 8 of 11 COVID-19 disease or in a Spanish elderly cohort [12]. Kuo [10] et al. reported that the APOE ε4ε4 genotype was associated with 2.2-fold increased risks of test positivity and of 4.3-fold more mortality after testing positive relative to APOE ε3ε3 individuals, suggesting that the APOE ε4ε4 genotype represents a significant risk for the development of severe COVID-19, as well as death following infection. Del Ser [12] et al. reported a significantly higher incidence of COVID-19 disease in the individuals carrying an APOE ε4 genotype. The effect of age [30] on the severity of COVID-19 disease and APOE [31] in dementia is well known. Therefore, controlling these factors is essential to have more reliable and accurate results. Interestingly, our stratification in dementia, non-dementia, and fatal COVID-19 disease outcome analysis adjusting by age and dementia diagnosis does not corroborate the previous results, suggesting a lack of association of APOE with COVID-19 outcome. Despite our findings, the effect of APOE in SARS-CoV-2 infection and its lethality deserves further investigation. Of 40 genes previously identified as crucial for SARS-CoV-2 infection, two, the endosomal entry receptor ACTR2 and the ATP6AP2 ATPase, are involved in endosome function [32]. Intriguingly, this molecular pathway has been prioritized as an important causal pathway associated with AD [33]. Curiously, ACTR2 and ATP6AP2 genes are more highly expressed in ApoE4 astrocytes, which have larger early endosomes than do ApoE3 cells [32]. More research is needed to determine the real impact of APOE alleles in COVID-19 morbid-mortality and host resistance to SARS-CoV-2 infection. The investigation of host factors affecting SARS-CoV-2 infection susceptibility and lethality may benefit from dementia-only GWAS studies. For example, exploring genetics elements in populations with more homogenous comorbid profiles might offer enhanced precision for studying APOE involvement in COVID-19 risk and prognosis. Hence, we pro- pose to nest COVID-19 studies in large-meta-GWAS for AD such as GR@ACE/DEGESCO or the European Alzheimer Disease Biobank (EADB; Bellenguez et al. [34]). Dementia-only studies could be very important in disentangling potential APOE effects that might be obscured by selection bias affecting SARS-CoV-2 exposure and infection outcome. We feel that dementia-only studies would be more resistant to obvious selection bias potentially affecting people with dementia during the COVID-19 crisis. On one hand, people with dementia may have an increased risk of infections because of their lack of autonomy for configuring self-protection measures. They have also an increased risk of being in nursing homes [35]. On the other hand, in practice, people with dementia may have had less chance of surviving because of potential discrimination in intensive care units during pan- demic peaks [36,37]. Furthermore, comorbidities typically associated with dementia might also contribute to the increased morbidity–mortality observed in SARS-CoV-2 infected individuals belonging to this vulnerable population [38]. The main limitation of the study is the small number of patients in the cohort with SARS-CoV-2 infection, which reduces the statistical power of the results and limits the possibility of evaluating other aspects of COVID-19 that could be influenced by genetics, including the severity of the infection. Another limitation is the lack of confirmation of SARS-CoV-2 infection in many cases: for a considerable period during the pandemic, the Spanish healthcare authorities recommended that infected patients be quarantined without PCR confirmation of the infection. This limitation might have contaminated the control groups of our study further reducing the power to detect genuine signals associated to susceptibility to SARS-CoV-2 infection and COVID-19 development, but not to disease mortality analyses conducted. Despite these considerations, we have been able to validate some signals and the strengths of the study provide relevant information to APOE and COVID-19 disease. For future studies, it would also be interesting to be able to compare the effects caused between the SARS-CoV-2 variants. In conclusion, we confirmed the 3p21.31 region (LZTFL1, SLC6A20), TYK2 gene as a ge- netic susceptibility locus involved in SARS-CoV-2 infection using an independent Spanish dataset. With COVID-19 HGI meta-analysis, other suggested regions were reinforced. In contrast, our Dementia-only GWAS study did not support an APOE locus involvement in J. Pers. Med. 2021, 11, 1318 9 of 11 SARS-CoV-2 pathobiology or COVID-19 prognosis. To increase the statistical power of this study, we continue monitoring COVID-19 disease in the GR@ACE/DEGESCO participants. Supplementary Materials: The following are available online at https://www.mdpi.com/article/ 10.3390/jpm11121318/s1, Supplementary Table S1: Table of emerging signals evaluated in GR@ACE/ DEGESCO cohort. Table S2: Meta-analysis table of emerging signals for GR@ACE/DEGESCO and HGI Consortia. Supplementary Table S3: Results for linear mixed modeling (LMM) for the signals replicated in GR@ACE/DEGESCO cohort in the different analysis. Author Contributions: Conceptualization and design the project: A.R. (Agustín Ruiz); Data curation and formal analysis: I.d.R. Methodology, Writing—Original Draft: I.d.R. and A.R. (Agustín Ruiz). Data acquisition, investigation, and revision of manuscript: I.d.R., I.H., L.M., I.Q., M.C., J.L.R., R.H.V., A.G.-P., E.F.-M., J.M., M.M.-G., A.F.-G., M.D.-F., C.L., S.G.-M., N.A., P.G.-G., R.P., O.S.-G., S.A.-L., A.R. (Alberto Rábano), A.A.P., A.B.P., A.C.-G., A.M.M., C.M.R., D.B.-R., M.T.P., E.R.-R., I.A., I.R.A., J.A.P., M.B.S.-A., M.F.-F., S.M., T.d.S., G.G.-R., P.S.-J., P.P., M.J.B., V.Á., L.M.R., P.M., G.P.-R., J.M.G.-A., M.M. (Miguel Medina), A.O., C.R.B., M.M. (Marta Marquié), M.E.S., Á.C., L.T., M.B. and A.R. (Agustín Ruiz). All authors have read and agreed to the published version of the manuscript. Funding: We would like to thank patients and controls who participated in this project. The present work has been performed as part of the doctoral program of I. de Rojas at the Universitat de Barcelona (Barcelona, Spain) supported by national grant from the Instituto de Salud Carlos III FI20/00215. The Genome Research @ Fundació ACE project (GR@ACE) is supported by Grifols SA, Fundación bancaria ‘La Caixa’, Fundació ACE, and CIBERNED. The Vallecas Project is supported by Queen Sofia Foundation and the Instituto de Salud Carlos III. The position held by SA-L is funded by Instituto de Salud Carlos III (Co-funded by European Social Fund “Investing in your future”) Sara Borrell Contract (CD19/00232). A.R. and M.B. receive support from the European Union/EFPIA Innovative Medicines Initiative Joint undertaking ADAPTED and MOPEAD projects (grant numbers 115975 and 115985, respectively). M.B. and A.R. are also supported by national grants PI13/02434, PI16/01861, PI17/01474, PI19/01240 and PI19/01301. Acción Estratégica en Salud is integrated into the Spanish National R + D + I Plan and funded by ISCIII (Instituto de Salud Carlos III)–Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER–‘Una manera de hacer Europa’). Some control samples and data from patients included in this study were provided in part by the National DNA Bank Carlos III (www.bancoadn.org, accessed date: 1 October 2021, University of Salamanca, Spain) and Hospital Universitario Virgen de Valme (Sevilla, Spain); they were processed following standard operating procedures with the appropriate approval of the Ethical and Scientific Committee. This research has been conducted using the COVID-19 Host Genetic Initiative public resource obtained through the web site (https://www.covid19hg.org/results/, accessed date: 1 October 2021). Institutional Review Board Statement: The ethics and scientific committees have approved, this research protocol (Acta 25/2016, Ethics Committee H., Clinic I Provincial, Barcelona, Spain). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request. Conflicts of Interest: The authors declare no conflict of interest. References 1. Zhu, N.; Zhang, D.; Wang, W.; Li, X.; Yang, B.; Song, J.; Zhao, X.; Huang, B.; Shi, W.; Lu, R.; et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N. Engl. J. Med. 2020, 382, 727–733. [CrossRef] [PubMed] 2. Zhou, F.; Yu, T.; Du, R.; Fan, G.; Liu, Y.; Liu, Z.; Xiang, J.; Wang, Y.; Song, B.; Gu, X.; et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. 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