The variability of the humoral response to antigenic stimulation has been documented for a long time 1 . While it is partly due to demographic and environmental factors, a substantial part of this variation is heritable and can thus be attributed to differences in the host genome. For example, human genetic factors were estimated to account for 35% (±6%) and 21% (±5%) of the variance in H. pylori and T. gondii antibody levels, and 60% (±11%) and 57% (±11%) of the variance in cytomegalovirus (CMV) and Epstein-Barr virus (EBV) serostatus, respectively 2 . This high heritability makes serological phenotypes highly promising targets for human genomic studies. study (GWAS) and meta-analysis in a total of 15,660 healthy individuals of European ancestry from three studies from Switzerland, the United Kingdom and Germany.
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The Cohorte Lausannoise (CoLaus) is a population-based prospective study that started in 2003 in Lausanne, Switzerland 13 . It includes 6,188 individuals of European descent (47.5% male) initially aged 35 to 75 years (mean ± SD: 51.1 ± 10.9), who were randomly selected from the general population and continuously undergo a follow-up every 5 years. Detailed phenotypic information was obtained from every study participant through questionnaires, a physical assessment and biological measurement of blood and urine markers. The institutional Ethics
Committee of the University of Lausanne, which afterwards became the Ethics Commission of Canton Vaud (www.cer-vd.ch) approved the baseline CoLaus study (reference 16/03, decisions of 13th January and 10th February 2003), and written consent was obtained from all participants.
The Göttingen Research Association for Schizophrenia (GRAS) Data Collection consists of 2,363 immunocompetent adults of European ancestry, comprising 1,147 anonymized blood donors (62.0% male, mean age ± SD: 37.5 ± 13.2) and 1,216 individuals with psychiatric diagnoses (64.9% male, mean age ± SD: 40.6 ± 13.5) 14, 15 . All study participants provided informed consent, including genetic testing, and the GRAS Data Collection has been approved by the ethical committee of the Georg-August-University of Göttingen (master committee) as well as by the respective local regulatory / ethical committees of all collaborating centers 15 .
The UK Biobank (UKB) is a population-based prospective study whose recruitment process has been described previously 16 . Briefly, half a million men and women aged 40-69 years (45.6% male, mean age ± SD: 56.5 ± 8.1) attended one of 22 UKB assessment centers located throughout England, Scotland and Wales between 2006 and 2010. All participants completed a touchscreen questionnaire, verbal interview and had a range of physical measurements and blood, urine and saliva samples taken for long-term storage. A subset of 20,000 individuals attended a repeat . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted November 4, 2020. ; https://doi.org/10.1101/2020.11.02.20224402 doi: medRxiv preprint assessment between 2012 and 2013. This project was conducted with approved access to UKB data under application numbers 50085 (PI: Fellay) and 43920. All UKB participants provided informed consent at recruitment. Ethics approval for the UKB study was obtained from the North West Centre for Research Ethics Committee (11/NW/0382).
To assess humoral responses to polyomaviruses, serum samples were independently shipped by the three studies to the Infections and Cancer Epidemiology Division at the German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ) in Heidelberg. Seroreactivity against BKPyV, HPyV6, JCPyV, MCPyV and WUPyV viral capsid protein 1 (VP1) was measured at serum dilution 1:1000 using multiplex serology based on glutathione-S-transferase (GST)-VP1 fusion capture immunosorbent assays combined with fluorescent bead technology 17 . Antigen preparation and methodology, as well as robustness of seroprevalence estimates, have been described previously for human polyomaviruses 18 . For the quantitative IgG level association analyses including only seropositive individuals, results above assay cut-off of 250 mean fluorescence intensity (MFI) were used. For the case-control study design, results were expressed as a binary output (serostatus: anti-polyomavirus IgG positive or negative) based on the same assay cut-off. Using the same assay, seroreactivity against six H. pylori antigens (HP1564 OMP, HP10 GroEL, HP547 CagA, HP887 VacA, HP73 UreaseA and HP875 Catalase) and four EBV antigens (VCA p18, EBNA, Zebra and EA-D) were measured in CoLaus. individuals were included for further analyses. Variants were excluded if they were missing in . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted November 4, 2020. ; https://doi.org/10.1101/2020.11.02.20224402 doi: medRxiv preprint >5% of the subjects or if they deviated significantly from Hardy-Weinberg equilibrium (HWE, P<10e-7), resulting in 697,923 SNPs kept for phasing and imputation.
To statistically estimate the haplotypes, the genotypes were phased using EAGLE2 v2.0.5 software and the Haplotype Reference Consortium (HRC) r1.1 reference panel 20, 21 . Genotype imputation was performed using two independent reference panels: the HRC reference panel and the merged 1000 Genomes Phase 3 and UK10K reference panel 20, 22, 23 . Both phasing and imputation were performed using the Sanger Imputation Service (https://imputation.sanger.ac.uk). The imputed data set (N=89 million SNPs) consisted of a) SNPs imputed with HRC reference panel only, b) SNPs imputed with the merged reference panel only, and c) SNPs with the highest imputation information (INFO) score if imputed with both reference panels. To filter out poorly imputed or rare genotypes, SNPs with INFO score < 0.8, minor allele frequency (MAF) < 1% or significant deviation from HWE (P<10e-7) were excluded, resulting in a final number of 9,031,264 SNPs available for association analysis. We also imputed 111 four-digit classical HLA alleles using SNP2HLA and the T1DGC Immunochip/HLA reference panel 24 .
Genome-wide association analyses were performed using mixed models in GCTA 25 . HLA association analyses were performed using generalized linear models in PLINK v2 26 . We assumed an additive model for SNP associations and a dominant model for associations with HLA alleles.
The top three principal components of ancestry, sex and age were used as covariates in all analyses.
Genome-wide SNP genotyping of GRAS study participants was performed using an Axiom®myDesignTM genotyping array (Affymetrix, Santa Clara, CA, USA). The quality control steps have been described previously 3 . Imputation of unobserved genotypes was performed using the 1,000 Genomes Project Phase 1 v3 haplotypes as reference panel. Genotypes were pre-phased with MaCH v19 and subsequently imputed by minimac 27 . SNPs with a reported INFO score < 0.8 or a MAF < 5%, as well as markers on sex chromosomes, were excluded from downstream analyses. SNPs were also filtered on the basis of missingness (excluded if <95% genotyping rate), and marked deviation from HWE (excluded if P<5e-07). We then used linear regression models in PLINK v1.9 to test for association between ~6 million SNPs and IgG responses using a continuous, quantitative approach (log-normalized IgG levels in seropositive samples) 26 . The first . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted November 4, 2020. ; https://doi.org/10.1101/2020.11.02.20224402 doi: medRxiv preprint three principal components of ancestry, calculated using GCTA (v1.24), as well as sex and age, were included as covariates in all analyses 25 .
Genotyping and imputation of UK Biobank individuals have been fully described by Bycroft et al. 28 . Briefly, samples were genotyped on either the UK BiLEVE Axiom array (Affymetrix) or UK Biobank Axiom array (Applied Biosystems). Genotypes were phased using SHAPEIT3 and the 1000 Genome phase 3 dataset as a reference, then imputed using IMUTE4 using the Haplotype Reference Consortium data, 1000 Genomes phase 3, and UK10K data as references. Serological markers of infection were measured for a random subset of 9,611 unrelated UKB participants (44.0% male, mean age ± SD: 56.5 ± 8.2) 29 . Association analyses were carried out using rankbased inverse normal transformed MFI values and linear mixed models as implemented in BOLT-LMM 30,31 , using age at recruitment and genetic sex as covariates, and variants with a MAF > 0.01 and an INFO score > 0.3.
Meta-analyses of the GWAS results obtained in the different cohorts were performed using a fixedeffect model in METAL 32 . For BKPyV and JCPyV, summary statistics of all three studies were used. For HPyV6 and WUPyV only the results of CoLaus and GRAS studies were used, and for MCPyV only the results of UKB and GRAS were used, as the data were not available in the UKB and CoLaus, respectively (Figure 1 ). The meta-analyses followed the sample size-based strategy, considering P-value, sample size and direction of effect. Bonferroni-corrected significance level threshold of P=5.6e-09 (P=5e-08 divided by the eight GWAS performed) was applied. Similarly, for HLA alleles, we determined significance thresholds correcting for the number of alleles, the viruses tested, and the two study designs (P=4.3e-05).
FUT2 secretor status was determined from the rs601338 genotype, where the wild-type rs601338 (G) encodes the secretor allele, whereas A is the nonsense "non-secretor" allele. Individuals with . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted November 4, 2020. ; https://doi.org/10.1101/2020.11.02.20224402 doi: medRxiv preprint homozygous major (GG) or heterozygous (GA) genotypes were considered as secretors, and compared to homozygous minor (AA) non-secretors 33 .
A total of 12 RNA samples from gastrointestinal tissue (200 ng to 225 ng each) were obtained from the Genotype-tissue expression project (GTEx) 34 Samples were incubated for 5 min at 20°C followed by 5 min at 65°C. The reactions were purified by using Agencourt AMPure XP beads (Beckman Coulter) and further ligated to HP-adapter using Blunt/TA Ligase Master Mix (New England BioLabs) with 10 min incubation at room temperature. Adapted DNA was purified using Dynabeads MyOne Streptavidin C1 (Life Technologies) and washed to remove unbounded DNA. The captured cDNAlibrary was eluted by resuspending the beads in ONT's Elution Buffer for 10 min at 37°C and the beads were pelleted using a magnetic rack leaving the supernatant containing the library. We used poretools 35 to extract fasta sequences from the ONT fast5 format, with a minimum length of 600 base pairs and forward and reverse strand sequence (2d reads). We then used nanocorrect 36 for computational . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted November 4, 2020. ; https://doi.org/10.1101/2020.11.02.20224402 doi: medRxiv preprint error correction and aligned all corrected reads to a list of MUC1 isoforms using the LAST aligner 37 . Each read was assigned to the isoform with the best alignment score.
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We included 3,689 individuals from CoLaus study (46% males, mean age ± SD: 53.1 ± 10.6), 2,363 from GRAS Data Collection (63% males, mean age ± SD: 39.1 ± 13.5) and 9,351 from the UKB (44% males, mean age ± SD: 56.5 ± 8.2), resulting in a total of 15,660 individuals with available genotyping data, serological data and covariates. All tested polyomaviruses had high seroprevalence in the three samples, with highest observed seroprevalence for WUPyV (96%), followed by BKPyV (91%), HPyV6 (84%), MCPyV (73%) and JCPyV (55%) ( Table 1 ). In all cohorts combined, the serological responses against several polyomaviruses correlated with age and sex, confirming previous observations 3, 38, 39 . We observed a significant decrease with age in antibody levels against BKPyV (P<2e-16), JCPyV (P=4.56e-03), MCPyV (P=5.77e-03) and
WUPyV (P<2e-16); and lower IgG levels against HPyV6 (P=3.51e-15), JCPyV (P<2e-16) and
MCPyV (P=1.07e-05) in female participants.
We performed a total of nine independent GWAS using either a case-control study design (serostatus: antibody-positive versus antibody-negative) or a continuous, quantitative approach (IgG levels in seropositive individuals) to search for human genetic determinants of the antibody response to BKPyV and JCPyV in the three cohorts, to HPyV6 and WUPyV in CoLaus and GRAS, and to MCPyV in GRAS and UKB (Figure 1) . We did not run a case-control analysis for WUPyV because of the very high seroprevalence of that virus (96%). Meta-analyses were conducted using GWAS summary statistics. For each of the five phenotypes, meta-analytic inflation factors l ranged from 0.99 to 1.01 across the tested cohorts, indicating proper control of population stratification ( Figure S1 ). In total, we identified four genome-wide significant loci, mapping to the HLA (for HPyV6, JCPyV and MCPyV), FUT2 (for BKPyV and JCPyV), STING1 (for MCPyV) and MUC1 (for WUPyV) regions (Figure 2) .
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Significant associations were observed in the HLA class II region on chromosome 6 for HPyV6, JCPyV and MCPyV (Figure 2) , with the lead variants being rs9272624 (P=9.62e-14), rs112463084 (P=2.18e-20) and rs147658078 (P=8.09e-20), respectively. To further dissect the association signals, we imputed 4-digit HLA alleles and tested them for association with anti-HPyV6, anti-JCPyV and anti-MCPyV VP1 IgG levels. The regional association plots are shown in Figure S2 and resulting association p-values are listed in Table 2 . We observed strong associations with quantitative seroreactivity for HLA-DRB1 and HLA-DQA1 alleles for all three human polyomaviruses. The size and directionality of the effects were virus-specific.
We observed significant associations in the FUT2 gene on chromosome 19 for BKPyV and JCPyV (Figure 2) . The fucosyltransferase 2 protein, encoded by FUT2, is expressed in epithelial cells and adds fucose to type 1 glycoprotein chains to form soluble ABH antigens that can be found in secretions and fluids 33, 40 . The top associated SNPs for BKPyV (rs681343, P=6.40e-16) and JCPyV (rs12462111, P=4.84e-10) are in high linkage disequilibrium (LD, r 2 > 0.7) with the common FUT2 nonsense variant rs601338 (P=6.81e-16 and P=1.89e-09, respectively). The homozygous genotype for the rs601338 minor allele (AA) is classically referred to as the "non-secretor" variant, as individuals homozygous for this null allele do not secrete blood group antigens at epithelial surfaces 33, 40 . Among the three cohorts, 24% of individuals were FUT2 non-secretors (AA), and 76% were FUT2 secretors (GG or GA). Overall, we observed that non-secretors had significantly higher IgG levels against both polyomaviruses in comparison to secretors (Figure 3 ).
We observed genome-wide significant associations with anti-MCPyV IgG levels in the STING1 gene on chromosome 5 (Figure 2) . STING1 encodes the endoplasmic reticulum resident membrane protein STING that functions as a major regulator of innate immunity. Upon viral infection and activation of systolic cyclic GMP-AMP synthase (cGAS), STING mediates type I . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted November 4, 2020. ; https://doi.org/10.1101/2020.11.02.20224402 doi: medRxiv preprint interferon production by infected cells to protect them and neighboring cells from local infection 41 . The top associated variant in meta-analysis using GRAS and UKB was rs7444313 (P=5.95e-15), a strong eQTL for STING1 in the GTEx dataset, whose G allele was associated with a stronger IgG response against MCPyV VP1 34 .
We observed a genome-wide significant association with anti-WUPyV IgG levels on chromosome 1, mapping to the MUC1 gene that encodes the Mucin1 protein (lead SNP rs12411216, P=2.70e-30; Figure 2 ). This variant is in perfect LD (r 2 =1) with the splicing variant rs4072037 (P=4.08e-30) located in the second exon of the MUC1 gene. The rs4072037 T allele was associated with a stronger IgG response against WUPyV VP1. The same allele was previously associated with an increased risk of gastric cancer 42, 43 . Because infections with H. pylori and EBV have been implicated in the pathogenesis of gastric cancers, we searched for potential associations of rs4072037 with the humoral response to these pathogens [44] [45] [46] [47] . Using GWAS data available in CoLaus, we performed serological analyses for six different H. pylori antigens and four EBV antigens, but did not find evidence for a rs4072037-dependent differential antibody response (Table S1 ).
The SNP rs4072037 has been functionally investigated previously, and was shown to cause alternative splicing at the 5' end of exon 2, leading to the absence or presence of 9 amino acids in the signal peptide region 43 . Due to the difficulty of determining full exon connectivity from shortread sequencing data, the distribution of isoforms remained unclear. Therefore, we have decided to use nanopore sequencing technology allowing us to investigate sequencing long reads. We obtained 12 stomach RNA samples from GTEx, six from homozygous carriers of the rs4072037 major allele T, and six from homozygous carriers of the minor allele C 34 . We amplified the MUC1 region and sequenced all barcoded amplicons on a single flow cell on the MinION sequencing device. In total, we obtained 1,121 reads spanning the full-length MUC1 isoforms, i.e. having assignable barcodes at both ends for downstream analysis (Figure S3 and S4; Table S2 ). We . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted November 4, 2020. ; https://doi.org/10.1101/2020.11.02.20224402 doi: medRxiv preprint exclusively observed an isoform with a short exon 2 in the TT individuals, whereas a longer isoform was always present in the CC individuals, thereby confirming the modulating effect of rs4072037 genotype on MUC1 splicing.
We then investigated whether the genetic architecture of antibody levels against human polyomaviruses is similar to that of serostatus to these same polyomaviruses. Serological status was defined based on the manufactures defined cut-off of 250 MFI (see Methods). Individuals with levels of IgG antibodies above the threshold were considered seropositive (cases), while those below the threshold were seronegative (controls) ( Table 1) . Case-control GWAS using logistic regression were performed independently in the three cohorts and meta-analyzed 32 . Q-Q plots revealed no inflation of the test statistics for HPyV6 (l=0.99) and JCPyV (l=0.98), while MCPyV (l=0.90) and BKPyV (l=0.72) showed varying degrees of deflation ( Figure S1 ). Chicago plots for the genome-wide significant loci are presented in Figure 2 . We observed again evidence of an involvement of HLA class II variation for JCPyV (rs9271025, P=4.31e-46) and MCPyV (rs73401330, P=8.49e-29) ( Table 2) . Strongest associations with seropositivity were observed for HLA-DQB1 allele. We also replicated the associations observed in FUT2 for JCPyV (rs2432132, P=1.70e-15) and STING1 for MCPyV (rs55792153, P=2.97e-09). Associations with FUT2 and HLA variants were not replicated for BKPyV and HPyV6, respectively. In addition, the casecontrol analyses did not reveal any additional associated region, suggesting that there are no SNPs purely associated with susceptibility.
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The copyright holder for this preprint this version posted November 4, 2020. ; https://doi.org/10.1101/2020.11.02.20224402 doi: medRxiv preprint Discussion Human polyomaviruses are highly prevalent and can cause severe disease in immunocompromised individuals. They present a wide range of tissue tropisms and appear to cause neurologic, renal, and skin diseases [48] [49] [50] Genes within the HLA region are prime candidates for susceptibility to viral infection and regulation of the immune response. HLA has been associated with multiple infectious diseases, such as HIV, hepatitis B, hepatitis C, and tuberculosis 52 . In this study, we confirm the involvement of HLA variation in the modulation of humoral immune response to two polyomaviruses, JCPyV and MCPyV 3,5,53 . Specifically, we observed the strongest associations with quantitative antibody levels for HLA-DRB1 and HLA-DQA1 alleles, and with seropositivity for HLA-DQB1 allele.
Our study also shows that FUT2 variation (rs601338 G>A) plays a role in the determination of antibody levels against BKPyV and JCPyV VP1. The FUT2 enzyme catalyzes the addition of a fucose residue to type 1 glycoprotein chains to form ABH blood group antigens that are released in secretions and at mucosal surfaces 54 . Consistent with previous reports, 78% of our study population carried at least one functional allele, which is sufficient to render an individual FUT2 secretor, whereas 22% of individuals were found to be homozygous for the nonsense variant leading to defective FUT2 and the absence of ABH antigens in secretions (FUT2 non-secretors) 33, 55 . Interestingly, non-secretors had significantly higher IgG titers against BKPyV and JCPyV compared to secretors, suggesting higher antigen exposure and/or stronger immune response. One hypothetic explanation is that the binding of polyomaviruses to host cell sialic acid receptors could be impaired in the presence of FUT2-dependent blood antigens on the mucosal surfaces.
Consequently, non-secretors might be more permissive to viral propagation and replication than . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted November 4, 2020. ; https://doi.org/10.1101/2020.11.02.20224402 doi: medRxiv preprint secretors. The same FUT2 variant is known to have an impact on several infections: non-secretors are protected against norovirus and rotavirus, but are at higher risk of infection with other pathogens, including e.g. Candida albicans, Streptococcus pneumoniae and mumps [55] [56] [57] [58] [59] [60] . The capacity to generate soluble ABH blood group antigens, dependent on the functionality of the FUT2 enzyme, represents an important modulator of infectious disease susceptibility in humans.
Our analyses confirm the implication of the STING1 gene in the determination of antibody levels against MCPyV VP1, which was recently reported by Kachuri et al. 61 is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted November 4, 2020. ; https://doi.org/10.1101/2020.11.02.20224402 doi: medRxiv preprint to alter the physiological functions of MUC1 because it leads to an alternative splicing of the 5'region of exon 2. As a consequence, a shorter protein isoform is produced, which impairs the protective function of MUC1 on the gastric mucosa 67 . The rs4072037 T/T genotype has been previously associated with an increased risk of gastric cancer 67,68 , most likely due to a concomitant increase in the risk of gastritis due to Helicobacter pylori infection 69 . The newly discovered association with humoral response to WUPyV is most likely coincidental. Indeed, the absence of any trace of WUPyV in cancer samples suggests that this virus is unlikely to play any role in gastric carcinogenesis 70 . However, our results suggest once again that MUC1 plays an essential role in the protection of gastric mucosa, and that a common, genetically-encoded alteration of MUC1 has a deleterious impact on that important physiological function.
For human polyomaviruses with seroprevalence below 95%, we investigated the relationship between the genetic contribution to serostatus and humoral immune response in seropositive individuals. Whereas the quantitative approach is purely looking at immune response in infected individuals, the case-control study design has the potential to also uncover genetic loci involved in susceptibility to infection. Our meta-analysis results suggest very similar genetic contributions to the continuous (quantitative) and binary (case-control) phenotypes, with comparable statistical strength. The same variable genetic loci in HLA class II, FUT2 and STING1 were found to be associated with JCPyV6 and MCPyV serostatus and IgG levels. These similarities in the results could be explained by the impossibility of being able to differentiate between individuals who were never infected and individuals who were infected but had an extremely weak antibody response.
Here we report the first meta-analyses aiming to identify human genetic determinants of the humoral immune response against multiple polyomaviruses. Statistically combining data from CoLaus, GRAS and a subset of the UKB, allowed us to run analyses on a total of 15,660 individuals of European ancestry. This provided greater statistical power and a more accurate estimate of the underlying effects, also reducing the risk of false-negative results. Some limitations need however to be considered. First, we did not have serological data for all five polyomaviruses in each cohort. Second, the meta-analyses relied on summary statistics derived from independently computed GWAS, which might result in biases due to differences in the design, analysis and . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted November 4, 2020. ; https://doi.org/10.1101/2020.11.02.20224402 doi: medRxiv preprint conduct of the individual studies. Third, our analyses were restricted to individuals of European ancestry, which limits the generalizability of our results. Finally, as mentioned above, individuals with very low IgG levels were excluded from the quantitative association analyses, due to the impossibility of distinguishing them from truly seronegative (i.e. never infected) study participants; this resulted in reduced statistical power.
In summary, we here report strong associations of HLA class II, FUT2, STING1, and MUC1 genetic variants with the intensity of the humoral IgG response to multiple human polyomaviruses.
Together, these results demonstrate the modulating contribution of host genetic variation to the individual response against some of the most prevalent human viruses.
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The copyright holder for this preprint this version posted November 4, 2020. ; https://doi.org/10.1101/2020.11.02.20224402 doi: medRxiv preprint Tables   Table 1. Descriptive statistics of polyomavirus infections in the three cohorts. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted November 4, 2020. ; https://doi.org/10.1101/2020.11.02.20224402 doi: medRxiv preprint SNPs are plotted on the x-axis according to their physical position on each chromosome and the strength of the association with antibody levels is indicated on the y-axis (as -log10 P-value for IgG response, and as +log10 P-value for serostatus). The dashed line marks the Bonferroni-corrected genome-wide significance threshold of 5.6e-09. For each locus, the SNP with the most significant association is plotted in red and labeled. Serostatus was not tested for WUPyV due to very high seroprevalence. Chromosome X is not shown since data were not available for all studies.
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