Distinct genetic architectures and environmental factors associate with host response to the \u03b32-herpesvirus infections

Neneh Sallah,Elena M Cornejo Castro,Robert Newton,Inês Barroso,Segun Fatumo,Alexander Dilthey ,Alexander J Mentzer,Martin Pollard ,Manjinder S Sandhu ,Nazzarena Labò ,Wendell Miley,Gershim Asiki,Elizabeth Young ,Deepti Gurdasani,Vickie Marshall,Denise Whitby,Paul Kellam,Cristina Pomilla,Martin L Hibberd,Tommy Carstensen

doi:10.1038/s41467-020-17696-2

Abstract

Kaposi’s sarcoma-associated herpesvirus (KSHV) and Epstein-Barr Virus (EBV) establish life-long infections and are associated with malignancies. Striking geographic variation in incidence and the fact that virus alone is insufficient to cause disease, suggests other co-factors are involved. Here we present epidemiological analysis and genome-wide association study (GWAS) in 4365 individuals from an African population cohort, to assess the influence of host genetic and non-genetic factors on virus antibody responses. EBV/KSHV co-infection (OR = 5.71(1.58–7.12)), HIV positivity (OR = 2.22(1.32–3.73)) and living in a more rural area (OR = 1.38(1.01–1.89)) are strongly associated with immunogenicity. GWAS reveals associations with KSHV antibody response in the HLA-B/C region (p = 6.64 × 10−09). For EBV, associations are identified for VCA (rs71542439, p = 1.15 × 10−12). Human leucocyte antigen (HLA) and trans-ancestry fine-mapping substantiate that distinct variants in HLA-DQA1 (p = 5.24 × 10−44) are driving associations for EBNA-1 in Africa. This study highlights complex interactions between KSHV and EBV, in addition to distinct genetic architectures resulting in important differences in pathogenesis and transmission.

Highlights

Narrow-sense heritability (h2) for anti-EBNA-1 IgG, anti-VCA IgG, anti-ORF73 IgG, anti-K8.1 IgG and antiK10.5 IgG traits were estimated using a linear mixed model (LMM) in FaST-LMM with two random effects, one based on genetic effects and the other on environmental effects using spatial location[31] recorded as Global Position System (GPS) coordinates as a proxy for environmental effects
To identify distinct SNPs, conditional analysis was performed in GEMMA
If any SNP was statistically significant, it was added stepwise onto the mixed model and analysed jointly; this was done until no SNPs with p < 5 × 10−9 11,33 remained

Summary

Introduction

Narrow-sense heritability (h2) for anti-EBNA-1 IgG, anti-VCA IgG, anti-ORF73 IgG, anti-K8.1 IgG and antiK10.5 IgG traits were estimated using a linear mixed model (LMM) in FaST-LMM with two random effects, one based on genetic effects and the other on environmental effects using spatial location[31] recorded as Global Position System (GPS) coordinates as a proxy for environmental effects. The statistical power to identify genetic variants of genome-wide significance and with different effect sizes given the sample size was estimated using QUANTO software (http://biostats.usc.edu/ software). We conducted analyses for all quantitative antibody traits for KSHV (N = 4365) and EBV (N = 3289 and N = 4365 (including overlapping samples from pilot study) by first applying a multivariable linear regression model adjusting for significant covariates in R.

Results

Conclusion