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Humans exhibit considerable variability in their immune responses to the same immune challenges. Such variation is widespread and affects individual and population-level susceptibility to infectious diseases and immune disorders. Although the factors influencing immune response diversity are partially understood, what mechanisms lead to the wide range of immune traits in healthy individuals remain largely unexplained. Here, we discuss the role that natural selection has played in driving phenotypic differences in immune responses across populations and present-day susceptibility to immune-related disorders. Further, we touch on future directions in the field of immunogenomics, highlighting the value of expanding this work to human populations globally, the utility of modeling the immune response as a dynamic process, and the importance of considering the potential polygenic nature of natural selection. Identifying loci acted upon by evolution may further pinpoint variants critically involved in disease etiology, and designing studies to capture these effects will enrich our understanding of the genetic contributions to immunity and immune dysregulation., (© 2024 The Authors. Immunological Reviews published by John Wiley & Sons Ltd.)

Motivation: Human epigenomic data has been generated by large consortia for thousands of cell types to be used as a reference map of normal and disease chromatin states. Since epigenetic data contains potentially identifiable information, similarly to genetic data, most raw files generated by these consortia are stored in controlled-access databases. It is important to protect identifiable information, but this should not hinder secure sharing of these valuable datasets., Results: Guided by the Framework for responsible sharing of genomic and health-related data from the Global Alliance for Genomics and Health (GA4GH), we have developed an approach and a tool to facilitate the exploration of epigenomics datasets' aggregate results, while filtering out identifiable information. Specifically, the EpiVar Browser allows a user to navigate an epigenetic dataset from a cohort of individuals and enables direct exploration of genotype-chromatin phenotype relationships. Because individual genotypes and epigenetic signal tracks are not directly accessible, and rather aggregated in the portal output, no identifiable data is released, yet the interface allows for dynamic genotype-epigenome interrogation. This approach has the potential to accelerate analyses that would otherwise require a lengthy multi-step approval process and provides a generalizable strategy to facilitate responsible access to sensitive epigenomics data., Availability and Implementation: Online portal: https://computationalgenomics.ca/tools/epivar; EpiVar Browser source code: https://github.com/c3g/epivar-browser; bw-merge-window tool source code: https://github.com/c3g/bw-merge-window., (© The Author(s) 2024. Published by Oxford University Press.)

Humans display remarkable interindividual variation in their immune response to identical challenges. Yet, our understanding of the genetic and epigenetic factors contributing to such variation remains limited. Here we performed in-depth genetic, epigenetic and transcriptional profiling on primary macrophages derived from individuals of European and African ancestry before and after infection with influenza A virus. We show that baseline epigenetic profiles are strongly predictive of the transcriptional response to influenza A virus across individuals. Quantitative trait locus (QTL) mapping revealed highly coordinated genetic effects on gene regulation, with many cis-acting genetic variants impacting concomitantly gene expression and multiple epigenetic marks. These data reveal that ancestry-associated differences in the epigenetic landscape can be genetically controlled, even more than gene expression. Lastly, among QTL variants that colocalized with immune-disease loci, only 7% were gene expression QTL, while the remaining genetic variants impact epigenetic marks, stressing the importance of considering molecular phenotypes beyond gene expression in disease-focused studies., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Previously, we showed that a massively parallel reporter assay, mSTARR-seq, could be used to simultaneously test for both enhancer-like activity and DNA methylation-dependent enhancer activity for millions of loci in a single experiment (Lea et al., 2018). Here, we apply mSTARR-seq to query nearly the entire human genome, including almost all CpG sites profiled either on the commonly used Illumina Infinium MethylationEPIC array or via reduced representation bisulfite sequencing. We show that fragments containing these sites are enriched for regulatory capacity, and that methylation-dependent regulatory activity is in turn sensitive to the cellular environment. In particular, regulatory responses to interferon alpha (IFNA) stimulation are strongly attenuated by methyl marks, indicating widespread DNA methylation-environment interactions. In agreement, methylation-dependent responses to IFNA identified via mSTARR-seq predict methylation-dependent transcriptional responses to challenge with influenza virus in human macrophages. Our observations support the idea that pre-existing DNA methylation patterns can influence the response to subsequent environmental exposures-one of the tenets of biological embedding. However, we also find that, on average, sites previously associated with early life adversity are not more likely to functionally influence gene regulation than expected by chance., Competing Interests: RJ, KA, LB, AL No competing interests declared, JT Reviewing editor, eLife, (© 2023, Johnston et al.)