Learning to Appreciate Our Differences. Part 2
These findings deserve attention, in part because of the use of a second population for independent validation, and in part because the SNP associations are biologically plausible: the products of these genes are involved in host defense against poxviruses. Although these results already suggest further experiments to understand the mechanisms that underlie these associations, and although they already suggest potential clinical applications, it may be useful to step back and consider a variety of different paths forward.
Our genome sequence serves as a blueprint for the “system” and contains a wealth of information about vulnerabilities, strengths, and potential, most of which still remains beyond our current ability to interpret. However, the technology and methodology used in genomewide SNP assessments have matured quickly, offering an opportunity for a more agnostic, “unsupervised” approach, rather than promoting reliance on prior suspicions or assumptions with the use of targeted assays. This technology and methodology includes next‐generation sequencing platforms, mass spectroscopy, allele‐specific polymerase chain reaction, single‐nucleotide primer extension, oligonucleotide ligation techniques, high‐density oligonucleotide microarrays, and combinations of the aforementioned approaches. So‐called genomewide association (GWA) studies are increasingly common in the biomedical literature, and they have revealed previously unsuspected links between genetic loci and disease. These studies will soon provide new clues about individuals who have an elevated risk for vaccine‐associated AEs. However, GWA studies also create important new needs, including well‐characterized host populations, large numbers of cases and controls, methods for distinguishing between true‐positive and false‐positive associations, and approaches for untangling polygenic traits or epistatic effects (gene‐gene interactions). As useful as GWA studies may be for revealing host vulnerabilities and risks, other approaches will also have an important place in this area of investigation. This is because our genome is dynamic: genetic and epigenetic structural modifications, changing levels of expression, and other aspects of regulatory control suggest approaches that will add to the value of primary sequence data.
Profiles of genomic response based on mRNA abundance patterns and, more recently, on abundance patterns of microRNAs have provided novel diagnostic and prognostic information about patients with cancer and, in a fewer number of studies, patients with acute inflammatory disorders and infection. Although these genomic patterns may be used to classify patients on the basis of clinical outcome and identify hosts in whom a protective immune response has or will occur, these patterns display significant temporal and spatial dynamic properties, especially during the acute phase after exposure or perturbation. As a result, it may be necessary to measure responses from specific anatomical compartments and/or at specific time points, to draw clinically useful conclusions. More‐traditional approaches for profiling human susceptibilities to infection and immunologic AEs have focused on functional aspects of the immune system, such as the lymphocyte activation state, epitope‐specific lymphocytes, secreted cytokine levels, and antibody reactivity profiles. Although useful, these approaches restrict our attention to a narrow subset of human physiological responses. Because our history of prior and current microbial exposures plays a significant role in determining how we respond to a new encounter, it is possible that profiling of the human indigenous microbiota will contribute to a more effective risk assessment for vaccine‐ and pathogen‐associated adverse outcomes.
As the complexity and dimensionality of host genetic, genomic, and immune response profiles expand, so will the challenges of validating putative predictors, diagnostics, and biomarkers and understanding the mechanisms behind these profiles. The solutions will include large, prospective, replicated cohorts; standardized specimen collection with clinical metadata; reconsideration of criteria for assessing causal relationships; and focused experimental investigation. Reif et al. highlight several of these needs. Importantly, the results of these efforts will promote public health and strengthen strategies for prevention of infectious diseases.