Learning to Appreciate Our Differences
- Department of Medicine and Department of Microbiology and Immunology, Stanford University, Stanford
- Veterans Affairs Health Care System, Palo Alto, California
- Reprints or correspondence: Dr. David A. Relman, VA Palo Alto Health Care System 154T, 3801 Miranda Ave., Palo Alto, CA 94304 (relman{at}stanford.edu).
(See the article by Reif et al., on pages 16–22.)
Despite overall levels of genetic similarity and shared physiological characteristics across the species, humans vary quite a bit in their individual responses to biological stress and noxious stimuli. Sometimes variant responses are dramatic and clinically important. This is certainly the case with respect to the responses of humans to microbial pathogens and their antigens. The consequences of infection by a pathogen in a host population vary from benign to catastrophic, as a complex function of the host genetics, the history of prior exposures and experiences, the current state of immune activation (both local and systemic), and, probably, a variety of other factors, including host nutritional status and the composition and structure of the indigenous microbiota. Although typical responses to vaccines are favorable, occasional responses are pathologic and costly to the host. If these aberrant responses could be predicted and understood mechanistically (the first element does not necessarily require the second), we would be able to reduce the number and/or severity of vaccine adverse events (AEs), improve vaccine design, and create personalized strategies for eliciting immune protection. In this issue of the Journal, Reif et al. [1] address this goal and provide an opportunity to discuss challenges and possible solutions.
Reif et al. [1] collected host genetic sequence data from 2 independent studies of the smallpox vaccine (Aventis Pasteur) in vaccinia virus-naive adults. Of 85 vaccinated subjects included in the first study, 16 developed a systemic AE (fever, lymphadenopathy, or generalized rash). Twenty-four of the 46 vaccinated subjects included in the second study developed 1 of these 3 systemic AEs.
The investigators obtained data on 1442 single-nucleotide polymorphisms (SNPs) located in or near ∼386 genes, as drawn from the National Cancer Institute Cancer Genome Anatomy Project SNP500Cancer Database [2], which includes genes or specific genetic variants associated with signaling pathways, immune response, and oncogenesis. These SNPs were assayed using a highly parallel genotyping technology based on allele-specific primer extension, ligation, amplification, and hybridization to bead-based oligonucleotide arrays (Illumina) [3]. Only the 36 SNPs (linked to 26 genes) that were found to have an AE-associated P value ≤.05 in the first study were assessed in the second study. Of these 36 SNPs, 3 were found to have an AE-associated P value ≤.05. One SNP is located in the 5,10-methylenetetrahydrofolate reductase (MTHFR) gene (P < .01), and 2 SNPs are located in the interferon regulatory factor-1 (IRF1) gene. In addition, 3 SNPs in the interleukin-4 (IL4) gene were significantly associated with AEs in the first study (P = .05) but did not quite achieve statistical significance in the second study (P = .06).
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 [4]. 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 withthe 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 [5, 6]. 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 [7], 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) [8]. 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 [9] have provided novel diagnostic and prognostic information about patients with cancer and, in a fewer number of studies, patients with acute inflammatory disorders [10] 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 [11], these patterns display significant temporal [10] 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 pro ling 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 [12], secreted cytokine levels [13, 14], 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 [15, 16]; and focused experimental investigation. Reif et al. [1] highlight several of these needs. Importantly, the results of these efforts will promote public health and strengthen strategies for prevention of infectious diseases.
Footnotes
-
Potential conflicts of interest: D.A.R. is a member of the scientific advisory boards of Novartis, NanoBio, Cepheid, and Applied Biosystems.
-
Financial support: National Institutes of Health Director's Pioneer Award; Doris Duke Distinguished Clinical Scientist Award.
- Received March 19, 2008.
- Accepted March 19, 2008.
- © 2008 by the Infectious Diseases Society of America.
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