Appreciating the Heterogeneity in Autoimmune Disease: Multiparameter Assessment of Intracellular Signaling Mechanisms

Statistical methods for studying disease subtype heterogeneity

A fundamental goal of epidemiologic research is to investigate the relationship between exposures and disease risk. Cases of the disease are often considered a single outcome and assumed to share a common etiology. However, evidence indicates that many human diseases arise and evolve through a range of heterogeneous molecular pathologic processes, influenced by diverse exposures. Pathogenic heterogeneity has been considered in various neoplasms such as colorectal, lung, prostate, and breast cancers, leukemia and lymphoma, and non-neoplastic diseases, including obesity, type II diabetes, glaucoma, stroke, cardiovascular disease, autism, and autoimmune disease. In this article, we discuss analytic options for studying disease subtype heterogeneity, emphasizing methods for evaluating whether the association of a potential risk factor with disease varies by disease subtype. Methods are described for scenarios where disease subtypes are categorical and ordinal and for cohort studies, matched and unmatched case-control studies, and case-case study designs. For illustration, we apply the methods to a molecular pathological epidemiology study of alcohol intake and colon cancer risk by tumor LINE-1 methylation subtypes. User-friendly software to implement the methods is publicly available.

A Meta-Regression Method for Studying Etiological Heterogeneity Across Disease Subtypes Classified by Multiple Biomarkers

In interdisciplinary biomedical, epidemiologic, and population research, it is increasingly necessary to consider pathogenesis and inherent heterogeneity of any given health condition and outcome. As the unique disease principle implies, no single biomarker can perfectly define disease subtypes. The complex nature of molecular pathology and biology necessitates biostatistical methodologies to simultaneously analyze multiple biomarkers and subtypes. To analyze and test for heterogeneity hypotheses across subtypes defined by multiple categorical and/or ordinal markers, we developed a meta-regression method that can utilize existing statistical software for mixed-model analysis. This method can be used to assess whether the exposure-subtype associations are different across subtypes defined by 1 marker while controlling for other markers and to evaluate whether the difference in exposure-subtype association across subtypes defined by 1 marker depends on any other markers. To illustrate this method in molecular pathological epidemiology research, we examined the associations between smoking status and colorectal cancer subtypes defined by 3 correlated tumor molecular characteristics (CpG island methylator phenotype, microsatellite instability, and the B-Raf protooncogene, serine/threonine kinase (BRAF), mutation) in the Nurses' Health Study (1980-2010) and the Health Professionals Follow-up Study (1986-2010). This method can be widely useful as molecular diagnostics and genomic technologies become routine in clinical medicine and public health.

Prostaglandin E2 exacerbates collagen-induced arthritis in mice through the inflammatory interleukin-23/interleukin-17 axis

OBJECTIVE

Recently, Th17 cells, a new subset of CD4+ T cells, emerged as major players in inflammation/autoimmunity. Maintenance of the Th17 phenotype requires interleukin-23 (IL-23), whereas the Th1-promoting cytokine IL-12p70 exerts a negative effect on Th17 cell differentiation. The lipid mediator prostaglandin E(2) (PGE(2)) acts primarily as a proinflammatory agent in autoimmune conditions, through mechanisms that remain to be elucidated. The aim of this study was to investigate whether PGE(2) released in inflammatory foci activates resident dendritic cells (DCs) to express IL-23 (at the expense of IL-12) and IL-6, resulting in a shift toward Th17 cell responses.

METHODS

The effect of PGE(2) on IL-23 production by DCs and subsequent induction of T cell-derived IL-17 was assessed in vitro and in vivo. The effect of the stable PGE analog misoprostol was evaluated in a murine model of rheumatoid arthritis, in conjunction with IL-23 and IL-17 expression in affected joints and draining lymph nodes.

RESULTS

In vivo administration of PGE(2) induced IL-23-dependent IL-17 production. Administration of misoprostol exacerbated collagen-induced arthritis (CIA). CIA exacerbation was associated with increased levels of IL-23p19/p40 messenger RNA and reduced expression of IL-12p35, and with increased levels of the proinflammatory cytokines IL-17, IL-1beta, IL-6, and tumor necrosis factor in the affected joint. Following ex vivo restimulation, draining lymph node cells from misoprostol-treated mice secreted higher levels of IL-17 and lower levels of interferon-gamma.

CONCLUSION

Our results indicate that PGE(2) enhances DC-derived IL-6 production and induces a shift in the IL-23/IL-12 balance in favor of IL-23, resulting in increased IL-17 production, presumably through the amplification of self-reactive Th17 cells.

Altered activation of AKT is required for the suppressive function of human CD4+CD25+ T regulatory cells

Suppression by T regulatory cells (Treg cells) is a major mechanism by which the immune system controls responses to self and nonharmful foreign proteins. Although there are many different types of Treg cells, the best characterized are those that constitutively express cell-surface IL-2Ralpha (CD25). We investigated whether altered T-cell-receptor (TCR)-mediated signaling in pure populations of ex vivo human CD4+CD25+ Treg cells might underlie their unique phenotype, including hyporesponsiveness to TCR-mediated activation and lack of cytokine production. CD4+CD25+ Treg cells displayed a consistent defect in phosphorylation of AKT at serine 473 and reduced phosphorylation of the AKT substrates FOXO and S6. Restoration of AKT activity via lentiviral-mediated expression of an inducibly active form of the kinase revealed that reduced activity of this pathway was necessary for the suppressive function of CD4+CD25+ Treg cells. These data represent the first demonstration of a causal association between altered signaling and the function of CD4+CD25+ Treg cells. Moreover, we have created the first system allowing inducible abrogation of suppression through manipulation of the suppressor cells. This system will be a powerful tool to further study the mechanism(s) of suppression by CD4+CD25+ Treg cells.

The challenge of analyzing the proteome in humans with autoimmune diseases

Analysis of blood samples from patients suffering from autoimmune diseases remains a mainstay in the clinic for initial diagnosis, prognostication, and clinical decision making. In particular, testing for the presence of serum autoantibodies has proved to be one of the most useful confirmatory assays for many different diseases. Recent genomic and transcript profiling studies have implicated certain cytokines, surface receptors, signaling pathways, and cell types in the pathogenesis of inflammatory diseases. The next obvious step is to delve into the much more complex level that follows the genome and transcriptome-the expressed proteome. This review focuses on several proteomics technologies being applied and/or developed by our laboratory for the study of autoimmunity, cancer, and cardiovascular disease, all of which are known to be associated with defects in immunity and inflammation. The findings of other participants in the recent Human Immunology Conference hosted by the Dana Foundation and the New York Academy of Sciences (May 17 & 18, 2005) are included. In particular, major pitfalls in the study of the human proteome are pointed out, and important areas for immediate investigation to move the field forward as rapidly as possible are proposed.