Abstract
The present review discusses recent studies that have identified genetic differences in inflammatory proteins associated with different phenotypic presentations of systemic inflammation. Basic genetic terminology is defined. Implications of genetic influences on the inflammatory response are discussed. The published associations of specific polymorphisms in antigen recognition pathways, proinflammatory cytokines, anti-inflammatory cytokines, and effector molecules are reviewed. The strongest and most consistent associations thus far have been with the tumor necrosis factor, lymphotoxin-α, and IL-1 receptor antagonist polymorphisms. However, large, phenotypically detailed studies are required to address all of the other potential polymorphisms in inflammatory molecule genes and their interactions.
Highlights
The fact that individual genetic differences impact on the risk for developing or dying from various diseases has long been accepted
The role of individual genetic differences as an explanation for these observations has been the subject of much speculation
During the past half-decade, advances in knowledge of the human genome, greater understanding of the inflammatory response, and the development of genotyping technologies have allowed us to start the process of identifying specific genetic mutations associated with different inflammatory phenotypes
Summary
An increasing array of polymorphisms in diverse inflammatory genes have been identified as candidates to explain part of the enormous phenotypic variability in the systemic inflammatory response. Illuminating, are already inadequate to assess the relative influence of and interactions between the currently identified loci. Phenotypically detailed studies, with adequate statistical power to address these issues are required. The size of these studies will be beyond a single institution and will require large, multicenter, collaborative efforts. Despite the size and complexity of the task, enormous potential to develop new therapeutic interventions is clearly possible once we understand and can predict individual inflammatory responses
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