The human immune system has a highly complex, multi-layered structure which has evolved to detect and respond to changes in the internal microenvironment of the body. Recognition occurs at the molecular or submolecular scale, via classical reversible receptor-ligand interactions, and can lead to a response with great sensitivity and speed. Remarkably, recognition is coupled to memory, such that responses are modulated by events which occurred years or even decades before. Although the immune system in general responds differently and more vigorously to stimuli entering the body from the outside (e.g. infections), this is an emergent property of the system: many of the recognition molecules themselves have no inherent bias towards external stimuli (non-self) but also bind targets found within the body (self). It is quite clear that the immune response registers pathophysiological changes in general. Cancer, wounding and chronic tissue injury are some obvious examples. Against this background, the immune system 'state' tracks the internal processes of the body, and is likely to encode information regarding both current and past disease processes. Moreover, the distributed nature of most immune responses (e.g. typically involving lymphoid tissue, non-lymphoid tissue, bone marrow, blood, extracellular interstitial spaces, etc.) means that many of the changes associated with immune responses are manifested systemically, and specifically can be detected in blood. This provides a very convenient route to sampling immune cells. We consider two different and complementary ways of querying the human immune 'state' using high-dimensional genomic screening methodologies, and discuss the potentials of these approaches and some of the technological and computational challenges to be overcome.
Keywords: T-cell repertoire; microarray; next generation sequencing; transcriptomics.