Immune System Function is Best Health Indicator
Data summary of a four-color flow cytometric analysis of 40 healthy blood donors (arrayed from left to right). The intensity of the bars represents the frequency of cells (around 0.1% to 10.0%) that responded to classes of stimuli (arrayed from top down). The responses include the production of IFN-?, IL2, or TNF? among CD4+ or CD8+ T cells. White bars represent missing
Blood-cell responses offer the most information about organismal health and history
John Dunne, NewScientist, 18 Jul 2005
Faith in the promise of pharmacogenomics has changed the plan for primary healthcare. We expect, someday, that doctors will discern what medicines to prescribe based in part on the mixture of genes sitting on the paper-covered exam tables in their offices.
But while I’m delighted about personalized medicine and its attendant technical and business innovations, I doubt that pharmacogenomics will drive healthcare much. I liken it to trying to understand Los Angeles by reading its phonebook. You will quickly recognize some important names, and with sufficient cross-referencing to other databases (school, hospital, credit, and criminal records, genealogy charts, grocery shipments, etc.), you might develop a sense of what’s going on and why some neighborhoods are safer than others, but it will be difficult because the information is too granular and too static.
I’m more encouraged about gene-expression and proteomic profiling. Here, at least, are dynamic assessments of an organism’s current state, where reactions to trauma or degeneration are likely visible, though perhaps very subtle. The biggest challenge here will be sorting wheat from chaff. Most mRNA and protein species will not be changing coordinate with disease or therapy. Changes that can be informative are likely to be cell-type specific, and so lost in a sea of complex tissue or body fluid. Nonetheless, big changes will be available for analysis, and biomarkers that highlight specific cellular changes could vastly alter the course of both drug development and patient management.
Immunomodulatory therapies serve as a good example. Clinically managing immunosuppressives has long been a somewhat crude art. These drugs are dosed empirically: If the patient shows opportunistic infection or liver or kidney toxicity, back off; if the patient shows rejection of the transplant, dose up. Both situations are expensive and dangerous, and a biomarker that could enable critical and dynamic dosing would save lives.
On a smaller but still informative scale, the recent withdrawal of natalizumab, an anti-VLA4 therapeutic antibody, is illuminating. Three patients among thousands undergoing treatment with this novel class were diagnosed with progressive multifocal leukoencephalopathy, a rare and often fatal disease associated with failure to control a common virus. Biomarkers that would allow clinicians to recognize such dangers will be critical.