Adaptive Pharmacogenomics, LLC

(I have asked my colleague, Dr. Sean David, to make some comments for this posting).

In 1971, Abdel Omran coined the term “epidemiological transition” to describe the shift from “pestilence and famines” to “man-made diseases” to the leading causes of morbidity and mortality observed with modernization and implementation of public health policies in developed nations. As chronic illness and the behaviors that modify risk for heart disease, cancer and stroke became the principal causes of death, so to did the public health and clinical response shift to prevention and treatment of these “man-made diseases” 1. Paradoxically, however, until recently the conventional view of the role of genomics in medicine has focused largely on predicting rare, highly penetrant genetic disorders that in many cases are neither preventable nor treatable. However, the enthusiasm for the potentially major contribution of genetic testing to treat chronic illnesses and their risk factors by the academic community has been tepid.

Reasons for either non-endorsement or caveats against using genetic testing to guide pharmacotherapy for smoking cessation, lipid disorders, diabetes, heart disease and cancer have frequently included observations of small effect sizes for disease risk prediction, the relatively greater contribution of non-genetic factors amenable to population-based interventions for prevention, the need to demonstrate that genetic testing improves outcomes, a lack of evidence that genetic testing changes health behavior in optimal ways and concerns about privacy protection 2-4.

Each of these rationales for resistance to widespread use of genetic tests for the treatment of common, chronic illnesses and health behaviors are, however, rooted in either the conflation of predictive genetics tests with pharmacogenomics, the implication that by adding genomic testing to our clinical toolboxes that we ignore public health interventions or will no longer advice our patients to eat better, exercise more or stop smoking, or fallacies about the evidence base for improved outcomes and either harmless or enhancing impact of communicating personal genomic data to guide treatment. An adequate rejoinder to each of the fallacies commonly underlying caveats against clinical pharmacogenomics would require a much broader discussion than would be possible here. Suffice it to say that in fact the effect sizes for many pharmacogenomic tests for any one polymorphism are often far greater than those observed for predictive genetic tests for common, chronic illnesses and the corpus of data showing the major clinical impact of these data is growing rapidly. Moreover, the Genetic Information Nondiscrimination Act of 2008 greatly advanced the protection of privacy and from genetic discrimination 5.

As reported in previous editions of the PharmGKB blog, evidence-based clinical pharmacogenomics guidelines are being iteratively released by the Clinical Pharmacogenomics Implementation Consortium (CPIC) and PharmGKB is effectively disseminating genomic clinical annotations 6. Moreover, in a recent paper in the New England Journal of Medicine, Topol and colleagues reported results from a study of more than 2,000 individuals who received genomewide testing and received personal genomic feedback regarding risk for many common, chronic diseases including diabetes, cancer, rheumatoid arthritis and neurodegenerative disorders including multiple scleroris and alzheimer’s disease. The investigators found no significant short-term changes in psychological health, diet or exercise or use of screening tests that would not be appropriate for asymptomatic individuals.

As a result of the encouraging trend of emerging pharmacogenomic tests of high clinical utility and validity without increase risk for unintended psychological or behavioral consequences and evolving debate amongst opinion leaders, clinical genomics is undergoing a measured but nonetheless advancing change in paradigm.
Just as it took decades for public health and medicine to adapt to a primary and secondary prevention-based approach to the epidemiological transition from “pestilence and famines” to “man-made diseases”, it has taken decades to broaden the view of genetic testing for mutations prediction of rare diseases with high penetrace diseases like Tay-Sachs or Cystic Fibrosis to the treatment of (not prediction for) common, low-penetrance illnesses. Contrary to the notion that clinical pharmacogenomics is a “risk-based strategy”, the population impact of widespread use of evidence-based clinical pharmacogenomics resulting in even small improvements in drug response and safety would be massive.

In the words of Sir David Weatherall and colleagues, “research in basic human biology and the biomedical sciences is entering the most exciting phase of its development. However, it is difficult to anticipate when the gains of this explosion in scientific knowledge will become available for the prevention and treatment of the major killers of mankind. Thus, medical research must strike a balance between the well-tried approaches of epidemiology, public health, and clinical investigation at the bedside with the application of discoveries in the completely new fields of science that have arisen from the genome revolution” 7.
To the degree that clinical best practice models, regulatory frameworks and establishment of cost-effectiveness of genomic testing are the subject for debate within the scientific and clinical communities and are rapidly undergoing translation and dissemination, 2011 could be a landmark year in the epidemiological transition for genetic risk prediction to treatment-based genomic medicine.



1. Omran AR. The epidemiologic transition. A theory of the epidemiology of population change. Milbank Mem Fund Q 1971;49:509-38.
2. Burke W, Psaty BM. Personalized medicine in the era of genomics. JAMA 2007;298:1682-4.
3. Feero WG, Guttmacher AE, Collins FS. The genome gets personal--almost. JAMA 2008;299:1351-2.
4. Brower V. FDA to regulate direct-to-consumer genetic tests. J Natl Cancer Inst 2010;102:1610-2, 7.
5. Hudson KL, Holohan MK, Collins FS. Keeping pace with the times--the Genetic Information Nondiscrimination Act of 2008. N Engl J Med 2008;358:2661-3.
6. Ashley EA, Butte AJ, Wheeler MT, et al. Clinical assessment incorporating a personal genome. Lancet 2010;375:1525-35.
7. Weatherall D, Greenwood G, Chee HL, Wasi P. Chapter 5 -- Science and Technology for Disease Control: Past, Present, and Future. In: Disease Control Priorities in Developing Countries 2nd edition. Washington, D.C.: World Bank; 2006.