Editor's Note: For another perspective on this topic, please see the accompanying Expert Analysis.

"Precision medicine (PM)," formerly known as "personalized medicine," is a series of ideas that stem in part from enthusiasm for the Human Genome Project (HGP).¹ The idea is that through insights from the HGP and follow-up genomic studies, it should be possible to "read" a given individuals genetic "code," and based on variations in that code engage in "P4 medicine;" that is, predictive, preventive, personalized, and participatory.² Additionally, many elements of this paradigm seem remote and/or upstream from the geriatric patient with multiple medical problems which frequently include iatrogenic issues associated with polypharmacy.³

That said, it seems to me that when any new claims of improved diagnostic testing and downstream paradigms emerge, they should be evaluated by asking four simple questions: 1) Is what is being discussed measurable? 2) If measurable, is it meaningful? 3) If meaningful, is it actionable? 4) And, finally, if actionable, is it durable?

Examples from many diseases and medical conditions can be used to address these questions. In what follows I will use a few example from cardiovascular and metabolic diseases to highlight my general skepticism about the transformative power of the PM paradigm. This does not mean that PM will not be useful in rare diseases and in unraveling so-called diagnostic odysseys.⁴ It does mean that the broad based genetic revolution in medicine envisioned by the advocates is likely to be less transformative than originally envisioned.⁵ Additionally, when great claims of potential transformation are made, it seems to me that the bar for success should be set high and include things like evidence for changes in disease specific death rates in the population.⁶

Measurable?

It is clear that gene variants associated with increases in risk for atherosclerosis, arrhythmia, obesity, and diabetes can be measured.

Meaningful?

How meaningful these variants are is much less clear. In general, the relative risks associated with a given variant are small, with values of 1.5 or less, and they explain a tiny fraction of the phenotypic variance. Many are in non-coding regions of the genome and remote and/or seemingly unconnected from pathways directly involved in the relevant pathophysiology.⁷ Many are also conditional and their impact is population specific. For example, the effects of FTO gene variants associated with body mass index (BMI) and obesity are blunted by physical activity.⁸ Likewise, arrhythmia-associated risk variants from small cohorts of patients are present but not associated with disease in unselected cohorts.⁹ It is also possible to make "gene risk scores" for a number of conditions, but for diabetes such scores do little to improve risk prediction compared to standard models.¹⁰ It is unclear if gene scores improve risk prediction over standard models for cardiovascular disease especially when lifestyle related factors are considered.¹¹ Together these examples pose numerous questions about how widely meaningful gene variants and gene scores are in predicting the risk of future disease.

Actionable?

So now the question is how actionable is the frequently ambiguous information discussed above? There are two important points to make here. First, there are limited studies, but in one small study individuals with high gene risk scores for cardiovascular disease who were counseled about their scores were more likely to start on a statin, but information about genetic risk did not motivate major changes in diet or exercise.¹² Second, there are case reports of significant overtreatment of some arrhythmia associated risks including inappropriate "pre-emptive" placement of defibrillators.¹³ These examples highlight that the route to pre-emption and prevention is not straightforward based on gene scores. For "geriatric" drugs like the anti-coagulant warfarin, pharmacogenomic testing to guide initial therapy failed in clinical trials.¹⁴ It is equally unclear how therapy with other commonly used classes of drugs might be genomically tailored in older people, and how the more generic problem of polypharmacy might be guided with high tech approaches in large populations.¹⁵

Durable?

So will personalized interventions based on gene scores "stick" and be durable? The short answer is that the available evidence is that gene scores do not motivate behavior change.¹⁶ Additionally, it is worth making three related observations: first, even in post-MI patients statin compliance at one year is low even when efforts are made to minimize barriers to compliance.¹⁷ If such patients are not maximally motivated, then who is? Second, significant predictive health information is available at essentially no cost using the "bathroom scale score," and this score system has been unable to stem the tide of obesity in high calorie, low physical activity societies. Third, there are many steps associated with the delivery of personalized risk modifying information and subsequent behavior uptake by individuals; this makes such efforts inherently "leaky."¹⁸ These examples suggest there is nothing especially sticky or durable about communicating genetic risk information on an individual basis, and that broad based participation in preventive measures based on gene scores is far from certain.

Lesson From the Past?

As I review the measurable, meaningful, actionable, and durable points above, I am reminded of the enthusiasm for Swan-Ganz catheter placement in ICU patients that was endemic in the 1980s. This "cult" was based on the idea that detailed hemodynamic measures could be made (true), that these measures were meaningful, that they could inform action, and that this package would lead to improved outcomes that would be durable.¹⁹ When tested, this technology had no meaningful impact on outcomes and was associated with significant iatrogenic complications.²⁰ Likewise we can all remember enthusiasm for essentially dilating all stenotic vessels when angioplasty emerged in the 1980s and 90s, and on further review this oculostenotic reflex was associated with over treatment, increased costs, and iatrogenic complications.²¹ Based on these historical precedents and echoes, it seems to me that a "cult" of Precision Medicine might be emerging along with an associated "oculogenomic" reflex that will have a net effect of evoking a new wave of over diagnosis, over treatment, and iatrogenic complications for many common conditions. It has been noted by numerous literary types that history does not repeat itself, but it does perhaps rhyme.

Based on this observation and the observations above, is it fair to warn that the oculogenomic rhyme is just starting?

References

1. Stanford Encyclopedia of Philosophy. The Human Genome Project. https://plato.stanford.edu/entries/human-genome/
2. Hood L, Flores M. A personal view on systems medicine and the emergence of proactive P4 medicine: predictive, preventive, personalized and participatory. N Biotechnol 2012;29:613-24.
3. Cooper JA, Cadogan CA, Patterson SM, et al. Interventions to improve the appropriate use of polypharmacy in older people: a Cochrane systematic review. BMJ Open 2015;5:e009235.
4. Lazaridis KN, Schal KA, Cousin MA, et al. Outcome of whole exome sequencing for diagnostic odyssey cases of an individualized medicine clinic: the Mayo Clinic experience. Mayo Clin Proc 2016;91:297-307.
5. Collins FS. Shattuck lecture--medical and societal consequences of the Human Genome Project. N Engl J Med 1999;34:28-37.
6. Bailar JC, Smith EM. Progress against cancer? N Engl J Med 1986;314:1226-32.
7. Boyle EA, Li YI, Pritchard JK. An expanded view of complex traits: from polygenic to omnigenic. Cell 2017;169:1177-86.
8. Ahmad S, Rukh G, Varga TV, et al. Gene x physical activity interactions in obesity: combined analysis of 111,421 individuals of European ancestry. PLoS Genet 2013;9:e1003607.
9. Van Driest SL, Wells QS, Stallings S, et al. Association of arrhythmia-related genetic variants with phenotypes documented in electronic medical records. JAMA 2016;315:47-57.
10. Hivert MF, Vassy JL, Meigs JB. Susceptibility to type 2 diabetes mellitus--from genes to prevention. Nat Rev Endocrinol 2014;10:198-205.
11. Khera AV, Emdin CA, Drake I, et al. Genetic risk, adherence to a healthy lifestyle, and coronary disease. N Engl J Med 2016;375:2349-58.
12. Kullo IJ, Jouni H, Austin EE, et al. Incorporating a genetic risk score into coronary heart disease risk estimates: effect on low-density lipoprotein cholesterol levels (the MI-GENES Clinical Trial). Circulation 2016;133:1181-8.
13. Ackerman JP, Bartos DC, Kapplinger JD, Tester DJ, Delisle BP, Ackerman MJ. The promise and peril of precision medicine: phenotyping still matters most. Mayo Clin Proc 2016. [Epub ahead of print]
14. Kimmel SE, French B, Kasner SE, et al. A pharmacogenetics versus a clinical algorithm for warfarin dosing. N Engl J Med 2013;369:2283-93.
15. Darwich AS, Ogungbenro K, Vinks AA, et al. Why has model-informed precision dosing not yet become common clinical reality? Lessons from the past and a roadmap for the future. Clin Pharmacol Ther 2017;101:646-56.
16. Hollands GJ, French DP, Griffin SJ, et al. The impact of communicating genetic risks of disease on risk-reducing health behavior: systematic review and meta-analysis. BMJ 2016;352:i1102.
17. Choudhry NK, Avorn J, Glynn RJ, et al. Full coverage for preventive medications after myocardial infarction. N Engl J Med 2011;365:2088-97.
18. Adams J, Mytton O, White M, Monsivais P. Why are some population interventions for diet and obesity more equitable and effective than others? The role of individual agency. PLoS Med 2016;13:e1001990.
19. Robin ED. The cult of the Swan-Ganz catheter. Overuse and abuse of pulmonary flow catheters. Ann Intern Med 1985:103;445-9.
20. Binanay C, Califf RM, Hasselblad V, et al. Evaluation study of congestive heart failure and pulmonary artery catheterization effectiveness: the ESCAPE trial. JAMA 2005;294:1625-33.
21. Soran O, Feldman AM, Cohen HA. Oculostenotic reflex and iatrogenosis fulminans. Circulation 2000;101:E198-9.

Keywords: Geriatrics, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Human Genome Project, Warfarin, Risk, Body Mass Index, Rare Diseases, Pharmaceutical Preparations, Iatrogenic Disease, Obesity, Diabetes Mellitus, Life Style, Exercise, Atherosclerosis, Angioplasty, Polypharmacy, Genetic Code, Cardiovascular Diseases, Arrhythmias, Cardiac, Defibrillators, Hemodynamics, Intensive Care Units, Precision Medicine

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