In the game of poker, players wager that their dealt hand will win the pot of cash. But the person with the best hand doesn’t always prevail: The player holding the worst hand can still seize control of their fate to win the pot.
In a way, our genes act as the dealt cards in the poker game called life. Many companies will provide a glimpse into the hand of cards by sequencing the genetic code. Based on the player’s genes, the companies provide advice – usually for a decent price – that purports to boost the person’s odds in winning.
Recently, the science writer Rebecca Robbins compared her genetic test results from five different companies (Robbins, 2016). The companies promised that the tests (geared towards athletes) would provide valuable insight and advice tailored to her genetic code, which would help maximize her performance.
Instead of clear insightful information, Rebecca received a mixed bag of molecular information (Robbins, 2016). The companies contradicted one another about how a particular genetic variant would affect her blood pressure, endurance, aerobic fitness, tendon health, and post exercise recovery time. The tests could not tell if her genes made her more suited for sports requiring endurance or short bursts of speed. Based on her genetic code, the “tailored” advice she received for optimizing her performance (e.g. stretching before exercising, eating a sensible/healthy diet, staying hydrated, etc.) was basic common sense that could benefit ANYONE in the general populace.
Aside from looking for a competitive edge in sports, many genetic tests will look for mutations that may determine the actionable course of treatment for a patient. However, the presence of the variant will not always change the course of standard medical treatment. Take the case of thrombophilia (a condition where a person can easily develop life threatening blood clots) as an example. Every year, Medicare spends $300 to $670 million dollars on genetic tests that determine if patients are likely to develop thrombophilia (Ross, 2016). Yet even if the tests came back positive, the regimen for treating a blood clot would not change (Ross, 2016). Why are patients and doctors willing to undergo the extra testing and spend the extra money?
Maybe it has something to with DNA sequencing becoming cheaper and the turnaround time for results becoming quicker? Maybe it has something to do with success stories about patients receiving treatment based on genetic information? Numerous cases exist in the literature about a patient (let’s say a cancer patient) getting a quick swab of the cheek, blood draw, or biopsy of the tumor. The results from the genetic testing reveal that a harbored mutation would make the patient more responsive to treatment X versus treatment Y. After undergoing the treatment suggested by the test results, the patient goes into remission. While this sounds like a cutting-edge breakthrough in modern medicine applicable to every ailment, it is a rare scenario in the grand scheme of things. It’s a good reminder that we do not necessarily need more information. We just need the right information.
Despite the genetic code appearing concrete, the dictated outcomes are malleable and heavily influenced by external factors, such as lifestyle choices, environmental factors, etc. In a recent study published in the New England Journal of Medicine, researchers observed that people with genetic predisposition for heart problems who lived a healthy lifestyle fared better than those with great genes who made poor lifestyle choices (Khera et al., 2016). In another study, people were identified harboring mutations guaranteed to cause serious ailments. Interestingly, these individuals were physically fine and showed no signs of the genetically caused ailment (Chen et al., 2016).
It is evident from these cases that getting a peek at our genetic playing cards is not going to give us the absolute certainty of winning. Something more than genetics is responsible for what is happening. One possible explanation could be proteins becoming activated or inhibited as a response to external cues, which might affect their measureable concentration within the body. Using SomaLogic’s SOMAscan technology, the changes in protein levels can be monitored as the body responds to external cues, such as diet, exercise, etc. By monitoring the protein levels, it is possible to gauge a patient’s chances of a cardiovascular event (Ganz et al., 2016), adjust drug dosage for maximum benefit (Park et al., 2013) or determine if a patient may have an adverse reaction to a drug (manuscript in preparation). This kind of information can be used more effectively by patients and their doctors to seize control and make more informed decisions towards a win in the poker game called life.
Chen, R., Shi, L., Hakenberg, J., Naughton, B., Sklar, P., Zhang, J., . . . Friend, S. H. (2016). Analysis of 589,306 genomes identifies individuals resilient to severe Mendelian childhood diseases. Nat Biotechnol, 34(5), 531-538. doi:10.1038/nbt.3514
Ganz, P., Heidecker, B., Hveem, K., Jonasson, C., Kato, S., Segal, M. R., . . . Williams, S. A. (2016). Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients With Stable Coronary Heart Disease. JAMA, 315(23), 2532-2541. doi:10.1001/jama.2016.5951
Khera, A. V., Emdin, C. A., Drake, I., Natarajan, P., Bick, A. G., Cook, N. R., . . . Kathiresan, S. (2016). Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease. N Engl J Med, 375(24), 2349-2358. doi:10.1056/NEJMoa1605086
Park, N. J., Wang, X., Diaz, A., Goos-Root, D. M., Bock, C., Vaught, J. D., . . . Strom, C. M. (2013). Measurement of cetuximab and panitumumab-unbound serum EGFR extracellular domain using an assay based on slow off-rate modified aptamer (SOMAmer) reagents. PLoS One, 8(8), e71703. doi:10.1371/journal.pone.0071703
Robbins, R. (2016). Genetic tests promised to help me achieve peak fitness. What I got was a fiasco. Retrieved from https://www.statnews.com/2016/11/03/genetic-testing-fitness-nutrition/
Ross, C. (2016). Genetic test costs taxpayers $500 million a year, with little to show for it. Retrieved from https://www.statnews.com/2016/11/02/genetic-test-medical-costs/