In Disney’s The Little Mermaid (1989), a vivacious, inquisitive mermaid becomes infatuated with humans. She eagerly learns everything she can about these mysterious creatures. In her scholarly pursuits, she talks extensively with a seabird who satiates her curiosity with extremely inaccurate knowledge, such as using a fork to comb hair. While we might chuckle at the misuse of the fork, we too often apply knowledge that only in hindsight causes chuckling or a quiet reflection of “OMG! What the *@#% were we thinking?”

For instance, consider genomics. Upon the near completion of the Human Genome Project, shell trumpets and fish choruses heralded the genetic revolution that was going transform medicine. In 2001, Francis Collins (current Director of the National Institutes of Health) and Victor McKusick co-wrote, “Genomic medicine holds the ultimate promise of revolutionizing the diagnosis and treatment of many illnesses (Collins & McKusick, 2001).” Since the completion of the project, it seems the floodgates have opened, releasing waves of genetic tests.

Nearly two decades later, the wave of enthusiasm is crashing. In a recent survey, most oncologists acknowledged that genomic testing does not meet expectations and has been overhyped (Genomeweb, 2017). They and other medical professionals also admitted that they did not have the expertise to adequately decipher the large amount of genetic data or to communicate them effectively to patients (Genomeweb, 2017; (Mikat-Stevens, Larson, & Tarini, 2015). Doctors often relied on the test manufacturer’s interpretations (Graber, 2015).

Consequently, knowledge acquired from genetics is not applied correctly. “Poor unfortunate souls” are getting over diagnosed and/or receiving unnecessary treatment based on the results. Recently, a young teenager received an implantable defibrillator based on genetic tests that said he was at risk for a fatal heart condition (Ackerman et al., 2016). A second opinion revealed that he did not have the fatal syndrome and that the implantable defibrillator was not necessary (Ackerman et al., 2016). Another study highlighted that half of women who undergo double mastectomies in the hopes of avoiding breast cancer had mutations, but not the kind known to increase cancer risk (Conger, 2017). Needless to say, a significant percentage of the doctors said that they would treat these women with mutations of unknown significance the same as those with the mutations known to increase risk (Conger, 2017).

It would have been ideal to have a clinical geneticist help guide both doctor and the patient through the murky data. However, there are too few of them for the huge demand placed upon them (Graber, 2015). Even some admit that they are having a hard time keeping up with the literature and new findings (Graber, 2015), which can totally change how one evaluates risk of disease based on genetics (Boyle, Li, & Pritchard, 2017; Chen et al., 2016).

Our understanding of genetics is really a drop in the ocean. As mentioned earlier, new findings are highlighting how little the scientific and medical communities know about a “simple” code. Healthy people are walking about with what might be considered “bad” genetics. Through lifestyle choices or some other undiscovered biological reason, these people are just fine (Chen et al., 2016; Khera et al., 2016). Callouts are being made to change how genetic contributions to diseases are determined (Boyle et al., 2017). Let’s face it, genomes are more complex than anyone could have foreseen.

Have we come to a point where we start quietly reflecting about the use of genomics in medicine? Yes. Already, the National Cancer Institute and the US Food and Drug Administration are considering proteogenomics as the new frontier for clinical diagnostics (Bonislawski, 2017). This approach, which couples genetic information with protein information to improve understanding of biological processes, could yield a more favorable outcome warranting celebratory singing by a Caribbean crab with a thick accent. As to not repeat the past, however, extreme care should be made to ensure that results and their limitations are clearly communicated and recipients know how to properly use the knowledge.


Ackerman, J. P., Bartos, D. C., Kapplinger, J. D., Tester, D. J., Delisle, B. P., & Ackerman, M. J. (2016). The Promise and Peril of Precision Medicine: Phenotyping Still Matters Most. Mayo Clin Proc. doi:10.1016/j.mayocp.2016.08.008

Bonislawski, A. (2017, July 21). FDA and NCI Memorandum Indicates Growing Interest in Proteogenomics as

Clinical Approach. Retrieved from

Boyle, E. A., Li, Y. I., & Pritchard, J. K. (2017). An Expanded View of Complex Traits: From Polygenic to Omnigenic. Cell, 169(7), 1177-1186. doi:10.1016/j.cell.2017.05.038

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

Collins, F. S., & McKusick, V. A. (2001). Implications of the Human Genome Project for medical science. JAMA, 285(5), 540-544.

Conger, K. (2017, April 12). Physicians’ misunderstanding of genetic test results may hamper mastectomy decisions for breast cancer patients. Retrieved from

Genomeweb (2017, May 2). In Survey, Oncologists See Genomic Testing as Important Advance, But Value

‘Below Expectations.’ Retrieved from

Graber, C. (2015, February 5, 2015). The Problem with Precision Medicine. The New Yorker.

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

Mikat-Stevens, N. A., Larson, I. A., & Tarini, B. A. (2015). Primary-care providers’ perceived barriers to integration of genetics services: a systematic review of the literature. Genet Med, 17(3), 169-176. doi:10.1038/gim.2014.101