Believe it or not, genomic signs do exist, but they lack the nifty monikers of animals, elements, constellations, etc., that we associate with the Zodiac. Unlike astrological signs, however, each genomic sign is largely unique to its individual (except for identical twins that share basically the same genome). Each sign, (written in two ways both forward and backward) contains about three billion letters, which does make pronunciation difficult.
How would you use a genomic sign? Genomes, like horoscopes, suggest one’s risk of some outcome in the course of life. It is true that a handful of people have benefitted enormously from knowing their genome. But only a handful. If you think about how external factors affect our biology, the majority of genetic research applies only to certain demographics (Begley, 2019), our limited understanding of our biology, and how we actually could be made up of multiple genomes), gauging the best health or medical decision from a DNA sequence could be just as accurate as the guidance offered by the stars.
How seriously do people take their genetic horoscopes? A recent survey of healthy people found that although many participants shared the risk information from genomic test results with their healthcare provider, 60% were skeptical of its accuracy (Zoltick et al., 2019). In the end, less than 10% of participants actually made lifestyle adjustments based on the information from the genetic tests.
What kind of information would really make people sit up, take notice and change their ways to try to prevent a bad outcome? It appears that genomics does not provide such information now and, may not even in the future. Would insights that reflected a real-time assessment of a person’s physiology – i.e., their actual health status and where they are headed – be sufficient to drive change? We are soon going to find out. It will be interesting to see what the future has in store.
Begley, S. (2019, March 11) Buffalo gave us spicy wings and the ‘book of life.’ Here’s why that’s undermining personalized medicine. STAT. Retrieved on March 12, 2019 from https://www.statnews.com/2019/03/11/human-reference-genome-shortcomings/.
Zoltick, E. S., Linderman, M. D., McGinniss, M. A., Ramos, E., Ball, M. P., Church, G. M., . . . PeopleSeq, C. (2019). Predispositional genome sequencing in healthy adults: design, participant characteristics, and early outcomes of the PeopleSeq Consortium. Genome Med, 11(1), 10. doi:10.1186/s13073-019-0619-9
Male birds-of-paradise use everything imaginable to charm their intended audience – a potential mate. Iridescent plumage bathed in sunlight, hypnotic dance moves and altering their surroundings all help them stand out amongst a dark overly crowded jungle. Could you imagine their success rates if they could master electricity and neon lighting?
Humans, too, do what they can to capture and charm their intended audience. Consider mass media and social media in an overly crowded media jungle. Captivating headlines, outrageous statements, evocative imagery, claims made by celebrities swirl and twirl around us begging us to read further, to “like” it, to share it, to click on an associated ad, and – the end game – to buy something.
No area of human endeavor is immune, not even science. As funding started getting tougher to attract and publishing in high-impact journals got more incentivized, writers changed their writing style to make their research more attractive to readers and stand out from amongst the crowd. The use of positive wording (e.g., “groundbreaking,” “unprecedented,” “innovative,” “novel,” “encouraging,” etc.) has increased over 880% in the last few decades (Vinkers, Tijdink, & Otte, 2015; Belluz, Plumer, &Resnick, 2016). And this has happened in parallel with the rise of genomics.
Timothy Caulfield recently documented this genomics-of-paradise dance in exquisite detail (Caulfield, 2018). Before the actual start of the Human Genome Project, the idea that it would be a “revolution” in medicine started permeating into the minds of people. The growing plumage of revolutionary promise helped secure the huge influx of cash needed to support such an endeavor. But the necessity to express enthusiasm and passion to help excite others about research can go too far. And, as Caulfield notes, many of the early genomics proponents crossed that line.
First, promises were made around the potential and imminence of successful gene therapy to fix genomic “problems.” When that promise remained just a promise after many years, the promises moved more to the development of actionable health insights from the genetic code, even to the point of “personalized” medicine. For a few individuals with highly penetrant, single allele diseases this promise was at least partially kept. But the general public has not seen the return on this huge investment in their lives yet.
Why do these promises remain elusive for the vast majority of people? The answer is quite simple. The more we learn about genomics, the more mind-bogglingly complex it is. We are finding that our understanding of genomics is but a drop in the ocean. For any given common trait, we are learning that it results from a jungle of genes instead of a single gene tree. This kind of complexity and uncertainty does not lend itself to the attractive sound bite or visual spectacle.
So, what is wrong with a little hype? Well, the sad truth is that even if a statement is completely ludicrous, people will start believing it if they hear it enough times (Caulfield, 2018) or hear celebrities saying it, which may even result in serious medical harm. Also, investors could lose their investments: A recent study highlighted just how many gullible investors throw their money at healthcare start-ups that have a paltry publication record and limited transparency about their technology (Cristea, Cahan, & Ioannidis, 2019).
It is true that hype will always be with us. People will always flock to it, even if its siren-like promises never come to fruition. But we cannot let it win. We have to look beyond hype-notic dance and scrutinize carefully what is being claimed in the context of real information and data. If a technology or piece of information is really going to revolutionize our health, its creators ought to make it a priority to showcase the reasons it will do so (e.g., the published peer-reviewed literature) and not just hide the issues behind the showy promise of misleading hype.
Belluz, J., Plumer, B., and Resnick, B. (2016, September 7) The 7 biggest problems facing science, according to 270 scientists. Vox. Retrieved on March 1, 2019 from https://www.vox.com/2016/7/14/12016710/science-challeges-research-funding-peer-review-process.
Caulfield, T. (2018). Spinning the Genome: Why Science Hype Matters. Perspect Biol Med, 61(4), 560-571. doi:10.1353/pbm.2018.0065
Cristea, I. A., Cahan, E. M., & Ioannidis, J. P. A. (2019). Stealth research: Lack of peer-reviewed evidence from healthcare unicorns. Eur J Clin Invest, e13072. doi:10.1111/eci.13072
Vinkers, C. H., Tijdink, J. K., & Otte, W. M. (2015). Use of positive and negative words in scientific PubMed abstracts between 1974 and 2014: retrospective analysis. BMJ, 351, h6467. doi:10.1136/bmj.h6467
If you have seen a drug commercial with a long list of potential ominous side effects, you would probably answer “Yes!” In fact, many of the more recent lucrative drugs only successfully helped about 4 to 25% of people treated (Schork, 2015). With such a low chance of the drug actually working, who wants to take on such a high stakes gamble? Do you feel lucky?
Precision medicine heralds the delivery of “the right treatment to the right patient at the right time.” Intuitively, the concept means that patients benefit by being spared from potentially harmful side effects of treatments that will not work for them and healthcare costs could be reduced by not wasting finite funds on treatments that will not benefit the patient.
Despite the promise of precision medicine, opinion pieces have been popping up asking whether or not the world is being misled by its proponents. For example, the author of a recent editorial discussed how some statistical analysis methods may misconstrue the number of patients who respond to treatments (Senn, 2018). The offenders the author identified included, but not limited to the following: arbitrary measurements; subjective cut-off lines for determining a patient who responds from one who does not respond to treatment; patient’s fluctuating physiology; and response rates. Another essay noted how treatments assigned based on genetic findings rarely actually work, but those success stories get overgeneralized and overhyped, which may mislead the public into thinking that the success rates of precision medicine are much higher than they are (Szabo, 2018).
Most of the recent editorial writers are not all doom-and-gloom for precision medicine: They do suggest steps that can be taken. Stephen Senn suggested avoiding arbitrary terms like “responder”, sticking with actual measurements (i.e., not using one’s own judgment to gauge a value), and using N-of-1 clinical trials (clinical trials done with one individual) – although individual clinical trials have their own issues that need to be addressed for them to be successful (Lillie et al., 2011).
But maybe we should take a step back and ask whether we are collecting the “right data” to deliver the “right treatments.” For example, measuring thousands of proteins simultaneously and repeatedly over time could provide more meaningful information about a person’s health status and its changes than other information, such as genomics. With its ability to provide a synopsis of a person’s changing physiology in real-time, the SOMAscan® platform has shown potential in providing a more accurate assessment of patients compared to the “gold standards,” which could have prevented bad outcomes in a clinical trial of a promising new drug (Williams et al., 2018). In other cases, the SOMAscan technology shows potential in outperforming the “gold standards” in offering a more accurate diagnosis, which can lead to being treated with the right treatment sooner (Barbour et al., 2017).
Using the SOMAscan platform in the treatment of patients could alleviate concerns being raised about precision medicine in additional ways. By using measurements that reflect what is happening to the individual at the molecular level, the researchers and clinicians would have the hard-core numbers and insights necessary to determine if patients are responding to medications or other treatments. This could allow for better assignment of responder vs non-responder. The molecular insight would also help visualize fluctuations in physiology, which could be seminal for understanding treatment performance and response rates.
We are just on the cusp of a new age for the practice of medicine. But we have to focus and not get swept up in the hype. There is no doubt that within the next few years we will have a way to determine the health status and the most precise treatment for the individual (right time health).
Barbour, C., Kosa, P., Komori, M., Tanigawa, M., Masvekar, R., Wu, T., . . . Bielekova, B. (2017). Molecular-based diagnosis of multiple sclerosis and its progressive stage. Ann Neurol, 82(5), 795-812. doi:10.1002/ana.25083
Lillie, E. O., Patay, B., Diamant, J., Issell, B., Topol, E. J., & Schork, N. J. (2011). The n-of-1 clinical trial: the ultimate strategy for individualizing medicine? Per Med, 8(2), 161-173. doi:10.2217/pme.11.7
Schork, N. J. (2015). Personalized medicine: Time for one-person trials. Nature, 520(7549), 609-611. doi:10.1038/520609a
Senn, S. (2018). Statistical pitfalls of personalized medicine. Nature, 563(7733), 619-621. doi:10.1038/d41586-018-07535-2
Szabo, L. (2018, September 11). Are We Being Misled About Precision Medicine? The New York Times. Retrieved on December 5, 2018 from https://www.nytimes.com/2018/09/11/opinion/cancer-genetic-testing-precision-medicine.html
Williams, S. A., Murthy, A. C., DeLisle, R. K., Hyde, C., Malarstig, A., Ostroff, R., . . . Ganz, P. (2018). Improving Assessment of Drug Safety Through Proteomics: Early Detection and Mechanistic Characterization of the Unforeseen Harmful Effects of Torcetrapib. Circulation, 137(10), 999-1010. doi:10.1161/CIRCULATIONAHA.117.028213
Congratulations! If you have decided to read this piece, you are curious about what proteomics is, and maybe even why it should matter to you. In fact, you are in good company as evidenced by a video-taped survey, where randomly selected individuals suggest definitions that amusingly demonstrate that they really have no idea what “proteomics” means.
Although the responses to the question are often funny, they are also a bit sad: Proteomics is on the edge of changing the lives of so many, yet is still so little understood. So, until Hollywood decides to do a proteomics movie with dinosaurs or Minions, the task falls onto the shoulders of those who are working to bring proteomics to all people. I’ll try to make a small contribution here.
What is proteomics?
Proteomics is not related to economics or a type of comics. It is the study of the proteome.
What is the proteome?
The proteome sounds like a nifty name for a stadium or mystical object, but there is nothing sporty or mystical to it. The proteome is simply a term that refers to all the proteins present in your body (or a specific part of your body) at any given moment in time. Similar to how the word “genome” refers to all your DNA and genes.
What is a protein?
Yes, “protein” can elicit images of healthy shakes or slabs of meat (or tofurkey), but protein-as-food is not the complete picture. Protein molecules are made from the instructions (genes) encoded in our DNA. We have an estimated 20,000 genes, which means that we have about 20,000 different proteins. Proteins, which can take on any shape imaginable including a barrel, are certainly the building blocks of life (including meat and non-meat substitutes). But in addition to building our bodies, they also carry out the day-to-day functions of and communications between different parts of the body. Just like cars, proteins can be modified with different features after they are built, such as being adorned with sugars, fats, etc. These modifications not only increase the diversity of our proteins, but may also modify their roles in our bodies. Proteins even respond to changes in environmental effects (e.g., diet, fitness, climate, infection, etc.) and help the body adjust accordingly.
How can proteomics benefit me?
As proteins carry out our day-to-day functions, their levels may fluctuate, which can be indicative of what the body is currently doing or how it is responding to something such as food or stress or medication. Tapping into this rich source of information could open the doors for improving your life in multiple ways, the most important of which may be to help you keep yourself healthy for as long as possible.
At SomaLogic, we realized the potential of tapping into this rich stream of information to improve lives. From a small sample of urine or blood, we gauge the levels of the proteins using our SOMAmer® reagents, which bind to specific proteins. With millions of measurements and clinical data, we harness the power of bioinformatics and machine learning to extract meaningful insights from the data treasure trove.
Over 200 scientific publications testify to our proteomic technology’s promise. It has been used to better understand the underpinnings of a wide range of diseases, including cancer, arthritis, Duchenne muscular dystrophy, Down syndrome, cardiovascular disease, diabetes, etc. The revelations could lead to new drug treatments or new ways of monitoring the effectiveness of treatments. Also, the technology has improved the understanding of how the body ages, responds to lifestyle changes, and more. We envision that one day, a person would be able to have their proteomes routinely assessed by the SOMAscan® platform and the resulting data translated into actionable insights that enable them to live a healthy life well into old age. That is something I think that everyone should care about.
How would the late Surrealist artist, Salvador Dalí, view his genome? I suspect that the artist, who had a flair for painting things in midair as cats and water seemed to hover nearby, would have been fascinated by not only the concept of genomics, but the widespread human view of it.
Consider one of his famous works, The Persistence of Memory (1931). All the iconography oozing from this work can’t be discussed in a few hundred words. So, let’s just home in on the most memorable elements of the painting – the clocks. Dalí once called those clocks the “camembert of time” (camembert is a delectable soft cheese that could theoretically be good as donut filling).
The iconic melting clocks communicate that our perception of time is not solid or concrete; it is fluid and ever changing. However, to many people time will always remain solid because that is how they uncritically perceive it. If I were to bet my camembert-filled donut, I would say Dalí would view his genome as he did time. But many people perceive it as concrete and static: One gene equals one inheritable trait; mutation X causes disease Y. The early work of Gregor Mendel and others may have unwittingly set the stage for this kind of genetic determinism. However, scientists have demonstrated that the genome is vastly more complex, engrained with redundant elements, buffeted by environmental changes, and unable to fully explain our physiological identity at any given moment or across time (Weiss, 2018).
Your genome simply does not paint the complete portrait of you or your health. First, it is only predictive, and only to some relative degree. People harbor mutations that “should” confer horrible outcomes that never materialize due to genomic mysteries or lifestyle choices. It would seem like the mutation is just hitching a ride in the genome. Second, we could all have many different genomes existing throughout the body, not just the one reported in the test results. Third, the DNA could have picked up phantom mutations during sequencing that were not present in the actual sample. Hitchhiking mutations, multi-genomes and phantom mutations – what great subject matter for a Surrealist artist!
Test results from a set of identical twins serve as yet another example of the fluidity of our genetic understanding of ourselves (Argo and Denne, 2019). Although a team of researchers from Yale University deemed the genomes of twin sisters to be identical (99.6% based on raw data), the twins received very different readouts/interpretations from a genetic testing company, perplexing the twins AND the researchers. Different reports from four other genetic testing companies also failed to agree, even for the same individual. Perplexing indeed!
If Salvador Dalí viewed our perception of genetics/genomics the same way as time, how would he represent this in his artwork? Would he have painted melting DNA that seemed to keep dividing to resemble a fractal or genomic reports that morph into different objects? Would there be phantom DNA? Who knows, we could spend years discussing the possibilities. What is certain is that trying to grasp a static understanding of genetics/genomics to define our health will not lead to the precision medicine promise of the right medical treatment at the right time. We need to listen to the voices that are emerging to break the engrained perception that our identity or future resides in our DNA.
Argo, C. and Denne, L. (2019, January 18). Twins get some ‘mystifying’ results when they put 5 DNA ancestry kits to the test. CBC News. Retrieved on January 22, 2019 from https://www.cbc.ca/news/technology/dna-ancestry-kits-twins-marketplace-1.4980976.
Weiss, K. M. (2018). Genetic Pointillism versus Physiological Form. Perspect Biol Med, 61(4), 503-516. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/30613033. doi:10.1353/pbm.2018.0060
Oh dear…what is that? Seeing (and feeling) a rash-riddled arm at 2 o’clock in the morning can be alarming. And turning to Dr. Smartphone Google adds even greater urgency to the fear: A rash can reflect a large number of conditions, from very serious to very mild. Even legit doctors have a tough time deciding which is which.
For example, it turns out that psoriasis, atopic dermatitis and contact dermatitis all present similar symptoms, which can make getting an accurate diagnosis – and treatment decision – difficult at best (Wang et al., 2017). A team of researchers from MedImmune, Mount Sinai Medical Center and Rockefeller University decided to try and fix that problem by testing the feasibility of developing a non-invasive test to differentiate between the different skin conditions and get the right individualized treatment sooner (Wang et al., 2017). Though previous genomic and transcriptomic analyses of skin biopsies have been informative, the team reasoned that proteomics may provide a better “real-time view” into the skin issues.
To put their hypothesis to the test, the researchers used SomaLogic® technology to measure the levels of proteins in serum samples from patients that had psoriasis, atopic dermatitis or contact dermatitis. Compared to healthy individuals, the researchers found 66 proteins that changed significantly in one of the three disease states. In other words, each type of rash could be diagnosed based on different protein changes. Interestingly, the researchers did find similar protein changes common to all three conditions, suggesting some shared biology.
As exciting as this news is that there is a possible basis in protein changes for making a definitive test for determining to determine the identity of the rash – and treat it effectively – is just beyond on the horizon, the researchers caution that the work is still very preliminary. But it does suggest a future where the rash decisions of Dr. Smartphone Google are less likely to make things scarier than they are.
Wang, J., Suarez-Farinas, M., Estrada, Y., Parker, M. L., Greenlees, L., Stephens, G., . . . Howell, M. D. (2017). Identification of unique proteomic signatures in allergic and non-allergic skin disease. Clin Exp Allergy, 47(11), 1456-1467. doi:10.1111/cea.12979