So many headlines announce the latest trends and decree what is no longer in style. It is reassuring to know that someone will let me know that my favorite things, such as a beloved garment or the hairstyle that I finally mastered, are no longer stylish.
Even in science, we have headlines announcing the latest and greatest technology. Recently, Nature put out an article about what technologies to watch in 2018 (Powell, 2018). One particularly trendy technology was the use of mass spectrometry and cryo-electron microscopy to connect changes in genotype with the corresponding physical manifestations (a.k.a. phenotypes). The article asserted that using mass spectrometry to measure proteins (the smallest manifestations of our phenotypes) is the key to better understanding the problems caused by disease. Fortunately, we not need to rely solely on difficult mass spectrometry technology to measure the proteins circulating through us.
Case in point: An international team recently published results from using the SOMAscan platform to link genotype to phenotype (Sun et al., 2018). This unprecedented achievement easily allowed the researchers to investigate the links between genetic variation and protein output. Their work suggested that if a direct genetic control exists for deciding protein concentration, it is likely due to regulation of messenger RNA. However, the authors could not entirely rule out other biological processes that could contribute to the changes in protein levels. They also found that if a genetic variation coincided with many protein abundance changes, it could be indicative of a biological pathway that linked them all.
Overall, connecting genotypes to phenotypes is a wonderful way to begin to better understand our biological Rube Goldberg machines and may very well lead to medical breakthroughs that help some individuals live a better life. But given the mind-blowing complexity of the genetic code, how transferable will this approach be to improving the health of the masses? Those who want to link genotype to phenotype to disease may not have chosen the most direct or simplest route to the summit of Mt. Improved Diagnostics.
The simplest route might just be to focus on proteins and avoid the complexity introduced by genomics. Do we need to wait till some headline says that proteomics is super trendy before it becomes the “omic” of choice? I think not. It is reassuring to know that others are not waiting to be told either, and are embarking on the use of proteomics in bettering the understanding of disease and improving medical treatment or diagnosis.
Powell, K. (2018). Technology to watch in 2018. Nature, 553(7689), 531-534. doi:10.1038/d41586-018-01021-5
Sun, B. B., Maranville, J. C., Peters, J. E., Stacey, D., Staley, J. R., Blackshaw, J., . . . Butterworth, A. S. (2018). Genomic atlas of the human plasma proteome. Nature, 558(7708), 73-79. doi:10.1038/s41586-018-0175-2
Circadian clock…biological clock…alarm clock… Face it. We are subjects to the clock whether mechanical or the one existing within us. This could not be truer than when it comes to how well we respond to medication.
The topic of time and when to take medication has appeared even in reading material geared to the interests of the general population. In Reader’s Digest, a recent article talks about “chronotherapy” (Simon, 2018), or taking medications based on a person’s circadian rhythm to maximize the effectiveness of the drugs and minimize the side effects. Suggestions are even made for the best time of day to take some popular forms of medications, such as allergy medications.
Chronotherapy is a bit more complicated than the Reader’s Digest article suggests. The fact is that many factors can affect a person’s circadian rhythm. Not too surprisingly, our choice of bedtime can affect our internal clock (Potter et al., 2016). Also, not surprisingly, what we shove into our mouths (in the form of food) can certainly alter our circadian rhythm (Oosterman, Kalsbeek, la Fleur, & Belsham, 2015). Our gender influences our internal clock (Santhi et al., 2016). Even the ravages of time (aging) adjust our clocks (Hood & Amir, 2017).
With so many factors affecting how our circadian rhythm functions, it seems like a Herculean task to make chronotherapy a reality. But it is necessary. As the oncologist Francis Lévi stated, “We have found that the timing is sometimes more important than the dose (Peeples, 2018).” A recent Nature article details just how important and invaluable chronotherapy can be to positive outcomes in treating diseases, particularly in performing cardiac surgery or treating cancer (Peeples, 2018).
But if chronotherapy demonstrably improves patient outcomes, why do only a small fraction of clinical trials incorporate it (Selfridge et al., 2016)? The Nature article suggests a few reasons why chronotherapy is not used more often; however, cost and complexity could also be reasons why. But with advances in technology, these reasons may disappear.
One such emerging technology is the SOMAscan platform. In a pilot study involving six individuals, researchers investigated using the SOMAscan platform (and other techniques) to watch the circadian rhythm of the individuals (Skarke et al., 2017). They found a small fraction of proteins that associated with inflammation and cancer changed during the day. It is tempting to think that if a larger number of people had been used in this study a larger fraction of proteins would have shown a temporal relationship. Maybe this will motivate a larger study?
Now that a technology exists which can show us how our proteins fluctuate during the day, we have a new opportunity at hand: the further realization of the promise of precision medicine by the wider application of chronotherapy across many diseases and conditions. It will be exciting to see how adoption of this technology could make chronotherapy more realistic even though so many things affect our clocks. Future therapies may have to include lifestyle adjustments to reduce day-to-day variability in our circadian rhythm. Time will tell.
Hood, S., & Amir, S. (2017). The aging clock: circadian rhythms and later life. J Clin Invest, 127(2), 437-446. doi:10.1172/JCI90328
Oosterman, J. E., Kalsbeek, A., la Fleur, S. E., & Belsham, D. D. (2015). Impact of nutrients on circadian rhythmicity. Am J Physiol Regul Integr Comp Physiol, 308(5), R337-350. doi:10.1152/ajpregu.00322.2014
Peeples, L. (2018). Medicine’s secret ingredient – it’s in the timing. Nature, 556(7701), 290-292. doi:10.1038/d41586-018-04600-8
Potter, G. D., Skene, D. J., Arendt, J., Cade, J. E., Grant, P. J., & Hardie, L. J. (2016). Circadian Rhythm and Sleep Disruption: Causes, Metabolic Consequences, and Countermeasures. Endocr Rev, 37(6), 584-608. doi:10.1210/er.2016-1083
Santhi, N., Lazar, A. S., McCabe, P. J., Lo, J. C., Groeger, J. A., & Dijk, D. J. (2016). Sex differences in the circadian regulation of sleep and waking cognition in humans. Proc Natl Acad Sci U S A, 113(19), E2730-2739. doi:10.1073/pnas.1521637113
Selfridge, J. M., Gotoh, T., Schiffhauer, S., Liu, J., Stauffer, P. E., Li, A., . . . Finkielstein, C. V. (2016). Chronotherapy: Intuitive, Sound, Founded…But Not Broadly Applied. Drugs, 76(16), 1507-1521. doi:10.1007/s40265-016-0646-4
Simon, N. Actually. There’s a Right Time to Take “Once a Day” Meds. Readers Digest. Retrieved on May 3, 2018 at https://www.rd.com/health/conditions/medication-timing/.
Skarke, C., Lahens, N. F., Rhoades, S. D., Campbell, A., Bittinger, K., Bailey, A., . . . FitzGerald, G. (2017). A Pilot Characterization of the Human Chronobiome. Sci Rep, 7(1), 17141. doi:10.1038/s41598-017-17362-6
We all experience life in three-dimensional space. Right now, apparently solid computer keyboard keys “click” as they recoil from the press of my fingers, while a chair beneath my rear resists the gravitational pull of our planet to keep me at the right height to reach the keyboard and eye the screen. The keyboard, the screen and my body are defined in relation to each other by height, weight and depth. Indeed, everything we do at the organismal level – and everything going on in us at the submicroscopic level of atoms and molecules – can be imagined as spacial interactions in three dimensions.
But position in space incompletely describes life. We also exist in time, a phantasmagoric fourth dimension that we limited human creatures experience as part hope (the future), part memories (the past) and even part loss (the present, where the future blinks into life and is relegated to the past in the same blink). Physicists argue endlessly over whether the fourth dimension of existence is best described as a kind of flow, a spotlight, or even a “block universe” (where all past and present and future are always existing). Fascinating, brain-beating arguments that ultimately raise as many questions as they answer. Yet the basic idea of four-dimensionality is compelling.
As a central attribute of life, health is also a matter of space and time. At any given moment of time (the present) our state of health is determined by a combination of microscopic and macroscopic interactions. From the temperature in the room to the proteins quivering in each neural synapse, there is an unimaginably large set of interactions of “stuff” defining the present moment. And which will change in the “next” moment, the next, and so forth, until the end of our life. Each of us experiences the summation of these changes as our uniquely personal health history in three dimensions over the fourth dimension of time.
The reality of a fourth dimension is underlined by the third pillar of precision medicine, i.e., finding the right treatment for the right patient AT THE RIGHT TIME. However, most precision medicine today focuses on understanding the genome, the blueprint — but not an actual building block — of the human body. Proponents for a genomic approach to precision medicine argue that if we could only understand each two-dimensional representation of genetic variation in a person’s genome, we could foretell future illness accurately and would be ready to “fix” it when it became the present.
This assertion is akin to saying that one can look at a blueprint of a building constructed, say, 40 years ago and be able to pick out today where the pipes are leaking, the walls are sagging, and the foundation crumbling. A sharp-eyed builder who knew the materials used to build the blueprint’s depiction might be able to raise alarm about the potential future failure of various elements, but it would simply be impossible to be more precise without a different kind of insight.
So why not examine the building blocks of health directly? Specifically, why not measure the molecules of four-dimensional life? I am referring to proteins, which change regularly in response to environment (including drug treatment) and genetic alterations. Proteins interact with each other in time and space to build – and destroy – bodily life. And proteins reveal not only your immediate health status but where you are headed in the near future, far more accurately and precisely than genes.
Did you know our blood is a big-time gossip? A little bit of it can reveal so much about you. For instance, it can tell us your gender, if you are overweight, and your age (Curran et al., 2017). For a mother, blood can also divulge information about her children because their genomic material still lingers on in her long after birth (It also can be used to identify the children’s father!) (Boddy, Fortunato, Wilson Sayres, & Aktipis, 2015; Stevens, 2016).
In addition to sharing information that is perfect fodder for reality shows and soap operas, blood also chatters away about our health. Compared to other medical testing that require biopsies, it is pretty easy to listen to the chatter. Docs already keenly listen and subject patients to many blood tests to get the inside scoop. The best part of using blood to glean medical insights is that it is minimally invasive!
Lately, news organizations have begun churning out many stories about liquid biopsies (looking at biomarkers in blood to gauge a health status) that captivate the public’s attention. The allure is understandable: A simple minimally invasive test that can give the needed insights into a person’s risk of potentially terminal diseases, such as cancer, that can be cured if caught early.
One such experimental test that had people wondering when it will make it to market came out of a recent collaboration (see comments section of Mone, 2018). This test was developed to monitor circulating tumor DNA (ctDNA) and protein biomarkers for about eight cancers of the ovaries, liver, stomach, pancreas, esophagus, colon, lung, or breast (Cohen et al., 2018). The authors reported that their test had good statistics for sensitivity (finding cancer) and specificity (only 1% false positives). What is remarkable is that the test could even pinpoint the location of the cancer, thanks to information from the protein biomarkers. Even though the test sounds like it is ready for primetime, the authors emphasized that there are still shortcomings to be solved and validation work to be done.
This caveat about cancer screening using ctDNAs is shared by other groups too. Recently, the American Society of Clinical Oncology and College of American Pathologists penned a review about assays using ctDNA (Merker et al., 2018). In the review, the reviewers noted the potential of using ctDNAs, but clinical validity and utility still need to be decided. [What is needed is a testbed, which involves looking at the practicality of the tests in a clinical setting!] The reviewers go on to mention that ctDNA tests have inherent problems, such as patients having different levels of ctDNA, tests might not be interchangeable (different protocols yield different results), and more.
As more news agencies publish about the latest means of listening to our blood’s juicy gossip, we must be careful to not get caught up in the hype. Yes, liquid biopsies show great promise, but a lot more work remains to make sure the messages being communicated are being interpreted correctly. Focusing on the wrong “words” could lead to a miscommunication or misinterpretation of what our blood is trying to tell us. This could result in missed diagnoses or people undergoing unnecessary and invasive procedures/treatments.
Boddy, A. M., Fortunato, A., Wilson Sayres, M., & Aktipis, A. (2015). Fetal microchimerism and maternal health: a review and evolutionary analysis of cooperation and conflict beyond the womb. Bioessays, 37(10), 1106-1118. doi:10.1002/bies.201500059
Cohen, J. D., Li, L., Wang, Y., Thoburn, C., Afsari, B., Danilova, L., . . . Papadopoulos, N. (2018). Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science, 359(6378), 926-930. doi:10.1126/science.aar3247
Curran, A. M., Fogarty Draper, C., Scott-Boyer, M. P., Valsesia, A., Roche, H. M., Ryan, M. F., . . . Kaput, J. (2017). Sexual Dimorphism, Age, and Fat Mass Are Key Phenotypic Drivers of Proteomic Signatures. J Proteome Res, 16(11), 4122-4133. doi:10.1021/acs.jproteome.7b00501
Merker, J. D., Oxnard, G. R., Compton, C., Diehn, M., Hurley, P., Lazar, A. J., . . . Turner, N. C. (2018). Circulating Tumor DNA Analysis in Patients With Cancer: American Society of Clinical Oncology and College of American Pathologists Joint Review. J Clin Oncol, JCO2017768671. doi:10.1200/JCO.2017.76.8671
Mone, A. (2018, January 19) Johns Hopkins researchers develop single blood test that screens for eight common cancers. Hub. (Retrieved on March 21, 2018 from https://hub.jhu.edu/2018/01/19/cancer-blood-test-johns-hopkins/).
Stevens, A. M. (2016). Maternal microchimerism in health and disease. Best Pract Res Clin Obstet Gynaecol, 31, 121-130. doi:10.1016/j.bpobgyn.2015.08.005
Face it. Despite our best intentions, bad stuff happens on occasion, as seen in the medical field. In hopes of a positive outcome, a patient undergoes treatment, but has a negative reaction. In the pursuit of “first do no harm,” more safeguards are put into place to minimize the chances of a negative outcome. As technology improves, however, we may soon have an equivalent to the bubble wrap suit, particularly in the development of new medical treatments.
The Food and Drug Administration (FDA) – the federal gatekeeper for new drugs – has established numerous criteria that drug candidates must meet before being sold in the U.S. marketplace (FDA, 2017a). After testing the drug candidate in animals, the clinical evaluation begins. The first phase involves looking at how the drug candidate is processed in a few healthy people and figuring out common side effects. If things look good and the drug is considered to be not too toxic, the investigation focuses on both the safety and the effectiveness of the drug candidate for treating the disease/condition in a large number of people. If all goes well with the testing and review, the FDA decides whether to approve the drug. Further monitoring of drug safety still happens after the approval, but success depends on medical professionals and insurance companies (FDA, 2017b; FDA, 2018).
Who foots the bill for all the testing done during the clinical phases? Well, usually the company or other parties who wishes to have the drug approved. You can imagine that this process is not cheap. It is the worst nightmare imaginable when something goes horribly wrong, particularly in later stages. Despite all the safety precautions taken, this nightmare becomes reality more often than anyone would like to see.
The unfathomable sadly materialized in the clinical testing of Pfizer’s drug candidate torcetrapib, designed to treat high cholesterol (Berenson, 2006). The safety barriers put in place failed. The initial biomarkers selected to monitor the drug recipients did not work to alert doctors that something was about to go horrifically wrong. Pfizer lost about a billion dollars in the development of the drug, and sons and daughters lost their lives (Williams et al., 2018).
In a retrospective study, researchers applied a new proteomic technology (SOMAscan platform) to blood samples collected from participants of the failed study (Williams et al., 2018). The data from this proteomic investigation illuminated unknown deep physiological effects of the experimental drug that were also quite pervasive, and which probably would not have been picked up by technologies available at the time the clinical trial was conducted. The effects were especially prevalent in the bodily functions of immunity and inflammation. The insights provided by the SOMAscan proteomic analysis offered probable explanations for the deaths attributed to taking the experimental drug.
Although the SOMAscan technology was not available at that time, the odds are very good that the problems with torcetrapib would have surfaced early enough to make a difference. It is important to note that during the clinical trials, clinicians used instead the best available measurement, the Framingham risk score (a score to assess the likelihood of having heart problems), to monitor the patients, and observed a decreased risk of heart problems for the experimental drug users (Williams et al., 2018). In the retrospective SOMAscan study, the proteomic data showed the opposite result; the experimental drug users were actually at an elevated risk (Williams et al., 2018). This is not the first-time proteomics beat the Framingham risk score, a gold standard for assessing cardiovascular event risks. In an earlier and separate retrospective study, the proteomic assessment using the SOMAscan platform outperformed the Framingham risk score in determining the patients most likely to suffer a heart attack (Ganz et al., 2016).
While it is too late to help those who suffered from the unexpected effects of torcetrapib, we now have an opportunity to spare others from unintended harm. Applying the proteomic bubble wrap during clinical trials may indeed prevent unnecessary deaths. Also, the SOMAscan platform may better identify patients who would benefit the most from the experimental drug or who should avoid it all costs. Already, we know that the inclusion of biomarkers in the stratification of patients to receive experimental treatment can improve the success rate for FDA approval (Wong, Siah, & Lo, 2018). However, we need to use every tool at our disposal to monitor the right things at the right time, to avoid the kind of outcomes seen with the torcetrapib trial.
Berenson, A. (2006, December 4). End of Drug Trial Is a Big Loss for Pfizer. The New York Times. Retrieved from http://www.nytimes.com/2006/12/04/health/04pfizer.html.
Food and Drug Administration. (2017a, November 24). The FDA’s Drug Review Process: Ensuring Drugs Are Safe and Effective. Retrieved on March 20, 2018 at https://www.fda.gov/Drugs/ResourcesForYou/Consumers/ucm143534.htm
Food and Drug Administration. (2017b, November 17). FDA’s Sentinel Initiative – Background. Retreived on March 20, 2018 at https://www.fda.gov/Safety/FDAsSentinelInitiative/ucm149340.htm
Food and Drug Administration. (2018, February 21). Questions and Answers on FDA’s Adverse Event Reporting System (FAERS). Retrieved on March 20, 2018 at https://www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Surveillance/AdverseDrugEffects/default.htm.
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
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
Wong, C. H., Siah, K. W., & Lo, A. W. (2018). Estimation of clinical trial success rates and related parameters. Biostatistics. doi:10.1093/biostatistics/kxx069
It is simple. It is non-invasive. Yet, it is not without risk. I am referring to imaging technologies, such as X-rays and computed tomography (CT) scans, that expose bodies to radiation to “see” under the skin.
What’s the risk with radiation? Well, the radiation can alter/damage DNA. Unfortunately, damaged DNA does not lead to one developing super powers despite what the comics might say. But damaged DNA can lead to cancer (ACS, 2015). And the risk only increases with repeated rounds of radiation exposure.
It’s true that the amount of radiation exposure from a simple X-ray of an extremity (e.g., an arm) is equivalent to about 3 hours of environmental radiation exposure for the typical adult (Radiological Society of North America, 2018). However, if you are subjected to many X-rays or other imaging procedures that use way more radiation over the course of your lifetime, the added radiation exposure quickly adds up. As you might expect, this extra exposure increases your cancer risk but not your Spidey senses.
What can be done to mitigate the risk? Cutting down on the number of X-rays would help. One superhero may swoop in to do just that: Researchers are pioneering the use of a simple blood sample to figure out if bones are healing.
Current monitoring of broken bones uses highly variable metrics and lacks universal standards. Researchers from Boston University set out to determine if a standardized lab test built on blood analysis could take the place of all these other approaches (Hussein et al., 2017). Using a mouse model, the researchers collected many samples and searched for different types of biomarkers. They noted that hundreds of proteins changed dramatically during the course of the bone-healing process. Optimistically, they noted that protein measurement-based blood tests may prove especially promising in monitoring human bone repair.
In a serendipitous and almost concurrent moment, an international group of researchers led by scientists from the Shriners Hospitals for Children and the Oregon Health and Science University in Portland happened upon related findings (Coghlan et al., 2017). These researchers set out to bring order to the field of monitoring how quickly children grow, which currently yields variable results, particularly in very young children. In their search, the researchers identified that the circulating levels of the protein “noncollagenous 1 domain of type X collagen” (CXM) tracked well with growth rate (specifically, the rate of bone growth). For young patients suffering from growth disorders, having a more precise way of monitoring growth rates proves crucial to gauge appropriate response to medical treatment. As for the moment of serendipity, the researchers also noted that the levels of CXM rise during the healing of broken bones.
We will likely never be able to eliminate imaging based on X-rays: It is just too useful. We may, however, be able to reduce our need for them with improved diagnostic technologies for particular uses, like monitoring bone healing. Not only will new approaches like blood analysis inevitably reduce the amount of radiation exposure, but it could be easier on the pocket book too: Just think of how many superhero comic books could be purchased for the cost of a CT scan or a standard X-ray!
American Cancer Society (ACS) medical and editorial content team. (2015, February 24). Do x-rays and gamma rays cause cancer? Retrieved from https://www.cancer.org/cancer/cancer-causes/radiation-exposure/x-rays-gamma-rays/do-xrays-and-gamma-rays-cause-cancer.html
Coghlan, R. F., Oberdorf, J. A., Sienko, S., Aiona, M. D., Boston, B. A., Connelly, K. J., . . . Horton, W. A. (2017). A degradation fragment of type X collagen is a real-time marker for bone growth velocity. Sci Transl Med, 9(419). doi:10.1126/scitranslmed.aan4669
Hussein, A. I., Mancini, C., Lybrand, K. E., Cooke, M. E., Matheny, H. E., Hogue, B. L., . . . Gerstenfeld, L. C. (2017). Serum proteomic assessment of the progression of fracture healing. J Orthop Res. doi:10.1002/jor.23754
Radiological Society of North America, Inc. (accessed February 8, 2018) Radiation Dose in X-Ray and CT Exams. Retrieved from https://www.radiologyinfo.org/en/info.cfm?pg=safety-xray