SomaLogic licenses GNS Healthcare’s REFS™ technology for analysis of its SOMAscan®-derived proteomic data

Combining the world-leading proteomic and artificial intelligence/machine learning technologies to produce novel, actionable health insights across many diseases, conditions and markets

SomaLogic and GNS Healthcare announced today that SomaLogic has obtained a license to apply GNS Healthcare’s proprietary REFS™ (Reverse Engineering & Forward Simulation) causal machine learning technology to SomaLogic’s proprietary SOMAscan®-derived protein data sets. The goal of this agreement is to leverage REFS to rapidly accelerate the translation of SomaLogic’s massive protein data into meaningful and actionable information for individual and population health management.

Living organisms function through complicated interconnected biological networks that respond dynamically to factors such as diet, environment, medication, infection and disease. SomaLogic’s SOMAscan platform taps into these networks by repeatedly measuring the changing levels of thousands of proteins circulating through the body over time. These large data sets require increasingly powerful machine learning-based tools like GNS Healthcare’s unique REFS platform, which builds computational models of the biological networks from the raw data to reveal new understandings of disease and even potential interventions.

“Our ability to measure 5,000 proteins in each of hundreds of thousands of samples requires that we be able to analyze all those data in a way that will ultimately result in making a difference for individuals and their health providers,” said Alister Reynolds, CEO of SomaLogic. “We believe that GNS Healthcare’s powerful REFS technology has the potential to become a critical tool for extracting those meaningful health insights.”

“Our REFS platform has proven itself repeatedly with genomic, transcriptomic, metabolite, clinical, labs, EMR, claims, and other data types, and we are excited to see how well it performs on real-time biological measurements like proteins,” said Colin Hill, CEO and cofounder of GNS Healthcare. “SOMAscan-derived protein data are perfectly suited to the REFS workflow, and we look forward to our platform fully proving its value again in this setting.”

Further specifics about the agreement were not disclosed.

 

###

GNS Healthcare Contact
Patty Kellicker
VP, Marketing
T: 617-374-2384
pkellicker@gnshealthcare.com

SomaLogic Contact
Laura S. Mizoue, Ph.D.
Communications Specialist
T: 720-417-7509
lmizoue@somalogic.com

About GNS Healthcare
GNS Healthcare solves healthcare’s matching problem for leading health plans, biopharma companies, and health systems. We transform massive and diverse data streams to precisely match therapeutics, procedures, and care management interventions to individuals, improving health outcomes and saving billions of dollars. Our causal learning and simulation platform, REFS, accelerates the discovery of what works for whom and why. Learn more at www.gnshealthcare.com.

About SomaLogic
SomaLogic delivers meaningful and actionable health-management insights that empower individuals worldwide to continuously optimize their personal health and wellness throughout their lives. These essential insights, which are provided through a global network of partners and users, are derived from precise, proprietary, and personalized measurement of critical changes in an individual’s proteins over time. For more information, visit www.somalogic.com.

 

Why Dread the Very Thing That Once Brought Us so Much Joy?

Why Dread the Very Thing That Once Brought Us so Much Joy?

“Happy birthday to you…” Do these words instill incapacitating fear or unbridled joy? Children welcome them with wide open arms and with great jubilation. As people age, the enthusiasm wanes to the point of dread. Why?

One possibility has to do with the aging process. Children look forward to getting older because with it come new found freedoms or rites of passage. At some point, we realize that aging is not as cool as we once thought. As we age, we fear the grim possibility of losing the very freedoms that we coveted in our youth, such as independence. But what if this did not have to be the case?

A key facilitator to our independence is our degree of health, which also decides how well we age. Those who are considered to be aging well typically look younger and are more active than one would expect for their chronological age. What if we have a laxer definition? What if the defining aspect was having a body that is biologically younger than what is stated on some document? For instance, a man may be 83 on paper but could really be 10 years younger based on how well his body works at the molecular level. It seems like science fiction, but it is already here in some ways. For example, a patient might be told by her doctor that her heart is functioning incredibly well for her age.

What we do not yet have is a clinical test that measures thousands of protein levels from many biological systems and breaks the news to us if they – and we – are aging well or not. But we are getting closer. In a first-of-its-kind study, researchers utilized the SOMAscan Platform to chart how our proteomes change with age and found proteins that tracked well with biological aging, which could lead to a better understanding of the molecular underpinnings of the process (Menni et al., 2015). Many of these proteins have been linked previously to aging, but it is unclear how others are contributing to the aging process. Although the results are incredibly promising, more and larger studies are needed to verify and expand on them.

Nevertheless, how exciting will it be to have a test that reveals our biological age? We could be significantly younger than what we are told by some calendar! It would certainly take the sting out of the next time someone wishes us a happy birthday. Who knows, birthdays might once again be a source of joy instead of dread.

 

References

Menni, C., Kiddle, S. J., Mangino, M., Vinuela, A., Psatha, M., Steves, C., . . . Valdes, A. M. (2015). Circulating Proteomic Signatures of Chronological Age. J Gerontol A Biol Sci Med Sci, 70(7), 809-816. doi:10.1093/gerona/glu121

 

Donuts Are Not the Only Things With Holes in Them

My love-hate nemesis is back. One encounter and our paths take a long time to diverge again. Despite all my efforts, my avoidance tactics have again failed and our paths have again converged. I speak, of course, of a delicious donut and its long-term clinging to my waist line.

As we age, our metabolism slows. The battle to shed pounds and support the svelte forms of our youth only becomes more difficult. But, numerous companies have sprung up to “help” us with our Herculean efforts to behave. Do any of them offer a valid method to help me sever ties permanently with the seductive donut?

Perhaps. Some genetic tests are now commercially available that promise to tell you the ideal diet based on your genes. Perusing some of the gene-recommended diets, it is clear they have captured what has always been promoted as a healthy diet (Robbins, 2016; Miller, 2018). Alas, I am looking for genetic permission to follow a diet rich in donuts and other sugary bakery goods. Nevertheless, people on the old-fashioned diet do spout off that they feel great and are losing weight (Miller, 2018). What gives? Could it truly be that genetics gave an insight or was it just following a healthy diet?

The successes (and not all people see success!) are not likely the result of properly matching diets to genotype. A recent and thorough study out of Stanford University, published in the Journal of the American Medical Association (JAMA), revealed that matching diets to genotypes does not give a person a huge advantage in weight loss (Gardner et al., 2018). Regardless of a match or not, participants lost weight. Eating healthy diets drove the weight loss. What this study does show is that we still have a lot to learn about the molecular underpinnings of weight loss and cannot rely on recommendations based solely on genetics.

If we look deeper into the biology of weight gain/loss, it is messier than my face after an encounter with delectable lemon curd filled donut. There are many reasons for the messiness; here are just a few:

1. People can lose weight based on the power of suggestion.

Yes, the power of suggestion is truly remarkable. In a study, two groups of women in the same profession were either told that their current level of activity met the surgeon general’s definition of an active lifestyle or were not given that info at all (Spiegel, 2008). After one month, the group informed about the surgeon general’s definition lost weight but had not increased their activity levels. The authors attributed the weight loss to a change in mindset. Quick! I need a doc or dietician to tell me that donuts can induce weight loss!

2. Genes can be turned on or off.

Research has shown that healthy lifestyle habits continually beat the genetic code predictions (Wang et al., 2018). It may sound unbelievable, but genes can be turned off or on before we are even born or in response to current environment (Youngson & Morris, 2013). Simple genetic tests may not be discerning which of these “make me fat now” genes are on or off.

3. The bacteria in our gut could be playing a role in weight loss.

In case you were not aware, our intestines are full of bacteria. In mice, researchers found that the guts of obese individuals were populated with certain types of bacteria (Ley et al., 2005). Soon after, it was learned that skinny mice could become obese if given the gut bacteria from fat mice (Turnbaugh et al., 2006). These early findings opened the flood gates to research looking at the contributions of gut bacteria in weight loss for humans. Guess what? Research shows that if our gut is populated by certain types of bacteria, it may give us an edge on losing weight (Hjorth et al., 2017; Youngson & Morris, 2013). There is still much to be learned, though, and some members of the research community are even calling these hopeful early findings into question (Begley, 2016).

It turns out that there is much to consider (and much unknown still) when it comes to factors that could affect our girth. Ugh! There must be a simpler way to help us better gauge our biological response to diets or even forecast if a diet will work.

Good news everybody! Proteomics (i.e., looking at the proteins in our body) may be the answer. Proteins (not genes) carry out the bulk of the metabolism work that happens at the molecular level. Already, technology has allowed us to look at the biological changes of least 5,000 proteins simultaneously. Initial work has shown promise in showing us how our bodies respond to diets (Oller Moreno et al., 2018) and indicated when a diet will be a huge failure (Thrush et al., 2017).

I may not be able to continue my love affair with the seductive donut as I get older without paying the consequences of increased mass. However, it is good to know that we may one day have the health insights necessary to better predict a diet where I might be able to have the occasional delectable gooey donut without a longer-term commitment to it.

 

References

Begley, S. (2016, September 22). Is the gut microbiome an important cause of obesity? STAT. Retrieved from https://www.statnews.com/2016/09/22/gut-microbiome-obesity.

Gardner, C. D., Trepanowski, J. F., Del Gobbo, L. C., Hauser, M. E., Rigdon, J., Ioannidis, J. P. A., . . . King, A. C. (2018). Effect of Low-Fat vs Low-Carbohydrate Diet on 12-Month Weight Loss in Overweight Adults and the Association With Genotype Pattern or Insulin Secretion: The DIETFITS Randomized Clinical Trial. JAMA, 319(7), 667-679. doi:10.1001/jama.2018.0245

Hjorth, M. F., Roager, H. M., Larsen, T. M., Poulsen, S. K., Licht, T. R., Bahl, M. I., . . . Astrup, A. (2017). Pre-treatment microbial Prevotella-to-Bacteroides ratio, determines body fat loss success during a 6-month randomized controlled diet intervention. Int J Obes (Lond). doi:10.1038/ijo.2017.220

Ley, R. E., Backhed, F., Turnbaugh, P., Lozupone, C. A., Knight, R. D., & Gordon, J. I. (2005). Obesity alters gut microbial ecology. Proc Natl Acad Sci U S A, 102(31), 11070-11075. doi:10.1073/pnas.0504978102

Miller A. (2018, January 16). Should You Take a Genetic Test to Find the Best Diet for You? U.S.News. Retrieved from https://health.usnews.com/wellness/articles/2018-01-16/should-you-take-a-genetic-test-to-find-the-best-diet-for-you.

Oller Moreno, S., Cominetti, O., Nunez Galindo, A., Irincheeva, I., Corthesy, J., Astrup, A., . . . Dayon, L. (2018). The differential plasma proteome of obese and overweight individuals undergoing a nutritional weight loss and maintenance intervention. Proteomics Clin Appl, 12(1). doi:10.1002/prca.201600150

Robbins, R. (2016, November 3). Genetic tests promised to help me achieve peak fitness. What I got was a fiasco. STAT. Retrieved from https://www.statnews.com/2016/11/03/genetic-testing-fitness-nutrition/.

Spiegel, A. (2008, January3). Hotel Maids Challenge the Placebo Effect. NPR. Retrieved from https://www.npr.org/templates/story/story.php?storyId=17792517.

Thrush, A. B., Antoun, G., Nikpay, M., Patten, D. A., DeVlugt, C., Mauger, J. F., . . . Harper, M. E. (2017). Diet-resistant obesity is characterized by a distinct plasma proteomic signature and impaired muscle fiber metabolism. Int J Obes (Lond). doi:10.1038/ijo.2017.286

Turnbaugh, P. J., Ley, R. E., Mahowald, M. A., Magrini, V., Mardis, E. R., & Gordon, J. I. (2006). An obesity-associated gut microbiome with increased capacity for energy harvest. Nature, 444(7122), 1027-1031. doi:10.1038/nature05414

Wang, T., Heianza, Y., Sun, D., Huang, T., Ma, W., Rimm, E. B., . . . Qi, L. (2018). Improving adherence to healthy dietary patterns, genetic risk, and long term weight gain: gene-diet interaction analysis in two prospective cohort studies. BMJ, 360, j5644. doi:10.1136/bmj.j5644

Youngson, N. A., & Morris, M. J. (2013). What obesity research tells us about epigenetic mechanisms. Philos Trans R Soc Lond B Biol Sci, 368(1609), 20110337. doi:10.1098/rstb.2011.0337

 

Inside Scoop on Latest Trends in Science: Details Inside!

Inside Scoop on Latest Trends in Science: Details Inside!

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.

 

References

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

 

Translating the “Book of Life”

Measuring proteins reveals how genetic changes help give rise to complex traits and diseases

An article published today in the journal Nature brings us closer to understanding how differences in the genomes of individuals help contribute to common diseases and influence disease risk. Specifically, this study — by far the largest of its kind to date — revealed the effects of genetic variations on the levels of circulating blood proteins across thousands of individuals.

Proteins play essential roles throughout the body, and changes in their concentrations can reflect a person’s health status at any given time. Proteins are also the targets of most drugs, so the results of this study open the door to understanding individual responses to medical treatments, one of the goals of precision medicine.

Over the past decade, genome-wide association studies (GWAS) have identified of DNA variants that are linked to complex traits and diseases but have not explained exactly why they are important. The vast majority of DNA differences flagged by GWAS lie in regions of the genome with no known function and have small effect sizes. This makes establishing causal relationships or determining disease risk extremely difficult, even for conditions with a strong hereditary component such as obesity or cancer.

In the largest study of its kind to date, an international team led by researchers from the University of Cambridge and Merck tested 10.6 million DNA variants against the levels of 2,994 plasma proteins — measured using the SOMAscan® assay — in 3,301 healthy individuals of European heritage. They identified 1,927 genetic variants that impact the levels of 1,478 plasma proteins, of which ~90% had not been previously reported. Many of the variants act in “trans” (i.e., they lie far from the gene whose activity is altered, typically on different chromosomes). Trans associations are particularly interesting because they can highlight biological connections that are otherwise difficult to predict.

The authors cross-referenced their findings with known disease-associated GWAS variants to identify proteins that might cause disease. Some disease-associated proteins are targets of existing drugs, which suggests possible therapeutics for new indications. Connecting protein perturbations to disease endpoints also allows identification of new drug targets and potential safety concerns for drugs under development. These results also suggest that monitoring protein levels over time may suffice for regular health management.

Reference: Sun, BB et al. (2018) “Genomic atlas of the human plasma proteome” Nature 558: 73-79

See also the University of Cambridge news release.

 
 

We Got Rhythm. We Got Precision Medicine.

We Got Rhythm. We Got Precision Medicine.

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.

 

References

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

 

Health in Space and Time

Health in Space and Time

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.

 

Blood: Our Gossipmonger

Blood: Our Gossipmonger

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.

 

References

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

 

 

The Proteomic Bubble Wrap Suit

The Proteomic Bubble Wrap Suit

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.

 

References

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

 

Melody Harris, J.D., appointed Chief Legal Officer of SomaLogic

April 2, 2018 – Boulder, CO – SomaLogic announced today that Melody Harris has joined SomaLogic as the company’s Chief Legal Officer. Ms. Harris comes to SomaLogic from Qualcomm Life, a digital health subsidiary of Qualcomm, where she led the legal, global privacy, and Quality, Regulatory & Compliance groups as Vice President & Chief Counsel.

“I am delighted that Melody has chosen to take on this central role at SomaLogic at this critical time of company growth,” said Al Reynolds, Chief Executive Officer of SomaLogic. “She brings with
her a wealth of experience in healthcare technology and data-centric business models that we need to help us accelerate the delivery of SomaLogic’s breakthrough precision health insights into multiple markets around the world.”

SomaLogic was founded to transform healthcare by accurately measuring the changing state of an individual’s health over time, as revealed by changes in the proteins that make up the human body. Regularly monitoring thousands of proteins, unlike genome sequencing, can reveal not only real-time health status but also what interventions (e.g., diet, prescription and/or lifestyle changes) could maximize that status.

“SomaLogic is bringing together a unique technology and business plan to entirely change how people world-wide manage their personal health,” said Ms. Harris. “This rare opportunity to make a real difference in people’s lives is exciting, and I am eager to join the SomaLogic team to help make that vision a reality.”

Ms. Harris joined Qualcomm Life with the acquisition of HealthyCircles, where she served as General Counsel. At HealthyCircles, Ms. Harris built the company’s legal and compliance functions and advised on early-stage product development related to data and privacy by design. Prior to HealthyCircles, Ms. Harris held a variety of senior leadership roles, including President & General Counsel of an international IP management firm, Executive Vice President and General Counsel of an international software development and consulting firm, and Senior IP counsel to U S WEST/Qwest. She received her J.D., cum laude, from the Harvard Law School and her B.A., cum laude, in political science from the University of Denver.

###

SomaLogic Contact
Laura S. Mizoue, Ph.D.
Communications Specialist
T: 720-417-7509
lmizoue@somalogic.com

About SomaLogic
SomaLogic delivers health management insights in real-time that empower individuals to take action to improve their personal health and wellness. These essential insights, provided through a global network of partners and users, are derived from precise, proprietary, and personalized measurement of critical changes in an individual’s protein makeup throughout life. For more information, visit http://www.somalogic.com/.