Born under atypical circumstances, a perfect storm wields unimaginable havoc. So, does a rare disease. What exactly constitutes a rare disease? In the U.S., the Orphan Drug Act of 1983 stipulated that “rarity” meant the disease affected fewer than 1 in 200,000 people, which applies to about 7,000 diseases (National Institutes of Health, 2017). With so many rare diseases, the NIH estimates that as many as 20 to 35 million Americans suffer from one of the ~7000 rare diseases, which is about 1 in 10. That means you likely know a person caught up in a not-so-rare perfect storm.
What makes a rare disease a perfect storm? Well, like a meteorological perfect storm, a unique combination of events transpires. Those afflicted with one of the roughly 7000 named biological storms hit the trifecta of difficulty in getting a correct diagnosis, finding a doctor knowledgeable of the disease and securing some type of treatment plan. Despite the good intent of the Orphan Drug Act of 1983, affordable treatments can be as rare as the disease itself. The rare disease not only challenge the actual patient, but also the doctors and researchers (Stoller, 2018).
Unlike the meteorological version, we have a shot at taming the biological perfect storm through new medical insights and improved communication. So, let us break out a new kind of powerful Doppler radar: proteomics. Yes, proteomics can reveal a lot about us and even potentially help people weather their particular storms.
Looking at Castleman disease, we can see proteomics in action (Pierson et al., 2018). This very rare and devastating disease involves enlarged lymph nodes and can be subdivided into one of three categories depending on symptoms and presence of a viral infection. One of these subgroups — Human Herpesvirus (HHV)-8-negative, idiopathic multicentric Castleman disease (iMCD) — wields extremely severe symptoms, can be fatal, arises from unknown origins and is difficult to treat. Dr. David Fajgenbaum and co-researchers used proteomics to tease out the details of iMCD, which can be further subdivided into two groups. They mentioned that initially it was thought that cytokines were the driving force behind iMCD, with interleukin-6 playing a significant role. However, only a third of patients responded to anti-interleukin-6 therapy. Through the proteomics, the researchers saw that the two subgroups of iMCD had two different proteomic profiles. This difference might explain why one group did not respond to anti-interleukin treatment and the other one did. Also, they found that although cytokines do play a part in the perfect storm, it is really a smaller group, chemokines (proteins that direct white blood cells to sites of infection) that are at the eye of the storm.
Just think, we maybe be witnessing the potential for calm after this storm! One day, we could have the means to determine quickly and accurately who may benefit from certain treatments. This work has also highlighted new targets for therapeutics or new potential treatment strategies. The proteomic Doppler radar could be our deliverance from the havoc wreaked by the perfect storm of rare disease.
National Institutes of Health/ National Center for Advancing Translational Sciences/ Genetic and Rare Diseases Information Center. (2017, November 30). FAQs About Rare Diseases. Retrieved on July 12, 2018 from https://rarediseases.info.nih.gov/diseases/pages/31/faqs-about-rare-diseases.
Pierson, S. K., Stonestrom, A. J., Shilling, D., Ruth, J., Nabel, C. S., Singh, A., . . . Fajgenbaum, D. C. (2018). Plasma proteomics identifies a ‘chemokine storm’ in idiopathic multicentric Castleman disease. Am J Hematol, 93(7), 902-912. doi:10.1002/ajh.25123
Stoller, J. K. (2018). The Challenge of Rare Diseases. Chest, 153(6), 1309-1314. doi:10.1016/j.chest.2017.12.018
What the …?? …. Standing back, I wonder what the artist envisioned while painting this piece. Did they just enjoy seeing the colors mix and build elaborate textures? Are they trying to communicate a new revelation about the human condition?
It turns out the artist is barely two years old. Far too young to really be grappling with existential questions. The artist most likely just enjoyed playing with the paint.
We have a normal tendency to over- or misinterpret things, whether it be art itself or the artist’s intentions. We can do the same with genomic data. With over 75,000 genetic tests available (Johnson, 2018), the deluge of information can wash over us and the medical experts, leaving us grappling with deeper questions of meaning and use.
Recently, a study came out about how primary care doctors, cardiologists or oncologists view genomic “art” (Pet et al., 2018). Many of the doctors surveyed showed concern over how to address the findings from consumer genomic tests that told healthy people they were at risk for serious diseases. They worried that the results could lead to unnecessary medical treatment, increased costs, potential complications and problems with insurance. Overall, they wanted the patients to be provided with clearly communicated, actionable results: “What does it mean and what should I do?”
How actionable or reliable can genomic test results be? If we scan the brush-strokes of the whole genome, many of us (including medical people) would be left scratching our heads and saying, “What the…?” As we previously noted, genomes are noisy to the point of being called “space vomit.” Yet, there is still a belief that genetic testing will be pivotal to healthcare in the future (Pet et al., 2018).
We are taking steps in the right direction for learning how to improve the interpretation of genomic art in a meaningful way, but do we even need to? Novartis scientists recently conducted a study to link genetic variants (think “mutations”) to disease by using proteomics (Emilsson et al., 2018). In their analysis of nearly 5,000 proteins found in serum, they learned that many proteins clustered into groups that were co-regulated. The study also revealed that the protein groupings could be used to glean health insights.
What happened when genomic data were layered onto the picture? Well, the study reiterated the difficulty in linking a genetic variant to a single protein, which highlights the complexity of our bodies. However, the study suggested that some variants could be connected to the identified protein groups.
Maybe just focusing on and maximizing the more immediate potential of proteins to reveal the inner working of our bodies is the most direct and interpretable route for realizing the artistic promise of precision medicine.
Johnson, C. (2018, May 7). Medicine’s Wild West: 10 new genetic tests enter the market each day. The Washington Post. Retrieved on August 1, 2018 from https://www.washingtonpost.com/news/wonk/wp/2018/05/07/medicines-wild-west-10-new-genetic-tests-enter-the-market-each-day/?utm_term=.6cf729004c2e.
Emilsson, V., Ilkov, M., Lamb, J. R., Finkel, N., Gudmundsson, E. F., Pitts, R., . . . Gudnason, V. (2018). Co-regulatory networks of human serum proteins link genetics to disease. Science. doi:10.1126/science.aaq1327
Pet, D. B., Holm, I. A., Williams, J. L., Myers, M. F., Novak, L. L., Brothers, K. B., . . . Clayton, E. W. (2018). Physicians’ perspectives on receiving unsolicited genomic results. Genet Med. doi:10.1038/s41436-018-0047-z
Your genome has been hacked! …literally. Recently, a direct-to-consumer genetic test company was hacked and information about millions of people was compromised (Thielking, 2018). In this day and age, it is not surprising when a company gets hacked. What is surprising is one of the ways a genetics company can be hacked. The sneaky route involves the malware being programmed into a DNA sample. When sequenced, the malware grants the hackers access. Sounds like a Hollywood movie plot, but it happened (Thielking, 2018).
Just how private is our biological information, and are people concerned? In a recent survey, about 47% people had concerns about the confidentiality of their genetic information derived from genealogical genetic testing (Hensley, 2018). Sadly, genetic information is difficult to keep secret. Aside from companies or other holders of genetic information being hacked, you can also lose your genetic privacy if your blood relatives choose to give away their genetic info like beads at Mardi Gras. This should not be a surprise, given the growing forensic use of relatives’ DNA to crack cold cases.
Is this only a genes problem, or are an individual’s proteins also a privacy risk? Although proteins can change rapidly in response to many different environmental changes, we can be named by our proteins. Not too long ago, a group of researchers used a mass spectrometry approach to identify a person based on the proteins found in a hair sample (Parker et al., 2016). They demonstrated that if a person carries a genetic variation that alters the amino acid sequence of a protein, then that person could be identified based on the protein sequence in the sample. Although hair has a relatively small number of proteins, it is likely that more complex protein samples, such as blood, could also be used to single out a person.
Is there a way to make mass spectrometry less revealing? One proposal is to remove some of the potentially distinguishing data, which would make it harder to link it back to a specific individual, but not impossible (Li, Bandeira, Wang, & Tang, 2016). Nevertheless, this is a step in the right direction, but it may already be too late.
A quick search on Google reveals numerous repositories where proteomic data have been shared. When it comes time to publish a scientific paper, some journals, such as PLOS journals), make sharing proteomic data mandatory (http://journals.plos.org/plosone/s/data-availability). It is worth noting that a few exceptions to making the data available do exist, but a chance of the data holder being hacked still remains. Although some journals merely recommend sharing the data (e.g., Cell https://www.cell.com/cell/authors), there are growing cries for more data transparency, including (Matheson, 2018). The government has made a similar proposition (Friedman, 2018). With such a demand for transparency and access to data, can we still hold onto our beloved privacy? And how does this affect people’s willingness to donate biological samples or partake in clinical studies? The only thing that is certain now is that once the data are out, there is no way to secure them again.
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
Friedman, L. (2018, March 26) The E.P.A. Says It Wants Research Transparency. Scientists See an Attack on Science. New York Times. (Retrieved on June 6, 2018 from https://www.nytimes.com/2018/03/26/climate/epa-scientific-transparency-honest-act.html).
Hensley, S. (2018, June 1) POLL: Genealogical Curiosity Is A Top Reason For DNA Tests; Privacy A Concern. NPR. (Retrieved on June 3, 2018 from https://www.npr.org/sections/health-shots/2018/06/01/616126056/poll-genealogical-curiosity-is-a-top-reason-for-dna-tests-privacy-a-concern).
Li, S., Bandeira, N., Wang, X., & Tang, H. (2016). On the privacy risks of sharing clinical proteomics data. AMIA Jt Summits Transl Sci Proc, 2016, 122-131.
Matheson S. (2018, May 30) Why you should deposit your raw data. Crosstalk [blog post]. Retrieved on June 6, 2018 from http://crosstalk.cell.com/blog/why-you-should-deposit-your-raw-data).
Parker, G. J., Leppert, T., Anex, D. S., Hilmer, J. K., Matsunami, N., Baird, L., . . . Leppert, M. (2016). Demonstration of Protein-Based Human Identification Using the Hair Shaft Proteome. PLoS One, 11(9), e0160653. doi:10.1371/journal.pone.0160653
Thielking, M. (2018, June 5) Genealogy site MyHeritage says 92 million user accountscompromised. STAT. (Retrieved on June 6, 2018 from https://www.statnews.com/2018/06/05/genealogy-site-myheritage-says-92-million-user-accounts-compromised/).
The warrior king of Sparta, King Leonidas, and his small legion found themselves arrayed against an army of hundreds of thousands. Though they fought bravely until the very end, the odds and ultimately the Fates did not favor the poor king and his legion in that gory battle of Thermopylae.
Such battles are waged not just historically, but also today, though in much tinier, subcellular arenas. Consider Duchenne muscular dystrophy (DMD), a disease that predominantly affects young men. The origins of the battle start at the genetic level (National Institutes of Health (NIH), 2018). Mutations in the DMD gene, which can happen sporadically or be inherited on the X chromosome, compromise the critical protein dystrophin. According to the NIH’s war reports, dystrophin plays a primary role in stabilizing and guarding muscle fibers. Losing it leads to a constant attack on muscle tone and integrity, and ultimately to muscle defeat.
Further reading of the NIH’s war reports supplies added details. Early on in the battle, the brave young warriors bear the full brunt of the attack. Although their muscles struggle mightily to maintain themselves, children with DMD experience mobility problems early. Their calf muscles become enlarged as fat cells and other tissue replace the muscle. Over time, this muscle destruction becomes widespread, leading to breathing difficulties, joint problems and enlarged hearts (cardiomyopathy). In addition to compromised bodies, the battle also wreaks havoc on their minds, burdening the warriors with cognitive impairment, communication problems and impaired social behavior. Like the valiant King Leonidas and his army, these modern warriors are doomed.
But maybe we can delay or even change the fate of current or future warriors. Maybe there are additional weapons we have not considered. For example, in a piece of intel we learn that dystrophin is important not only to muscle formation, but also to signaling (i.e., communications between cells), and disruption of communications could be contributing to the disease (Allen, Whitehead, & Froehner, 2016). The intel’s authors postulate that a deeper understanding about the disruption in communications could open the door for more therapeutics as well as improvements in diagnosis, checking disease progression and assessing the effectiveness of treatments (Allen et al., 2016).
The SOMAscan platform, a proteomic technology, has been enlisted in battle against the tragic disease. The technology revealed that as few as six proteins maybe needed to accurately diagnose the disease (Parolo et al., 2018). Proteomics also revealed that DMD altered the communications in the immune system, the neurotrophin signaling pathway, apoptosis (cell death) and additional effectors of other biological systems (Parolo et al., 2018).
Once diagnosed, it becomes imperative to continue surveillance of the disease’s progression. One way to monitor progression involves invasive muscle biopsies. Recently, researchers developed a new less invasive way to monitor the progression using the SOMAscan platform, and it only requires a blood sample (Spitali et al., 2018). Over time, the tests revealed that the levels of hundreds of proteins changed, which could be indicative of muscle deterioration, increase of fat cells and heart problems (Spitali et al., 2018). Another group used the SOMAscan platform to identify biomarkers for cardiomyopathy in DMD patients (Anderson et al., 2017).
The war of the ages continues, but it may not last forever. As mentioned, proteomics can reveal the weaknesses of the DMD enemy and the effects of therapeutic strategies at the molecular level (Hathout et al., 2016). Let us hope that with different tactics, the fates may start to favor the brave and valiant warriors.
Allen, D. G., Whitehead, N. P., & Froehner, S. C. (2016). Absence of Dystrophin Disrupts Skeletal Muscle Signaling: Roles of Ca2+, Reactive Oxygen Species, and Nitric Oxide in the Development of Muscular Dystrophy. Physiol Rev, 96(1), 253-305. doi:10.1152/physrev.00007.2015
Anderson, J., Seol, H., Gordish-Dressman, H., Hathout, Y., Spurney, C. F., & Investigators, C. (2017). Interleukin 1 Receptor-Like 1 Protein (ST2) is a Potential Biomarker for Cardiomyopathy in Duchenne Muscular Dystrophy. Pediatr Cardiol, 38(8), 1606-1612. doi:10.1007/s00246-017-1703-9
Hathout, Y., Conklin, L. S., Seol, H., Gordish-Dressman, H., Brown, K. J., Morgenroth, L. P., . . . Hoffman, E. P. (2016). Serum pharmacodynamic biomarkers for chronic corticosteroid treatment of children. Sci Rep, 6, 31727. doi:10.1038/srep31727
National Institutes of Health. Duchenne muscular dystrophy. Retrieved on June 27, 2018 from https://rarediseases.info.nih.gov/diseases/6291/duchenne-muscular-dystrophy.
Parolo, S., Marchetti, L., Lauria, M., Misselbeck, K., Scott-Boyer, M. P., Caberlotto, L., & Priami, C. (2018). Combined use of protein biomarkers and network analysis unveils deregulated regulatory circuits in Duchenne muscular dystrophy. PLoS One, 13(3), e0194225. doi:10.1371/journal.pone.0194225
Spitali, P., Hettne, K., Tsonaka, R., Charrout, M., van den Bergen, J., Koeks, Z., . . . Aartsma-Rus, A. (2018). Tracking disease progression non-invasively in Duchenne and Becker muscular dystrophies. J Cachexia Sarcopenia Muscle. doi:10.1002/jcsm.12304
As most of you know, we are all mutants. Each of us carries variations in our gene sequence that, collectively, mark us uniquely. What does it mean to have a mutation? The simple answer is that you have a genetic sequence that is different than the decided upon consensus or “wild-type” sequence.
Well, what decides the “wild-type” sequence? To put it simply, it is the sequence most typically seen to date. This is where we enter a paradox. Pending the source of the genetic information used to decide the “wild-type” sequence, we could potentially be using information that is relevant for one demographic, but not for another.
The realization of this paradox is not a new phenomenon. For instance, Maynard Olson concluded that a single wild-type genetic sequence is a mere illusion and a wild-type human simply does not exist (Olson, 2011). He also said, “…genetics is unlikely to revolutionize medicine until we develop a better understanding of normal phenotypic variation (Olson, 2011).”
If we look at the literature, it seems that these words fell onto deaf ears or were just placed on a side burner. Since 2005, the number of studies involving genome-wide association studies (GWAS) to look for genetic mutations (i.e., variations) that can indicate a person’s risk of disease has exploded (Gallagher & Chen-Plotkin, 2018). Many associations have been made about genetic changes and a variety of diseases, however, they are only correlative in most cases. Compared to the deluge of GWAS studies, little has been done to determine that the associations found are indeed causing the disease (Gallagher & Chen-Plotkin, 2018).
Even if a direct link has been found, it does not completely explain why people who harbor genetic mutations known to cause detrimental disease appear perfectly healthy. In looking at a population of ~500,000 individuals, a recent genomic analysis revealed that 13 individuals harbored mutations that normally give rise to severe Mendellian childhood diseases but these people show no physical manifestations of the diseases (Chen et al., 2016). While this might seem a rare event, it really is not. From analyzing the genomes of 1000 “healthy” people, one group estimated that an average individual may actually be harboring >400 genetic changes that can damage the person’s biological equilibrium and >2 known disease causing mutations (Xue et al., 2012).
With everyone potentially harboring so many genetic changes that could have profound consequences, how is it that the clear majority of the people on this planet are functioning, and even functioning well? As James Evan from the University of North Carolina said in an NPR article, “The good news is that most of those mutations do not overtly cause disease, and we appear to have all kinds of redundancy and backup mechanisms to take care of that (Stein, 2012).”
What should we take away from all of this with regards to our individual health? Well, this is another reminder that our genes really only convey a risk and not an imminent fate. This is particularly true when the link between a genetic change and physical outcome is only correlative and not yet directly linked. Until researchers sift through all the associations found through GWAS to identify the ones that actually cause problems (this might not even be possible for the vast majority of associations found), we need to focus on the phenotypes. This includes – perhaps primarily – the proteins encoded by the genes and how they respond to our environment. Focusing on how proteins respond to environmental cues may begin to reveal the buffering systems and lead us to a path of health enlightenment.
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
Gallagher, M. D., & Chen-Plotkin, A. S. (2018). The Post-GWAS Era: From Association to Function. Am J Hum Genet, 102(5), 717-730. doi:10.1016/j.ajhg.2018.04.002
Olson, M. V. (2011). Genome-sequencing anniversary. What does a “normal” human genome look like? Science, 331(6019), 872. doi:10.1126/science.1203236
Stein, R. (2012, December 6) Perfection Is Skin Deep: Everyone Has Flawed Genes. NPR. (Retrieved on May 16, 2018 from https://www.npr.org/sections/health-shots/2012/12/06/166648187/perfection-is-skin-deep-everyone-has-flawed-genes).
Xue, Y., Chen, Y., Ayub, Q., Huang, N., Ball, E. V., Mort, M., . . . Genomes Project, C. (2012). Deleterious- and disease-allele prevalence in healthy individuals: insights from current predictions, mutation databases, and population-scale resequencing. Am J Hum Genet, 91(6), 1022-1032. doi:10.1016/j.ajhg.2012.10.015
“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.
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