Daily News for Neuros, Nurses & Savvy MSers: 208,152 Viewers, 8,368 Stories & Studies
Click Here For My Videos, Advice, Tips, Studies and Trials.
Timothy L. Vollmer, MD
Department of Neurology
University of Colorado Health Sciences Center Professor

Co-Director of the RMMSC at Anschutz Medical Center

Medical Director-Rocky Mountain MS Center
Click here to read my columns
Brian R. Apatoff, MD, PhD
Multiple Sclerosis Institute
Center for Neurological Disorders

Associate Professor Neurology and Neuroscience,

Weill Medical College of Cornell University

Clinical Attending in Neurology,
New York-Presbyterian Hospital
You'll get FREE Breaking News Alerts on new MS treatments as they are approved

HERE'S A FEW OF OUR 6000+ Facebook & MySpace FRIENDS
Timothy L. Vollmer M.D.
Department of Neurology
University of Colorado Health Sciences Center
Co-Director of the RMMSC at Anschutz Medical Center
Medical Director-Rocky Mountain MS Center

Click to view 1280 MS Walk photos!

"MS Can Not
Rob You of Joy"
"I'm an Mom has MS and we have a message for everyone."
- Jennifer Hartmark-Hill MD
Beverly Dean

"I've had MS for 2 years...this is the most important advice you'll ever hear."
"This is how I give myself a painless injection."
Heather Johnson

"A helpful tip for newly diagnosed MS patients."
"Important advice on choosing MS medication "
Joyce Moore

This page is powered by Blogger. Isn't yours?



Diagnosing MS with a Blood Test: Interview with IQuity CEO, Dr. Chase Spurlock

IQuity’s Senior Scientist, John T. Tossberg, pictured at IQuity’s lab

MS is an autoimmune disease that afflicts an approximate 2.5 million patients world-wide, giving rise to multiple issues regarding quality of life and the potential for disability. Up to 15,000 people are newly diagnosed with MS every year in the US, while another 45,000 experience a clinical precursor with similar symptoms. Distinguishing between MS and other possible neurological conditions typically requires multiple brain MRIs and cerebrospinal fluid testing, which are costly and take a long time. Fortunately, the diagnostic technology company IQuity (pronounced I-Q-witty) has been working to speed that up with an RNA-based test to aid doctors in diagnosing MS, as well as a host of other autoimmune diseases. Medgadget spoke to Vanderbilt University faculty member and IQuity’s Founder and CEO, Dr. Chase Spurlock, about the introduction of their IsolateMS diagnostic test to the market.

Mohammad Saleh, Medgadget: Can you tell us about IQuity’s mission and the science behind your new technology?

Chase Spurlock, IQuity: IQuity is the product of over 10 years of research that was conducted at Vanderbilt University. We licensed the technology a couple of years ago and continue to advance it and further our understanding of RNA in the context of human disease. At a foundational level, what we’ve developed is a process that can identify the presence or absence of disease by analyzing gene expression – which is a measurement of real-time activity in cells. By analyzing RNA, you can capture a snapshot of the information taking place molecularly inside cells. We’ve harnessed that information and analyzed it to provide new tools for doctors so, when used with other diagnostic methods, they can tell if a patient does or does not have a disease. I’m an immunologist by training, and one of the biggest clinical problems is autoimmune disease – when the very system that’s meant to keep you healthy actually turns on you and makes you sick. In many cases, we don’t know how these diseases arise, and a lot of them are difficult to diagnose. Misdiagnosis is very common, particularly early on.

So we set out to develop a new tool that utilizes RNA to be able to answer this detection question. We found that patients with an autoimmune disease, and even patients with other types of diseases like infections, have very different gene expression patterns that we could detect at the level of RNA. Of the autoimmune diseases that we examined, each individual disease had its own molecular portrait. With the invention of computer-science-based approaches, such as machine learning, that have advanced significantly over the past five or six years, we can now leverage these techniques to be able to analyze our data sets in ways that weren’t possible 10 years ago. What this allows us to do is to develop clinical assays that measure RNA and then analyze the resulting data using these cutting-edge techniques. This produces a result that is reported to the doctor indicating whether or not a patient’s molecular portrait or gene expression profile fits with a particular disease. We find that this approach can be used at the earliest onset of symptoms – so this molecular signature is present at the earliest stages of disease. If you look at a lot of the known autoimmune diseases, early diagnosis and treatment leads to the best outcomes. Early diagnosis is key.

Medgadget: You look at lncRNAs, which is different than looking at the mRNA transcriptome. Why is that?

Spurlock: Our original studies, performed more than 10 years ago, focused primarily on protein-coding genes or mRNAs. The dogma at one time was very linear: DNA makes RNA; RNA makes protein – so we thought most of the RNAs code for proteins. But with the completion of the Human Genome Project in the early 2000s and the follow-up ENCODE project, we now appreciate that the vast majority of the genome is transcribed. Of the active transcription, only a small sliver of the genes actively transcribed code for protein. So what does the remainder of this transcription do? Prior to 2010, a relatively new class of non-coding RNA molecules, called lncRNAs (long non-coding RNAs), gained significant traction in the literature. These lncRNAs are functionally different from short non-coding RNA (less than 100 base pairs). If you look at the patterns of lncRNA expression across cell types, they are differentially expressed in such a way that they are very indicative of cell identity. lncRNA expression pattern was very specific for a particular type of cell. The work that we did identified one of the first lncRNAs that was differentially expressed in rheumatoid arthritis and found that levels of this lncRNA responded to therapy in a cross-sectional study. That was one of the early links between lncRNAs and autoimmune disease. We followed this up further to look at certain subsets of immune cells in a paper published in Nature Communications in 2015, where we identified lncRNAs that were differentially expressed among T-helper cells – including Th1, Th2, and Th17 cells in humans. Given the cell-type-specific nature of lncRNAs that we found, we followed these studies by examining gen expression profiles in human disease by doing a simple comparison of mRNAs versus lncRNAs in patients. What we found was that in protein-coding genes, you struggle to see a 2-fold difference across case-control comparisons (i.e. healthy controls vs. multiple sclerosis patients). The lncRNAs are much more dynamic, often showing a 4-fold difference or greater. The ability to detect larger and very significant differences in certain patient populations allows for better applications of machine-learning methods so we can carve out specific algorithms and models to contrast disease vs. non-disease.

Medgadget: You mentioned that this is analogous to taking a snapshot look inside the cell. How do these lncRNA expressions change over the course of the diseases that you are interested in?

Spurlock: One of the things that we’re focused on immediately is the determination of the presence or absence of disease – being able to look inside a blood cell and ask if a patient has an expression profile consistent with multiple sclerosis or not. What we’re going to be doing in the future is taking that a step further and asking how these lncRNAs change as a consequence of time or therapy. That might allow us to determine, for instance in the case of multiple sclerosis, if a patient is entering a period of relapse. Perhaps one day we’ll develop a test that will give a doctor an early warning system to indicate that a patient is in relapse and therefore needs more aggressive therapy or monitoring. The same holds true for other autoimmune diseases such as Crohn’s disease, where you have flares that are associated with bowel damage. These could be avoided since clinical treatments are highly effective, and knowing when relapses or remissions are occurring adds to the tools available for the doctor’s clinical decision-making process.

Medgadget: As I understand it, in its current form, IsolateMS is able to indicate whether a disease exists, but not answer what stage of clinical progression it’s in. Is this correct?

Spurlock: In the case of MS, we took an approach of trying to identify MS vs. non-MS. The reason we decided to go with that approach stems from the floating nature of the clinical criteria for the stages of MS – the criteria for what constitutes relapsing, remitting, and primary vs. secondary progressive MS is still a moving target. We know that the patient has MS, but it’s been very difficult for the clinician to definitively say which stage it is. Our algorithms depend on good dataset inputs to train models that can detect whether a molecular profile is specific for different stages of the disease. Given the incomplete nature of the clinical criteria to make those determinations, we decided not to pursue that at this time with this assay. However, it is one of our ongoing R&D goals. We want to take that molecular profile and further interrogate it to define the clinical stage of disease.

Medgadget: How is MS typically diagnosed without IQuity’s IsolateMS system?

Spurlock: Ultimately this will be a complementary test in the clinical pathway. Historically, diagnosis for MS was based on clinical criteria alone, and then we progressed to other measurements such as testing spinal fluid or electrical activity in the brain. Diagnosis of MS was revolutionized in 2001 with the inclusion of MRI studies to be able to detect lesions that occur in the central nervous system. The clinical criteria for MRI currently require observation of changes in the size of a lesion over time – which can force a patient to wait for long periods before some physicians are comfortable labeling the diagnosis as clinically definite MS. Spinal fluid analysis has its own difficulties, such as patient discomfort and reduced accuracy compared to other methods. The physicians that we’ve talked to would like to alternatives to spinal fluid analysis and view our blood test as one such alternative. So we can potentially combine our test with MRI scans in order to have that additional confirmatory test for an MS diagnosis.

Medgadget: Is a blood sample necessary for this test or are other bodily fluids valid as well?

Spurlock: Yes, we need blood because we detect lncRNA from a whole-blood sample that’s then collected in a PAXgene® tube. We take a few teaspoons of blood from a patient’s arm and collect it into these tubes that immediately stabilize the RNA – allowing us to capture an immediate snapshot of the transcriptional activity occurring in a cell. This is in contrast to other methods that might use cell sorting or a similar process to isolate particular subsets. If a cell population is out of the body for any length of time, these transcriptional profiles can shift – so having the PAXgene® technology to immediately capture the transcriptional profiles of these cells helps us push pause on that process and is key for the assay’s success. These tubes were a joint venture between BD and Qiagen, and they’ve been well documented for their stable shelf life. We’ve also tested their stability during shipment over great distances, and they’re one reasons why we’ve been able to succeed in carving out this disease-related molecular signature.

Medgadget: Are you marketing this platform as a diagnostic or screening technology?

Spurlock: It’s a diagnostic. We don’t want to be labelled as a screen. This is also a provider-ordered, not direct-to-consumer, test. So doctors would have to have a reason in their medical judgment to order this test because they suspect MS or some other inflammatory neurologic condition and want to use this test to rule it in or out.

Medgadget: You’ve developed this around a centralized testing facility. Why did you choose that instead of developing a testing platform for hospitals and other labs?

Spurlock: Great question! We are initially going to go to market as a laboratory-developed test, which is regulated under CMS/CLIA (Clinical Laboratory Improvement Amendments). To qualify for that, the test has to be produced, sold and marketed by an individual lab. However, if you were to put this test in multiple labs across the country, it would require FDA approval. That may be something we pursue in the future, but we’re initially going to market as a laboratory-developed test to speed up the time required to introduce this new test to patients.

Medgadget: So by going this route, you were able to get the product to market faster without having to go through the expensive process of clinical trials?

Spurlock: Right, but you have to remember that immediately with the launch of this clinical assay, IQuity will be working with physicians to document the utility of our test in patient populations. We want to see how this test changes the physician decision process and how the patient diagnostic process is altered with the inclusion of this RNA-based assay.

Medgadget: How does this test compare to existing systems when it comes to cost?

Spurlock: If you look at the cost of MRIs and factor in high deductible plans – patients end up paying out of pocket for a number of these procedures because insurance companies are placing limitations on the number of MRI scans that are covered in a particular time period. Looking at the market, the price for a molecular-based test like ours can be $2,000-$5,000. We plan to offer assistance to patients so that the price could be as little as $1,250. It will not initially be covered by insurance companies, so we’ll be going to market with a patient-paid test.

Medgadget: Your company website mentions that you’re working on applying the same technology to irritable bowel syndrome and fibromyalgia. Could you touch on those applications and why you chose these diseases in particular?

Spurlock: That’s part of our expanding portfolio under our Isolate test panels. If a patient comes into the doctor’s office with gastrointestinal distress, it’s typically one of two broad classifications: irritable bowel syndrome (IBS) or inflammatory bowel disease (IBD). In the case of IBD, Crohn’s disease affects the entire GI tract, while colitis is confined to a very distinct portion of the tract. So being able to know, at the earliest onset of symptoms, what you’re faced with is critical. If a doctor suspects IBS and we detect a signal for IBD, we can get these patients to a gastroenterology clinic so they could be appropriately treated as early as possible. There was actually a study showing that a significant number of patients diagnosed with IBS were in fact Crohn’s patients and already had significant levels of bowel damage. Unfortunately, once the damage has occurred, it’s too late. So just like in MS, having a good yes or no assay for IBS, in contrast to these inflammatory processes like IBD, could be of enormous clinical benefit. In the case of MS, we’re not trying to replace the MRI; and in the case of GI diseases, we’re not expecting to eliminate scopes. What we are doing is allowing doctors to have an early test that would effectively triage that patient and increase the provider’s efficiency. So as a primary care doctor who runs this test, I would probably be able to manage IBS in my clinic. But if this is in fact a case of IBD, I need to refer this patient to the GI doctor for a scope appointment and potential initiation of therapy to stave off the bowel damage.

In the case of rheumatology, we’ve worked for a long time looking at different expression signatures that were present in commonly-seen diseases like rheumatoid arthritis or lupus. We were very successful there, but around the year 2009 we saw that the clinical decision-making process for fibromyalgia syndrome was starting to come into focus. Compared to other diseases, such as depression, fibromyalgia had a very distinct molecular portrait. These patients are primarily women that have been struggling to get a diagnosis – they’re in pain and it was something we felt we needed to take a look at. A rheumatologist has to exclude rheumatoid arthritis or lupus before they can give a positive diagnosis of fibromyalgia, so we’re hoping to provide that extra tool for the clinical decision-making process.

Medgadget: Any estimates on when those assays will be coming to market?

Spurlock: For the GI assay, we’re anticipating a summer release. In the case of fibromyalgia, we’re aiming for a fall release. This is all under our Isolate panel to rule in or rule out a disease, and it’ll be the first wave of these assays. Hopefully someday soon we’ll be able to do disease activity monitoring as well.

Medgadget: As an immunologist, an obvious interest is autoimmune diseases. But I’m wondering if IQuity’s future goals include other diseases and fields of interest?

Spurlock: If we look at some diseases like Alzheimer’s, we’re able to detect distinct profiles in those diseases as well. But we want to be very focused and direct in our approach. According to numbers published by the NIH, autoimmune diseases are right up there with heart disease, diabetes and cancer. If you think about how often we talk about autoimmune disease in the news, it’s nowhere near these other conditions. It’s a tremendously underserved community and we’re looking to change that.

Story Source: The above story is based on materials provided by MEDGADGET
Note: Materials may be edited for content and length

Go to Newer News Go to Older News