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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary 4 Neurological and Eye Diseases The search for biomarkers for neurological and eye diseases has been under way for years, and technological advances, especially in retinal imaging, are showing promise in areas of research that encompass several neurological diseases. Of the approximately 600 neurological disorders, there are only a handful of biomarkers available, making it unclear which are best suited for investment. A rational approach to biomarker development hinges on two key elements: better understanding of the etiology and pathogenesis of a given disorder, and the use of data and stored biological samples from ongoing and prior clinical trials. In Session IV, workshop participants discussed several areas of neurological medicine where a high-impact biomarker could emerge, including Parkinson’s disease, multiple sclerosis, stroke, spinal muscular atrophy, and retinal degeneration.
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary LESSONS FROM FAILED CLINICAL TRIALS Uric acid has become a leading candidate as a biomarker for tracing the progression of Parkinson’s disease, said Dr. Ira Shoulson, professor of neurology at the University of Rochester. Uric acid levels that are too high are responsible for gout, but higher uric acid levels at the middle ranges found in the Parkinson’s clinical trials turned out to reduce the risk for progression of Parkinson’s disease by approximately 25 percent, according to a published meta-analysis of observational studies, reported Shoulson (Weisskopf et al., 2007). The observational studies were spun off of three previous clinical trials of anti-Parkinson drugs. Not all the clinical trials turned out to be successful for their main purpose (i.e., finding a new treatment for Parkinson’s), but collection of blood and cerebrospinal fluid (CSF) uric acid during the trials turned out to be vital. Identification of uric acid as a putative biomarker came about fortuitously. It occurred during a meeting of investigators to determine why a clinical trial of an anti-Parkinsonian drug, sponsored by two pharmaceutical companies, had failed. One of the investigators ventured that patients with higher uric acid at baseline seemed to fare the best. Once Shoulson and the other investigators analyzed the data more closely, they reached the same conclusion. In this particular trial, they found that male patients with the highest levels of uric acid especially had reduced their risk of Parkinson’s progression by about 50 percent, according to Shoulson, who described the data presented at a recent Society for Neuroscience meeting (Schwarzschild et al., 2006). Furthermore, the results from the clinical trial suggested a possible mechanism for uric acid’s role. Uric acid is a strong antioxidant, and it is the product of the metabolism of purines. The link between higher levels of uric acid and reduction of Parkinson’s progression made mechanistic sense, they hypothesized, considering that oxidative mechanisms are implicated in the pathogenesis of Parkinson’s disease and other neurological disorders (Floyd, 1999). But what specific target was protected from oxidation by uric acid? The failed clinical trial provided a clue because it also had collected data on levels of the dopamine transporter in the striatum by using SPECT images of [123I] β-CIT uptake (the striatum’s loss of dopamine transmission is one of the central lesions in Parkinson’s disease). On subsequent analysis, investigators found that uric acid had a dose-dependent effect on the levels of dopamine transporter: patients with the lowest levels of uric acid had the highest loss of dopamine transporter over time,
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary whereas those with the highest levels of uric acid had the lowest loss of dopamine transporter over time. This dose response suggested at least one mechanism by which uric acid may exert its protective effects, according to Shoulson (Schwarzschild et al., 2006). The analysis of the uric acid effect from this trial spurred investigators to reexamine results from the previous clinical trial (DATATOP), which studied 800 patients and had also collected data on uric acid levels. Researchers were able to use epidemiological methods to investigate the association between uric acid and Parkinson’s disease progression and found that uric acid conferred dose-related beneficial effects: The higher the serum uric acid level, the lower the risk of developing Parkinson’s disease disability. The findings from the CSF analysis of uric acid in this study were even more robust that those with serum uric acid. The lesson from this experience with Parkinson’s disease, said Shoulson, was that clinical trials provided a treasure trove of data that could be reanalyzed once potential biomarkers were identified. He also pointed out that the reanalysis of the clinical trial data was not only supported by the National Institutes of Health, but was also supported by pharmaceutical companies. He expressed the hope that DNA collection from clinical trials might allow whole-genome scanning to search for genotype markers related to biomarkers of risk, disease progression, or response to treatment. BIOMARKERS OF MULTIPLE SCLEROSIS Several promising biomarkers are on the horizon for multiple sclerosis (MS), but all face significant, though not insurmountable, barriers to progress, asserted Dr. Gavin Giovannoni, professor of neurology at Queen Mary’s School of Medicine and Dentistry, London. His presentation covered two main topics: (1) the types of organizational reforms needed for the neuroscience field as a whole to promote development of surrogate markers of sufficient validity to warrant Food and Drug Administration (FDA) qualification and (2) the more specific topic of developing promising biomarkers for MS, particularly ones for predicting prognosis. The MS field faces one overarching hurdle spanning both topics: a flawed gold standard for assessing the disease’s clinical course. Without a responsive and well-validated clinical outcome measure as a gold standard, biomarker development is thwarted from the start. For years, the
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary gold standard for MS has been the Expanded Disability Status Scale (EDSS). Developed before the era of rigorous psychometric evaluation, this scale would never have passed muster by today’s standards. Recent research has exposed problems with the scale, including its inter- and intrarater reliability, ceiling and floor effects, nonlinearity, and large coefficient of variation (CV), which reduces statistical power to detect differences between study groups (Hobart, Freeman, and Thompson, 2000). The scale’s psychometric problems became most apparent, Giovannoni recounted, with the publication of a 1998 paper showing only a modest correlation between the EDSS and a candidate biomarker for earlier stages of relapsing-remitting MS (Lycke et al., 1998). The levels of the biomarker in the CSF were associated with clinical exacerbations and exacerbation frequency; they steadily declined after the onset of the previous clinical exacerbation, but were only moderately associated with the EDSS. MS does have other biomarkers that pertain to the early stages of disease, the relapsing-remitting stage. Relapse rate due to focal inflammatory disease activity correlates with the imaging biomarker of gadolinium-enhancing lesions on magnetic resonance imaging (MRI) (McFarland et al., 2002). But there are no well-validated biomarkers for the next stage—the secondary progressive phase—which typically occurs 5 to 15 years after first relapse. During this stage, patients become increasingly disabled without necessarily having superimposed relapses. A prognostic biomarker during this period is highly needed, said Giovannoni. A biomarker not only would predict prognosis, but also would enable researchers to have a gold standard for testing new treatments. One vitally needed treatment is a neuroprotective agent to modify the course of disease, considering that no treatment now serves this purpose. Generalized and regional brain and spinal cord atrophy measurements are currently being evaluated as potential primary outcome measures in exploratory neuroprotective trials. The lack of a good biomarker for the progressive stage of disease motivated Giovannoni’s laboratory to begin a decade-long search. In the process, he encountered major organizational and scientific impediments to biomarker development. One major conclusion he drew from the experience was that the problems transcend the MS field and extend across all brain disorders. Another conclusion was that the neuroscience field must approach biomarker development in as rigorous and scientific a manner as it does drug development.
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary Giovannoni laid out the scientific process he felt was needed for validation of a biomarker (Figure 4-1). In recognition of the necessity of biomarker development and validation, he said he turned to the cancer field, which, in his view, has become a model that neuroscience should emulate. The cancer field has set up a network in the United States and Europe, with one of its prime activities being to develop guidelines on how to design, conduct, and report biomarker studies (McShane et al., 2005). The guidelines are so important to the field that the same paper describing them was published simultaneously in seven of the top oncology journals. The oncology guidelines begin with the recognition that the guidelines given in the paper cover standardized reporting of materials and methods, including patient selection, specimen characteristics, assay methods, reporting of results, analysis and presentation, and discussion. With the cancer field as its model, Giovannoni and his European colleagues have created a “BioMS Consortium.” They plan to issue at least three consensus papers, the first of which covers biobanking (i.e., the FIGURE 4-1 Scientific process for biomarker validation. NOTE: Coefficient of variation (CV). SOURCE: Giovannoni, 2006.
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary collection, processing, storage, and databasing of samples). The second paper will issue guidelines on reporting biomarker studies, as adapted from the oncology network. Another major impediment to biomarker development is the failure of researchers to report negative results. If journals are reluctant to accept papers of this kind, it is incumbent upon the field to create a register of successful and failed biomarker studies so that other laboratories do not waste time and resources to repeat the analyses. Giovannoni emphasized that this is the foremost message of his presentation: to underscore the urgency of publishing negative results. He then turned to specific steps that industry can take to advance biomarker research. The most important yet thorny issue is the incorporation of potentially new biomarkers into clinical trials. These are potential biomarkers that are not accepted outcome measures but that may become useful in the future with further analysis. Citing experience from the cardiac field, Giovannoni pointed out that industry has no incentives to incorporate novel biomarkers because they may uncover useful surrogate biomarkers that give competitors an edge in future trials. Establishing a surrogate biomarker may reduce study duration and thus helps competitors gain quicker access to market. For this reason, industry will need incentives to incorporate novel biomarkers in clinical trials (Box 4-1). The most important advance will be to find a replacement for the EDSS for assessing clinical course of MS, asserted Giovannoni. Without a new assessment tool as a gold standard, none of the prospective biomarkers can be carefully evaluated. Giovannoni then turned to the specific biomarker his laboratory has been working on for the past 10 years: heavy chain neurofilaments as a prognostic biomarker for the later stage of MS, the stage when disease and disability are steadily progressive. Neurofilaments are intracellular proteins that form the internal cytoskeleton of the axon, maintaining its size, shape, and structure. Giovannoni’s laboratory has established that heavy chain neurofilaments are a bulk biomarker of axon damage. Whenever axons are injured or destroyed, they release neurofilaments into the extracellular fluid that can be measured in the CSF. Giovannoni and his colleagues have proposed that the levels of heavy chain neuro-
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary BOX 4-1 Organizational Steps to Advance Biomarker Research Steps for the neurology field Develop new gold standard for clinical course (EDSS is flawed). Develop large, organizational networks to facilitate science for biomarker development (e.g., European Biomarkers in MS, modeled on oncology networks). Standardize data collection and other scientific procedures needed for new biomarker development. Publish negative results through open-access publishing (e.g., Journal of Negative Results) and the creation of a biomarker study register, similar to clinical trial registers. Steps for industry Incorporate potential biomarkers into clinical trials. Miniaturize and multiplex assays using emerging technologies, particularly for use in animal models. Biomarkers that are well validated in established animal models of specific diseases are more likely to be incorporated into clinical trials. Develop multiplex assays to minimize the volume of fluid required for performing assays. Develop real-time or rapid assays, which are particularly relevant in the neuro intensive care setting to allow biomarkers to inform clinical decision making in individual patients (e.g., head injury and stroke). filaments might be useful surrogate markers of disability and prognosis (Petzold et al., 2002; Petzold, 2005).To determine the utility of the biomarker, his laboratory followed patients prospectively for 3 years. They found that a higher proportion of patients with progressive disease displayed higher levels of heavy chain neurofilaments over time than did those with relapsing-remitting disease or controls. Higher levels in CSF were correlated with three different disability scales (Petzold, 2005). The study concluded that cumulative axonal losses, as reflected by increased levels of heavy chain neurofilaments, are responsible for sustained disability in MS and convey a poor prognosis. This putative biomarker for poor prognosis may make it feasible to enrich studies with subjects more likely to progress and, therefore, improve the power of studies testing disease-modifying therapies. The high-neurofilament group of patients is likely to reveal a protective effect, if there is one, with administration of
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary a disease-modifying treatment. In fact, Giovannoni reported his participation in an exploratory study of the anticonvulsant lamotrigine—a potential disease-modifying therapy for progressive MS—to test this hypothesis. Heavy chain neurofilaments are not the only biomarkers under consideration for MS. Other potential biomarkers are glial fibrillary acid protein and other markers of astrocytic and microglial activation that represent cellular response to any central nervous system (CNS) injury or challenge. Others include the neural cell adhesion molecule, which is thought to be a marker of axonal plasticity and synaptogenesis. A very promising marker that has already been included in the design of upcoming clinical trials due to its potential in cross-sectional studies is optical coherence tomography (Frohman et al., 2006). It is a noninvasive ultrasound imaging examination of the retina that is capable of measuring the thickness of the nerve fiber layer of the retina. Retinal nerve fibers are an accessible component of the CNS and are frequently targets of MS autoimmune attack. The loss of retinal axons indicates disease progression, albeit limited to the anterior visual pathway. BIOMARKERS OF STROKE A biomarker derived from MRI shows promising, near-term impact for acute ischemic stroke, said Dr. Steven Warach, chief of the Section on Stroke Diagnostics and Therapeutics at the National Institute of Neurological Disorders and Stroke (NINDS). His presentation focused on the value and versatility of a single MRI-based biomarker. The single biomarker has several applications to stroke clinical trials: patient selection, dose finding, and evidence of drug efficacy. The current lack of valid biomarkers for acute stroke trials is largely responsible, in his view, for the failure over the past 2 decades of most drugs tested in acute stroke clinical trials. Rarely have trials required an objective confirmation of the presence of biological target for patient selection, and even less frequently have they required evidence of a drug’s target biological activity to move a drug from Phase II to Phase III. He characterizes this enormous obstacle to progress as the “disconnect between laboratory successes and larger clinical trials” and argues that it must be tackled head-on by development of better biomarkers. In animal models, lesion volume reduction with treatment is both necessary and sufficient evi-
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary dence of treatment efficacy and is required to move a treatment from the laboratory to clinical trials. The only effective therapy for acute ischemic stroke is the thrombolytic agent tissue plasminogen activator (tPA), which was introduced in 1996 (NINDS rt-PA Stroke Study Group, 1995). But only about 2 percent of eligible patients actually receive the drug, mainly because of the tight time window of only 3 hours in which the drug must be given after a stroke. Another related reason is the difficulty of arriving at the stroke diagnosis, which must be made on an emergency basis. Concern among emergency room physicians about the accuracy of making a positive diagnosis of ischemic stroke by clinical exam on the one hand and excluding a diagnosis of brain hemorrhage by computed tomography (CT) scan on the other have further limited the utilization of tPA (American Academy of Emergency Medicine, 2007). The growing consensus regarding the value of MRI markers has been accompanied by growing recognition of the importance of data sharing, particularly from Phase II trials. But the efforts are still inchoate, said Warach. He wishes to launch more organized data sharing across industry and academic trials, as well as broader acceptance of MRI over CT to diagnose stroke in the emergency room. He and his collaborators established that MRI is better than CT for detection of acute ischemic stroke, although the two are of equal benefit for detection of acute intracranial hemorrhage (for which tPA is contraindicated) (Chalela et al., 2007). Current and previous clinical trial data are still valuable for pooling because new ways to analyze MRI results have been developed and thus can be applied to the raw data. The key to data sharing is to standardize procedures for acquisition and processing of MRI data and to standardize and fully validate certain parameters for selection of patients and outcomes. The foremost parameter of interest, according to Warach, is the existence of tissue that is not already infarcted but is at risk for infarction as the lesion evolves. That at-risk tissue is the so-called ischemic penumbra. It is a ring of endangered tissue outside the immediate focal ischemia. The focal ischemia is a dynamic lesion—with time, the focal lesion may expand into the penumbra. But the penumbral tissue is potentially amenable to salvage by restoring blood flow (Kidwell et al., 2003). Natural history studies reveal the dynamic nature of the lesion: There is typically a one- to twofold increase in the volume size of the infarct from baseline to 3 months. Early and accurate identification of potentially salvageable tissue (i.e., the penumbra) is key, for it may enable selection of the best
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary candidate patients for early stroke therapies and also may minimize complications. The presence of penumbral tissue in greater volume than that of ischemic tissue renders a patient more amenable to treatment. There is consensus in the field that relative lesion volume reduction within the penumbra holds the greatest promise as a biomarker to measure efficacy of a drug, according to Warach. MRI is used to measure the biomarker by revealing the mismatch between diffusion and perfusion. The diffusion-weighted imaging captures the core lesion of the stroke, which will infarct without adequate reperfusion and will enlarge within the penumbra, which is measured by the perfusion-weighted imaging. The value of MRI biomarkers is already being tested in clinical trials. In these trials a strong relationship has been observed between clinical outcomes (to 3 months post-stroke) and a change in lesion volume from acute to chronic time points. Patients who achieved good clinical outcomes had smaller increases in lesion volumes than patients with poor outcomes. Having a mismatch on MRI where perfusion is greater than diffusion has been incorporated in two ways in clinical trials of another thrombolytic drug, desmoteplase, as a selection criterion and as a baseline measure of ischemic pathology against which to assess drug effect. It was an eligibility criterion for the trial, along with clinical criteria. MRI reperfusion 4 to 8 hours after treatment and good clinical outcome at 90 days were used as the efficacy outcome measures to select the dose that was taken forward in subsequent trials (Furlan et al., 2006). To ensure high impact of this MRI biomarker, there is a need to pool clinical trial and academic observational studies into some repository and to reach consensus on how the data should be acquired and processed. There is also a need, said Warach, to refine our definition of the ideal “penumbral” patient for clinical trials, as well as to refine definitions for outcome and validation. The pharmaceutical industry has embraced this approach, and there are several ongoing international collaborations, but the effort needs to be greatly expanded to cover greater academic and industry participation, considering that there have been about 20 completed or ongoing acute stroke trials utilizing MRI. A major impetus for pooling data came from the stunning failure of AstraZenica’s NXY059, it followed all conventional wisdom for successful development of neuroprotective stroke therapies. The drug’s failure has led even biomarker skeptics to the view that a measure of biological activity should be a necessary step in stroke drug development. Finally, the repository might also collect DNA samples from patients to determine if there are any genetic contributions predisposing to stroke recovery. As the effort is launched,
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary the MRI biomarker must be validated against a clinically effective therapy (such as tPA), and it must be qualified by the FDA before it can become a surrogate marker. BIOMARKERS FOR SPINAL MUSCULAR ATROPHY Spinal muscular atrophy (SMA) is a devastating motor neuron disorder affecting infants and young children. It is second to cystic fibrosis as the most common fatal genetic disorder in children. Approximately 1 in 35 people are carriers for this autosomal recessive condition. The 50,000 infants or children with the condition either fail to develop normally or progressively lose the ability to stand, sit, and eventually move. About 50 percent of affected children die before the age of 2. Despite the tragic nature of the disorder, there is much hope for treatment or cure, said Dr. Meg Winberg, director of research at the Spinal Muscular Atrophy Foundation. Her presentation touched upon many of the remarkable advances that have occurred in recent years, all of which have created a climate of opportunity for biomarker development and the prospect of well-designed clinical trials. Progress in understanding the disorder has reached the point that NINDS has named SMA as a leading disorder for drug development. Several drugs are already being tested in investigator-initiated clinical trials supported by NINDS, although some are open-label and thus potentially vulnerable to what has been found in controlled trials: a large placebo effect. While large pharmaceutical companies are thus far noncommittal with respect to SMA, Winberg stated that her organization foresees, with further progress in biomarker development, a sizable market—$500 million to $1 billion in annual revenues—that may be attractive to biotechnology firms (Box 4-2) (Spinal Muscular Atrophy Foundation, March 2007). SMA is characterized as a single-gene disorder; the defective gene responsible for SMA was identified in 1995 (Lefebvre et al., 1995). In infants and children with SMA, the normal gene—Survival Motor Neuron 1 (SMN1)—is deleted, leaving them dependent on the activity of a closely related but defective backup gene, SMN2. The number of copies of SMN2 correlates with disease severity, said Winberg. One copy of the mutated gene is associated with the most severe form of SMA, known as type I, in which children never sit independently. Children with SMA
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary BOX 4-2 Why Spinal Muscular Atrophy Is Ripe for Biomarker Development Severe, often fatal, congenital neurological disease. Disease gene identified. Several treatments under investigation; efforts to validate SMN as a biomarker are in progress. One in 35 people are carriers. As common as cystic fibrosis and sickle cell anemia. Sizable market anticipated ($500 million to $1 billion annually). SOURCE: Winberg, 2007. type II, who have more copies of the mutated gene, are capable of sitting but generally do not achieve the ability to stand and walk independently. Children with SMA type III, who usually have the most copies of the mutated gene, are capable of standing and walking independently at some point but often lose this ability as the disease progresses, noted Winberg. The gene copy number effect also applies to animal models of transgenic mice lacking endogenous SMN who are given increasing SMN2 gene copy numbers (Monani et al., 2000). The relationship between copy number and severity of disorder has led to the hypothesis that drugs that increase the expression of full-length SMN would be expected to improve motor performance and muscle strength. Compared with the normal SMN1 gene, the defect in SMN2 is a single point mutation that results in a splicing defect. The end product is a truncated SMN protein (Monani, 2005). The functions of the normal, full-length SMN protein are still actively being studied, but recent research points to its role in assembly of small nuclear ribonucleoprotein particles (Wan et al., 2005). SMN protein insufficiency also affects other aspects of RNA metabolism and axonal growth, especially of motor neurons. Given the goal of increasing SMN expression, investigators have focused on SMN transcript and protein levels as biomarkers. Methods for SMN detection have been developed, but they have limitations (Sumner et al., 2006). In one study, SMN mRNA was assayed by quantitative reverse transcription polymerase chain reaction, and SMN protein was assayed by a cell immunoassay. Although both were measured with high reliability and temporal stability, their levels in the blood are only correlated with clinical severity in type I patients (Sumner et al., 2006). The
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary levels were not correlated with clinical severity of type II and type III patients. Still, if they respond to drug treatment, these biomarkers may prove useful in animal models and human clinical trials despite their limitations, said Winberg. To facilitate biomarker development, Winberg first recommended a more practical, sensitive method for assaying SMN protein. Current approaches such as quantitative western blotting, cell immunoassay, or ELISA all require significant blood volumes due to the low level of SMN protein expression. Drawing a smaller volume of blood is more practical and ethically acceptable for infants and children. Her second recommendation is to understand more about the natural history of SMN. Little is known, for example, about the developmental profile of SMN transcript and protein levels during the prenatal, perinatal, and postnatal periods. The SMN protein may play a more critical role during certain periods of development, noted Winberg. In addition, little is known about blood levels of transcript or protein in relation to levels found in the spinal cord and other tissues, either cross-sectionally or longitudinally. Studies of this kind will require recruitment of additional patients, investigators, and sites. Such studies may uncover a surrogate marker that will shorten clinical trial duration, which now requires 6 to 18 months. These realistic goals for biomarker development should attract greater commercial interest in SMA. BIOMARKERS FOR NEURODEGENERATIVE DISEASES OF THE RETINA Neurodegenerative diseases of the retina are exceedingly common in the general population, particularly among older people. Glaucoma, diabetic retinopathy, retinal dystrophies, and age-related macular degeneration collectively affect more than 15 million Americans, reported Dr. Paul Sieving, director of the National Eye Institute. Furthermore, their incidence is increasing as the U.S. population ages. Each of these disorders targets different cell layers of the retina and carries a great human toll, including blindness (Figure 4-2). Sieving’s presentation summarized the extensive advances that have been made in identifying biomarkers as well as mapping their genes. Just as vital, he reported, is compelling new evidence of the retina’s value as a window for identifying biomarkers for other neurodegenerative
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary FIGURE 4-2 Retinal neurodegenerative disease—clinical targets. NOTE: Numbers indicate number of affected Americans. Age-related macular degeneration (AMD); nerve fiber layer (NFL); retinal ganglion cell (RGC); retinal pigment epithelial (RPE). SOURCE: Sieving, 2007. diseases such as MS. Because of its accessibility, the retina may hold enormous promise for finding biomarkers of other neurodegenerative diseases, for which tissue accessibility is a formidable obstacle. The retina’s value depends on whether the potential biomarkers are expressed there and whether the other disorder has functional impact on vision. Vision researchers have found a panoply of biomarkers for each of the retinal diseases. One familiar example is high intraocular pressure as a biomarker for glaucoma. High intraocular pressure leads to the demise of retinal ganglion cells, beginning with degeneration of their axons, said Sieving. Other markers, some of which have been available for 150 years, screen for disorders of photoreceptors found on retinal ganglion cells. More broadly, Sieving pointed out that the vision field has been remarkably successful for the past 20 years in identifying mutated genes associated with retinal neurodegenerative disorders. For example, nearly 200 genes have been found to be associated with the demise of the rods and cones (Figure 4-3). Yet the success of the field has had a paradoxical
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary FIGURE 4-3 Retinal neurodegenerative disease genes: Disease pathophysiology correlates to developing new risk biomarkers. SOURCE: Daiger, 2007. effect: it has uncovered too many therapeutic targets but not enough understanding of the contribution of each one to the pathophysiology of the disorders. Selecting the best therapeutic targets from a host of potential targets depends heavily on their playing a prominent role in pathophysiology, according to Sieving. One disorder, age-related macular degeneration, appears to stand as a counterexample to this problem. Researchers have found that a few inflammatory biomarkers account for 74 percent of risk, said Sieving. The biomarkers are polymorphisms in several immune complement molecules, such as complement factor H, complement component 2, and complement factor B (Edwards et al., 2005; Haines et al., 2005; Klein et al., 2005; Moshfeghi and Blumenkranz, 2007). While investigators still do not yet know the full relationship of these complement molecules to pathophysiology, their epidemiological contribution to disease risk helps to identify them as important targets. These discoveries are not only of interest to the vision field, but may also have applications elsewhere: some of the complement proteins associated with macular degeneration are similar to those associated with other neurodegenerative disorders. The value of this overlap becomes even more evident with the new imaging technologies developed for retinal imaging.
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Neuroscience Biomarkers and Biosignatures: Converging Technologies, Emerging Partnerships, Workshop Summary PROMISING TOOLS FOR USE IN OTHER APPLICATIONS Retinal imaging has an illustrious history tracing back to 1850, when Hermann von Helmholtz invented the ophthalmoscope. Several of the newest imaging technologies may hold value to many neurodegenerative disorders besides those affecting the retina. The first is a structural technology known as optical coherence tomography. It allows each cellular layer of the retina to be visualized with 3μ axial resolution and image reconstruction. It carries applications for ocular diagnostics and therapeutic tracking, particularly for retinal ganglion cell axon loss in glaucoma and congenital X-linked retinoschisis (Apushkin et al., 2005). It also holds utility for MS by virtue of its ability to image loss of fibers in the retinal nerve fiber layer, which is a common manifestation of MS (Fisher et al., 2006). Another new structural technology is adaptive optics. Its resolution is so great that it allows individual photoreceptors to be imaged. Pioneered by David Williams and colleagues at the University of Rochester, the technology has confirmed that human color vision depends on three color receptors—red, green, and blue cones—as first postulated in the early 1800s by Thomas Young. A final tool is the development of metabolic biomarkers, which potentially could be localized together with structural imaging (Gu et al., 2003). Combination techniques would allow dynamic tracking of functional disruptions and pathophysiology with high resolution and in real time, said Sieving. He described an animal model in which monkeys’ retinal ganglion cells are labeled and then, after their retrograde transport, are individually visualized in the retina. He stressed the potential for overlap with other neurodegenerative diseases, pointing out, for example, that elevated level of homocysteine is a metabolic biomarker not only for age-related macular degeneration but also for cardiac disease. He ended his presentation with the message that the science is poised to take advantage of ultra-high-resolution imaging tools to develop dynamic functional markers for studying neurodegenerative retinal diseases as well as other neurodegenerative disease. The insights gained can be applied to understanding pathophysiology as well as providing outcome measures for clinical trials.