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Neurological and psychiatric conditions, in particular, need good biomarkers.....

http://www.nyas.org/ebriefreps/splash.asp?intEbriefID=771&PartnerCD=AlzForum&TrackCD=eB771

Reported by Kathleen McGowan | posted March 24, 2009

Until relatively recently, biomarkers were not a popular area of investigation. By the 1980s, many believed that by individualizing treatment, subdividing disease, and explicating pathophysiology, genetics would make biomarkers unnecessary. The essential role of biomarkers as tools to understanding how drugs work and disease progresses was eclipsed by the rising star of the human genome.

Yet the need for biomarkers—simple, accessible indices of complex biological phenomena—only grew. Now their absence is crippling pharmaceutical research; drug development pipelines are drying up. Meanwhile, record numbers of experimental compounds are failing in increasingly expensive late-stage clinical trials.

Neurological and psychiatric conditions, in particular, need good biomarkers. The inaccessibility of the brain, the lack of knowledge about pathophysiology, and the chronic degenerative course of many of these diseases make it difficult to judge who has the disease, how best to treat, and whether or not experimental treatments are successful. The need for clinical biomarkers may soon become acute: the most promising candidate treatments for conditions such as Alzheimer's disease (AD) are likely to be most effective for patients in the earliest stages of disease—possibly even before the onset of symptoms.

How to move forward collectively with identifying and validating such brain-based biomarkers was the focus of Biomarkers in Brain Disease, a conference sponsored by the New York Academy of Sciences and the Global Medical Excellence Cluster of South East England and held from January 26–28, 2009, at Oxford University. In general, the meeting focused on biomarkers as used in drug development and clinical trials.

In the last few decades, researchers have proposed increasingly sophisticated hypotheses of disease for conditions ranging from depression to Parkinson's, but their ability to test them has not kept up, pointed out keynote speaker William Potter of Merck Research Laboratories. Drug development for depression is a good example: Of the more than 75 potential targets in depression, the mechanisms by which they might affect the condition have been established for only a handful. "That's the reality, and that's a field that we thought was way ahead," he cautioned.

Biomarkers are shining a light on the brain processes involved in these diseases.
But there are signs of progress. Disease-related profiles in cerebrospinal fluid (CSF) have been established for Alzheimer's disease, and much attention is focused on doing the same in plasma. Imaging techniques such as positron emission tomography (PET), magnetic resonance imaging (MRI), and, more recently, diffusion tensor imaging (DTI) are becoming useful adjuncts for the diagnosis and monitoring of neurodegenerative disease and for the testing of antidepressant candidate drugs. Proteomics and metabolomics will no doubt identify characteristic biochemical signatures of physiological processes. None of these techniques are yet ready to answer the biggest questions, said Potter, but we're getting closer. "It's not too strong to say that biomarkers are shining a light on the brain processes involved in these diseases," he said. After years of neglect, we can now look forward to an era in which the biomarker finally comes of age.

Biomarkers: a typology

Most broadly, a biomarker is a quantifiable measure correlated with or predictive of a physiological process involved in health or disease. "Biomarker" means different things in different contexts, so one of the most important challenges in biomarker development is conceptual rather than scientific: researchers must be absolutely clear about what they're looking for and what they plan to do with the information.

Even at this conference, speakers did not agree upon one typology to categorize biomarkers, but rather proposed different categories based on different criteria. Potter distinguished two types of biomarkers. For neurologists, a biomarker is a quantifiable difference in brain tissue or CSF associated with the course or severity of symptoms, he said. But for a drug developer, a biomarker could be any measure of drug action that is proximal to its clinical effect.

Cristina Sampaio of the University of Lisbon proposed three categories:

Disease-associated biomarkers of risk, diagnosis, and progression
drug-related biomarkers that relate to pharmacogenomics and drug response
patient-associated biomarkers that reflect compliance or relate to adverse events
Focusing solely on biomarkers as used in drug development, Orest Hurko of Wyeth Research identified four subtypes:

Biomarkers reflecting dosing and receptor occupancy
those identifying patients most likely to suffer toxic effects from the drug
those predicting which patients will have the most robust response
those offering an early indicator of efficacy
"It is meaningless to speak of a biomarker unless you specify which of these four questions it is to address," said Hurko.

Biomarker development should be considered an "extremely high-risk undertaking."
The time and expense of identifying and validating a biomarker can be just as burdensome as developing a drug, so biomarker development should be considered an "extremely high-risk undertaking," cautioned Hurko. And the Holy Grail—a biomarker that can serve as a surrogate measure of disease for regulatory purposes—is vanishingly rare. A few have held up in other fields of medicine, such as cholesterol levels for risk of heart disease or T-cell count for AIDS progression. But so far, none stand alone in neurological or psychiatric disease.

Expensive as they are, however, biomarkers can be useful in clinical trials by improving power, rationalizing dosing, and saving money by preventing even costlier research. Candidate drugs for CNS diseases have one of the highest attrition rates in the pharmaceutical industry. "We fail late, which is not a good place to fail," said Holly Soares of Pfizer. A biomarker can tell you when it's time to call it quits. A biomarker can also convert a failure into a learning opportunity, by testing the hypothesis that engaging the new target has an effect. Without being able to monitor what's going on inside the brain, drug development is just a shot in the dark.

As Carol Brayne of the University of Cambridge pointed out, if biomarkers can be developed for risk, diagnosis, and progression, it is also important to keep a public health perspective when deciding whether they should be used in clinical practice. In the case of biomarkers for predicting risk, for example, there is the potential for misdiagnosis and expensive overtreatment of disease, particularly for brain diseases like dementia, which is actually a spectrum of disorders. She advocated for a system that would operate in parallel with biomarker development to assess the public health, ethical, social, and legal implications of potential biomarker-based interventions.

Alzheimer's: The state of the art

Biomarkers are sorely needed for Alzheimer's disease: As many as 150 targets have been suggested to be relevant to AD, Potter pointed out, but few have been validated; that is, proven to influence the pathophysiology of the disease. In terms of treatment, because the disease is slow to progress, assessing whether or not a therapy is effective is a challenge. Clinical trials for potential AD drugs will by necessity be very large and very long, and a biomarker that reflects pathophysiology could give an early signal of success or failure.

The best AD treatments may be neuroprotective agents that must be given before clinical symptoms become evident; thus a biomarker would be required to identify who is likely to benefit. Some of the most promising potential treatments are disease-modifying agents such as β-secretase inhibitors, anti-inflammatories, or immunotherapy, but a disease-modifying effect can't be proven on clinical outcomes alone; physiological changes in the brain must be documented.

A few good AD biomarkers have been established, although none have yet been fully validated. [See Soares slide 13.] Three peptides, amyloid-beta 42 (Aβ-42), total tau, and phosphorylated tau (phosphotau), have been most thoroughly studied, with the confirmed finding that tau levels increase and Aβ-42 levels decrease in the CSF of people with AD. By monitoring all three, Henrik Zetterberg's group at the Sahlgrenska Academy at the University of Gothenburg can predict conversion to AD in a heterogeneous population. However, peptide levels have no relationship to individual disease state and cannot be used to track progression. Zetterberg mentioned another promising approach: analyzing the pattern of Aβ fragments in CSF with mass spectrometry. He noted that Aβ-42 levels in plasma have no relationship to those in CSF and cannot be used to diagnose disease. [See Zetterberg slide 25.]

Some types of neuroimaging are coming into their own, such as volumetric structural images that capture hippocampal atrophy, which can diagnose AD at specificity and sensitivity above 90%. Pittsburgh-B is a relatively new ligand that can be paired with PET to image overall amyloid in the brain. It has low specificity: many people have a significant amyloid load and normal cognition.

Alzheimer's: Where we must go

So far, the many efforts to identify plasma biomarkers have not succeeded, but there is good evidence that they ultimately will be found, said Simon Lovestone of King's College London. Lovestone has used 2-D gel electrophoresis and mass spectrometry-based proteomics to identify two plasma-based candidates, complement factor H and α-2 macroglobulin, that correlate with disease activity in the brain. An "in silico" search of existing literature also pointed to C-reactive protein as a potential predictor of disease progression.

Multiple biomarkers across several modalities will ultimately be necessary.
Holly Soares described Pfizer's project with the biomarker-testing firm Rules-Based Medicine to develop a panel of up to 151 analytes in blood that could identify presymptomatic patients. She and Lovestone were two of the many speakers who emphasized that multiple biomarkers across several modalities will ultimately be necessary. "I don't think we're in the game of any one protein or gene or anything else being the answer," Lovestone said.

Imaging, although expensive, could reduce the number of people needed for a successful clinical trial, argued Nick Fox of University College London. In one recent study, an estimated 320 human volunteers were needed to show a 50% effect on progression in one year, using a standard behavioral measure. With MRI structural imaging of hippocampal volume, the number could have been as low as 21. Structural imaging can also be used to monitor disease onset or progression in individual patients: Fox's group has pioneered a technique that allows sequential structural images of the brain in people at risk of AD to be precisely compared. Other imaging technologies that are more preliminary include diffusion tensor imaging, which visualizes white matter, functional MRI, which might profitably be combined with vMRI, and FDG-PET, which can distinguish between AD and other dementias by pinpointing activity changes.


Genetic biomarkers may be most practical in AD to identify who is at high risk for the disease or to predict prognosis, suggested Richard Mayeux of Columbia University. The unique power of genetic biomarkers is that they are present at birth, long before disease onset. His group has focused on variants of SORL1 in a population in the Dominican Republic; other risk variants include the well-known ApoE4 allele, and possibly LRP6 and GAB2.

Cognitive biomarkers may not be as flashy, but refinements in these could yield cheap and widely applicable tools. Barbara Sahakian of the University of Cambridge described success with CANTAB, a cognitive battery that probes the function of the hippocampus, a brain region experiencing early decline in AD. This test, particularly when paired with tests of semantic memory, can distinguish elderly adults with AD from those with other cognitive problems and predict decline in a nonclinical sample of healthy older adults.

Other diseases: lessons learned

Alzheimer's is the 800-pound gorilla of neurodegenerative disease, but biomarkers are being pursued for many other brain diseases. Schizophrenia offers a very different challenge: Effective therapies are available for this disease, but the major difficulty is in timely diagnosis. The hope is that because the disorder appears to have a long prodromal phase, early intervention could alleviate or even prevent psychotic episodes.

Beginning with postmortem brain samples and moving to CSF and serum, Sabine Bahn at the University of Cambridge has found evidence of dysregulation in the periphery as well—which hints of an accessible schizophrenia biomarker. Working with Rules-Based Medicine, her group has identified a panel of 54 biomarkers that predicts schizophrenia with more than 90% specificity and sensitivity, and differentiates from depression, MS, and bipolar disorder.

Making the argument for systems thinking and the power of metabolomics, Jeremy Nicholson of Imperial College London presented provocative data linking autism to variation in gut enzymes and gut microbial flora. Metabolomics can explicate disease even where gene-association studies fail, he argued, by identifying biomarker clusters that reflect both environmental and genetic variation. At the individual level, metabolomic profiling can predict therapeutic outcomes. At the population level, the approach can be used for biomarker discovery to generate hypotheses that are mechanism-based and physiologically testable. The 1.5 kg of gut bacteria make a highly significant contribution to human physiology, Nicholson pointed out: collectively, the human microbiome may have 20 times as many druggable targets as does the human genome.

In Parkinson's, one of the simplest biomarkers is measuring a patient's ability to tap his or her hand.
In Huntington's disease, the D-2 dopamine receptor antagonist raclopride can be used as a ligand in combination with PET imaging to visualize the loss of brain tissue, a powerful but expensive technique. One of the simplest biomarkers turns out to be surprisingly effective, Roger Barker of the University of Cambridge explained: measuring the patient's ability to tap his or her hand, which deteriorates as the disease progresses. Barker also described a slightly more sophisticated version of this movement-measuring technique: a "saccadometer" built of head-mounted lasers to track eye movements. The patient's ability to follow a moving laser light is a sensitive and accurate index of disease progression. For Huntington's disease, an autosomal-dominant genetic disorder with highly variable disease onset, the central questions are whether a patient is beginning to suffer symptoms, and whether treatment is working. A major European study, Track-HD, is now evaluating biomarkers in a large population of pre-manifest carriers.

In multiple sclerosis, a demyelinating disorder, visualization of brain lesions via MRI is now accepted as part of the clinical criteria for diagnosis by the European drug-regulatory agency. Gavin Giovannoni showed a striking example of the neurological damage that occurs in MS patients, highlighting the need for early diagnosis and treatment. [See Giovannoni slide 13.] MRI data helped get Avonex approved for patients who had had a single demyelinating episode and were at a very high risk of developing definitive MS, "the only real approval based on biomarkers" so far in neurological disease, said Cristina Sampaio.

In MS, autoimmune antibodies attack axons and demyelinate them, but the hope is that sodium-channel blockers and anti-inflammatory agents such as lamotrigine or riluzole may protect axons from death. Clinical trials suggest that if used early on, treatments such as alemtuzumab (CAMPATH), a monoclonal antibody approved for B-cell chronic lymphocytic leukemia, may prevent relapses and disability over the long term. These drugs are promising, but because they are neuroprotective agents, studies are difficult to power. Giovannoni described using heavy-chain neurofilament (NF), a nonspecific marker of axonal damage, as a biomarker. In the CSF, baseline levels of hypophosphorylated neurofilament predict disability in three years' time. "We think this is a prognostic marker for disease progression, or degree of damage due to MS attack," he said. NF could "enrich" clinical trials by identifying the patients who are most likely to benefit.

A collective future

Relying on surrogate biomarker is risky, cautioned Sampaio, telling the story of glycemia in diabetes: For a long time, the FDA accepted glycemic control as a valid surrogate biomarker of disease improvement. In 2007, rosiglitazone, which reduces blood glucose, was shown to increase raise cardiac risk. Some diabetes researchers have suggested that it should be abandoned as a primary endpoint surrogate; at the end of 2008, the FDA concluded that while this biomarker is still an "acceptable" surrogate for new drug approval, developers must now also prove that the candidate drug does not raise cardiovascular risk, a substantial additional burden.

Even validation of "non-surrogate" or "presurrogate" biomarkers will require unprecedented collaboration, cooperation, and standardization, because the process will likely demand large studies that can prove a putative biomarker is robust and reliable among a heterogeneous population. Many talks focused on how best to carry that out. Issues that seem trivial, such as which samples to collect, what readouts to measure, and how these should be curated and documented, are in fact major hurdles to overcome. "Something as seemingly innocuous as file formats can have a profound impact on how effectively we share things," said Arthur Toga of the University of California, Los Angeles School of Medicine.

Validating biomarker will require unprecedented collaboration and standardization.
Successful large-scale collaborations will likely require public-private partnerships, free data sharing, and extensive involvement of regulatory agencies. One such model is the Alzheimer's Disease Neuroimaging Initiative, a $60 million project funded by the National Institute on Aging, private foundations, and the pharmaceutical industry and led by Michael Weiner at University of California, San Francisco. European and Japanese projects have been incorporated into this study, which now includes 25 centers and more than 800 volunteers, and all the data is freely available. "This is an example of how a small amount of money can make a difference, expand collaboration and open up dialog," said Maria Carrillo of the Alzheimer's Association USA, which has taken on the job of maintaining international information flow.

AddNeuroMed, a cross-European effort that links clinical and preclinical research, is another such example of collaboration. Here, the effort is focused on identifying a key target of progression that can substitute for clinical measures in trials of disease-modifying agents. Richard Mayeux also described his data-sharing successes with the NIA-LOAD study, which has made available data from 3698 people either with AD or in an AD family. "My personal experience is that making data and samples available to everyone from the beginning actually works," he said. "You find you have more collaborators than you would have dreamed of."

Despite the obvious challenges, Alzheimer's disease may present a unique opportunity for massive international collaboration in biomarker development to succeed. All the ingredients are there: A disease with a major impact, plenty of funding, a strong public mandate for new treatments, and hundreds of labs around the world focused on the problem. These collaborations could set the pace for biomarker development in other diseases.

Bruno Vellas, head of the European Task Force on Disease-Modifying Alzheimer's Trials reminded the audience of the critical need for better research and clinical tools as he reviewed a number of failed clinical trials for drugs to treat Alzheimer's disease. In the hope of improving future outcomes, the task force has focused its third meeting on the use of biomarkers.

Kathleen McGowan is a freelance magazine writer specializing in science and medicine.