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Archives for May 2013

Genomind Releases Statement Supporting NIMH Announcement to Move Away from DSM Categories

Genomind, a personalized medicine company, has released a statement in response to the National Institute of Mental Health’s (NIMH) announcement by Director Dr. Thomas Insel that the organization will be re-orienting its research away from DSM categories, supporting the move and its potential to influence improved treatment of patients with mental disorders.

DSM (Diagnostic and Statistical Manual of Mental Disorders) is a psychiatric diagnostics system based upon patient-reported symptoms that are used to define succinct syndromes and make medication choices. While the system has been in place for decades, it has not taken into consideration patient etiology or pathophysiology.

The remedy proposed by NIMH is the Research Domain Criteria (RDoC) Project, which would alter procedures to include genetics, imaging, cognitive science, and other specific endophenotypes which reflect specific changes in the brain associated with psychiatric conditions, creating a fuller understanding of both a patient’s disorder and how to best address treatment.

Genomind believes that the use of biomarkers in psychiatry can only help improve patient care. Better knowledge of a patient’s genetics can lead to better medication choices by reducing adverse drug side effects, which are based upon genetic impairments in drug metabolism. Continued research and focus on biomarkers may also help the industry understand underlying pathophysiological changes in the brain that lead to psychiatric disorders.

“The core of Genomind’s philosophy is that psychiatric disorders are dimensional, not categorical, and NIMH’s position directly supports this,” says Dr. Jay Lombard, Genomind’s Chief Scientific Officer and Medical Director. “We hope this move by the NIMH and the resulting RDoC Project will not only allow patients to receive more personalized, tailored care, but help the mental health community gain greater insight into how we can improve treatment even further in the future.”

Genomind is committed to discovery of the underlying causes of neuropsychiatric disorders and supports the development of personalized medicine that improves patients’ lives. The company’s core product is the GeneceptTM Assay, a comprehensive, simple-to-use tool for understanding genetic and biological markers that best inform response to different psychiatric treatments including depression, bipolar disorder, schizophrenia, anxiety disorders, autism and ADHD.

Source: Genomind

Atrophy in Key Region of Brain Associated with Multiple Sclerosis

Magnetic resonance imaging (MRI) measurements of atrophy in an important area of the brain are an accurate predictor of multiple sclerosis (MS), according to a new study published online in the journal Radiology. According to the researchers, these atrophy measurements offer an improvement over current methods for evaluating patients at risk for MS.

MS develops as the body’s immune system attacks and damages myelin, the protective layer of fatty tissue that surrounds nerve cells within the brain and spinal cord. Symptoms include visual disturbances, muscle weakness and trouble with coordination and balance. People with severe cases can lose the ability to speak or walk.

Approximately 85 percent of people with MS suffer an initial, short-term neurological episode known as clinically isolated syndrome (CIS). A definitive MS diagnosis is based on a combination of factors, including medical history, neurological exams, development of a second clinical attack and detection of new and enlarging lesions with contrast-enhanced or T2-weighted MRI.

“For some time we’ve been trying to understand MRI biomarkers that predict MS development from the first onset of the disease,” said Robert Zivadinov, M.D., Ph.D., FAAN, from the Buffalo Neuroimaging Analysis Center of the University at Buffalo in Buffalo, N.Y. “In the last couple of years, research has become much more focused on the thalamus.”

The thalamus is a structure of gray matter deep within the brain that acts as a kind of relay center for nervous impulses. Recent studies found atrophy of the thalamus in all different MS disease types and detected thalamic volume loss in pediatric MS patients.

“Thalamic atrophy may become a hallmark of how we look at the disease and how we develop drugs to treat it,” Dr. Zivadinov said.

For this study, Dr. Zivadinov and colleagues investigated the association between the development of thalamic atrophy and conversion to clinically definite MS.

“One of the most important reasons for the study was to understand which regions of the brain are most predictive of a second clinical attack,” he said. “No one has really looked at this over the long term in a clinical trial.”

The researchers used contrast-enhanced MRI for initial assessment of 216 CIS patients. They performed follow-up scans at six months, one year and two years. Over two years, 92 of 216 patients, or 42.6 percent, converted to clinically definite MS. Decreases in thalamic volume and increase in lateral ventricle volumes were the only MRI measures independently associated with the development of clinically definite MS.

“First, these results show that atrophy of the thalamus is associated with MS,” Dr. Zivadinov said. “Second, they show that thalamic atrophy is a better predictor of clinically definite MS than accumulation of T2-weighted and contrast-enhanced lesions.”

The findings suggest that measurement of thalamic atrophy and increase in ventricular size may help identify patients at high risk for conversion to clinically definite MS in future clinical trials involving CIS patients.

“Thalamic atrophy is an ideal MRI biomarker because it’s detectable at very early stage,” Dr. Zivadinov said. “It has very good predictive value, and you will see it used more and more in the future.”

The research team continues to follow the study group, with plans to publish results from the four-year follow-up next summer. They are also trying to learn more about the physiology of the thalamic involvement in MS.

“The next step is to look at where the lesions develop over two years with respect to the location of the atrophy,” Dr. Zivadinov said. “Thalamic atrophy cannot be explained entirely by accumulation of lesions; there must be an independent component that leads to loss of thalamus.”

MS affects more than 2 million people worldwide, according to the Multiple Sclerosis International Foundation. There is no cure, but early diagnosis and treatment can slow development of the disease.

Source: Thalamic Atrophy is Associated with Development of Clinically Definite Multiple Sclerosis

Source: EurekAlert!

Alzheimer’s Markers Predict Start of Mental Decline

Scientists at Washington University School of Medicine in St. Louis have helped identify many of the biomarkers for Alzheimer’s disease that could potentially predict which patients will develop the disorder later in life. Now, studying spinal fluid samples and health data from 201 research participants at the Charles F. and Joanne Knight Alzheimer’s Disease Research Center, the researchers have shown the markers are accurate predictors of Alzheimer’s years before symptoms develop.

“We wanted to see if one marker was better than the other in predicting which of our participants would get cognitive impairment and when they would get it,” said Catherine Roe, PhD, research assistant professor of neurology. “We found no differences in the accuracy of the biomarkers.”

The study, supported in part by the National Institute on Aging, appears in Neurology.

The researchers evaluated markers such as the buildup of amyloid plaques in the brain, newly visible thanks to an imaging agent developed in the last decade; levels of various proteins in the cerebrospinal fluid, such as the amyloid fragments that are the principal ingredient of brain plaques; and the ratios of one protein to another in the cerebrospinal fluid, such as different forms of the brain cell structural protein tau.

The markers were studied in volunteers whose ages ranged from 45 to 88. On average, the data available on study participants spanned four years, with the longest recorded over 7.5 years.

The researchers found that all of the markers were equally good at identifying subjects who were likely to develop cognitive problems and at predicting how soon they would become noticeably impaired.

Next, the scientists paired the biomarkers data with demographic information, testing to see if sex, age, race, education and other factors could improve their predictions.

“Sex, age and race all helped to predict who would develop cognitive impairment,” Roe said. “Older participants, men and African Americans were more likely to become cognitively impaired than those who were younger, female and Caucasian.”

Roe described the findings as providing more evidence that scientists can detect Alzheimer’s disease years before memory loss and cognitive decline become apparent.

“We can better predict future cognitive impairment when we combine biomarkers with patient characteristics,” she said. “Knowing how accurate biomarkers are is important if we are going to some day be able to treat Alzheimer’s before symptoms and slow or prevent the disease.”

Clinical trials are already underway at Washington University and elsewhere to determine if treatments prior to symptoms can prevent or delay inherited forms of Alzheimer’s disease. Reliable biomarkers for Alzheimer’s should one day make it possible to test the most successful treatments in the much more common sporadic forms of Alzheimer’s.

Study: Amyloid imaging and CSF biomarkers in predicting cognitive impairment up to 7.5 years later

Source: EurekAlert!

The Michael J. Fox Foundation Launches New Arm Of Parkinson’s Progression Markers Initiative Studying At-Risk Populations In Parkinson’s Disease

The Parkinson’s Progression Markers Initiative (PPMI), a landmark biomarker clinical study, has completed enrollment of its initial 600-member cohort of Parkinson’s patients and controls, and will launch additional study cohorts to leverage the existing PPMI infrastructure and evaluate multiple potential biomarkers for Parkinson’s disease (PD). The first of these new cohorts launches today and will investigate risk factors for PD that may enable diagnosis before the onset of motor symptoms.

The pre-motor arm of PPMI will enroll participants who do not have Parkinson’s disease but do have one of three potential risk factors for PD: a reduced sense of smell (hyposmia); rapid eye movement sleep behavior disorder (RBD); or a mutation in the LRRK2 gene (the single greatest genetic contributor to PD known to date). Research to date indicates that each of these factors can be linked to an increased risk of developing Parkinson’s disease, though many people with these conditions do not go on to develop PD. Validating these risk factors and better characterizing their connection to Parkinson’s could enable detection of the disease prior to the onset of motor symptoms and open new avenues toward identifying biomarkers — critical tools in the quest for therapies that can slow or stop disease progression.

“If scientists can learn more about the biological processes taking place in people with any of these three risk factors, we may be able to define biomarkers even before typical symptoms begin,” said Ken Marek , MD, principal investigator of PPMI and president and senior scientist at the Institute for Neurodegenerative Disorders in New Haven, Connecticut. “Finding a biomarker for PD could mean earlier diagnosis of the disease and lead to new drugs that may delay or even prevent the onset of motor symptoms.”

PPMI seeks 10,000 individuals to complete a brief online survey to determine eligibility for the loss-of-smell cohort. Participants in the other groups will largely be enrolled via research centers. This new arm will take place at 23 sites across the world where participants will undergo the same clinical assessments, imaging and collection of biospecimens as the original study.

PPMI’s open-source design and infrastructure has opened the door to evaluating multiple potential biomarkers under one umbrella, building on a precedent created by the Alzheimer’s Disease Neuroimaging Initiative (ADNI). All PPMI clinical data and characterized biosamples are available in real time, providing researchers around the world with an unprecedented resource to help speed and unify disparate biomarker validation studies. To date, 460 scientists from academia and industry have downloaded PPMI data more than 50,000 times in over 30 countries worldwide, and 21 applications have been made for use of PPMI biospecimens in biomarker research. Initial baseline data from PPMI’s original newly diagnosed and control cohorts will be presented this June at the Movement Disorders Society and is expected to be published later this year.

“Lessons learned from Alzheimer’s have taught us the importance of pursuing biomarker research concurrent with therapeutic development,” said Todd Sherer , Ph.D., CEO of The Michael J. Fox Foundation for Parkinson’s Research. “In the third year of PPMI, it is evident that a large-scale biomarker study is not only possible in Parkinson’s disease, but is already yielding scientific insights that could help transform the field’s pursuit of a cure.”

Source: PR Newswire

Firm Hopes Big Data Can Personalize Health Care

When Colin Hill’s father was diagnosed with later-stage prostate cancer last summer, he was treated the same as every other patient with the illness.

This standardized approach bothered Hill, who believes medicine should approach each patient’s illness as unique, with medication tailored to the person’s history and biology.

“You show up to the hospital, and it’s like Groundhog Day,” Hill said, with patients being cared for the same way, over and over again. “It’s this outdated standard of care created for this hypothetical average patient. But no one’s an average patient.”

A genetic analysis of the tumor in his 69-year-old father, Foster Hill, found he had a genetic variant of the cancer that does not usually respond well to the hormone therapy Lupron, the current standard of care. But not knowing what else would work, doctors gave Foster Hill Lupron anyway. Luckily, the treatment seems to be helping, and his father’s outlook is much improved.

Hill hopes a Kendall Square company he founded 13 years ago, GNS Healthcare, will eventually improve medical care for his father — and for countless others — by providing personalized treatment. GNS is among the leaders in using Big Data analytics to learn more about diseases, patients, and treatments.

With data from thousands of cases, GNS uses artificial intelligence to determine what treatment made the crucial difference for each patient.

The company is deploying enormous computing power to produce a more complete understanding of treatments for rheumatoid arthritis, diabetes, cancers, and other illnesses.

For example, it is working with the Dana-Farber Cancer Institute and Mount Sinai Medical School to build a computer model of multiple myeloma, so researchers can better understand what works well for patients today, as well as develop more effective treatments for the blood cancer. It is involved in a similar collaboration with Brigham and Women’s Hospital and several other partners to learn more about multiple sclerosis.

Harvard Medical School recently agreed to use a GNS computing platform to analyze how cells replicate or transform into different types, for insights into­ conditions such as cancer and neurodegenerative diseases, Hill said.

And the company has a partnership with the Centers for Medicare & Medicaid Services and Health Services Advisory Group to assess health care quality measures, as well as other recent deals with pharmaceutical companies, hospitals, and advocacy groups, and the insurance giants Aetna and Blue Cross Blue Shield.

“It’s exciting times for us,” Hill said, after 13 years of developing his approach to analyzing health care. “We are now in the thick of things.”

Hill did not always have such an absorbing interest in science. He went to college at Virginia Tech — mainly to play tennis. “I was more serious than I was good,” he quipped.

But while there, he became fascinated by physics and chaos theory — the idea that complex patterns could result from simple rules.

His imagination was stoked by a summer job in 1996 at Santa Fe Institute, an interdisciplinary research center focused on highly complex issues. Hill then went on to graduate from McGill and then Cornell University.

By then, the Human Genome Project was becoming a reality, capturing the attention of many scientists, including a young Hill.

“That’s when two and two came together,” Hill said. “It was like ‘Oh yeah, the stuff we’re doing, though it’s pretty theoretical, it is going to be the thing that links these pieces together,’ ” including chaos theory, genetics, Big Data, and health care.

Now he’s in the middle of the so-called Big Data revolution in health care. Companies such as GNS have an enormous capacity for crunching troves of information on patients, diseases, and medical outcomes collected by medical providers, insurers, and other big players.

Hill likes to say he wants GNS to capture the “data exhaust thrown off” by every interaction a patient has with the health care system, from the doctor’s office to the hospital to the pharmacy. A bad reaction to medication is a data point worth having; ditto for other side effects, as well as results of all kinds of procedures and interventions — bad or good.

While such data sets are getting easier to find, Hill said, genetic information is still too expensive to be truly useful.

“What we don’t have yet for my dad and for other men with prostate cancer is a large coherent set of data on prostate cancer patients that includes the molecular level,” Hill said.

With information aggregated from thousands of cases, Hill said, GNS uses artificial intelligence algorithms developed out of chaos theory to determine what treatment made the crucial difference for each patient, and with it what is likely to work best for the next patient — rather than simply trying one medication after another, as is often done today.

“What we’re trying to get at is not just patterns and trends, but reverse engineer the mechanisms that gave rise to the data,” he said. “We’re trying to find the cause-effect relationships within the data.”

This ability to predict results is what sets GNS apart, said Dr. Atul Butte of Stanford University, one of the academic leaders of the Big Data movement. That’s the “nifty part of their technology,” Butte said.

Alexis Borisy, a partner at the Boston life sciences venture capital firm Third Rock Ventures, said GNS is in the vanguard of Big Data companies analyzing health care information.

“They’ve had a chance to learn, refine, and they’ve kept with it so they’ve had a lot of experience to build on,” Borisy said.

He and Hill have known each other since they were young business executives more than a decade ago, and he said he has tremendous respect for Hill’s intelligence, persistence, and communication skills.

“He is one of the visionaries in the space,” said Borisy, who also serves as chairman of Foundation Medicine, a molecular information company, and interim chief executive of Warp Drive Bio, both of Cambridge. “I think it’s fair to say he’s kept GNS growing and building by the force of his personality and the force of his efforts.”

Source: The Boston Globe