Posts tagged biomarkers
Articles and news from the latest research reports.
New technique could benefit Alzheimer’s diagnosis
Swinburne researchers have developed a technique to create a highly sensitive surface for measuring the concentration of a peptide that is a biomarker for early stage Alzheimer’s disease.
(Image caption: Ultrashort-laser pulses were used to write ripples on the surface of sapphire. The self-organised nano-structure of ripples (seen in the image) is a perfect sensing surface after coating with a nanometre-thin layer of gold made by evaporation or sputtering. Such surface ripples were used in the study of amyloid detection.)
Alzheimer’s disease was first recorded more than 100 years ago, but there is still no effective therapy to stop or slow the progression of the disease. Sufferers can lose up to 60 per cent of their neuronal cells before a diagnosis is obtained.
Diagnosis at the very early stages before neuronal degeneration has begun is vital for testing and developing new treatments.
Abnormality of the beta amyloid peptide in cerebrospinal fluid appears to be the earliest and most significant marker of Alzheimer’s. Currently there are no standardised tests to detect these biomarkers.
The researchers have developed a sensor based on nanotechnology that outperforms commercial sensors and demonstrates fast and reliable measurement of beta amyloid oligomers at low concentrations.
The key to the high sensitivity is the laser nano-textured gold coated surface. This sensor can identify concentrations of beta amyloid in a quantitative manner for the first time.
“We showed that sensors based on light scattering can indeed deliver QUANTATIVE measurements and they can be made fast,” Professor of Nanophotonics Saulius Juodkazis said.
“The sensor platform we developed by laser nano-texturing of surfaces is delivering results of the highest sensitivity and repeatability.
“The challenge is to create fast and efficient fabrication of sensors based on nanotechnology and develop new analytical methods of detection. This means we should be able to detect markers of diseases at far lower levels.”
Surface enhanced Raman spectroscopy (SERS) is one of the most sensitive and highly specific label-free detection methods which may evolve as a detection technique for different forms of beta amyloid or as a rapid, low cost technique to validate new biomarkers before developing standard assays for enzyme-linked immunosorbent assays (ELISAs).
This research is a PhD project work of Dr Ricardas Buividas who received his doctorate in May 2014. It was published in the Journal of Biophotonics.
(Source: swinburne.edu.au)
Smell and eye tests show potential to detect Alzheimer’s early
A decreased ability to identify odors might indicate the development of cognitive impairment and Alzheimer’s disease, while examinations of the eye could indicate the build-up of beta-amyloid, a protein associated with Alzheimer’s, in the brain, according to the results of four research trials reported today at the Alzheimer’s Association International Conference® 2014 (AAIC® 2014) in Copenhagen.
In two of the studies, the decreased ability to identify odors was significantly associated with loss of brain cell function and progression to Alzheimer’s disease. In two other studies, the level of beta-amyloid detected in the eye (a) was significantly correlated with the burden of beta-amyloid in the brain and (b) allowed researchers to accurately identify the people with Alzheimer’s in the studies.
Beta-amyloid protein is the primary material found in the sticky brain “plaques” characteristic of Alzheimer’s disease. It is known to build up in the brain many years before typical Alzheimer’s symptoms of memory loss and other cognitive problems.
"In the face of the growing worldwide Alzheimer’s disease epidemic, there is a pressing need for simple, less invasive diagnostic tests that will identify the risk of Alzheimer’s much earlier in the disease process," said Heather Snyder, Ph.D., Alzheimer’s Association director of Medical and Scientific Operations. "This is especially true as Alzheimer’s researchers move treatment and prevention trials earlier in the course of the disease."
"More research is needed in the very promising area of Alzheimer’s biomarkers because early detection is essential for early intervention and prevention, when new treatments become available. For now, these four studies reported at AAIC point to possible methods of early detection in a research setting to choose study populations for clinical trials of Alzheimer’s treatments and preventions," Snyder said.
With the support of the Alzheimer’s Association and the Alzheimer’s community, the United States created its first National Plan to Address Alzheimer’s Disease in 2012. The plan includes the critical goal, which was adopted by the G8 at the Dementia Summit in 2013, of preventing and effectively treating Alzheimer’s by 2025. It is only through strong implementation and adequate funding of the plan, including an additional $200 million in fiscal year 2015 for Alzheimer’s research, that we’ll meet that goal. For more information and to get involved, visit http://www.alz.org.
Clinically, at this time it is only possible to detect Alzheimer’s late in its development, when significant brain damage has already occurred. Biological markers of Alzheimer’s disease may be able to detect it at an earlier stage. For example, using brain PET imaging in conjunction with a specialized chemical that binds to beta-amyloid protein, the buildup of the protein as plaques in the brain can be revealed years before symptoms appear. These scans can be expensive and are not available everywhere. Amyloid can also be detected in cerebrospinal fluid through a lumbar puncture where a needle is inserted between two bones (vertebrae) in your lower back to remove a sample of the fluid that surrounds your brain and spinal cord.
(Image: Getty Images)
Significant step towards blood test for Alzheimer’s
Scientists have identified a set of 10 proteins in the blood which can predict the onset of Alzheimer’s, marking a significant step towards developing a blood test for the disease. The study, led by King’s College London and UK proteomics company, Proteome Sciences plc,analysed over 1,000 individuals and is the largest of its kind to date.
There are currently no effective long-lasting drug treatments for Alzheimer’s, and it is believed that many new clinical trials fail because drugs are given too late in the disease process. A blood test could be used to identify patients in the early stages of memory loss for clinical trials to find drugs to halt the progression of the disease.
The study, published in Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, is the result of an international collaboration led by King’s College London and Proteome Sciences plc, funded by Alzheimer’s Research UK, the UK Medical Research Council, the National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre and Proteome Sciences.
The researchers used data from three international studies. Blood samples from a total of 1,148 individuals (476 with Alzheimer’s disease; 220 with ‘Mild Cognitive Impairment’ (MCI) and 452 elderly controls without dementia) were analysed for 26 proteins previously shown to be associated with Alzheimer’s disease. A sub-group of 476 individuals across all three groups also had an MRI brain scan.
Researchers identified 16 of these 26 proteins to be strongly associated with brain shrinkage in either MCI or Alzheimer’s. They then ran a second series of tests to establish which of these proteins could predict the progression from MCI to Alzheimer’s. They identified a combination of 10 proteins capable of predicting whether individuals with MCI would develop Alzheimer’s disease within a year, with an accuracy of 87 percent.
Dr Abdul Hye, lead author of the study from the Institute of Psychiatry at King’s College London, said: “Memory problems are very common, but the challenge is identifying who is likely to develop dementia. There are thousands of proteins in the blood, and this study is the culmination of many years’ work identifying which ones are clinically relevant. We now have a set of 10 proteins that can predict whether someone with early symptoms of memory loss, or mild cognitive impairment, will develop Alzheimer’s disease within a year, with a high level of accuracy.”
Professor Simon Lovestone, senior author of the study from the University of Oxford, who led the work whilst at King’s, said: “Alzheimer’s begins to affect the brain many years before patients are diagnosed with the disease. Many of our drug trials fail because by the time patients are given the drugs, the brain has already been too severely affected. A simple blood test could help us identify patients at a much earlier stage to take part in new trials and hopefully develop treatments which could prevent the progression of the disease. The next step will be to validate our findings in further sample sets, to see if we can improve accuracy and reduce the risk of misdiagnosis, and to develop a reliable test suitable to be used by doctors.”
Dr Eric Karran, Director of Research at Alzheimer’s Research UK, the UK’s leading dementia research charity, said: “As the onset of Alzheimer’s is often slow and subtle, a blood test to identify those at high risk of the disease at an early stage would be of real value. Detecting the first signs of Alzheimer’s could improve clinical trials for new treatments and help those already concerned about their memory, but we’re not currently in a position to use such a test to screen the general population.
“With an ageing population, and age the biggest risk factor for Alzheimer’s, we are expecting rising numbers of people to be affected over the coming years. It’s important to develop new ways to intervene early in the disease to help people maintain their quality of life for as long as possible.”
Dr Ian Pike, co-author of the paper from Proteome Sciences, said: “By linking the best British academic and commercial research, this landmark study in Alzheimer’s disease is a major advance in the development of a simple blood test to identify the disease before clinical symptoms appear. This is the window that will offer the best chance of successful treatment. Equally important, a blood test will be considerably easier and less expensive than using brain imaging or cerebrospinal spinal fluid.
“We are in the process of selecting commercial partners to combine the protein biomarkers in a blood test for the global market, a key step forward to deliver effective and early treatment for this crippling disease.”
Alzheimer’s disease is the most common form of dementia. Globally, it is estimated that 135 million people will have dementia by 2050. In 2010, the annual global cost of dementia was estimated at$604 billion. MCI includes problems with day-to-day memory, language and attention,and can be an early sign of dementia, or a symptom of stress or anxiety. Approximately 10% of people diagnosed with MCI develop dementia within a year but apart from regular assessments to measure memory decline, there is currently no accurate way of predicting who will, or won’t, develop dementia.
Previous studies have also shown that PET brain scans and plasma in lumbar fluid can be used to predict the onset of dementia from MCI. However, PET imaging is highly expensive and lumbar punctures invasive.
(Source: kcl.ac.uk)
Changes in proteins may predict ALS progression
Measuring changes in certain proteins — called biomarkers — in people with amyotrophic lateral sclerosis may better predict the progression of the disease, according to scientists at Penn State College of Medicine.
ALS is often referred to as Lou Gehrig’s disease, is a neurological disease in which the brain loses its ability to control movement as motor neurons degenerate. The course of the disease varies, with survival ranging from months to decades.
"The cause of most cases of ALS remains unknown," said James Connor, Distinguished Professor of Neurosurgery, Neural and Behavioral Sciences and Pediatrics. "Although several genetic and environmental factors have been identified, each accounts for only a fraction of the total cases of ALS."
This clinical variation in patients presents challenges in terms of managing the disease and developing new treatments. Finding relevant biomarkers, which are objective measures that reflect changes in biological processes or reactions to treatments, may help address these challenges.
The project was led by Xiaowei Su, an M.D./ Ph.D. student in Connor’s laboratory, in collaboration with Zachary Simmons, director of the Penn State Hershey ALS Clinic and Research Center. Su studied plasma and cerebrospinal fluid samples previously collected from patients undergoing diagnostic evaluation, who were later identified as having ALS. Analysis shows that looking at multiple biomarkers to predict progression is not only mathematically possible, it improves upon methods using single biomarkers.
Statistical models analyzing plasma had reasonable ability to predict total disease duration and used seven relevant biomarkers. For example, higher levels of the protein IL-10 predict a longer disease duration. IL-10 is involved with anti-inflammation, suggesting that lower levels of inflammation are associated with a longer disease duration.
The researchers identified six biomarkers for cerebrospinal fluid. For example, higher levels of G-CSF — a growth factor known to have protective effects on motor neurons, the cells that die in ALS — predicts a longer disease duration.
Perhaps most importantly, the results suggest that a combination of biomarkers from both plasma and cerebrospinal fluid better predict disease duration.
While the size of this study is small, the ability of the specific biomarkers used to predict prognosis suggests that the approach holds promise.
"The results argue for the usefulness of researching this approach for ALS both in terms of predicting disease progression and in terms of determining the impact of therapeutic strategies," Connor said. "The results present a compelling starting point for the use of this method in larger studies and provide insights for novel therapeutic targets."
(Source: news.psu.edu)
![The Search for the Best Depression Treatment
Brain scans, blood samples, and other diagnostic tests could one day direct doctors to the best treatments for depression patients and uncover the biological basis of the condition.
When someone is diagnosed with depression, patient and doctor often begin a long trial-and-error process of testing different treatments. Sometimes they work, sometimes they don’t, so patients may try several options before finding the best one. But in the future, a brain scan, blood test, or some combination could help guide doctors to the best drugs, or lead them to suggest talk therapy.
Recently, Emory University researcher Helen Mayberg reported that a PET scan, a commonly used imaging method, can reveal whether a patient will respond better to an antidepressant or cognitive behavioral therapy. And in May, Medscape reported that David Mischoulon of Massachusetts General Hospital presented findings that the amount of a particular protein in the blood of depression patients could indicate whether a patient would do better by adding a form of folic acid to his or her treatment.
A key goal of such research is to distinguish between causes of depression. “The presence of certain biomarkers might give us a clue whether [a particular patient’s] depression is truly biologically driven, or whether it is depression like sadness over an event,” says Mischoulon. “If we can identify people who have these biological bases, it might suggest these patients might do better with medications, as opposed to psychotherapies or meditation.”
According to the World Health Organization, depression is the leading cause of disability globally. Many people do not seek or do not have access to treatment, and among those who do, fewer than 40 percent of depression patients improve with the first type of treatment they try. The problem is not that treatments like antidepressants and cognitive behavioral therapy don’t work, it’s that no one treatment works for every patient. Researchers from many disciplines, from neuroscience to genomics, are studying this complex disorder, which likely represents many different conditions with unique origins and treatments. Large clinical trials to predict a patient’s response to therapy or drugs based on brain or body biomarkers could improve treatment for future patients and perhaps uncover a clearer understanding of depression’s origins.
“You see now a number of big studies on predictive biomarkers,” says Mayberg, who has pioneered pacemaker-like implants as a treatment for severe cases of depression. She’s also involved in a large study of patients who will be treated with antidepressants or cognitive behavioral therapy based on brain scans. “It’s going to be interesting over the next year or two to see how this plays out,” she says. One question will be whether researchers will be able to identify markers that are both unambiguous but also practical to test. Brain scans may be the best place to start, she says, because they focus on the origin of the condition, but once good biomarkers are identified via brain scan, surrogates found in the blood may provide a simpler and more affordable option.
One challenge for researchers is that depression is probably a conglomeration of many diseases, says Madhukar Trivedi, a University of Texas Southwestern researcher heading a large trial that is trying to distinguish patients who respond better to one type of antidepressant compared to another. “There are a lot of subtypes in depression, so any given marker, whether genetic, protein, imaging, or EEG, ends up accounting for only a small percentage of variance for any group of patients,” says Trivedi.
If these researchers are successful, they could dramatically change how depression is treated and perhaps diagnosed. Doctors in the United States use the Diagnostic and Statistical Manual of Mental Disorders, or DSM, to diagnose depression. The diagnoses are largely based on the collection of symptoms presented or described by patients. In May, the head of the National Institute of Mental Health, Thomas Insel, announced that his institution would focus its research in areas other than the categories presented by the DSM. “Patients with mental disorders deserve better,” he said.
Bruce Cuthbert is heading the NIMH’s project to establish new ways of studying mental illness and potentially to improve future versions of the DSM by more precisely identifying the brain abnormalities in various diseases, including depression. The idea behind the project is to map out the genetic, circuit, and cognitive aspects of mental illness and to focus on individual features of disorders instead of clinical diagnoses. It could provide the information necessary to improve the DSM so that it is based on neuroscience and not just collections of symptoms. “In the future, we might define the disorders differently, or we might not. But this project will provide a framework to look at neural systems and how they operate and how that contributes to disease,” says Cuthbert.
Perhaps more immediately, the NIMH project could help researchers tune clinical trials of drugs to the right patients by focusing on discrete symptoms. For example, anhedonia, the inability to feel pleasure or seek pleasure, is a major symptom of depression, but it is also found in other patients, such as those with schizophrenia. By recruiting patients with measurable anhedonia, drug developers may be more likely to succeed in clinical trials than if they focused only on depression patients, says Cuthbert.
The NIMH project could also help to identify biomarkers of depression. “It could give us a structure to look at the pathology through different markers of the disease,” says Trivedi. “The goal is fantastic, but the proof is going to come in doing it.”](http://40.media.tumblr.com/2cee06d8ba637a69d1ed2f2d29d4c882/tumblr_mr0drrDP3b1rog5d1o1_500.jpg)
The Search for the Best Depression Treatment
Brain scans, blood samples, and other diagnostic tests could one day direct doctors to the best treatments for depression patients and uncover the biological basis of the condition.
When someone is diagnosed with depression, patient and doctor often begin a long trial-and-error process of testing different treatments. Sometimes they work, sometimes they don’t, so patients may try several options before finding the best one. But in the future, a brain scan, blood test, or some combination could help guide doctors to the best drugs, or lead them to suggest talk therapy.
Recently, Emory University researcher Helen Mayberg reported that a PET scan, a commonly used imaging method, can reveal whether a patient will respond better to an antidepressant or cognitive behavioral therapy. And in May, Medscape reported that David Mischoulon of Massachusetts General Hospital presented findings that the amount of a particular protein in the blood of depression patients could indicate whether a patient would do better by adding a form of folic acid to his or her treatment.
A key goal of such research is to distinguish between causes of depression. “The presence of certain biomarkers might give us a clue whether [a particular patient’s] depression is truly biologically driven, or whether it is depression like sadness over an event,” says Mischoulon. “If we can identify people who have these biological bases, it might suggest these patients might do better with medications, as opposed to psychotherapies or meditation.”
According to the World Health Organization, depression is the leading cause of disability globally. Many people do not seek or do not have access to treatment, and among those who do, fewer than 40 percent of depression patients improve with the first type of treatment they try. The problem is not that treatments like antidepressants and cognitive behavioral therapy don’t work, it’s that no one treatment works for every patient. Researchers from many disciplines, from neuroscience to genomics, are studying this complex disorder, which likely represents many different conditions with unique origins and treatments. Large clinical trials to predict a patient’s response to therapy or drugs based on brain or body biomarkers could improve treatment for future patients and perhaps uncover a clearer understanding of depression’s origins.
“You see now a number of big studies on predictive biomarkers,” says Mayberg, who has pioneered pacemaker-like implants as a treatment for severe cases of depression. She’s also involved in a large study of patients who will be treated with antidepressants or cognitive behavioral therapy based on brain scans. “It’s going to be interesting over the next year or two to see how this plays out,” she says. One question will be whether researchers will be able to identify markers that are both unambiguous but also practical to test. Brain scans may be the best place to start, she says, because they focus on the origin of the condition, but once good biomarkers are identified via brain scan, surrogates found in the blood may provide a simpler and more affordable option.
One challenge for researchers is that depression is probably a conglomeration of many diseases, says Madhukar Trivedi, a University of Texas Southwestern researcher heading a large trial that is trying to distinguish patients who respond better to one type of antidepressant compared to another. “There are a lot of subtypes in depression, so any given marker, whether genetic, protein, imaging, or EEG, ends up accounting for only a small percentage of variance for any group of patients,” says Trivedi.
If these researchers are successful, they could dramatically change how depression is treated and perhaps diagnosed. Doctors in the United States use the Diagnostic and Statistical Manual of Mental Disorders, or DSM, to diagnose depression. The diagnoses are largely based on the collection of symptoms presented or described by patients. In May, the head of the National Institute of Mental Health, Thomas Insel, announced that his institution would focus its research in areas other than the categories presented by the DSM. “Patients with mental disorders deserve better,” he said.
Bruce Cuthbert is heading the NIMH’s project to establish new ways of studying mental illness and potentially to improve future versions of the DSM by more precisely identifying the brain abnormalities in various diseases, including depression. The idea behind the project is to map out the genetic, circuit, and cognitive aspects of mental illness and to focus on individual features of disorders instead of clinical diagnoses. It could provide the information necessary to improve the DSM so that it is based on neuroscience and not just collections of symptoms. “In the future, we might define the disorders differently, or we might not. But this project will provide a framework to look at neural systems and how they operate and how that contributes to disease,” says Cuthbert.
Perhaps more immediately, the NIMH project could help researchers tune clinical trials of drugs to the right patients by focusing on discrete symptoms. For example, anhedonia, the inability to feel pleasure or seek pleasure, is a major symptom of depression, but it is also found in other patients, such as those with schizophrenia. By recruiting patients with measurable anhedonia, drug developers may be more likely to succeed in clinical trials than if they focused only on depression patients, says Cuthbert.
The NIMH project could also help to identify biomarkers of depression. “It could give us a structure to look at the pathology through different markers of the disease,” says Trivedi. “The goal is fantastic, but the proof is going to come in doing it.”
Children who were later diagnosed with autism spectrum disorder had excessive cerebrospinal fluid and enlarged brains in infancy, a study by a multidisciplinary team of researchers with the UC Davis MIND Institute has found, raising the possibility that those brain anomalies may serve as potential biomarkers for the early identification of the neurodevelopmental disorder.
The study is the first to follow the brain-growth trajectories from infancy in children who later develop autism and the first to associate excessive cerebrospinal fluid during infancy with autism. “Early Brain Development and Elevated Extra-Axial Fluid in Infants who Develop Autism Spectrum Disorder,” is published online today in the neurology journal Brain, published by Oxford University Press.
"This is the first report of an infant brain anomaly associated with autism that is detectable by using conventional structural MRI,” said MIND Institute Director of Research David Amaral, who co-led the study.
"This study raises the potential of developing a very early method of detecting autism spectrum disorder. Early detection is critical, because early intervention can decrease the cognitive and behavioral impairments associated with autism and may result in more positive long-term outcomes for the child,” Amaral said.
The study was conducted in 55 infants between 6 and 36 months of age, 33 of whom had an older sibling with autism. Twenty-two infants were children with no family history of the condition.
The researchers reported that the brain anomaly was detected significantly more often in the high-risk infants who were later diagnosed with autism between 24 and 36 months. Prior research by Sally Ozonoff, the vice chair for research and professor in the Department of Psychiatry and Behavioral Sciences, who co-led the study, has shown that the risk of autism is nearly 20 times greater in siblings of children with autism than in the general population. The U. S. Centers for Disease Control and Prevention puts the overall incidence of autism at 1 in 88.
The excessive cerebrospinal fluid and enlarged brain volume were detected by periodically measuring the infants’ brain growth and development using magnetic resonance imaging (MRI), and by regularly assessing their cognitive, social, communication and motor development. Both the high- and low-risk infants underwent their first MRI scans at 6 to 9 months. The second MRI scans occurred when they were 12 to 15 months old. The third was conducted between 18 and 24 months. The MRIs were conducted while the infants were sleeping naturally, without the need for sedation or anesthesia.
At 6 months, the researchers began intensive behavioral assessments of the infants’ development. Their parents also periodically completed questionnaires about their babies’ behaviors. These tests were conducted until the infants were 24 to 36 months old, when each child was evaluated as having autism spectrum disorder, other developmental delays, or typical development.
In addition to the 10 children diagnosed with autism, 24 percent of the high-risk and 13.5 percent of the low-risk infants were classified as having other developmental delays. Some 45.5 percent of high-risk and over 86 percent of low-risk babies were found to be developing normally.
The researchers found that by 6 to 9 months of age, the children who developed autism had elevated cerebrospinal fluid levels in the “extra-axial” space above and surrounding the brain, and that those fluid levels remained abnormally elevated between 18 to 24 months of age. The more fluid during early infancy, the more severe were the child’s autism symptoms when diagnosed, the study found.
In the infants who would go on to be diagnosed with autism, the ”extra-axial” fluid volume was, on average, 33 percent greater at 12 to 15 months and 22 percent greater at 18 to 24 months, when compared with typically developing infants. At 6 to 9 months, the extra-axial fluid volume was 20 percent greater, when compared with typically developing infants.
The study also provided the first MRI evidence of brain enlargement in autism prior to 24 months. The infants in the study diagnosed with autism had, on average, 7 percent larger brain volumes at 12 months, compared with the typically developing infants.
The excessive extra-axial fluid and enlarged brain volume were detected by brain imaging before behavioral signs of autism were evident. “The cause of the increased extra-axial fluid and enlarged brain size is currently unknown”, Amaral said.
Early diagnosis may be of particular benefit to infants whose older siblings have been diagnosed with autism, but the researchers caution that this finding must be replicated before it could aid in the early diagnosis of ASD. The MIND Institute is currently collaborating with other research institutions to replicate these findings and to evaluate how well the potential biomarker can accurately predict a later diagnosis of ASD.
“It is critical to understand how often this brain finding is present in children who do not develop autism, as well,” said Ozonoff. “For a biomarker to be useful in predicting autism outcomes, we want to be sure it does not produce an unacceptable level of false positives.”
“If this finding of elevated extra-axial fluid is replicated in a larger sample of infants who develop autism, and it accurately distinguishes between infants who do not develop autism, it has the potential of becoming a noninvasive biomarker that would aid in early detection, and ultimately improve the long-term outcomes of these children through early intervention,” said Mark Shen, UC Davis graduate student and the study’s lead author.
Newly Identified Bone Marrow Stem Cells Reveal Markers for ALS
Amyotrophic Lateral Sclerosis (ALS) is a devastating motor neuron disease that rapidly atrophies the muscles, leading to complete paralysis. Despite its high profile — established when it afflicted the New York Yankees’ Lou Gehrig — ALS remains a disease that scientists are unable to predict, prevent, or cure.
Although several genetic ALS mutations have been identified, they only apply to a small number of cases. The ongoing challenge is to identify the mechanisms behind the non-genetic form of the disease and draw useful comparisons with the genetic forms.
Now, using samples of stem cells derived from the bone marrow of non-genetic ALS patients, Prof. Miguel Weil of Tel Aviv University’s Laboratory for Neurodegenerative Diseases and Personalized Medicine in the Department of Cell Research and Immunology and his team of researchers have uncovered four different biomarkers that characterize the non-genetic form of the disease. Each sample shows similar biological abnormalities to four specific genes, and further research could reveal additional commonalities. “Because these genes and their functions are already known, they give us a specific direction for research into non-genetic ALS diagnostics and therapeutics,” Prof. Weil says. His initial findings were reported in the journal Disease Markers.
Giving in to stress
To hunt for these biomarkers, Prof. Weil and his colleagues turned to samples of bone marrow collected from ALS patients. Though more difficult to collect than blood, bone marrow’s stem cells are easy to isolate and grow in a consistent manner. In the lab, he used these cells as cellular models for the disease. He ultimately discovered that cells from different ALS patients shared the same abnormal characteristics of four different genes that may act as biomarkers of the disease. And because the characteristics appear in tissues that are related to ALS — including in muscle, brain, and spinal cord tissues in mouse models of genetic ALS — they may well be connected to the degenerative process of the disease in humans, he believes.
Searching for the biological significance of these abnormalities, Prof. Weil put the cells under stress, applying toxins to induce the cells’ defense mechanisms. Healthy cells will try to fight off threats and often prove quite resilient, but ALS cells were found to be overwhelmingly sensitive to stress, with the vast majority choosing to die rather than fight. Because this is such an ingrained response, it can be used as a feature for drug screening for the disease, he adds.
The hunt for therapeutics
Whether these biomarkers are a cause or consequence of ALS is still unknown. However, this finding remains an important step towards uncovering the mechanisms of the disease. Because these genes have already been identified, it gives scientists a clear direction for future research. In addition, these biomarkers could lead to earlier and more accurate diagnostics.
Next, Prof. Weil plans to use his lab’s high-throughput screening facility — which can test thousands of compounds’ effects on diseased cells every day — to search for drug candidates with the potential to affect the abnormal expression of these genes or the stress response of ALS cells. A compound that has an impact on these indicators of ALS could be meaningful for treating the disease, he says.
Prof. Weil is the director of the new Cell Screening Facility for Personalized Medicine at TAU. The facility is dedicated to finding potential drugs for rare and Jewish hereditary diseases.
(Source: aftau.org)
New Research Points to Biomarker that Could Track Huntington’s Disease Progression
A hallmark of neurodegenerative diseases such as Alzheimer’s, Parkinson’s and Huntington’s is that by the time symptoms appear, significant brain damage has already occurred—and currently there are no treatments that can reverse it. A team of SRI International researchers has demonstrated that measurements of electrical activity in the brains of mouse models of Huntington’s disease could indicate the presence of disease before the onset of major symptoms. The findings, “Longitudinal Analysis of the Electroencephalogram and Sleep Phenotype in the R6/2 Mouse Model of Huntington’s Disease,” are published in the July 2013 issue of the neurology journal Brain, published by Oxford University Press.
SRI researchers led by Stephen Morairty, Ph.D., a director in the Center for Neuroscience in SRI Biosciences, and Simon Fisher, Ph.D., a postdoctoral fellow at SRI, used electroencephalography (EEG), a noninvasive method commonly used in humans, to measure changes in neuronal electrical activity in a mouse model of Huntington’s disease. Identification of significant changes in the EEG prior to the onset of symptoms would add to evidence that the EEG can be used to identify biomarkers to screen for the presence of a neurodegenerative disease. Further research on such potential biomarkers might one day enable the tracking of disease progression in clinical trials and could facilitate drug development.
“EEG signals are composed of different frequency bands such as delta, theta and gamma, much as light is composed of different frequencies that result in the colors we call red, green and blue,” explained Thomas Kilduff, Ph.D., senior director, Center for Neuroscience, SRI Biosciences. “Our research identified abnormalities in all three of these bands in Huntington’s disease mice. Importantly, the activity in the theta and gamma bands slowed as the disease progressed, indicating that we may be tracking the underlying disease process.”
EEG has shown promise as an indicator of underlying brain dysfunction in neurodegenerative diseases, which otherwise occurs surreptitiously until symptoms appear. Until now, most investigations of EEG in patients with neurodegenerative diseases and in animal models of neurodegenerative diseases have shown significant changes in EEG patterns only after disease symptoms occurred.
“Our breakthrough is that we have found an EEG signature that appears to be a biomarker for the presence of disease in this mouse model of Huntington’s disease that can identify early changes in the brain prior to the onset of behavioral symptoms,” said Morairty, the paper’s senior author. “While the current study focused on Huntington’s disease, many neurodegenerative diseases produce changes in the EEG that are associated with the degenerative process. This is the first step in being able to use the EEG to predict both the presence and progression of neurodegenerative diseases.”
Although previous studies have shown there are distinct and extensive changes in EEG patterns in Alzheimer’s and Huntington’s disease patients, researchers are looking for changes that may occur decades before disease onset.
Huntington’s disease is an inherited disorder that causes certain nerve cells in the brain to die, resulting in motor dysfunction, cognitive decline and psychiatric symptoms. It is the only major neurodegenerative disease where the cause is known with certainty: a genetic mutation that produces a change in a protein that is toxic to neurons.
(Source: sri.com)
Leading researchers report on the elusive search for biomarkers in Huntington’s disease
While Huntington’s disease (HD) is currently incurable, the HD research community anticipates that new disease-modifying therapies in development may slow or minimize disease progression. The success of HD research depends upon the identification of reliable and sensitive biomarkers to track disease and evaluate therapies, and these biomarkers may eventually be used as outcome measures in clinical trials. Biomarkers could be especially helpful to monitor changes during the time prior to diagnosis and appearance of overt symptomatology. Three reports in the current issue of the Journal of Huntington’s Disease explore the potential of neuroimaging, proteomic analysis of brain tissue, and plasma inflammatory markers as biomarkers for Huntington’s disease.
"Characteristics of an ideal biomarker include quantification which is reliable, reproducible across sites, minimally invasive and widely available. The biomarker should show low variability in the normal population and change linearly with disease progression, ideally over short time intervals. Finally, the biomarker should respond predictably to an intervention which modifies the disease," says Elin Rees, researcher at UCL Institute of Neurology, London.
In the first report, Rees and colleagues explore the use of neuroimaging biomarkers. She says they are strong candidates as outcome measures in future clinical trials because of their clear relevance to the neuropathology of disease and their increased precision and sensitivity compared with some standard functional measures. This review looks at results from longitudinal imaging studies, focusing on the most widely available imaging modalities: structural MRI (volumetric and diffusion), functional MRI, and PET.
"All imaging modalities are logistically complicated and expensive compared with standard clinical or cognitive end-points and their sensitivity is generally reduced in individuals with later stage HD due to movement," says Rees. "Nevertheless, imaging has several advantages including the ability to track progression in the pre-manifest stage before any detectable clinical or cognitive change."
Current evidence suggests that the best neuroimaging biomarkers are structural MRI and PET using [11C] raclopride (RACLO-PET) as the tracer, in order to assess changes in the basal ganglia, especially the caudate.
A study led by Garth J.S. Cooper, PhD, professor of Biochemistry and Clinical Biochemistry at the School of Biological Sciences and the Department of Medicine at the University of Auckland, used comparative proteome analysis to identify how protein expression might correlate with Huntington’s neurodegeneration in two regions of human brain: the middle frontal gyrus (MFG) and the visual cortex (VC). The investigators studied post mortem human brain tissue from seven HD brains and eight matched controls. They found that the MFG of HD brains differentially expressed 22 proteins compared to controls, while only seven were different in the VC. Several of these proteins had not been linked to HD previous. Investigators categorized these proteins into six general functional categories: stress response, apoptosis, glycolysis, vesicular trafficking, and endocytosis. They determined that there is a common thread in the degenerative processes associated with HD, Alzheimer’s disease, and diabetes.
The third report explores the possibility that inflammatory markers in plasma can be used to track HD, noting that immune changes are apparent even during the preclinical stage. “The innate immune system orchestrates an inflammatory response involving complex interactions between cytokines, chemokines and acute phase proteins and is thus a rich source of potential biomarkers,” says Maria Björkqvist, PhD, head of the Brain Disease Biomarker Unit, Department of Experimental Science of Lund University, Sweden.
The authors compare plasma levels of several markers involved in inflammation and innate immunity of healthy controls and HD patients at different stages of disease. Two methods were used to analyze plasma: antibody-based technologies and multiple reaction monitoring (MRM).
None of the measures were significantly altered in both HD cohorts tested and none correlated with HD disease stage. Only one substance, C-reactive protein (CRP), was decreased in early HD – but this was found in only one of the two cohorts, so the finding may not be reliable. The investigators were unable to confirm other studies that had found HD-related changes in other inflammatory markers, including components of the complement system.
Some markers correlated with clinical measures. For instance, ApoE was positively correlated with depression and irritability scores, suggesting an association between ApoE and mood changes.
Even though recent data suggest that the immune system is likely to be a modifier of HD disease, inflammatory proteins do not seem to be likely candidates to be biomarkers for HD. “Many proteomic studies designed to provide potential biomarkers of disease have generated significant findings, however, often these biomarkers fail to replicate during the validation process,” says Björkqvist.
(Source: eurekalert.org)
![Study finds that sleep apnea and Alzheimer’s are linked
A new study looking at sleep-disordered breathing (SDB) and markers for Alzheimer’s disease (AD) risk in cerebrospinal fluid (CSF) and neuroimaging adds to the growing body of research linking the two.
But this latest study also poses an interesting question: Could AD in its “preclinical stages” also lead to SDB and explain the increased prevalence of SDB in the elderly?
The study will be presented at the ATS 2013 International Conference.
"It’s really a chicken and egg story," said Ricardo S. Osorio, MD, a research assistant professor at NYU School of Medicine who led the study. "Our study did not determine the direction of the causality, and, in fact, didn’t uncover a significant association between the two, until we broke out the data on lean and obese patients."
When the researchers did consider body mass, they found that lean patients (defined as having a body mass index <25) with SDB did possess several specific and non-specific biomarkers of AD risk (increased P-Tau and T-Tau in CSF, hippocampal atrophy using structural MRI, and glucose hypometabolism using FDG-PET in several AD-vulnerable regions). Among obese patients (BMI >25), glucose hypometabolism was also found in the medial temporal lobe, but was not significant in other AD-vulnerable regions.
"We know that about 10 to 20 percent of middle-aged adults in the United States have SDB [defined as an apnea-hypopnea index greater than 5] and that the number jumps dramatically in those over the age of 65," said Dr. Osorio, noting that studies put the percentage of people over the age of 65 with SDB between 30 and 60 percent. "We don’t know why it becomes so prevalent, but one factor may be that some of these patients are in the earliest preclinical stages of AD."
According to Dr. Osorio, the biochemical harbingers of AD are present 15 to 20 years before any of its currently recognized symptoms become apparent.
The NYU study enrolled 68 cognitively normal elderly patients (mean age 71.4±5.6, range 64-87) who underwent two nights of home monitoring for SDB and were tested for at least one diagnostic indicator of AD. The researchers looked at P-Tau, T-Tau and Aβ42 in CSF, FDG-PET (to measure glucose metabolism), Pittsburgh compound B (PiB) PET to measure amyloid load, and/or structural MRI to measure hippocampal volume. Reduced glucose metabolism in AD-vulnerable regions, decreased hippocampal volume, changes in P-Tau, T-Tau and Aβ42, and increased binding of PiB-PET are recognized as markers of risk for AD and have been reported to be abnormal in healthy subjects before the disease onset.
Biomarkers for AD risk were found only among lean study participants with SDB. These patients showed a linear association between the severity of SDB and CSF levels of the biomarker P-Tau (F = 5.83, t=2.41, β=0.47; p< 0.05) and between SDB and glucose hypometabolism using FDG-PET, in the medial temporal lobe (F=6.34, t=-2.52, β=-0.57,p<0.05), the posterior cingulate cortex/precuneus (F=11.62, t=-3.41, β=-0.69, p<0.01) and a composite score of all AD-vulnerable regions (F=4.48, t=-2.11, β=-0.51, p<0.05). Lean SDB patients also showed smaller hippocampi when compared to lean controls (F=4.2, p<0.05), but no differences were found in measures of amyloid burden such as decreased Aβ42 in CSF or PiB positive scans.
Dr. Osorio and his colleagues are planning to test their hypothesis that very early stage preclinical AD brain injury that associates with these biomarkers can lead to SDB. They have proposed a two-year longitudinal study that would enroll 200 cognitively normal subjects, include AD biomarkers and treat those patients with moderate to severe SDB with continuous positive airway pressure, or CPAP, over time.
The purpose of the new study would be to determine the “direction” of causality between SDB and preclinical AD in elderly patients. After an initial assessment, the patients would be given CPAP to treat their sleep apnea. After six months, they would be evaluated again for biomarker evidence of AD.
"If the biomarkers change, it may indicate that SDB is causing AD," explained Dr. Osorio. "If they don’t change, the probable conclusion is that these patients are going to develop AD with or without CPAP, and that AD may either be causing the apneas or may simply coexist with SDB as part of aging."
Either way, Dr. Osorio believes the relationship between SDB and AD deserves further study.
"Sleep apnea skyrockets in the elderly, and this fact hasn’t been given the attention it deserves by the sleep world or the Alzheimer’s world," Dr. Osorio said. "Sleep particularly suffers from an outmoded perception that it is an inactive physiological process, when, in reality, it is a very active part of the day for the brain."](http://41.media.tumblr.com/6a53931d85c0688a19f1b1a50fac7dc1/tumblr_mn3hqygKfJ1rog5d1o1_500.jpg)
Study finds that sleep apnea and Alzheimer’s are linked
A new study looking at sleep-disordered breathing (SDB) and markers for Alzheimer’s disease (AD) risk in cerebrospinal fluid (CSF) and neuroimaging adds to the growing body of research linking the two.
But this latest study also poses an interesting question: Could AD in its “preclinical stages” also lead to SDB and explain the increased prevalence of SDB in the elderly?
The study will be presented at the ATS 2013 International Conference.
"It’s really a chicken and egg story," said Ricardo S. Osorio, MD, a research assistant professor at NYU School of Medicine who led the study. "Our study did not determine the direction of the causality, and, in fact, didn’t uncover a significant association between the two, until we broke out the data on lean and obese patients."
When the researchers did consider body mass, they found that lean patients (defined as having a body mass index <25) with SDB did possess several specific and non-specific biomarkers of AD risk (increased P-Tau and T-Tau in CSF, hippocampal atrophy using structural MRI, and glucose hypometabolism using FDG-PET in several AD-vulnerable regions). Among obese patients (BMI >25), glucose hypometabolism was also found in the medial temporal lobe, but was not significant in other AD-vulnerable regions.
"We know that about 10 to 20 percent of middle-aged adults in the United States have SDB [defined as an apnea-hypopnea index greater than 5] and that the number jumps dramatically in those over the age of 65," said Dr. Osorio, noting that studies put the percentage of people over the age of 65 with SDB between 30 and 60 percent. "We don’t know why it becomes so prevalent, but one factor may be that some of these patients are in the earliest preclinical stages of AD."
According to Dr. Osorio, the biochemical harbingers of AD are present 15 to 20 years before any of its currently recognized symptoms become apparent.
The NYU study enrolled 68 cognitively normal elderly patients (mean age 71.4±5.6, range 64-87) who underwent two nights of home monitoring for SDB and were tested for at least one diagnostic indicator of AD. The researchers looked at P-Tau, T-Tau and Aβ42 in CSF, FDG-PET (to measure glucose metabolism), Pittsburgh compound B (PiB) PET to measure amyloid load, and/or structural MRI to measure hippocampal volume. Reduced glucose metabolism in AD-vulnerable regions, decreased hippocampal volume, changes in P-Tau, T-Tau and Aβ42, and increased binding of PiB-PET are recognized as markers of risk for AD and have been reported to be abnormal in healthy subjects before the disease onset.
Biomarkers for AD risk were found only among lean study participants with SDB. These patients showed a linear association between the severity of SDB and CSF levels of the biomarker P-Tau (F = 5.83, t=2.41, β=0.47; p< 0.05) and between SDB and glucose hypometabolism using FDG-PET, in the medial temporal lobe (F=6.34, t=-2.52, β=-0.57,p<0.05), the posterior cingulate cortex/precuneus (F=11.62, t=-3.41, β=-0.69, p<0.01) and a composite score of all AD-vulnerable regions (F=4.48, t=-2.11, β=-0.51, p<0.05). Lean SDB patients also showed smaller hippocampi when compared to lean controls (F=4.2, p<0.05), but no differences were found in measures of amyloid burden such as decreased Aβ42 in CSF or PiB positive scans.
Dr. Osorio and his colleagues are planning to test their hypothesis that very early stage preclinical AD brain injury that associates with these biomarkers can lead to SDB. They have proposed a two-year longitudinal study that would enroll 200 cognitively normal subjects, include AD biomarkers and treat those patients with moderate to severe SDB with continuous positive airway pressure, or CPAP, over time.
The purpose of the new study would be to determine the “direction” of causality between SDB and preclinical AD in elderly patients. After an initial assessment, the patients would be given CPAP to treat their sleep apnea. After six months, they would be evaluated again for biomarker evidence of AD.
"If the biomarkers change, it may indicate that SDB is causing AD," explained Dr. Osorio. "If they don’t change, the probable conclusion is that these patients are going to develop AD with or without CPAP, and that AD may either be causing the apneas or may simply coexist with SDB as part of aging."
Either way, Dr. Osorio believes the relationship between SDB and AD deserves further study.
"Sleep apnea skyrockets in the elderly, and this fact hasn’t been given the attention it deserves by the sleep world or the Alzheimer’s world," Dr. Osorio said. "Sleep particularly suffers from an outmoded perception that it is an inactive physiological process, when, in reality, it is a very active part of the day for the brain."