Neurons in the nose could be the key to early, fast, and accurate diagnosis, says a TAU researcher
A debilitating mental illness, schizophrenia can be difficult to diagnose. Because physiological evidence confirming the disease can only be gathered from the brain during an autopsy, mental health professionals have had to rely on a battery of psychological evaluations to diagnose their patients.
Now, Dr. Noam Shomron and Prof. Ruth Navon of Tel Aviv University’s Sackler Faculty of Medicine, together with PhD student Eyal Mor from Dr. Shomron’s lab and Prof. Akira Sawa of Johns Hopkins Hospital in Baltimore, Maryland, have discovered a method for physical diagnosis — by collecting tissue from the nose through a simple biopsy. Surprisingly, collecting and sequencing neurons from the nose may lead to “more sure-fire” diagnostic capabilities than ever before, Dr. Shomron says.
This finding, which was reported in the journal Neurobiology of Disease, could not only lead to a more accurate diagnosis, it may also permit the crucial, early detection of the disease, giving rise to vastly improved treatment overall.
From the nose to diagnosis
Until now, biomarkers for schizophrenia had only been found in the neuron cells of the brain, which can’t be collected before death. By that point it’s obviously too late to do the patient any good, says Dr. Shomron. Instead, psychiatrists depend on psychological evaluations for diagnosis, including interviews with the patient and reports by family and friends.
For a solution to this diagnostic dilemma, the researchers turned to the olfactory system, which includes neurons located on the upper part of the inner nose. Researchers at Johns Hopkins University collected samples of olfactory neurons from patients diagnosed with schizophrenia and a control group of non-affected individuals, then sent them to Dr. Shomron’s TAU lab.
Dr. Shomron and his fellow researchers applied a high-throughput technology to these samples, studying the microRNA of the olfactory neurons. Within these molecules, which help to regulate our genetic code, they were able to identify a microRNA which is highly elevated in those with schizophrenia, compared to individuals who do not have the disease.
"We were able to narrow down the microRNA to a differentially expressed set, and from there down to a specific microRNA which is elevated in individuals with the disease compared to healthy individuals," explains Dr. Shomron. Further research revealed that this particular microRNA controls genes associated with the generation of neurons.
In practice, material for biopsy could be collected through a quick and easy outpatient procedure, using a local anesthetic, says Dr. Shomron. And with microRNA profiling results ready in a matter of hours, this method could evolve into a relatively simple and accurate test to diagnose a very complicated illness.
Early detection, early intervention
Though there is much more to investigate, Dr. Shomron has high hopes for this diagnostic method. It’s important to determine whether this alteration in microRNA expression begins before schizophrenic symptoms begin to exhibit themselves, or only after the disease fully develops, he says. If this change comes near the beginning of the timeline, it could be invaluable for early diagnostics. This would mean early intervention, better treatment, and possibly even the postponement of symptoms.
If, for example, a person has a family history of schizophrenia, this test could reveal whether they too suffer from the disease. And while such advanced warning doesn’t mean a cure is on the horizon, it will help both patient and doctor identify and prepare for the challenges ahead.
(Source: aftau.org)
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The age at which a child with autism is diagnosed is related to the particular suite of behavioral symptoms he or she exhibits, new research from the University of Wisconsin-Madison shows.
Certain diagnostic features, including poor nonverbal communication and repetitive behaviors, were associated with earlier identification of an autism spectrum disorder, according to a study in the April issue of the Journal of the American Academy of Child and Adolescent Psychiatry. Displaying more behavioral features was also associated with earlier diagnosis.
"Early diagnosis is one of the major public health goals related to autism," says lead study author Matthew Maenner, a researcher at the UW-Madison Waisman Center. "The earlier you can identify that a child might be having problems, the sooner they can receive support to help them succeed and reach their potential."
But there is a large gap between current research and what is actually happening in schools and communities, Maenner adds. Although research suggests autism can be reliably diagnosed by age 2, the new analysis shows that fewer than half of children with autism are identified in their communities by age 5.
One challenge is that autism spectrum disorders (ASD) are extremely diverse. According to the criteria outlined in the Diagnostic and Statistical Manual of Mental Disorders Fourth Edition - Text Revision (DSM-IV-TR), the standard handbook used for classification of psychiatric disorders, there are more than 600 different symptom combinations that meet the minimum criteria for diagnosing autistic disorder, one subtype of ASD.
Previous research on age at diagnosis has focused on external factors such as gender, socioeconomic status, and intellectual disability. Maenner and his colleagues instead looked at patterns of the 12 behavioral features used to diagnose autism according to the DSM-IV-TR.
He and Maureen Durkin, a UW-Madison professor of population health and pediatrics and Waisman Center investigator, studied records of 2,757 8-year- olds from 11 surveillance sites in the nationwide Autism and Developmental Disabilities Monitoring Network, run by the Centers for Disease Control and Prevention (CDC). They found significant associations between the presence of certain behavioral features and age at diagnosis.
"When it comes to the timing of autism identification, the symptoms actually matter quite a bit," Maenner says.
In the study population, the median age at diagnosis (the age by which half the children were diagnosed) was 8.2 years for children with only seven of the listed behavioral features but dropped to just 3.8 years for children with all 12 of the symptoms.
The specific symptoms present also emerged as an important factor. Children with impairments in nonverbal communication, imaginary play, repetitive motor behaviors, and inflexibility in routines were more likely to be diagnosed at a younger age, while those with deficits in conversational ability, idiosyncratic speech and relating to peers were more likely to be diagnosed at a later age.
These patterns make a lot of sense, Maenner says, since they involve behaviors that may arise at different developmental times. The findings suggest that children who show fewer behavioral features or whose autism is characterized by symptoms typically identified at later ages may face more barriers to early diagnosis.
But they also indicate that more screening may not always lead to early diagnoses for everyone.
"Increasing the intensity of screening for autism might lead to identifying more children earlier, but it could also catch a lot of people at later ages who might not have otherwise been identified as having autism," Maenner says.
(Source: news.wisc.edu)
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MRI Can Screen Patients for Alzheimer’s Disease or Frontotemporal Lobar Degeneration, Using Penn-designed Model
When trying to determine the root cause of a person’s dementia, using an MRI can effectively and non-invasively screen patients for Alzheimer’s disease or Frontotemporal Lobar Degeneration (FTLD), according to a new study by researchers from the Perelman School of Medicine at the University of Pennsylvania. Using an MRI-based algorithm effectively differentiated cases 75 percent of the time, according to the study, published in the December 26th, 2012, issue of Neurology, the medical journal of the American Academy of Neurology. The non-invasive approach reported in this study can track disease progression over time more easily and cost-effectively than other tests, particularly in clinical trials testing new therapies.
Researchers used the MRIs to predict the ratio of two biomarkers for the diseases - the proteins total tau and beta-amyloid - in the cerebrospinal fluid. Cerebrospinal fluid analyses remain the most accurate method for predicting the disease cause, but requires a more invasive lumbar puncture. “Using this novel method, we obtain a single biologically meaningful value from analyzing MRI data in this manner and then we can derive a probabilistic estimate of the likelihood of Alzheimer’s or FTLD,” said the study’s lead author, Corey McMillan, PhD, of the Perelman School of Medicine and Frontotemporal Degeneration Center at the University of Pennsylvania.
Using the MRI prediction method was 75 percent accurate at identifying the correct diagnosis in both patients with pre-confirmed disease diagnoses and those with biomarker levels confirmed by lumbar punctures, which shows comparable overlap between accuracy of the MRI and lumbar puncture methods. “For those remaining 25 percent of cases that are borderline, a lumbar puncture testing spinal fluid may provide a more accurate estimate of the pathological diagnosis.”
Accurate tests to measure disease progression are very important in neurodegenerative diseases, especially as clinical trials test new therapies to slow or stop the progression or the disease. Biomarkers for neurodegenerative diseases have been steadily improving, with new developments including spinal fluid tests detecting tau and amyloid-beta protein levels and other neuroimaging techniques developed at Penn Medicine, as part of the Alzheimer’s Disease Neuroimaging Initiative. While a spinal fluid test can be used to accurately pinpoint whether disease-specific proteins are present, the test requires a more invasive lumbar puncture making it more difficult to repeat over time. And for studies using other imaging techniques, such as test measuring whole brain volume, reduced sensitivity of the measurement requires more patients to be enrolled in clinical trials for statistical power to be achieved.
“Since this method yields a single biological value, it is possible to use MRI to screen patients for inclusion in clinical trials in a cost-effective manner and to provide an outcome measure that optimizes power in drug treatment trials,” the authors concluded.
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PredictAD software promises early diagnosis of Alzheimer’s
Scientists at VTT Technical Research Centre in Finland have developed new software called PredictAD that could significantly boost the early diagnosis of Alzheimer’s disease.
The comparative software contrasts patient’s measurements with those of other patients kept in large databases, then visualizes the status of the patient with an index and graphics.
The support system and imaging methods were developed by VTT and Imperial College London.
The researchers used material compiled in the U.S. by the Alzheimer’s Disease Neuroimaging Initiative based on the records of 288 patients with memory problems. Nearly half of them, or 140 individuals, were diagnosed with Alzheimer’s disease on average 21 months after the initial measurements, which is about the same as the current European average of 20 months.
The researchers concluded that half of the patients could have been diagnosed with the disease around a year earlier, or nine months after the initial measurements. They say the accuracy of the predictions was comparable to clinical diagnosis.
There are several advantages of an early diagnosis of Alzheimer’s. It can delay institutionalization and slow down the progress of the disease. It is also advantageous from the clinical trials perspective because if patients caught early can be included in the trials, treatment is likely to be more effective.
Working towards the same goal, researchers at Lancaster University in the U.K. recently developed an eye test method to detect early signs of Alzheimer’s.
The VTT researchers will spend the next five years carrying out the test at memory clinics in Europe. They also hope to expand its scope to include other illnesses that cause dementia. According to 2010 figures, an estimated 35.6 people live with dementia worldwide, and that number is expected to rise to 65.7 million by 2030.
The findings of the research were published in the Journal of Alzheimer’s Disease in November 2012. VTT cooperated with the University of Eastern Finland and Copenhagen University Hospital Rigshospitalet on this project.
Filed under alzheimer's disease PredictAD dementia software diagnosis memory science
Anatomical Brain Images Alone Can Accurately Diagnose Chronic Neuropsychiatric Illnesses
Objective
Diagnoses using imaging-based measures alone offer the hope of improving the accuracy of clinical diagnosis, thereby reducing the costs associated with incorrect treatments. Previous attempts to use brain imaging for diagnosis, however, have had only limited success in diagnosing patients who are independent of the samples used to derive the diagnostic algorithms. We aimed to develop a classification algorithm that can accurately diagnose chronic, well-characterized neuropsychiatric illness in single individuals, given the availability of sufficiently precise delineations of brain regions across several neural systems in anatomical MR images of the brain.
Methods
We have developed an automated method to diagnose individuals as having one of various neuropsychiatric illnesses using only anatomical MRI scans. The method employs a semi-supervised learning algorithm that discovers natural groupings of brains based on the spatial patterns of variation in the morphology of the cerebral cortex and other brain regions. We used split-half and leave-one-out cross-validation analyses in large MRI datasets to assess the reproducibility and diagnostic accuracy of those groupings.
Results
In MRI datasets from persons with Attention-Deficit/Hyperactivity Disorder, Schizophrenia, Tourette Syndrome, Bipolar Disorder, or persons at high or low familial risk for Major Depressive Disorder, our method discriminated with high specificity and nearly perfect sensitivity the brains of persons who had one specific neuropsychiatric disorder from the brains of healthy participants and the brains of persons who had a different neuropsychiatric disorder.
Conclusions
Although the classification algorithm presupposes the availability of precisely delineated brain regions, our findings suggest that patterns of morphological variation across brain surfaces, extracted from MRI scans alone, can successfully diagnose the presence of chronic neuropsychiatric disorders. Extensions of these methods are likely to provide biomarkers that will aid in identifying biological subtypes of those disorders, predicting disease course, and individualizing treatments for a wide range of neuropsychiatric illnesses.
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Autism Blood Test Shows Promise
Diagnosing autism could soon be much simpler, with researchers saying this week that they’ve developed a blood test that appears to identify those with the disorder even before symptoms are apparent.
The early-stage test developed at Boston Children’s Hospital may be able to flag about two-thirds of those with autism, researchers reported in the journal PLOS ONE.
Currently, clinicians rely on observation to screen children for autism. Most kids are not diagnosed until after age 4, according to the U.S. Centers for Disease Control and Prevention.
But a blood test offers the promise of flagging kids and potentially enrolling them in early intervention programs even before symptoms appear.
In order to develop the test, researchers analyzed blood samples from 66 boys with autism and 33 without the developmental disorder in an effort to establish patterns. Ultimately, the scientists were able to focus on a group of 55 genes that they used to successfully identify autism with 68 percent accuracy in a second test group made up of 104 people with autism and 82 controls.
“It’s clear that no single mutation or even a single pathway is responsible for all cases,” said Isaac Kohane of Boston Children’s Hospital who worked on the research. “By looking at this 55-gene signature, which can capture disruptions in multiple pathways at once, we can say with about 70 percent accuracy, ‘this child does not have autism,’ or ‘this child could be at risk,’ putting him at the head of the queue for early intervention and evaluation. And we can do it relatively inexpensively and quickly.”
The blood test is not yet ready for prime time, researchers said, but it has been licensed to the company SynapDx for further exploration and potential commercialization.
Filed under autism blood test diagnosis neurodevelopmental disorders ASD genetics science
Researchers Study Cry Acoustics of Infants to Determine Risk for Autism
Autism is a poorly understood family of related conditions. People with autism generally lack normal social interaction skills and engage in a variety of unusual and often characteristic behaviors, such as repetitive movements. While there is no specific medical treatment for autism, some success has been shown with early behavioral intervention.
Understanding the importance of early diagnosis, researchers at Women & Infants’Brown Center for the Study of Children at Riskin collaboration with researchers at University of Pittsburgh have been studying the cry acoustics of six-month-old infants. Their research has recently been published in Autism Research.
“Because we can measure various aspects of babies’ cries from the earliest days of life, it may be possible to use this technique to identify risk for neurological problems such as autism long before we can detect behavioral differences,” said Stephen J. Sheinkopf, PhD, lead researcher, psychologist at the Brown Center for the Study of Children at Risk, and assistant professor (research) in the Department of Psychiatry and Human Behavior at The Warren Alpert Medical School of Brown University.
The study examined ways in which infants at risk for autism produced cries as compared to the cries of low-risk infants. Recordings of babies’ cries were excerpted from vocal and video recordings of six-month-old infants at risk for autism spectrum disorder (ASD) and those with low risk. Infants were considered to be at risk if they had an older sibling with a confirmed ASD diagnosis.
Cries were categorized as either pain related or non-pain related based on observations of the videotapes. At-risk infants produced pain related cries with higher and more variable fundamental frequency (commonly referred to as “pitch”) as compared to low-risk infants. A small number of the at-risk infants were later diagnosed with an ASD at 36 months of age. The cries for these babies had among the highest fundamental frequency values and also differed in other acoustic characteristics.
“These findings demonstrate the potential of this approach for babies as young as six months of age,” said Dr. Sheinkopf.
(Photo: Thinkstock Source: Getty Images)
Filed under autism ASD infants cry acoustics diagnosis neuroscience psychology science
Health professionals may soon have a new method of diagnosing Parkinson’s disease, one that is noninvasive and inexpensive, and, in early testing, has proved to be effective more than 90 percent of the time.
In addition, this new method has the potential to track the progression of Parkinson’s, as well as measure the effectiveness of treatments for the disorder, said Rahul Shrivastav, professor and chairperson of Michigan State University’s Department of Communicative Sciences and Disorders and a member of the team developing the new method.
It involves monitoring a patient’s speech patterns – specifically, movement patterns of the tongue and jaw.
“In Parkinson’s disease, a common limitation is that the movements become slow and have a reduced range,” said Shrivastav. “We believe we see this pattern in speech too – the tongue doesn’t move as far as it should, doesn’t move as quickly as it should and produces subtle changes in speech patterns.”
This method is particularly sensitive to Parkinson’s disease speech and, Shrivastav said, is effective with only two seconds of speech.
“That’s significant in several ways: The detection methodology is noninvasive, easy to administer, inexpensive and capable of being used remotely and in telemedicine applications,” he said.
Presently there are no tried-and-true methods for diagnosing Parkinson’s. Shrivastav said if a person is showing early symptoms of the disease, which include tremors, slower movements or rigid muscles, he or she is given a drug to treat the disease.
“If the symptoms go away,” he said, “then it’s assumed you must have Parkinson’s disease.”
In more advanced cases, he said, symptoms are usually prominent enough that it is fairly easy to diagnose.
Parkinson’s disease is a neurological disorder affecting a half million people in the United States, with 50,000 newly diagnosed cases every year. It occurs when nerve cells in the brain stop producing a chemical called dopamine, which helps control muscle movement. Without dopamine, the nerve cells cannot properly send messages, leading to the loss of muscle function.
While there is no cure for Parkinson’s disease, early detection is particularly important since the treatments currently available for controlling symptoms are most effective at that stage.
(Source: news.msu.edu)
Filed under parkinson's disease diagnosis noninvasive speech patterns neuroscience psychology science
Study on ADHD, Provide New Insight Into Prevalence and Treatment Needs
Attention Deficit Hyperactivity Disorder is both under and over diagnosed.
That’s the result of one of the largest studies conducted on ADHD in the United States, published in the Journal of Attention Disorders.
A substantial number of children being treated for ADHD may not have the disorder, while many children who do have the symptoms are going untreated, according to the 10-year Project to Learn about ADHD in Youth (PLAY) study funded by the National Center on Birth Defects and Developmental Disabilities of the Centers of Disease Control and Prevention
"Childhood ADHD is a major public health problem. Many studies rely on parent reporting of an ADHD diagnosis, which is a function of both the child’s access to care in order to be diagnosed, and the parent’s perception that there is a problem," said Robert McKeown, of the University of South Carolina’s Arnold School of Public Health, who led the South Carolina portion of the study.
"Further complicating our understanding of the prevalence of ADHD and its treatment is that the diagnosis often is made by a clinician who has little experience assessing and diagnosing mental disorders. As a result, ADHD is both under and over diagnosed," said McKeown, distinguished professor emeritus in the department of epidemiology and biostatistics.
The study, conducted between 2002-2012, was a collaborative research project with the University of South Carolina’s Arnold School and School of Medicine and the University of Oklahoma’s Health Sciences Center.
"To our knowledge, this is the largest community-based epidemiologic study of ADHD to date," McKeown said.
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Genetic diseases diagnosed within 50 hours
The new technology screens the whole genome of the baby from a drop of their blood before homing in on abnormalities in single genes that could explain their ill health.
Genetic diseases are thought to affect up to one in a hundred children and are one of the leading causes of admission to intensive care units immediately after birth.
In about 500 of the conditions - including Krabbe disease, a nervous system disorder - early treatment can prevent the development of severe disability and life-threatening symptoms.
Most of the diseases are extremely rare and many are unfamiliar to doctors, but analysing a baby’s genes to find the cause of their condition currently takes up to six weeks.
Researchers from Children’s Mercy Hospital in Kansas City said this could be cut down to 50 hours using the new method, described in the Science Translational Medicine journal.
Filed under genetic diseases diagnosis genome sequencing genomics neuroscience psychology science
