Biomarkers and Autism Research
Synopsis: Information regarding efficacy biomarkers for autism workshop where participants agreed biomarker development should be a priority for autism research.1
Author: Thomas C. Weiss Contact: Disabled World
Published: 2014-01-14 Updated: 2017-02-19
The U.S. National Institutes of Health defines, 'biomarkers,' as, 'biological characteristics that can be objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacological responses to therapeutic intervention.'
In medicine, a biomarker is a measurable characteristic that reflects the severity or presence of some disease state. More generally a biomarker is anything that can be used as an indicator of a particular disease state or some other physiological state of an organism. Biomarkers can be classified based on different parameters. They can be classified based on their characteristics such as imaging biomarkers (CT, PET, MRI) or molecular biomarkers.
Researchers can use biomarkers as measures to test the efficacy of therapies in early-stage trials. SFARI held an informal meeting at Stony Brook University in New York to discuss efficacy biomarkers for autism. The goal was to prompt discussion concerning potential biomarkers and to build and strengthen collaborations among attendees. Workshop participants agreed that biomarker development should be a priority for autism research and called for an improved, 'second wave,' of biomarker research which would set more realistic expectations for biomarkers than have existed in the past.
Researchers stated For one, they said, biomarkers should not replace clinical diagnosis. Biomarkers can, however, identify subgroups of individuals within the autism spectrum who could be that biomarkers should not replace clinical diagnosis. They said that biomarkers can; however, identify subgroups of people within the autism spectrum who could be treated with specific interventions. Despite the extreme heterogeneity of autism there is a highly conserved mechanism of social behavior that goes awry in people with the disorder. Biomarkers can help scientists to devise a therapeutic approach that may be applied across the spectrum.
It is important to acknowledge that biomarker measures might not be fixed across a person's lifetime, particularly in a developmental disorder such as autism, concluded the attendees. When interpreting functional significance and predicting clinical outcomes, Professor of Pediatrics and Neuroscience at Harvard Medical School's Charles Nelson stated, 'A single measure at a single time point can be very misleading.' Even the direction of a measure compared with controls, such as whether brain activity is suppressed or elevated, may vary.
Electroencephalography (EEG) measurements, for example, reveal differences in brain activity at 18 months of age between the siblings of children with autism, who are at risk of developing the disorder, and typical controls, according to Mr. Nelson. At age 24 months; however, measurements from the two groups become more similar. If the trend were to continue, measurements from the high-risk siblings might show a completely different pattern when compared to controls when they reach the age of 36 months said Mr. Nelson.
Biomarker development becomes further complicated by the fact that due to clinical testing regulations, researchers usually need to validate biomarkers in adults. These markers; however, are most useful for identifying young children who are candidates for early interventions. Researchers need to replicate biomarkers and use them to predict outcome in independent samples according to the meeting attendees. There are a number of reports of potential biomarkers published, but few make it through the scientific process of verification according to Deputy Director of the National Institute of Neurological Disorders and Stroke's Walter Koroshetz. Participants also advocated for a collaborative approach to biomarker research because biomarkers are most powerful when they combine measures from multiple disciplines.
Chart showing types of biomarkers in autism
Participants considered a variety of biomarkers as they met. The biomarkers included different types such as:
The participants also addressed whether these types of biomarkers should be used alone or combined into panels. Biomarkers may be either distal or proximal, meaning they are either close to the clinical manifestation of the condition, or more representative of the underlying mechanism. Several of the researchers showed of proximal, or clinical, biomarkers.
The fact that autism is associated with defects in attention to social cues means people with the disorder might miss out on opportunities for social learning. The deficiencies are associated with underlying neural processes, specifically electrophysiological responses to social stimuli according to Chief Science Officer at Autism Speaks, Geraldine Dawson. People with autism also show atypical responses in the reward center of their brains, many times preferring monetary to social rewards.
Director of Emory University's Marcus Autism Center in Atlanta, Ami Klin, uses eye-tracking technology to show that people with look at different aspects of a social scenario than others do. As with eye-tracking, the best biomarkers should capture what happens in naturalistic social environments because these are the situations people with autism have the most trouble with, according to Ami Klin.
The, 'Q-sensor,' is a wireless wristband developed by Matthew Goodwin and colleagues at the Massachusetts Institute of Technology Media Lab. The sensor permits researchers to track in real time body motion and activity of a person's sympathetic nervous system. The sympathetic nervous system regulates heart rate, sweating and pupil dilation. The technology might allow researchers to develop biomarkers of arousal, stress and anxiety in everyday life for people with autism. Goodwin also showed examples of video technology and computer analysis techniques used to capture behaviors in real life settings.
The measures are especially suited to assessing and quantifying repetitive behaviors and atypical gait in people with autism. Repetitive behaviors are proposed to be 1 of only 2 core domains of autism in the Diagnostic and Statistical Manual of Mental Disorders DSM-5. Children with autism also have atypical pupillary responses, such as delays in pupil constriction in response to light stimulation according to Professor of Pediatrics and Pathology at the University of Missouri's Thompson Center for Autism and Developmental Disorders' Judith Miles. Ms. Miles has done significant work on, 'dysmorphology,' or atypical facial and physical features - another potential biomarker for autism. As an example, using three-dimensional facial imaging, Ms. Miles has shown that children with autism have different patterns of facial features than controls do.
Brain imaging measures might represent biomarkers that lie in the middle of the distal-proximal axis suggested Professor of Radiology at the Children's Hospital of Philadelphia, Timothy Roberts. Due to this, imaging biomarkers are ideal for translation into the clinic and as endpoints for drug trials, according to Mr. Roberts. For example, brain responses to changes in sound frequency, measured by magnetoencephalography (MEG), are delayed in children with autism when compared with controls and children who experience language delay.
Functional magnetic resonance imaging has also identified patterns of brain activity in different brain regions in children with autism. These measures; however, are at times shared by unaffected siblings of children with autism, and might represent, 'endophenotypes,' which indicate underlying genetic risk factors. Unaffected siblings may also have compensatory biomarkers that protect them from developing autism. It is difficult to separate out which biomarkers represent the underlying biology that causes autism and which arise as a consequence of the disorder, according to Associate Professor of Psychology at Yale Child Study Center's Kevin Pelphrey. Researchers also discussed biomarkers more distal to the manifestation of autism, to include genetic and proteomic measures.
Biomarkers based on genetic differences may help distinguish people with autism based on the underlying mechanism of their autism said Professor of Neurology at the University of California, Los Angeles Daniel Geschwind. However, gene expression differences between the blood cells of people with autism and their siblings represent a, 'weak signal,' according to Professor Geschwind.
Professor Geschwind has analyzed patterns of gene expression in the blood cells of 200 people with autism and 200 siblings who do not have autism and found distinct differences. Yet the distinct patterns cannot be reproduced in another 200 people with autism. People with autism do have reproducibly different gene expression patterns from unrelated controls, but the difference is not as meaningful as showing differences with siblings who are not affected because siblings carry the same genetic risk, yet do not have a diagnosis, says Professor Geschwind.
Researchers can use various mouse models of autism to link a particular genetic defect with mouse behaviors relevant to autism symptoms and with biomarkers such as gene expression profiles, blood pressure or heart rate says Chief of the Laboratory of Behavioral Neuroscience at the National Institute of Mental Health in Bethesda, Jacqueline Crawley. Rigorously replicated behavioral profiles in mouse models are also well-suited for testing potential autism therapies.
Some mice have significant defects in the levels of neurons that dampen signals in the brain and express the neurotransmitter, 'gamma aminobutyric acid (GABA),' reported Professor of Clinical Neurobiology at the University of Heidelberg's Hannah Monyer. Professor Monyer has shown that GABA neurons can make long-range connections in the brain, implicating them in connectivity defects seen in people with autism.
Those in attended who are experts outside of autism research presented approaches to biomarker identification that are not yet common practice in the autism field. For example, there are nearly 6,000 peer-reviewed articles that cross-reference cancer and proteomics, but only 9 that do so for autism and proteomics. Proteomics is a powerful way to identify changes in gene expression in the blood of people with autism. Researchers can screen thousands of proteins at once and resolve differences among samples using mass spectrometry. Because mass spectrometry may validate these proteomic markers in people, researchers can screen for hundreds of different potential biomarkers at once. Different patterns of protein expression might correlate with the level of symptoms and identify groups of people with specific traits.
Another proteomics approach is to use a peptoid library, which detects antibodies circulating in blood. The approach could be more powerful than proteomic screens because it detects the body's immune response to protein levels, which may be amplified compared with the protein levels themselves.
The workshop ended with a discussion of next steps, to include plans to continue the discussion and pursue collaborations online. Attendees set priorities for developing autism biomarkers such as using statistical and computational approaches to aggregate data and look for dynamic trends in biomarkers over the course of development. They also agreed that the field should identify the most promising biomarkers and ensure that data collection and research into these areas are standardized, permitting researchers to share data across different studies.
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