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Autism detection improved by multimodal neuroimaging
Autism detection improved by multimodal neuroimaging
Combined measurements of brain anatomy, connectivity and neurochemistry distinguish autism spectrum disorder subjects from controls.

rajeshRajesh Kana and Lauren LiberoIn an ancient Indian parable, a group of blind men touches different parts of a large animal to find what it is. Only when they share the descriptions of an ear, tail, trunk and leg do they know it is an elephant.

Rajesh Kana, Ph.D., of the University of Alabama at Birmingham has brought a similar approach to the classification, and eventual diagnosis, of autism. Kana and colleagues are the first to combine three different measures of the brain — anatomy, the connectivity between different brain regions, and levels of a neurochemical — to distinguish people with autism spectrum disorder (ASD) from matched, typically developing peers. This multimodal approach, published online this week in the journal “Cortex,” is distinct from many previous studies that have used a single neuroimaging measure. While those studies uncovered widespread functional and anatomical brain abnormalities in ASD, the results were not highly consistent, possibly reflecting the complex brain pathology in autism spectrum disorders.

At this time, autism diagnosis is based on behavior. Kana’s multimodal neuroimaging-based classification is a step toward a possible biomarker for autism and possibly diagnosing autism at an early age, perhaps as early as 6 months, when the brain is very plastic and intervention might be more effective. “But that’s a long, long way off,” said Kana, an associate professor in the Department of Psychology in the UAB College of Arts and Sciences and an associate scientist in UAB’s Civitan International Research Center.

This preliminary study needs to be validated with a larger sample, Kana said; but it “emphasizes that the brain abnormalities in autism may not be confined to a single area. Rather, they are distributed across different areas at multiple levels and layers.”

At this time, autism diagnosis is based on behavior. Kana’s multimodal neuroimaging-based classification is a step toward a possible biomarker for autism and possibly diagnosing autism at an early age, perhaps as early as 6 months, when the brain is very plastic and intervention might be more effective.

Kana, corresponding author of the study, examined 19 high-functioning adults with ASD and 18 typically developing peers, who were matched for age and intelligence. Using the 3-Tesla scanner in the UAB Civitan Functional Neuroimaging Laboratory, Kana’s group performed structural magnetic resonance imaging (MRI) to measure brain cortical thickness (volume data), diffusion tensor imaging to measure the connectivity of white-matter fibers of the brain, and proton magnetic resonance spectroscopy to measure brain neurotransmitters like N-acetylaspartate. The brain’s white-matter areas are like electrical cables that link different regions of the brain.

The same MRI machine does all three measurements, using different settings for each. The volume data take 10 minutes, connectivity measurements take12 minutes and the spectroscopy takes 30 minutes. While some participants were comfortable in the tight space of an MRI, others needed training in a nonfunctioning simulator MRI before any testing.

Kana’s group found significant differences in some specific measurements using each of the three neuroimaging approaches. They then combined certain of these key differences into a decision tree model — akin to the differential diagnosis flowchart used by clinicians. This decision-tree model gave a classification accuracy of 91.9 percent for distinguishing ASD subjects from the controls.

“Autism is such a heterogeneous disorder, and every patient presents with different symptoms and levels of severity,” said Lauren Libero, Ph.D., first author of the study. “That makes it really challenging to try to find one explanation within the brain for the very complex symptoms of autism.”

“This study is important,” said Libero who is now a post-doctoral scholar at the University of California-Davis MIND Institute(Medical Investigation of Neurodevelopmental Disorders), “because we found that different combinations of alterations in the brain could lead to the same or different levels of symptom severity. This could explain why previous studies have found varying results when it comes to which areas of the brain are affected in autism. There likely is not one uniform pattern affecting everyone with autism.” 

“We also found that combining different MRI techniques led to better classification of our participants with autism,” Libero said. “Most previous studies have focused on using one technique at a time, even though we have evidence that there are alterations in the brain in autism in terms of structure, white-matter connectivity, and brain chemical concentrations. When we are looking at a disorder that is so complex, multiple modalities of investigation can be more efficient to separate autism from other disorders, or to identify subgroups within autism. Our study found a way to combine measures of brain structure, white matter diffusion, and neurochemical concentration to classify our participants by their diagnosis, as well as their level of autism severity.”

This start by Kana and colleagues to unlock the neuropathology of autism needs to be validated using a larger sample of subjects to improve the generalizability of these preliminary findings. Kana also wants to look at lower-functioning ASD subjects, younger ASD children and a larger number of female participants.

Lucina Uddin, Ph.D., assistant professor in the Department of Psychology at the University of Miami, who was not part of the research team, said, "The combination of multiple neuroimaging modalities is a clear strength of the current study, and the authors are to be commended for undertaking the difficult task of trying to reconcile results from methods designed to tap different aspects of brain structure and function. Although the classification results are promising, application to new and larger datasets will be critical for testing how well the classifier built here deals with new cases. In addition, it will be interesting to see whether data collected from much younger children can be classified using this method, as the disorder typically emerges in the first few years of life.”

Specific significant findings in the Libero et al. Cortex paper include:

  • Increased cortical thickness in ASD participants, compared to controls, across the left cingulate, left pars opercularis of the inferior frontal gyrus, left inferior temporal cortex and the right precuneus;
  • Reduced cortical thickness in the right cuneus and right precentral gyrus;
  • Reduced white matter connectivity (as measured by reduced fractional anisotropy and increased radial diffusivity) for two discrete clusters on the forceps minor of the corpus callosum; and
  • Reduction in N-acetylaspartate in the dorsal anterior cingulate cortex.

Just three of these significant differences — radial diffusivity in the right forceps minor, cortical thickness in the left pars opercularis and fractional anisotropy in the left forceps minor —yielded the best decision tree for distinguishing ASD participants from controls.

Kana and colleagues also built a decision tree with five of the significant findings that sorted ASD participants by disease severity.

The other authors of the paper are Thomas Deramus, graduate student in the UAB Department of Psychology; Adrienne Lahti, M.D., the Patrick H. Linton Professor in the UAB Department of Psychiatry and director of UAB’s Division of Behavioral Neurobiology; and Gopikrishna Deshpande, Ph.D., assistant professor in the Auburn University Department of Electrical and Computer Engineering.

ASD is a complex disorder of brain development. ASD patients show a triad of impairments: impaired social interaction with others, impaired verbal and nonverbal communication, and impaired play and imaginative activities. 

Upcoming MHRC Health Disparities Research Symposium examines the science of health disparities
Upcoming MHRC Health Disparities Research Symposium examines the science of health disparities
Guest speaker and former Surgeon General Regina Benjamin among many who will see new approaches and successful models of current health-disparities research.

mona fouad 2012 Mona FouadThe UAB Minority Health & Health Disparities Research Center (MHRC) will host the 2015 UAB Health Disparities Research Symposium, “The Science of Health Disparities: From Social Causes to Personalized Medicine,” March 17-18 in the DoubleTree by Hilton on 20th Street South in Birmingham. In its 10th year, the symposium highlights work by undergraduate, graduate and faculty researchers in the field of health disparities.

“The symposium showcases the work being done to reduce health inequities in Alabama and our nation. It provides an overview of the latest in health-disparities research. Scientists and scholars look to it as an excellent opportunity to share discoveries, new approaches and successful models,” said Mona Fouad, M.D., MPH, director and professor, UAB Division of Preventive Medicine, and director of the UAB MHRC.

Speaking at the dinner Tuesday, March 17, will be Regina Benjamin, M.D., MBA, the 18th surgeon general and professor and endowed chair in the Xavier University of Louisiana Department of Public Health Science.

The 2015 conference is co-sponsored by three national transdisciplinary collaborative centers for health-disparities research: the Mid-South TCC, focused on the social determinants of health and led by Fouad; the Center for Healthy African American Men through Partnerships (CHAAMPS), led by Selwyn Vickers, M.D., dean of the UAB School of Medicine; and the Gulf States Health Policy Center, led by Benjamin.

The symposium will feature seven plenary sessions:

  • Social Conditions as a Fundamental Cause of Health Disparities – Bruce Link, Ph.D., professor of epidemiology and sociomedical sciences, Columbia University Mailman School of Public Health
  • Challenges and Opportunities in Studying the Multilevel Determinants of Health – Ana Diez Roux, M.D., Ph.D., dean and Distinguished Professor of Epidemiology, Drexel University School of Public Health
  • Social Consequences of Genetic Explanations for Racial Differences in Health – Jo Phelan, Ph.D., professor of sociomedical sciences, Columbia University Mailman School of Public Health
  • Personalized Medicine: Implications for Disparities in Drug Response – Nita Limdi, Pharm.D., Ph.D., professor UAB School of Medicine; director, UAB Personalized Medicine Institute
  • African-American Men’s Health: Breaking the Silence – Mark Alexander, Ph.D., 100 Black Men of America Inc.
  • Policy Solutions for Health Disparities – Brian Smedley, Ph.D., executive director, National Collaborative for Health Equity
  • Academic-Community Partnerships – Barbara A. Israel, Ph.D., professor of health behavior and health education, University of Michigan; and Zachary Rowe, executive director, Friends of Parkside

In addition, UAB will announce the 2015 Excellence in Mentoring Awards and will present awards for oral presentations and poster presentations.

Two UAB faculty honored by the American Society of Nutrition
Two UAB faculty honored by the American Society of Nutrition
The American Society of Nutrition honors two UAB scientists.

barbara gower2Barbara GowerTwo faculty members in the Department of Nutrition Sciences at the University of Alabama at Birmingham are among 23 recipients of the 2015 Scientist, Clinician, Educator/Mentor & Young Investigator Awards given by the American Society of Nutrition.

Barbara A. Gower, Ph.D., has received the Dannon Institute Mentorship Award, supported by the Dannon Institute, in the category of Senior Investigator – Educator & Mentor Awards.

In the category of Young Investigator Awards, Daniel L. Smith Jr., Ph.D., has received the Bio-Serv Award in Experimental Animal Nutrition, supported by Bio-Serv Inc.

Gower and Smith, along with the other award winners, will be recognized in a ceremony Sunday, March 29, during the ASN Scientific Sessions and Annual Meeting at Experimental Biology 2015 in Boston, Massachusetts.

daniel smithDaniel Smith“The work of these scientists, from young investigators to lifelong researchers, has helped advance the field in leaps and bounds. I couldn’t be more pleased to honor these individuals,” said ASN President Simin Nikbin Meydani, DVM, Ph.D.

Gower, who is professor and vice chair for Research in the Department of Nutrition Sciences and an associate scientist in the Nutrition Obesity Research Center, focuses on obesity and energy metabolism, with an emphasis on insulin secretion/action and the role of the endocrine system. Her ongoing research is directed toward understanding the physiologic basis for the greater prevalence of type 2 diabetes among African-Americans in both children and adults.

Smith is an assistant professor in the department whose research looks at the interaction of nutrition and metabolism in relation to aging and disease. He is interested in topics including obesity, calorie restriction, calorie restriction mimetics, brown adipose tissue, ulcerative dermatitis in C57BL/6 mice, and systems biology of aging using budding yeast chronological lifespan.

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