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Blood-based gene expression signatures of infants and toddlers with autism
Stephen J Glatt1, Ming T Tsuang1, Mary Winn1
1Dr. Glatt is with the Psychiatric Genetic Epidemiology and Neurobiology Laboratory (PsychGENe Lab), Medical Genetics Research Center, State University of New York (SUNY) Upstate Medical University. Dr. Tsuang is with Harvard Institute of Psychiatric Epidemiology and Genetics, Harvard School of Public Health, and Harvard Medical School; the Center for Behavioral Genomics, University of California-San Diego (UCSD); Veterans Affairs San Diego Healthcare System; and the Institute of Genomic Medicine, UCSD. Dr. Winn is with UCSD and the Scripps Translational Science Institute. Drs. Chandler and Collins are with the Center for Behavioral Genomics, UCSD. Drs. Lopez, Weinfeld, Carter, Pierce, and Courchesne are with the Autism Center of Excellences, UCSD. Dr. Schork is with the Scripps Translational Science Institute.
Insights
Researchers identified early autism spectrum disorder (ASD) biomarkers in infant blood. This discovery offers a potential blood-based diagnostic tool for early autism risk assessment in children.
Area of Science:
- Neuroscience
- Genetics
- Pediatrics
Background:
- Autism spectrum disorders (ASDs) are highly heritable neurodevelopmental conditions with early childhood onset.
- Early diagnostic biomarkers for ASDs are crucial for timely intervention and treatment.
- Current diagnostic methods lack reliable, early-stage peripheral blood biomarkers.
Purpose of the Study:
- To identify transcriptome-wide mRNA expression biomarkers for autism spectrum disorders in infants.
- To develop a classifier for early ASD risk detection using peripheral blood samples.
- To establish the first potential peripheral blood-based biomarker panel for early autism risk.
Main Methods:
- A prospective, longitudinal study involving infants and toddlers at risk for ASDs and typically developing controls.
- Collection and microarray analysis of mRNA expression profiles from peripheral blood mononuclear cells.
- Development and validation of a biomarker classifier using a split-sample approach.
Main Results:
- Potential ASD biomarkers were identified in 50% of the study sample.
- A classifier built from these biomarkers demonstrated high diagnostic accuracy in the validation cohort.
- mRNA expression abnormalities were reliably detected in peripheral blood cells.
Conclusions:
- Peripheral blood mRNA expression profiles in infants show promise as early biomarkers for autism risk.
- The identified biomarkers are safely and easily assayed in infants, facilitating early detection.
- Further research is needed to validate these biomarkers and explore their link to neural mechanisms in autism.
Objective:
Autism spectrum disorders (ASDs) are highly heritable neurodevelopmental disorders that onset clinically during the first years of life. ASD risk biomarkers expressed early in life could significantly impact diagnosis and treatment, but no transcriptome-wide biomarker classifiers derived from fresh blood samples from children with autism have yet emerged.
Method:
Using a community-based, prospective, longitudinal method, we identified 60 infants and toddlers at risk for ASDs (autistic disorder and pervasive developmental disorder), 34 at-risk for language delay, 17 at-risk for global developmental delay, and 68 typically developing comparison children. Diagnoses were confirmed via longitudinal follow-up. Each child's mRNA expression profile in peripheral blood mononuclear cells was determined by microarray.
Results:
Potential ASD biomarkers were discovered in one-half of the sample and used to build a classifier, with high diagnostic accuracy in the remaining half of the sample.
Conclusions:
The mRNA expression abnormalities reliably observed in peripheral blood mononuclear cells, which are safely and easily assayed in infants, offer the first potential peripheral blood-based, early biomarker panel of risk for autism in infants and toddlers. Future work should verify these biomarkers and evaluate whether they may also serve as indirect indices of deviant molecular neural mechanisms in autism.
