Scientists have identified two separate biological forms of autism by studying how different regions of the brain communicate with each other, a finding that could reshape how the condition is diagnosed and treated in the future.
An international research team discovered that autism encompasses at least two distinct subtypes, each driven by different patterns of brain connectivity. One subtype involves unusually strong communication between brain regions, while the other shows weaker connections. The distinction matters because it points to fundamentally different biological mechanisms at work, opening the door to treatments tailored to each person's individual neurobiology.
The breakthrough came from an unusual research approach: scientists at Italy's Istituto Italiano di Tecnologia and New York's Child Mind Institute used mouse models to understand the basic biology, then confirmed their findings in human brain scans from over 1,900 individuals. The work, published in Nature Neuroscience, represents the first large-scale effort to link brain imaging patterns directly to their biological roots.
The team examined functional brain connectivity across 20 different mouse models and compared scans from 940 children and young adults with autism against more than 1,000 neurotypical controls. What emerged were two consistent subtypes. The first showed reduced communication between brain regions, a pattern called hypoconnectivity, and was tied to synaptic pathways involved in cell-to-cell communication. The second displayed increased connectivity, known as hyperconnectivity, and was linked to immune system processes in the brain.
Together, these two groups accounted for roughly 25 percent of the autistic individuals studied, suggesting that while these subtypes are significant, additional forms of autism likely exist.
The mouse research proved crucial. By combining brain imaging with genetic and biochemical analysis in animals, researchers could pinpoint exactly which molecular mechanisms produce which connectivity patterns. They then used those patterns as a biological reference guide to search for matching signatures in human brain scans.
"The mouse models gave us a biological 'Rosetta Stone," explained Dr. Adriana Di Martino of the Child Mind Institute. "We could see which biological pathways drive which connectivity signatures, then search for those same patterns in humans."
When the team analyzed human imaging data from the Autism Brain Imaging Data Exchange, a massive international neuroimaging resource, they found the same hyperconnectivity and hypoconnectivity patterns. Gene expression analyses strengthened the link: brain regions showing hypoconnectivity were enriched with synaptic genes, while hyperconnected regions showed enrichment of immune-related genes. These molecular findings closely matched what the mouse studies had revealed.
The subtypes appeared consistently across dozens of independent datasets from research centers worldwide, providing strong validation that the findings were real and reproducible.
The two subtypes also showed differences in overall brain organization and produced modest variations on standard autism severity assessments. Individuals in the hyperconnectivity group tended to score somewhat higher on measures of autism severity, though researchers cautioned against reading too much into these behavioral differences.
Dr. Alessandro Gozzi, director of the Center for Neuroscience and Cognitive Systems at the Italian Institute of Technology, emphasized that the brain-based markers reveal distinctions that behavioral tests alone cannot capture. "For decades, we've observed tremendous variability in how autism manifests, but we lacked direct evidence that these differences reflected distinct underlying biology," he said.
The researchers acknowledge that these two connectivity patterns likely represent only a portion of autism's full biological diversity. As larger datasets become available and analytical methods improve, additional subtypes may surface. The current findings set a foundation for future precision medicine approaches that could one day match individual patients with treatments designed for their specific neurobiological subtype.
Author Jessica Williams: "This is the kind of biological granularity medicine has been chasing for autism for years, and finally seeing it materialize in the data is genuinely exciting."
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