New York (USA) / Rovereto, Trento (Italy), May 29, 2026 – An international research team led by Istituto Italiano di Tecnologia (IIT Italian Institute of Technology) in Rovereto (Trento, Italy) and the Child Mind Institute in New York (USA), and in collaboration with researchers from the University of Trento, Italy, has shown that it is possible to identify at least two distinct subtypes of autism, defined by their patterns of brain connectivity. In the "hyperconnectivity" subtype, brain areas communicate more than usual; in the "hypoconnectivity" subtype, communication between brain areas is reduced. The study aims to develop tools for precise, personalized autism care and support. The research paper was published in the international journal Nature Neuroscience .
The research study was coordinated by Alessandro Gozzi, PhD, director of the Center for Neuroscience and Cognitive Systems (CNCS) at the IIT and Adriana Di Martino, MD, founding director of the Autism Center at the Child Mind Institute, and it represents the first systematic effort to decode human brain imaging patterns (via fMRI) by tracing them back to their molecular underpinnings in mouse models. By linking patterns of connectivity to specific biological pathways, the findings offer a foundation for precision medicine approaches.
Therefore, the researchers analyzed functional connectivity across 20 mouse models and brain scans from 940 children and young adults with autism and over 1,000 neurotypical individuals. The findings revealed two reproducible autism subtypes: one characterized by reduced brain connectivity (hypoconnectivity) linked to synaptic pathways, the other by increased connectivity (hyperconnectivity) associated with immune-related systems. Together, these subtypes accounted for approximately 25% of individuals with autism examined in the study.
"For decades, we've observed tremendous variability in how autism manifests, but we lacked direct evidence that these differences reflected distinct underlying biology," said Dr. Alessandro Gozzi, at Italian Institute of Technology. "Our approach enabled us to isolate specific genetic and immune factors, then translate those signatures to human brain scans, showing that different connectivity patterns encode different mechanistic pathways underlying autism."
The team combined brain imaging with genetic and biochemical analyses in mouse models, linking connectivity patterns to specific alterations in cellular function. This revealed how specific molecular pathways, including synaptic and immune-related mechanisms, manifest as distinct connectivity patterns observable with fMRI. The study established biological reference patterns from mice that guided subtype identification in human brain scans.
"The mouse models gave us a biological 'Rosetta Stone," said Dr. Adriana Di Martino at the Child Mind Institute. "We could see which biological pathways drive which connectivity signatures, then search for those same patterns in humans."
The human data came from the Autism Brain Imaging Data Exchange (ABIDE) — a pioneering neuroimaging initiative co-founded by Dr. Di Martino that aggregates datasets from research laboratories worldwide — and the Child Mind Institute.
The analyses identified corresponding hypo- and hyperconnectivity subtypes in the human data. Gene expression analyses confirmed that human brain regions showing hypoconnectivity were enriched for synaptic genes, while hyperconnected regions showed enrichment for immune-related genes — mirroring the mechanisms identified in mouse models. Importantly, the subtypes were reproducible across independent datasets, validating their biological consistency.
"Finding the same subtypes reproducible across dozens of independent research sites was critical validation," added Dr. Gozzi.
The two subtypes exhibited different functional brain architecture and showed modest differences on standardized autism assessments, with the hyperconnectivity subtype scoring moderately higher on autism severity measures.
"Brain-based biological markers reveal distinctions that current behavioral assessments don't fully capture," noted Dr. Di Martino.
The researchers emphasize that while the current findings capture two dominant patterns of brain connectivity in autism, the full diversity of the spectrum likely encompasses additional subtypes that larger datasets and refined analytical approaches may reveal.
The research was made possible by an international collaboration coordinated by the Italian Institute of Technology and the Child Mind Institute, with funding from the Simons Foundation Autism Research Initiative, the European Research Council through the #DISCONN and #BRAINAMICS projects, the Brain and Behavior Foundation, the Fondazione Telethon, and the US National Institute of Mental Health.
The paper, "Autism subtypes identified using cross-species functional connectivity analyses," is published in Nature Neuroscience and is available at https://doi.org/10.1038/s41593-026-02287-z .
Child Mind Institute
The Child Mind Institute is an independent nonprofit organization dedicated to transforming the lives of children and families struggling with mental health and learning disorders. Through cutting-edge research, evidence-based clinical care, and public education, the Child Mind Institute builds open science platforms and digital tools to accelerate discovery and improve youth mental health worldwide. Learn more at childmind.org .
ISTITUTO ITALIANO DI TECNOLOGIA
The Istituto Italiano di Tecnologia (Italian Institute of Technology – IIT) is a state-funded scientific research center that promotes technological development with the aim of supporting excellence in both basic and applied research and fostering the growth of the national economic system. The main headquarters is in Genoa (north-west Italy), with four Central Research Laboratories, complemented by a Network of Centers consisting of 12 hubs across Italy (Treviso, Turin, Aosta, two in Milan, Trento, Ferrara, Rome, Pisa, Pontedera, Naples, and Lecce) and two outstations abroad (MIT and Harvard in the United States).The total IIT staff exceeds 1,900 people, 50% of whom come from abroad, representing 62 countries worldwide. IIT's research activity is characterized by strong multidisciplinary collaboration and focuses on four main scientific areas: robotics, nanomaterials, computational sciences, and technologies for the life sciences. To date, IIT's output includes more than 23,000 publications, over 1,000 institutional projects — more than 70 of which are funded by the European Research Council —over 1,200 active patents, more than 1,000 commercial collaboration agreements signed, 41 start-ups established, and more than 50 currently in the launch phase.
