Summary:
By analyzing over 1,000 mouse brain transcriptomes across 17 genetic lines, researchers discovered that more than 1,200 autism-risk mutations converge into two opposing molecular states in the prefrontal cortex. The two groups display inverse patterns of synaptic and gene-regulatory activity, as well as distinct responses to experimental drugs, establishing a framework to evaluate treatments across diverse genetic backgrounds.
Key Facts:
- Two Divergent Molecular States: Genetically distinct autism models fall into two recurring patterns: Group 1 exhibits decreased synaptic communication genes alongside elevated chromatin and RNA processing activity, whereas Group 2 shows the exact opposite balance.
- Context Influences Molecular Grouping: The classification is not strictly dictated by genetics; in 7 of the 17 mouse strains, males and females carrying the exact same mutation fell into opposing groups, with patterns also shifting across developmental stages and brain regions.
- Differential Drug Responses: The two molecular profiles responded differently to early postnatal exposures to fluoxetine and lithium, with Group 1 showing a more consistent shift toward control gene expression patterns than Group 2.
Source: Institute for Basic Science (IBS)
Autism spectrum disorder (ASD) has been linked to variations in more than 1,200 risk genes, presenting a major puzzle for neuroscientists: Do these diverse genetic changes disrupt the brain in hundreds of separate ways, or do they channel through shared biological networks?
To investigate this question, a research team led by Professor KIM Eunjoon at the Center for Synaptic Brain Dysfunctions within the Institute for Basic Science (IBS) took a systems-level approach. Rather than focusing on single mutations in isolation, the researchers analyzed more than 1,000 mouse brain transcriptomes spanning 17 genetically engineered mouse lines.
Their findings reveal that distinct genetic disruptions converge into two broad, opposing molecular states inside the prefrontal cortex—offering a unifying lens to explore disease mechanisms and drug responses.
“Genetic discoveries have revealed extraordinary diversity in autism, but diversity alone does not explain the biology,” noted co-corresponding author Dr. BAE Mihyun. “Our study suggests that many different genetic mutations converge into a limited number of molecular brain states, providing a framework for understanding autism at the level of shared biology rather than individual genes.”
A Molecular Seesaw: Synapses Versus Gene Regulation
The 17 mouse models studied harbored mutations spanning critical neurodevelopmental processes, including synaptic communication, chromatin regulation, and intracellular signaling cascades. Both male and female mice were evaluated, alongside cohorts treated with fluoxetine or lithium during early postnatal development.
Across gene expression, alternative RNA splicing, and co-expression network analyses, the team discovered a recurring molecular divide:
- Group 1: Displayed reduced expression of genes essential for synaptic communication, paired with increased expression of genes governing chromatin remodeling and RNA processing.
- Group 2: Exhibited the mirrored opposite profile, showing elevated synaptic gene expression alongside down-regulated gene-regulatory machinery.
Single-nucleus sequencing of roughly one million individual cell nuclei from 205 mice revealed that these signatures do not stem from a single defective neuron type. Instead, they reflect coordinated, network-wide shifts across diverse neuronal and glial cell populations, with Group 1 showing wider variations in the relative proportions of specific brain cells.
The Role of Sex, Age, and Brain Region
Crucially, the study showed that an individual mutation does not permanently lock an animal into one specific molecular category.
In seven of the 17 mouse lines, male and female mice carrying identical genetic mutations sorted into opposite molecular groups. Tracking four lines across maturation revealed that these molecular assignments can shift over developmental time. Furthermore, while the two-group divide was clear in the prefrontal cortex, it was far less pronounced in the hippocampus.
These dynamics demonstrate that molecular pathology in ASD is highly context-dependent, shaped by the interplay of sex, developmental age, and neuroanatomical region rather than genetic code alone.
Stratifying Drug Responses
The researchers also evaluated how these two molecular profiles reacted to fluoxetine and lithium—compounds previously observed to alter behavioral phenotypes in select animal models, though neither serves as an approved treatment for core ASD features.
The drugs exerted markedly different effects depending on the molecular profile:
- Group 1 models exhibited a more consistent normalization, shifting select gene expression programs closer to patterns seen in neurotypical control mice.
- Group 2 models displayed variable, heterogeneous responses across cell types and gene networks.
Neither compound reversed the underlying imbalances in cell-type proportions, indicating that their influence was limited to specific transcriptional circuits within select neuronal subsets.
Translational Potential and Human Parallels
When examining transcriptomic datasets from the prefrontal cortex of 40 autistic individuals and 17 neurotypical controls, the investigators detected two human subgroups displaying opposing patterns of synaptic gene activity.
However, notable differences remained: human postmortem samples exhibited more pronounced immune and inflammatory pathway signals, and current data cannot link human subgroups directly to specific upstream mutations. The authors caution that these findings remain exploratory and cannot yet be used to diagnose clinical subtypes, forecast individual support needs, or select medications.
“Instead of asking which gene is mutated, we asked whether different mutations produce common molecular patterns in the brain,” said Director KIM Eunjoon. “That perspective revealed a surprising level of convergence across genetically distinct forms of autism.”
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- Journal paper reviewed in full.
- Additional context added by our staff.
About this Genetics and Neurology Research:
- Media Contact: William Suh
- Source: Institute for Basic Science
- Image Credit: Image generated for Neuroscience News
- Original Research is Open Access: Science (September 15, 2026). “Transcriptome-based classification in mice with ASD-risk mutations” Authors: Junyeop Daniel Roh, Yukyung Jun, Heesu Jeon, Junyoung Kim, Yunho Yi, Minji Kim, Heejin Cho, Yusang Oh, Heera Moon, Jinkyeong Kim, Seongbin Kim, Jeseung Ryu, Muwon Kang, Jisoo Kim, Yeonghyeon Kim, Yewon Jung, Taesun Yoo, Hyoseon Oh, Hyosang Kim, Chunmei Jin, Yeji Yang, Gahyeon Choi, Sunjoo Ahn, Jin Young Kim, Hyojin Kang, Mihyun Bae, and Eunjoon Kim.
- DOI: 10.1126/science.adz6688
Abstract
Transcriptome-based classification in mice with ASD-risk mutations
Autism spectrum disorder (ASD) is a neurodevelopmental condition with a strong genetic component. Large-scale human genetic studies have identified >1200 ASD-risk genes. We report a sex-balanced atlas of 1008 prefrontal RNA sequencing (RNA-seq) profiles from 17 mouse lines carrying ASD-risk mutations. Our analysis identified two opposing transcriptomic states.
The two groups differed in sex bias, regional specificity, developmental stability, cell type remodeling, and responses to fluoxetine and lithium. Single-nucleus RNA-seq revealed broader cell type remodeling in group 1 than in group 2, and cell type–specific modules showed reciprocal associations that mirrored bulk transcriptomic signatures.
The framework classifies independent mouse lines and identifies subgroups with conserved synaptic directionality, supporting molecular stratification.
