Anthony-Samuel LaMantia, Thomas Maynard and colleagues show that a mouse model of 22q11.2 deletion syndrome has fewer long-distance cortico-cortical connections, which is caused in part by mitochondrial dysfunction.
Research Highlights
Highlights of SFARI-funded papers, selected by the SFARI science team.
Using single-nucleus RNA sequencing of postmortem cortical tissue from individuals with ASD, Arnold Kriegstein and colleagues identify upper-layer excitatory neurons and microglia as key cell types affected in ASD.
Two studies using SPARK’s research matching program attest to its effectiveness for rapid and large-scale testing of research questions Two studies from Brigitta Monz, Richard Houghton and colleagues provide examples of the effectiveness of SPARK’s research match program to rapidly recruit thousands of individuals for the large-scale testing of research questions.
Brief treatment with statin yields long-term benefit in rat model of fragile X syndrome Peter Kind and colleagues show that brief treatment with lovastatin results in sustained correction of physiological and behavioral deficits in a rat model of fragile X syndrome.
Substantial role for biallelic mutations in autism risk, particularly in females Timothy Yu and colleagues analyzed exome sequencing data to estimate that recessive mutations contribute to approximately 5 percent of all cases of autism, including 10 percent of females.
A genome-wide assessment of noncoding risk variants in autism Olga Troyanskaya, Robert Darnell and colleagues applied deep-learning methods to whole-genome sequencing data from SSC families and identified a clear enrichment for de novo noncoding variation in ASD.
Neurons from individuals with SHANK2-associated autism exhibit increased neuronal connectivity James Ellis and colleagues used a sparse co-culture system for iPSC-derived cortical neurons to assess neuronal connectivity, demonstrating increased connectivity in SHANK2-mediated ASD.
Development of a single-cell mouse cortical gene expression pattern resource that identifies putative brain disorder subtypes Mark Zylka and colleagues generated single-cell RNA-seq data from wild-type mouse cortex during early development and demonstrated how such a resource can be used to identify putative brain disorder subtypes based on expression profiles.
Cryptic splice mutations: A major new source of risk variants for neurodevelopmental disorders Kyle Kai-How Farh and Stephan Sanders developed a deep-learning method to predict risk mutations that affect mRNA splicing and contribute substantially to neurodevelopmental disorders.
Impaired reward circuitry during voice processing predicts social communication abilities in autism Vinod Menon and colleagues report that a difference in the activation of a voice-processing network comprising reward and salience detection systems is a distinguishing feature of autism.