Highlights of SFARI-funded papers, selected by the SFARI science team.
Genevieve Konopka and colleagues coupled brain imaging with measures of gene expression to reveal that gene expression patterns in the cortex that typically underlie functional brain activity in neurotypical individuals are affected in people with autism.
Joshua K. Hartshorne, Stefano Anzellotti and colleagues used machine learning to disentangle variations in neuroanatomy that are specific to autism from variations common to the general population.
Gina Turrigiano and colleagues showed that the phosphorylation state of the autism-associated synaptic scaffold protein Shank3 can bias synapses toward upward or downward homeostatic plasticity.
Vinod Menon and colleagues showed that a subregion of the auditory cortex decodes emotional cues in a communication partner’s voice and that this predicts social communication abilities in children.
Catherine Dulac and her collaborators identified a population of cells in the hypothalamus that generate fever and influence the activity of brain areas associated with behavior during sickness, with implications for the effects of fever on social behavior in autism.
So Hyun Kim, Catherine Lord and colleagues developed a new telehealth approach to autism assessment — the Brief Observation of Symptoms of Autism (BOSA) — for use during COVID-19 and beyond.
Daniel Geschwind and colleagues showed that Cntnap2 knockout mice exhibit alterations in brain-wide connectivity related to social behaviors and that oxytocin within the nucleus accumbens regulates changes in connectivity.
Helen Bateup and colleagues showed that a loss of Tsc1 from striatal direct pathway neurons altered synaptic function and enhanced motor routine learning in mice. These findings suggest that changes in select types of striatal neurons may underlie altered motor behaviors in individuals with tuberous sclerosis complex and autism.
Yufeng Cheng, Wendy Chung, Chang “April” Shu and their colleagues used machine-learning models to develop a method for large-scale studies to estimate cognitive ability in individuals with autism for whom formal IQ tests are not available.
Ian Lipkin, Mady Hornig and colleagues showed that levels of immune molecules in mothers during pregnancy and in cord blood at birth are highly predictive of later autism diagnoses.