The list of risk genes for ASD with associated mutations continues to grow at a substantial pace, but for many of these mutations, a basic understanding of the functional impact of the mutations on the encoded proteins is missing. In this project, Marc Vidal and Lilia Iakoucheva plan to functionally characterize a collection of ASD gene variants by assessing the effects of mutations on protein stability and protein-protein interactions. This integrative approach will enable the identification of causative variants and characterization of the functional impact of these variants in the context of brain-expressed isoforms.

For many proteins encoded by autism risk genes, having too much or too little of them in each neuron are both problematic. To treat such disorders, it is important to increase the amount of gene expression in the “too little” scenario without overshooting into the “too much” scenario. Wei-Hsiang Huang, in collaboration with Xiaojing Gao, plan to work on a feedback control loop, consisting of engineered biomolecules, to achieve such quantitatively consistent regulation of gene levels.

Although thousands of de novo missense mutations have been detected in people with ASD, it is challenging to identify which mutations induce risk. To address this gap, Haiyuan Yu and Kathryn Roeder aim to continue their efforts to develop an experimentally and computationally integrated interactome perturbation screening pipeline to study these mutations. Additionally, they plan to continue to develop analytical methods to identify ASD risk genes and understand the interrelationships among these genes.

There is a critical unmet need to define ASD-causing genes and determine how variants in those genes perturb molecular networks leading to disease. This project aims to address these issues using robust functional assays in model organisms designed to uncover disease networks and provide clinical predictive values of large numbers of variants. Christopher Loewen and colleagues expect to provide much needed progress in identifying clinically relevant ASD susceptibility variants to improve our understanding of ASD and potential treatments.

A critical step towards antisense oligonucleotide (ASO) development for haploinsufficiency is the identification of targets that have demonstrable inhibitory effects on the expression of ASD genes. Jonathan Sebat’s team proposes to accelerate ASO development for ASD risk genes using novel high-throughput platforms for target identification, focusing on regulatory RNA targets that can be readily characterized in transcriptome-wide screens.

Even with tremendous advances in understanding of the causes, autism remains mostly without specific treatments. Antisense oligonucleotides (ASOs) are programmable drugs that can target specific mutations. Joseph Gleeson’s lab plans to generate ASOs to target specific ASD-linked mutations and assess these drugs in stem cell models for individualized therapy.

Samouil Farhi is a group leader at the Klarman Cell Observatory at the Broad Institute of MIT and Harvard, where he leads the Optical Profiling Platform. He joined the Broad Institute in July 2018 after completing his Ph.D. in chemical biology at Harvard University with Adam Cohen, where he developed methods for all-optical investigations of neuronal systems. The platform’s goal is to bring next-generation imaging approaches to bear on large-scale biological problems, with a focus on profiling the spatial organization of tissues, high-content phenotypic screens and all-optical studies of the electrical properties of cells.

PCDH19-clustering epilepsy (PCE) is a severe childhood epilepsy that manifests with medically refractory seizures, intellectual disability and frequent features of ASD. The current project aims to develop antisense oligonucleotide therapy that targets the underlying disease mechanism to halt or reverse PCE-related brain abnormalities. This therapy will be tested in robust human brain organoid and mouse models of PCE.