No abstract

Proteomics is the large-scale study of the total protein content and their overall function within a cell through multiple facets of research. Advancements in proteomic methods have moved past the simple quantification of proteins to the identification of post-translational modifications (PTMs) and the ability to probe interactions between these proteins, spatially and temporally. Increased sensitivity and resolution of mass spectrometers and sample preparation protocols have drastically reduced the large amount of cells required and the experimental variability that had previously hindered its use in studying human neurological disorders. Proteomics offers a new perspective to study the altered molecular pathways and networks that are associated with autism spectrum disorders (ASD). The differences between the transcriptome and proteome, combined with the various types of post-translation modifications that regulate protein function and localization, highlight a novel level of research that has not been appropriately investigated. In this review, we will discuss strategies using proteomics to study ASD and other neurological disorders, with a focus on how these approaches can be combined with induced pluripotent stem cell (iPSC) studies. Proteomic analysis of iPSC-derived neurons have already been used to measure changes in the proteome caused by patient mutations, analyze changes in PTMs that resulted in altered biological pathways, and identify potential biomarkers. Further advancements in both proteomic techniques and human iPSC differentiation protocols will continue to push the field towards better understanding ASD disease pathophysiology. Proteomics using iPSC-derived neurons from individuals with ASD offers a window for observing the altered proteome, which is necessary in the future development of therapeutics against specific targets. Autism spectrum disorders

Autism spectrum disorder (ASD) is a genetically heterogeneous disorder. Sequencing studies have identified hundreds of risk genes for autism spectrum disorder (ASD), but the signaling networks of genes at the protein level remain largely unexplored, which can provide insight into previously unknown individual and convergent disease pathways in the brain. To address this gap, we used neuron-specific proximity-labeling proteomics (BioID) to identify protein-protein interaction (PPI) networks of 41 ASD-risk genes. Network analysis revealed the combined 41 risk gene PPI network map had more shared connectivity between unrelated ASD-risk genes than represented in existing public databases. We identified common pathways between established and uncharacterized risk genes, including synaptic transmission, mitochondrial/metabolic processes, Wnt signaling pathways, ion channel activity and MAPK signaling. Investigation of the mitochondrial and metabolic network using gene knockouts revealed a functional hub in neurons for multiple risk genes not previously associated with this pathway. Further, we identified that the uncharacterized ASD-risk gene PPP2R5D localizes to the synapse, which is disrupted by patient de novo missense mutations. Investigation of de novo missense variants of additional synaptic ASD-risk genes demonstrated that changes in PPI networks can capture synaptic transmission deficits. The neuronal 41 ASD-risk gene PPI network map also revealed enrichment for an additional 112 ASD-risk genes and human brain cell types implicated in ASD pathology. Interestingly, clustering of ASD-risk genes based on their PPI network connectivity identified multiple gene groups that correlate mutation-type to clinical behavior scores. Together, our data reveal that using PPI networks to map ASD risk genes can identify previously unknown individual and convergent neuronal signaling networks, provide a method to assess the impact of patient variants, and reveal new biological insight into disease mechanisms.

Background Pain is a complex neurobiological response with a multitude of causes; however, patients with autism spectrum disorder (ASD) often report chronic pain with no known etiology. Recent research has been aimed toward identifying the causal mechanisms of pain in mouse and human models of ASD. In recent years, efforts have been made to better document and explore secondary phenotypes observed in ASD patients in the clinic. As new sequencing studies have become more powered with larger cohorts within ASD, specific genes and their variants are often left uncharacterized or validated. In this review we highlight ASD risk genes often presented with pain comorbidities. Aims This mini-review bridges the gap between two fields of literature, neurodevelopmental disorders and pain research. We discuss the importance of the genetic landscape of ASD and its links to pain phenotypes. Results Among the numerous genes implicated in ASD, few have been implicated with varying severities of pain comorbidity. Mutations in these genes, such as SCN9A, SHANK3 , and CNTNAP2 , lead to altered neuronal function that produce different responses to pain, shown in both mouse and human models. Conclusion There is a necessity to use new technologies to advance the current understanding of ASD risk genes and their contributions to pain. Secondly, there is a need to power future ASD risk genes associated with pain with their own cohort, because a better understanding is needed of this subpopulation.

SCN2A is an autism spectrum disorder (ASD) risk gene and encodes a voltage-gated sodium channel. However, the impact of autism-associated SCN2A de novo variants on human neuron development is unknown. We studied SCN2A using isogenic SCN2A-/- induced pluripotent stem cells (iPSCs), and patient-derived iPSCs harboring a p.R607* or a C-terminal p.G1744* de novo truncating variant. We used Neurogenin2 to generate excitatory glutamatergic neurons and found that SCN2A+/p.R607* and SCN2A-/- neurons displayed a reduction in synapse formation and excitatory synaptic activity using multielectrode arrays and electrophysiology. However, the p.G1744* variant, which leads to early-onset seizures in addition to ASD, altered action-potential dynamics but not synaptic activity. Proteomic and functional analysis of SCN2A+/p.R607* neurons revealed defects in neuronal morphology and bioenergetic pathways, which were not present in SCN2A+/p.G1744* neurons. Our study reveals that SCN2A de novo variants can have differential impact on human neuron function and signaling.