We used established databases in standard ways to systematically characterize gene ontologies, pathways and functional linkages in the large set of genes now associated with autism spectrum disorders (ASDs). These conditions are particularly challenging—they lack clear pathognomonic biological markers, they involve great heterogeneity across multiple levels (genes, systemic biological and brain characteristics, and nuances of behavioral manifestations)—and yet everyone with this diagnosis meets the same defining behavioral criteria. Using the human gene list from Simons Foundation Autism Research Initiative (SFARI) we performed gene set enrichment analysis with the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Database, and then derived a pathway network from pathway-pathway functional interactions again in reference to KEGG. Through identifying the GO (Gene Ontology) groups in which SFARI genes were enriched, mapping the coherence between pathways and GO groups, and ranking the relative strengths of representation of pathway network components, we 1) identified 10 disease-associated and 30 function-associated pathways 2) revealed calcium signaling pathway and neuroactive ligand-receptor interaction as the most enriched, statistically significant pathways from the enrichment analysis, 3) showed calcium signaling pathways and MAPK signaling pathway to be interactive hubs with other pathways and also to be involved with pervasively present biological processes, 4) found convergent indications that the process “calcium-PRC (protein kinase C)-Ras-Raf-MAPK/ERK” is likely a major contributor to ASD pathophysiology, and 5) noted that perturbations associated with KEGG’s category of environmental information processing were common. These findings support the idea that ASD-associated genes may contribute not only to core features of ASD themselves but also to vulnerability to other chronic and systemic problems potentially including cancer, metabolic conditions and heart diseases. ASDs may thus arise, or emerge, from underlying vulnerabilities related to pleiotropic genes associated with pervasively important molecular mechanisms, vulnerability to environmental input and multiple systemic co-morbidities.

Objective:In this cross-sectional study, we aimed to evaluate brain structural abnormalities in relation to glial activation in the same cohort of participants.Methods:Ten individuals with amyotrophic lateral sclerosis (ALS) and 10 matched healthy controls underwent brain imaging using integrated MR/PET and the radioligand [11C]-PBR28. Diagnosis history and clinical assessments including Upper Motor Neuron Burden Scale (UMNB) were obtained from patients with ALS. Diffusion tensor imaging (DTI) analyses including tract-based spatial statistics and tractography were applied. DTI metrics including fractional anisotropy (FA) and diffusivities (mean, axial, and radial) were measured in regions of interest. Cortical thickness was assessed using surface-based analysis. The locations of structural changes, measured by DTI and the areas of cortical thinning, were compared to regional glial activation measured by relative [11C]-PBR28 uptake.Results:In this cohort of individuals with ALS, reduced FA and cortical thinning colocalized with regions demonstrating higher radioligand binding. [11C]-PBR28 binding in the left motor cortex was correlated with FA (r = −0.68, p < 0.05) and cortical thickness (r = −0.75, p < 0.05). UMNB was correlated with glial activation (r = +0.75, p < 0.05), FA (r = −0.77, p < 0.05), and cortical thickness (r = −0.75, p < 0.05) in the motor cortex.Conclusions:Increased uptake of the glial marker [11C]-PBR28 colocalizes with changes in FA and cortical thinning. This suggests a link between disease mechanisms (gliosis and inflammation) and structural changes (cortical thinning and white and gray matter changes). In this multimodal neuroimaging work, we provide an in vivo model to investigate the pathogenesis of ALS.

Glial activation measured by in vivo [ C]-PBR28 PET is increased in pathologically relevant regions in people with ALS and correlates with clinical measures. Ann Neurol 2018;83:1186-1197.