Biology subjects

Scherer, S. W.

Publications and source records attributed to Scherer, S. W..

3 recordsLinked to original sources

bioRxiv2018

CNTN5-/+ or EHMT2-/+ iPSC-Derived Neurons from Individuals with Autism Develop Hyperactive Neuronal Networks

Induced pluripotent stem cell (iPSC)-derived cortical neurons are increasingly used as a model to study developmental aspects of Autism Spectrum Disorder (ASD), which is clinically and genetically heterogeneous. To study the complex relationship of rare (penetrant) variant(s) and common (weaker) polygenic risk variant(s) to ASD, \"isogenic\" iPSC-derived neurons from probands and family-based controls, for modeling, is critical. We developed a standardized set of procedures, designed to control for heterogeneity in reprogramming and differentiation, and generated 53 different iPSC-derived glutamatergic neuronal lines from 25 participants from 12 unrelated families with ASD (14 ASD-affected individuals, 3 unaffected siblings, 8 unaffected parents). Heterozygous de novo (7 families; 16p11.2, NRXN1, DLGAP2, CAPRIN1, VIP, ANOS1, THRA) and rare-inherited (2 families; CNTN5, AGBL4) presumed-damaging variants were characterized in ASD risk genes/loci. In three additional families, functional candidates for ASD (SET), and combinations of putative etiologic variants (GLI3/KIF21A and EHMT2/UBE2I combinations in separate families), were modeled. We used a large-scale multi-electrode array (MEA) as our primary high-throughput phenotyping assay, followed by patch clamp recordings. Our most compelling new results revealed a consistent spontaneous network hyperactivity in neurons deficient for CNTN5 or EHMT2. Our biobank of iPSC-derived neurons and accompanying genomic data are available to accelerate ASD research.

neuroscience↗

bioRxiv2018

Complete Disruption of Autism-Susceptibility Genes by Gene-Editing Predominantly Reduces Functional Connectivity of Isogenic Human Neurons

Autism Spectrum Disorder is phenotypically and genetically heterogeneous, but genomic analyses have identified candidate susceptibility genes. We present a CRISPR gene editing strategy to insert a protein tag and premature termination sites creating an induced pluripotent stem cell (iPSC) knockout resource for functional studies of 10 ASD-relevant genes (AFF2/FMR2, ANOS1, ASTN2, ATRX, CACNA1C, CHD8, DLGAP2, KCNQ2, SCN2A, TENM1). Neurogenin 2 (NEUROG2)-directed differentiation of iPSCs allowed production of cortical excitatory neurons, and mutant proteins were not detectable. RNAseq revealed convergence of several neuronal networks. Using both patch-clamp and multi-electrode array approaches, the electrophysiological deficits measured were distinct for different mutations. However, they culminated in a consistent reduction in synaptic activity, including reduced spontaneous excitatory post-synaptic current frequencies in AFF2/FMR2-, ASTN2-, ATRX-, KCNQ2- and SCN2A-null neurons. Despite ASD susceptibility genes belonging to different gene ontologies, isogenic stem cell resources can reveal common functional phenotypes, such as reduced functional connectivity.

neuroscience↗

bioRxiv2018

Matching drug transcriptional signatures to rare losses disrupting synaptic gene networks identifies known and novel candidate drugs for schizophrenia

Schizophrenia is a complex neuropsychiatric disorder. The etiology is not fully understood, but genetics plays an important role. Pathway analysis of genetic variants have suggested a central role for neuronal synaptic processes. Currently available antipsychotic medications successfully control positive symptoms (hallucinations and delusions) largely by inhibiting the dopamine D2 receptors; however, these drugs have more limited impact on negative symptoms (social withdrawal, flat affections, anhedonia) and cognitive deterioration. Drug development efforts have focused on a wide range of neurotransmitter systems and other agents, with conflicting or inconclusive results. New drug development paradigms are needed. A recent analysis, using common variant association results to match drugs based on their transcriptional perturbation signature, found drugs enriched in known antipsychotics plus novel candidates.\n\nWe followed a similar approach, but started our analysis from a synaptic gene network implicated by rare copy number loss variants. We found that a significant number of antipsychotics (p-value = 0.0002) and other psychoactive drugs (p-value = 0.0004) upregulate synaptic network genes. Based on global gene expression similarity, active drugs formed two main clusters: one with many known antipsychotics and antidepressants, the other with various drug categories including two nootropics. We specifically recommend further examination of nootropics with limited side effects (meclofenoxate, piracetam and vinpocetine) for combination therapy with antipsychotics to improve cognitive performance. Detailed experimental follow-up is required to further evaluate other candidate drugs lacking an official nervous system indication, although, for at least a few of these, psychoactive effects have been reported in the literature.

bioinformatics↗