22837
Using iPSCs to Study Pathobiology and Drug Targets for Phelan-Mcdermid Syndrome
Autism spectrum disorder (ASD) has high heritability and a prevalence of ca. 1% worldwide, but heterogeneity has made identifying the underlying pathobiology difficult. By focusing on genetic disorders with high penetrance for causing ASD, common pathobiological pathways might be identified. Phelan-McDermid syndrome (PMS) is one such genetic ASD-associated syndrome, where the neurobehavioral changes are caused by haploinsufficiency of the gene SHANK3, which encodes for a scaffolding protein of the post-synaptic density of glutamatergic synapses. While animal models provide great insight into the pathways involved in PMS, some features of the disease may not be captured because of neuronal variation across species. One approach to deal with this shortcoming is to generate induced pluripotent stem cells (iPSCs) from patients that can then be differentiated into neural progenitor cells (NPCs) and neurons.
Objectives:
Results from a recent study indicate that iPSC-derived neurons from PMS patients show excitatory synaptic deficits similar to those seen in animal models. This provides further support for our hypothesis that expression analysis from such cells can provide valuable insight into the underlying pathobiology and can be mapped to the expression profiles of FDA-approved drugs to identify candidates for repositioning as novel PMS therapeutics. Therefore, we aim to 1) generate high-quality iPSC clones from PMS patients and siblings; 2) differentiate them into neurons that capture the neurobiological phenotype of PMS in patients; 3) identify PMS-associated differential gene expression in iPSC-derived neurons by RNA sequencing; and, 4) identify candidate drugs by comparing gene expression patterns for FDA-approved drugs with PMS-associated expression.
Methods:
Blood samples from patients with PMS and unaffected siblings have been collected for 14 patient/sibling pairs and are being reprogrammed using a non-integrating virus to express reprogramming factors. Three clones are selected for each patient after quality control (QC). Clones are then transfected with lentiviruses carrying vectors to induce expression of NGN2 under the control of doxycycline, followed by puromycin selection. Astrocytes are added at day 2 to support synapse formation, and after 3 weeks, cells are harvested and processed for RNA isolation, followed by RNA sequencing. The PMS-associated changes in gene expression are then analyzed to understand the underlying neurobiology, and compared to known gene expression profiles of FDA-approved drugs and used to identify candidate PMS therapeutics based on anti-correlation between disease and drug gene expression.
Results:
Ten patient/sibling pairs have been reprogrammed and high quality clones have been obtained after QC, while the remaining 4 patient/sibling pairs are currently being reprogrammed. NPC generation and neuronal induction has been performed on clones as they finish QC testing. Studies making use of Axion high-throughput Microelectrode arrays are being piloted as a means of high throughput electrophysiological analyses.
Conclusions:
iPSCs from PMS patients offer a powerful tool for disease characterization, drug identification, and screening. Generating an expression profile for these patient-derived neurons will provide a unique perspective on the transcriptional signature of PMS that can be used to understand neurobiology and, in conjunction with other models of the disease and known drug expression profiles, to identify new therapeutics.
Objectives: Results from a recent study indicate that iPSC-derived neurons from PMS patients show excitatory synaptic deficits similar to those seen in animal models. This provides further support for our hypothesis that expression analysis from such cells can provide valuable insight into the underlying pathobiology and can be mapped to the expression profiles of FDA-approved drugs to identify candidates for repositioning as novel PMS therapeutics. Therefore, we aim to 1) generate high-quality iPSC clones from PMS patients and siblings; 2) differentiate them into neurons that capture the neurobiological phenotype of PMS in patients; 3) identify PMS-associated differential gene expression in iPSC-derived neurons by RNA sequencing; and, 4) identify candidate drugs by comparing gene expression patterns for FDA-approved drugs with PMS-associated expression.
Methods: Blood samples from patients with PMS and unaffected siblings have been collected for 14 patient/sibling pairs and are being reprogrammed using a non-integrating virus to express reprogramming factors. Three clones are selected for each patient after quality control (QC). Clones are then transfected with lentiviruses carrying vectors to induce expression of NGN2 under the control of doxycycline, followed by puromycin selection. Astrocytes are added at day 2 to support synapse formation, and after 3 weeks, cells are harvested and processed for RNA isolation, followed by RNA sequencing. The PMS-associated changes in gene expression are then analyzed to understand underlying neurobiology, and compared to known gene expression profiles of FDA-approved drugs and used to identify candidate PMS therapeutics based on anti-correlation between disease and drug gene expression.
Results: Ten patient/sibling pairs have been reprogrammed and high quality clones have been obtained after QC, while the remaining 4 patient/sibling pairs are currently being reprogrammed. NPC generation and neuronal induction has been performed on clones as they finish QC testing. Studies making use of Axion high-throughput Microelectrode array are being piloted as a means of high throughput electrophysiological analyses.
Conclusions: iPSCs from PMS patients offer a powerful tool for disease characterization, drug identification, and screening. Generating an expression profile for these patient-derived neurons will provide a unique perspective on the transcriptional signature of PMS that can be used to understand neurobiology and, in conjunction with other models of the disease and known drug expression profiles, to identify new therapeutics.