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Therapeutic Development

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therapeutic development

Discover seminars, jobs, and research tagged with therapeutic development across World Wide.
2 curated items2 Seminars
Updated over 2 years ago
2 items · therapeutic development
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SeminarNeuroscience

Integration of 3D human stem cell models derived from post-mortem tissue and statistical genomics to guide schizophrenia therapeutic development

Jennifer Erwin, Ph.D
Lieber Institute for Brain Development; Department of Neurology and Neuroscience; Johns Hopkins University School of Medicine
Mar 14, 2023

Schizophrenia is a neuropsychiatric disorder characterized by positive symptoms (such as hallucinations and delusions), negative symptoms (such as avolition and withdrawal) and cognitive dysfunction1. Schizophrenia is highly heritable, and genetic studies are playing a pivotal role in identifying potential biomarkers and causal disease mechanisms with the hope of informing new treatments. Genome-wide association studies (GWAS) identified nearly 270 loci with a high statistical association with schizophrenia risk; however each locus confers only a small increase in risk therefore it is difficult to translate these findings into understanding disease biology that can lead to treatments. Induced pluripotent stem cell (iPSC) models are a tractable system to translate genetic findings and interrogate mechanisms of pathogenesis. Mounting research with patient-derived iPSCs has proposed several neurodevelopmental pathways altered in SCZ, such as neural progenitor cell (NPC) proliferation, imbalanced differentiation of excitatory and inhibitory cortical neurons. However, it is unclear what exactly these iPS models recapitulate, how potential perturbations of early brain development translates into illness in adults and how iPS models that represent fetal stages can be utilized to further drug development efforts to treat adult illness. I will present the largest transcriptome analysis of post-mortem caudate nucleus in schizophrenia where we discovered that decreased presynaptic DRD2 autoregulation is the causal dopamine risk factor for schizophrenia (Benjamin et al, Nature Neuroscience 2022 https://doi.org/10.1038/s41593-022-01182-7). We developed stem cell models from a subset of the postmortem cohort to better understand the molecular underpinnings of human psychiatric disorders (Sawada et al, Stem Cell Research 2020). We established a method for the differentiation of iPS cells into ventral forebrain organoids and performed single cell RNAseq and cellular phenotyping. To our knowledge, this is the first study to evaluate iPSC models of SZ from the same individuals with postmortem tissue. Our study establishes that striatal neurons in the patients with SCZ carry abnormalities that originated during early brain development. Differentiation of inhibitory neurons is accelerated whereas excitatory neuronal development is delayed, implicating an excitation and inhibition (E-I) imbalance during early brain development in SCZ. We found a significant overlap of genes upregulated in the inhibitory neurons in SCZ organoids with upregulated genes in postmortem caudate tissues from patients with SCZ compared with control individuals, including the donors of our iPS cell cohort. Altogether, we demonstrate that ventral forebrain organoids derived from postmortem tissue of individuals with schizophrenia recapitulate perturbed striatal gene expression dynamics of the donors’ brains (Sawada et al, biorxiv 2022 https://doi.org/10.1101/2022.05.26.493589).

SeminarNeuroscience

Understanding the cellular and molecular landscape of autism spectrum disorders

Karun Singh
Krembil Research Institute, University Health Network, Toronto, Faculty of Medicine, University of Toronto
Mar 14, 2021

Large genomic studies of individuals with autism spectrum disorders (ASD) have revealed approximately 100-200 high risk genes. However, whether these genes function in similar or different signaling networks in brain cells (neurons) remains poorly studied. We are using proteomic technology to build an ASD-associated signaling network map as a resource for the Autism research community. This resource can be used to study Autism risk genes and understand how pathways are convergent, and how patient mutations change the interaction profile. In this presentation, we will present how we developed a pipeline using neurons to build protein-protein interaction profiles. We detected previously unknown interactions between different ASD risk genes that have never been linked together before, and for some genes, we identified new signaling pathways that have not been previously reported. This resource will be available to the research community and will foster collaborations between ASD researchers to help accelerate therapeutics for ASD and related disorders.