TCF4 Mutations Disrupt Synaptic Function Through Dysregulation of RIMBP2 in Patient-Derived Cortical Neurons.

Background: Genetic variation in the TCF4 (transcription factor 4) gene is associated with risk for a variety of developmental and psychiatric conditions, which includes a syndromic form of autism spectrum disorder called Pitt-Hopkins syndrome (PTHS). TCF4 encodes an activity-dependent transcription factor that is highly expressed during cortical development and in animal models has been shown to regulate various aspects of neuronal development and function. However, our understanding of how disease-causing mutations in TCF4 confer pathophysiology in a human context is lacking.

Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia.

Genetics have nominated many schizophrenia risk genes and identified convergent signals between schizophrenia and neurodevelopmental disorders. However, functional interpretation of the nominated genes in the relevant brain cell types is often lacking. We executed interaction proteomics for six schizophrenia risk genes that have also been implicated in neurodevelopment in human induced cortical neurons.

Protein interaction studies in human induced neurons indicate convergent biology underlying autism spectrum disorders.

Autism spectrum disorders (ASDs) have been linked to genes with enriched expression in the brain, but it is unclear how these genes converge into cell-type-specific networks. We built a protein-protein interaction network for 13 ASD-associated genes in human excitatory neurons derived from induced pluripotent stem cells (iPSCs). The network contains newly reported interactions and is enriched for genetic and transcriptional perturbations observed in individuals with ASDs.

Genoppi is an open-source software for robust and standardized integration of proteomic and genetic data.

Combining genetic and cell-type-specific proteomic datasets can generate biological insights and therapeutic hypotheses, but a technical and statistical framework for such analyses is lacking. Here, we present an open-source computational tool called Genoppi (lagelab.org/genoppi) that enables robust, standardized, and intuitive integration of quantitative proteomic results with genetic data.

Choice of Intensive Lifestyle Change and/or Metformin after Shared Decision Making for Diabetes Prevention: Results from the Prediabetes Informed Decisions and Education (PRIDE) Study.

Introduction: While the Diabetes Prevention Program Study demonstrated that intensive lifestyle change and metformin both reduce type 2 diabetes incidence, there are little data on patient preferences in real-world, clinical settings.

Methods: The Prediabetes Informed Decisions and Education (PRIDE) study was a cluster-randomized trial of shared decision making (SDM) for diabetes prevention. In PRIDE, pharmacists engaged patients with prediabetes in SDM using a decision aid with information about both evidence-based options.

Mind the translational gap: using iPS cell models to bridge from genetic discoveries to perturbed pathways and therapeutic targets.

Autism spectrum disorder (ASD) comprises a group of neurodevelopmental disorders characterized by impaired social interactions as well as the presentation of restrictive and repetitive behaviors. ASD is highly heritable but genetically heterogenous with both common and rare genetic variants collaborating to predispose individuals to the disorder. In this review, we synthesize recent efforts to develop human induced pluripotent stem cell (iPSC)-derived models of ASD-related phenotypes.

Effectiveness of Shared Decision-making for Diabetes Prevention: 12-Month Results from the Prediabetes Informed Decision and Education (PRIDE) Trial.

Importance: Intensive lifestyle change (e.g., the Diabetes Prevention Program) and metformin reduce type 2 diabetes risk among patients with prediabetes.