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. METHODS: To model PTHS, we differentiated human cortical neurons from human induced pluripotent stem cells that were derived from patients with PTHS and neurotypical individuals. To identify pathophysiology and disease mechanisms, we assayed cortical neurons with whole-cell electrophysiology, Ca2+ imaging, multielectrode arrays, immunocytochemistry, and RNA sequencing. RESULTS: Cortical neurons derived from patients with TCF4 mutations showed deficits in spontaneous synaptic transmission, network excitability, and homeostatic plasticity. Transcriptomic analysis indicated that these phenotypes resulted in part from altered expression of genes involved in presynaptic neurotransmission and identified the presynaptic binding protein RIMBP2 as the most differentially expressed gene in PTHS neurons. Remarkably, TCF4-dependent deficits in spontaneous synaptic transmission and network excitability were rescued by increasing RIMBP2 expression in presynaptic neurons. CONCLUSIONS: Taken together, these results identify TCF4 as a critical transcriptional regulator of human synaptic development and plasticity and specifically identifies dysregulation of presynaptic function as an early pathophysiology in PTHS.

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. The resulting protein network is enriched for common variant risk of schizophrenia in Europeans and East Asians, is down-regulated in layer 5/6 cortical neurons of individuals affected by schizophrenia, and can complement fine-mapping and eQTL data to prioritize additional genes in GWAS loci. A sub-network centered on HCN1 is enriched for common variant risk and contains proteins (HCN4 and AKAP11) enriched for rare protein-truncating mutations in individuals with schizophrenia and bipolar disorder. Our findings showcase brain cell-type-specific interactomes as an organizing framework to facilitate interpretation of genetic and transcriptomic data in schizophrenia and its related disorders.

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. We leveraged the network data to show that the ASD-linked brain-specific isoform of ANK2 is important for its interactions with synaptic proteins and to characterize a PTEN-AKAP8L interaction that influences neuronal growth. The IGF2BP1-3 complex emerged as a convergent point in the network that may regulate a transcriptional circuit of ASD-associated genes. Our findings showcase cell-type-specific interactomes as a framework to complement genetic and transcriptomic data and illustrate how both individual and convergent interactions can lead to biological insights into ASDs.

TCF4 mutations disrupt synaptic function through dysregulation of RIMBP2 in patient-derived cortical neurons.

Genetic variation in the transcription factor 4 ( TCF4) gene is associated with risk for a variety of developmental and psychiatric conditions, which includes a syndromic form of ASD called Pitt Hopkins Syndrome (PTHS). TCF4 encodes an activity-dependent transcription factor that is highly expressed during cortical development and in animal models is 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. Here we show that cortical neurons derived from patients with TCF4 mutations have deficits in spontaneous synaptic transmission, network excitability and homeostatic plasticity. Transcriptomic analysis indicates these phenotypes result from altered expression of genes involved in presynaptic neurotransmission and identifies the presynaptic binding protein, RIMBP2 as the most differentially expressed gene in PTHS neurons. Remarkably, TCF4-dependent deficits in spontaneous synaptic transmission and network excitability were rescued by increasing RIMBP2 expression in presynaptic neurons. Together, these results identify TCF4 as a critical transcriptional regulator of human synaptic development and plasticity and specifically identifies dysregulation of presynaptic function as an early pathophysiology in PTHS.

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. We use Genoppi to analyze 16 cell-type-specific protein interaction datasets of four proteins (BCL2, TDP-43, MDM2, PTEN) involved in cancer and neurological disease. Through systematic quality control of the data and integration with published protein interactions, we show a general pattern of both cell-type-independent and cell-type-specific interactions across three cancer cell types and one human iPSC-derived neuronal cell type. Furthermore, through the integration of proteomic and genetic datasets in Genoppi, our results suggest that the neuron-specific interactions of these proteins are mediating their genetic involvement in neurodegenerative diseases. Importantly, our analyses suggest that human iPSC-derived neurons are a relevant model system for studying the involvement of BCL2 and TDP-43 in amyotrophic lateral sclerosis.

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. We recorded which diabetes prevention option(s) participants chose after the SDM visit. We also evaluated logistic regression models examining predictors of choosing intensive lifestyle change ± metformin, compared to metformin or usual care, and predictors of choosing metformin ± intensive lifestyle change, compared to intensive lifestyle change or usual care. RESULTS: Among PRIDE participants (n = 515), 55% chose intensive lifestyle change, 8.5% chose metformin, 15% chose both options, and 21.6% declined both options. Women (odds ratio [OR] = 1.60, P = 0.023) had higher odds than men of choosing intensive lifestyle change. Patients >60 years old (OR = 0.50, P = 0.028) had lower odds than patients <50 years old of choosing metformin. Participants with higher body mass index (BMI) had higher odds of choosing intensive lifestyle change (OR = 1.07 per BMI unit increase, P = 0.005) v. other options and choosing metformin (OR = 1.06 per BMI unit increase, P = 0.008) v. other options. CONCLUSIONS: Patients with prediabetes are making choices for diabetes prevention that generally align with recommendations and expected benefits from the published literature. Our results are important for policy makers and clinicians, as well as program planners developing systemwide approaches for diabetes prevention.

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. We firstly address concerns regarding the relevance and validity of available neuronal iPSC-derived models. We then critically evaluate the robustness of various differentiation and cell culture protocols used for producing cell types of relevance to ASD. By exploring iPSC models of ASD reported thus far, we examine to what extent cellular and neuronal phenotypes with potential relevance to ASD can be linked to genetic variants found to underlie it. Lastly, we outline promising strategies by which iPSC technology can both enhance the power of genetic studies to identify ASD risk factors and nominate pathways that are disrupted across groups of ASD patients that might serve as common points for therapeutic intervention.

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. However, real-world uptake remains low. Shared decision-making (SDM) may increase awareness and help patients select and follow through with informed options for diabetes prevention that are aligned with their preferences. OBJECTIVE: To test the effectiveness of a prediabetes SDM intervention. DESIGN: Cluster randomized controlled trial. SETTING: Twenty primary care clinics within a large regional health system. PARTICIPANTS: Overweight/obese adults with prediabetes (BMI ≥ 24 kg/m2 and HbA1c 5.7-6.4%) were enrolled from 10 SDM intervention clinics. Propensity score matching was used to identify control patients from 10 usual care clinics. INTERVENTION: Intervention clinic patients were invited to participate in a face-to-face SDM visit with a pharmacist who used a decision aid (DA) to describe prediabetes and four possible options for diabetes prevention: DPP, DPP ± metformin, metformin only, or usual care. MAIN OUTCOMES AND MEASURES: Primary endpoint was uptake of DPP (≥ 9 sessions), metformin, or both strategies at 4 months. Secondary endpoint was weight change (lbs.) at 12 months. RESULTS: Uptake of DPP and/or metformin was higher among SDM participants (n = 351) than controls receiving usual care (n = 1028; 38% vs. 2%, p < .001). At 12-month follow-up, adjusted weight loss (lbs.) was greater among SDM participants than controls (- 5.3 vs. - 0.2, p < .001). LIMITATIONS: Absence of DPP supplier participation data for matched patients in usual care clinics. CONCLUSIONS AND RELEVANCE: A prediabetes SDM intervention led by pharmacists increased patient engagement in evidence-based options for diabetes prevention and was associated with significantly greater uptake of DPP and/or metformin at 4 months and weight loss at 12 months. Prediabetes SDM may be a promising approach to enhance prevention efforts among patients at increased risk. TRIAL REGISTRATION: This study was registered at clinicaltrails.gov (NCT02384109)).