Mitochondrial quality control in health and in Parkinson's disease.

As a central hub for cellular metabolism and intracellular signaling, the mitochondrion is a pivotal organelle, dysfunction of which has been linked to several human diseases including neurodegenerative disorders and in particular Parkinson's disease. An inherent challenge that mitochondria face is the continuous exposure to diverse stresses that increase their likelihood of dysregulation. In response, eukaryotic cells have evolved sophisticated quality control mechanisms to monitor, identify, repair, and/or eliminate abnormal or misfolded proteins within the mitochondrion and/or the dysfunctional mitochondrion itself. Chaperones identify unstable or otherwise abnormal conformations in mitochondrial proteins and can promote their refolding to recover their correct conformation and stability. However, if repair is not possible, the abnormal protein is selectively degraded to prevent potentially damaging interactions with other proteins or its oligomerization into toxic multimeric complexes. The autophagic-lysosomal system and the ubiquitin-proteasome system mediate the selective and targeted degradation of such abnormal or misfolded protein species. Mitophagy (a specific kind of autophagy) mediates the selective elimination of dysfunctional mitochondria, to prevent the deleterious effects of the dysfunctional organelles within the cell. Despite our increasing understanding of the molecular responses toward dysfunctional mitochondria, many key aspects remain relatively poorly understood. Here, we review the emerging mechanisms of mitochondrial quality control including quality control strategies coupled to mitochondrial import mechanisms. In addition, we review the molecular mechanisms regulating mitophagy, with an emphasis on the regulation of PINK1/Parkin-mediated mitophagy in cellular physiology and in the context of Parkinson's disease cell biology.

Tom20 gates PINK1 activity and mediates its tethering of the TOM and TIM23 translocases upon mitochondrial stress.

Mutations in PTEN-induced putative kinase 1 (PINK1) cause autosomal recessive early-onset Parkinson's disease (PD). PINK1 is a Ser/Thr kinase that regulates mitochondrial quality control by triggering mitophagy mediated by the ubiquitin (Ub) ligase Parkin. Upon mitochondrial damage, PINK1 accumulates on the outer mitochondrial membrane forming a high-molecular-weight complex with the translocase of the outer membrane (TOM). PINK1 then phosphorylates Ub, which enables recruitment and activation of Parkin followed by autophagic clearance of the damaged mitochondrion. Thus, Parkin-dependent mitophagy hinges on the stable accumulation of PINK1 on the TOM complex. Yet, the mechanism linking mitochondrial stressors to PINK1 accumulation and whether the translocases of the inner membrane (TIMs) are also involved remain unclear. Herein, we demonstrate that mitochondrial stress induces the formation of a PINK1-TOM-TIM23 supercomplex in human cultured cell lines, dopamine neurons, and midbrain organoids. Moreover, we show that PINK1 is required to stably tether the TOM to TIM23 complexes in response to stress such that the supercomplex fails to accumulate in cells lacking PINK1. This tethering is dependent on an interaction between the PINK1 N-terminal-C-terminal extension module and the cytosolic domain of the Tom20 subunit of the TOM complex, the disruption of which, by either designer or PD-associated PINK1 mutations, inhibits downstream mitophagy. Together, the findings provide key insight into how PINK1 interfaces with the mitochondrial import machinery, with important implications for the mechanisms of mitochondrial quality control and PD pathogenesis.

Machine learning nominates the inositol pathway and novel genes in Parkinson's disease.

There are 78 loci associated with Parkinson's disease in the most recent genome-wide association study (GWAS), yet the specific genes driving these associations are mostly unknown. Herein, we aimed to nominate the top candidate gene from each Parkinson's disease locus and identify variants and pathways potentially involved in Parkinson's disease. We trained a machine learning model to predict Parkinson's disease-associated genes from GWAS loci using genomic, transcriptomic and epigenomic data from brain tissues and dopaminergic neurons. We nominated candidate genes in each locus and identified novel pathways potentially involved in Parkinson's disease, such as the inositol phosphate biosynthetic pathway (INPP5F, IP6K2, ITPKB and PPIP5K2). Specific common coding variants in SPNS1 and MLX may be involved in Parkinson's disease, and burden tests of rare variants further support that CNIP3, LSM7, NUCKS1 and the polyol/inositol phosphate biosynthetic pathway are associated with the disease. Functional studies are needed to further analyse the involvements of these genes and pathways in Parkinson's disease.

ScRNAbox: empowering single-cell RNA sequencing on high performance computing systems.

BACKGROUND: Single-cell RNA sequencing (scRNAseq) offers powerful insights, but the surge in sample sizes demands more computational power than local workstations can provide. Consequently, high-performance computing (HPC) systems have become imperative. Existing web apps designed to analyze scRNAseq data lack scalability and integration capabilities, while analysis packages demand coding expertise, hindering accessibility. RESULTS: In response, we introduce scRNAbox, an innovative scRNAseq analysis pipeline meticulously crafted for HPC systems. This end-to-end solution, executed via the SLURM workload manager, efficiently processes raw data from standard and Hashtag samples. It incorporates quality control filtering, sample integration, clustering, cluster annotation tools, and facilitates cell type-specific differential gene expression analysis between two groups. We demonstrate the application of scRNAbox by analyzing two publicly available datasets. CONCLUSION: ScRNAbox is a comprehensive end-to-end pipeline designed to streamline the processing and analysis of scRNAseq data. By responding to the pressing demand for a user-friendly, HPC solution, scRNAbox bridges the gap between the growing computational demands of scRNAseq analysis and the coding expertise required to meet them.

Weakly electric fish distinguish between envelope stimuli arising from different behavioral contexts.

Understanding how sensory information is processed by the brain in order to give rise to behavior remains poorly understood in general. Here, we investigated the behavioral responses of the weakly electric fish Apteronotus albifrons to stimuli arising from different contexts, by measuring changes in the electric organ discharge (EOD) frequency. Specifically, we focused on envelopes, which can arise either because of movement (i.e. motion envelopes) or because of interactions between the electric fields of three of more fish (i.e. social envelopes). Overall, we found that the animal's EOD frequency effectively tracked the detailed time course of both motion and social envelopes. In general, behavioral sensitivity (i.e. gain) decreased while phase lag increased with increasing envelope and carrier frequency. However, changes in gain and phase lag as a function of changes in carrier frequency were more prominent for motion than for social envelopes in general. Importantly, we compared behavioral responses to motion and social envelopes with similar characteristics. Although behavioral sensitivities were similar, we observed an increased response lag for social envelopes, primarily for low carrier frequencies. Thus, our results imply that the organism can, based on behavioral responses, distinguish envelope stimuli resulting from movement from those that instead result from social interactions. We discuss the implications of our results for neural coding of envelopes and propose that behavioral responses to motion and social envelopes are mediated by different neural circuits in the brain.

The X-linked inhibitor of apoptosis regulates long-term depression and learning rate.

Hippocampal long-term depression (LTD) is an active form of synaptic plasticity that is necessary for consolidation of spatial memory, contextual fear memory, and novelty acquisition. Recent studies have shown that caspases (CASPs) play an important role in NMDA receptor-dependent LTD and are involved in postsynaptic remodeling and synaptic maturation. In the present study, we examined the role of X-linked inhibitor of apoptosis (XIAP), a putative endogenous CASP inhibitor, in synaptic plasticity in the hippocampus. Analysis in acute brain slices and in cultured hippocampal neurons revealed that XIAP deletion increases CASP-3 activity, enhances α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor internalization, sharply increases LTD, and significantly reduces synapse density. In vivo behaviors related to memory were also altered in XIAP(-/-) mice, with faster acquisition of spatial object location and increased fear memory observed. Together, these results indicate that XIAP plays an important physiologic role in regulating sublethal CASP-3 activity within central neurons and thereby facilitates synaptic plasticity and memory acquisition.-Gibon, J., Unsain, N., Gamache, K., Thomas, R. A., De Leon, A., Johnstone, A., Nader, K., Séguéla, P., Barker, P. A. The X-linked inhibitor of apoptosis regulates long-term depression and learning rate.

Transcriptomics of Human Brain Tissue in Parkinson's Disease: a Comparison of Bulk and Single-cell RNA Sequencing.

Parkinson's disease (PD) is a chronic and progressive neurodegenerative disease leading to motor dysfunction and, in some cases, dementia. Transcriptome analysis is one promising approach for characterizing PD and other neurodegenerative disorders by informing how specific disease events influence gene expression and contribute to pathogenesis. With the emergence of single-cell and single-nucleus RNA sequencing (scnRNA-seq) technologies, the transcriptional landscape of neurodegenerative diseases can now be described at the cellular level. As the application of scnRNA-seq is becoming routine, it calls to question how results at a single-cell resolution compare to those obtained from RNA sequencing of whole tissues (bulk RNA-seq), whether the findings are compatible, and how the assays are complimentary for unraveling the elusive transcriptional changes that drive neurodegenerative disease. Herein, we review the studies that have leveraged RNA-seq technologies to investigate PD. Through the integration of bulk and scnRNA-seq findings from human, post-mortem brain tissue, we use the PD literature as a case study to evaluate the compatibility of the results generated from each assay and demonstrate the complementarity of the sequencing technologies. Finally, through the lens of the PD transcriptomic literature, we evaluate the current feasibility of bulk and scnRNA-seq technologies to illustrate the necessity of both technologies for achieving a comprehensive insight into the mechanism by which gene expression promotes neurodegenerative disease. We conclude that the continued application of both assays will provide the greatest insight into neurodegenerative disease pathology, providing both cell-specific and whole-tissue level information.

CelltypeR: A flow cytometry pipeline to characterize single cells from brain organoids.

Motivated by the cellular heterogeneity in complex tissues, particularly in brain and induced pluripotent stem cell (iPSC)-derived brain models, we developed a complete workflow to reproducibly characterize cell types in complex tissues. Our approach combines a flow cytometry (FC) antibody panel with our computational pipeline CelltypeR, enabling dataset aligning, unsupervised clustering optimization, cell type annotating, and statistical comparisons. Applied to human iPSC derived midbrain organoids, it successfully identified the major brain cell types. We performed fluorescence-activated cell sorting of CelltypeR-defined astrocytes, radial glia, and neurons, exploring transcriptional states by single-cell RNA sequencing. Among the sorted neurons, we identified subgroups of dopamine neurons: one reminiscent of substantia nigra cells most vulnerable in Parkinson's disease. Finally, we used our workflow to track cell types across a time course of organoid differentiation. Overall, our adaptable analysis framework provides a generalizable method for reproducibly identifying cell types across FC datasets in complex tissues.

An adapted protocol to derive microglia from stem cells and its application in the study of CSF1R-related disorders.

BACKGROUND: Induced pluripotent stem cell-derived microglia (iMGL) represent an excellent tool in studying microglial function in health and disease. Yet, since differentiation and survival of iMGL are highly reliant on colony-stimulating factor 1 receptor (CSF1R) signaling, it is difficult to use iMGL to study microglial dysfunction associated with pathogenic defects in CSF1R. METHODS: Serial modifications to an existing iMGL protocol were made, including but not limited to changes in growth factor combination to drive microglial differentiation, until successful derivation of microglia-like cells from an adult-onset leukoencephalopathy with axonal spheroids and pigmented glia (ALSP) patient carrying a c.2350G > A (p.V784M) CSF1R variant. Using healthy control lines, the quality of the new iMGL protocol was validated through cell yield assessment, measurement of microglia marker expression, transcriptomic comparison to primary microglia, and evaluation of inflammatory and phagocytic activities. Similarly, molecular and functional characterization of the ALSP patient-derived iMGL was carried out in comparison to healthy control iMGL. RESULTS: The newly devised protocol allowed the generation of iMGL with enhanced transcriptomic similarity to cultured primary human microglia and with higher scavenging and inflammatory competence at ~ threefold greater yield compared to the original protocol. Using this protocol, decreased CSF1R autophosphorylation and cell surface expression was observed in iMGL derived from the ALSP patient compared to those derived from healthy controls. Additionally, ALSP patient-derived iMGL presented a migratory defect accompanying a temporal reduction in purinergic receptor P2Y12 (P2RY12) expression, a heightened capacity to internalize myelin, as well as heightened inflammatory response to Pam3CSK4. Poor P2RY12 expression was confirmed to be a consequence of CSF1R haploinsufficiency, as this feature was also observed following CSF1R knockdown or inhibition in mature control iMGL, and in CSF1RWT/KO and CSF1RWT/E633K iMGL compared to their respective isogenic controls. CONCLUSIONS: We optimized a pre-existing iMGL protocol, generating a powerful tool to study microglial involvement in human neurological diseases. Using the optimized protocol, we have generated for the first time iMGL from an ALSP patient carrying a pathogenic CSF1R variant, with preliminary characterization pointing toward functional alterations in migratory, phagocytic and inflammatory activities.

The p75NTR intracellular domain generated by neurotrophin-induced receptor cleavage potentiates Trk signaling.

The p75 neurotrophin receptor (p75NTR) potentiates Trk signaling, but the underlying mechanisms remain uncertain. Here, we examine the relationship between p75NTR cleavage and Trk signaling. We found that, in PC12 cells, nerve growth factor (NGF) induces rapid and robust alpha-secretase- and gamma-secretase-dependent cleavage of p75NTR, releasing the resulting intracellular domain into the cytosol. Brain-derived neurotrophic factor similarly induces p75NTR cleavage in primary cerebellar granule neurons. p75NTR cleavage occurs by means of Trk-dependent activation of MEK-Erk signaling and induction of alpha-secretase activity, and is independent of ligand binding to p75NTR. Neurons and PC12 cells lacking p75NTR display defects in neurotrophin-dependent Akt activation. Normal Akt activation is rescued using full-length p75NTR or the p75 intracellular domain, but not cleavage-resistant p75NTR. We then demonstrate that NGF-dependent growth arrest of PC12 cells requires p75NTR cleavage and generation of the intracellular domain. We conclude that generation of the soluble p75NTR intracellular domain by Trk-induced cleavage plays a fundamental role in Trk-dependent signaling events.

Trk-dependent ADAM17 activation facilitates neurotrophin survival signaling.

Signaling by TrkA and TrkB receptor tyrosine kinase is required for peripheral neuron survival. TrkA and TrkB signaling is facilitated by the p75 neurotrophin receptor (p75NTR), a member of the tumor necrosis factor (TNF) receptor superfamily, through mechanisms that remain obscure. Here, we demonstrate that TrkA and TrkB induces MEK-dependent phosphorylation of the transmembrane cysteine protease ADAM17 (a disintegrin and metalloprotease 17) at the intracellular residue threonine 735. Phosphorylation at this site activates ADAM17 and causes cleavage of p75NTR and production of the receptors' intracellular domain (p75NTR(ICD)) in PC12 cells and in primary cerebellar granule neurons. We show that Trk-induced ADAM17 phosphorylation and generation of the p75NTR(ICD) is required for neurotrophin-induced Erk and Akt activation and for neurotrophin-dependent survival signaling. Survival of PC12 cells maintained in 10 ng/ml nerve growth factor drops by 47% in cells depleted of ADAM17; this survival deficit is resolved if the p75NTR(ICD) is overexpressed in the ADAM17 depleted cells. These studies identify a novel signaling circuit in which Trk activates ADAM17-dependent p75NTR(ICD) production to feedback to sustain Trk signaling and Trk-dependent survival.

LGI1 is a Nogo receptor 1 ligand that antagonizes myelin-based growth inhibition.

Mutations in leucine-rich glioma inactivated (LGI1) are a genetic cause of autosomal dominant temporal lobe epilepsy with auditory features. LGI1 is a secreted protein that shares homology with members of the SLIT family, ligands that direct axonal repulsion and growth cone collapse, and we therefore considered the possibility that LGI1 may regulate neuronal process extension or growth cone collapse. Here we report that LGI1 does not affect growth directly but instead enhances neuronal growth on myelin-based inhibitory substrates and antagonizes myelin-induced growth cone collapse. We show that LGI1 mediates this effect by functioning as a specific Nogo receptor 1 (NgR1) ligand that antagonizes the action of myelin-based inhibitory cues. Finally, we demonstrate that NgR1 and ADAM22 physically associate to form a receptor complex in which NgR1 facilitates LGI1 binding to ADAM22.

Pharmacological Inhibition of Brain EGFR Activation By a BBB-penetrating Inhibitor, AZD3759, Attenuates α-synuclein Pathology in a Mouse Model of α-Synuclein Propagation.

Aggregation and deposition of α-synuclein (α-syn) in Lewy bodies within dopamine neurons of substantia nigra (SN) is the pathological hallmark of Parkinson's disease (PD). These toxic α-syn aggregates are believed to propagate from neuron-to-neuron and spread the α-syn pathology throughout the brain beyond dopamine neurons in a prion-like manner. Targeting propagation of such α-syn aggregates is of high interest but requires identifying pathways involving in this process. Evidence from previous Alzheimer's disease reports suggests that EGFR may be involved in the prion-like propagation and seeding of amyloid-ß. We show here that EGFR regulates the uptake of exogenous α-syn-PFFs and the levels of endogenous α-syn in cell cultures and a mouse model of α-syn propagation, respectively. Thus, we tested the therapeutic potentials of AZD3759, a highly selective BBB-penetrating EGFR inhibitor, in a preclinical mouse model of α-syn propagation. AZD3759 decreases activated EGFR levels in the brain and reduces phosphorylated α-synuclein (pSyn) pathology in brain sections, including striatum and SN. As AZD3759 is already in the clinic, this paper's results suggest a possible repositioning of AZD3759 as a disease-modifying approach for PD.

A Multistep Workflow to Evaluate Newly Generated iPSCs and Their Ability to Generate Different Cell Types.

Induced pluripotent stem cells (iPSCs) derived from human somatic cells have created new opportunities to generate disease-relevant cells. Thus, as the use of patient-derived stem cells has become more widespread, having a workflow to monitor each line is critical. This ensures iPSCs pass a suite of quality-control measures, promoting reproducibility across experiments and between labs. With this in mind, we established a multistep workflow to assess our newly generated iPSCs. Our workflow tests four benchmarks: cell growth, genomic stability, pluripotency, and the ability to form the three germline layers. We also outline a simple test for assessing cell growth and highlight the need to compare different growth media. Genomic integrity in the human iPSCs is analyzed by G-band karyotyping and a qPCR-based test for the detection of common karyotypic abnormalities. Finally, we confirm that the iPSC lines can differentiate into a given cell type, using a trilineage assay, and later confirm that each iPSC can be differentiated into one cell type of interest, with a focus on the generation of cortical neurons. Taken together, we present a multistep quality-control workflow to evaluate newly generated iPSCs and detail the findings on these lines as they are tested within the workflow.

Auto-qPCR; a python-based web app for automated and reproducible analysis of qPCR data.

Quantifying changes in DNA and RNA levels is essential in numerous molecular biology protocols. Quantitative real time PCR (qPCR) techniques have evolved to become commonplace, however, data analysis includes many time-consuming and cumbersome steps, which can lead to mistakes and misinterpretation of data. To address these bottlenecks, we have developed an open-source Python software to automate processing of result spreadsheets from qPCR machines, employing calculations usually performed manually. Auto-qPCR is a tool that saves time when computing qPCR data, helping to ensure reproducibility of qPCR experiment analyses. Our web-based app ( https://auto-q-pcr.com/ ) is easy to use and does not require programming knowledge or software installation. Using Auto-qPCR, we provide examples of data treatment, display and statistical analyses for four different data processing modes within one program: (1) DNA quantification to identify genomic deletion or duplication events; (2) assessment of gene expression levels using an absolute model, and relative quantification (3) with or (4) without a reference sample. Our open access Auto-qPCR software saves the time of manual data analysis and provides a more systematic workflow, minimizing the risk of errors. Our program constitutes a new tool that can be incorporated into bioinformatic and molecular biology pipelines in clinical and research labs.

Midbrain organoids with an SNCA gene triplication model key features of synucleinopathy.

SNCA, the first gene associated with Parkinson's disease, encodes the α-synuclein protein, the predominant component within pathological inclusions termed Lewy bodies. The presence of Lewy bodies is one of the classical hallmarks found in the brain of patients with Parkinson's disease, and Lewy bodies have also been observed in patients with other synucleinopathies. However, the study of α-synuclein pathology in cells has relied largely on two-dimensional culture models, which typically lack the cellular diversity and complex spatial environment found in the brain. Here, to address this gap, we use three-dimensional midbrain organoids, differentiated from human-induced pluripotent stem cells derived from patients carrying a triplication of the SNCA gene and from CRISPR/Cas9 corrected isogenic control iPSCs. These human midbrain organoids recapitulate key features of α-synuclein pathology observed in the brains of patients with synucleinopathies. In particular, we find that SNCA triplication human midbrain organoids express elevated levels of α-synuclein and exhibit an age-dependent increase in α-synuclein aggregation, manifested by the presence of both oligomeric and phosphorylated forms of α-synuclein. These phosphorylated α-synuclein aggregates were found in both neurons and glial cells and their time-dependent accumulation correlated with a selective reduction in dopaminergic neuron numbers. Thus, human midbrain organoids from patients carrying SNCA gene multiplication can reliably model key pathological features of Parkinson's disease and provide a powerful system to study the pathogenesis of synucleinopathies.

A molecular gradient along the longitudinal axis of the human hippocampus informs large-scale behavioral systems.

The functional organization of the hippocampus is distributed as a gradient along its longitudinal axis that explains its differential interaction with diverse brain systems. We show that the location of human tissue samples extracted along the longitudinal axis of the adult human hippocampus can be predicted within 2mm using the expression pattern of less than 100 genes. Futhermore, this model generalizes to an external set of tissue samples from prenatal human hippocampi. We examine variation in this specific gene expression pattern across the whole brain, finding a distinct anterioventral-posteriodorsal gradient. We find frontal and anterior temporal regions involved in social and motivational behaviors, and more functionally connected to the anterior hippocampus, to be clearly differentiated from posterior parieto-occipital regions involved in visuospatial cognition and more functionally connected to the posterior hippocampus. These findings place the human hippocampus at the interface of two major brain systems defined by a single molecular gradient.

The Nogo Receptor Ligand LGI1 Regulates Synapse Number and Synaptic Activity in Hippocampal and Cortical Neurons.

Leucine-rich glioma-inactivated protein 1 (LGI1) is a secreted neuronal protein and a Nogo receptor 1 (NgR1) ligand. Mutations in LGI1 in humans causes autosomal dominant lateral temporal lobe epilepsy and homozygous deletion of LGI1 in mice results in severe epileptic seizures that cause early postnatal death. NgR1 plays an important role in the development of CNS synapses and circuitry by limiting plasticity in the adult cortex via the activation of RhoA. These relationships and functions prompted us to examine the effect of LGI1 on synapse formation in vitro and in vivo. We report that application of LGI1 increases synaptic density in neuronal culture and that LGI1 null hippocampus has fewer dendritic mushroom spines than in wild-type (WT) littermates. Further, our electrophysiological investigations demonstrate that LGI1 null hippocampal neurons possess fewer and weaker synapses. RhoA activity is significantly increased in cortical cultures derived from LGI1 null mice and using a reconstituted system; we show directly that LGI1 antagonizes NgR1-tumor necrosis factor receptor orphan Y (TROY) signaling. Our data suggests that LGI1 enhances synapse formation in cortical and hippocampal neurons by reducing NgR1 signaling.

Identification of genetic variants of LGI1 and RTN4R (NgR1) linked to schizophrenia that are defective in NgR1-LGI1 signaling.

BACKGROUND: The protein NgR1 is encoded by RTN4R, a gene linked to schizophrenia. We previously reported NgR1 as receptor for the epilepsy-linked protein LGI1. NgR1 regulates synapse number and synaptic plasticity, whereas LGI1 antagonizes NgR1 signaling and promotes synapse formation. Impairments in synapse formation are common in neurological disease and we hypothesized that an LGI1-NgR1 signaling pathway may contribute to the development of schizophrenia. METHODS: We screened two unrelated schizophrenic populations for variants in RTN4R and LGI1 using whole exome sequencing and Sanger sequencing. We tested the ability of LGI1 to bind rare coding variants of NgR1 using a cell surface binding assays and the signaling ability of NgR1 using COS7 cell-spreading assays. RESULTS: We observed a previously reported rare coding variant in RTN4R (c.1195C>T, pR399W). We report the first LGI1 mutations to be identified in individuals with schizophrenia. Three different LGI1 mutations were found, two missense mutations (c.205G>A, p.V69I) and (c.313G>A, V105M), and an intronic variant (g.897T>C) that likely leads to a protein truncation. We found NgR1(R119W) and NgR1(277C) have a reduced ability to bind LGI1 in a cell surface binding assay. COS7 cell-spreading assays reveal that NgR1 mutants are impaired in their ability to mediate RhoA activation. CONCLUSION: Variants in NgR1 and LGI1 may be associated with schizophrenia and variants in NgR1 found in schizophrenic patients have impaired LGI1-NgR1 signaling. Impaired LGI1-NgR1 signaling may contribute to disease progression.