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Understanding the normal function of the Huntingtin (HTT) protein is of significance in the design and implementation of therapeutic strategies for Huntington's disease (HD). Expansion of the CAG repeat in the HTT gene, encoding an expanded polyglutamine (polyQ) repeat within the HTT protein, causes HD and may compromise HTT's normal activity contributing to HD pathology. Here, we investigated the previously defined role of HTT in autophagy specifically through studying HTT's association with ubiquitin. We find that HTT interacts directly with ubiquitin in vitro. Tandem affinity purification was used to identify ubiquitinated and ubiquitin-associated proteins that copurify with a HTT N-terminal fragment under basal conditions. Copurification is enhanced by HTT polyQ expansion and reduced by mimicking HTT serine 421 phosphorylation. The identified HTT-interacting proteins include RNA-binding proteins (RBPs) involved in mRNA translation, proteins enriched in stress granules, the nuclear proteome, the defective ribosomal products (DRiPs) proteome and the brain-derived autophagosomal proteome. To determine whether the proteins interacting with HTT are autophagic targets, HTT knockout (KO) cells and immunoprecipitation of lysosomes were used to investigate autophagy in the absence of HTT. HTT KO was associated with reduced abundance of mitochondrial proteins in the lysosome, indicating a potential compromise in basal mitophagy, and increased lysosomal abundance of RBPs which may result from compensatory up-regulation of starvation-induced macroautophagy. We suggest HTT is critical for appropriate basal clearance of mitochondrial proteins and RBPs, hence reduced HTT proteostatic function with mutation may contribute to the neuropathology of HD.

DNA damage is a common cellular feature seen in cancer and neurodegenerative disease, but fast and accurate methods for quantifying DNA damage are lacking. Comet assays are a biochemical tool to measure DNA damage based on the migration of broken DNA strands towards a positive electrode, which creates a quantifiable 'tail' behind the cell. However, a major limitation of this approach is the time needed for analysis of comets in the images with available open-source algorithms. The requirement for manual curation and the laborious pre- and post-processing steps can take hours to days. To overcome these limitations, we developed AutoComet, a new open-source algorithm for comet analysis that utilizes automated comet segmentation and quantification of tail parameters. AutoComet first segments and filters comets based on size and intensity and then filters out comets without a well-connected head and tail, which significantly increases segmentation accuracy. Because AutoComet is fully automated, it minimizes curator bias and is scalable, decreasing analysis time over ten-fold, to less than 3 s per comet. AutoComet successfully detected statistically significant differences in tail parameters between cells with and without induced DNA damage, and was more comparable to the results of manual curation than other open-source software analysis programs. We conclude that the AutoComet algorithm provides a fast, unbiased and accurate method to quantify DNA damage that avoids the inherent limitations of manual curation and will significantly improve the ability to detect DNA damage.

Using induced pluripotent stem cells (iPSCs) to understand the mechanisms of neurological disease holds great promise; however, there is a lack of well-curated lines from a large array of participants. Answer ALS has generated over 1,000 iPSC lines from control and amyotrophic lateral sclerosis (ALS) patients along with clinical and whole-genome sequencing data. The current report summarizes cell marker and gene expression in motor neuron cultures derived from 92 healthy control and 341 ALS participants using a 32-day differentiation protocol. This is the largest set of iPSCs to be differentiated into motor neurons, and characterization suggests that cell composition and sex are significant sources of variability that need to be carefully controlled for in future studies. These data are reported as a resource for the scientific community that will utilize Answer ALS data for disease modeling using a wider array of omics being made available for these samples.

The Foundational Data Initiative for Parkinson Disease (FOUNDIN-PD) is an international collaboration producing fundamental resources for Parkinson disease (PD). FOUNDIN-PD generated a multi-layered molecular dataset in a cohort of induced pluripotent stem cell (iPSC) lines differentiated to dopaminergic (DA) neurons, a major affected cell type in PD. The lines were derived from the Parkinson's Progression Markers Initiative study, which included participants with PD carrying monogenic PD variants, variants with intermediate effects, and variants identified by genome-wide association studies and unaffected individuals. We generated genetic, epigenetic, regulatory, transcriptomic, and longitudinal cellular imaging data from iPSC-derived DA neurons to understand molecular relationships between disease-associated genetic variation and proximate molecular events. These data reveal that iPSC-derived DA neurons provide a valuable cellular context and foundational atlas for modeling PD genetic risk. We have integrated these data into a FOUNDIN-PD data browser as a resource for understanding the molecular pathogenesis of PD.

Zika virus (ZIKV) infects fetal neural progenitor cells (NPCs) causing severe neurodevelopmental disorders in utero. Multiple pathways involved in normal brain development are dysfunctional in infected NPCs but how ZIKV centrally reprograms these pathways remains unknown. Here we show that ZIKV infection disrupts subcellular partitioning of host transcripts critical for neurodevelopment in NPCs and functionally link this process to the up-frameshift protein 1 (UPF1). UPF1 is an RNA-binding protein known to regulate decay of cellular and viral RNAs and is less expressed in ZIKV-infected cells. Using infrared crosslinking immunoprecipitation and RNA sequencing (irCLIP-Seq), we show that a subset of mRNAs loses UPF1 binding in ZIKV-infected NPCs, consistent with UPF1's diminished expression. UPF1 target transcripts, however, are not altered in abundance but in subcellular localization, with mRNAs accumulating in the nucleus of infected or UPF1 knockdown cells. This leads to diminished protein expression of FREM2, a protein required for maintenance of NPC identity. Our results newly link UPF1 to the regulation of mRNA transport in NPCs, a process perturbed during ZIKV infection.

Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iPS) cell lines, multi-omic data derived from iPS neurons and longitudinal clinical and smartphone data from over 1,000 patients with ALS. This resource provides population-level biological and clinical data that may be employed to identify clinical-molecular-biochemical subtypes of amyotrophic lateral sclerosis (ALS). A unique smartphone-based system was employed to collect deep clinical data, including fine motor activity, speech, breathing and linguistics/cognition. The iPS spinal neurons were blood derived from each patient and these cells underwent multi-omic analytics including whole-genome sequencing, RNA transcriptomics, ATAC-sequencing and proteomics. The intent of these data is for the generation of integrated clinical and biological signatures using bioinformatics, statistics and computational biology to establish patterns that may lead to a better understanding of the underlying mechanisms of disease, including subgroup identification. A web portal for open-source sharing of all data was developed for widespread community-based data analytics.

A major advance in the study of Huntington's disease (HD) has been the development of human disease models employing induced pluripotent stem cells (iPSCs) derived from patients with HD. Because iPSCs provide an unlimited source of cells and can be obtained from large numbers of HD patients, they are a uniquely valuable tool for investigating disease mechanisms and for discovering potential disease-modifying therapeutics. Here, we summarize some of the important findings in HD pathophysiology that have emerged from studies of patient-derived iPSC lines. Because they retain the genome and actual disease mutations of the patient, they provide a cell source to investigate genetic contributions to the disease. iPSCs provide advantages over other disease models. While iPSC-based technology erases some epigenetic marks, newly developed transdifferentiation methods now let us investigate epigenetic factors that control expression of mutant huntingtin (mHTT). Human HD iPSC lines allow us to investigate how endogenous levels of mHTT affect cell health, in contrast to other models that often rely on overexpressing the protein. iPSCs can be differentiated into neurons and other disease-related cells such as astrocytes from different brain regions to study brain regional differences in the disease process, as well as the cell-cell dependencies involved in HD-associated neurodegeneration. They also serve as a tissue source to investigate factors that impact CAG repeat instability, which is involved in regional differences in neurodegeneration in the HD brain. Human iPSC models can serve as a powerful model system to identify genetic modifiers that may impact disease onset, progression, and symptomatology, providing novel molecular targets for drug discovery.

Neurotoxicity can be detected in live microscopy by morphological changes such as retraction of neurites, fragmentation, blebbing of the neuronal soma and ultimately the disappearance of fluorescently labeled neurons. However, quantification of these features is often difficult, low-throughput, and imprecise due to the overreliance on human curation. Recently, we showed that convolutional neural network (CNN) models can outperform human curators in the assessment of neuronal death from images of fluorescently labeled neurons, suggesting that there is information within the images that indicates toxicity but that is not apparent to the human eye. In particular, the CNN's decision strategy indicated that information within the nuclear region was essential for its superhuman performance. Here, we systematically tested this prediction by comparing images of fluorescent neuronal morphology from nuclear-localized fluorescent protein to those from freely diffused fluorescent protein for classifying neuronal death. We found that biomarker-optimized (BO-) CNNs could learn to classify neuronal death from fluorescent protein-localized nuclear morphology (mApple-NLS-CNN) alone, with super-human accuracy. Furthermore, leveraging methods from explainable artificial intelligence, we identified novel features within the nuclear-localized fluorescent protein signal that were indicative of neuronal death. Our findings suggest that the use of a nuclear morphology marker in live imaging combined with computational models such mApple-NLS-CNN can provide an optimal readout of neuronal death, a common result of neurotoxicity.

Parkinson's disease (PD) is the second-most prevalent neurodegenerative disorder, characterized by the loss of dopaminergic neurons (mDA) in the midbrain. The underlying mechanisms are only partly understood and there is no treatment to reverse PD progression. Here, we investigated the disease mechanism using mDA neurons differentiated from human induced pluripotent stem cells (hiPSCs) carrying the ILE368ASN mutation within the PINK1 gene, which is strongly associated with PD. Single-cell RNA sequencing (RNAseq) and gene expression analysis of a PINK1-ILE368ASN and a control cell line identified genes differentially expressed during mDA neuron differentiation. Network analysis revealed that these genes form a core network, members of which interact with all known 19 protein-coding Parkinson's disease-associated genes. This core network encompasses key PD-associated pathways, including ubiquitination, mitochondrial function, protein processing, RNA metabolism, and vesicular transport. Proteomics analysis showed a consistent alteration in proteins of dopamine metabolism, indicating a defect of dopaminergic metabolism in PINK1-ILE368ASN neurons. Our findings suggest the existence of a network onto which pathways associated with PD pathology converge, and offers an inclusive interpretation of the phenotypic heterogeneity of PD.

Cellular events underlying neurodegenerative disease may be captured by longitudinal live microscopy of neurons. While the advent of robot-assisted microscopy has helped scale such efforts to high-throughput regimes with the statistical power to detect transient events, time-intensive human annotation is required. We addressed this fundamental limitation with biomarker-optimized convolutional neural networks (BO-CNNs): interpretable computer vision models trained directly on biosensor activity. We demonstrate the ability of BO-CNNs to detect cell death, which is typically measured by trained annotators. BO-CNNs detected cell death with superhuman accuracy and speed by learning to identify subcellular morphology associated with cell vitality, despite receiving no explicit supervision to rely on these features. These models also revealed an intranuclear morphology signal that is difficult to spot by eye and had not previously been linked to cell death, but that reliably indicates death. BO-CNNs are broadly useful for analyzing live microscopy and essential for interpreting high-throughput experiments.

Neurodegenerative diseases are challenging for systems biology because of the lack of reliable animal models or patient samples at early disease stages. Induced pluripotent stem cells (iPSCs) could address these challenges. We investigated DNA, RNA, epigenetics, and proteins in iPSC-derived motor neurons from patients with ALS carrying hexanucleotide expansions in C9ORF72. Using integrative computational methods combining all omics datasets, we identified novel and known dysregulated pathways. We used a C9ORF72 Drosophila model to distinguish pathways contributing to disease phenotypes from compensatory ones and confirmed alterations in some pathways in postmortem spinal cord tissue of patients with ALS. A different differentiation protocol was used to derive a separate set of C9ORF72 and control motor neurons. Many individual -omics differed by protocol, but some core dysregulated pathways were consistent. This strategy of analyzing patient-specific neurons provides disease-related outcomes with small numbers of heterogeneous lines and reduces variation from single-omics to elucidate network-based signatures.

Cell death is a critical process that occurs normally in health and disease. However, its study is limited due to available technologies that only detect very late stages in the process or specific death mechanisms. Here, we report the development of a family of fluorescent biosensors called genetically encoded death indicators (GEDIs). GEDIs specifically detect an intracellular Ca2+ level that cells achieve early in the cell death process and that marks a stage at which cells are irreversibly committed to die. The time-resolved nature of a GEDI delineates a binary demarcation of cell life and death in real time, reformulating the definition of cell death. We demonstrate that GEDIs acutely and accurately report death of rodent and human neurons in vitro, and show that GEDIs enable an automated imaging platform for single cell detection of neuronal death in vivo in zebrafish larvae. With a quantitative pseudo-ratiometric signal, GEDIs facilitate high-throughput analysis of cell death in time-lapse imaging analysis, providing the necessary resolution and scale to identify early factors leading to cell death in studies of neurodegeneration.

Persistent cytoplasmic aggregates containing RNA binding proteins (RBPs) are central to the pathogenesis of late-onset neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS). These aggregates share components, molecular mechanisms, and cellular protein quality control pathways with stress-induced RNA granules (SGs). Here, we assess the impact of stress on the global mRNA localization landscape of human pluripotent stem cell-derived motor neurons (PSC-MNs) using subcellular fractionation with RNA sequencing and proteomics. Transient stress disrupts subcellular RNA and protein distributions, alters the RNA binding profile of SG- and ALS-relevant RBPs and recapitulates disease-associated molecular changes such as aberrant splicing of STMN2. Although neurotypical PSC-MNs re-establish a normal subcellular localization landscape upon recovery from stress, cells harboring ALS-linked mutations are intransigent and display a delayed-onset increase in neuronal cell death. Our results highlight subcellular molecular distributions as predictive features and underscore the utility of cellular stress as a paradigm to study ALS-relevant mechanisms.

Human genetics provides unbiased insights into the causes of human disease, which can be used to create a foundation for effective ways to more accurately diagnose patients, stratify patients for more successful clinical trials, discover and develop new therapies, and ultimately help patients choose the safest and most promising therapeutic option based on their risk profile. But the process for translating basic observations from human genetics studies into pathogenic disease mechanisms and treatments is laborious and complex, and this challenge has particularly slowed the development of interventions for neurodegenerative disease. In this review, we discuss the many steps in the process, the important considerations at each stage, and some of the latest tools and technologies that are available to help investigators translate insights from human genetics into diagnostic and therapeutic strategies that will lead to the sort of advances in clinical care that make a difference for patients.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Altered cellular metabolism is believed to be an important contributor to pathogenesis of the neurodegenerative disorder Huntington's disease (HD). Research has primarily focused on mitochondrial toxicity, which can cause death of the vulnerable striatal neurons, but other aspects of metabolism have also been implicated. Most previous studies have been carried out using postmortem human brain or non-human cells. Here, we studied bioenergetics in an induced pluripotent stem cell-based model of the disease. We found decreased adenosine triphosphate (ATP) levels in HD cells compared to controls across differentiation stages and protocols. Proteomics data and multiomics network analysis revealed normal or increased levels of mitochondrial messages and proteins, but lowered expression of glycolytic enzymes. Metabolic experiments showed decreased spare glycolytic capacity in HD neurons, while maximal and spare respiratory capacities driven by oxidative phosphorylation were largely unchanged. ATP levels in HD neurons could be rescued with addition of pyruvate or late glycolytic metabolites, but not earlier glycolytic metabolites, suggesting a role for glycolytic deficits as part of the metabolic disturbance in HD neurons. Pyruvate or other related metabolic supplements could have therapeutic benefit in HD.

Frontotemporal degeneration (FTD) is a complex disease presenting as a spectrum of clinical disorders with progressive degeneration of frontal and temporal brain cortices and extensive neuroinflammation that result in personality and behavior changes, and eventually, death. There are currently no effective therapies for FTD. While 60-70% of FTD patients are sporadic cases, the other 30-40% are heritable (familial) cases linked to mutations in several known genes. We focus here on FTD caused by mutations in the GRN gene, which encodes a secreted protein, progranulin (PGRN), that has diverse roles in regulating cell survival, immune responses, and autophagy and lysosome function in the brain. FTD-linked mutations in GRN reduce brain PGRN levels that lead to autophagy and lysosome dysfunction, TDP43 accumulation, excessive microglial activation, astrogliosis, and neuron death through still poorly understood mechanisms. PGRN insufficiency has also been linked to Alzheimers disease (AD), and so the development of therapeutics for GRN-linked FTD that restore PGRN levels and function may have broader application for other neurodegenerative diseases. This review focuses on a strategy to increase PGRN to functional, healthy levels in the brain by identifying novel genetic and chemical modulators of neuronal PGRN levels. This article is part of the special issue entitled The Quest for Disease-Modifying Therapies for Neurodegenerative Disorders.

Frontotemporal degeneration (FTD) is a complex disease presenting as a spectrum of clinical disorders with progressive degeneration of frontal and temporal brain cortices and extensive neuroinflammation that result in personality and behavior changes, and eventually, death. There are currently no effective therapies for FTD. While 60-70% of FTD patients are sporadic cases, the other 30-40% are heritable (familial) cases linked to mutations in several known genes. We focus here on FTD caused by mutations in the GRN gene, which encodes a secreted protein, progranulin (PGRN), that has diverse roles in regulating cell survival, immune responses, and autophagy and lysosome function in the brain. FTD-linked mutations in GRN reduce brain PGRN levels that lead to autophagy and lysosome dysfunction, TDP43 accumulation, excessive microglial activation, astrogliosis, and neuron death through still poorly understood mechanisms. PGRN insufficiency has also been linked to Alzheimer's disease (AD), and so the development of therapeutics for GRN-linked FTD that restore PGRN levels and function may have broader application for other neurodegenerative diseases. This review focuses on a strategy to increase PGRN to functional, healthy levels in the brain by identifying novel genetic and chemical modulators of neuronal PGRN levels. This article is part of the special issue entitled 'The Quest for Disease-Modifying Therapies for Neurodegenerative Disorders'.

The autophagy lysosomal pathway (ALP) is a major mechanism for degrading intracellular macromolecules. The catabolic products can then be used by the cell for energy or as building blocks to make other macromolecules. Since its discovery, a variety of cellular pathways have emerged that target components with varying specificity for lysosomal degradation. Under some circumstances, lysosomes may release their contents into the extracellular space where they may serve signaling or pathogenic functions. The ALP is active in healthy cells, and the level of activity can be regulated by nutrient-sensing and metabolic signaling pathways. The ALP is the primary pathway by which lipids and damaged organelles are degraded and may be the only pathway capable of degrading aggregated proteins. As such, there has been intense interest in understanding the role of the ALP in the accumulation of aggregated misfolded proteins characteristic of many of the major adult-onset neurodegenerative diseases. This review focuses on recent advances in our understanding of the ALP and its potential relationship to the pathogenesis and treatment of neurodegenerative diseases.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

BackgroundGenome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease.MethodsWe did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation.FindingsBetween Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16-36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10-7).InterpretationThese data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data.FundingThe National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources).

Introduction: Neurodegenerative diseases affect millions of people worldwide. Neurodegeneration is gradual over time, characterized by neuronal death that causes deterioration of cognitive or motor functions, ultimately leading to the patient's death. Currently, there are no treatments that effectively slow the progression of any neurodegenerative disease, but improved microscopy assays and models for neurodegeneration could lead the way to the discovery of disease-modifying therapeutics. Areas covered: Herein, the authors describe cell-based assays used to discover drugs with the potential to slow neurodegeneration, and their associated disease models. They focus on microscopy technologies that can be adapted to a high-throughput screening format that both detect cell death and monitor early signs of neurodegeneration and functional changes to identify drugs that the block early stages of neurodegeneration. Expert opinion: Many different phenotypes have been used in screens for the development of therapeutics towards neurodegenerative disease. The context of each phenotype in relation to neurodegeneration must be established to identify therapeutics likely to successfully target and treat disease. The use of improved models of neurodegeneration, statistical analyses, computational models, and improved markers of neuronal death will help in this pursuit and lead to better screening methods to identify therapeutic compounds against neurodegenerative disease.

Stress granules (SGs) form during cellular stress and are implicated in neurodegenerative diseases such as amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD). To yield insights into the role of SGs in pathophysiology, we performed a high-content screen to identify small molecules that alter SG properties in proliferative cells and human iPSC-derived motor neurons (iPS-MNs). One major class of active molecules contained extended planar aromatic moieties, suggesting a potential to intercalate in nucleic acids. Accordingly, we show that several hit compounds can prevent the RNA-dependent recruitment of the ALS-associated RNA-binding proteins (RBPs) TDP-43, FUS, and HNRNPA2B1 into SGs. We further demonstrate that transient SG formation contributes to persistent accumulation of TDP-43 into cytoplasmic puncta and that our hit compounds can reduce this accumulation in iPS-MNs from ALS patients. We propose that compounds with planar moieties represent a promising starting point to develop small-molecule therapeutics for treating ALS/FTD.

Current approaches for dynamic profiling of single cells rely on dissociated cultures, which lack important biological features existing in tissues. Organotypic slice cultures preserve aspects of structural and synaptic organisation within the brain and are amenable to microscopy, but established techniques are not well adapted for high throughput or longitudinal single cell analysis. Here we developed a custom-built, automated confocal imaging platform, with improved organotypic slice culture and maintenance. The approach enables fully automated image acquisition and four-dimensional tracking of morphological changes within individual cells in organotypic cultures from rodent and human primary tissues for at least 3 weeks. To validate this system, we analysed neurons expressing a disease-associated version of huntingtin (HTT586Q138-EGFP), and observed that they displayed hallmarks of Huntington's disease and died sooner than controls. By facilitating longitudinal single-cell analyses of neuronal physiology, our system bridges scales necessary to attain statistical power to detect developmental and disease phenotypes.

Deficient progranulin levels cause dose-dependent neurological syndromes: haploinsufficiency leads to frontotemporal lobar degeneration (FTLD) and nullizygosity produces adult-onset neuronal ceroid lipofuscinosis. Mechanisms controlling progranulin levels are largely unknown. To better understand progranulin regulation, we performed a genome-wide RNAi screen using an ELISA-based platform to discover genes that regulate progranulin levels in neurons. We identified 830 genes that raise or lower progranulin levels by at least 1.5-fold in Neuro2a cells. When inhibited by siRNA or some by submicromolar concentrations of small-molecule inhibitors, 33 genes of the druggable genome increased progranulin levels in mouse primary cortical neurons; several of these also raised progranulin levels in FTLD model mouse neurons. "Hit" genes regulated progranulin by transcriptional or posttranscriptional mechanisms. Pathway analysis revealed enrichment of hit genes from the autophagy-lysosome pathway (ALP), suggesting a key role for this pathway in regulating progranulin levels. Progranulin itself regulates lysosome function. We found progranulin deficiency in neurons increased autophagy and caused abnormally enlarged lysosomes and boosting progranulin levels restored autophagy and lysosome size to control levels. Our data link the ALP to neuronal progranulin: progranulin levels are regulated by autophagy and, in turn, progranulin regulates the ALP. Restoring progranulin levels by targeting genetic modifiers reversed FTLD functional deficits, opening up potential opportunities for future therapeutics development.SIGNIFICANCE STATEMENT Progranulin regulates neuron and immune functions and is implicated in aging. Loss of one functional allele causes haploinsufficiency and leads to frontotemporal lobar degeneration (FTLD), the second leading cause of dementia. Progranulin gene polymorphisms are linked to Alzheimer's disease (AD) and complete loss of function causes neuronal ceroid lipofuscinosis. Despite the critical role of progranulin levels in neurodegenerative disease risk, almost nothing is known about their regulation. We performed an unbiased screen and identified specific pathways controlling progranulin levels in neurons. Modulation of these pathways restored levels in progranulin-deficient neurons and reversed FTLD phenotypes. We provide a new comprehensive understanding of the genetic regulation of progranulin levels and identify potential targets to treat FTLD and other neurodegenerative diseases, including AD.

BackgroundPD is a complex polygenic disorder. In recent years, several genes from the endocytic membrane-trafficking pathway have been suggested to contribute to disease etiology. However, a systematic analysis of pathway-specific genetic risk factors is yet to be performed.ObjectivesTo comprehensively study the role of the endocytic membrane-trafficking pathway in the risk of PD.MethodsLinkage disequilibrium score regression was used to estimate PD heritability explained by 252 genes involved in the endocytic membrane-trafficking pathway including genome-wide association studies data from 18,869 cases and 22,452 controls. We used pathway-specific single-nucleotide polymorphisms to construct a polygenic risk score reflecting the cumulative risk of common variants. To prioritize genes for follow-up functional studies, summary-data based Mendelian randomization analyses were applied to explore possible functional genomic associations with expression or methylation quantitative trait loci.ResultsThe heritability estimate attributed to endocytic membrane-trafficking pathway was 3.58% (standard error = 1.17). Excluding previously nominated PD endocytic membrane-trafficking pathway genes, the missing heritability was 2.21% (standard error = 0.42). Random heritability simulations were estimated to be 1.44% (standard deviation = 0.54), indicating that the unbiased total heritability explained by the endocytic membrane-trafficking pathway was 2.14%. Polygenic risk score based on endocytic membrane-trafficking pathway showed a 1.25 times increase of PD risk per standard deviation of genetic risk. Finally, Mendelian randomization identified 11 endocytic membrane-trafficking pathway genes showing functional consequence associated to PD risk.ConclusionsWe provide compelling genetic evidence that the endocytic membrane-trafficking pathway plays a relevant role in disease etiology. Further research on this pathway is warranted given that critical effort should be made to identify potential avenues within this biological process suitable for therapeutic interventions. © 2019 International Parkinson and Movement Disorder Society.

BACKGROUND:Large image datasets acquired on automated microscopes typically have some fraction of low quality, out-of-focus images, despite the use of hardware autofocus systems. Identification of these images using automated image analysis with high accuracy is important for obtaining a clean, unbiased image dataset. Complicating this task is the fact that image focus quality is only well-defined in foreground regions of images, and as a result, most previous approaches only enable a computation of the relative difference in quality between two or more images, rather than an absolute measure of quality. RESULTS:We present a deep neural network model capable of predicting an absolute measure of image focus on a single image in isolation, without any user-specified parameters. The model operates at the image-patch level, and also outputs a measure of prediction certainty, enabling interpretable predictions. The model was trained on only 384 in-focus Hoechst (nuclei) stain images of U2OS cells, which were synthetically defocused to one of 11 absolute defocus levels during training. The trained model can generalize on previously unseen real Hoechst stain images, identifying the absolute image focus to within one defocus level (approximately 3 pixel blur diameter difference) with 95% accuracy. On a simpler binary in/out-of-focus classification task, the trained model outperforms previous approaches on both Hoechst and Phalloidin (actin) stain images (F-scores of 0.89 and 0.86, respectively over 0.84 and 0.83), despite only having been presented Hoechst stain images during training. Lastly, we observe qualitatively that the model generalizes to two additional stains, Hoechst and Tubulin, of an unseen cell type (Human MCF-7) acquired on a different instrument. CONCLUSIONS:Our deep neural network enables classification of out-of-focus microscope images with both higher accuracy and greater precision than previous approaches via interpretable patch-level focus and certainty predictions. The use of synthetically defocused images precludes the need for a manually annotated training dataset. The model also generalizes to different image and cell types. The framework for model training and image prediction is available as a free software library and the pre-trained model is available for immediate use in Fiji (ImageJ) and CellProfiler.

The original version of this Article incorrectly gave a publication date of 8 October 2018; this should have been 28 September 2018. This has now been corrected in the PDF and HTML versions of the Article.

Huntington's disease is a progressive neurodegenerative disorder caused by polyglutamine-expanded mutant huntingtin (mHTT). Here, we show that the deubiquitinase Usp12 rescues mHTT-mediated neurodegeneration in Huntington's disease rodent and patient-derived human neurons, and in Drosophila. The neuroprotective role of Usp12 may be specific amongst related deubiquitinases, as the closely related homolog Usp46 does not suppress mHTT-mediated toxicity. Mechanistically, we identify Usp12 as a potent inducer of neuronal autophagy. Usp12 overexpression accelerates autophagic flux and induces an approximately sixfold increase in autophagic structures as determined by ultrastructural analyses, while suppression of endogenous Usp12 slows autophagy. Surprisingly, the catalytic activity of Usp12 is not required to protect against neurodegeneration or induce autophagy. These findings identify the deubiquitinase Usp12 as a regulator of neuronal proteostasis and mHTT-mediated neurodegeneration.

Parkinson's disease (PD) is the second most common neurodegenerative disease and its pathogenic mechanisms are poorly understood. The majority of PD cases are sporadic but a number of genes are associated with familial PD. Sporadic and familial PD have many molecular and cellular features in common, suggesting some shared pathogenic mechanisms. Induced pluripotent stem cells (iPSCs) have been derived from patients harboring a range of different mutations of PD-associated genes. PD patient-derived iPSCs have been differentiated into relevant cell types, in particular dopaminergic neurons and used as a model to study PD. In this review, we describe how iPSCs have been used to improve our understanding of the pathogenesis of PD. We describe what cellular and molecular phenotypes have been observed in neurons derived from iPSCs harboring known PD-associated mutations and what common pathways may be involved.

Although gene discovery in neuropsychiatric disorders, including autism spectrum disorder, intellectual disability, epilepsy, schizophrenia, and Tourette disorder, has accelerated, resulting in a large number of molecular clues, it has proven difficult to generate specific hypotheses without the corresponding datasets at the protein complex and functional pathway level. Here, we describe one path forward-an initiative aimed at mapping the physical and genetic interaction networks of these conditions and then using these maps to connect the genomic data to neurobiology and, ultimately, the clinic. These efforts will include a team of geneticists, structural biologists, neurobiologists, systems biologists, and clinicians, leveraging a wide array of experimental approaches and creating a collaborative infrastructure necessary for long-term investigation. This initiative will ultimately intersect with parallel studies that focus on other diseases, as there is a significant overlap with genes implicated in cancer, infectious disease, and congenital heart defects.

The activity-regulated cytoskeletal (Arc) gene is implicated in numerous synaptic plasticity paradigms, including long-term potentiation and depression and homeostatic plasticity, and is critical for consolidating memory. How Arc facilitates these forms of plasticity is not fully understood. Unlike other neuronal immediate-early genes, Arc encodes a protein that shuttles between the somatodendritic and nuclear compartments to regulate synaptic plasticity. Little attention has been paid to Arc's role in the nucleus. Here, we highlight the regulatory elements and signaling cascades required to induce Arc transcription and discuss the significance of Arc nuclear localization for synaptic plasticity and scaling. We integrate these findings into the context of cognitive function and disease and propose a model in which Arc mediates an effect on memory as a "chaser" of synaptic activity through homeostatic scaling.

Microscopy is a central method in life sciences. Many popular methods, such as antibody labeling, are used to add physical fluorescent labels to specific cellular constituents. However, these approaches have significant drawbacks, including inconsistency; limitations in the number of simultaneous labels because of spectral overlap; and necessary perturbations of the experiment, such as fixing the cells, to generate the measurement. Here, we show that a computational machine-learning approach, which we call "in silico labeling" (ISL), reliably predicts some fluorescent labels from transmitted-light images of unlabeled fixed or live biological samples. ISL predicts a range of labels, such as those for nuclei, cell type (e.g., neural), and cell state (e.g., cell death). Because prediction happens in silico, the method is consistent, is not limited by spectral overlap, and does not disturb the experiment. ISL generates biological measurements that would otherwise be problematic or impossible to acquire.

To identify novel genes associated with ALS, we undertook two lines of investigation. We carried out a genome-wide association study comparing 20,806 ALS cases and 59,804 controls. Independently, we performed a rare variant burden analysis comparing 1,138 index familial ALS cases and 19,494 controls. Through both approaches, we identified kinesin family member 5A (KIF5A) as a novel gene associated with ALS. Interestingly, mutations predominantly in the N-terminal motor domain of KIF5A are causative for two neurodegenerative diseases: hereditary spastic paraplegia (SPG10) and Charcot-Marie-Tooth type 2 (CMT2). In contrast, ALS-associated mutations are primarily located at the C-terminal cargo-binding tail domain and patients harboring loss-of-function mutations displayed an extended survival relative to typical ALS cases. Taken together, these results broaden the phenotype spectrum resulting from mutations in KIF5A and strengthen the role of cytoskeletal defects in the pathogenesis of ALS.

Our brains represent spatial information in egocentric (self-based) or allocentric (landmark-based) coordinates. Rodent studies have demonstrated a critical role for the caudate in egocentric navigation and the hippocampus in allocentric navigation. We administered tests of egocentric and allocentric working memory to individuals with premotor Huntington's disease (pmHD), which is associated with early caudate nucleus atrophy, and controls. Each test had 80 trials during which subjects were asked to remember 2 locations over 1-sec delays. The only difference between these otherwise identical tests was that locations could only be coded in self-based or landmark-based coordinates. We applied a multiatlas-based segmentation algorithm and computed point-wise Jacobian determinants to measure regional variations in caudate and hippocampal volumes from 3T MRI. As predicted, the pmHD patients were significantly more impaired on egocentric working memory. Only egocentric accuracy correlated with caudate volumes, specifically the dorsolateral caudate head, right more than left, a region that receives dense efferents from dorsolateral prefrontal cortex. In contrast, only allocentric accuracy correlated with hippocampal volumes, specifically intermediate and posterior regions that connect strongly with parahippocampal and posterior parietal cortices. These results indicate that the distinction between egocentric and allocentric navigation applies to working memory. The dorsolateral caudate is important for egocentric working memory, which can explain the disproportionate impairment in pmHD. Allocentric working memory, in contrast, relies on the hippocampus and is relatively spared in pmHD.

Neural cultures derived from Huntington's disease (HD) patient-derived induced pluripotent stem cells were used for 'omics' analyses to identify mechanisms underlying neurodegeneration. RNA-seq analysis identified genes in glutamate and GABA signaling, axonal guidance and calcium influx whose expression was decreased in HD cultures. One-third of gene changes were in pathways regulating neuronal development and maturation. When mapped to stages of mouse striatal development, the profiles aligned with earlier embryonic stages of neuronal differentiation. We observed a strong correlation between HD-related histone marks, gene expression and unique peak profiles associated with dysregulated genes, suggesting a coordinated epigenetic program. Treatment with isoxazole-9, which targets key dysregulated pathways, led to amelioration of expanded polyglutamine repeat-associated phenotypes in neural cells and of cognitive impairment and synaptic pathology in HD model R6/2 mice. These data suggest that mutant huntingtin impairs neurodevelopmental pathways that could disrupt synaptic homeostasis and increase vulnerability to the pathologic consequence of expanded polyglutamine repeats over time.

Mutations in leucine-rich repeat kinase 2 (LRRK2) and α-synuclein lead to Parkinson's disease (PD). Disruption of protein homeostasis is an emerging theme in PD pathogenesis, making mechanisms to reduce the accumulation of misfolded proteins an attractive therapeutic strategy. We determined if activating nuclear factor erythroid 2-related factor (Nrf2), a potential therapeutic target for neurodegeneration, could reduce PD-associated neuron toxicity by modulating the protein homeostasis network. Using a longitudinal imaging platform, we visualized the metabolism and location of mutant LRRK2 and α-synuclein in living neurons at the single-cell level. Nrf2 reduced PD-associated protein toxicity by a cell-autonomous mechanism that was time-dependent. Furthermore, Nrf2 activated distinct mechanisms to handle different misfolded proteins. Nrf2 decreased steady-state levels of α-synuclein in part by increasing α-synuclein degradation. In contrast, Nrf2 sequestered misfolded diffuse LRRK2 into more insoluble and homogeneous inclusion bodies. By identifying the stress response strategies activated by Nrf2, we also highlight endogenous coping responses that might be therapeutically bolstered to treat PD.

We identified drug seeds for treating Huntington's disease (HD) by combining in vitro single molecule fluorescence spectroscopy, in silico molecular docking simulations, and in vivo fly and mouse HD models to screen for inhibitors of abnormal interactions between mutant Htt and physiological Ku70, an essential DNA damage repair protein in neurons whose function is known to be impaired by mutant Htt. From 19,468 and 3,010,321 chemicals in actual and virtual libraries, fifty-six chemicals were selected from combined in vitro-in silico screens; six of these were further confirmed to have an in vivo effect on lifespan in a fly HD model, and two chemicals exerted an in vivo effect on the lifespan, body weight and motor function in a mouse HD model. Two oligopeptides, hepta-histidine (7H) and Angiotensin III, rescued the morphological abnormalities of primary neurons differentiated from iPS cells of human HD patients. For these selected drug seeds, we proposed a possible common structure. Unexpectedly, the selected chemicals enhanced rather than inhibited Htt aggregation, as indicated by dynamic light scattering analysis. Taken together, these integrated screens revealed a new pathway for the molecular targeted therapy of HD.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative condition characterized by the progressive deterioration of motor neurons in the cortex and spinal cord. Using an automated robotic microscope platform that enables the longitudinal tracking of thousands of single neurons, we examine the effects a large library of compounds on modulating the survival of primary neurons expressing a mutation known to cause ALS. The goal of our analysis is to identify the few potentially beneficial compounds among the many assayed, the vast majority of which do not extend neuronal survival. This resembles the large-scale simultaneous inference scenario familiar from microarray analysis, but transferred to the survival analysis setting due to the novel experimental setup. We apply a three-component mixture model to censored survival times of thousands of individual neurons subjected to hundreds of different compounds. The shrinkage induced by our model significantly improves performance in simulations relative to performing treatment-wise survival analysis and subsequent multiple testing adjustment. Our analysis identified compounds that provide insight into potential novel therapeutic strategies for ALS.

Huntington's disease (HD) is a progressive, adult-onset neurodegenerative disease caused by a polyglutamine (polyQ) expansion in the N-terminal region of the protein huntingtin (HTT). There are no cures or disease-modifying therapies for HD. HTT has a highly conserved Akt phosphorylation site at serine 421, and prior work in HD models found that phosphorylation at S421 (S421-P) diminishes the toxicity of mutant HTT (mHTT) fragments in neuronal cultures. However, whether S421-P affects the toxicity of mHTT in vivo remains unknown. In this work, we used murine models to investigate the role of S421-P in HTT-induced neurodegeneration. Specifically, we mutated the human mHTT gene within a BAC to express either an aspartic acid or an alanine at position 421, mimicking tonic phosphorylation (mHTT-S421D mice) or preventing phosphorylation (mHTT-S421A mice), respectively. Mimicking HTT phosphorylation strongly ameliorated mHTT-induced behavioral dysfunction and striatal neurodegeneration, whereas neuronal dysfunction persisted when S421 phosphorylation was blocked. We found that S421 phosphorylation mitigates neurodegeneration by increasing proteasome-dependent turnover of mHTT and reducing the presence of a toxic mHTT conformer. These data indicate that S421 is a potent modifier of mHTT toxicity and offer in vivo validation for S421 as a therapeutic target in HD.

Although implicated in neurodegeneration, autophagy has been characterized mostly in yeast and mammalian non-neuronal cells. In a recent study, we sought to determine if SPHK1 (sphingosine kinase 1), implicated previously in macroautophagy/autophagy in cancer cells, regulates autophagy in neurons. SPHK1 synthesizes sphingosine-1-phosphate (S1P), a bioactive lipid involved in cell survival. In our study, we discovered that, when neuronal autophagy is pharmacologically stimulated, SPHK1 relocalizes to the endocytic and autophagic organelles. Interestingly, in non-neuronal cells stimulated with growth factors, SPHK1 translocates to the plasma membrane, where it phosphorylates sphingosine to produce S1P. Whether SPHK1 also binds to the endocytic and autophagic organelles in non-neuronal cells upon induction of autophagy has not been demonstrated. Here, we determined if the effect in neurons is operant in the SH-SY5Y neuroblastoma cell line. In both non-differentiated and differentiated SH-SY5Y cells, a short incubation of cells in amino acid-free medium stimulated the formation of SPHK1-positive puncta, as in neurons. We also found that, unlike neurons in which these puncta represent endosomes, autophagosomes, and amphisomes, in SH-SY5Y cells SPHK1 is bound only to the endosomes. In addition, a dominant negative form of SPHK1 was very toxic to SH-SY5Y cells, but cultured primary cortical neurons tolerated it significantly better. These results suggest that autophagy in neurons is regulated by mechanisms that differ, at least in part, from those in SH-SY5Y cells.