We describe a human single-nuclei transcriptomic atlas for the substantia nigra (SN), generated by sequencing approximately 17,000 nuclei from matched cortical and SN samples. We show that the common genetic risk for Parkinson's disease (PD) is associated with dopaminergic neuron (DaN)-specific gene expression, including mitochondrial functioning, protein folding and ubiquitination pathways. We identify a distinct cell type association between PD risk and oligodendrocyte-specific gene expression. Unlike Alzheimer's disease (AD), we find no association between PD risk and microglia or astrocytes, suggesting that neuroinflammation plays a less causal role in PD than AD. Beyond PD, we find associations between SN DaNs and GABAergic neuron gene expression and multiple neuropsychiatric disorders. Conditional analysis reveals that distinct neuropsychiatric disorders associate with distinct sets of neuron-specific genes but converge onto shared loci within oligodendrocytes and oligodendrocyte precursors. This atlas guides our aetiological understanding by associating SN cell type expression profiles with specific disease risk.

Induced pluripotent stem cell (iPSC) technologies have provided in vitro models of inaccessible human cell types, yielding new insights into disease mechanisms especially for neurological disorders. However, without due consideration, the thousands of new human iPSC lines generated in the past decade will inevitably affect the reproducibility of iPSC-based experiments. Differences between donor individuals, genetic stability and experimental variability contribute to iPSC model variation by impacting differentiation potency, cellular heterogeneity, morphology, and transcript and protein abundance. Such effects will confound reproducible disease modelling in the absence of appropriate strategies. In this Review, we explore the causes and effects of iPSC heterogeneity, and propose approaches to detect and account for experimental variation between studies, or even exploit it for deeper biological insight.

SummaryReproducibility in molecular and cellular studies is fundamental to scientific discovery. To establish the reproducibility of a well-defined long-term neuronal differentiation protocol, we repeated the cellular and molecular comparison of the same two iPSC lines across five distinct laboratories. Despite uncovering acceptable variability within individual laboratories, we detect poor cross-site reproducibility of the differential gene expression signature between these two lines. Factor analysis identifies the laboratory as the largest source of variation along with several variation-inflating confounders such as passaging effects and progenitor storage. Single-cell transcriptomics shows substantial cellular heterogeneity underlying inter-laboratory variability and being responsible for biases in differential gene expression inference. Factor analysis-based normalization of the combined dataset can remove the nuisance technical effects, enabling the execution of robust hypothesis-generating studies. Our study shows that multi-center collaborations can expose systematic biases and identify critical factors to be standardized when publishing novel protocols, contributing to increased cross-site reproducibility.

Parkinson’s disease (PD) is the second most common neurodegenerative disorder and a central role for α-synuclein (αSyn; SNCA ) in disease aetiology has been proposed based on genetics and neuropathology. To better understand the pathological mechanisms of αSyn, we generated induced pluripotent stem cells (iPSCs) from healthy individuals and PD patients carrying the A53T SNCA mutation or a triplication of the SNCA locus and differentiated them into dopaminergic neurons (DAns). iPSC-derived DAn from PD patients carrying either mutation showed increased intracellular Syn accumulation, and DAns from patients carrying the SNCA triplication displayed oligomeric Syn pathology and elevated Syn extracellular release. Transcriptomic analysis of purified DAns revealed perturbations in expression of genes linked to mitochondrial function, consistent with observed reduction in mitochondrial respiration, impairment in mitochondrial membrane potential, aberrant mitochondrial morphology and decreased levels of phosphorylated DRP1 Ser616 . Parkinson’s iPSC-derived DAns showed increased endoplasmic reticulum stress and impairments in cholesterol and lipid homeostasis. Together, these data show a correlation between Syn cellular pathology and deficits in metabolic and cellular bioenergetics in the pathology of PD.

Dystonia is a neurological disorder characterized by sustained or intermittent muscle contractions causing abnormal movements and postures, often occurring in absence of any structural brain abnormality. Psychiatric comorbidities, including anxiety, depression, obsessive-compulsive disorder and schizophrenia, are frequent in patients with dystonia. While mutations in a fast-growing number of genes have been linked to Mendelian forms of dystonia, the cellular, anatomical, and molecular basis remains unknown for most genetic forms of dystonia, as does its genetic and biological relationship to neuropsychiatric disorders. Here we applied an unbiased systems-biology approach to explore the cellular specificity of all currently known dystonia-associated genes, predict their functional relationships, and test whether dystonia and neuropsychiatric disorders share a genetic relationship. To determine the cellular specificity of dystonia-associated genes in the brain, single-nuclear transcriptomic data derived from mouse brain was used together with expression-weighted cell-type enrichment. To identify functional relationships among dystonia-associated genes, we determined the enrichment of these genes in co-expression networks constructed from 10 human brain regions. Stratified linkage-disequilibrium score regression was used to test whether co-expression modules enriched for dystonia-associated genes significantly contribute to the heritability of anxiety, major depressive disorder, obsessive-compulsive disorder, schizophrenia, and Parkinson’s disease. Dystonia-associated genes were significantly enriched in adult nigral dopaminergic neurons and striatal medium spiny neurons. Furthermore, 4 of 220 gene co-expression modules tested were significantly enriched for the dystonia-associated genes. The identified modules were derived from the substantia nigra, putamen, frontal cortex, and white matter, and were all significantly enriched for genes associated with synaptic function. Finally, we demonstrate significant enrichments of the heritability of major depressive disorder, obsessive-compulsive disorder and schizophrenia within the putamen and white matter modules, and a significant enrichment of the heritability of Parkinson’s disease within the substantia nigra module. In conclusion, multiple dystonia-associated genes interact and contribute to pathogenesis likely through dysregulation of synaptic signalling in striatal medium spiny neurons, adult nigral dopaminergic neurons and frontal cortical neurons. Furthermore, the enrichment of the heritability of psychiatric disorders in the co-expression modules enriched for dystonia-associated genes indicates that psychiatric symptoms associated with dystonia are likely to be intrinsic to its pathophysiology.

We present a novel ab initio predictor of protein enzymatic class. The predictor can classify proteins, solely based on their sequences, into one of six classes extracted from the enzyme commission (EC) classification scheme and is trained on a large, curated database of over 6,000 non-redundant proteins which we have assembled in this work. The predictor is powered by an ensemble of N-to-1 Neural Network, a novel architecture which we have recently developed. N-to-1 Neural Networks operate on the full sequence and not on predefined features. All motifs of a predefined length (31 residues in this work) are considered and are compressed by an N-to-1 Neural Network into a feature vector which is automatically determined during training. We test our predictor in 10-fold cross-validation and obtain state of the art results, with a 96% correct classification and 86% generalized correlation. All six classes are predicted with a specificity of at least 80% and false positive rates never exceeding 7%. We are currently investigating enhanced input encoding schemes which include structural information, and are analyzing trained networks to mine motifs that are most informative for the prediction, hence, likely, functionally relevant.

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severe Taiwanese Smn -/-;SMN2 SMA mice ( 22) that could potentially be restored by known and available pharmacological compounds. This strategy uncovered several potential therapeutic candidates, including harmine, which was further evaluated in cell and animal models, showing an ability to restore molecular networks and improve several disease phenotypes, including lifespan and weight. Our study highlights the tremendous potential of intersecting disease multiomics with drug perturbational responses to identify therapeutic compounds capable of modulating dysfunctional cellular and molecular networks to ameliorate SMA phenotypes. ResultsEarly restoration of SMN in SMA mice restores muscle protein and transcript expression. We first set out to determine the effect of early SMN restoration on the proteomic and transcriptomic profiles of SMA skeletal muscle, with the intent to design therapeutic strategies against the genes and proteins that remained unchanged. To do so, the severe Taiwanese Smn -/-;SMN2 SMA mouse model ( 22) received a facial i.v. injection at P0 and P2 of the previously described Pip6a-phosphordiamidate morpholino oligomer (Pip6a-PMO) or Pip6a-scrambled pharmacological compounds (10 μg/g; ref. 23,24). Pip6a is a cell-penetrating peptide (CPP) conjugated either to an SMN2 exon 7 inclusion-promoting ASO (PMO) or a scrambled ASO (23, 24). We have previously reported that administration of Pip6a-PMO to newborn Smn -/-;SMN2 mice led to increased SMN protein levels in numerous tissues, including skeletal muscle, and a concomitant 40-fold increase in survival ( 23). We harvested the tibialis anterior (TA) from P2 (presymptomatic) untreated Smn -/-;SMN2 and WT mice, P7 (symptomatic) untreated Smn -/-;SMN2 and WT mice, and P7 Pip6a-scrambled Smn -/-;SMN2 and Pip6a-PMO-treated Smn -/-;SMN2 mice. TAs were then cut in 2, whereby one half was used for transcriptomics (whole-transcript array assay) and the other for proteomics (liquid chromatography-mass spectrometry; LC-MS). Quantitative PCR (qPCR) analysis of the ratio of FL SMN2 over total SMN2 confirms a significant increase in FL SMN2 expression in P7 Pip6a-PMO-treated Smn -/-;SMN2 mice compared with age-matched untreated and Pip6a-scrambled-treated Smn -/-;SMN2 mice (Figure 1A).Despite differences between the transcriptomic and proteomic methodologies, highlighted by hierarchical clustering and combined Principal Component Analysis (PCA; Supplemental Figure 1; supplemental material available online with this article; https://doi.org/10.1172/jci.insight.149446DS1), we were able to find clear separation of experimental groups and agreement between transcriptomic and proteomic profiles once the variance attributed to the differences in methodologies was removed (Figure 1B). At P7, we observed a clear separation of Smn -/-;SMN2 and WT samples, where only Pip6a-PMO-treated Smn -/-;SMN2 mice clustered with WT (Figure 1B and Supplemental Figure 2). We also found that P2 Smn -/-;SMN2 and WT samples clustered together (Figure 1B and Supplemental Figure 2), suggest...