Transcriptomic correlates of neuron electrophysiological diversity.

How neuronal diversity emerges from complex patterns of gene expression remains poorly understood. Here we present an approach to understand electrophysiological diversity through gene expression by integrating pooled- and single-cell transcriptomics with intracellular electrophysiology. Using neuroinformatics methods, we compiled a brain-wide dataset of 34 neuron types with paired gene expression and intrinsic electrophysiological features from publically accessible sources, the largest such collection to date. We identified 420 genes whose expression levels significantly correlated with variability in one or more of 11 physiological parameters. We next trained statistical models to infer cellular features from multivariate gene expression patterns. Such models were predictive of gene-electrophysiological relationships in an independent collection of 12 visual cortex cell types from the Allen Institute, suggesting that these correlations might reflect general principles relating expression patterns to phenotypic diversity across very different cell types. Many associations reported here have the potential to provide new insights into how neurons generate functional diversity, and correlations of ion channel genes like Gabrd and Scn1a (Nav1.1) with resting potential and spiking frequency are consistent with known causal mechanisms. Our work highlights the promise and inherent challenges in using cell type-specific transcriptomics to understand the mechanistic origins of neuronal diversity.

Secondary neurotransmitter deficiencies in epilepsy caused by voltage-gated sodium channelopathies: A potential treatment target?

We describe neurotransmitter abnormalities in two patients with drug-resistant epilepsy resulting from deleterious de novo mutations in sodium channel genes. Whole exome sequencing identified a de novo SCN2A splice-site mutation (c.2379+1G>A, p.Glu717Gly.fs*30) resulting in deletion of exon 14, in a 10-year old male with early onset global developmental delay, intermittent ataxia, autism, hypotonia, epileptic encephalopathy and cerebral/cerebellar atrophy. In the cerebrospinal fluid both homovanillic acid and 5-hydroxyindoleacetic acid were significantly decreased; extensive biochemical and genetic investigations ruled out primary neurotransmitter deficiencies and other known inborn errors of metabolism. In an 8-year old female with an early onset intractable epileptic encephalopathy, developmental regression, and progressive cerebellar atrophy, a previously unreported de novo missense mutation was identified in SCN8A (c.5615G>A; p.Arg1872Gln), affecting a highly conserved residue located in the C-terminal of the Nav1.6 protein. Aside from decreased homovanillic acid and 5-hydroxyindoleacetic acid, 5-methyltetrahydrofolate was also found to be low. We hypothesize that these channelopathies cause abnormal synaptic mono-amine metabolite secretion/uptake via impaired vesicular release and imbalance in electrochemical ion gradients, which in turn aggravate the seizures. Treatment with oral 5-hydroxytryptophan, l-Dopa/Carbidopa, and a dopa agonist resulted in mild improvement of seizure control in the male case, most likely via dopamine and serotonin receptor activated signal transduction and modulation of glutamatergic, GABA-ergic and glycinergic neurotransmission. Neurotransmitter analysis in other sodium channelopathy patients will help validate our findings, potentially yielding novel treatment opportunities.

Mitochondrial complex I deficiency stratifies idiopathic Parkinson's disease.

Idiopathic Parkinson's disease (iPD) is believed to have a heterogeneous pathophysiology, but molecular disease subtypes have not been identified. Here, we show that iPD can be stratified according to the severity of neuronal respiratory complex I (CI) deficiency, and identify two emerging disease subtypes with distinct molecular and clinical profiles. The CI deficient (CI-PD) subtype accounts for approximately a fourth of all cases, and is characterized by anatomically widespread neuronal CI deficiency, a distinct cell type-specific gene expression profile, increased load of neuronal mtDNA deletions, and a predilection for non-tremor dominant motor phenotypes. In contrast, the non-CI deficient (nCI-PD) subtype exhibits no evidence of mitochondrial impairment outside the dopaminergic substantia nigra and has a predilection for a tremor dominant phenotype. These findings constitute a step towards resolving the biological heterogeneity of iPD with implications for both mechanistic understanding and treatment strategies.

Not every estimate counts - evaluation of cell composition estimation approaches in brain bulk tissue data.

BACKGROUND: Variation in cell composition can dramatically impact analyses in bulk tissue samples. A commonly employed approach to mitigate this issue is to adjust statistical models using estimates of cell abundance derived directly from omics data. While an arsenal of estimation methods exists, the applicability of these methods to brain tissue data and whether or not cell estimates can sufficiently account for confounding cellular composition has not been adequately assessed. METHODS: We assessed the correspondence between different estimation methods based on transcriptomic (RNA sequencing, RNA-seq) and epigenomic (DNA methylation and histone acetylation) data from brain tissue samples of 49 individuals. We further evaluated the impact of different estimation approaches on the analysis of H3K27 acetylation chromatin immunoprecipitation sequencing (ChIP-seq) data from entorhinal cortex of individuals with Alzheimer's disease and controls. RESULTS: We show that even closely adjacent tissue samples from the same Brodmann area vary greatly in their cell composition. Comparison across different estimation methods indicates that while different estimation methods applied to the same data produce highly similar outcomes, there is a surprisingly low concordance between estimates based on different omics data modalities. Alarmingly, we show that cell type estimates may not always sufficiently account for confounding variation in cell composition. CONCLUSIONS: Our work indicates that cell composition estimation or direct quantification in one tissue sample should not be used as a proxy to the cellular composition of another tissue sample from the same brain region of an individual-even if the samples are directly adjacent. The highly similar outcomes observed among vastly different estimation methods, highlight the need for brain benchmark datasets and better validation approaches. Finally, unless validated through complementary experiments, the interpretation of analyses outcomes based on data confounded by cell composition should be done with great caution, and ideally avoided all together.

A nationwide study of the incidence, prevalence and mortality of Parkinson's disease in the Norwegian population.

Epidemiological studies of Parkinson's disease (PD) show variable and partially conflicting findings with regard to incidence, prevalence, and mortality. These differences are commonly attributed to technical and methodological factors, including small sample sizes, differences in diagnostic practices, and population heterogeneity. We leveraged the Norwegian Prescription Database, a population-based registry of drug prescriptions dispensed from Norwegian pharmacies to assess the incidence, prevalence, and mortality of PD in Norway. The diagnosis of PD was defined based on the prescription of dopaminergic drugs for the indication of PD over a continuous time. During 2004-2017, 12,229 males and 9831 females met our definition for PD diagnosis. PD prevalence increased over the observation period, with larger changes observed in the older age groups. Incidence and prevalence of PD increased with age, peaking at 85 years. The male/female prevalence ratio was 1.5 across all ages, whereas the incidence ratio increased with age, from 1.4 in those 60 years, to 2.03 among those >90 years. While PD mortality was generally higher than that of the general population, mortality odds ratios decreased with age, approaching 1.0 among individuals >90 years old. When adjusted for the sex-specific mortality of the general population, the mortality among females with PD was equal to or higher than the mortality among males with PD. Our findings demonstrate that the epidemiological features of PD, including sex-differences, are age and time-period dependent and indicate that sex differences in PD mortality are unlikely to stem from disease-specific negative impact of survival in males.

Genome-wide histone acetylation analysis reveals altered transcriptional regulation in the Parkinson's disease brain.

BACKGROUND: Parkinson's disease (PD) is a complex, age-related neurodegenerative disorder of largely unknown etiology. PD is strongly associated with mitochondrial respiratory dysfunction, which can lead to epigenetic dysregulation and specifically altered histone acetylation. Nevertheless, and despite the emerging role of epigenetics in age-related brain disorders, the question of whether aberrant histone acetylation is involved in PD remains unresolved. METHODS: We studied fresh-frozen brain tissue from two independent cohorts of individuals with idiopathic PD (n = 28) and neurologically healthy controls (n = 21). We performed comprehensive immunoblotting to identify histone sites with altered acetylation levels in PD, followed by chromatin immunoprecipitation sequencing (ChIP-seq). RNA sequencing data from the same individuals was used to assess the impact of altered histone acetylation on gene expression. RESULTS: Immunoblotting analyses revealed increased acetylation at several histone sites in PD, with the most prominent change observed for H3K27, a marker of active promoters and enhancers. ChIP-seq analysis further indicated that H3K27 hyperacetylation in the PD brain is a genome-wide phenomenon with a strong predilection for genes implicated in the disease, including SNCA, PARK7, PRKN and MAPT. Integration of the ChIP-seq with transcriptomic data from the same individuals revealed that the correlation between promoter H3K27 acetylation and gene expression is attenuated in PD patients, suggesting that H3K27 acetylation may be decoupled from transcription in the PD brain. Strikingly, this decoupling was most pronounced among nuclear-encoded mitochondrial genes, corroborating the notion that impaired crosstalk between the nucleus and mitochondria is involved in the pathogenesis of PD. Our findings independently replicated in the two cohorts. CONCLUSIONS: Our findings strongly suggest that aberrant histone acetylation and altered transcriptional regulation are involved in the pathophysiology of PD. We demonstrate that PD-associated genes are particularly prone to epigenetic dysregulation and identify novel epigenetic signatures associated with the disease.

Common gene expression signatures in Parkinson's disease are driven by changes in cell composition.

The etiology of Parkinson's disease is largely unknown. Genome-wide transcriptomic studies in bulk brain tissue have identified several molecular signatures associated with the disease. While these studies have the potential to shed light into the pathogenesis of Parkinson's disease, they are also limited by two major confounders: RNA post-mortem degradation and heterogeneous cell type composition of bulk tissue samples. We performed RNA sequencing following ribosomal RNA depletion in the prefrontal cortex of 49 individuals from two independent case-control cohorts. Using cell type specific markers, we estimated the cell type composition for each sample and included this in our analysis models to compensate for the variation in cell type proportions. Ribosomal RNA depletion followed by capture by random primers resulted in substantially more even transcript coverage, compared to poly(A) capture, in post-mortem tissue. Moreover, we show that cell type composition is a major confounder of differential gene expression analysis in the Parkinson's disease brain. Accounting for cell type proportions attenuated numerous transcriptomic signatures that have been previously associated with Parkinson's disease, including vesicle trafficking, synaptic transmission, immune and mitochondrial function. Conversely, pathways related to endoplasmic reticulum, lipid oxidation and unfolded protein response were strengthened and surface as the top differential gene expression signatures in the Parkinson's disease prefrontal cortex. Our results indicate that differential gene expression signatures in Parkinson's disease bulk brain tissue are significantly confounded by underlying differences in cell type composition. Modeling cell type heterogeneity is crucial in order to unveil transcriptomic signatures that represent regulatory changes in the Parkinson's disease brain and are, therefore, more likely to be associated with underlying disease mechanisms.

Effects of the putative lithium mimetic ebselen on pilocarpine-induced neural activity.

Lithium, commonly used to treat bipolar disorder, potentiates the ability of the muscarinic agonist pilocarpine to induce seizures in rodents. As this potentiation by lithium is reversed by the administration of myo-inositol, the potentiation may be mediated by inhibition of inositol monophosphatase (IMPase), a known target of lithium. Recently, we demonstrated that ebselen is a 'lithium mimetic' in regard to behaviours in both mice and man. Ebselen inhibits IMPase in vitro and lowers myo-inositol in vivo in the brains of mice and men, making ebselen the only known inhibitor of IMPase, other than lithium, that penetrates the blood-brain barrier. Our objective was to determine the effects of ebselen on sensitization to pilocarpine-induced seizures and neural activity. We administered ebselen at different doses and time intervals to mice, followed by injection of a sub-seizure dose of pilocarpine. We assessed seizure and neural activity by a subjective seizure rating scale, by monitoring tremors, and by induction of the immediate early gene c-fos. In contrast to lithium, ebselen did not potentiate the ability of pilocarpine to induce seizures. Unexpectedly, ebselen inhibited pilocarpine-induced tremor as well as pilocarpine-induced increases in c-fos mRNA levels. Both lithium and ebselen inhibit a common target, IMPase, but only lithium potentiates pilocarpine-induced seizures, consistent with their polypharmacology at diverse molecular targets. We conclude that ebselen does not potentiate pilocarpine-induced seizures and instead, reduces pilocarpine-mediated neural activation. This lack of potentiation of muscarinic sensitization may be one reason for the lack of side-effects observed with ebselen treatment clinically.

Mega-Analysis of Gene Expression in Mouse Models of Alzheimer's Disease.

While multiple studies have been conducted of gene expression in mouse models of Alzheimer's disease (AD), their findings have not reached a clear consensus and have not accounted for the potentially confounding effects of changes in cellular composition. To help address this gap, we conducted a re-analysis based meta-analysis (mega-analysis) of ten independent studies of hippocampal gene expression in mouse models of AD. We used estimates of cellular composition as covariates in statistical models aimed to identify genes differentially expressed (DE) at either early or late stages of progression. Our analysis revealed changes in gene expression at early phases shared across studies, including dysregulation of genes involved in cholesterol biosynthesis and the complement system. Expression changes at later stages were dominated by cellular compositional effects. Thus, despite the considerable heterogeneity of the mouse models, we identified common patterns that may contribute to our understanding of AD etiology. Our work also highlights the importance of controlling for cellular composition effects in genomics studies of neurodegeneration.

Transcriptomic Evidence for Alterations in Astrocytes and Parvalbumin Interneurons in Subjects With Bipolar Disorder and Schizophrenia.

BACKGROUND: High-throughput expression analyses of postmortem brain tissue have been widely used to study bipolar disorder and schizophrenia. However, despite the extensive efforts, no consensus has emerged as to the functional interpretation of the findings. We hypothesized that incorporating information on cell type-specific expression would provide new insights. METHODS: We reanalyzed 15 publicly available bulk tissue expression datasets on schizophrenia and bipolar disorder, representing various brain regions from eight different cohorts of subjects (unique subjects: 332 control, 129 bipolar disorder, 341 schizophrenia). We studied changes in the expression profiles of cell type marker genes and evaluated whether these expression profiles could serve as surrogates for relative abundance of their corresponding cells. RESULTS: In both bipolar disorder and schizophrenia, we consistently observed an increase in the expression profiles of cortical astrocytes and a decrease in the expression profiles of fast-spiking parvalbumin interneurons. No changes in astrocyte expression profiles were observed in subcortical regions. Furthermore, we found that many of the genes previously identified as differentially expressed in schizophrenia are highly correlated with the expression profiles of astrocytes or fast-spiking parvalbumin interneurons. CONCLUSIONS: Our results indicate convergence of transcriptome studies of schizophrenia and bipolar disorder on changes in cortical astrocytes and fast-spiking parvalbumin interneurons, providing a unified interpretation of numerous studies. We suggest that these changes can be attributed to alterations in the relative abundance of the cells and are important for understanding the pathophysiology of the disorders.

Assessing Transcriptome Quality in Patch-Seq Datasets.

Patch-seq, combining patch-clamp electrophysiology with single-cell RNA-sequencing (scRNAseq), enables unprecedented access to a neuron's transcriptomic, electrophysiological, and morphological features. Here, we present a re-analysis of five patch-seq datasets, representing cells from ex vivo mouse brain slices and in vitro human stem-cell derived neurons. Our objective was to develop simple criteria to assess the quality of patch-seq derived single-cell transcriptomes. We evaluated patch-seq transcriptomes for the expression of marker genes of multiple cell types, benchmarking these against analogous profiles from cellular-dissociation based scRNAseq. We found an increased likelihood of off-target cell-type mRNA contamination in patch-seq cells from acute brain slices, likely due to the passage of the patch-pipette through the processes of adjacent cells. We also observed that patch-seq samples varied considerably in the amount of mRNA that could be extracted from each cell, strongly biasing the numbers of detectable genes. We developed a marker gene-based approach for scoring single-cell transcriptome quality post-hoc. Incorporating our quality metrics into downstream analyses improved the correspondence between gene expression and electrophysiological features. Our analysis suggests that technical confounds likely limit the interpretability of patch-seq based single-cell transcriptomes. However, we provide concrete recommendations for quality control steps that can be performed prior to costly RNA-sequencing to optimize the yield of high-quality samples.

Cross-Laboratory Analysis of Brain Cell Type Transcriptomes with Applications to Interpretation of Bulk Tissue Data.

Establishing the molecular diversity of cell types is crucial for the study of the nervous system. We compiled a cross-laboratory database of mouse brain cell type-specific transcriptomes from 36 major cell types from across the mammalian brain using rigorously curated published data from pooled cell type microarray and single-cell RNA-sequencing (RNA-seq) studies. We used these data to identify cell type-specific marker genes, discovering a substantial number of novel markers, many of which we validated using computational and experimental approaches. We further demonstrate that summarized expression of marker gene sets (MGSs) in bulk tissue data can be used to estimate the relative cell type abundance across samples. To facilitate use of this expanding resource, we provide a user-friendly web interface at www.neuroexpresso.org.

Whose sample is it anyway? Widespread misannotation of samples in transcriptomics studies.

Concern about the reproducibility and reliability of biomedical research has been rising. An understudied issue is the prevalence of sample mislabeling, one impact of which would be invalid comparisons. We studied this issue in a corpus of human transcriptomics studies by comparing the provided annotations of sex to the expression levels of sex-specific genes. We identified apparent mislabeled samples in 46% of the datasets studied, yielding a 99% confidence lower-bound estimate for all studies of 33%. In a separate analysis of a set of datasets concerning a single cohort of subjects, 2/4 had mislabeled samples, indicating laboratory mix-ups rather than data recording errors. While the number of mixed-up samples per study was generally small, because our method can only identify a subset of potential mix-ups, our estimate is conservative for the breadth of the problem. Our findings emphasize the need for more stringent sample tracking, and that re-users of published data must be alert to the possibility of annotation and labelling errors.