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

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.

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.

Distinctive whole-brain cell types predict tissue damage patterns in thirteen neurodegenerative conditions

For over a century, brain research narrative has mainly centered on neuron cells. Accordingly, most neurodegenerative studies focus on neuronal dysfunction and their selective vulnerability, while we lack comprehensive analyses of other major cell types' contribution. By unifying spatial gene expression, structural MRI, and cell deconvolution, here we describe how the human brain distribution of canonical cell types extensively predicts tissue damage in 13 neurodegenerative conditions, including early- and late-onset Alzheimer's disease, Parkinson's disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, mutations in presenilin-1, and 3 clinical variants of frontotemporal lobar degeneration (behavioral variant, semantic and non-fluent primary progressive aphasia) along with associated three-repeat and four-repeat tauopathies and TDP43 proteinopathies types A and C. We reconstructed comprehensive whole-brain reference maps of cellular abundance for six major cell types and identified characteristic axes of spatial overlapping with atrophy. Our results support the strong mediating role of non-neuronal cells, primarily microglia and astrocytes, in spatial vulnerability to tissue loss in neurodegeneration, with distinct and shared across-disorder pathomechanisms. These observations provide critical insights into the multicellular pathophysiology underlying spatiotemporal advance in neurodegeneration. Notably, they also emphasize the need to exceed the current neuro-centric view of brain diseases, supporting the imperative for cell-specific therapeutic targets in neurodegeneration.

Nigral transcriptomic profiles in Engrailed-1 hemizygous mouse models of Parkinson's disease reveal upregulation of oxidative phosphorylation-related genes associated with delayed dopaminergic neurodegeneration

Introduction

Parkinson's disease (PD) is the second most common neurodegenerative disorder, increasing both in terms of prevalence and incidence. To date, only symptomatic treatment is available, highlighting the need to increase knowledge on disease etiology in order to develop new therapeutic strategies. Hemizygosity for the gene Engrailed-1 (En1), encoding a conserved transcription factor essential for the programming, survival, and maintenance of midbrain dopaminergic neurons, leads to progressive nigrostriatal degeneration, motor impairment and depressive-like behavior in SwissOF1 (OF1-En1+/-). The neurodegenerative phenotype is, however, absent in C57Bl/6j (C57-En1+/-) mice. En1+/- mice are thus highly relevant tools to identify genetic factors underlying PD susceptibility.

Methods

Transcriptome profiles were defined by RNAseq in microdissected substantia nigra from 1-week old OF1, OF1- En1+/-, C57 and C57- En1+/- male mice. Differentially expressed genes (DEGs) were analyzed for functional enrichment. Neurodegeneration was assessed in 4- and 16-week old mice by histology.

Results

Nigrostriatal neurodegeneration was manifested in OF1- En1+/- mice by increased dopaminergic striatal axonal swellings from 4 to 16 weeks and decreased number of dopaminergic neurons in the SNpc at 16 weeks compared to OF1. In contrast, C57- En1+/- mice had no significant increase in axonal swellings or cell loss in SNpc at 16 weeks. Transcriptomic analyses identified 198 DEGs between OF1- En1+/- and OF1 mice but only 52 DEGs between C57- En1+/- and C57 mice. Enrichment analysis of DEGs revealed that the neuroprotective phenotype of C57- En1+/- mice was associated with a higher expression of oxidative phosphorylation-related genes compared to both C57 and OF1- En1+/- mice.

Discussion

Our results suggest that increased expression of genes encoding mitochondrial proteins before the onset of neurodegeneration is associated with increased resistance to PD-like nigrostriatal neurodegeneration. This highlights the importance of genetic background in PD models, how different strains can be used to model clinical and sub-clinical pathologies and provides insights to gene expression mechanisms associated with PD susceptibility and progression.

Dual roles of UPRer and UPRmt in neurodegenerative diseases

The unfolded protein response (UPR) is a cellular stress response mechanism induced by the accumulation of unfolded or misfolded proteins. Within the endoplasmic reticulum and mitochondria, a dynamic balance exists between protein folding mechanisms and unfolded protein levels under normal conditions. Disruption of this balance or an accumulation of unfolded proteins in these organelles can result in stress responses and UPR. The UPR restores organelle homeostasis and promotes cell survival by increasing the expression of chaperone proteins, regulating protein quality control systems, and enhancing the protein degradation pathway. However, prolonged or abnormal UPR can also have negative effects, including cell death. Therefore, many diseases, especially neurodegenerative diseases, are associated with UPR dysfunction. Neurodegenerative diseases are characterized by misfolded proteins accumulating and aggregating, and neuronal cells are particularly sensitive to misfolded proteins and are prone to degeneration. Many studies have shown that the UPR plays an important role in the pathogenesis of neurodegenerative diseases. Here, we will discuss the possible contributions of the endoplasmic reticulum unfolded protein response (UPRer) and the mitochondrial unfolded protein response (UPRmt) in the development of several neurodegenerative diseases.

The molecular genetic landscape of human brain size variation

Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease.

Transcriptomic profiling of Parkinson's disease brains reveals disease stage specific gene expression changes

Parkinson´s disease (PD) is a progressive neurodegenerative disorder characterized by both motor and non-motor symptoms. Aggravation of symptoms is mirrored by accumulation of protein aggregates mainly composed by alpha-synuclein in different brain regions, called Lewy bodies (LB). Previous studies have identified several molecular mechanisms as autophagy and inflammation playing a role in PD pathogenesis. Increased insights into mechanisms involved in early disease stages and driving the progression of the LB pathology are required for the development of disease-modifying strategies. Here, we aimed to elucidate disease stage-specific transcriptomic changes in brain tissue of well-characterized PD and control donors. We collected frontal cortex samples from 84 donors and sequenced both the coding and non-coding RNAs. We categorized our samples into groups based on their degree of LB pathology aiming to recapitulate a central aspect of disease progression. Using an analytical pipeline that corrected for sex, age at death, RNA quality, cell composition and unknown sources of variation, we found major disease stage-specific transcriptomic changes. Gene expression changes were most pronounced in donors at the disease stage when microscopic LB changes first occur in the sampled brain region. Additionally, we identified disease stage-specific enrichment of brain specific pathways and immune mechanisms. On the contrary, we showed that mitochondrial mechanisms are enriched throughout the disease course. Our data-driven approach also suggests a role for several poorly characterized lncRNAs in disease development and progression of PD. Finally, by combining genetic and epigenetic information, we highlighted two genes (MAP4K4 and PHYHIP) as candidate genes for future functional studies. Together our results indicate that transcriptomic dysregulation and associated functional changes are highly disease stage-specific, which has major implications for the study of neurodegenerative disorders.

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.

Genetic modifiers of synucleinopathies-lessons from experimental models

α-Synuclein is a pleiotropic protein underlying a group of progressive neurodegenerative diseases, including Parkinson's disease and dementia with Lewy bodies. Together, these are known as synucleinopathies. Like all neurological diseases, understanding of disease mechanisms is hampered by the lack of access to biopsy tissues, precluding a real-time view of disease progression in the human body. This has driven researchers to devise various experimental models ranging from yeast to flies to human brain organoids, aiming to recapitulate aspects of synucleinopathies. Studies of these models have uncovered numerous genetic modifiers of α-synuclein, most of which are evolutionarily conserved. This review discusses what we have learned about disease mechanisms from these modifiers, and ways in which the study of modifiers have supported ongoing efforts to engineer disease-modifying interventions for synucleinopathies.

Systems level analysis of sex-dependent gene expression changes in Parkinson's disease

Parkinson's disease (PD) is a heterogeneous disorder, and among the factors which influence the symptom profile, biological sex has been reported to play a significant role. While males have a higher age-adjusted disease incidence and are more frequently affected by muscle rigidity, females present more often with disabling tremors. The molecular mechanisms involved in these differences are still largely unknown, and an improved understanding of the relevant factors may open new avenues for pharmacological disease modification. To help address this challenge, we conducted a meta-analysis of disease-associated molecular sex differences in brain transcriptomics data from case/control studies. Both sex-specific (alteration in only one sex) and sex-dimorphic changes (changes in both sexes, but with opposite direction) were identified. Using further systems level pathway and network analyses, coordinated sex-related alterations were studied. These analyses revealed significant disease-associated sex differences in mitochondrial pathways and highlight specific regulatory factors whose activity changes can explain downstream network alterations, propagated through gene regulatory cascades. Single-cell expression data analyses confirmed the main pathway-level changes observed in bulk transcriptomics data. Overall, our analyses revealed significant sex disparities in PD-associated transcriptomic changes, resulting in coordinated modulations of molecular processes. Among the regulatory factors involved, NR4A2 has already been reported to harbor rare mutations in familial PD and its pharmacological activation confers neuroprotective effects in toxin-induced models of Parkinsonism. Our observations suggest that NR4A2 may warrant further research as a potential adjuvant therapeutic target to address a subset of pathological molecular features of PD that display sex-associated profiles.

Altered transcriptome-proteome coupling indicates aberrant proteostasis in Parkinson's disease

Aberrant proteostasis is thought to be implicated in Parkinson's disease (PD), but patient-derived evidence is scant. We hypothesized that impaired proteostasis is reflected as altered transcriptome-proteome correlation in the PD brain. We integrated transcriptomic and proteomic data from prefrontal cortex of PD patients and young and aged controls to assess RNA-protein correlations across samples. The aged brain showed a genome-wide decrease in mRNA-protein correlation. Genes encoding synaptic vesicle proteins showed negative correlations, likely reflecting spatial separation of mRNA and protein into soma and synapses. PD showed a broader transcriptome-proteome decoupling, consistent with a proteome-wide decline in proteostasis. Genes showing negative correlation in PD were enriched for proteasome subunits, indicating accentuated spatial separation of transcript and protein in PD neurons. In addition, PD showed positive correlations for mitochondrial respiratory chain genes, suggesting a tighter regulation in the face of mitochondrial dysfunction. Our results support the hypothesis that aberrant proteasomal function is implicated in PD pathogenesis.

Genetic Analysis of Six Transmembrane Protein Family Genes in Parkinson’s Disease in a Large Chinese Cohort

Objectives

Parkinson’s disease (PD) is a neurodegenerative disorder with the manifestation of motor symptoms and non-motor symptoms. Previous studies have indicated the role of several transmembrane (TMEM) protein family genes in PD pathogenesis.

Materials and Methods

In order to better investigate the genetic role of PD-related TMEM protein family genes in PD, including TMEM230, TMEM59, TMEM108, TMEM163, TMEM175, and TMEM229B, 1,917 sporadic early onset PD (sEOPD) or familial PD (FPD) patients and 1,652 healthy controls were analyzed by whole-exome sequencing (WES) while 1,962 sporadic late-onset PD (sLOPD) and 1,279 healthy controls were analyzed by whole-genome sequencing (WGS). Rare and common variants for each gene were included in the analysis.

Results

One hundred rare damaging or loss of function variants of six genes were found at the threshold of MAF < 0.1%. Three rare Dmis variants of TMEM230 were specifically identified in PD. Rare missense variants of TMEM59 were statistically significantly associated with PD in the WES cohort, indicating the role of TMEM59 in FPD and sEOPD. Rare missense variants of TMEM108 were suggestively associated with PD in the WGS cohort, indicating the potential role of TMEM108 in sLOPD. The rare variant of the other three genes and common variants of six genes were not significantly associated with PD.

Conclusion

We performed a large case-control study to systematically investigate the role of several PD-related TMEM protein family genes in PD. We identified three PD-specific variants in TMEM230, the significant association of TMEM59 with FPD, and sEOPD and the suggestive association of TMEM108 with sLOPD.

A Machine Learning Approach to Parkinson’s Disease Blood Transcriptomics

The increased incidence and the significant health burden associated with Parkinson’s disease (PD) have stimulated substantial research efforts towards the identification of effective treatments and diagnostic procedures. Despite technological advancements, a cure is still not available and PD is often diagnosed a long time after onset when irreversible damage has already occurred. Blood transcriptomics represents a potentially disruptive technology for the early diagnosis of PD. We used transcriptome data from the PPMI study, a large cohort study with early PD subjects and age matched controls (HC), to perform the classification of PD vs. HC in around 550 samples. Using a nested feature selection procedure based on Random Forests and XGBoost we reached an AUC of 72% and found 493 candidate genes. We further discussed the importance of the selected genes through a functional analysis based on GOs and KEGG pathways.

Transcriptional analysis of peripheral memory T cells reveals Parkinson's disease-specific gene signatures

Parkinson's disease (PD) is a multi-stage neurodegenerative disorder with largely unknown etiology. Recent findings have identified PD-associated autoimmune features including roles for T cells. To further characterize the role of T cells in PD, we performed RNA sequencing on PBMC and peripheral CD4 and CD8 memory T cell subsets derived from PD patients and age-matched healthy controls. When the groups were stratified by their T cell responsiveness to alpha-synuclein (α-syn) as a proxy for an ongoing inflammatory autoimmune response, the study revealed a broad differential gene expression profile in memory T cell subsets and a specific PD associated gene signature. We identified significant enrichment of transcriptomic signatures previously associated with PD, including for oxidative stress, phosphorylation, autophagy of mitochondria, cholesterol metabolism and inflammation, and the chemokine signaling proteins CX3CR1, CCR5, and CCR1. In addition, we identified genes in these peripheral cells that have previously been shown to be involved in PD pathogenesis and expressed in neurons, such as LRRK2, LAMP3, and aquaporin. Together, these findings suggest that features of circulating T cells with α-syn-specific responses in PD patients provide insights into the interactive processes that occur during PD pathogenesis and suggest potential intervention targets.

A protocol to extract cell-type-specific signatures from differentially expressed genes in bulk-tissue RNA-seq

Bulk-tissue RNA-seq is widely used to dissect variation in gene expression levels across tissues and under different experimental conditions. Here, we introduce a protocol that leverages existing single-cell expression data to deconvolve patterns of cell-type-specific gene expression in differentially expressed gene lists from highly heterogeneous tissue. We apply this protocol to interrogate cell-type-specific gene expression and variation in cell type composition between the distinct sublayers of the hippocampal CA1 region of the brain in a rodent model of epilepsy.

For complete details on the use and execution of this protocol, please refer to Cid et al. (2021).

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A protocol to explore gene signatures from bulk RNA-seq at the cell-type-specific level

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Deconvolution of complex gene signatures from highly heterogeneous tissues

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Publicly available single-cell gene expression dataset is retrieved and curated

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Gene signatures across brain regions and disease states are surveyed in scRNA-seq data

A Hybrid Machine Learning and Network Analysis Approach Reveals Two Parkinson's Disease Subtypes from 115 RNA-Seq Post-Mortem Brain Samples

Precision medicine emphasizes fine-grained diagnostics, taking individual variability into account to enhance treatment effectiveness. Parkinson’s disease (PD) heterogeneity among individuals proves the existence of disease subtypes, so subgrouping patients is vital for better understanding disease mechanisms and designing precise treatment. The purpose of this study was to identify PD subtypes using RNA-Seq data in a combined pipeline including unsupervised machine learning, bioinformatics, and network analysis. Two hundred and ten post mortem brain RNA-Seq samples from PD (n = 115) and normal controls (NCs, n = 95) were obtained with systematic data retrieval following PRISMA statements and a fully data-driven clustering pipeline was performed to identify PD subtypes. Bioinformatics and network analyses were performed to characterize the disease mechanisms of the identified PD subtypes and to identify target genes for drug repurposing. Two PD clusters were identified and 42 DEGs were found (p adjusted ≤ 0.01). PD clusters had significantly different gene network structures (p < 0.0001) and phenotype-specific disease mechanisms, highlighting the differential involvement of the Wnt/β-catenin pathway regulating adult neurogenesis. NEUROD1 was identified as a key regulator of gene networks and ISX9 and PD98059 were identified as NEUROD1-interacting compounds with disease-modifying potential, reducing the effects of dopaminergic neurodegeneration. This hybrid data analysis approach could enable precision medicine applications by providing insights for the identification and characterization of pathological subtypes. This workflow has proven useful on PD brain RNA-Seq, but its application to other neurodegenerative diseases is encouraged.

Correcting Differential Gene Expression Analysis for Cyto-Architectural Alterations in Substantia Nigra of Parkinson's Disease Patients Reveals Known and Potential Novel Disease-Associated Genes and Pathways

Several studies have analyzed gene expression profiles in the substantia nigra to better understand the pathological mechanisms causing Parkinson’s disease (PD). However, the concordance between the identified gene signatures in these individual studies was generally low. This might have been caused by a change in cell type composition as loss of dopaminergic neurons in the substantia nigra pars compacta is a hallmark of PD. Through an extensive meta-analysis of nine previously published microarray studies, we demonstrated that a big proportion of the detected differentially expressed genes was indeed caused by cyto-architectural alterations due to the heterogeneity in the neurodegenerative stage and/or technical artefacts. After correcting for cell composition, we identified a common signature that deregulated the previously unreported ammonium transport, as well as known biological processes such as bioenergetic pathways, response to proteotoxic stress, and immune response. By integrating with protein interaction data, we shortlisted a set of key genes, such as LRRK2, PINK1, PRKN, and FBXO7, known to be related to PD, others with compelling evidence for their role in neurodegeneration, such as GSK3β, WWOX, and VPC, and novel potential players in the PD pathogenesis. Together, these data show the importance of accounting for cyto-architecture in these analyses and highlight the contribution of multiple cell types and novel processes to PD pathology, providing potential new targets for drug development.

α-Synuclein antisense transcript SNCA-AS1 regulates synapses- and aging-related genes suggesting its implication in Parkinson's disease

SNCA protein product, α‐synuclein, is widely renowned for its role in synaptogenesis and implication in both aging and Parkinson's disease (PD), but research efforts are still needed to elucidate its physiological functions and mechanisms of regulation. In this work, we aim to characterize SNCA‐AS1, antisense transcript to the SNCA gene, and its implications in cellular processes. The overexpression of SNCA‐AS1 upregulates both SNCA and α‐synuclein and, through RNA‐sequencing analysis, we investigated the transcriptomic changes of which both genes are responsible. We highlight how they impact neurites' extension and synapses' biology, through specific molecular signatures. We report a reduced expression of markers associated with synaptic plasticity, and we specifically focus on GABAergic and dopaminergic synapses, for their relevance in aging processes and PD, respectively. A reduction in SNCA‐AS1 expression leads to the opposite effect. As part of this signature is co‐regulated by the two genes, we discriminate between functions elicited by genes specifically altered by SNCA‐AS1 or SNCA's overexpression, observing a relevant role for SNCA‐AS1 in synaptogenesis through a shared molecular signature with SNCA. We also highlight how numerous deregulated pathways are implicated in aging‐related processes, suggesting that SNCA‐AS1 could be a key player in cellular senescence, with implications for aging‐related diseases. Indeed, the upregulation of SNCA‐AS1 leads to alterations in numerous PD‐specific genes, with an impact highly comparable to that of SNCA's upregulation. Our results show that SNCA‐AS1 elicits its cellular functions through the regulation of SNCA, with a specific modulation of synaptogenesis and senescence, presenting implications in PD.

Gene-corrected p.A30P SNCA patient-derived isogenic neurons rescue neuronal branching and function

Parkinson's disease (PD) is characterised by the degeneration of A9 dopaminergic neurons and the pathological accumulation of alpha-synuclein. The p.A30P SNCA mutation generates the pathogenic form of the alpha-synuclein protein causing an autosomal-dominant form of PD. There are limited studies assessing pathogenic SNCA mutations in patient-derived isogenic cell models. Here we provide a functional assessment of dopaminergic neurons derived from a patient harbouring the p.A30P SNCA mutation. Using two clonal gene-corrected isogenic cell lines we identified image-based phenotypes showing impaired neuritic processes. The pathological neurons displayed impaired neuronal activity, reduced mitochondrial respiration, an energy deficit, vulnerability to rotenone, and transcriptional alterations in lipid metabolism. Our data describes for the first time the mutation-only effect of the p.A30P SNCA mutation on neuronal function, supporting the use of isogenic cell lines in identifying image-based pathological phenotypes that can serve as an entry point for future disease-modifying compound screenings and drug discovery strategies.

Cross-platform transcriptional profiling identifies common and distinct molecular pathologies in Lewy body diseases

Parkinson's disease (PD), Parkinson's disease with dementia (PDD) and dementia with Lewy bodies (DLB) are three clinically, genetically and neuropathologically overlapping neurodegenerative diseases collectively known as the Lewy body diseases (LBDs). A variety of molecular mechanisms have been implicated in PD pathogenesis, but the mechanisms underlying PDD and DLB remain largely unknown, a knowledge gap that presents an impediment to the discovery of disease-modifying therapies. Transcriptomic profiling can contribute to addressing this gap, but remains limited in the LBDs. Here, we applied paired bulk-tissue and single-nucleus RNA-sequencing to anterior cingulate cortex samples derived from 28 individuals, including healthy controls, PD, PDD and DLB cases (n = 7 per group), to transcriptomically profile the LBDs. Using this approach, we (i) found transcriptional alterations in multiple cell types across the LBDs; (ii) discovered evidence for widespread dysregulation of RNA splicing, particularly in PDD and DLB; (iii) identified potential splicing factors, with links to other dementia-related neurodegenerative diseases, coordinating this dysregulation; and (iv) identified transcriptomic commonalities and distinctions between the LBDs that inform understanding of the relationships between these three clinical disorders. Together, these findings have important implications for the design of RNA-targeted therapies for these diseases and highlight a potential molecular "window" of therapeutic opportunity between the initial onset of PD and subsequent development of Lewy body dementia.

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.

Reduced ribosomal DNA transcription in the prefrontal cortex of suicide victims: consistence of new molecular RT-qPCR findings with previous morphometric data from AgNOR-stained pyramidal neurons

Prefrontal cortical regions play a key role in behavioural regulation, which is profoundly disturbed in suicide. The study was carried out on frozen cortical samples from the anterior cingulate cortex (dorsal and ventral parts, ACd and ACv), the orbitofrontal cortex (OFC), and the dorsolateral cortex (DLC) obtained from 20 suicide completers (predominantly violent) with unknown psychiatric diagnosis and 21 non-suicidal controls. The relative level of ribosomal RNA (rRNA) as a marker of the transcriptional activity of ribosomal DNA (rDNA) was evaluated bilaterally in prefrontal regions mentioned above (i.e. in eight regions of interest, ROIs) by reverse transcription and quantitative polymerase chain reaction (RT-qPCR). The overall statistical analysis revealed a decrease in rDNA activity in suicide victims versus controls, particularly in male subjects. Further ROI-specific post hoc analyses revealed a significant decrease in this activity in suicides compared to non-suicides in five ROIs. This effect was accentuated in the ACv, where it was observed bilaterally. Our findings suggest that decreased rDNA transcription in the prefrontal cortex plays an important role in suicide pathogenesis and corresponds with our previous morphometric analyses of AgNOR-stained neurons.

Differential transcript usage in the Parkinson's disease brain

Studies of differential gene expression have identified several molecular signatures and pathways associated with Parkinson's disease (PD). The role of isoform switches and differential transcript usage (DTU) remains, however, unexplored. Here, we report the first genome-wide study of DTU in PD. We performed RNA sequencing following ribosomal RNA depletion in prefrontal cortex samples of 49 individuals from two independent case-control cohorts. DTU was assessed using two transcript-count based approaches, implemented in the DRIMSeq and DEXSeq tools. Multiple PD-associated DTU events were detected in each cohort, of which 23 DTU events in 19 genes replicated across both patient cohorts. For several of these, including THEM5, SLC16A1 and BCHE, DTU was predicted to have substantial functional consequences, such as altered subcellular localization or switching to non-protein coding isoforms. Furthermore, genes with PD-associated DTU were enriched in functional pathways previously linked to PD, including reactive oxygen species generation and protein homeostasis. Importantly, the vast majority of genes exhibiting DTU were not differentially expressed at the gene-level and were therefore not identified by conventional differential gene expression analysis. Our findings provide the first insight into the DTU landscape of PD and identify novel disease-associated genes. Moreover, we show that DTU may have important functional consequences in the PD brain, since it is predicted to alter the functional composition of the proteome. Based on these results, we propose that DTU analysis is an essential complement to differential gene expression studies in order to provide a more accurate and complete picture of disease-associated transcriptomic alterations.

Donor-Specific Transcriptomic Analysis of Alzheimer's Disease-Associated Hypometabolism Highlights a Unique Donor, Ribosomal Proteins and Microglia

Alzheimer's disease (AD) starts decades before clinical symptoms appear. Low-glucose utilization in regions of the cerebral cortex marks early AD. To identify these regions, we conducted a voxel-wise meta-analysis of previous studies conducted with positron emission tomography that compared AD patients with healthy controls. The resulting map marks hypometabolism in the posterior cingulate, middle frontal, angular gyrus, and middle and inferior temporal regions. Using the Allen Human Brain Atlas, we identified genes that show spatial correlation across the cerebral cortex between their expression and this hypometabolism. Of the six brains in the Atlas, one demonstrated a strong spatial correlation between gene expression and hypometabolism. Previous neuropathological assessment of this brain from a 39-year-old male noted a neurofibrillary tangle in the entorhinal cortex. Using the transcriptomic data, we estimate lower proportions of neurons and more microglia in the hypometabolic regions when comparing this donor's brain with the other five donors. Within this single brain, signal recognition particle (SRP)-dependent cotranslational protein targeting genes, which encode primarily cytosolic ribosome proteins, are highly expressed in the hypometabolic regions. Analyses of human and mouse data show that expression of these genes increases progressively across AD-associated states of microglial activation. In addition, genes involved in cell killing, chronic inflammation, ubiquitination, tRNA aminoacylation, and vacuole sorting are associated with the hypometabolism map. These genes suggest disruption of the protein life cycle and neuroimmune activation. Taken together, our molecular characterization reveals a link to AD-associated hypometabolism that may be relevant to preclinical stages of AD.