Transcriptomic signatures of brain regional vulnerability to Parkinson's disease

Association between Parkinson's Disease and Cancer: New Findings and Possible Mediators

Epidemiological evidence points to an inverse association between Parkinson's disease (PD) and almost all cancers except melanoma, for which this association is positive. The results of multiple studies have demonstrated that patients with PD are at reduced risk for the majority of neoplasms. Several potential biological explanations exist for the inverse relationship between cancer and PD. Recent results identified several PD-associated proteins and factors mediating cancer development and cancer-associated factors affecting PD. Accumulating data point to the role of genetic traits, members of the synuclein family, neurotrophic factors, the ubiquitin-proteasome system, circulating melatonin, and transcription factors as mediators. Here, we present recent data about shared pathogenetic factors and mediators that might be involved in the association between these two diseases. We discuss how these factors, individually or in combination, may be involved in pathology, serve as links between PD and cancer, and affect the prevalence of these disorders. Identification of these factors and investigation of their mechanisms of action would lead to the discovery of new targets for the treatment of both diseases.

Exploring functional dysconnectivity in schizophrenia: alterations in eigenvector centrality mapping and insights into related genes from transcriptional profiles

Schizophrenia is a mental health disorder characterized by functional dysconnectivity. Eigenvector centrality mapping (ECM) has been employed to investigate alterations in functional connectivity in schizophrenia, yet the results lack consistency, and the genetic mechanisms underlying these changes remain unclear. In this study, whole-brain voxel-wise ECM analyses were conducted on resting-state functional magnetic resonance imaging data. A cohort of 91 patients with schizophrenia and 91 matched healthy controls were included during the discovery stage. Additionally, in the replication stage, 153 individuals with schizophrenia and 182 healthy individuals participated. Subsequently, a comprehensive analysis was performed using an independent transcriptional database derived from six postmortem healthy adult brains to explore potential genetic factors influencing the observed functional dysconnectivity, and to investigate the roles of identified genes in neural processes and pathways. The results revealed significant and reliable alterations in the ECM across multiple brain regions in schizophrenia. Specifically, there was a significant decrease in ECM in the bilateral superior and middle temporal gyrus, and an increase in the bilateral thalamus in both the discovery and replication stages. Furthermore, transcriptional analysis revealed 420 genes whose expression patterns were related to changes in ECM, and these genes were enriched mainly in biological processes associated with synaptic signaling and transmission. Together, this study enhances our knowledge of the neural processes and pathways involved in schizophrenia, shedding light on the genetic factors that may be linked to functional dysconnectivity in this disorder.

Morphometric similarity differences in drug-naive Parkinson's disease correlate with transcriptomic signatures

BACKGROUND

Differences in cortical morphology have been reported in individuals with Parkinson's disease (PD). However, the pathophysiological mechanism of transcriptomic vulnerability in local brain regions remains unclear.

OBJECTIVE

This study aimed to characterize the morphometric changes of brain regions in early drug-naive PD patients and uncover the brain-wide gene expression correlates.

METHODS

The morphometric similarity (MS) network analysis was used to quantify the interregional structural similarity from multiple magnetic resonance imaging anatomical indices measured in each brain region of 170 early drug-naive PD patients and 123 controls. Then, we applied partial least squares regression to determine the relationship between regional changes in MS and spatial transcriptional signatures from the Allen Human Brain Atlas dataset, and identified the specific genes related to MS differences in PD. We further investigated the biological processes by which the PD-related genes were enriched and the cellular characterization of these genes.

RESULTS

Our results showed that MS was mainly decreased in cingulate, frontal, and temporal cortical areas and increased in parietal and occipital cortical areas in early drug-naive PD patients. In addition, genes whose expression patterns were associated with regional MS changes in PD were involved in astrocytes, excitatory, and inhibitory neurons and were functionally enriched in neuron-specific biological processes related to trans-synaptic signaling and nervous system development.

CONCLUSIONS

These findings advance our understanding of the microscale genetic and cellular mechanisms driving macroscale morphological abnormalities in early drug-naive PD patients and provide potential targets for future therapeutic trials.

More than meets the eye in Parkinson's disease and other synucleinopathies: from proteinopathy to lipidopathy

The accumulation of proteinaceous inclusions in the brain is a common feature among neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease (PD), and dementia with Lewy bodies (DLB). The main neuropathological hallmark of PD and DLB are inclusions, known as Lewy bodies (LBs), enriched not only in α-synuclein (aSyn), but also in lipid species, organelles, membranes, and even nucleic acids. Furthermore, several genetic risk factors for PD are mutations in genes involved in lipid metabolism, such as GBA1, VSP35, or PINK1. Thus, it is not surprising that mechanisms that have been implicated in PD, such as inflammation, altered intracellular and vesicular trafficking, mitochondrial dysfunction, and alterations in the protein degradation systems, may be also directly or indirectly connected through lipid homeostasis. In this review, we highlight and discuss the recent evidence that suggests lipid biology as important drivers of PD, and which require renovated attention by neuropathologists. Particularly, we address the implication of lipids in aSyn accumulation and in the spreading of aSyn pathology, in mitochondrial dysfunction, and in ER stress. Together, this suggests we should broaden the view of PD not only as a proteinopathy but also as a lipidopathy.

Brain-wide transcriptome-based metabolic alterations in Parkinson's disease: human inter-region and human-experimental model correlations

Alterations in brain metabolism are closely associated with the molecular hallmarks of Parkinson's disease (PD). A clear understanding of the main metabolic perturbations in PD is therefore important. Here, we retrospectively analysed the expression of metabolic genes from 34 PD-control post-mortem human brain transcriptome data comparisons from literature, spanning multiple brain regions. We found high metabolic correlations between the Substantia nigra (SN)- and cerebral cortex-derived tissues. Moreover, three clusters of PD patient cohorts were identified based on perturbed metabolic processes in the SN - each characterised by perturbations in (a) bile acid metabolism (b) omega-3 fatty acid metabolism, and (c) lipoic acid and androgen metabolism - metabolic themes not comprehensively addressed in PD. These perturbations were supported by concurrence between transcriptome and proteome changes in the expression patterns for CBR1, ECI2, BDH2, CYP27A1, ALDH1B1, ALDH9A1, ADH5, ALDH7A1, L1CAM, and PLXNB3 genes, providing a valuable resource for drug targeting and diagnosis. Also, we analysed 58 PD-control transcriptome data comparisons from in vivo/in vitro disease models and identified experimental PD models with significant correlations to matched human brain regions. Collectively, our findings suggest metabolic alterations in several brain regions, heterogeneity in metabolic alterations between study cohorts for the SN tissues and the need to optimize current experimental models to advance research on metabolic aspects of PD.

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.

RNA alternative splicing impacts the risk for alcohol use disorder

Alcohol use disorder (AUD) is a complex genetic disorder characterized by problems arising from excessive alcohol consumption. Identifying functional genetic variations that contribute to risk for AUD is a major goal. Alternative splicing of RNA mediates the flow of genetic information from DNA to gene expression and expands proteome diversity. We asked whether alternative splicing could be a risk factor for AUD. Herein, we used a Mendelian randomization (MR)-based approach to identify skipped exons (the predominant splicing event in brain) that contribute to AUD risk. Genotypes and RNA-seq data from the CommonMind Consortium were used as the training dataset to develop predictive models linking individual genotypes to exon skipping in the prefrontal cortex. We applied these models to data from the Collaborative Studies on Genetics of Alcoholism to examine the association between the imputed cis-regulated splicing outcome and the AUD-related traits. We identified 27 exon skipping events that were predicted to affect AUD risk; six of these were replicated in the Australian Twin-family Study of Alcohol Use Disorder. Their host genes are DRC1, ELOVL7, LINC00665, NSUN4, SRRM2 and TBC1D5. The genes downstream of these splicing events are enriched in neuroimmune pathways. The MR-inferred impacts of the ELOVL7 skipped exon on AUD risk was further supported in four additional large-scale genome-wide association studies. Additionally, this exon contributed to changes of gray matter volumes in multiple brain regions, including the visual cortex known to be involved in AUD. In conclusion, this study provides strong evidence that RNA alternative splicing impacts the susceptibility to AUD and adds new information on AUD-relevant genes and pathways. Our framework is also applicable to other types of splicing events and to other complex genetic disorders.

Therapeutic Role of ELOVL in Neurological Diseases

Fatty acids play an important role in controlling the energy balance of mammals. De novo lipogenesis also generates a significant amount of lipids that are endogenously produced in addition to their ingestion. Fatty acid elongation beyond 16 carbons (palmitic acid), which can lead to the production of very long chain fatty acids (VLCFA), can be caused by the rate-limiting condensation process. Seven elongases, ELOVL1-7, have been identified in mammals and each has a unique substrate specificity. Researchers have recently developed a keen interest in the elongation of very long chain fatty acids protein 1 (ELOVL1) enzyme as a potential treatment for a variety of diseases. A number of neurological disorders directly or indirectly related to ELOVL1 involve the elongation of monounsaturated (C20:1 and C22:1) and saturated (C18:0-C26:0) acyl-CoAs. VLCFAs and ELOVL1 have a direct impact on the neurological disease. Other neurological symptoms such as ichthyotic keratoderma, spasticity, and hypomyelination have also been linked to the major enzyme (ELOVL1). Recently, ELOVL1 has also been heavily used to treat a number of diseases. The current review focuses on in-depth unique insights regarding the role of ELOVL1 as a therapeutic target and associated neurological disorders.

Assessment of Alzheimer-related pathologies of dementia using machine learning feature selection

Although a variety of brain lesions may contribute to the pathological assessment of dementia, the relationship of these lesions to dementia, how they interact and how to quantify them remains uncertain. Systematically assessing neuropathological measures by their degree of association with dementia may lead to better diagnostic systems and treatment targets. This study aims to apply machine learning approaches to feature selection in order to identify critical features of Alzheimer-related pathologies associated with dementia. We applied machine learning techniques for feature ranking and classification to objectively compare neuropathological features and their relationship to dementia status during life using a cohort (n=186) from the Cognitive Function and Ageing Study (CFAS). We first tested Alzheimer's Disease and tau markers and then other neuropathologies associated with dementia. Seven feature ranking methods using different information criteria consistently ranked 22 out of the 34 neuropathology features for importance to dementia classification. Although highly correlated, Braak neurofibrillary tangle stage, beta-amyloid and cerebral amyloid angiopathy features were ranked the highest. The best-performing dementia classifier using the top eight neuropathological features achieved 79% sensitivity, 69% specificity and 75% precision. However, when assessing all seven classifiers and the 22 ranked features, a substantial proportion (40.4%) of dementia cases was consistently misclassified. These results highlight the benefits of using machine learning to identify critical indices of plaque, tangle and cerebral amyloid angiopathy burdens that may be useful for classifying dementia.

Investigating the shared genetic architecture and causal relationship between pain and neuropsychiatric disorders

Pain often occurs in parallel with neuropsychiatric disorders. However, the underlying mechanisms and potential causality have not been well studied. We collected the genome-wide association study (GWAS) summary statistics of 26 common pain and neuropsychiatric disorders with sample size ranging from 17,310 to 482,730 in European population. The genetic correlation between pair of pain and neuropsychiatric disorders, as well as the relevant cell types were investigated by linkage disequilibrium (LD) score regression analyses. Then, transcriptome-wide association study (TWAS) was applied to identify the potential shared genes by integrating the gene expression information and GWAS. In addition, Mendelian randomization (MR) analyses were conducted to infer the potential causality between pain and neuropsychiatric disorders. Among the 169 pairwise pain and neuropsychiatric disorders, 55 pairs showed positive correlations (median r_g = 0.43) and 9 pairs showed negative correlations (median r_g =  -0.31). Using MR analyses, 26 likely causal associations were identified, including that neuroticism and insomnia were risk factors for most of short-term pain, and multisite chronic pain was risk factor for neuroticism, insomnia, major depressive disorder and attention deficit/hyperactivity disorder, and vice versa. The signals of pain and neuropsychiatric disorders tended to be enriched in the functional regions of cell types from central nervous system (CNS). A total of 19 genes shared in at least one pain and neuropsychiatric disorder pair were identified by TWAS, including AMT, NCOA6, and UNC45A, which involved in glycine degradation, insulin secretion, and cell proliferation, respectively. Our findings provided the evidence of shared genetic structure, causality and potential shared pathogenic mechanisms between pain and neuropsychiatric disorders, and enhanced our understanding of the comorbidities of pain and neuropsychiatric disorders.

Genes critical for development and differentiation of dopaminergic neurons are downregulated in Parkinson's disease

We performed transcriptome analysis using RNA sequencing on substantia nigra pars compacta (SNpc) from mice after acute and chronic 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) treatment and from Parkinson's disease (PD) patients. Acute and chronic exposure to MPTP resulted in decreased expression of genes involved in sodium channel regulation. However, upregulation of pro-inflammatory pathways was seen after single dose but not after chronic MPTP treatment. Dopamine biosynthesis and synaptic vesicle recycling pathways were downregulated in PD patients and after chronic MPTP treatment in mice. Genes essential for midbrain development and determination of dopaminergic phenotype such as, LMX1B, FOXA1, RSPO2, KLHL1, EBF3, PITX3, RGS4, ALDH1A1, RET, FOXA2, EN1, DLK1, GFRA1, LMX1A, NR4A2, GAP43, SNCA, PBX1, and GRB10 were downregulated in human PD and overexpression of GFP tagged LMX1B rescued MPP⁺ induced death in SH-SY5Y neurons. Downregulation of gene ensemble involved in development and differentiation of dopaminergic neurons indicate their potential involvement in pathogenesis and progression of human PD.

Increased Levels of the Parkinson's Disease-Associated Gene ITPKB Correlate with Higher Expression Levels of α-Synuclein, Independent of Mutation Status

Autosomal dominant mutations in the gene encoding α-synuclein (SNCA) were the first to be linked with hereditary Parkinson's disease (PD). Duplication and triplication of SNCA has been observed in PD patients, together with mutations at the N-terminal of the protein, among which A30P and A53T influence the formation of fibrils. By overexpressing human α-synuclein in the neuronal system of Drosophila, we functionally validated the ability of IP3K2, an ortholog of the GWAS identified risk gene, Inositol-trisphosphate 3-kinase B (ITPKB), to modulate α-synuclein toxicity in vivo. ITPKB mRNA and protein levels were also increased in SK-N-SH cells overexpressing wild-type α-synuclein, A53T or A30P mutants. Kinase overexpression was detected in the cytoplasmatic and in the nuclear compartments in all α-synuclein cell types. By quantifying mRNAs in the cortex of PD patients, we observed higher levels of ITPKB mRNA when SNCA was expressed more (p < 0.05), compared to controls. A positive correlation was also observed between SNCA and ITPKB expression in the cortex of patients, which was not seen in the controls. We replicated this observation in a public dataset. Our data, generated in SK-N-SH cells and in cortex from PD patients, show that the expression of α-synuclein and ITPKB is correlated in pathological situations.

The Role of Endophilin A1 in Lipopolysaccharide-Induced Parkinson's Disease Model Mice

BACKGROUND

Endophilin A1 (EPA1) is encoded by the SH3GL2 gene, and SH3GL2 was designated as a Parkinson's disease (PD) risk locus by genome-wide association analysis, suggesting that EPA1 may be involved in the occurrence and development of PD.

OBJECTIVE

To investigate the role of EPA1 in lipopolysaccharide (LPS)-induced PD model mice.

METHODS

The mice PD model was prepared by injecting LPS into the substantia nigra (SN), and the changes in the behavioral data of mice in each group were observed. The damage of dopaminergic neurons, activation of microglia, and reactive oxygen species (ROS) generation were detected by immunofluorescence method; calcium ion concentration was detected by calcium content detection kit; EPA1 and inflammation and its related indicators were detected by western blot method. EPA1 knockdown was performed by an adeno-associated virus vector containing EPA1-shRNA-eGFP infusion.

RESULTS

LPS-induced PD model mice developed behavioral dysfunction, SN dopaminergic nerve damage, significantly increased calcium ion, calpain 1, and ROS production, activated NLRP1 inflammasome and promoted pro-inflammatory cell release, and SN EPA1 knockdown improves behavioral disorders, alleviates dopaminergic neuron damage, reduces calcium, calpain 1, ROS generation, and blocks NLRP1 inflammasome-driven inflammatory responses.

CONCLUSION

The expression of EPA1 in the SN of LPS-induced PD model mice was increased, and it played a role in promoting the occurrence and development of PD. EPA1 knockdown inhibited the NLRP1 inflammasome activation, decreased the release of inflammatory factors and ROS generation, and alleviated dopaminergic neuron damage. This indicated that EPA1 may participating in the occurrence and development of PD.

Discovery and validation of Ferroptosis-related molecular patterns and immune characteristics in Alzheimer's disease

Background

To date, the pathogenesis of Alzheimer's disease is still not fully elucidated. Much evidence suggests that Ferroptosis plays a crucial role in the pathogenesis of AD, but little is known about its molecular immunological mechanisms. Therefore, this study aims to comprehensively analyse and explore the molecular mechanisms and immunological features of Ferroptosis-related genes in the pathogenesis of AD.

Materials and methods

We obtained the brain tissue dataset for AD from the GEO database and downloaded the Ferroptosis-related gene set from FerrDb for analysis. The most relevant Hub genes for AD were obtained using two machine learning algorithms (Least absolute shrinkage and selection operator (LASSO) and multiple support vector machine recursive feature elimination (mSVM-RFE)). The study of the Hub gene was divided into two parts. In the first part, AD patients were genotyped by unsupervised cluster analysis, and the different clusters' immune characteristics were analysed. A PCA approach was used to quantify the FRGscore. In the second part: we elucidate the biological functions involved in the Hub genes and their role in the immune microenvironment by integrating algorithms (GSEA, GSVA and CIBERSORT). Analysis of Hub gene-based drug regulatory networks and mRNA-miRNA-lncRNA regulatory networks using Cytoscape. Hub genes were further analysed using logistic regression models.

Results

Based on two machine learning algorithms, we obtained a total of 10 Hub genes. Unsupervised clustering successfully identified two different clusters, and immune infiltration analysis showed a significantly higher degree of immune infiltration in type A than in type B, indicating that type A may be at the peak of AD neuroinflammation. Secondly, a Hub gene-based Gene-Drug regulatory network and a ceRNA regulatory network were successfully constructed. Finally, a logistic regression algorithm-based AD diagnosis model and Nomogram diagram were developed.

Conclusion

Our study provides new insights into the role of Ferroptosis-related molecular patterns and immune mechanisms in AD, as well as providing a theoretical basis for the addition of diagnostic markers for AD.

Inflammation and immune dysfunction in Parkinson disease

Parkinson disease (PD) is a progressive neurodegenerative disease that affects peripheral organs as well as the central nervous system and involves a fundamental role of neuroinflammation in its pathophysiology. Neurohistological and neuroimaging studies support the presence of ongoing and end-stage neuroinflammatory processes in PD. Moreover, numerous studies of peripheral blood and cerebrospinal fluid from patients with PD suggest alterations in markers of inflammation and immune cell populations that could initiate or exacerbate neuroinflammation and perpetuate the neurodegenerative process. A number of disease genes and risk factors have been identified as modulators of immune function in PD and evidence is mounting for a role of viral or bacterial exposure, pesticides and alterations in gut microbiota in disease pathogenesis. This has led to the hypothesis that complex gene-by-environment interactions combine with an ageing immune system to create the 'perfect storm' that enables the development and progression of PD. We discuss the evidence for this hypothesis and opportunities to harness the emerging immunological knowledge from patients with PD to create better preclinical models with the long-term goal of enabling earlier identification of at-risk individuals to prevent, delay and more effectively treat the disease.

Transcriptome-wide and stratified genomic structural equation modeling identify neurobiological pathways shared across diverse cognitive traits

Functional genomic methods are needed that consider multiple genetically correlated traits. Here we develop and validate Transcriptome-wide Structural Equation Modeling (T-SEM), a multivariate method for studying the effects of tissue-specific gene expression across genetically overlapping traits. T-SEM allows for modeling effects on broad dimensions spanning constellations of traits, while safeguarding against false positives that can arise when effects of gene expression are specific to a subset of traits. We apply T-SEM to investigate the biological mechanisms shared across seven distinct cognitive traits (N = 11,263-331,679), as indexed by a general dimension of genetic sharing (g). We identify 184 genes whose tissue-specific expression is associated with g, including 10 genes not identified in univariate analysis for the individual cognitive traits for any tissue type, and three genes whose expression explained a significant portion of the genetic sharing across g and different subclusters of psychiatric disorders. We go on to apply Stratified Genomic SEM to identify enrichment for g within 28 functional categories. This includes categories indexing the intersection of protein-truncating variant intolerant (PI) genes and specific neuronal cell types, which we also find to be enriched for the genetic covariance between g and a psychotic disorders factor.

Transcriptomic and connectomic correlates of differential spatial patterning among gliomas

Unravelling the complex events driving grade-specific spatial distribution of brain tumour occurrence requires rich datasets from both healthy individuals and patients. Here, we combined open-access data from The Cancer Genome Atlas, the UK Biobank and the Allen Brain Human Atlas to disentangle how the different spatial occurrences of glioblastoma multiforme and low-grade gliomas are linked to brain network features and the normative transcriptional profiles of brain regions. From MRI of brain tumour patients, we first constructed a grade-related frequency map of the regional occurrence of low-grade gliomas and the more aggressive glioblastoma multiforme. Using associated mRNA transcription data, we derived a set of differential gene expressions from glioblastoma multiforme and low-grade gliomas tissues of the same patients. By combining the resulting values with normative gene expressions from post-mortem brain tissue, we constructed a grade-related expression map indicating which brain regions express genes dysregulated in aggressive gliomas. Additionally, we derived an expression map of genes previously associated with tumour subtypes in a genome-wide association study (tumour-related genes). There were significant associations between grade-related frequency, grade-related expression and tumour-related expression maps, as well as functional brain network features (specifically, nodal strength and participation coefficient) that are implicated in neurological and psychiatric disorders. These findings identify brain network dynamics and transcriptomic signatures as key factors in regional vulnerability for glioblastoma multiforme and low-grade glioma occurrence, placing primary brain tumours within a well established framework of neurological and psychiatric cortical alterations.

Characterization of exogenous αSN response genes and their relation to Parkinson’s disease using network analyses

Despite extensive research, the molecular mechanisms underlying the toxicity of αSN in Parkinson’s disease (PD) pathology are still poorly understood. To address this, we used a microarray dataset to identify genes that are induced and differentially expressed after exposure to toxic αSN aggregates, which we call exogenous αSN response (EASR) genes. Using systems biology approaches, we then determined, at multiple levels of analysis, how these EASR genes could be related to PD pathology. A key result was the identification of functional connections between EASR genes and previously identified PD-related genes by employing the proteins’ interactions networks and 9 brain region-specific co-expression networks. In each brain region, co-expression modules of EASR genes were enriched for gene sets whose expression are altered by SARS-CoV-2 infection, leading to the hypothesis that EASR co-expression genes may explain the observed links between COVID-19 and PD. An examination of the expression pattern of EASR genes in different non-neurological healthy brain regions revealed that regions with lower mean expression of the upregulated EASR genes, such as substantia nigra, are more vulnerable to αSN aggregates and lose their neurological functions during PD progression. Gene Set Enrichment Analysis of healthy and PD samples from substantia nigra revealed that a specific co-expression network, “TNF-α signaling via NF-κB”, is an upregulated pathway associated with the PD phenotype. Inhibitors of the “TNF-α signaling via NF-κB” pathway may, therefore, decrease the activity level of this pathway and thereby provide therapeutic benefits for PD patients. We virtually screened FDA-approved drugs against these upregulated genes (NR4A1, DUSP1, and FOS) using docking-based drug discovery and identified several promising drugs. Altogether, our study provides a better understanding of αSN toxicity mechanisms in PD and identifies potential therapeutic targets and small molecules for treatment of PD.

Epigenome-wide association study of human frontal cortex identifies differential methylation in Lewy body pathology

Parkinson's disease (PD) and dementia with Lewy bodies (DLB) are closely related progressive disorders with no available disease-modifying therapy, neuropathologically characterized by intraneuronal aggregates of misfolded α-synuclein. To explore the role of DNA methylation changes in PD and DLB pathogenesis, we performed an epigenome-wide association study (EWAS) of 322 postmortem frontal cortex samples and replicated results in an independent set of 200 donors. We report novel differentially methylated replicating loci associated with Braak Lewy body stage near TMCC2, SFMBT2, AKAP6 and PHYHIP. Differentially methylated probes were independent of known PD genetic risk alleles. Meta-analysis provided suggestive evidence for a differentially methylated locus within the chromosomal region affected by the PD-associated 22q11.2 deletion. Our findings elucidate novel disease pathways in PD and DLB and generate hypotheses for future molecular studies of Lewy body pathology.

Effects of the administration of Elovl5-dependent fatty acids on a spino-cerebellar ataxia 38 mouse model

Background

Spinocerebellar ataxia 38 (SCA38) is a rare autosomal neurological disorder characterized by ataxia and cerebellar atrophy. SCA38 is caused by mutations of ELOVL5 gene. ELOVL5 gene encodes a protein, which elongates long chain polyunsaturated fatty acids (PUFAs). Knockout mice lacking Elovl5 recapitulate SCA38 symptoms, including motor coordination impairment and disruption of cerebellar architecture. We asked whether, in Elovl5 knockout mice (Elovl5^−/−), a diet with both ω3 and ω6 PUFAs downstream Elovl5 can prevent the development of SCA38 symptoms, and at which age such treatment is more effective. Elovl5^−/− mice were fed either with a diet without or containing PUFAs downstream the Elovl5 enzyme, starting at different ages. Motor behavior was assessed by the balance beam test and cerebellar structure by morphometric analysis.

Results

The administration from birth of the diet containing PUFAs downstream Elovl5 led to a significant amelioration of the motor performance in the beam test of Elovl5^−/− mice, with a reduction of foot slip errors at 6 months from 2.2 ± 0.3 to 1.3 ± 0.2 and at 8 months from 3.1 ± 0.5 to 1.9 ± 0.3. On the contrary, administration at 1 month of age or later had no effect on the motor impairment. The cerebellar Purkinje cell layer and the white matter area of Elovl5^{−/ −}mice were not rescued even by the administration of diet from birth, suggesting that the improvement of motor performance in the beam test was due to a functional recovery of the cerebellar circuitry.

Conclusions

These results suggest that the dietary intervention in SCA38, whenever possible, should be started from birth or as early as possible.

Genetic mechanisms underlying brain functional homotopy: a combined transcriptome and resting-state functional MRI study

Functional homotopy, the high degree of spontaneous activity synchrony and functional coactivation between geometrically corresponding interhemispheric regions, is a fundamental characteristic of the intrinsic functional architecture of the brain. However, little is known about the genetic mechanisms underlying functional homotopy. Resting-state functional magnetic resonance imaging data from a discovery dataset (656 healthy subjects) and 2 independent cross-race, cross-scanner validation datasets (103 and 329 healthy subjects) were used to calculate voxel-mirrored homotopic connectivity (VMHC) indexing brain functional homotopy. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial correlation analysis was conducted to identify genes linked to VMHC. We found 1,001 genes whose expression measures were spatially associated with VMHC. Functional enrichment analyses demonstrated that these VMHC-related genes were enriched for biological functions including protein kinase activity, ion channel regulation, and synaptic function as well as many neuropsychiatric disorders. Concurrently, specific expression analyses showed that these genes were specifically expressed in the brain tissue, in neurons and immune cells, and during nearly all developmental periods. In addition, the VMHC-associated genes were linked to multiple behavioral domains, including vision, execution, and attention. Our findings suggest that interhemispheric communication and coordination involve a complex interaction of polygenes with a rich range of functional features.

Multi-platform quantitation of alpha-synuclein human brain proteoforms suggests disease-specific biochemical profiles of synucleinopathies

Based on immunostainings and biochemical analyses, certain post-translationally modified alpha-synuclein (aSyn) variants, including C-terminally truncated (CTT) and Serine-129 phosphorylated (pSer129) aSyn, are proposed to be involved in the pathogenesis of synucleinopathies such as Parkinson’s disease with (PDD) and without dementia (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). However, quantitative information about aSyn proteoforms in the human brain in physiological and different pathological conditions is still limited. To address this, we generated sequential biochemical extracts of the substantia nigra, putamen and hippocampus from 28 donors diagnosed and neuropathologically-confirmed with different synucleinopathies (PD/PDD/DLB/MSA), as well as Alzheimer’s disease, progressive supranuclear palsy, and aged normal subjects. The tissue extracts were used to build a reverse phase array including 65 aSyn antibodies for detection. In this multiplex approach, we observed increased immunoreactivity in donors with synucleinopathies compared to controls in detergent-insoluble fractions, mainly for antibodies against CT aSyn and pSer129 aSyn. In addition, despite of the restricted sample size, clustering analysis suggested disease-specific immunoreactivity signatures in patient groups with different synucleinopathies. We aimed to validate and quantify these findings using newly developed immunoassays towards total, 119 and 122 CTT, and pSer129 aSyn. In line with previous studies, we found that synucleinopathies shared an enrichment of post-translationally modified aSyn in detergent-insoluble fractions compared to the other analyzed groups. Our measurements allowed for a quantitative separation of PDD/DLB patients from other synucleinopathies based on higher detergent-insoluble pSer129 aSyn concentrations in the hippocampus. In addition, we found that MSA stood out due to enrichment of CTT and pSer129 aSyn also in the detergent-soluble fraction of the SN and putamen. Together, our results achieved by multiplexed and quantitative immunoassay-based approaches in human brain extracts of a limited sample set point to disease-specific biochemical aSyn proteoform profiles in distinct neurodegenerative disorders.

Transcriptomic and cellular decoding of functional brain connectivity changes reveal regional brain vulnerability to pro- and anti-inflammatory therapies

BACKGROUND

Systemic inflammation induces acute changes in mood, motivation and cognition that closely resemble those observed in depressed individuals. However, the mechanistic pathways linking peripheral inflammation to depression-like psychopathology via intermediate effects on brain function remain incompletely understood.

METHODS

We combined data from 30 patients initiating interferon-α treatment for Hepatitis-C and 20 anti-tumour necrosis factor (TNF) therapy for inflammatory arthritis and used resting-state functional magnetic resonance imaging to investigate acute effects of each treatment on regional global brain connectivity (GBC). We leveraged transcriptomic data from the Allen Human Brain Atlas to uncover potential biological and cellular pathways underpinning regional vulnerability to GBC changes induced by each treatment.

RESULTS

Interferon-α and anti-TNF therapies both produced differential small-to-medium sized decreases in regional GBC. However, these were observed within distinct brain regions and the regional patterns of GBC changes induced by each treatment did not correlate suggesting independent underlying processes. Further, the spatial distribution of these differential GBC decreases could be captured by multivariate patterns of constitutive regional expression of genes respectively related to: i) neuroinflammation and glial cells; and ii) glutamatergic neurotransmission and neurons. The extent to which each participant expressed patterns of GBC changes aligning with these patterns of transcriptomic vulnerability also correlated with both acute treatment-induced changes in interleukin-6 (IL-6) and, for Interferon-α, longer-term treatment-associated changes in depressive symptoms.

CONCLUSIONS

Together, we present two transcriptomic models separately linking regional vulnerability to the acute effects of interferon-α and anti-TNF treatments on brain function to glial neuroinflammation and glutamatergic neurotransmission. These findings generate hypotheses about two potential brain mechanisms through which bidirectional changes in peripheral inflammation may contribute to the development/resolution of psychopathology.

Methylated Cytochrome P450 and the Solute Carrier Family of Genes Correlate With Perturbations in Bile Acid Metabolism in Parkinson’s Disease

Parkinson’s disease (PD) is second most prevalent neurodegenerative disorder following Alzheimer’s disease. Parkinson’s disease is hypothesized to be caused by a multifaceted interplay between genetic and environmental factors. Herein, and for the first time, we describe the integration of metabolomics and epigenetics (genome-wide DNA methylation; epimetabolomics) to profile the frontal lobe from people who died from PD and compared them with age-, and sex-matched controls. We identified 48 metabolites to be at significantly different concentrations (FDR q < 0.05), 4,313 differentially methylated sites [5’-C-phosphate-G-3’ (CpGs)] (FDR q < 0.05) and increased DNA methylation age in the primary motor cortex of people who died from PD. We identified Primary bile acid biosynthesis as the major biochemical pathway to be perturbed in the frontal lobe of PD sufferers, and the metabolite taurine (p-value = 5.91E-06) as being positively correlated with CpG cg14286187 (SLC25A27; CYP39A1) (FDR q = 0.002), highlighting previously unreported biochemical changes associated with PD pathogenesis. In this novel multi-omics study, we identify regulatory mechanisms which we believe warrant future translational investigation and central biomarkers of PD which require further validation in more accessible biomatrices.

A co-expression network based molecular characterization of genes responsive for Braak stages in Parkinson's disease

The progression of Parkinson's disease (PD) is defined by six Braak stages. We used transcriptome data from PD patients with Braak stage information to understand underlying molecular mechanisms for the progress of the disease. We created networks of genes with decreased/increased co-expression from control group to Braak 5-6 stages. These networks are significantly associated with PD related mechanisms such as mitochondrial dysfunction and synaptic signaling among others. Applying Weighted Gene Correlation Network Analysis (WGCNA) algorithm to the co-expression networks led to more specific modules enriched with neurodegeneration related disease pathways, seizure, abnormality of coordination, and hypotonia. Furthermore, we showed that one of the co-expression networks is clustered into three major communities with dedicated molecular functions: (i) tubulin folding pathway, gap junction related mechanisms, neuronal system (ii) synaptic vesicle, intracellular vesicle, proteasome complex, PD genes (iii) energy metabolism, mitochondrial mechanisms, oxidative phosphorylation, TCA cycle, PD genes. The co-expression relations we identified in this study as crucial players in the disease progression cover several known PD-associated genes and genes whose products are known to physically interact with alpha-synuclein protein.

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.

Mapping the sequence specificity of heterotypic amyloid interactions enables the identification of aggregation modifiers

Heterotypic amyloid interactions between related protein sequences have been observed in functional and disease amyloids. While sequence homology seems to favour heterotypic amyloid interactions, we have no systematic understanding of the structural rules determining such interactions nor whether they inhibit or facilitate amyloid assembly. Using structure-based thermodynamic calculations and extensive experimental validation, we performed a comprehensive exploration of the defining role of sequence promiscuity in amyloid interactions. Using tau as a model system we demonstrate that proteins with local sequence homology to tau amyloid nucleating regions can modify fibril nucleation, morphology, assembly and spreading of aggregates in cultured cells. Depending on the type of mutation such interactions inhibit or promote aggregation in a manner that can be predicted from structure. We find that these heterotypic amyloid interactions can result in the subcellular mis-localisation of these proteins. Moreover, equilibrium studies indicate that the critical concentration of aggregation is altered by heterotypic interactions. Our findings suggest a structural mechanism by which the proteomic background can modulate the aggregation propensity of amyloidogenic proteins and we discuss how such sequence-specific proteostatic perturbations could contribute to the selective cellular susceptibility of amyloid disease progression.

In this work, Louros et al. uncover a rule book for interactions of amyloids with other proteins. This grammar was shown to promote cellular spreading of tau aggregates in cells, but can also be harvested to develop structure-based aggregation blockers.

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.

A Critical Analysis of Intestinal Enteric Neuron Loss and Constipation in Parkinson's Disease

Constipation afflicts many patients with Parkinson's disease (PD) and significantly impacts on patient quality of life. PD-related constipation is caused by intestinal dysfunction, but the etiology of this dysfunction in patients is unknown. One possible cause is neuron loss within the enteric nervous system (ENS) of the intestine. This review aims to 1) Critically evaluate the evidence for and against intestinal enteric neuron loss in PD patients, 2) Justify why PD-related constipation must be objectively measured, 3) Explore the potential link between loss of enteric neurons in the intestine and constipation in PD, 4) Provide potential explanations for disparities in the literature, and 5) Outline data and study design considerations to improve future research. Before the connection between intestinal enteric neuron loss and PD-related constipation can be confidently described, future research must use sufficiently large samples representative of the patient population (majority diagnosed with idiopathic PD for at least 5 years), implement a consistent neuronal quantification method and study design, including standardized patient recruitment criteria, objectively quantify intestinal dysfunctions, publish with a high degree of data transparency and account for potential PD heterogeneity. Further investigation into other potential influencers of PD-related constipation is also required, including changes in the function, connectivity, mitochondria and/or α-synuclein proteins of enteric neurons and their extrinsic innervation. The connection between enteric neuron loss and other PD-related gastrointestinal (GI) issues, including gastroparesis and dysphagia, as well as changes in nutrient absorption and the microbiome, should be explored in future research.

Imaging transcriptomics: Convergent cellular, transcriptomic, and molecular neuroimaging signatures in the healthy adult human brain

The integration of transcriptomic and neuroimaging data, "imaging transcriptomics," has recently emerged to generate hypotheses about potential biological pathways underlying regional variability in neuroimaging features. However, the validity of this approach is yet to be examined in depth. Here, we sought to bridge this gap by performing transcriptomic decoding of the regional distribution of well-known molecular markers spanning different elements of the biology of the healthy human brain. Imaging transcriptomics identifies biological and cell pathways that are consistent with the known biology of a wide range of molecular neuroimaging markers. The extent to which it can capture patterns of gene expression that align well with elements of the biology of the neuroinflammatory axis, at least in healthy controls without a proinflammatory challenge, is inconclusive. Imaging transcriptomics might constitute an interesting approach to improve our understanding of the biological pathways underlying regional variability in a wide range of neuroimaging phenotypes.

The Reactive Species Interactome in the Brain

Significance: Redox pioneer Helmut Sies attempted to explain reactive species' challenges faced by organelles, cells, tissues, and organs via three complementary definitions: (i) oxidative stress, that is, the disturbance in the prooxidant-antioxidant defense balance in favor of the prooxidants; (ii) oxidative eustress, the low physiological exposure to prooxidants; and (iii) oxidative distress, the supraphysiological exposure to prooxidants. Recent Advances: Identification, concentration, and interactions are the most important elements to improve our understanding of reactive species in physiology and pathology. In this context, the reactive species interactome (RSI) is a new multilevel redox regulatory system that identifies reactive species families, reactive oxygen species (ROS), reactive nitrogen species (RNS), and reactive sulfur species, and it integrates their interactions with their downstream biological targets. Critical Issues: We propose a united view to fully combine reactive species identification, oxidative eustress and distress, and the RSI system. In this view, we also propose including the forgotten reactive carbonyl species, an increasingly rediscovered reactive species family related to the other reactive families, and key enzymes within the RSI. We focus on brain physiology and pathology to demonstrate why this united view should be considered. Future Directions: More studies are needed for an improved understanding of the contributions of reactive species through their identification, concentration, and interactions, including in the brain. Appreciating the RSI in its entirety should unveil new molecular players and mechanisms in physiology and pathology in the brain and elsewhere.

Gene alteration in zebrafish exposed to a mixture of substances of abuse

A recent surge in the use and abuse of diverse prescribed psychotic and illicit drugs necessitates the surveillance of drug residues in source water and the associated ecological impacts of chronic exposure to the aquatic organism. Thirty-six psychotic and illicit drug residues were determined in discharged wastewater from two centralized municipal wastewater treatment facilities and two wastewater receiving creeks for seven consecutive days in Kentucky. Zebrafish (Danio rerio) larvae were exposed to the environmental relevant mixtures of all drug residues, all illicit drugs, and all prescribed psychotic drugs. The extracted RNA from fish homogenates was sequenced, and differentially expressed sequences were analyzed for known or predicted nervous system expression, and screened annotated protein-coding genes to the true environmental cocktail mixture. Illicit stimulant (cocaine and one metabolite), opioids (methadone, methadone metabolite, and oxycodone), hallucinogen (MDA), benzodiazepine (oxazepam and temazepam), carbamazepine, and all target selective serotonin reuptake inhibitors including sertraline, fluoxetine, venlafaxine, and citalopram were quantified in 100% of collected samples from both creeks. The high dose cocktail mixture exposure group revealed the largest group of differentially expressed genes: 100 upregulated and 77 downregulated (p ≤ 0.05; q ≤ 0.05). The top 20 differentially expressed sequences in each exposure group comprise 82 unique transcripts corresponding to 74% annotated genes, 7% non-coding sequences, and 19% uncharacterized sequences. Among 61 differentially expressed sequences that corresponded to annotated protein-coding genes, 23 (38%) genes or their homologs are known to be expressed in the nervous system of fish or other organisms. Several of the differentially expressed sequences are associated primarily with the immune system, including several major histocompatibility complex class I and interferon-induced proteins. Interleukin-1 beta (downregulated in this study) abnormalities are considered a risk factor for psychosis. This is the first study to assess the contributions of multiple classes of psychotic and illicit drugs in combination with developmental gene expression.

Human Cytomegalovirus Uses a Host Stress Response To Balance the Elongation of Saturated/Monounsaturated and Polyunsaturated Very-Long-Chain Fatty Acids

Stress and virus infection regulate lipid metabolism. Human cytomegalovirus (HCMV) infection induces fatty acid (FA) elongation and increases the abundance of lipids with very-long-chain FA (VLCFA) tails. While reprogramming of metabolism can be stress related, the role of stress in HCMV reprogramming of lipid metabolism is poorly understood. In this study, we engineered cells to knock out protein kinase R (PKR)-like endoplasmic reticulum kinase (PERK) in the ER stress pathway and measured lipid changes using lipidomics to determine if PERK is needed for lipid changes associated with HCMV infection. In HCMV-infected cells, PERK promotes increases in the levels of phospholipids with saturated FA (SFA) and monounsaturated FA (MUFA) VLCFA tails. Further, PERK enhances FA elongase 7 (ELOVL7) protein levels, which elongates SFA and MUFA VLCFAs. Additionally, we found that increases in the elongation of polyunsaturated fatty acids (PUFAs) associated with HCMV infection were independent of PERK and that lipids with PUFA tails accumulated in HCMV-infected PERK knockout cells. Additionally, the protein levels of ELOVL5, which elongates PUFAs, are increased by HCMV infection through a PERK-independent mechanism. These observations show that PERK differentially regulates ELOVL7 and ELOVL5, creating a balance between the synthesis of lipids with SFA/MUFA tails and PUFA tails. Additionally, we found that PERK was necessary for virus replication and the infectivity of released viral progeny. Overall, our findings indicate that PERK—and, more broadly, ER stress—may be necessary for the membrane biogenesis needed to generate infectious HCMV virions.

Elovl5 Expression in the Central Nervous System of the Adult Mouse

ELOVL5 (Elongase of Very-Long Fatty Acid 5) gene encodes for an enzyme that elongates long chain fatty acids, with a marked preference for polyunsaturated molecules. In particular, it plays an essential role in the elongation of omega-3 and omega-6 fatty acids, precursors for long-chain polyunsaturated fatty acids (PUFAs). Mutations of ELOVL5 cause the spino-cerebellar ataxia type 38 (SCA38), a rare autosomal neurological disease characterized by gait abnormality, dysarthria, dysphagia, hyposmia and peripheral neuropathy, conditions well represented by a mouse model with a targeted deletion of this gene (Elovl5^–/– mice). However, the expression pattern of this enzyme in neuronal and glial cells of the central nervous system (CNS) is still uninvestigated. This work is aimed at filling this gap of knowledge by taking advantage of an Elovl5-reporter mouse line and immunofluorescence analyses on adult mouse CNS sections and glial cell primary cultures. Notably, Elovl5 appears expressed in a region- and cell type-specific manner. Abundant Elovl5-positive cells were found in the cerebellum, brainstem, and primary and accessory olfactory regions, where mitral cells show the most prominent expression. Hippocampal pyramidal cells of CA2/CA3 where also moderately labeled, while in the rest of the telencephalon Elovl5 expression was high in regions related to motor control. Analysis of primary glial cell cultures revealed Elovl5 expression in oligodendroglial cells at various maturation steps and in microglia, while astrocytes showed a heterogeneous in vivo expression of Elovl5. The elucidation of Elovl5 CNS distribution provides relevant information to understand the physiological functions of this enzyme and its PUFA products, whose unbalance is known to be involved in many pathological conditions.

Variable Effects of PD-Risk Associated SNPs and Variants in Parkinsonism-Associated Genes on Disease Phenotype in a Community-Based Cohort

Genetic risk factors for Parkinson's disease (PD) risk and progression have been identified from genome-wide association studies (GWAS), as well as studies of familial forms of PD, implicating common variants at more than 90 loci and pathogenic or likely pathogenic variants at 16 loci. With the goal of understanding whether genetic variants at these PD-risk loci/genes differentially contribute to individual clinical phenotypic characteristics of PD, we used structured clinical documentation tools within the electronic medical record in an effort to provide a standardized and detailed clinical phenotypic characterization at the point of care in a cohort of 856 PD patients. We analyzed common SNPs identified in previous GWAS studies, as well as low-frequency and rare variants at parkinsonism-associated genes in the MDSgene database for their association with individual clinical characteristics and test scores at baseline assessment in our community-based PD patient cohort: age at onset, disease duration, Unified Parkinson's Disease Rating Scale I-VI, cognitive status, initial and baseline motor and non-motor symptoms, complications of levodopa therapy, comorbidities and family history of neurological disease with one or more than one affected family members. We find that in most cases an individual common PD-risk SNP identified in GWAS is associated with only a single clinical feature or test score, while gene-level tests assessing low-frequency and rare variants reveal genes associated in either a unique or partially overlapping manner with the different clinical features and test scores. Protein-protein interaction network analysis of the identified genes reveals that while some of these genes are members of already identified protein networks others are not. These findings indicate that genetic risk factors for PD differentially affect the phenotypic presentation and that genes associated with PD risk are also differentially associated with individual disease phenotypic characteristics at baseline. These findings raise the intriguing possibility that different SNPs/gene effects impact discrete phenotypic characteristics. Furthermore, they support the hypothesis that different gene and protein-protein interaction networks that underlie PD risk, the PD phenotype, and the neurodegenerative process leading to the disease phenotype, and point to the significance of the genetic background on disease phenotype.

Molecular characterization of the stress network in individuals at risk for schizophrenia

The biological mechanisms underlying inter-individual differences in human stress reactivity remain poorly understood. We aimed to identify the molecular underpinning of aberrant neural stress sensitivity in individuals at risk for schizophrenia. Linking mRNA expression data from the Allen Human Brain Atlas to task-based fMRI revealed 201 differentially expressed genes in cortex-specific brain regions differentially activated by stress in individuals with low (healthy siblings of schizophrenia patients) or high (healthy controls) stress sensitivity. These genes are associated with stress-related psychiatric disorders (e.g. schizophrenia and anxiety) and include markers for specific neuronal populations (e.g. ADCYAP1, GABRB1, SSTR1, and TNFRSF12A), neurotransmitter receptors (e.g. GRIN3A, SSTR1, GABRB1, and HTR1E), and signaling factors that interact with the corticosteroid receptor and hypothalamic-pituitary-adrenal axis (e.g. ADCYAP1, IGSF11, and PKIA). Overall, the identified genes potentially underlie altered stress reactivity in individuals at risk for schizophrenia and other psychiatric disorders and play a role in mounting an adaptive stress response in at-risk individuals, making them potentially druggable targets for stress-related diseases.

Tat-Endophilin A1 Fusion Protein Protects Neurons from Ischemic Damage in the Gerbil Hippocampus: A Possible Mechanism of Lipid Peroxidation and Neuroinflammation Mitigation as Well as Synaptic Plasticity

The present study explored the effects of endophilin A1 (SH3GL2) against oxidative damage brought about by H₂O₂ in HT22 cells and ischemic damage induced upon transient forebrain ischemia in gerbils. Tat-SH3GL2 and its control protein (Control-SH3GL2) were synthesized to deliver it to the cells by penetrating the cell membrane and blood–brain barrier. Tat-SH3GL2, but not Control-SH3GL2, could be delivered into HT22 cells in a concentration- and time-dependent manner and the hippocampus 8 h after treatment in gerbils. Tat-SH3GL2 was stably present in HT22 cells and degraded with time, by 36 h post treatment. Pre-incubation with Tat-SH3GL2, but not Control-SH3GL2, significantly ameliorated H₂O₂-induced cell death, DNA fragmentation, and reactive oxygen species formation. SH3GL2 immunoreactivity was decreased in the gerbil hippocampal CA1 region with time after ischemia, but it was maintained in the other regions after ischemia. Tat-SH3GL2 treatment in gerbils appreciably improved ischemia-induced hyperactivity 1 day after ischemia and the percentage of NeuN-immunoreactive surviving cells increased 4 days after ischemia. In addition, Tat-SH3GL2 treatment in gerbils alleviated the increase in lipid peroxidation as assessed by the levels of malondialdehyde and 8-iso-prostaglandin F2α and in pro-inflammatory cytokines such as tumor necrosis factor-α, interleukin-1β, and interleukin-6; while the reduction of protein levels in markers for synaptic plasticity, such as postsynaptic density 95, synaptophysin, and synaptosome associated protein 25 after transient forebrain ischemia was also observed. These results suggest that Tat-SH3GL2 protects neurons from oxidative and ischemic damage by reducing lipid peroxidation and inflammation and improving synaptic plasticity after ischemia.

Stem-cell-derived human microglia transplanted into mouse brain to study human disease

Microglia are critically involved in complex neurological disorders with a strong genetic component, such as Alzheimer's disease, Parkinson's disease and frontotemporal dementia. Although mouse microglia can recapitulate aspects of human microglia physiology, they do not fully capture the human genetic aspects of disease and do not reproduce all human cell states. Primary cultures of human microglia or microglia derived from human induced pluripotent stem cells (PSCs) are difficult to maintain in brain-relevant cell states in vitro. Here we describe MIGRATE (microglia in vitro generation refined for advanced transplantation experiments, which provides a combined in vitro differentiation and in vivo xenotransplantation protocol to study human microglia in the context of the mouse brain. This article details an accurate, step-by-step workflow that includes in vitro microglia differentiation from human PSCs, transplantation into the mouse brain and quantitative analysis of engraftment. Compared to current differentiation and xenotransplantation protocols, we present an optimized, faster and more efficient approach that yields up to 80% chimerism. To quantitatively assess engraftment efficiency by flow cytometry, access to specialized flow cytometry is required. Alternatively, the percentage of chimerism can be estimated by standard immunohistochemical analysis. The MIGRATE protocol takes ~40 d to complete, from culturing PSCs to engraftment efficiency assessment.

Parkinson's Disease Subtypes: Critical Appraisal and Recommendations

BACKGROUND

In Parkinson's disease (PD), there is heterogeneity in the clinical presentation and underlying biology. Research on PD subtypes aims to understand this heterogeneity with potential contribution for the knowledge of disease pathophysiology, natural history and therapeutic development. There have been many studies of PD subtypes but their impact remains unclear with limited application in research or clinical practice.

OBJECTIVE

To critically evaluate PD subtyping systems.

METHODS

We conducted a systematic review of PD subtypes, assessing the characteristics of the studies reporting a subtyping system for the first time. We completed a critical appraisal of their methodologic quality and clinical applicability using standardized checklists.

RESULTS

We included 38 studies. The majority were cross-sectional (n = 26, 68.4%), used a data-driven approach (n = 25, 65.8%), and non-clinical biomarkers were rarely used (n = 5, 13.1%). Motor characteristics were the domain most commonly reported to differentiate PD subtypes. Most of the studies did not achieve the top rating across items of a Methodologic Quality checklist. In a Clinical Applicability Checklist, the clinical importance of differences between subtypes, potential treatment implications and applicability to the general population were rated poorly, and subtype stability over time and prognostic value were largely unknown.

CONCLUSION

Subtyping studies undertaken to date have significant methodologic shortcomings and most have questionable clinical applicability and unknown biological relevance. The clinical and biological signature of PD may be unique to the individual, rendering PD resistant to meaningful cluster solutions. New approaches that acknowledge the individual-level heterogeneity and that are more aligned with personalized medicine are needed.

Imaging Transcriptomics in Neurodegenerative Diseases

Imaging transcriptomics investigates the relationship between neuroanatomical/neuroimaging features and gene expression. The spatial and temporal distribution of the expressed genes and their pattern of spreading over time can contribute to elucidating cellular and molecular processes involved in neurodegeneration. In this study, we review recent findings regarding the correlation between neuroimaging and expression data in neurodegenerative diseases with a focus on Alzheimer's disease and Parkinson's disease. An association between gene expression data and different neuroimaging neurodegeneration features, such as R2 relaxation time and volumetric cortical atrophy, was established. Several positive and negative expression correlations were identified, and they confirmed the focal nature of neurodegeneration. Positively correlated genes were associated with cell motility, immune system activity, neuroinflammation, and microglia. Data from connectome studies support the hypothesis of selective network vulnerability and a temporal spreading pattern in neurodegenerative pathologies. Genes related to cellular mobility and transport are overexpressed in the neuroimaging-defined delineated areas of degeneration. In addition, expression enrichment of genes involved in immunological processes in vulnerable regions-such as the Toll-like receptor, a receptor involved in innate immunity-plays a major role in neuroinflammation in neurodegenerative diseases. However, substantial limitations must be overcome in future studies: the lack of high-quality resolution expression data, the lack of standardized study protocols, and insufficient sensitive early stage neuroimaging markers of degeneration. Identifying neuroimaging and expression prodromal biomarkers and investigating their causal relation in the preclinical disease stage may enable early targeted therapy before the onset of irreversible brain changes.

Differences in network controllability and regional gene expression underlie hallucinations in Parkinson's disease

Visual hallucinations are common in Parkinson's disease and are associated with poorer prognosis. Imaging studies show white matter loss and functional connectivity changes with Parkinson's visual hallucinations, but the biological factors underlying selective vulnerability of affected parts of the brain network are unknown. Recent models for Parkinson's disease hallucinations suggest they arise due to a shift in the relative effects of different networks. Understanding how structural connectivity affects the interplay between networks will provide important mechanistic insights. To address this, we investigated the structural connectivity changes that accompany visual hallucinations in Parkinson's disease and the organizational and gene expression characteristics of the preferentially affected areas of the network. We performed diffusion-weighted imaging in 100 patients with Parkinson's disease (81 without hallucinations, 19 with visual hallucinations) and 34 healthy age-matched controls. We used network-based statistics to identify changes in structural connectivity in Parkinson's disease patients with hallucinations and performed an analysis of controllability, an emerging technique that allows quantification of the influence a brain region has across the rest of the network. Using these techniques, we identified a subnetwork of reduced connectivity in Parkinson's disease hallucinations. We then used the Allen Institute for Brain Sciences human transcriptome atlas to identify regional gene expression patterns associated with affected areas of the network. Within this network, Parkinson's disease patients with hallucinations showed reduced controllability (less influence over other brain regions), than Parkinson's disease patients without hallucinations and controls. This subnetwork appears to be critical for overall brain integration, as even in controls, nodes with high controllability were more likely to be within the subnetwork. Gene expression analysis of gene modules related to the affected subnetwork revealed that down-weighted genes were most significantly enriched in genes related to mRNA and chromosome metabolic processes (with enrichment in oligodendrocytes) and upweighted genes to protein localization (with enrichment in neuronal cells). Our findings provide insights into how hallucinations are generated, with breakdown of a key structural subnetwork that exerts control across distributed brain regions. Expression of genes related to mRNA metabolism and membrane localization may be implicated, providing potential therapeutic targets.

Interferon-γ signaling synergizes with LRRK2 in neurons and microglia derived from human induced pluripotent stem cells

Parkinson's disease-associated kinase LRRK2 has been linked to IFN type II (IFN-γ) response in infections and to dopaminergic neuronal loss. However, whether and how LRRK2 synergizes with IFN-γ remains unclear. In this study, we employed dopaminergic neurons and microglia differentiated from patient-derived induced pluripotent stem cells carrying LRRK2 G2019S, the most common Parkinson's disease-associated mutation. We show that IFN-γ enhances the LRRK2 G2019S-dependent negative regulation of AKT phosphorylation and NFAT activation, thereby increasing neuronal vulnerability to immune challenge. Mechanistically, LRRK2 G2019S suppresses NFAT translocation via calcium signaling and possibly through microtubule reorganization. In microglia, LRRK2 modulates cytokine production and the glycolytic switch in response to IFN-γ in an NFAT-independent manner. Activated LRRK2 G2019S microglia cause neurite shortening, indicating that LRRK2-driven immunological changes can be neurotoxic. We propose that synergistic LRRK2/IFN-γ activation serves as a potential link between inflammation and neurodegeneration in Parkinson's disease.

Genetic Risk Profiling in Parkinson's Disease and Utilizing Genetics to Gain Insight into Disease-Related Biological Pathways

Parkinson's disease (PD) is a complex disorder underpinned by both environmental and genetic factors. The latter only began to be understood around two decades ago, but since then great inroads have rapidly been made into deconvoluting the genetic component of PD. In particular, recent large-scale projects such as genome-wide association (GWA) studies have provided insight into the genetic risk factors associated with genetically ''complex'' PD (PD that cannot readily be attributed to single deleterious mutations). Here, we discuss the plethora of genetic information provided by PD GWA studies and how this may be utilized to generate polygenic risk scores (PRS), which may be used in the prediction of risk and trajectory of PD. We also comment on how pathway-specific genetic profiling can be used to gain insight into PD-related biological pathways, and how this may be further utilized to nominate causal PD genes and potentially druggable therapeutic targets. Finally, we outline the current limits of our understanding of PD genetics and the potential contribution of variation currently uncaptured in genetic studies, focusing here on uncatalogued structural variants.