Deep sequencing of proteotoxicity modifier genes uncovers a Presenilin-2/beta-amyloid-actin genetic risk module shared among alpha-synucleinopathies.

Whether neurodegenerative diseases linked to misfolding of the same protein share genetic risk drivers or whether different protein-aggregation pathologies in neurodegeneration are mechanistically related remains uncertain. Conventional genetic analyses are underpowered to address these questions. Through careful selection of patients based on protein aggregation phenotype (rather than clinical diagnosis) we can increase statistical power to detect associated variants in a targeted set of genes that modify proteotoxicities. Genetic modifiers of alpha-synuclein (ɑS) and beta-amyloid (Aß) cytotoxicity in yeast are enriched in risk factors for Parkinson's disease (PD) and Alzheimer's disease (AD), respectively. Here, along with known AD/PD risk genes, we deeply sequenced exomes of 430 ɑS/Aß modifier genes in patients across alpha-synucleinopathies (PD, Lewy body dementia and multiple system atrophy). Beyond known PD genes GBA1 and LRRK2, rare variants AD genes (CD33, CR1 and PSEN2) and Aß toxicity modifiers involved in RhoA/actin cytoskeleton regulation (ARGHEF1, ARHGEF28, MICAL3, PASK, PKN2, PSEN2) were shared risk factors across synucleinopathies. Actin pathology occurred in iPSC synucleinopathy models and RhoA downregulation exacerbated ɑS pathology. Even in sporadic PD, the expression of these genes was altered across CNS cell types. Genome-wide CRISPR screens revealed the essentiality of PSEN2 in both human cortical and dopaminergic neurons, and PSEN2 mutation carriers exhibited diffuse brainstem and cortical synucleinopathy independent of AD pathology. PSEN2 contributes to a common-risk signal in PD GWAS and regulates ɑS expression in neurons. Our results identify convergent mechanisms across synucleinopathies, some shared with AD.

Identification of 27 allele-specific regulatory variants in Parkinson's disease using a massively parallel reporter assay.

Genome wide association studies (GWAS) have identified a number of genomic loci that are associated with Parkinson's disease (PD) risk. However, the majority of these variants lie in non-coding regions, and thus the mechanisms by which they influence disease development, and/or potential subtypes, remain largely elusive. To address this, we used a massively parallel reporter assay (MPRA) to screen the regulatory function of 5254 variants that have a known or putative connection to PD. We identified 138 loci with enhancer activity, of which 27 exhibited allele-specific regulatory activity in HEK293 cells. The identified regulatory variant(s) typically did not match the original tag variant within the PD associated locus, supporting the need for deeper exploration of these loci. The existence of allele specific transcriptional impacts within HEK293 cells, confirms that at least a subset of the PD associated regions mark functional gene regulatory elements. Future functional studies that confirm the putative targets of the empirically verified regulatory variants will be crucial for gaining a greater understanding of how gene regulatory network(s) modulate PD risk.

Discovering genetic mechanisms underlying the co-occurrence of Parkinson's disease and non-motor traits.

Understanding the biological mechanisms that underlie the non-motor symptoms of Parkinson's disease (PD) requires comprehensive frameworks that unravel the complex interplay of genetic risk factors. Here, we used a disease-agnostic brain cortex gene regulatory network integrated with Mendelian Randomization analyses that identified 19 genes whose changes in expression were causally linked to PD. We further used the network to identify genes that are regulated by PD-associated genome-wide association study (GWAS) SNPs. Extended protein interaction networks derived from PD-risk genes and PD-associated SNPs identified convergent impacts on biological pathways and phenotypes, connecting PD with established co-occurring traits, including non-motor symptoms. These findings hold promise for therapeutic development. In conclusion, while distinct sets of genes likely influence PD risk and outcomes, the existence of genes in common and intersecting pathways associated with other traits suggests that they may contribute to both increased PD risk and symptom heterogeneity observed in people with Parkinson's.

Parkinson's disease: From genetics to molecular dysfunction and targeted therapeutic approaches.

Parkinson's disease (PD) is the most common neurodegenerative movement disorder in the elderly. As the pathogenesis of PD is still not fully understood, medications with the capacity of halting the disease progression are currently unavailable. The discovery of genes that are causative for, or increase susceptibility to PD is pivotal for the development of novel therapeutic approaches, as they are critical for the onset of PD and the molecular pathways underlying its pathogenesis. By reviewing relevant data, we discuss causative genes, and those associated with PD susceptibility and quantitative traits. Through Gene Ontology database and STRING analysis, we emphasize the roles of inorganic cation transmembrane transport pathways and hypothalamic pituitary thyroid axis, in addition to the established roles of inflammation/oxidative stress and mitochondrial dysfunction in the pathogenesis of PD. It is hoped these insights 1) untangle the clinical complex presentations of PD, 2) reveal the interwoven molecular network leading to PD, and 3) identify critical molecular targets to facilitate novel PD drug discovery, with a view to providing improved consultation and personalized medicine for patients with PD in the future.

Evaluation of plasma levels of NFL, GFAP, UCHL1 and tau as Parkinson's disease biomarkers using multiplexed single molecule counting.

Objective biomarkers for Parkinson's Disease (PD) could aid early and specific diagnosis, effective monitoring of disease progression, and improved design and interpretation of clinical trials. Although alpha-synuclein remains a biomarker candidate of interest, the multifactorial and heterogenous nature of PD highlights the need for a PD biomarker panel. Ideal biomarker candidates include markers that are detectable in easily accessible samples, (ideally blood) and that reflect the underlying pathological process of PD. In the present study, we explored the diagnostic and prognostic PD biomarker potential of the SIMOA neurology 4-plex-A biomarker panel, which included neurofilament light (NFL), glial fibrillary acid protein (GFAP), tau and ubiquitin C-terminal hydrolase L1 (UCHL-1). We initially performed a serum vs plasma comparative study to determine the most suitable blood-based matrix for the measurement of these proteins in a multiplexed assay. The levels of NFL and GFAP in plasma and serum were highly correlated (Spearman rho-0.923, p < 0.0001 and rho = 0.825, p < 0.001 respectively). In contrast, the levels of tau were significantly higher in plasma compared to serum samples (p < 0.0001) with no correlation between sample type (Spearman p > 0.05). The neurology 4-plex-A panel, along with plasma alpha-synuclein was then assessed in a cross-sectional cohort of 29 PD patients and 30 controls. Plasma NFL levels positively correlated with both GFAP and alpha-synuclein levels (rho = 0.721, p < 0.0001 and rho = 0.390, p < 0.05 respectively). As diagnostic biomarkers, the control and PD groups did not differ in their mean NFL, GFAP, tau or UCHL-1 plasma levels (t test p > 0.05). As disease state biomarkers, motor severity (MDS-UPDRS III) correlated with increased NFL (rho = 0.646, p < 0.0001), GFAP (rho = 0.450, p < 0.05) and alpha-synuclein levels (rho = 0.406, p < 0.05), while motor stage (Hoehn and Yahr) correlated with increased NFL (rho = 0.455, p < 0.05) and GFAP (rho = 0.549, p < 0.01) but not alpha-synuclein levels (p > 0.05). In conclusion, plasma was determined to be most suitable blood-based matrix for multiplexing the neurology 4-plex-A panel. Given their correlation with motor features of PD, NFL and GFAP appear to be promising disease state biomarker candidates and further longitudinal validation of these two proteins as blood-based biomarkers for PD progression is warranted.

Identifying robust and reliable volatile organic compounds in human sebum for biomarker discovery.

Sebum from sebaceous glands is a rich source of volatile organic compounds (VOCs) that can readily be sampled non-invasively from the surface of skin. The VOC profiles of sebum can then be used to obtain information regarding different medical conditions including diabetes and Parkinson's Disease. However, the effects of sampling approaches and environmental factors on sebum VOC profiles are not established and the confident attribution of VOCs to disease states needs to be free of extraneous influences such as sampling materials and preparatory conditions. Here, we investigated a more standardised skin swab sampling approach for profiling sebum VOCs from healthy human subjects using thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). Using a standard GC-MS method for the chemical analysis of sebum swabs, a surprisingly high number of VOCs originate from 'blank' medical swab material alone (up to 74 VOCs) and from the ambient environment (up to 29 VOCs) based on control experiments. We found that heat-treatment of medical swabs prior to GC-MS reduced the number of VOCs detected from 'blank' swabs and improved the reproducibility of VOC profiling, however significant VOC absorption can still occur from environmental exposure to ambient air. VOCs identified in 'blank' swabs consisted predominantly of hydrocarbons, esters, and silicon-based compounds and depended strongly on the material used (cotton and polyester-rayon). Environmental VOCs found to absorb to swabs from the ambient air during sampling included 1-butylheptyl-benzene and hexadecanoic acid methyl ester as well as exogenous VOCs such as isopropyl palmitate and isopropyl myristate. In contrast, sebum VOCs consisted primarily of esters, alcohols, ketones, and aldehydes. 23 and 18 VOCs were identified in sebum collected using polyester-rayon and cotton-based medical swabs, respectively, with 14 VOCs common to both swabs. The effect of subject bathing prior to sebum sampling had minimal impact on the VOC profiles. However, individual differences owing to external factors such as skin type, diet, and exercise will likely influence sebum production. This study highlights the importance of using rigorous controls in sebum sampling, and recommendations are provided for future research involving sebum VOC analysis. For example, the use of sebum sample replicates across multiple days, and the use of control swabs during sample collection is required to confirm the origin and reliability of sebum VOCs. It is anticipated that these recommendations in conjunction with a library of well-established VOCs from medical swabs will further strengthen biomarker identification resulting from sebum VOC analysis.

Redefining the hypotheses driving Parkinson's diseases research.

Parkinson's disease (PD) research has largely focused on the disease as a single entity centred on the development of neuronal pathology within the central nervous system. However, there is growing recognition that PD is not a single entity but instead reflects multiple diseases, in which different combinations of environmental, genetic and potential comorbid factors interact to direct individual disease trajectories. Moreover, an increasing body of recent research implicates peripheral tissues and non-neuronal cell types in the development of PD. These observations are consistent with the hypothesis that the initial causative changes for PD development need not occur in the central nervous system. Here, we discuss how the use of neuronal pathology as a shared, qualitative phenotype minimises insights into the possibility of multiple origins and aetiologies of PD. Furthermore, we discuss how considering PD as a single entity potentially impairs our understanding of the causative molecular mechanisms, approaches for patient stratification, identification of biomarkers, and the development of therapeutic approaches to PD. The clear consequence of there being distinct diseases that collectively form PD, is that there is no single biomarker or treatment for PD development or progression. We propose that diagnosis should shift away from the clinical definitions, towards biologically defined diseases that collectively form PD, to enable informative patient stratification. N-of-one type, clinical designs offer an unbiased, and agnostic approach to re-defining PD in terms of a group of many individual diseases.

Single Molecule Fingerprinting Reveals Different Amplification Properties of α-Synuclein Oligomers and Preformed Fibrils in Seeding Assay.

The quantification of α-synuclein aggregates has emerged as a promising biomarker for synucleinopathies. Assays that amplify and detect such aggregates have revealed the presence of seeding-competent species in biosamples of patients diagnosed with Parkinson's disease. However, multiple species, such as oligomers and amyloid fibrils, are formed during the aggregation of α-synuclein; these species are likely to coexist in biological samples, and thus it remains unclear which species(s) are contributing to the signal detected in seeding assays. To identify individual contributions to the amplification process, recombinant oligomers and preformed fibrils were produced and purified to characterize their individual biochemical and seeding potential. Here, we used single molecule spectroscopy to track the formation and purification of oligomers and fibrils at the single particle level and compare their respective seeding potential in an amplification assay. Single molecule detection validates that size-exclusion chromatography efficiently separates oligomers from fibrils. Oligomers were found to be seeding-competent, but our results reveal that their seeding behavior is very different compared to that of preformed fibrils, in our amplification assay. Overall, our data suggest that even a low number of preformed fibrils present in biosamples is likely to dominate the response in seeding assays.

Establishing gene regulatory networks from Parkinson's disease risk loci.

The latest meta-analysis of genome-wide association studies identified 90 independent variants across 78 genomic regions associated with Parkinson's disease, yet the mechanisms by which these variants influence the development of the disease remains largely elusive. To establish the functional gene regulatory networks associated with Parkinson's disease risk variants, we utilized an approach combining spatial (chromosomal conformation capture) and functional (expression quantitative trait loci) data. We identified 518 genes subject to regulation by 76 Parkinson's variants across 49 tissues, whicih encompass 36 peripheral and 13 CNS tissues. Notably, one-third of these genes were regulated via trans-acting mechanisms (distal; risk locus-gene separated by >1 Mb, or on different chromosomes). Of particular interest is the identification of a novel trans-expression quantitative trait loci-gene connection between rs10847864 and SYNJ1 in the adult brain cortex, highlighting a convergence between familial studies and Parkinson's disease genome-wide association studies loci for SYNJ1 (PARK20) for the first time. Furthermore, we identified 16 neurodevelopment-specific expression quantitative trait loci-gene regulatory connections within the foetal cortex, consistent with hypotheses suggesting a neurodevelopmental involvement in the pathogenesis of Parkinson's disease. Through utilizing Louvain clustering we extracted nine significant and highly intraconnected clusters within the entire gene regulatory network. The nine clusters are enriched for specific biological processes and pathways, some of which have not previously been associated with Parkinson's disease. Together, our results not only contribute to an overall understanding of the mechanisms and impact of specific combinations of Parkinson's disease variants, but also highlight the potential impact gene regulatory networks may have when elucidating aetiological subtypes of Parkinson's disease.

Defining early changes in Alzheimer's disease from RNA sequencing of brain regions differentially affected by pathology.

Tau pathology in Alzheimer's disease (AD) spreads in a predictable pattern that corresponds with disease symptoms and severity. At post-mortem there are cortical regions that range from mildly to severely affected by tau pathology and neuronal loss. A comparison of the molecular signatures of these differentially affected areas within cases and between cases and controls may allow the temporal modelling of disease progression. Here we used RNA sequencing to explore differential gene expression in the mildly affected primary visual cortex and moderately affected precuneus of ten age-, gender- and RNA quality-matched post-mortem brains from AD patients and healthy controls. The two regions in AD cases had similar transcriptomic signatures but there were broader abnormalities in the precuneus consistent with the greater tau load. Both regions were characterised by upregulation of immune-related genes such as those encoding triggering receptor expressed on myeloid cells 2 and membrane spanning 4-domains A6A and milder changes in insulin/IGF1 signalling. The precuneus in AD was also characterised by changes in vesicle secretion and downregulation of the interneuronal subtype marker, somatostatin. The 'early' AD transcriptome is characterised by perturbations in synaptic vesicle secretion on a background of neuroimmune dysfunction. In particular, the synaptic deficits that characterise AD may begin with the somatostatin division of inhibitory neurotransmission.

Machine Learning Identifies Six Genetic Variants and Alterations in the Heart Atrial Appendage as Key Contributors to PD Risk Predictivity.

Parkinson's disease (PD) is a complex neurodegenerative disease with a range of causes and clinical presentations. Over 76 genetic loci (comprising 90 SNPs) have been associated with PD by the most recent GWAS meta-analysis. Most of these PD-associated variants are located in non-coding regions of the genome and it is difficult to understand what they are doing and how they contribute to the aetiology of PD. We hypothesised that PD-associated genetic variants modulate disease risk through tissue-specific expression quantitative trait loci (eQTL) effects. We developed and validated a machine learning approach that integrated tissue-specific eQTL data on known PD-associated genetic variants with PD case and control genotypes from the Wellcome Trust Case Control Consortium. In so doing, our analysis ranked the tissue-specific transcription effects for PD-associated genetic variants and estimated their relative contributions to PD risk. We identified roles for SNPs that are connected with INPP5P, CNTN1, GBA and SNCA in PD. Ranking the variants and tissue-specific eQTL effects contributing most to the machine learning model suggested a key role in the risk of developing PD for two variants (rs7617877 and rs6808178) and eQTL associated transcriptional changes of EAF1-AS1 within the heart atrial appendage. Similarly, effects associated with eQTLs located within the Brain Cerebellum were also recognized to confer major PD risk. These findings were replicated in two additional, independent cohorts (the UK Biobank, and NeuroX) and thus warrant further mechanistic investigations to determine if these transcriptional changes could act as early contributors to PD risk and disease development.

Common Variants Coregulate Expression of GBA and Modifier Genes to Delay Parkinson's Disease Onset.

BACKGROUND: GBA mutations are numerically the most significant genetic risk factor for Parkinson's disease (PD), yet these mutations have low penetrance, suggesting additional mechanisms. OBJECTIVES: The objective of this study was to determine if the penetrance of GBA in PD can be explained by regulatory effects on GBA and modifier genes. METHODS: Genetic variants associated with the regulation of GBA were identified by screening 128 common single nucleotide polymorphisms (SNPs) in the GBA locus for spatial cis-expression quantitative trail locus (supported by chromatin interactions). RESULTS: We identified common noncoding SNPs within GBA that (1) regulate GBA expression in peripheral tissues, some of which display α-synuclein pathology and (2) coregulate potential modifier genes in the central nervous system and/or peripheral tissues. Haplotypes based on 3 of these SNPs delay disease onset by 5 years. In addition, SNPs on 6 separate chromosomes coregulate GBA expression specifically in either the substantia nigra or cortex, and their combined effect potentially modulates motor and cognitive symptoms, respectively. CONCLUSIONS: This work provides a new perspective on the haplotype-specific effects of GBA and the genetic etiology of PD, expanding the role of GBA from the gene encoding the ß-glucocerebrosidase (GCase) to that of a central regulator and modifier of PD onset, with GBA expression itself subject to distant regulation. Some idiopathic patients might possess insufficient GBA-encoded GCase activity in the substantia nigra as the result of distant regulatory variants and therefore might benefit from GBA-targeting therapeutics. The SNPs' regulatory impacts provide a plausible explanation for the variable phenotypes also observed in GBA-centric Gaucher's disease and dementia with Lewy bodies. © 2020 The Authors. Movement Disorders published by Wiley Periodicals, LLC on behalf of International Parkinson and Movement Disorder Society.

Regulation of mitochondrial metabolism in murine skeletal muscle by the medium-chain fatty acid receptor Gpr84.

Fatty acid receptors have been recognized as important players in glycaemic control. This study is the first to describe a role for the medium-chain fatty acid (MCFA) receptor G-protein-coupled receptor (Gpr) 84 in skeletal muscle mitochondrial function and insulin secretion. We are able to show that Gpr84 is highly expressed in skeletal muscle and adipose tissue. Mice with global deletion of Gpr84 [Gpr84 knockout (KO)] exhibit a mild impairment in glucose tolerance when fed a MCFA-enriched diet. Studies in mice and pancreatic islets suggest that glucose intolerance is accompanied by a defect in insulin secretion. MCFA-fed KO mice also exhibit a significant impairment in the intrinsic respiratory capacity of their skeletal muscle mitochondria, but at the same time also exhibit a substantial increase in mitochondrial content. Changes in canonical pathways of mitochondrial biogenesis and turnover are unable to explain these mitochondrial differences. Our results show that Gpr84 plays a crucial role in regulating mitochondrial function and quality control.-Montgomery, M. K., Osborne, B., Brandon, A. E., O'Reilly, L., Fiveash, C. E., Brown, S. H. J., Wilkins, B. P., Samsudeen, A., Yu, J., Devanapalli, B., Hertzog, A., Tolun, A. A., Kavanagh, T., Cooper, A. A., Mitchell, T. W., Biden, T. J., Smith, N. J., Cooney, G. J., Turner, N. Regulation of mitochondrial metabolism in murine skeletal muscle by the medium-chain fatty acid receptor Gpr84.

Publisher Correction: Enhancers active in dopamine neurons are a primary link between genetic variation and neuropsychiatric disease.

In the version of this article initially published, the legends for Supplementary Figs. 4-8 and 10-14 contained errors. The Supplementary Figure legends have been corrected in the HTML and PDF versions of the article.

Enhancers active in dopamine neurons are a primary link between genetic variation and neuropsychiatric disease.

Enhancers function as DNA logic gates and may control specialized functions of billions of neurons. Here we show a tailored program of noncoding genome elements active in situ in physiologically distinct dopamine neurons of the human brain. We found 71,022 transcribed noncoding elements, many of which were consistent with active enhancers and with regulatory mechanisms in zebrafish and mouse brains. Genetic variants associated with schizophrenia, addiction, and Parkinson's disease were enriched in these elements. Expression quantitative trait locus analysis revealed that Parkinson's disease-associated variants on chromosome 17q21 cis-regulate the expression of an enhancer RNA in dopamine neurons. This study shows that enhancers in dopamine neurons link genetic variation to neuropsychiatric traits.

Lysosomal-associated membrane protein 2 isoforms are differentially affected in early Parkinson's disease.

Lysosomes are the primary catabolic compartment for the degradation of intracellular proteins through autophagy. The presence of abnormal intracellular α-synuclein-positive aggregates in Parkinson's disease (PD) indicates that the degradative capacity of lysosomes is impaired in PD. Specific dysfunction of chaperone-mediated autophagy (CMA) in PD is suggested by reductions in the CMA membrane receptor, lysosomal-associated membrane protein (LAMP) 2A, although whether LAMP2A is the only LAMP2 isoform affected by PD is unknown. Messenger RNA (mRNA) and protein expression of all three LAMP2 isoforms was assessed in brain extracts from regions with and without PD-related increases in α-synuclein in autopsy samples from subjects in the early pathological stage of PD (n = 9), compared to age- and postmortem delay-matched controls (n = 10). In the early stages of PD, mRNA expression of all LAMP2 isoforms was not different from controls, with LAMP2B and LAMP2C protein levels also unchanged in PD. The selective loss of LAMP2A protein directly correlated with the increased levels of α-synuclein and decreased levels of the CMA chaperone heat shock cognate protein 70 in the same PD samples, as well as with the accumulation of cytosolic CMA substrate proteins. Our data show that LAMP2 protein isoforms are differentially affected in the early stages of PD, with LAMP2A selectively reduced in association with increased α-synuclein, and suggests that dysregulation of CMA-mediated protein degradation occurs before substantial α-synuclein aggregation in PD.