A contact binary satellite of the asteroid (152830) Dinkinesh.

Asteroids with diameters less than about 5 km have complex histories because they are small enough for radiative torques (that is, YORP, short for the Yarkovsky-O'Keefe-Radzievskii-Paddack effect)1 to be a notable factor in their evolution2. (152830) Dinkinesh is a small asteroid orbiting the Sun near the inner edge of the main asteroid belt with a heliocentric semimajor axis of 2.19 AU; its S-type spectrum3,4 is typical of bodies in this part of the main belt5. Here we report observations by the Lucy spacecraft6,7 as it passed within 431 km of Dinkinesh. Lucy revealed Dinkinesh, which has an effective diameter of only 720 m, to be unexpectedly complex. Of particular note is the presence of a prominent longitudinal trough overlain by a substantial equatorial ridge and the discovery of the first confirmed contact binary satellite, now named (152830) Dinkinesh I Selam. Selam consists of two near-equal-sized lobes with diameters of 210 m and 230 m. It orbits Dinkinesh at a distance of 3.1 km with an orbital period of about 52.7 h and is tidally locked. The dynamical state, angular momentum and geomorphologic observations of the system lead us to infer that the ridge and trough of Dinkinesh are probably the result of mass failure resulting from spin-up by YORP followed by the partial reaccretion of the shed material. Selam probably accreted from material shed by this event.

Genome-wide analyses reveal a potential role for the MAPT, MOBP, and APOE loci in sporadic frontotemporal dementia.

Frontotemporal dementia (FTD) is the second most common cause of early-onset dementia after Alzheimer disease (AD). Efforts in the field mainly focus on familial forms of disease (fFTDs), while studies of the genetic etiology of sporadic FTD (sFTD) have been less common. In the current work, we analyzed 4,685 sFTD cases and 15,308 controls looking for common genetic determinants for sFTD. We found a cluster of variants at the MAPT (rs199443; p = 2.5 × 10-12, OR = 1.27) and APOE (rs6857; p = 1.31 × 10-12, OR = 1.27) loci and a candidate locus on chromosome 3 (rs1009966; p = 2.41 × 10-8, OR = 1.16) in the intergenic region between RPSA and MOBP, contributing to increased risk for sFTD through effects on expression and/or splicing in brain cortex of functionally relevant in-cis genes at the MAPT and RPSA-MOBP loci. The association with the MAPT (H1c clade) and RPSA-MOBP loci may suggest common genetic pleiotropy across FTD and progressive supranuclear palsy (PSP) (MAPT and RPSA-MOBP loci) and across FTD, AD, Parkinson disease (PD), and cortico-basal degeneration (CBD) (MAPT locus). Our data also suggest population specificity of the risk signals, with MAPT and APOE loci associations mainly driven by Central/Nordic and Mediterranean Europeans, respectively. This study lays the foundations for future work aimed at further characterizing population-specific features of potential FTD-discriminant APOE haplotype(s) and the functional involvement and contribution of the MAPT H1c haplotype and RPSA-MOBP loci to pathogenesis of sporadic forms of FTD in brain cortex.

MIR-NATs repress MAPT translation and aid proteostasis in neurodegeneration.

The human genome expresses thousands of natural antisense transcripts (NAT) that can regulate epigenetic state, transcription, RNA stability or translation of their overlapping genes1,2. Here we describe MAPT-AS1, a brain-enriched NAT that is conserved in primates and contains an embedded mammalian-wide interspersed repeat (MIR), which represses tau translation by competing for ribosomal RNA pairing with the MAPT mRNA internal ribosome entry site3. MAPT encodes tau, a neuronal intrinsically disordered protein (IDP) that stabilizes axonal microtubules. Hyperphosphorylated, aggregation-prone tau forms the hallmark inclusions of tauopathies4. Mutations in MAPT cause familial frontotemporal dementia, and common variations forming the MAPT H1 haplotype are a significant risk factor in many tauopathies5 and Parkinson's disease. Notably, expression of MAPT-AS1 or minimal essential sequences from MAPT-AS1 (including MIR) reduces-whereas silencing MAPT-AS1 expression increases-neuronal tau levels, and correlate with tau pathology in human brain. Moreover, we identified many additional NATs with embedded MIRs (MIR-NATs), which are overrepresented at coding genes linked to neurodegeneration and/or encoding IDPs, and confirmed MIR-NAT-mediated translational control of one such gene, PLCG1. These results demonstrate a key role for MAPT-AS1 in tauopathies and reveal a potentially broad contribution of MIR-NATs to the tightly controlled translation of IDPs6, with particular relevance for proteostasis in neurodegeneration.

Tissue specific LRRK2 interactomes reveal a distinct striatal functional unit.

Mutations in LRRK2 are the most common genetic cause of Parkinson's disease. Despite substantial research efforts, the physiological and pathological role of this multidomain protein remains poorly defined. In this study, we used a systematic approach to construct the general protein-protein interactome around LRRK2, which was then evaluated taking into consideration the differential expression patterns and the co-expression behaviours of the LRRK2 interactors in 15 different healthy tissue types. The LRRK2 interactors exhibited distinct expression features in the brain as compared to the peripheral tissues analysed. Moreover, a high degree of similarity was found for the LRRK2 interactors in putamen, caudate and nucleus accumbens, thus defining a potential LRRK2 functional cluster within the striatum. The general LRRK2 interactome paired with the expression profiles of its members constitutes a powerful tool to generate tissue-specific LRRK2 interactomes. We exemplified the generation of the tissue-specific LRRK2 interactomes and explored the functions highlighted by the "core LRRK2 interactors" in the striatum in comparison with the cerebellum. Finally, we illustrated how the LRRK2 general interactome reported in this manuscript paired with the expression profiles can be used to trace the relationship between LRRK2 and specific interactors of interest, here focusing on the LRRK2 interactors belonging to the Rab protein family.

Genetic topography and cortical cell loss in Huntington's disease link development and neurodegeneration.

Cortical cell loss is a core feature of Huntington's disease (HD), beginning many years before clinical motor diagnosis, during the premanifest stage. However, it is unclear how genetic topography relates to cortical cell loss. Here, we explore the biological processes and cell types underlying this relationship and validate these using cell-specific post-mortem data. Eighty premanifest participants on average 15 years from disease onset and 71 controls were included. Using volumetric and diffusion MRI we extracted HD-specific whole brain maps where lower grey matter volume and higher grey matter mean diffusivity, relative to controls, were used as proxies of cortical cell loss. These maps were combined with gene expression data from the Allen Human Brain Atlas (AHBA) to investigate the biological processes relating genetic topography and cortical cell loss. Cortical cell loss was positively correlated with the expression of developmental genes (i.e. higher expression correlated with greater atrophy and increased diffusivity) and negatively correlated with the expression of synaptic and metabolic genes that have been implicated in neurodegeneration. These findings were consistent for diffusion MRI and volumetric HD-specific brain maps. As wild-type huntingtin is known to play a role in neurodevelopment, we explored the association between wild-type huntingtin (HTT) expression and developmental gene expression across the AHBA. Co-expression network analyses in 134 human brains free of neurodegenerative disorders were also performed. HTT expression was correlated with the expression of genes involved in neurodevelopment while co-expression network analyses also revealed that HTT expression was associated with developmental biological processes. Expression weighted cell-type enrichment (EWCE) analyses were used to explore which specific cell types were associated with HD cortical cell loss and these associations were validated using cell specific single nucleus RNAseq (snRNAseq) data from post-mortem HD brains. The developmental transcriptomic profile of cortical cell loss in preHD was enriched in astrocytes and endothelial cells, while the neurodegenerative transcriptomic profile was enriched for neuronal and microglial cells. Astrocyte-specific genes differentially expressed in HD post-mortem brains relative to controls using snRNAseq were enriched in the developmental transcriptomic profile, while neuronal and microglial-specific genes were enriched in the neurodegenerative transcriptomic profile. Our findings suggest that cortical cell loss in preHD may arise from dual pathological processes, emerging as a consequence of neurodevelopmental changes, at the beginning of life, followed by neurodegeneration in adulthood, targeting areas with reduced expression of synaptic and metabolic genes. These events result in age-related cell death across multiple brain cell types.

Regulation of mitophagy by the NSL complex underlies genetic risk for Parkinson's disease at 16q11.2 and MAPT H1 loci.

Parkinson's disease is a common incurable neurodegenerative disease. The identification of genetic variants via genome-wide association studies has considerably advanced our understanding of the Parkinson's disease genetic risk. Understanding the functional significance of the risk loci is now a critical step towards translating these genetic advances into an enhanced biological understanding of the disease. Impaired mitophagy is a key causative pathway in familial Parkinson's disease, but its relevance to idiopathic Parkinson's disease is unclear. We used a mitophagy screening assay to evaluate the functional significance of risk genes identified through genome-wide association studies. We identified two new regulators of PINK1-dependent mitophagy initiation, KAT8 and KANSL1, previously shown to modulate lysine acetylation. These findings suggest PINK1-mitophagy is a contributing factor to idiopathic Parkinson's disease. KANSL1 is located on chromosome 17q21 where the risk associated gene has long been considered to be MAPT. While our data do not exclude a possible association between the MAPT gene and Parkinson's disease, they provide strong evidence that KANSL1 plays a crucial role in the disease. Finally, these results enrich our understanding of physiological events regulating mitophagy and establish a novel pathway for drug targeting in neurodegeneration.

Cytosolic sequestration of spatacsin by Protein Kinase A and 14-3-3 proteins.

Mutations in SPG11, encoding spatacsin, constitute the major cause of autosomal recessive Hereditary Spastic Paraplegia (HSP) with thinning of the corpus callosum. Previous studies showed that spatacsin orchestrates cellular traffic events through the formation of a coat-like complex and its loss of function results in lysosomal and axonal transport impairments. However, the upstream mechanisms that regulate spatacsin trafficking are unknown. Here, using proteomics and CRISPR/Cas9-mediated tagging of endogenous spatacsin, we identified a subset of 14-3-3 proteins as physiological interactors of spatacsin. The interaction is modulated by Protein Kinase A (PKA)-dependent phosphorylation of spatacsin at Ser1955, which initiates spatacsin trafficking from the plasma membrane to the intracellular space. Our study provides novel insight in understanding spatacsin physio-pathological roles with mechanistic dissection of its associated pathways.

SLITRK2, an X-linked modifier of the age at onset in C9orf72 frontotemporal lobar degeneration.

The G4C2-repeat expansion in C9orf72 is the most common cause of frontotemporal dementia and of amyotrophic lateral sclerosis. The variability of age at onset and phenotypic presentations is a hallmark of C9orf72 disease. In this study, we aimed to identify modifying factors of disease onset in C9orf72 carriers using a family-based approach, in pairs of C9orf72 carrier relatives with concordant or discordant age at onset. Linkage and association analyses provided converging evidence for a locus on chromosome Xq27.3. The minor allele A of rs1009776 was associated with an earlier onset (P = 1 × 10-5). The association with onset of dementia was replicated in an independent cohort of unrelated C9orf72 patients (P = 0.009). The protective major allele delayed the onset of dementia from 5 to 13 years on average depending on the cohort considered. The same trend was observed in an independent cohort of C9orf72 patients with extreme deviation of the age at onset (P = 0.055). No association of rs1009776 was detected in GRN patients, suggesting that the effect of rs1009776 was restricted to the onset of dementia due to C9orf72. The minor allele A is associated with a higher SLITRK2 expression based on both expression quantitative trait loci (eQTL) databases and in-house expression studies performed on C9orf72 brain tissues. SLITRK2 encodes for a post-synaptic adhesion protein. We further show that synaptic vesicle glycoprotein 2 and synaptophysin, two synaptic vesicle proteins, were decreased in frontal cortex of C9orf72 patients carrying the minor allele. Upregulation of SLITRK2 might be associated with synaptic dysfunctions and drives adverse effects in C9orf72 patients that could be modulated in those carrying the protective allele. How the modulation of SLITRK2 expression affects synaptic functions and influences the disease onset of dementia in C9orf72 carriers will require further investigations. In summary, this study describes an original approach to detect modifier genes in rare diseases and reinforces rising links between C9orf72 and synaptic dysfunctions that might directly influence the occurrence of first symptoms.

Seventy-Two-Hour LRRK2 Kinase Activity Inhibition Increases Lysosomal GBA Expression in H4, a Human Neuroglioma Cell Line.

Mutations in LRRK2 and GBA1 are key contributors to genetic risk of developing Parkinson's disease (PD). To investigate how LRRK2 kinase activity interacts with GBA and contributes to lysosomal dysfunctions associated with the pathology of PD. The activity of the lysosomal enzyme ß-Glucocerebrosidase (GCase) was assessed in a human neuroglioma cell model treated with two selective inhibitors of LRKK2 kinase activity (LRRK2-in-1 and MLi-2) and a GCase irreversible inhibitor, condutirol-beta-epoxide (CBE), under 24 and 72 h experimental conditions. We observed levels of GCase activity comparable to controls in response to 24 and 72 h treatments with LRRK2-in-1 and MLi-2. However, GBA protein levels increased upon 72 h treatment with LRRK2-in-1. Moreover, LC3-II protein levels were increased after both 24 and 72 h treatments with LRRK2-in-1, suggesting an activation of the autophagic pathway. These results highlight a possible regulation of lysosomal function through the LRRK2 kinase domain and suggest an interplay between LRRK2 kinase activity and GBA. Although further investigations are needed, the enhancement of GCase activity might restore the defective protein metabolism seen in PD.

Advances in protein-protein interaction network analysis for Parkinson's disease.

Protein-protein interactions (PPIs) are a key component of the subcellular molecular networks which enable cells to function. Due to their importance in homeostasis, alterations to the networks can be detrimental, leading to cellular dysfunction and ultimately disease states. Parkinson's disease (PD) is a progressive neurodegenerative condition with multifactorial aetiology, spanning genetic variation and environmental modifiers. At a molecular and systems level, the characterisation of PD is the focus of extensive research, largely due to an unmet need for disease modifying therapies. PPI network analysis approaches are a valuable strategy to accelerate our understanding of the molecular crosstalk and biological processes underlying PD pathogenesis, especially due to the complex nature of this disease. In this review, we describe the utility of PPI network approaches in modelling complex systems, focusing on previous work in PD research. We discuss four principal strategies for using PPI network approaches: to infer PD related cellular functions, pathways and novel genes; to support genomics studies; to study the interactome of single PD related genes; and to compare the molecular basis of PD to other neurodegenerative disorders. This is an evolving area of research which is likely to further expand as omics data generation and availability increase. These approaches complement and bridge-the-gap between genetics and functional research to inform future investigations. In this review we outline several limitations that require consideration, acknowledging that ongoing challenges in this field continue to be addressed and the refinement of these approaches will facilitate further advances using PPI network analysis for understanding complex diseases.

Mendelian and Sporadic FTD: Disease Risk and Avenues from Genetics to Disease Pathways Through In Silico Modelling.

Frontotemporal dementia (FTD) is regarded as the second most common form of young-onset dementia after Alzheimer's disease (AD).FTD is a complex neurodegenerative condition characterised by heterogeneous clinical, pathological and genetic features. No efficient measures for early diagnosis and therapy are available.Familial (Mendelian) forms of disease have been studied over the past 20 years. Conversely, the genetics of sporadic forms of FTD (up to 70% of all cases) is understudied and still poorly understood. All this taken together suggests that more powerful and in-depth studies to tackle missing heritability and define the genetic architecture of sporadic FTD, with particular focus on the different subtypes (i.e. clinical and pathological diagnoses), are warranted.In parallel, it will be critical to translate the genetic findings into functional understanding of disease, i.e. moving from the identification of risk genes to the definition of risk pathways. It will be necessary to implement a paradigm shift - from reductionist to holistic approaches - to better interpret genetics and assist functional studies aimed at modelling and validating such risk pathways.In this chapter, we focus on the heterogeneous features of FTD touching upon its complex genetic landscape and discuss how novel approaches (e.g. computationally driven systems biology) promise to revolutionise the translation of genetic information into functional understanding of disease pathogenesis.

Leucine-rich repeat kinase 2 and lysosomal dyshomeostasis in Parkinson disease.

Over the last two decades, a number of studies have underlined the importance of lysosomal-based degradative pathways in maintaining the homeostasis of post-mitotic cells, and revealed the remarkable contribution of a functional autophagic machinery in the promotion of longevity. In contrast, defects in the clearance of organelles and aberrant protein aggregates have been linked to accelerated neuronal loss and neurological dysfunction. Several neurodegenerative disorders, among which Alzheimer disease (AD), Frontotemporal dementia, and Amyotrophic Lateral Sclerosis to name a few, are associated with alterations of the autophagy and endo-lysosomal pathways. In Parkinson disease (PD), the most prevalent genetic determinant, Leucine-rich repeat kinase 2 (LRRK2), is believed to be involved in the regulation of intracellular vesicle traffic, autophagy and lysosomal function. Here, we review the current understanding of the mechanisms by which LRRK2 regulates lysosomal-based degradative pathways in neuronal and non-neuronal cells and discuss the impact of pathogenic PD mutations in contributing to lysosomal dyshomeostasis.

Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences.

Advances in the technologies and informatics used to generate and process large biological data sets (omics data) are promoting a critical shift in the study of biomedical sciences. While genomics, transcriptomics and proteinomics, coupled with bioinformatics and biostatistics, are gaining momentum, they are still, for the most part, assessed individually with distinct approaches generating monothematic rather than integrated knowledge. As other areas of biomedical sciences, including metabolomics, epigenomics and pharmacogenomics, are moving towards the omics scale, we are witnessing the rise of inter-disciplinary data integration strategies to support a better understanding of biological systems and eventually the development of successful precision medicine. This review cuts across the boundaries between genomics, transcriptomics and proteomics, summarizing how omics data are generated, analysed and shared, and provides an overview of the current strengths and weaknesses of this global approach. This work intends to target students and researchers seeking knowledge outside of their field of expertise and fosters a leap from the reductionist to the global-integrative analytical approach in research.

PINOT: an intuitive resource for integrating protein-protein interactions.

BACKGROUND: The past decade has seen the rise of omics data for the understanding of biological systems in health and disease. This wealth of information includes protein-protein interaction (PPI) data derived from both low- and high-throughput assays, which are curated into multiple databases that capture the extent of available information from the peer-reviewed literature. Although these curation efforts are extremely useful, reliably downloading and integrating PPI data from the variety of available repositories is challenging and time consuming. METHODS: We here present a novel user-friendly web-resource called PINOT (Protein Interaction Network Online Tool; available at http://www.reading.ac.uk/bioinf/PINOT/PINOT_form.html) to optimise the collection and processing of PPI data from IMEx consortium associated repositories (members and observers) and WormBase, for constructing, respectively, human and Caenorhabditis elegans PPI networks. RESULTS: Users submit a query containing a list of proteins of interest for which PINOT extracts data describing PPIs. At every query submission PPI data are downloaded, merged and quality assessed. Then each PPI is confidence scored based on the number of distinct methods used for interaction detection and the number of publications that report the specific interaction. Examples of how PINOT can be applied are provided to highlight the performance, ease of use and potential utility of this tool. CONCLUSIONS: PINOT is a tool that allows users to survey the curated literature, extracting PPI data in relation to a list of proteins of interest. PINOT extracts a similar numbers of PPIs as other, analogous, tools and incorporates a set of innovative features. PINOT is able to process large queries, it downloads human PPIs live through PSICQUIC and it applies quality control filters on the downloaded PPI data (i.e. removing the need for manual inspection by the user). PINOT provides the user with information on detection methods and publication history for each downloaded interaction data entry and outputs the results in a table format that can be straightforwardly further customised and/or directly uploaded into network visualization software. Video abstract.

A C6orf10/LOC101929163 locus is associated with age of onset in C9orf72 carriers.

The G4C2-repeat expansion in C9orf72 is the most common known cause of amyotrophic lateral sclerosis and frontotemporal dementia. The high phenotypic heterogeneity of C9orf72 patients includes a wide range in age of onset, modifiers of which are largely unknown. Age of onset could be influenced by environmental and genetic factors both of which may trigger DNA methylation changes at CpG sites. We tested the hypothesis that age of onset in C9orf72 patients is associated with some common single nucleotide polymorphisms causing a gain or loss of CpG sites and thus resulting in DNA methylation alterations. Combined analyses of epigenetic and genetic data have the advantage of detecting functional variants with reduced likelihood of false negative results due to excessive correction for multiple testing in genome-wide association studies. First, we estimated the association between age of onset in C9orf72 patients (n = 46) and the DNA methylation levels at all 7603 CpG sites available on the 450 k BeadChip that are mapped to common single nucleotide polymorphisms. This was followed by a genetic association study of the discovery (n = 144) and replication (n = 187) C9orf72 cohorts. We found that age of onset was reproducibly associated with polymorphisms within a 124.7 kb linkage disequilibrium block tagged by top-significant variation, rs9357140, and containing two overlapping genes (LOC101929163 and C6orf10). A meta-analysis of all 331 C9orf72 carriers revealed that every A-allele of rs9357140 reduced hazard by 30% (P = 0.0002); and the median age of onset in AA-carriers was 6 years later than GG-carriers. In addition, we investigated a cohort of C9orf72 negative patients (n = 2634) affected by frontotemporal dementia and/or amyotrophic lateral sclerosis; and also found that the AA-genotype of rs9357140 was associated with a later age of onset (adjusted P = 0.007 for recessive model). Phenotype analyses detected significant association only in the largest subgroup of patients with frontotemporal dementia (n = 2142, adjusted P = 0.01 for recessive model). Gene expression studies of frontal cortex tissues from 25 autopsy cases affected by amyotrophic lateral sclerosis revealed that the G-allele of rs9357140 is associated with increased brain expression of LOC101929163 (a non-coding RNA) and HLA-DRB1 (involved in initiating immune responses), while the A-allele is associated with their reduced expression. Our findings suggest that carriers of the rs9357140 GG-genotype (linked to an earlier age of onset) might be more prone to be in a pro-inflammatory state (e.g. by microglia) than AA-carriers. Further, investigating the functional links within the C6orf10/LOC101929163/HLA-DRB1 pathway will be critical to better define age-dependent pathogenesis of frontotemporal dementia and amyotrophic lateral sclerosis.

Comparative Protein Interaction Network Analysis Identifies Shared and Distinct Functions for the Human ROCO Proteins.

Signal transduction cascades governed by kinases and GTPases are a critical component of the command and control of cellular processes, with the precise outcome partly determined by direct protein-protein interactions (PPIs). Here, we use the human ROCO proteins as a model for investigating PPI signaling events-taking advantage of the unique dual kinase/GTPase activities and scaffolding properties of these multidomain proteins. PPI networks are reported that encompass the human ROCO proteins, developed using two complementary approaches. First, using the recently developed weighted PPI network analysis (WPPINA) pipeline, a confidence-weighted overview of validated ROCO protein interactors is obtained from peer-reviewed literature. Second, novel ROCO PPIs are assessed experimentally via protein microarray screens. The networks derived from these orthologous approaches are compared to identify common elements within the ROCO protein interactome; functional enrichment analysis of this common core of the network identified stress response and cell projection organization as shared functions within this protein family. Despite the presence of these commonalities, the results suggest that many unique interactors and therefore some specialized cellular roles have evolved for different members of the ROCO proteins. Overall, this multi-approach strategy to increase the resolution of protein interaction networks represents a prototype for the utility of PPI data integration in understanding signaling biology.

Stratification of candidate genes for Parkinson's disease using weighted protein-protein interaction network analysis.

BACKGROUND: Genome wide association studies (GWAS) have helped identify large numbers of genetic loci that significantly associate with increased risk of developing diseases. However, translating genetic knowledge into understanding of the molecular mechanisms underpinning disease (i.e. disease-specific impacted biological processes) has to date proved to be a major challenge. This is primarily due to difficulties in confidently defining candidate genes at GWAS-risk loci. The goal of this study was to better characterize candidate genes within GWAS loci using a protein interactome based approach and with Parkinson's disease (PD) data as a test case. RESULTS: We applied a recently developed Weighted Protein-Protein Interaction Network Analysis (WPPINA) pipeline as a means to define impacted biological processes, risk pathways and therein key functional players. We used previously established Mendelian forms of PD to identify seed proteins, and to construct a protein network for genetic Parkinson's and carried out functional enrichment analyses. We isolated PD-specific processes indicating 'mitochondria stressors mediated cell death', 'immune response and signaling', and 'waste disposal' mediated through 'autophagy'. Merging the resulting protein network with data from Parkinson's GWAS we confirmed 10 candidate genes previously selected by pure proximity and were able to nominate 17 novel candidate genes for sporadic PD. CONCLUSIONS: With this study, we were able to better characterize the underlying genetic and functional architecture of idiopathic PD, thus validating WPPINA as a robust pipeline for the in silico genetic and functional dissection of complex disorders.

The LRRK2 signalling system.

The LRRK2 gene is a major contributor to genetic risk for Parkinson's disease and understanding the biology of the leucine-rich repeat kinase 2 (LRRK2, the protein product of this gene) is an important goal in Parkinson's research. LRRK2 is a multi-domain, multi-activity enzyme and has been implicated in a wide range of signalling events within the cell. Because of the complexities of the signal transduction pathways in which LRRK2 is involved, it has been challenging to generate a clear idea as to how mutations and disease associated variants in this gene are altered in disease. Understanding the events in which LRRK2 is involved at a systems level is therefore critical to fully understand the biology and pathobiology of this protein and is the subject of this review.

Weighted Protein Interaction Network Analysis of Frontotemporal Dementia.

The genetic analysis of complex disorders has undoubtedly led to the identification of a wealth of associations between genes and specific traits. However, moving from genetics to biochemistry one gene at a time has, to date, rather proved inefficient and under-powered to comprehensively explain the molecular basis of phenotypes. Here we present a novel approach, weighted protein-protein interaction network analysis (W-PPI-NA), to highlight key functional players within relevant biological processes associated with a given trait. This is exemplified in the current study by applying W-PPI-NA to frontotemporal dementia (FTD): We first built the state of the art FTD protein network (FTD-PN) and then analyzed both its topological and functional features. The FTD-PN resulted from the sum of the individual interactomes built around FTD-spectrum genes, leading to a total of 4198 nodes. Twenty nine of 4198 nodes, called inter-interactome hubs (IIHs), represented those interactors able to bridge over 60% of the individual interactomes. Functional annotation analysis not only reiterated and reinforced previous findings from single genes and gene-coexpression analyses but also indicated a number of novel potential disease related mechanisms, including DNA damage response, gene expression regulation, and cell waste disposal and potential biomarkers or therapeutic targets including EP300. These processes and targets likely represent the functional core impacted in FTD, reflecting the underlying genetic architecture contributing to disease. The approach presented in this study can be applied to other complex traits for which risk-causative genes are known as it provides a promising tool for setting the foundations for collating genomics and wet laboratory data in a bidirectional manner. This is and will be critical to accelerate molecular target prioritization and drug discovery.

The LRRK2-macroautophagy axis and its relevance to Parkinson's disease.

A wide variety of different functions and an impressive array of interactors have been associated with leucine-rich repeat kinase 2 (LRRK2) over the years. Here, I discuss the hypothesis that LRRK2 may be capable of interacting with different proteins at different times and places, therefore, controlling a plethora of diverse functions based on the different complexes formed. Among these, I will then focus on macroautophagy in the general context of the endolysosomal system. First, the relevance of autophagy in Parkinson's disease will be evaluated giving a brief overview of all the relevant Parkinson's disease genes; then, the association of LRRK2 with macroautophagy and the endolysosomal pathway will be analyzed based on the supporting literature.