Identifying consensus disease pathways in Parkinson's disease using an integrative systems biology approach

Itga5-PTEN signaling regulates striatal synaptic strength and motor coordination in Parkinson's disease

Background: Parkinson's disease (PD) is marked by the loss of dopaminergic neurons in the substantia nigra pars compacta, leading to motor and cognitive dysfunctions. The molecular mechanisms underlying synaptic alterations in PD remain elusive, with a focus on the role of Itga5 in synaptic integrity and motor coordination and TAT-Itga5 was designed to suppress PTEN activity in this investigation. Methods: This study utilized MPTP-induced PD animal models to investigate the expression and role of Itga5 in the striatum. Techniques included quantitative PCR, Western blotting, immunostaining, CRISPR-CasRx-mediated knockdown, electrophysiological assays, behavioral tests, and mass spectrometry. Results: Itga5 expression was significantly reduced in MPTP-induced PD models. In these models, a marked decrease in dendritic spine density and a shift towards thinner spines in striatal GABA neurons were observed, suggesting impaired synaptic integration. Knockdown of Itga5 resulted in reduced dendritic branching, decreased mushroom spines, and increased thin spines, altering synaptic architecture. Electrophysiological analyses revealed changes in action potential and spontaneous excitatory postsynaptic currents, indicating altered synaptic transmission. Motor behavior assessments showed that Itga5 deficiency led to impairments in fine motor control and coordination. Furthermore, Itga5 was found to interact with PTEN, affecting AKT signaling crucial for synaptic development and motor coordination. Conclusion: The study demonstrates that Itga5 plays a critical role in maintaining synaptic integrity and motor coordination in PD. The Itga5-PTEN-AKT pathway represents a potential therapeutic target for addressing synaptic and motor dysfunctions in PD.

A Diagnostic Model for Parkinson's Disease Based on Anoikis-Related Genes

Parkinson's disease (PD) is the second most prevalent neurodegenerative disease, and its pathological mechanisms are thought to be closely linked to apoptosis. Anoikis, a specific type of apoptosis, has recently been suggested to play a role in the progression of Parkinson's disease; however, the underlying mechanisms are not well understood. To explore the potential mechanisms involved in PD, we selected genes from the GSE28894 dataset and compared their expression in PD patients and healthy controls to identify differentially expressed genes (DEGs), and selected anoikis-related genes (ANRGs) from the DEGs. Furthermore, the least absolute shrinkage and selection operator (LASSO) regression approach and multivariate logistic regression highlighted five key genes-GSK3B, PCNA, CDC42, DAPK2, and SRC-as biomarker candidates. Subsequently, we developed a nomogram model incorporating these 5 genes along with age and sex to predict and diagnose PD. To evaluate the model's coherence, clinical applicability, and distinguishability, we utilized receiver operating characteristic (ROC) curves, the C-index, and calibration curves and validated it in both the GSE20295 dataset and our center's external clinical data. In addition, we confirmed the differential expression of the 5 model genes in human blood samples through qRT-PCR and Western blotting. Our constructed anoikis-related PD diagnostic model exhibits satisfactory predictive accuracy and offers novel insights into both diagnosis and treatment strategies for Parkinson's disease while facilitating its implementation in clinical practice.

A Systematic Review of Extracellular Matrix-Related Alterations in Parkinson's Disease

The role of the extracellular matrix (ECM) in Parkinson's disease (PD) is not well understood, even though it is critical for neuronal structure and signaling. This systematic review identified the top deregulated ECM-related pathways in studies that used gene set enrichment analyses (GSEA) to document transcriptomic, proteomic, or genomic alterations in PD. PubMed and Google scholar were searched for transcriptomics, proteomics, or genomics studies that employed GSEA on data from PD tissues or cells and reported ECM-related pathways among the top-10 most enriched versus controls. Twenty-seven studies were included, two of which used multiple omics analyses. Transcriptomics and proteomics studies were conducted on a variety of tissue and cell types. Of the 17 transcriptomics studies (16 data sets), 13 identified one or more adhesion pathways in the top-10 deregulated gene sets or pathways, primarily related to cell adhesion and focal adhesion. Among the 8 proteomics studies, 5 identified altered overarching ECM gene sets or pathways among the top 10. Among the 4 genomics studies, 3 identified focal adhesion pathways among the top 10. The findings summarized here suggest that ECM organization/structure and cell adhesion (particularly focal adhesion) are altered in PD and should be the focus of future studies.

The CHD Protein Kismet Restricts the Synaptic Localization of Cell Adhesion Molecules at the Drosophila Neuromuscular Junction

The appropriate expression and localization of cell surface cell adhesion molecules must be tightly regulated for optimal synaptic growth and function. How neuronal plasma membrane proteins, including cell adhesion molecules, cycle between early endosomes and the plasma membrane is poorly understood. Here we show that the Drosophila homolog of the chromatin remodeling enzymes CHD7 and CHD8, Kismet, represses the synaptic levels of several cell adhesion molecules. Neuroligins 1 and 3 and the integrins αPS2 and βPS are increased at kismet mutant synapses but Kismet only directly regulates transcription of neuroligin 2. Kismet may therefore regulate synaptic CAMs indirectly by activating transcription of gene products that promote intracellular vesicle trafficking including endophilin B (endoB) and/or rab11. Knock down of EndoB in all tissues or neurons increases synaptic FasII while knock down of EndoB in kis mutants does not produce an additive increase in FasII. In contrast, neuronal expression of Rab11, which is deficient in kis mutants, leads to a further increase in synaptic FasII in kis mutants. These data support the hypothesis that Kis influences the synaptic localization of FasII by promoting intracellular vesicle trafficking through the early endosome.

Identification of diagnostic and prognostic biomarkers of PD using a multiplex proteomics approach

Given the complexity of Parkinson's disease (PD), achieving acceptable diagnostic and prognostic accuracy will require the support of a panel of diverse biomarkers. We used Proximity extension assays to measure a panel of 92 proteins in CSF of 120 newly diagnosed PD patients and 45 control subjects without neurological disease. From 75 proteins detectable in the CSF of >90% of the subjects, regularized regression analysis identified four proteins (β-NGF, CD38, tau and NCAN) as downregulated in newly diagnosed PD patients (age at diagnosis 67.2 ± 9.4 years) compared to controls (age 65.4 ± 10.9 years). Higher tau (β -0.82 transformed MMSE points/year, 95% CI -1.37 to -0.27, P = 0.005) was also linked to faster cognitive decline over the first ten years after PD diagnosis. These findings provide insights into multiple aspects of PD pathophysiology and may serve as the foundation for identifying new biomarkers and therapeutic targets.

Biomedical knowledge graph learning for drug repurposing by extending guilt-by-association to multiple layers

Computational drug repurposing aims to identify new indications for existing drugs by utilizing high-throughput data, often in the form of biomedical knowledge graphs. However, learning on biomedical knowledge graphs can be challenging due to the dominance of genes and a small number of drug and disease entities, resulting in less effective representations. To overcome this challenge, we propose a "semantic multi-layer guilt-by-association" approach that leverages the principle of guilt-by-association - "similar genes share similar functions", at the drug-gene-disease level. Using this approach, our model DREAMwalk: Drug Repurposing through Exploring Associations using Multi-layer random walk uses our semantic information-guided random walk to generate drug and disease-populated node sequences, allowing for effective mapping of both drugs and diseases in a unified embedding space. Compared to state-of-the-art link prediction models, our approach improves drug-disease association prediction accuracy by up to 16.8%. Moreover, exploration of the embedding space reveals a well-aligned harmony between biological and semantic contexts. We demonstrate the effectiveness of our approach through repurposing case studies for breast carcinoma and Alzheimer's disease, highlighting the potential of multi-layer guilt-by-association perspective for drug repurposing on biomedical knowledge graphs.

Proteins and Transcriptional Dysregulation of the Brain Extracellular Matrix in Parkinson's Disease: A Systematic Review

The extracellular matrix (ECM) of the brain is a dynamic structure made up of a vast network of bioactive macromolecules that modulate cellular events. Structural, organizational, and functional changes in these macromolecules due to genetic variation or environmental stressors are thought to affect cellular functions and may result in disease. However, most mechanistic studies to date usually focus on the cellular aspects of diseases and pay less attention to the relevance of the processes governing the dynamic nature of the extracellular matrix in disease pathogenesis. Thus, due to the ECM's diversified biological roles, increasing interest in its involvement in disease, and the lack of sufficient compiled evidence regarding its relationship with Parkinson's disease (PD) pathology, we aimed to compile the existing evidence to boost the current knowledge on the area and provide refined guidance for the future research. Here, in this review, we gathered postmortem brain tissue and induced pluripotent stem cell (iPSC)-related studies from PubMed and Google Scholar to identify, summarize and describe common macromolecular alterations in the expression of brain ECM components in Parkinson's disease (PD). A literature search was conducted up until 10 February 2023. The overall hits from the database and manual search for proteomic and transcriptome studies were 1243 and 1041 articles, respectively. Following a full-text review, 10 articles from proteomic and 24 from transcriptomic studies were found to be eligible for inclusion. According to proteomic studies, proteins such as collagens, fibronectin, annexins, and tenascins were recognized to be differentially expressed in Parkinson's disease. Transcriptomic studies displayed dysregulated pathways including ECM-receptor interaction, focal adhesion, and cell adhesion molecules in Parkinson's disease. A limited number of relevant studies were accessed from our search, indicating that much work remains to be carried out to better understand the roles of the ECM in neurodegeneration and Parkinson's disease. However, we believe that our review will elicit focused primary studies and thus support the ongoing efforts of the discovery and development of diagnostic biomarkers as well as therapeutic agents for Parkinson's disease.

RNA-seq analysis of gene expression profiles in posttraumatic stress disorder, Parkinson's disease and schizophrenia identifies roles for common and distinct biological pathways

Evidence suggests that shared pathophysiological mechanisms in neuropsychiatric disorders (NPDs) may contribute to risk and resilience. We used single-gene and network-level transcriptomic approaches to investigate shared and disorder-specific processes underlying posttraumatic stress disorder (PTSD), Parkinson's disease (PD) and schizophrenia in a South African sample. RNA-seq was performed on blood obtained from cases and controls from each cohort. Gene expression and weighted gene correlation network analyses (WGCNA) were performed using DESeq2 and CEMiTool, respectively. Significant differences in gene expression were limited to the PTSD cohort. However, WGCNA implicated, amongst others, ribosomal expression, inflammation and ubiquitination as key players in the NPDs under investigation. Differential expression in ribosomal-related pathways was observed in the PTSD and PD cohorts, and focal adhesion and extracellular matrix pathways were implicated in PD and schizophrenia. We propose that, despite different phenotypic presentations, core transdiagnostic mechanisms may play important roles in the molecular aetiology of NPDs.

Distinct genetic regions are associated with differential population susceptibility to chemical exposures

Interactions between environmental factors and genetics underlie the majority of chronic human diseases. Chemical exposures are likely an underestimated contributor, yet gene-environment (GxE) interaction studies rarely assess their modifying effects. Here, we describe a novel method to profile the human genome and identify regions associated with differential population susceptibility to chemical exposures. Single nucleotide polymorphisms (SNPs) implicated in enriched chemical-disease intersections were identified and validated for three chemical classes with expected GxE interaction potential (neuroactive, hepatoactive, and cardioactive compounds). The same approach was then used to characterize consumer product classes with unknown risk for GxE interactions (washing products, cosmetics, and adhesives). Additionally, high-risk variant sets that may confer differential population susceptibility were identified for these consumer product groups through frequent itemset mining and pathway analysis. A dataset of 2454 consumer product chemical-disease linkages, with risk values, SNPs, and pathways for each association was developed, describing the interplay between environmental factors and genetics in human disease progression. We found that genetic hotspots implicated in GxE interactions differ across chemical classes (e.g., washing products had high-risk SNPs implicated in nervous system disease) and illustrate how this approach can discover new associations (e.g., washing product n-butoxyethanol implicated SNPs in the PI3K-Akt signaling pathway for Alzheimer's disease). Hence, our approach can predict high-risk genetic regions for differential population susceptibility to chemical exposures and characterize chemical modifying factors in specific diseases. These methods show promise for describing how chemical exposures can lead to varied health outcomes in a population and for incorporating inter-individual variability into chemical risk assessment.

Loss of p21-activated kinase Mbt/PAK4 causes Parkinson-like phenotypes in Drosophila

Parkinson's disease (PD) provokes bradykinesia, resting tremor, rigidity and postural instability, and also non-motor symptoms such as depression, anxiety, sleep and cognitive impairments. Similar phenotypes can be induced in Drosophila melanogaster through modification of PD-relevant genes or the administration of PD-inducing toxins. Recent studies correlated deregulation of human p21-activated kinase 4 (PAK4) with PD, leaving open the question of a causative relationship of mutations in this gene for manifestation of PD symptoms. To determine whether flies lacking the PAK4 homolog Mushroom bodies tiny (Mbt) show PD-like phenotypes, we tested for a variety of PD criteria. Here, we demonstrate that mbt mutant flies show PD-like phenotypes including age-dependent movement deficits, reduced life expectancy and fragmented sleep. They also react to a stressful situation with higher immobility, indicating an influence of Mbt on emotional behavior. Loss of Mbt function has a negative effect on the number of dopaminergic protocerebral anterior medial (PAM) neurons, most likely caused by a proliferation defect of neural progenitors. The age-dependent movement deficits are not accompanied by a corresponding further loss of PAM neurons. Previous studies highlighted the importance of a small PAM subgroup for age-dependent PD motor impairments. We show that impaired motor skills are caused by a lack of Mbt in this PAM subgroup. In addition, a broader re-expression of Mbt in PAM neurons improves life expectancy. Conversely, selective Mbt knockout in the same cells shortens lifespan. We conclude that mutations in Mbt/PAK4 can play a causative role in the development of PD phenotypes.

Chemically Induced Models of Parkinson's Disease: History and Perspectives for the Involvement of Ferroptosis

Ferroptosis is a newly discovered form of necrotic cell death characterized by its dependency on iron and lipid peroxidation. Ferroptosis has attracted much attention recently in the area of neurodegeneration since the involvement of ferroptosis in Parkinson’s disease (PD), a major neurodegenerative disease, has been indicated using animal models. Although PD is associated with both genetic and environmental factors, sporadic forms of PD account for more than 90% of total PD. Following the importance of environmental factors, various neurotoxins are used as chemical inducers of PD both in vivo and in vitro. In contrast to other neurodegenerative diseases such as Alzheimer’s and Huntington’s diseases (AD and HD), many of the characteristics of PD can be reproduced in vivo by the use of specific neurotoxins. Given the indication of ferroptosis in PD pathology, several studies have been conducted to examine whether ferroptosis plays role in the loss of dopaminergic neurons in PD. However, there are still few reports showing an authentic form of ferroptosis in neuronal cells during exposure to the neurotoxins used as PD inducers. In this review article, we summarize the history of the uses of chemicals to create PD models in vivo and in vitro. Besides, we also survey recent reports examining the possible involvement of ferroptosis in chemical models of PD.

Non-Coding RNAs in the Brain-Heart Axis: The Case of Parkinson's Disease

Parkinson's disease (PD) is a complex and heterogeneous disorder involving multiple genetic and environmental influences. Although a wide range of PD risk factors and clinical markers for the symptomatic motor stage of the disease have been identified, there are still no reliable biomarkers available for the early pre-motor phase of PD and for predicting disease progression. High-throughput RNA-based biomarker profiling and modeling may provide a means to exploit the joint information content from a multitude of markers to derive diagnostic and prognostic signatures. In the field of PD biomarker research, currently, no clinically validated RNA-based biomarker models are available, but previous studies reported several significantly disease-associated changes in RNA abundances and activities in multiple human tissues and body fluids. Here, we review the current knowledge of the regulation and function of non-coding RNAs in PD, focusing on microRNAs, long non-coding RNAs, and circular RNAs. Since there is growing evidence for functional interactions between the heart and the brain, we discuss the benefits of studying the role of non-coding RNAs in organ interactions when deciphering the complex regulatory networks involved in PD progression. We finally review important concepts of harmonization and curation of high throughput datasets, and we discuss the potential of systems biomedicine to derive and evaluate RNA biomarker signatures from high-throughput expression data.

Advances in Astrocyte Computational Models: From Metabolic Reconstructions to Multi-omic Approaches

The growing importance of astrocytes in the field of neuroscience has led to a greater number of computational models devoted to the study of astrocytic functions and their metabolic interactions with neurons. The modeling of these interactions demands a combined understanding of brain physiology and the development of computational frameworks based on genomic-scale reconstructions, system biology, and dynamic models. These computational approaches have helped to highlight the neuroprotective mechanisms triggered by astrocytes and other glial cells, both under normal conditions and during neurodegenerative processes. In the present review, we evaluate some of the most relevant models of astrocyte metabolism, including genome-scale reconstructions and astrocyte-neuron interactions developed in the last few years. Additionally, we discuss novel strategies from the multi-omics perspective and computational models of other glial cell types that will increase our knowledge in brain metabolism and its association with neurodegenerative diseases.

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

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

Association Between Parkinson's Disease and Melanoma: Putting the Pieces Together

Patients with Parkinson’s disease (PD) generally have reduced risk of developing many types of cancers, except melanoma—a malignant tumor of melanin-producing cells in the skin. For decades, a large number of epidemiological studies have reported that the occurrence of melanoma is higher than expected among subjects with PD, and the occurrence of PD is reciprocally higher than expected among patients with melanoma. More recent epidemiological studies further indicated a bidirectional association, not only in the patients themselves but also in their relatives. This association between PD and melanoma offers a unique opportunity to understand PD. Here, we summarize epidemiological, clinical, and biological evidence in regard to shared risk factors and possible underlying mechanisms for these two seemingly distinct conditions.

Cerebrospinal fluid proteomics implicates the granin family in Parkinson's disease

Parkinson's disease, the most common age-related movement disorder, is a progressive neurodegenerative disease with unclear etiology. Better understanding of the underlying disease mechanism(s) is an urgent need for the development of disease-modifying therapeutics. Limited studies have been performed in large patient cohorts to identify protein alterations in cerebrospinal fluid (CSF), a proximal site to pathology. We set out to identify disease-relevant protein changes in CSF to gain insights into the etiology of Parkinson's disease and potentially assist in disease biomarker identification. In this study, we used liquid chromatography-tandem mass spectrometry in data-independent acquisition (DIA) mode to identify Parkinson's-relevant biomarkers in cerebrospinal fluid. We quantified 341 protein groups in two independent cohorts (n = 196) and a longitudinal cohort (n = 105 samples, representing 40 patients) consisting of Parkinson's disease and healthy control samples from three different sources. A first cohort of 53 Parkinson's disease and 72 control samples was analyzed, identifying 53 proteins with significant changes (p < 0.05) in Parkinson's disease relative to healthy control. We established a biomarker signature and multiple protein ratios that differentiate Parkinson's disease from healthy controls and validated these results in an independent cohort. The second cohort included 28 Parkinson's disease and 43 control samples. Independent analysis of these samples identified 41 proteins with significant changes. Evaluation of the overlapping changes between the two cohorts identified 13 proteins with consistent and significant changes (p < 0.05). Importantly, we found the extended granin family proteins as reduced in disease, suggesting a potential common mechanism for the biological reduction in monoamine neurotransmission in Parkinson's patients. Our study identifies several novel protein changes in Parkinson's disease cerebrospinal fluid that may be exploited for understanding etiology of disease and for biomarker development.

Systems pharmacology based approach to investigate the in-vivo therapeutic efficacy of Albizia lebbeck (L.) in experimental model of Parkinson's disease

Background

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by loss of dopaminergic neurons in substantia nigra pars compacta and clinically manifested mainly with motor dysfunctions. Plants are rich source of medicinally important bioactive compounds and inhabitants of underdeveloped countries used plants for treatment of various ailments. Albizia lebbeck has been reported to possess antioxidant and neuroprotective properties that suggest the evaluation of its traditional therapeutic potential in neurodegenerative diseases.

The aim of present study was to validate the traditional use of Albizia lebbeck (L.) and delineate its mechanism of action in PD. The systems pharmacology approach was employed to explain the Albizia lebbeck (L.) mechanism of action in PD.

Methods

The haloperidol-induced catalepsy was adopted as experimental model of PD for in-vivo studies in wistar albino rats. The systems pharmacology approach was employed to explain the Albizia lebbeck (L.) mechanism of action in PD.

Results

In-vivo studies revealed that Albizia lebbeck improved the motor functions and endurance as demonstrated in behavioral studies which were further supported by the rescue of endogenous antioxidant defense and reversal of ultrastructural damages in histological studies. System pharmacology approach identified 25 drug like compounds interacting with 132 targets in a bipartite graph that revealed the synergistic mechanism of action at system level. Kaemferol, phytosterol and okanin were found to be the important compounds nodes with prominent target nodes of TDP1 and MAPT.

Conclusion

The therapeutic efficiency of Albizia lebbeck in PD was effectively delineated in our experimental and systems pharmacology approach. Moreover, this approach further facilitates the drug discovery from Albizia lebbeck for PD.

Quantitative Trait Module-Based Genetic Analysis of Alzheimer's Disease

The pathological features of Alzheimer's Disease (AD) first appear in the medial temporal lobe and then in other brain structures with the development of the disease. In this work, we investigated the association between genetic loci and subcortical structure volumes of AD on 393 samples in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Brain subcortical structures were clustered into modules using Pearson's correlation coefficient of volumes across all samples. Module volumes were used as quantitative traits to identify not only the main effect loci but also the interactive effect loci for each module. Thirty-five subcortical structures were clustered into five modules, each corresponding to a particular brain structure/area, including the limbic system (module I), the corpus callosum (module II), thalamus-cerebellum-brainstem-pallidum (module III), the basal ganglia neostriatum (module IV), and the ventricular system (module V). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment results indicate that the gene annotations of the five modules were distinct, with few overlaps between different modules. We identified several main effect loci and interactive effect loci for each module. All these loci are related to the function of module structures and basic biological processes such as material transport and signal transduction.

A Combined Transcriptomic and Genomic Analysis Identifies a Gene Signature Associated With the Response to Anti-TNF Therapy in Rheumatoid Arthritis

Background: Rheumatoid arthritis (RA) is the most frequent autoimmune disease involving the joints. Although anti-TNF therapies have proven effective in the management of RA, approximately one third of patients do not show a significant clinical response. The objective of this study was to identify new genetic variation associated with the clinical response to anti-TNF therapy in RA.

Methods: We performed a sequential multi-omic analysis integrating different sources of molecular information. First, we extracted the RNA from synovial biopsies of 11 RA patients starting anti-TNF therapy to identify gene coexpression modules (GCMs) in the RA synovium. Second, we analyzed the transcriptomic association between each GCM and the clinical response to anti-TNF therapy. The clinical response was determined at week 14 using the EULAR criteria. Third, we analyzed the association between the GCMs and anti-TNF response at the genetic level. For this objective, we used genome-wide data from a cohort of 348 anti-TNF treated patients from Spain. The GCMs that were significantly associated with the anti-TNF response were then tested for validation in an independent cohort of 2,706 anti-TNF treated patients. Finally, the functional implication of the validated GCMs was evaluated via pathway and cell type epigenetic enrichment analyses.

Results: A total of 149 GCMs were identified in the RA synovium. From these, 13 GCMs were found to be significantly associated with anti-TNF response (P < 0.05). At the genetic level, we detected two of the 13 GCMs to be significantly associated with the response to adalimumab (P = 0.0015) and infliximab (P = 0.021) in the Spain cohort. Using the independent cohort of RA patients, we replicated the association of the GCM associated with the response to adalimumab (P = 0.0019). The validated module was found to be significantly enriched for genes involved in the nucleotide metabolism (P = 2.41e-5) and epigenetic marks from immune cells, including CD4+ regulatory T cells (P = 0.041).

Conclusions: These findings show the existence of a drug-specific genetic basis for anti-TNF response, thereby supporting treatment stratification in the search for response biomarkers in RA.

A Meta-Analysis of Alzheimer's Disease Brain Transcriptomic Data

BACKGROUND

Microarray technologies have identified imbalances in the expression of specific genes and biological pathways in Alzheimer's disease (AD) brains. However, there is a lack of reproducibility across individual AD studies, and many related neurodegenerative and mental health disorders exhibit similar perturbations.

OBJECTIVE

Meta-analyze publicly available transcriptomic data from multiple brain-related disorders to identify robust transcriptomic changes specific to AD brains.

METHODS

Twenty-two AD, eight schizophrenia, five bipolar disorder, four Huntington's disease, two major depressive disorder, and one Parkinson's disease dataset totaling 2,667 samples and mapping to four different brain regions (temporal lobe, frontal lobe, parietal lobe, and cerebellum) were analyzed. Differential expression analysis was performed independently in each dataset, followed by meta-analysis using a combining p-value method known as Adaptively Weighted with One-sided Correction.

RESULTS

Meta-analysis identified 323, 435, 1,023, and 828 differentially expressed genes specific to the AD temporal lobe, frontal lobe, parietal lobe, and cerebellum brain regions, respectively. Seven of these genes were consistently perturbed across all AD brain regions with SPCS1 gene expression pattern replicating in RNA-Seq data. A further nineteen genes were perturbed specifically in AD brain regions affected by both plaques and tangles, suggesting possible involvement in AD neuropathology. In addition, biological pathways involved in the "metabolism of proteins" and viral components were significantly enriched across AD brains.

CONCLUSION

This study identified transcriptomic changes specific to AD brains, which could make a significant contribution toward the understanding of AD disease mechanisms and may also provide new therapeutic targets.

Genetic variation at the glycosaminoglycan metabolism pathway contributes to the risk of psoriatic arthritis but not psoriasis

OBJECTIVE

Psoriatic arthritis (PsA) is a chronic inflammatory arthritis affecting up to 30% of patients with psoriasis (Ps). To date, most of the known risk loci for PsA are shared with Ps, and identifying disease-specific variation has proven very challenging. The objective of the present study was to identify genetic variation specific for PsA.

METHODS

We performed a genome-wide association study in a cohort of 835 patients with PsA and 1558 controls from Spain. Genetic association was tested at the single marker level and at the pathway level. Meta-analysis was performed with a case-control cohort of 2847 individuals from North America. To confirm the specificity of the genetic associations with PsA, we tested the associated variation using a purely cutaneous psoriasis cohort (PsC, n=614) and a rheumatoid arthritis cohort (RA, n=1191). Using network and drug-repurposing analyses, we further investigated the potential of the PsA-specific associations to guide the development of new drugs in PsA.

RESULTS

We identified a new PsA risk single-nucleotide polymorphism at B3GNT2 locus (p=1.10e-08). At the pathway level, we found 14 genetic pathways significantly associated with PsA (p_FDR<0.05). From these, the glycosaminoglycan (GAG) metabolism pathway was confirmed to be disease-specific after comparing the PsA cohort with the cohorts of patients with PsC and RA. Finally, we identified candidate drug targets in the GAG metabolism pathway as well as new PsA indications for approved drugs.

CONCLUSION

These findings provide insights into the biological mechanisms that are specific for PsA and could contribute to develop more effective therapies.

Axon guidance pathway genes are associated with schizophrenia risk

In the present study, we analyzed schizophrenia (SCZ)-related genome-wide association studies (GWAS) to identify genes and pathways associated with SCZ. We identified 1,098 common genes (1,098/9,468) and 20 shared KEGG pathways (both P<0.01) by integrating candidate genes from the European and American SCZ-related GWAS. The pathways related to axon guidance, long term potentiation and arrhythmogenic right ventricular cardiomyopathy (ARVC) were highly significant (P<10^-3). Moreover, 15 axon guidance pathway-related genes were associated with SCZ. The association between axon guidance pathway genes and SCZ was validated by a two-stage case-control study on Shandong migrants in northeastern China. Moreover, individuals with the rs9944880 TT polymorphism in the deleted in colorectal cancer (DCC) gene were associated with SCZ. These findings indicate that the axon guidance pathway genes and the rs9944880 SNP in DCC gene are associated with SCZ pathogenesis.

Parkinson's disease research: adopting a more human perspective to accelerate advances

Parkinson's disease (PD) affects 1% of the population over 60 years old and, with global increases in the aging population, presents huge economic and societal burdens. The etiology of PD remains unknown; most cases are idiopathic, presumed to result from genetic and environmental risk factors. Despite 200 years since the first description of PD, the mechanisms behind initiation and progression of the characteristic neurodegenerative processes are not known. Here, we review progress and limitations of the multiple PD animal models available and identify advances that could be implemented to better understand pathological processes, improve disease outcome, and reduce dependence on animal models. Lessons learned from reducing animal use in PD research could serve as guideposts for wider biomedical research.

Computational systems biology approaches for Parkinson's disease

Parkinson's disease (PD) is a prime example of a complex and heterogeneous disorder, characterized by multifaceted and varied motor- and non-motor symptoms and different possible interplays of genetic and environmental risk factors. While investigations of individual PD-causing mutations and risk factors in isolation are providing important insights to improve our understanding of the molecular mechanisms behind PD, there is a growing consensus that a more complete understanding of these mechanisms will require an integrative modeling of multifactorial disease-associated perturbations in molecular networks. Identifying and interpreting the combinatorial effects of multiple PD-associated molecular changes may pave the way towards an earlier and reliable diagnosis and more effective therapeutic interventions. This review provides an overview of computational systems biology approaches developed in recent years to study multifactorial molecular alterations in complex disorders, with a focus on PD research applications. Strengths and weaknesses of different cellular pathway and network analyses, and multivariate machine learning techniques for investigating PD-related omics data are discussed, and strategies proposed to exploit the synergies of multiple biological knowledge and data sources. A final outlook provides an overview of specific challenges and possible next steps for translating systems biology findings in PD to new omics-based diagnostic tools and targeted, drug-based therapeutic approaches.

MicroRNA alterations in iPSC-derived dopaminergic neurons from Parkinson disease patients

MicroRNA (miRNA) misregulation in peripheral blood has been linked to Parkinson disease (PD) but its role in the disease progression remains elusive. We performed an explorative genome-wide study of miRNA expression levels in dopaminergic neurons (DAn) from PD patients generated by somatic cell reprogramming and induced pluripotent stem cells differentiation. We quantified expression levels of 377 miRNAs in DAn from 3 sporadic PD patients (sPD), 3 leucine-rich repeat kinase 2-associated PD patients (L2PD) (total 6 PD), and 4 healthy controls. We identified differential expression of 10 miRNA of which 5 were upregulated in PD (miR-9-5p, miR-135a-5p, miR-135b-5p, miR-449a, and miR-449b-5p) and 5 downregulated (miR-141-3p, miR-199a-5p, miR-299-5p, miR-518e-3p, and miR-519a-3p). Changes were similar in sPD and L2PD. Integrative analysis revealed significant correlations between miRNA/mRNA expression. Moreover, upregulation of miR-9-5p and miR-135b-5p was associated with downregulation of transcription factors related to the DNA hypermethylation of enhancer elements in PD DAn (FOXA1 and NR3C1). In summary, miRNA changes are associated with monogenic L2PD and sPD and co-occur with epigenetic changes in DAn from PD patients.

DLG2, but not TMEM229B, GPNMB, and ITGA8 polymorphism, is associated with Parkinson's disease in a Taiwanese population

Transmembrane or membrane-associated protein dysfunction is increasingly recognized as an important mechanism of pathogenesis in Parkinson's disease (PD). Previous genome-wide association studies and their meta-analysis in PD genes have identified several risk foci in transmembrane protein-encoding genes. Herein, we investigated the effect of 4 such PD-associated genetic variants reported in Caucasians, including discs-large membrane-associated guanylate kinase scaffolding protein 2 (DLG2 rs3793947), transmembrane protein 229B (TMEM229B rs1555399), glycoprotein nonmetastatic melanoma protein B (GPNMB rs199347), and integrin subunit alpha 8 (ITGA8 rs7077361). A total of 1185 Taiwanese subjects comprising 592 PD patients and 593 unrelated age-matched controls were genotyped. DLG2 rs3793947 AA genotype showed a significantly lower prevalence in female PD patients compared to the female controls (p = 0.019). The recessive model analysis also demonstrated a reduced PD risk for females in AA genotype (odds ratio = 0.573, 95% confidence interval: 0.379-0.868, p = 0.008). The frequencies of TMEM229B rs1555399 and GPNMB rs199347 genotypes and alleles were similar in PD patients and controls. ITG8 rs7077361 was not polymorphic in all subjects of this study. These data suggested that DLG2, but not TMEM229B, GPNMB, and ITGA8, influenced the risk of PD in Taiwan.

Repulsive Guidance Molecule a (RGMa) Induces Neuropathological and Behavioral Changes That Closely Resemble Parkinson's Disease

Repulsive guidance molecule member a (RGMa) is a membrane-associated or released guidance molecule that is involved in axon guidance, cell patterning, and cell survival. In our previous work, we showed that RGMa is significantly upregulated in the substantia nigra of patients with Parkinson's disease. Here we demonstrate the expression of RGMa in midbrain human dopaminergic (DA) neurons. To investigate whether RGMa might model aspects of the neuropathology of Parkinson's disease in mouse, we targeted RGMa to adult midbrain dopaminergic neurons using adeno-associated viral vectors. Overexpression of RGMa resulted in a progressive movement disorder, including motor coordination and imbalance, which is typical for a loss of DA release in the striatum. In line with this, RGMa induced selective degeneration of dopaminergic neurons in the substantia nigra (SN) and affected the integrity of the nigrostriatal system. The degeneration of dopaminergic neurons was accompanied by a strong microglia and astrocyte activation. The behavioral, molecular, and anatomical changes induced by RGMa in mice are remarkably similar to the clinical and neuropathological hallmarks of Parkinson's disease. Our data indicate that dysregulation of RGMa plays an important role in the pathology of Parkinson's disease, and antibody-mediated functional interference with RGMa may be a disease modifying treatment option.SIGNIFICANCE STATEMENT Parkinson's disease (PD) is a neurodegenerative disease characterized by severe motor dysfunction due to progressive degeneration of mesencephalic dopaminergic (DA) neurons in the substantia nigra. To date, there is no regenerative treatment available. We previously showed that repulsive guidance molecule member a (RGMa) is upregulated in the substantia nigra of PD patients. Adeno-associated virus-mediated targeting of RGMa to mouse DA neurons showed that overexpression of this repulsive axon guidance and cell patterning cue models the behavioral and neuropathological characteristics of PD in a remarkable way. These findings have implications for therapy development as interfering with the function of this specific axon guidance cue may be beneficial to the survival of DA neurons.

Genome-wide pathway analysis identifies VEGF pathway association with oral ulceration in systemic lupus erythematosus

Background

Systemic lupus erythematosus (SLE) is a genetically complex rheumatic disease characterized by heterogeneous clinical manifestations of unknown etiology. Recent studies have suggested the existence of a genetic basis for SLE heterogeneity. The objective of the present study was to identify new genetic variation associated with the clinically relevant phenotypes in SLE.

Methods

A two-stage pathway-based approach was used to identify the genetic variation associated with the main clinical phenotypes in SLE. In the discovery stage, 482 SLE patients were genotyped using Illumina Human Quad610 microarrays. Association between 798 reference genetic pathways from the Molecular Signatures Database and 11 SLE phenotypes was tested using the set-based method implemented in PLINK software. Pathways significantly associated after multiple test correction were subsequently tested for replication in an independent cohort of 425 SLE patients. Using an in silico approach, we analyzed the functional effects of common SLE therapies on the replicated genetic pathways. The association of known SLE risk variants with the development of the clinical phenotypes was also analyzed.

Results

In the discovery stage, we found a significant association between the vascular endothelial growth factor (VEGF) pathway and oral ulceration (P value for false discovery rate (P_FDR) < 0.05), and between the negative regulation signaling pathway of retinoic acid inducible gene-I/melanoma differentiation associated gene 5 and the production of antinuclear antibodies (P_FDR < 0.05). In the replication stage, we validated the association between the VEGF pathway and oral ulceration. Therapies commonly used to treat mucocutaneous phenotypes in SLE were found to strongly influence VEGF pathway gene expression (P = 4.60e-4 to 5.38e-14). Analysis of known SLE risk loci identified a strong association between PTPN22 and the risk of hematologic disorder and with the development of antinuclear antibodies.

Conclusions

The present study has identified VEGF genetic pathway association with the risk of oral ulceration in SLE. New therapies targeting the VEGF pathway could be more effective in reducing the severity of this phenotype. These findings represent a first step towards the understanding of the genetic basis of phenotype heterogeneity in SLE.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-017-1345-6) contains supplementary material, which is available to authorized users.

Concordance analysis of microarray studies identifies representative gene expression changes in Parkinson's disease: a comparison of 33 human and animal studies

BACKGROUND

As the popularity of transcriptomic analysis has grown, the reported lack of concordance between different studies of the same condition has become a growing concern, raising questions as to the representativeness of different study types, such as non-human disease models or studies of surrogate tissues, to gene expression in the human condition.

METHODS

In a comparison of 33 microarray studies of Parkinson's disease, correlation and clustering analyses were used to determine the factors influencing concordance between studies, including agreement between different tissue types, different microarray platforms, and between neurotoxic and genetic disease models and human Parkinson's disease.

RESULTS

Concordance over all studies is low, with correlation of only 0.05 between differential gene expression signatures on average, but increases within human patients and studies of the same tissue type, rising to 0.38 for studies of human substantia nigra. Agreement of animal models, however, is dependent on model type. Studies of brain tissue from Parkinson's disease patients (specifically the substantia nigra) form a distinct group, showing patterns of differential gene expression noticeably different from that in non-brain tissues and animal models of Parkinson's disease; while comparison with other brain diseases (Alzheimer's disease and brain cancer) suggests that the mixed study types display a general signal of neurodegenerative disease. A meta-analysis of these 33 microarray studies demonstrates the greater ability of studies in humans and highly-affected tissues to identify genes previously known to be associated with Parkinson's disease.

CONCLUSIONS

The observed clustering and concordance results suggest the existence of a 'characteristic' signal of Parkinson's disease found in significantly affected human tissues in humans. These results help to account for the consistency (or lack thereof) so far observed in microarray studies of Parkinson's disease, and act as a guide to the selection of transcriptomic studies most representative of the underlying gene expression changes in the human disease.

Red hair, MC1R variants, and risk for Parkinson's disease - a meta-analysis

Several studies have been conducted with mixed results since our initial report of increased Parkinson's disease risk in individuals with red hair and/or red hair‐associated p.R151C variant of the MC1R gene, both of which confer high melanoma risk. We performed a meta‐analysis of six publications on red hair, MC1R, and Parkinson's disease. We found that red hair (pooled odds ratios = 1.68, 95% confidence intervals: 1.07, 2.64) and p.R151C (pooled odds ratios = 1.10, 95% confidence intervals: 1.00, 1.21), but not p.R160W, were associated with greater risk for Parkinson's disease. Our results support potential roles of pigmentation and its key regulator MC1R in the pathogenesis of Parkinson's disease.

Genome-wide pathway-based association analysis identifies risk pathways associated with Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disease. It is generally believed that it is influenced by both genetic and environmental factors, but the precise pathogenesis of PD is unknown to date. In this study, we performed a pathway analysis based on genome-wide association study (GWAS) to detect risk pathways of PD in three GWAS datasets. We first mapped all SNP markers to autosomal genes in each GWAS dataset. Then, we evaluated gene risk values using the minimum P-value of the tagSNPs. We took a pathway as a unit to identify the risk pathways based on the cumulative risks of the genes in the pathway. Finally, we combine the analysis results of the three datasets to detect the high risk pathways associated with PD. We found there were five same pathways in the three datasets. Besides, we also found there were five pathways which were shared in two datasets. Most of these pathways are associated with nervoussystem. Five pathways had been reported to be PD-related pathways in the previous literature. Our findings also implied that there was a close association between immune response and PD. Continued investigation of these pathways will further help us explain the pathogenesis of PD.

Identification of disease-associated pathways in pancreatic cancer by integrating genome-wide association study and gene expression data

In order to additionally understand the pathogenesis of pancreatic cancer (PC), the present study conducted pathway analysis based on genome-wide association study (GWAS) and gene expression data to predict genes that are associated with PC. GWAS data (accession no., pha002874.1) were downloaded from National Center for Biotechnology Information (NCBI) database of Genotypes and Phenotypes, which included data concerning 1,896 patients with PC and 1,939 control individuals. Gene expression data [accession no., GSE23952; human pancreatic carcinoma Panc-1 transforming growth factor-β (TGF-β) treatment assay] were downloaded from NCBI Gene Expression Omnibus. Gene set enrichment analysis was used to identify significant pathways in the GWAS or gene expression profiles. Meta-analysis was performed based on pathway analysis of the two data sources. In total, 58 and 280 pathways were identified to be significant in the GWAS and gene expression data, respectively, with 7 pathways significant in both the data profiles. Hsa 04350 TGF-β signaling pathway had the smallest meta P-value. Other significant pathways in the two data sources were negative regulation of DNA-dependent transcription, the nucleolus, negative regulation of RNA metabolic process, the cellular defense response, exocytosis and galactosyltransferase activity. By constructing the gene-pathway network, 5 pathways were closely associated, apart from exocytosis and galactosyltransferase activity pathways. Among the 7 pathways, 11 key genes (2.9% out of a total of 380 genes) from the GWAS data and 43 genes (10.5% out of a total of 409 genes) from the gene expression data were differentially expressed. Only Abelson murine leukemia viral oncogene homolog 1 from the nucleolus pathway was significantly expressed in by both data sources. Overall, the results of the present analysis provide possible factors for the occurrence of PC, and the identification of the pathways and genes associated with PC provides valuable data for investigating the pathogenesis of PC in future studies.

SUR1 Receptor Interaction with Hesperidin and Linarin Predicts Possible Mechanisms of Action of Valeriana officinalis in Parkinson

Parkinson's disease (PD) is one of the most common neurodegenerative disorders. A theoretical approach of our previous experiments reporting the cytoprotective effects of the Valeriana officinalis compounds extract for PD is suggested. In addiction to considering the PD as a result of mitochondrial metabolic imbalance and oxidative stress, such as in our previous in vitro model of rotenone, in the present manuscript we added a genomic approach to evaluate the possible underlying mechanisms of the effect of the plant extract. Microarray of substantia nigra (SN) genome obtained from Allen Brain Institute was analyzed using gene set enrichment analysis to build a network of hub genes implicated in PD. Proteins transcribed from hub genes and their ligands selected by search ensemble approach algorithm were subjected to molecular docking studies, as well as 20 ns Molecular Dynamics (MD) using a Molecular Mechanic Poison/Boltzman Surface Area (MMPBSA) protocol. Our results bring a new approach to Valeriana officinalis extract, and suggest that hesperidin, and probably linarin are able to relieve effects of oxidative stress during ATP depletion due to its ability to binding SUR1. In addition, the key role of valerenic acid and apigenin is possibly related to prevent cortical hyperexcitation by inducing neuronal cells from SN to release GABA on brain stem. Thus, under hyperexcitability, oxidative stress, asphyxia and/or ATP depletion, Valeriana officinalis may trigger different mechanisms to provide neuronal cell protection.

Neurological Diseases from a Systems Medicine Point of View

The difficulty to understand, diagnose, and treat neurological disorders stems from the great complexity of the central nervous system on different levels of physiological granularity. The individual components, their interactions, and dynamics involved in brain development and function can be represented as molecular, cellular, or functional networks, where diseases are perturbations of networks. These networks can become a useful research tool in investigating neurological disorders if they are properly tailored to reflect corresponding mechanisms. Here, we review approaches to construct networks specific for neurological disorders describing disease-related pathology on different scales: the molecular, cellular, and brain level. We also briefly discuss cross-scale network analysis as a necessary integrator of these scales.

The EIF4G1 gene and Parkinson's disease

Variants in the EIF4G1 gene have been recently identified to be responsible for autosomal dominant PD (PARK18), but its role in the PD-related neurodegeneration is unclear. Several EIF4G1 mutation/variants were found to be associated with PD, and functional studies have suggested that these variants may impair the ability of cells to rapidly and dynamically respond to stress, thus probably participating in the development of PD, and these indicated that EIF4G1 variants may play an important role in pathogenicity of PD, although the frequency is low. Further studies involving large sample size of patients with PD from diverse populations, as well as studies of EIF4G1 expression and in scaffold function, are warranted.

A Pooling Genome-Wide Association Study Combining a Pathway Analysis for Typical Sporadic Parkinson's Disease in the Han Population of Chinese Mainland

Genome-wide association studies (GWAS) on sporadic Parkinson's disease (sPD) are mainly conducted in European and American populations at present, and the Han populations of Chinese mainland (HPCM) almost have not been studied yet. Here, we conducted a pooling GWAS combining a pathway analysis with 862,198 autosomal single nucleotide polymorphisms of IlluminaHumanOmniZhongHua-8 in 250 sPD and 250 controls from HPCM precluded toxicant exposure, age, and heavy coffee drinking habit interference. We revealed that among the 22 potential loci implicated, PRDM2/KIAA1026 (kgp8090149), TSG1/MANEA (kgp154172), PDE10A (kgp8130520), MDGA2 (rs9323124), ATPBD4/LOC100288892 (kgp11333367), ZFP64/TSHZ2 (kgp4156164), PAQR3/ARD1B (kgp9482779), FLJ23172/FNDC3B (kgp760898), C18orf1 (kgp348599), FLJ43860/NCRNA00051 (kgp4105983), CYP1B1/C2orf58 (kgp11353523), WNT9A/LOC728728 (rs849898), ANXA1/LOC100130911 (rs10746953), FLJ35379/LOC100132423 (kgp9550589), PLEKHN1 (kgp7172368), DMRT2/SMARCA2 (kgp10769919), ZNF396/INO80C (rs1362858), C3orf67/LOC339902 (rs6783485), LOC285194/IGSF11 (rs1879553), FGF10/MRPS30 (rs13153459), BARX1/PTPDC1 (kgp6542803), and COL5 A2 (rs11186), the peak significance was at the kgp4105983 of FLJ43860 gene in chromosome 8, the first top strongest associated locus with sPD was PRDM2 (kgp8090149) in chromosome 1, and the 24 pathways including 100 significantly associated genes were strongly associated with sPD from HPCM. The 40 genes were shared by at least two pathways. The most possible associated pathways with sPD were axon guidance, ECM-receptor interaction, neuroactive ligand-receptor interaction, tight junction, focal adhesion, gap junction, long-term depression, drug metabolism-cytochrome P450, adherens junction, endocytosis, and protein digestion and absorption. Our results indicated that these loci, pathways, and their related genes might be involved in the pathogenesis of sPD from HPCM and provided some novel evidences for further searching the genetic pathogenesis of sPD.

Genetics of aging, health, and survival: dynamic regulation of human longevity related traits

Background: The roles of genetic factors in human longevity would be better understood if one can use more efficient methods in genetic analyses and investigate pleiotropic effects of genetic variants on aging and health related traits.

Data and methods: We used EMMAX software with modified correction for population stratification to perform genome wide association studies (GWAS) of female lifespan from the original FHS cohort. The male data from the original FHS cohort and male and female data combined from the offspring FHS cohort were used to confirm findings. We evaluated pleiotropic effects of selected genetic variants as well as gene-smoking interactions on health and aging related traits. Then we reviewed current knowledge on functional properties of genes related to detected variants.

Results: The eight SNPs with genome-wide significant variants were negatively associated with lifespan in both males and females. After additional QC, two of these variants were selected for further analyses of their associations with major diseases (cancer and CHD) and physiological aging changes. Gene-smoking interactions contributed to these effects. Genes closest to detected variants appear to be involved in similar biological processes and health disorders, as those found in other studies of aging and longevity e.g., in cancer and neurodegeneration.

Conclusions: The impact of genes on longevity may involve trade-off-like effects on different health traits. Genes that influence lifespan represent various molecular functions but may be involved in similar biological processes and health disorders, which could contribute to genetic heterogeneity of longevity and the lack of replication in genetic association studies.

Complex network-driven view of genomic mechanisms underlying Parkinson's disease: analyses in dorsal motor vagal nucleus, locus coeruleus, and substantia nigra

Parkinson's disease (PD)—classically characterized by severe loss of dopaminergic neurons in the substantia nigra pars compacta—has a caudal-rostral progression, beginning in the dorsal motor vagal nucleus and, in a less extent, in the olfactory system, progressing to the midbrain and eventually to the basal forebrain and the neocortex. About 90% of the cases are idiopathic. To study the molecular mechanisms involved in idiopathic PD we conducted a comparative study of transcriptional interaction networks in the dorsal motor vagal nucleus (VA), locus coeruleus (LC), and substantia nigra (SN) of idiopathic PD in Braak stages 4-5 (PD) and disease-free controls (CT) using postmortem samples. Gene coexpression networks (GCNs) for each brain region (patients and controls) were obtained to identify highly connected relevant genes (hubs) and densely interconnected gene sets (modules). GCN analyses showed differences in topology and module composition between CT and PD networks for each anatomic region. In CT networks, VA, LC, and SN hub modules are predominantly associated with neuroprotection and homeostasis in the ageing brain, whereas in the patient's group, for the three brain regions, hub modules are mostly related to stress response and neuron survival/degeneration mechanisms.

Systems-based analyses of brain regions functionally impacted in Parkinson's disease reveals underlying causal mechanisms

Detailed analysis of disease-affected tissue provides insight into molecular mechanisms contributing to pathogenesis. Substantia nigra, striatum, and cortex are functionally connected with increasing degrees of alpha-synuclein pathology in Parkinson's disease. We undertook functional and causal pathway analysis of gene expression and proteomic alterations in these three regions, and the data revealed pathways that correlated with disease progression. In addition, microarray and RNAseq experiments revealed previously unidentified causal changes related to oligodendrocyte function and synaptic vesicle release, and these and other changes were reflected across all brain regions. Importantly, subsets of these changes were replicated in Parkinson's disease blood; suggesting peripheral tissue may provide important avenues for understanding and measuring disease status and progression. Proteomic assessment revealed alterations in mitochondria and vesicular transport proteins that preceded gene expression changes indicating defects in translation and/or protein turnover. Our combined approach of proteomics, RNAseq and microarray analyses provides a comprehensive view of the molecular changes that accompany functional loss and alpha-synuclein pathology in Parkinson's disease, and may be instrumental to understand, diagnose and follow Parkinson's disease progression.

Large scale analysis of phenotype-pathway relationships based on GWAS results

The widely used pathway-based approach for interpreting Genome Wide Association Studies (GWAS), assumes that since function is executed through the interactions of multiple genes, different perturbations of the same pathway would result in a similar phenotype. This assumption, however, was not systemically assessed on a large scale. To determine whether SNPs associated with a given complex phenotype affect the same pathways more than expected by chance, we analyzed 368 phenotypes that were studied in >5000 GWAS. We found 216 significant phenotype-pathway associations between 70 of the phenotypes we analyzed and known pathways. We also report 391 strong phenotype-phenotype associations between phenotypes that are affected by the same pathways. While some of these associations confirm previously reported connections, others are new and could shed light on the molecular basis of these diseases. Our findings confirm that phenotype-associated SNPs cluster into pathways much more than expected by chance. However, this is true for <20% (70/368) of the phenotypes. Different types of phenotypes show markedly different tendencies: Virtually all autoimmune phenotypes show strong clustering of SNPs into pathways, while most cancers and metabolic conditions, and all electrophysiological phenotypes, could not be significantly associated with any pathway despite being significantly associated with a large number of SNPs. While this may be due to missing data, it may also suggest that these phenotypes could result only from perturbations of specific genes and not from other perturbations of the same pathway. Further analysis of pathway-associated versus gene-associated phenotypes is, therefore, needed in order to understand disease etiology and in order to promote better drug target selection.

Interactions between cell adhesion and the synaptic vesicle cycle in Parkinson's disease

Synaptic dysfunction has been identified as an early neuropathologic event in Parkinson's disease. Synapses depend critically on the adhesion of neurons to one another, glial cells, and the extracellular matrix. Cell-cell and cell-matrix adhesions regulate the structure and function of synapses, in part, through interactions with structural elements such as actin and microtubule proteins. These proteins are critical not only for neuronal structure and polarity, but also for the synaptic vesicle cycle, including maintenance of and transfer between vesicle pools, exocytosis, and vesicle recycling. Pathway analyses of genome wide association studies (GWAS) in Parkinson's disease have identified frequent single nucleotide polymorphisms (SNPs) in cell adhesion pathways, suggesting that dysfunction in cell adhesion may play a role in disease pathology. Based on these observations, it may be hypothesized that Parkinson's disease is due to synaptic dysfunction caused by genetic variations in cell adhesion pathways that affect actin and/or microtubule-mediated events in the synaptic vesicle cycle. Furthermore, it is hypothesized that cells with pacemaker-like activity-a characteristic of neurons that degenerate in Parkinson's disease-may depend more on actin for recruiting synaptic vesicles for release than do less active neurons, thereby enhancing their sensitivity to SNPs in cell adhesion pathways and explaining the selectivity of neurodegeneration. Cells may ultimately die due to detachment from the extracellular matrix. This hypothesis suggests that further exploration of cell adhesion pathways and their linkage to neurotransmitter release through cell structural proteins such as actin and microtubules may provide important insights into Parkinson's disease.

Detecting genetic interactions in pathway-based genome-wide association studies

Pathway-based genome-wide association studies (GWAS) can exploit collective effects of causal variants in a pathway to increase power of detection. However, current methods for pathway-based GWAS do not consider epistatic effects of genetic variants, although interactions between genetic variants may play an important role in influencing complex traits. In this paper, we employed a Bayesian Lasso logistic regression model for pathway-based GWAS to include all possible main effects and a large number of pairwise interactions of single nucleotide polymorphisms (SNPs) in a pathway, and then inferred the model with an efficient group empirical Bayesian Lasso (EBLasso) method. Using the inferred model, the statistical significance of a pathway was tested with the Wald statistics. Reliable effects in a significant pathway were selected using the stability selection technique. Extensive computer simulations demonstrated that our group EBlasso method significantly outperformed two competitive methods in most simulation setups and offered similar performance in other simulation setups. When applying to a GWAS dataset for Parkinson disease, EBLasso identified three significant pathways including the primary bile acid biosynthesis pathway, the neuroactive ligand-receptor interaction, and the MAPK signaling pathway. All effects identified in the primary bile acid biosynthesis pathway and many of effects in the other two pathways were epistatic effects. The group EBLasso method provides a valuable tool for pathway-based GWAS to identify main and epistatic effects of genetic variants.

Genome-wide association study combining pathway analysis for typical sporadic amyotrophic lateral sclerosis in Chinese Han populations

Sporadic amyotrophic lateral sclerosis (sALS) is a severe neurodegenerative disease that causes progressive motor neuron death. Although the etiology of sALS remains unknown, genetic variants are thought to predispose individuals to the disease. Several recent genome-wide association studies have identified a number of loci that increase sALS susceptibility, but these only explain a small proportion of the disease. To extend the current genetic evidence and to identify novel candidates of sALS, we performed a pooling genome-wide association study by 859,311 autosomal single-nucleotide polymorphisms of IlluminaHumanOmniZhongHua-8 combining pathway analysis in 250 typical sALS cases precluding age, clinical course, and phenotype interference and 250 control subjects from Chinese Han populations (CHP). The results revealed that 8 novel loci of 1p34.3, 3p21.1, 3p22.2, 10p15.2, 22q12.1, 3q13.11, 11q25, 12q24.33, and 5 previously reported loci of CNTN4 (kgp11325216), ATXN1 (kgp8327591), C9orf72 (kgp6016770), ITPR2 (kgp3041552), and SOD1 (kgp10760302) were associated with sALS from CHP. Furthermore, the pathway analysis based on the Gene Set Analysis Toolkit V2 showed that 10 top pathways were strongly associated with sALS from CHP, and among them, the 7 most potentially candidate pathways were phosphatidylinositol signaling system, Wnt signaling pathway, axon guidance, MAPK signaling pathway, neurotrophin signaling pathway, arachidonic acid metabolism, and T-cell receptor signaling pathway, a total of 39 significantly associate genes in 7 candidate pathways was suggested to involve in the pathogenesis of sALS from CHP. In conclusion, our results revealed several new loci and pathways related to sALS from CHP and extend the association evidence for partial loci, genes, and pathways, which were previously identified in other populations. Thus, our data provided new clues for exploring the pathogenesis of sALS.

Integrative network analysis unveils convergent molecular pathways in Parkinson's disease and diabetes

Background

Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level.

Methods and Findings

Using a random walk algorithm within the human functional linkage network we identified a molecular cluster of 478 neighboring genes closely associated with confirmed Parkinson's disease and type 2 diabetes genes. Biological and functional analysis identified the protein serine-threonine kinase activity, MAPK cascade, activation of the immune response, and insulin receptor and lipid signaling as convergent pathways. Integration of results from microarrays studies identified a blood signature comprising seven genes whose expression is dysregulated in Parkinson's disease and type 2 diabetes. Among this group of genes, is the amyloid precursor protein (APP), previously associated with neurodegeneration and insulin regulation. Quantification of RNA from whole blood of 192 samples from two independent clinical trials, the Harvard Biomarker Study (HBS) and the Prognostic Biomarker Study (PROBE), revealed that expression of APP is significantly upregulated in Parkinson's disease patients compared to healthy controls. Assessment of biomarker performance revealed that expression of APP could distinguish Parkinson's disease from healthy individuals with a diagnostic accuracy of 80% in both cohorts of patients.

Conclusions

These results provide the first evidence that Parkinson's disease and diabetes are strongly linked at the molecular level and that shared molecular networks provide an additional source for identifying highly sensitive biomarkers. Further, these results suggest for the first time that increased expression of APP in blood may modulate the neurodegenerative phenotype in type 2 diabetes patients.