Informing disease modelling with brain-relevant functional genomic annotations

The past decade has seen a surge in the number of disease/trait-associated variants, largely because of the union of studies to share genetic data and the availability of electronic health records from large cohorts for research use. Variant discovery for neurological and neuropsychiatric genome-wide association studies, including schizophrenia, Parkinson's disease and Alzheimer's disease, has greatly benefitted; however, the translation of these genetic association results to interpretable biological mechanisms and models is lagging. Interpreting disease-associated variants requires knowledge of gene regulatory mechanisms and computational tools that permit integration of this knowledge with genome-wide association study results. Here, we summarize key conceptual advances in the generation of brain-relevant functional genomic annotations and amongst tools that allow integration of these annotations with association summary statistics, which together provide a new and exciting opportunity to identify disease-relevant genes, pathways and cell types in silico. We discuss the opportunities and challenges associated with these developments and conclude with our perspective on future advances in annotation generation, tool development and the union of the two

ATP regulates the differentiation of mammalian skeletal muscle by activation of a P2X5 receptor on satellite cells

ATP is well known for its role as an intracellular energy source. However, there is increasing awareness of its role as an extracellular messenger molecule (Burnstock, 1997). Although evidence for the presence of receptors for extracellular ATP on skeletal myoblasts was first published in 1983 (Kolb and Wakelam), their physiological function has remained unclear. In this paper we used primary cultures of rat skeletal muscle satellite cells to investigate the role of purinergic signaling in muscle formation. Using immunocytochemistry, RT-PCR, and electrophysiology, we demonstrate that the ionotropic P2X5 receptor is present on satellite cells and that activation of a P2X receptor inhibits proliferation, stimulates expression of markers of muscle cell differentiation, including myogenin, p21, and myosin heavy chain, and increases the rate of myotube formation. Furthermore, we demonstrate that ATP application results in a significant and rapid increase in the phosphorylation of MAPKs, particularly p38, and that inhibition of p38 activity can prevent the effect of ATP on cell number. These results not only demonstrate the existence of a novel regulator of skeletal muscle differentiation, namely ATP, but also a new role for ionotropic P2X receptors in the control of cell fate

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

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

Mitochondrial-nuclear cross-talk in the human brain is modulated by cell type and perturbed in neurodegenerative disease

Mitochondrial dysfunction contributes to the pathogenesis of many neurodegenerative diseases. The mitochondrial genome encodes core respiratory chain proteins, but the vast majority of mitochondrial proteins are nuclear-encoded, making interactions between the two genomes vital for cell function. Here, we examine these relationships by comparing mitochondrial and nuclear gene expression across different regions of the human brain in healthy and disease cohorts. We find strong regional patterns that are modulated by cell-type and reflect functional specialisation. Nuclear genes causally implicated in sporadic Parkinson's and Alzheimer's disease (AD) show much stronger relationships with the mitochondrial genome than expected by chance, and mitochondrial-nuclear relationships are highly perturbed in AD cases, particularly through synaptic and lysosomal pathways, potentially implicating the regulation of energy balance and removal of dysfunction mitochondria in the etiology or progression of the disease. Finally, we present MitoNuclearCOEXPlorer, a tool to interrogate key mitochondria-nuclear relationships in multi-dimensional brain data

Brain iron accumulation affects myelin-related molecular systems implicated in a rare neurogenetic disease family with neuropsychiatric features

The ‘neurodegeneration with brain iron accumulation’ (NBIA) disease family entails movement or cognitive impairment, often with psychiatric features. To understand how iron loading affects the brain, we studied mice with disruption of two iron regulatory genes, hemochromatosis (Hfe) and transferrin receptor 2 (Tfr2). Inductively coupled plasma atomic emission spectroscopy demonstrated increased iron in the Hfe-/- × Tfr2mut brain (P=0.002, n =5/group), primarily localized by Perls’ staining to myelinated structures. Western immunoblotting showed increases of the iron storage protein ferritin light polypeptide and microarray and real-time reverse transcription-PCR revealed decreased transcript levels (P<0.04, n =5/group) for five other NBIA genes, phospholipase A2 group VI, fatty acid 2-hydroxylase, ceruloplasmin, chromosome 19 open reading frame 12 and ATPase type 13A2. Apart from the ferroxidase ceruloplasmin, all are involved in myelin homeostasis; 16 other myelin-related genes also showed reduced expression (P<0.05), although gross myelin structure and integrity appear unaffected (P>0.05). Overlap (P<0.0001) of differentially expressed genes in Hfe-/- × Tfr2mut brain with human gene co-expression networks suggests iron loading influences expression of NBIA-related and myelin-related genes co-expressed in normal human basal ganglia. There was overlap (P<0.0001) of genes differentially expressed in Hfe-/- × Tfr2mut brain and post-mortem NBIA basal ganglia. Hfe-/- × Tfr2mut mice were hyperactive (P<0.0112) without apparent cognitive impairment by IntelliCage testing (P>0.05). These results implicate myelin-related systems involved in NBIA neuropathogenesis in early responses to iron loading. This may contribute to behavioral symptoms in NBIA and hemochromatosis and is relevant to patients with abnormal iron status and psychiatric disorders involving myelin abnormalities or resistant to conventional treatments

An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks

Background: Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used R software package for the generation of gene co-expression networks (GCN). WGCNA generates both a GCN and a derived partitioning of clusters of genes (modules). We propose k-means clustering as an additional processing step to conventional WGCNA, which we have implemented in the R package km2gcn (k-means to gene co-expression network, https://github.com/juanbot/km2gcn). Results: We assessed our method on networks created from UKBEC data (10 different human brain tissues), on networks created from GTEx data (42 human tissues, including 13 brain tissues), and on simulated networks derived from GTEx data. We observed substantially improved module properties, including: (1) few or zero misplaced genes; (2) increased counts of replicable clusters in alternate tissues (x3.1 on average); (3) improved enrichment of Gene Ontology terms (seen in 48/52 GCNs) (4) improved cell type enrichment signals (seen in 21/23 brain GCNs); and (5) more accurate partitions in simulated data according to a range of similarity indices. Conclusions: The results obtained from our investigations indicate that our k-means method, applied as an adjunct to standard WGCNA, results in better network partitions. These improved partitions enable more fruitful downstream analyses, as gene modules are more biologically meaningful

Gene co-expression networks shed light into diseases of brain iron accumulation

Aberrant brain iron deposition is observed in both common and rare neurodegenerative disorders, including those categorized as Neurodegeneration with Brain Iron Accumulation (NBIA), which are characterized by focal iron accumulation in the basal ganglia. Two NBIA genes are directly involved in iron metabolism, but whether other NBIA-related genes also regulate iron homeostasis in the human brain, and whether aberrant iron deposition contributes to neurodegenerative processes remains largely unknown. This study aims to expand our understanding of these iron overload diseases and identify relationships between known NBIA genes and their main interacting partners by using a systems biology approach. We used whole-transcriptome gene expression data from human brain samples originating from 101 neuropathologically normal individuals (10 brain regions) to generate weighted gene co-expression networks and cluster the 10 known NBIA genes in an unsupervised manner. We investigated NBIA-enriched networks for relevant cell types and pathways, and whether they are disrupted by iron loading in NBIA diseased tissue and in an in vivo mouse model. We identified two basal ganglia gene co-expression modules significantly enriched for NBIA genes, which resemble neuronal and oligodendrocytic signatures. These NBIA gene networks are enriched for iron-related genes, and implicate synapse and lipid metabolism related pathways. Our data also indicates that these networks are disrupted by excessive brain iron loading. We identified multiple cell types in the origin of NBIA disorders. We also found unforeseen links between NBIA networks and iron-related processes, and demonstrate convergent pathways connecting NBIAs and phenotypically overlapping diseases. Our results are of further relevance for these diseases by providing candidates for new causative genes and possible points for therapeutic intervention

CoExp: A Web Tool for the Exploitation of Co-expression Networks

Gene co-expression networks are a powerful type of analysis to construct gene groupings based on transcriptomic profiling. Co-expression networks make it possible to discover modules of genes whose mRNA levels are highly correlated across samples. Subsequent annotation of modules often reveals biological functions and/or evidence of cellular specificity for cell types implicated in the tissue being studied. There are multiple ways to perform such analyses with weighted gene co-expression network analysis (WGCNA) amongst one of the most widely used R packages. While managing a few network models can be done manually, it is often more advantageous to study a wider set of models derived from multiple independently generated transcriptomic data sets (e.g., multiple networks built from many transcriptomic sources). However, there is no software tool available that allows this to be easily achieved. Furthermore, the visual nature of co-expression networks in combination with the coding skills required to explore networks, makes the construction of a web-based platform for their management highly desirable. Here, we present the CoExp Web application, a user-friendly online tool that allows the exploitation of the full collection of 109 co-expression networks provided by the CoExpNets suite of R packages. We describe the usage of CoExp, including its contents and the functionality available through the family of CoExpNets packages. All the tools presented, including the web front- and back-ends are available for the research community so any research group can build its own suite of networks and make them accessible through their own CoExp Web application. Therefore, this paper is of interest to both researchers wishing to annotate their genes of interest across different brain network models and specialists interested in the creation of GCNs looking for a tool to appropriately manage, use, publish, and share their networks in a consistent and productive manner