Huntington's disease: degradation of mutant huntingtin by autophagy

Autophagy is a nonspecific bulk degradation pathway for long-lived cytoplasmic proteins, protein complexes, or damaged organelles. This process is also a major degradation pathway for many aggregate-prone, disease-causing proteins associated with neurodegenerative disorders, such as mutant huntingtin in Huntington's disease. In this review, we discuss factors regulating the degradation of mutant huntingtin by autophagy. We also report the growing list of new drugs/pathways that upregulate autophagy to enhance the clearance of this mutant protein, as autophagy upregulation may be a tractable strategy for the treatment of Huntington's disease.     

Mutations in a BTB-Kelch Protein, KLHL7, Cause Autosomal-Dominant Retinitis Pigmentosa

Retinitis pigmentosa (RP) refers to a genetically heterogeneous group of progressive neurodegenerative diseases that result in dysfunction and/or death of rod and cone photoreceptors in the retina. So far, 18 genes have been identified for autosomal-dominant (ad) RP. Here, we describe an adRP locus (RP42) at chromosome 7p15 through linkage analysis in a six-generation Scandinavian family and identify a disease-causing mutation, c.449G→A (p.S150N), in exon 6 of the KLHL7 gene. Mutation screening of KLHL7 in 502 retinopathy probands has revealed three different missense mutations in six independent families. KLHL7 is widely expressed, including expression in rod photoreceptors, and encodes a 75 kDa protein of the BTB-Kelch subfamily within the BTB superfamily. BTB-Kelch proteins have been implicated in ubiquitination through Cullin E3 ligases. Notably, all three putative disease-causing KLHL7 mutations are within a conserved BACK domain; homology modeling suggests that mutant amino acid side chains can potentially fill the cleft between two helices, thereby affecting the ubiquitination complexes. Mutations in an identical region of another BTB-Kelch protein, gigaxonin, have previously been associated with giant axonal neuropathy. Our studies suggest an additional role of the ubiquitin-proteasome protein-degradation pathway in maintaining neuronal health and in disease.     

Evolutionary conservation and disease gene association of the human genes composing pseudogenes

Pseudogenes, the 'genomic fossils' present portrayal of evolutionary history of human genome. The human genes configuring pseudogenes are also now coming forth as important resources in the study of human protein evolution. In this communication, we explored evolutionary conservation of the genes forming pseudogenes over the genes lacking any pseudogene and delving deeper, we probed an evolutionary rate difference between the disease genes in the two groups. We illustrated this differential evolutionary pattern by gene expressivity, number of regulatory miRNA targeting per gene, abundance of protein complex forming genes and lesser percentage of protein intrinsic disorderness. Furthermore, pseudogenes are observed to harbor sequence variations, over their entirety, those become degenerative disease-causing mutations though the disease involvement of their progenitors is still unexplored. Here, we unveiled an immense association of disease genes in the genes casting pseudogenes in human. We interpreted the issue by disease associated miRNA targeting, genes containing polymorphisms in miRNA target sites, abundance of genes having disease causing non-synonymous mutations, disease gene specific network properties, presence of genes having repeat regions, affluence of dosage sensitive genes and the presence of intrinsically unstructured protein regions.     

A homolog of the proteasome-related RING10 gene is essential for yeast cell growth.

Proteasomes are intracellular protein complexes displaying multiproteolytic activities. These complexes have been implicated in the antigen degradation process that generates peptides associated with the major histocompatibility complex (MHC) class-I molecule. RING10 and RING12 are genes encoded by the class-II region of the human MHC that have sequence homology to proteasome-encoding genes. We have identified a yeast gene, called PRG1, that encodes a protein predicted to contain 55.6% sequence identity to 80% of the RING10 gene product. Genomic disruption of PRG1 revealed that it is essential for yeast cell growth. These data strongly indicate that the antigen-processing system present in vertebrates evolved from a basic cellular process present in all organisms.     

A Network Based Method for Analysis of lncRNA-Disease Associations and Prediction of lncRNAs Implicated in Diseases

Increasing evidence has indicated that long non-coding RNAs (lncRNAs) are implicated in and associated with many complex human diseases. Despite of the accumulation of lncRNA-disease associations, only a few studies had studied the roles of these associations in pathogenesis. In this paper, we investigated lncRNA-disease associations from a network view to understand the contribution of these lncRNAs to complex diseases. Specifically, we studied both the properties of the diseases in which the lncRNAs were implicated, and that of the lncRNAs associated with complex diseases. Regarding the fact that protein coding genes and lncRNAs are involved in human diseases, we constructed a coding-non-coding gene-disease bipartite network based on known associations between diseases and disease-causing genes. We then applied a propagation algorithm to uncover the hidden lncRNA-disease associations in this network. The algorithm was evaluated by leave-one-out cross validation on 103 diseases in which at least two genes were known to be involved, and achieved an AUC of 0.7881. Our algorithm successfully predicted 768 potential lncRNA-disease associations between 66 lncRNAs and 193 diseases. Furthermore, our results for Alzheimer''s disease, pancreatic cancer, and gastric cancer were verified by other independent studies.     

EvoTol: a protein-sequence based evolutionary intolerance framework for disease-gene prioritization

Methods to interpret personal genome sequences are increasingly required. Here, we report a novel framework (EvoTol) to identify disease-causing genes using patient sequence data from within protein coding-regions. EvoTol quantifies a gene''s intolerance to mutation using evolutionary conservation of protein sequences and can incorporate tissue-specific gene expression data. We apply this framework to the analysis of whole-exome sequence data in epilepsy and congenital heart disease, and demonstrate EvoTol''s ability to identify known disease-causing genes is unmatched by competing methods. Application of EvoTol to the human interactome revealed networks enriched for genes intolerant to protein sequence variation, informing novel polygenic contributions to human disease.     

Genetic variation and the mitogen-activated protein kinase (MAPK) signaling pathway

Non-synonymous single nucleotide polymorphisms (nsSNPs) are known to alter protein function, contributing to disease susceptibility. This report explores the nature of nsSNPs in the gene products of the highly conserved mitogen-activated protein kinase (MAPK) signaling pathways already implicated in cancer development. MAPK signaling pathways regulate cellular processes such as proliferation, differentiation, apoptosis, and survival mediated through interconnected signaling cascades. Using the dbSNP database, we have identified 25 nsSNPs in 17 out of 98 MAPK genes studied. Computational algorithms were used to predict whether the amino acid substitutions were evolutionarily tolerated, or affected putative functional units such as phosphorylation sites, protein motifs and domains. This study predicts that 36% of nsSNPs are likely to have functional consequences, based on evolutionary conservation analysis, and 36% based on phosphorylation prediction analysis. All such nsSNPs represent potentially functional and disease-causing/modifying alleles. More interestingly, the epistatic relationships discussed in this report represent potential synergistic/ antagonistic/additive effects of nsSNP combinations found within the same protein, or within members of the same protein complex and cascades. This strategy can effectively determine which nsSNPs potentially alter protein function, and can be utilized to study the genetic architecture and disease association of other biological protein complexes and networks.     

The WD repeat-containing protein IFTA-1 is required for retrograde intraflagellar transport

The assembly and maintenance of cilia require intraflagellar transport (IFT), a microtubule-dependent bidirectional motility of multisubunit protein complexes along ciliary axonemes. Defects in IFT and the functions of motile or sensory cilia are associated with numerous human ailments, including polycystic kidney disease and Bardet-Biedl syndrome. Here, we identify a novel Caenorhabditis elegans IFT gene, IFT-associated gene 1 (ifta-1), which encodes a WD repeat-containing protein with strong homology to a mammalian protein of unknown function. Both the C. elegans and human IFTA-1 proteins localize to the base of cilia, and in C. elegans, IFTA-1 can be observed to undergo IFT. IFTA-1 is required for the function and assembly of cilia, because a C. elegans ifta-1 mutant displays chemosensory abnormalities and shortened cilia with prominent ciliary accumulations of core IFT machinery components that are indicative of retrograde transport defects. Analyses of C. elegans IFTA-1 localization/motility along bbs mutant cilia, where anterograde IFT assemblies are destabilized, and in a che-11 IFT gene mutant, demonstrate that IFTA-1 is closely associated with the IFT particle A subcomplex, which is implicated in retrograde IFT. Together, our data indicate that IFTA-1 is a novel IFT protein that is required for retrograde transport along ciliary axonemes.     

HIV-1 integrase forms stable tetramers and associates with LEDGF/p75 protein in human cells

We studied human immunodeficiency virus, type 1 (HIV-1) integrase (IN) complexes derived from nuclei of human cells stably expressing the viral protein from a synthetic gene. We show that in the nuclear extracts IN exists as part of a large distinct complex with an apparent Stokes radius of 61 A, which dissociates upon dilution yielding a core molecule of 41 A. We isolated the IN complexes from cells expressing FLAG-tagged IN and demonstrated that the 41 A core is a tetramer of IN, whereas 61 A molecules are composed of IN tetramers associated with a cellular protein with an apparent molecular mass of 76 kDa. This novel integrase interacting protein was found to be identical to lens epithelium-derived growth factor (LEDGF/p75), a protein implicated in regulation of gene expression and cellular stress response. HIV-1 IN and LEDGF co-localized in the nuclei of human cells stably expressing IN. Furthermore, recombinant LEDGF robustly enhanced strand transfer activity of HIV-1 IN in vitro. Our findings indicate that the minimal IN molecule in human cells is a homotetramer, suggesting that at least an octamer of IN is required to accomplish coordinated integration of both retroviral long terminal repeats and that LEDGF is a cellular factor involved in this process.     

Caspase-mediated parkin cleavage in apoptotic cell death

The parkin protein is important for the survival of the neurons that degenerate in Parkinson's disease as demonstrated by disease-causing lesions in the parkin gene. The Chinese hamster ovary and the SH-SY5Y cell line stably expressing recombinant human parkin combined with epitope-specific parkin antibodies were used to investigate the proteolytic processing of human parkin during apoptosis by immunoblotting. Parkin is cleaved during apoptosis induced by okadaic acid, staurosporine, and camptothecin, thereby generating a 38-kDa C-terminal fragment and a 12-kDa N-terminal fragment. The cleavage was not significantly affected by the disease-causing mutations K161N, G328E, T415N, and G430D and the polymorphism R366W. Parkin and its 38-kDa proteolytic fragment is preferentially associated with vesicles, thereby indicating that cleavage is a membrane-associated event. The proteolysis is sensitive to inhibitors of caspases. The cleavage site was mapped by site-directed mutagenesis of potential aspartic residues and revealed that mutation of Asp-126 alone abrogated the parkin cleavage. The tetrapeptide aldehyde LHTD-CHO, representing the amino acid sequence N-terminal to the putative cleavage site was an efficient inhibitor of parkin cleavage. This suggests that parkin function is compromised in neuropathological states associated with an increased caspase activation, thereby further adding to the cellular stress.     

The orphan disease networks

The low prevalence rate of orphan diseases (OD) requires special combined efforts to improve diagnosis, prevention, and discovery of novel therapeutic strategies. To identify and investigate relationships based on shared genes or shared functional features, we have conducted a bioinformatic-based global analysis of all orphan diseases with known disease-causing mutant genes. Starting with a bipartite network of known OD and OD-causing mutant genes and using the human protein interactome, we first construct and topologically analyze three networks: the orphan disease network, the orphan disease-causing mutant gene network, and the orphan disease-causing mutant gene interactome. Our results demonstrate that in contrast to the common disease-causing mutant genes that are predominantly nonessential, a majority of orphan disease-causing mutant genes are essential. In confirmation of this finding, we found that OD-causing mutant genes are topologically important in the protein interactome and are ubiquitously expressed. Additionally, functional enrichment analysis of those genes in which mutations cause ODs shows that a majority result in premature death or are lethal in the orthologous mouse gene knockout models. To address the limitations of traditional gene-based disease networks, we also construct and analyze OD networks on the basis of shared enriched features (biological processes, cellular components, pathways, phenotypes, and literature citations). Analyzing these functionally-linked OD networks, we identified several additional OD-OD relations that are both phenotypically similar and phenotypically diverse. Surprisingly, we observed that the wiring of the gene-based and other feature-based OD networks are largely different; this suggests that the relationship between ODs cannot be fully captured by the gene-based network alone.     

In silico investigation of the ATP7B gene: insights from functional prediction of non-synonymous substitution to protein structure

ATP7B is a copper-transporting ATPase that plays a key role in the regulation of copper homeostasis. Mutations in the ATP7B gene are causative for Wilson’s disease, and recent reports have suggested that genetic variants are associated with susceptibility to Alzheimer’s disease. Unfortunately, it is difficult to profile experimentally novel genetic variants in the ATP7B gene, because the human protein X-ray structure is not yet entirely understood. In order to investigate ATP7B non-synonymous substitutions, we used an in silico amino acid sequence-based approach. Specifically, we analyzed 337 ATP7B non-synonymous substitutions, which included Wilson’s disease-causing mutations (DVs) and non Wilson’s disease-causing variants (NDVs), with an algorithm that estimated a combined probability (cP_del) of an amino acidic change to be deleterious for the protein function. This approach appeared to reliably indentify the probability of DVs and NDVs to be deleterious and to profile still unknown gene variants. Specifically, after analyzing ATP7B protein domains with the cP_del method, we found results in line with the predicted–modeled domains and some new suggestions. In conclusion, a functional survey of amino acid changes in the ATP7B protein is provided herein, and we suggest that this bioinformatic method can furnish information about novel ATP7B mutations. Furthermore, the same approach can be applied to other uncharacterized proteins.     

Associating Genes and Protein Complexes with Disease via Network Propagation

A fundamental challenge in human health is the identification of disease-causing genes. Recently, several studies have tackled this challenge via a network-based approach, motivated by the observation that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein or functional interactions. However, most of these approaches use only local network information in the inference process and are restricted to inferring single gene associations. Here, we provide a global, network-based method for prioritizing disease genes and inferring protein complex associations, which we call PRINCE. The method is based on formulating constraints on the prioritization function that relate to its smoothness over the network and usage of prior information. We exploit this function to predict not only genes but also protein complex associations with a disease of interest. We test our method on gene-disease association data, evaluating both the prioritization achieved and the protein complexes inferred. We show that our method outperforms extant approaches in both tasks. Using data on 1,369 diseases from the OMIM knowledgebase, our method is able (in a cross validation setting) to rank the true causal gene first for 34% of the diseases, and infer 139 disease-related complexes that are highly coherent in terms of the function, expression and conservation of their member proteins. Importantly, we apply our method to study three multi-factorial diseases for which some causal genes have been found already: prostate cancer, alzheimer and type 2 diabetes mellitus. PRINCE''s predictions for these diseases highly match the known literature, suggesting several novel causal genes and protein complexes for further investigation.     

Genome-wide scan identifies loci associated with classical BSE occurrence

Classical bovine spongiform encephalopathy (BSE) is an acquired prion disease that is invariably fatal in cattle and has been implicated as a significant human health risk. Sequence variations in the coding region of the prion gene (PRNP) have been associated with acquired transmissible spongiform encephalopathy (TSE) susceptibility in mammals; however, this is not the case in cattle. It has been hypothesized that genes, in addition to the prion gene, contribute to genetic susceptibility of acquired TSEs. Accordingly, genetic studies of classical BSE in cattle identified loci other than PRNP that are associated with disease incidence. The objective of this study was to utilize a genome-wide association study to test for genetic loci associated with classical BSE. The samples include 143 BSE affected (case) and 173 unaffected half sib (control) animals collected in the mid 1990s in Southern England. The data analysis identifies loci on two different chromosomes associated with BSE disease occurrence. Most notable is a single nucleotide polymorphism on chromosome 1 at 29.15 Mb that is associated with BSE disease (p = 3.09E-05). Additionally, a locus on chromosome 14, within a cluster of SNPs showed a trend toward significance (p = 5.24E-05). It is worth noting that in a human vCJD study markers on human chromosome 8, a region with shared synteny to the region identified on cattle chromosome 14, were associated with disease. Further, our candidate genes appear to have plausible biological relevance with the known etiology of TSE disease. One of the candidate genes is hypothetical gene LOC521010, similar to FK506 binding protein 2 located on chromosome 1 at 29.32 Mb. This gene encodes a protein that is a member of the immunophilin protein family and is involved in basic cellular processes including protein folding. The chromosomal regions identified in this study and candidate genes within these regions merit further investigation.     

G-protein-coupled receptors and asthma endophenotypes: the cysteinyl leukotriene system in perspective

Genetic variation in specific G-protein coupled receptors (GPCRs) is associated with a spectrum of respiratory disease predispositions and drug response phenotypes. Although certain GPCR gene variants can be disease-causing through the expression of inactive, overactive, or constitutively active receptor proteins, many more GPCR gene variants confer risk for potentially deleterious endophenotypes. Endophenotypes are traits, such as bronchiole hyperactivity, atopy, and aspirin intolerant asthma, which have a strong genetic component and are risk factors for a variety of more complex outcomes that may include disease states. GPCR genes implicated in asthma endophenotypes include variants of the cysteinyl leukotriene receptors (CYSLTR1 and CYSLTR2), and prostaglandin D2 receptors (PTGDR and CRTH2), thromboxane A2 receptor (TBXA2R), beta2-adrenergic receptor (ADRB2), chemokine receptor 5 (CCR5), and the G protein-coupled receptor associated with asthma (GPRA). This review of the contribution of variability in these genes places the contribution of the cysteinyl leukotriene system to respiratory endophenotypes in perspective. The genetic variant(s) of receptors that are associated with endophenotypes are discussed in the context of the extent to which they contribute to a disease phenotype or altered drug efficacy.     

A computational method based on the integration of heterogeneous networks for predicting disease-gene associations

The identification of disease-causing genes is a fundamental challenge in human health and of great importance in improving medical care, and provides a better understanding of gene functions. Recent computational approaches based on the interactions among human proteins and disease similarities have shown their power in tackling the issue. In this paper, a novel systematic and global method that integrates two heterogeneous networks for prioritizing candidate disease-causing genes is provided, based on the observation that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein interactions. In this method, the association score function between a query disease and a candidate gene is defined as the weighted sum of all the association scores between similar diseases and neighbouring genes. Moreover, the topological correlation of these two heterogeneous networks can be incorporated into the definition of the score function, and finally an iterative algorithm is designed for this issue. This method was tested with 10-fold cross-validation on all 1,126 diseases that have at least a known causal gene, and it ranked the correct gene as one of the top ten in 622 of all the 1,428 cases, significantly outperforming a state-of-the-art method called PRINCE. The results brought about by this method were applied to study three multi-factorial disorders: breast cancer, Alzheimer disease and diabetes mellitus type 2, and some suggestions of novel causal genes and candidate disease-causing subnetworks were provided for further investigation.