Identification of deleterious non-synonymous single nucleotide polymorphisms using sequence-derived information

Background  

As the number of non-synonymous single nucleotide polymorphisms (nsSNPs), also known as single amino acid polymorphisms (SAPs), increases rapidly, computational methods that can distinguish disease-causing SAPs from neutral SAPs are needed. Many methods have been developed to distinguish disease-causing SAPs based on both structural and sequence features of the mutation point. One limitation of these methods is that they are not applicable to the cases where protein structures are not available. In this study, we explore the feasibility of classifying SAPs into disease-causing and neutral mutations using only information derived from protein sequence.     

A module-based analytical strategy to identify novel disease-associated genes shows an inhibitory role for interleukin 7 Receptor in allergic inflammation

Background  

The identification of novel genes by high-throughput studies of complex diseases is complicated by the large number of potential genes. However, since disease-associated genes tend to interact, one solution is to arrange them in modules based on co-expression data and known gene interactions. The hypothesis of this study was that such a module could be a) found and validated in allergic disease and b) used to find and validate one ore more novel disease-associated genes.     

Genome bioinformatic analysis of nonsynonymous SNPs

Background  

Genome-wide association studies of common diseases for common, low penetrance causal variants are underway. A proportion of these will alter protein sequences, the most common of which is the non-synonymous single nucleotide polymorphism (nsSNP). It would be an advantage if the functional effects of an nsSNP on protein structure and function could be predicted, both for the final identification process of a causal variant in a disease-associated chromosome region, and in further functional analyses of the nsSNP and its disease-associated protein.     

Generation of human scFvs antibodies recognizing a prion protein epitope expressed on the surface of human lymphoblastoid cells

Background  

A hallmark of prion disease is the transformation of normal cellular prion protein (PrPc) into an infectious disease-associated isoform, (PrPsc). Anti-prion protein monoclonal antibodies are invaluable for structure-function studies of PrP molecules. Furthermore recent in vitro and in vivo studies indicate that anti-PrP monoclonal antibodies can prevent the incorporation of PrPc into propagating prions.     

SNP HiTLink: a high-throughput linkage analysis system employing dense SNP data

Background  

During this recent decade, microarray-based single nucleotide polymorphism (SNP) data are becoming more widely used as markers for linkage analysis in the identification of loci for disease-associated genes. Although microarray-based SNP analyses have markedly reduced genotyping time and cost compared with microsatellite-based analyses, applying these enormous data to linkage analysis programs is a time-consuming step, thus, necessitating a high-throughput platform.     

The functional importance of disease-associated mutation

Background  

For many years, scientists believed that point mutations in genes are the genetic switches for somatic and inherited diseases such as cystic fibrosis, phenylketonuria and cancer. Some of these mutations likely alter a protein's function in a manner that is deleterious, and they should occur in functionally important regions of the protein products of genes. Here we show that disease-associated mutations occur in regions of genes that are conserved, and can identify likely disease-causing mutations.     

Life quality impairment caused by hookworm-related cutaneous larva migrans in resource-poor communities in Manaus, Brazil

Background

Hookworm-related cutaneous larva migrans (CLM) is a common but neglected tropical skin disease caused by the migration of animal hookworm larvae in the epidermis. The disease causes intense pruritus and is associated with important morbidity. The extent to which CLM impairs skin disease-associated life quality has never been studied.

Methods

A modified version of the Dermatology Life Quality Index (mDLQI) was used to determine skin disease-associated life quality in 91 adult and child patients with CLM, living in resource-poor communities in Manaus, Brazil. Symptoms and signs were documented and skin disease-associated life quality was semi-quantitatively assessed using mDLQI scores. The assessment was repeated two and four weeks after treatment with ivermectin.

Results

Ninety-one point five percent of the study participants showed a considerable reduction of skin disease-associated life quality at the time of diagnosis. The degree of impairment correlated with the intensity of infection (rho = 0.76, p<0.001), the number of body areas affected (rho = 0.30; p = 0.004), and the presence of lesions on visible areas of the skin (p = 0.002). Intense pruritus, sleep disturbance (due to itching) and the feeling of shame were the most frequent skin disease-associated life quality restrictions (reported by 93.4%, 73.6%, and 64.8% of the patients, respectively). No differences were observed in skin disease-associated life quality restriction between boys and girls or men and women. Two weeks after treatment with ivermectin, skin disease-associated life quality improved significantly. After four weeks, 73.3% of the patients considered their disease-associated life quality to have returned to normal.

Conclusions

CLM significantly impaired the skin disease-associated life quality in child and adult patients living in urban slums in North Brazil. After treatment with ivermectin, life quality normalised rapidly.     

Evolutionary analyses of KCNQ1 and HERG voltage-gated potassium channel sequences reveal location-specific susceptibility and augmented chemical severities of arrhythmogenic mutations

Background  

Mutations in HERG and KCNQ1 potassium channels have been associated with Long QT syndrome and atrial fibrillation, and more recently with sudden infant death syndrome and sudden unexplained death. In other proteins, disease-associated amino acid mutations have been analyzed according to the chemical severity of the changes and the locations of the altered amino acids according to their conservation over metazoan evolution. Here, we present the first such analysis of arrhythmia-associated mutations (AAMs) in the HERG and KCNQ1 potassium channels.     

Dam inactivation in <Emphasis Type="Italic">Neisseria meningitidis</Emphasis>: prevalence among diverse hyperinvasive lineages

Background  

DNA adenine methyltransferase (Dam) activity is absent in many, but not all, disease isolates of Neisseria meningitidis, as a consequence of the insertion of a restriction endonuclease-encoding gene, the 'dam replacing gene' (drg) at the dam locus. Here, we report the results of a survey to assess the prevalence of drg in a globally representative panel of disease-associated meningococci.     

Spontaneous action potentials and circumnutation in <Emphasis Type="Italic">Helianthus annuus</Emphasis>

Action potentials (APs) in plants are involved in fast leaf or trap closure as well as elongation, respiration, photosynthesis, and fertilization regulation. Here, spontaneous APs (SAPs) in relation to endogenous stem movement named circumnutation (CN) have been investigated in Helianthus annuus in different light conditions in freely circumnutating and immobilized plants. Extracellular electrical measurements and time-lapse photography were carried out simultaneously. The parameters of CN (trajectory length, period, and direction) and the number and transmission direction of SAPs were analysed. In continuous light (25–40 μmol m^?2 s^?1), all plants circumnutating vigorously in a regular elliptical manner and no SAPs were observed. In light/dark conditions, the plants circumnutated in a daily pattern, most SAPs were observed in the dark and freely circumnutated sunflowers had two times more SAPs (10 SAPs/24 h/plant) than the immobilized plants (5 SAPs/24 h/plant). In continuous very low light (5 μmol m^?2 s^?1), the plants circumnutated weakly and irregularly and SAPs appeared without the circadian pattern. 3–5 SAPs/24/plant occurred in the freely circumnutating and immobilized plants. In light/dark and continuous very low light conditions, an ultradian rhythm of SAPs was observed and the mean spacing between SAPs was approx. 121–271 min in the freely circumnutating and immobilized plants. Under all light conditions, more SAPs were transmitted basipetally than acropetally. One-hour lasting series of 3–4 min spaced SAPs locally propagated were observed as well in very low light. Basipetal and acropetal SAPs passing along the stem motor region accompany irregularity, changes in the CN trajectory direction, and stem torsion. These results demonstrate that APs and CN changes play a role in plant adaptation to light conditions and that there is an ultradian rhythm of SAPs beside ultradian CN rhythm.     

Identification and structural analysis of C-terminally truncated collapsin response mediator protein-2 in a murine model of prion diseases

Background  

Prion diseases are fatal neurodegenerative disorders that accompany an accumulation of the disease-associated form(s) of prion protein (PrP^Sc) in the central nervous system. The neuropathological changes in the brain begin with focal deposits of PrP^Sc, followed by pathomorphological abnormalities of axon terminal degeneration, synaptic loss, atrophy of dendritic trees, and eventual neuronal cell death in the lesions. However, the underlying molecular basis for these neuropathogenic abnormalities is not fully understood.     

Relationship between clinical signs and postmortem test status in cattle experimentally infected with the bovine spongiform encephalopathy agent

Background  

Various clinical protocols have been developed to aid in the clinical diagnosis of classical bovine spongiform encephalopathy (BSE), which is confirmed by postmortem examinations based on vacuolation and accumulation of disease-associated prion protein (PrP^d) in the brain. The present study investigated the occurrence and progression of sixty selected clinical signs and behaviour combinations in 513 experimentally exposed cattle subsequently categorised postmortem as confirmed or unconfirmed BSE cases. Appropriate undosed or saline inoculated controls were examined similarly and the data analysed to explore the possible occurrence of BSE-specific clinical expression in animals unconfirmed by postmortem examinations.     

CoagVDb: a comprehensive database for coagulation factors and their associated SAPs

The current state of the art in medical genetics is to identify and classify the functional (deleterious) or non-functional (neutral) single amino acid substitutions (SAPs), also known as non-synonymous SNPs (nsSNPs). The primary goal is to elucidate the mechanisms through which functional SAPs exert their effects, and ultimately interrogating this information for association with complex phenotypes. This work focuses on coagulation factors involved in the coagulation cascade pathway which plays a vital role in the maintenance of homeostasis in the human system. We developed an integrated coagulation variation database, CoagVDb, which makes use of the biological information from various public databases such as NCBI, OMIM, UniProt, PDB and SAPs (rsIDs/variant). CoagVDb enriched with computational prediction scores classify SAPs as either deleterious or tolerated. Also, various other properties are incorporated such as amino acid composition, secondary structure elements, solvent accessibility, ordered/disordered regions, conservation, and the presence of disulfide bonds. This specialized database provides integration of various prediction scores from different computational methods along with gene, protein, and disease information. We hope our database will act as a useful reference resource for hematologists to reveal protein structure–function relationship and disease genotype–phenotype correlation.

Electronic supplementary material

The online version of this article (doi:10.1186/s40659-015-0028-5) contains supplementary material, which is available to authorized users.     

Highly interconnected genes in disease-specific networks are enriched for disease-associated polymorphisms

Background

Complex diseases are associated with altered interactions between thousands of genes. We developed a novel method to identify and prioritize disease genes, which was generally applicable to complex diseases.

Results

We identified modules of highly interconnected genes in disease-specific networks derived from integrating gene-expression and protein interaction data. We examined if those modules were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies. First, we analyzed publicly available gene expression microarray and genome-wide association study (GWAS) data from 13, highly diverse, complex diseases. In each disease, highly interconnected genes formed modules, which were significantly enriched for genes harboring disease-associated SNPs. To test if such modules could be used to find novel genes for functional studies, we repeated the analyses using our own gene expression microarray and GWAS data from seasonal allergic rhinitis. We identified a novel gene, FGF2, whose relevance was supported by functional studies using combined small interfering RNA-mediated knock-down and gene expression microarrays. The modules in the 13 complex diseases analyzed here tended to overlap and were enriched for pathways related to oncological, metabolic and inflammatory diseases. This suggested that this union of the modules would be associated with a general increase in susceptibility for complex diseases. Indeed, we found that this union was enriched with GWAS genes for 145 other complex diseases.

Conclusions

Modules of highly interconnected complex disease genes were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies.     

Diagnosing Fatty Liver Disease: A Comparative Evaluation of Metabolic Markers,Phenotypes, Genotypes and Established Biomarkers

Background

To date, liver biopsy is the only means of reliable diagnosis for fatty liver disease (FLD). Owing to the inevitable biopsy-associated health risks, however, the development of valid noninvasive diagnostic tools for FLD is well warranted.

Aim

We evaluated a particular metabolic profile with regard to its ability to diagnose FLD and compared its performance to that of established phenotypes, conventional biomarkers and disease-associated genotypes.

Methods

The study population comprised 115 patients with ultrasound-diagnosed FLD and 115 sex- and age-matched controls for whom the serum concentration was measured of 138 different metabolites, including acylcarnitines, amino acids, biogenic amines, hexose, phosphatidylcholines (PCs), lyso-PCs and sphingomyelins. Established phenotypes, biomarkers, disease-associated genotypes and metabolite data were included in diagnostic models for FLD using logistic regression and partial least-squares discriminant analysis. The discriminative power of the ensuing models was compared with respect to area under curve (AUC), integrated discrimination improvement (IDI) and by way of cross-validation (CV).

Results

Use of metabolic markers for predicting FLD showed the best performance among all considered types of markers, yielding an AUC of 0.8993. Additional information on phenotypes, conventional biomarkers or genotypes did not significantly improve this performance. Phospholipids and branched-chain amino acids were most informative for predicting FLD.

Conclusion

We show that the inclusion of metabolite data may substantially increase the power to diagnose FLD over that of models based solely upon phenotypes and conventional biomarkers.     

Multivariate modeling identifies neutrophil- and Th17-related factors as differential serum biomarkers of chronic murine colitis

Background

Diagnosis of chronic intestinal inflammation, which characterizes inflammatory bowel disease (IBD), along with prediction of disease state is hindered by the availability of predictive serum biomarker. Serum biomarkers predictive of disease state will improve trials for therapeutic intervention, and disease monitoring, particularly in genetically susceptible individuals. Chronic inflammation during IBD is considered distinct from infectious intestinal inflammation thereby requiring biomarkers to provide differential diagnosis. To address whether differential serum biomarkers could be identified in murine models of colitis, immunological profiles from both chronic spontaneous and acute infectious colitis were compared and predictive serum biomarkers identified via multivariate modeling.

Methodology/Principal Findings

Discriminatory multivariate modeling of 23 cytokines plus chlorotyrosine and nitrotyrosine (protein adducts from reactive nitrogen species and hypochlorite) in serum and tissue from two murine models of colitis was performed to identify disease-associated biomarkers. Acute C. rodentium-induced colitis in C57BL/6J mice and chronic spontaneous Helicobacter-dependent colitis in TLR4^−/− x IL-10^−/− mice were utilized for evaluation. Colon profiles of both colitis models were nearly identical with chemokines, neutrophil- and Th17-related factors highly associated with intestinal disease. In acute colitis, discriminatory disease-associated serum factors were not those identified in the colon. In contrast, the discriminatory predictive serum factors for chronic colitis were neutrophil- and Th17-related factors (KC, IL-12/23p40, IL-17, G-CSF, and chlorotyrosine) that were also elevated in colon tissue. Chronic colitis serum biomarkers were specific to chronic colitis as they were not discriminatory for acute colitis.

Conclusions/Significance

Immunological profiling revealed strikingly similar colon profiles, yet distinctly different serum profiles for acute and chronic colitis. Neutrophil- and Th17-related factors were identified as predictive serum biomarkers of chronic colitis, but not acute colitis, despite their presence in colitic tissue of both diseases thereby demonstrating the utility of mathematical modeling for identifying disease-associated serum biomarkers.     

FitSNPs: highly differentially expressed genes are more likely to have variants associated with disease

Background

Candidate single nucleotide polymorphisms (SNPs) from genome-wide association studies (GWASs) were often selected for validation based on their functional annotation, which was inadequate and biased. We propose to use the more than 200,000 microarray studies in the Gene Expression Omnibus to systematically prioritize candidate SNPs from GWASs.

Results

We analyzed all human microarray studies from the Gene Expression Omnibus, and calculated the observed frequency of differential expression, which we called differential expression ratio, for every human gene. Analysis conducted in a comprehensive list of curated disease genes revealed a positive association between differential expression ratio values and the likelihood of harboring disease-associated variants. By considering highly differentially expressed genes, we were able to rediscover disease genes with 79% specificity and 37% sensitivity. We successfully distinguished true disease genes from false positives in multiple GWASs for multiple diseases. We then derived a list of functionally interpolating SNPs (fitSNPs) to analyze the top seven loci of Wellcome Trust Case Control Consortium type 1 diabetes mellitus GWASs, rediscovered all type 1 diabetes mellitus genes, and predicted a novel gene (KIAA1109) for an unexplained locus 4q27. We suggest that fitSNPs would work equally well for both Mendelian and complex diseases (being more effective for cancer) and proposed candidate genes to sequence for their association with 597 syndromes with unknown molecular basis.

Conclusions

Our study demonstrates that highly differentially expressed genes are more likely to harbor disease-associated DNA variants. FitSNPs can serve as an effective tool to systematically prioritize candidate SNPs from GWASs.     

SIDD: A Semantically Integrated Database towards a Global View of Human Disease

Background

A number of databases have been developed to collect disease-related molecular, phenotypic and environmental features (DR-MPEs), such as genes, non-coding RNAs, genetic variations, drugs, phenotypes and environmental factors. However, each of current databases focused on only one or two DR-MPEs. There is an urgent demand to develop an integrated database, which can establish semantic associations among disease-related databases and link them to provide a global view of human disease at the biological level. This database, once developed, will facilitate researchers to query various DR-MPEs through disease, and investigate disease mechanisms from different types of data.

Methodology

To establish an integrated disease-associated database, disease vocabularies used in different databases are mapped to Disease Ontology (DO) through semantic match. 4,284 and 4,186 disease terms from Medical Subject Headings (MeSH) and Online Mendelian Inheritance in Man (OMIM) respectively are mapped to DO. Then, the relationships between DR-MPEs and diseases are extracted and merged from different source databases for reducing the data redundancy.

Conclusions

A semantically integrated disease-associated database (SIDD) is developed, which integrates 18 disease-associated databases, for researchers to browse multiple types of DR-MPEs in a view. A web interface allows easy navigation for querying information through browsing a disease ontology tree or searching a disease term. Furthermore, a network visualization tool using Cytoscape Web plugin has been implemented in SIDD. It enhances the SIDD usage when viewing the relationships between diseases and DR-MPEs. The current version of SIDD (Jul 2013) documents 4,465,131 entries relating to 139,365 DR-MPEs, and to 3,824 human diseases. The database can be freely accessed from: http://mlg.hit.edu.cn/SIDD.     

Worldwide population differentiation at disease-associated SNPs

Background

Recent genome-wide association (GWA) studies have provided compelling evidence of association between genetic variants and common complex diseases. These studies have made use of cases and controls almost exclusively from populations of European ancestry and little is known about the frequency of risk alleles in other populations. The present study addresses the transferability of disease associations across human populations by examining levels of population differentiation at disease-associated single nucleotide polymorphisms (SNPs).

Methods

We genotyped ~1000 individuals from 53 populations worldwide at 25 SNPs which show robust association with 6 complex human diseases (Crohn's disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, coronary artery disease and obesity). Allele frequency differences between populations for these SNPs were measured using Fst. The Fst values for the disease-associated SNPs were compared to Fst values from 2750 random SNPs typed in the same set of individuals.

Results

On average, disease SNPs are not significantly more differentiated between populations than random SNPs in the genome. Risk allele frequencies, however, do show substantial variation across human populations and may contribute to differences in disease prevalence between populations. We demonstrate that, in some cases, risk allele frequency differences are unusually high compared to random SNPs and may be due to the action of local (i.e. geographically-restricted) positive natural selection. Moreover, some risk alleles were absent or fixed in a population, which implies that risk alleles identified in one population do not necessarily account for disease prevalence in all human populations.

Conclusion

Although differences in risk allele frequencies between human populations are not unusually large and are thus likely not due to positive local selection, there is substantial variation in risk allele frequencies between populations which may account for differences in disease prevalence between human populations.