Characterization of foot-and-mouth disease virus types Ο and Asia 1 RNA

Foot-and-mouth disease is an acute and highly contagious febrile disease affecting cloven-footed animals. Identification of the foot-and-mouth disease virus (FMDV), the causative agent of the disease, posed problems because of the occurrence of many types and subtypes of the virus. A molecular approach based on oligonucleotide mapping of FMDV RNA has been used for the identification and characterization of virus isolates obtained in a disease outbreak (King et al., 1981). One-dimensional oligonucleotide mapping was used for rapid analysis of FMDV RNA (LaTorre et al., 1982). FMDV types Ο and Asia 1 of Indian origin are being routinely used for vaccine production in India. This report presents the differences between FMDV types Ο and Asia 1 at molecular level based on one-dimensional oligonucleotide mapping of virus-induced poly (A) RNA.

Simulation and graph mining tools for improving gene mapping efficiency

Gene mapping is a systematic search for genes that affect observable characteristics of an organism. In this thesis we offer computational tools to improve the efficiency of (disease) gene-mapping efforts. In the first part of the thesis we propose an efficient simulation procedure for generating realistic genetical data from isolated populations. Simulated data is useful for evaluating hypothesised gene-mapping study designs and computational analysis tools. As an example of such evaluation, we demonstrate how a population-based study design can be a powerful alternative to traditional family-based designs in association-based gene-mapping projects. In the second part of the thesis we consider a prioritisation of a (typically large) set of putative disease-associated genes acquired from an initial gene-mapping analysis. Prioritisation is necessary to be able to focus on the most promising candidates. We show how to harness the current biomedical knowledge for the prioritisation task by integrating various publicly available biological databases into a weighted biological graph. We then demonstrate how to find and evaluate connections between entities, such as genes and diseases, from this unified schema by graph mining techniques. Finally, in the last part of the thesis, we define the concept of reliable subgraph and the corresponding subgraph extraction problem. Reliable subgraphs concisely describe strong and independent connections between two given vertices in a random graph, and hence they are especially useful for visualising such connections. We propose novel algorithms for extracting reliable subgraphs from large random graphs. The efficiency and scalability of the proposed graph mining methods are backed by extensive experiments on real data. While our application focus is in genetics, the concepts and algorithms can be applied to other domains as well. We demonstrate this generality by considering coauthor graphs in addition to biological graphs in the experiments.

Exploring Genetic Factors Involved in Huntington Disease Age of Onset: E2F2 as a New Potential Modifier Gene

Age of onset (AO) of Huntington disease (HD) is mainly determined by the length of the CAG repeat expansion (CAGexp) in exon 1 of the HTT gene. Additional genetic variation has been suggested to contribute to AO, although the mechanism by which it could affect AO is presently unknown. The aim of this study is to explore the contribution of candidate genetic factors to HD AO in order to gain insight into the pathogenic mechanisms underlying this disorder. For that purpose, two AO definitions were used: the earliest age with unequivocal signs of HD (earliest AO or eAO), and the first motor symptoms age (motor AO or mAO). Multiple linear regression analyses were performed between genetic variation within 20 candidate genes and eAO or mAO, using DNA and clinical information of 253 HD patients from REGISTRY project. Gene expression analyses were carried out by RT-qPCR with an independent sample of 35 HD patients from Basque Country Hospitals. We found suggestive association signals between HD eAO and/or mAO and genetic variation within the E2F2, ATF7IP, GRIN2A, GRIN2B, LINC01559, HIP1 and GRIK2 genes. Among them, the most significant was the association between eAO and rs2742976, mapping to the promoter region of E2F2 transcription factor. Furthermore, rs2742976 T allele patient carriers exhibited significantly lower lymphocyte E2F2 gene expression, suggesting a possible implication of E2F2-dependent transcriptional activity in HD pathogenesis. Thus, E2F2 emerges as a new potential HD AO modifier factor.

Mapping the gene for autosomal dominant restless legs syndrome in an Irish family

Restless Legs Syndrome (RLS) is a common neurological disorder affecting nearly 15% of the general population. Ironically, RLS can be described as the most common condition one has never heard of. It is usually characterised by uncomfortable, unpleasant sensations in the lower limbs inducing an uncontrollable desire to move the legs. RLS exhibits a circadian pattern with symptoms present predominantly in the evening or at night, thus leading to sleep disruption and daytime somnolence. RLS is generally classified into primary (idiopathic) and secondary (symptomatic) forms. Primary RLS includes sporadic and familial cases of which the age of onset is usually less than 45 years and progresses slowly with a female to male ratio of 2:1. Secondary forms often occur as a complication of another health condition, such as iron deficiency or thyroid dysfunction. The age of onset is usually over 45 years, with an equal male to female ratio and more rapid progression. Ekbom described the familial component of the disorder in 1945 and since then many studies have been published on the familial forms of the disorder. Molecular genetic studies have so far identified ten loci (5q, 12q, 14p, 9p, 20p, 16p, 19p, 4q, 17p). No specific gene within these loci has been identified thus far. Association mapping has highlighted a further five areas of interest. RLS6 has been found to be associated with SNPs in the BTBD9 gene. Four other variants were found within intronic and intergenic regions of MEIS1, MAP2K5/LBXCOR1, PTPRD and NOS1. The pathophysiology of RLS is complex and remains to be fully elucidated. Conditions associated with secondary RLS, such as pregnancy or end-stage renal disease, are characterised by iron deficiency, which suggests that disturbed iron homeostasis plays a role. Dopaminergic dysfunction in subcortical systems also appears to play a central role. An ongoing study within the Department of Pathology (University College Cork) is investigating the genetic characteristics of RLS in Irish families. A three generation RLS pedigree RLS3002 consisting of 11 affected and 7 unaffected living family members was recruited. The family had been examined for four of the known loci (5q, 12q, 14p and 9p) (Abdulrahim 2008). The aim of this study was to continue examining this Irish RLS pedigree for possible linkage to the previously described loci and associated regions. Using informative microsatellite markers linkage was excluded to the loci on 5q, 12q, 14p, 9p, 20p, 16p, 19p, 4q, 17p and also within the regions reported to be associated with RLS. This suggested the presence of a new unidentified locus. A genome-wide scan was performed using two microsatellite marker screening sets (Research Genetics Inc. Mapping set and the Applied Biosystems Linkage mapping set version 2.5). Linkage analysis was conducted under an autosomal dominant model with a penetrance of 95% and an allele frequency of 0.01. A maximum LOD score of 3.59 at θ=0.00 for marker D19S878 indicated significant linkage on chromosome 19p. Haplotype analysis defined a genetic region of 6.57 cM on chromosome 19p13.3, corresponding to 2.5 Mb. There are approximately 100 genes annotated within the critical region. Sequencing of two candidate genes, KLF16 and GAMT, selected on the assumed pathophysiology of RLS, did not identify any sequence variant. This study provides evidence of a novel RLS locus in an Irish pedigree, thus supporting the picture of RLS as a genetically heterogeneous trait.

High-throughput isolation and mapping of C. elegans mutants susceptible to pathogen infection.

We present a novel strategy that uses high-throughput methods of isolating and mapping C. elegans mutants susceptible to pathogen infection. We show that C. elegans mutants that exhibit an enhanced pathogen accumulation (epa) phenotype can be rapidly identified and isolated using a sorting system that allows automation of the analysis, sorting, and dispensing of C. elegans by measuring fluorescent bacteria inside the animals. Furthermore, we validate the use of Amplifluor as a new single nucleotide polymorphism (SNP) mapping technique in C. elegans. We show that a set of 9 SNPs allows the linkage of C. elegans mutants to a 5-8 megabase sub-chromosomal region.

Loss-of-function mutations in the cathepsin C gene result in periodontal disease and palmoplantar keratosis

Papillon-Lefevre syndrome, or keratosis palmoplantaris with periodontopathia (PLS, MIM 245000), is an autosomal recessive disorder that is mainly ascertained by dentists because of the severe periodontitis that afflicts patients(1,2). Both the deciduous and permanent dentitions are affected, resulting in premature tooth loss. Palmoplantar keratosis, varying from mild psoriasiform scaly skin to overt hyperkeratosis, typically develops within the first three years of life. Keratosis also affects other sites such as elbows and knees. Most PLS patients display both periodontitis and hyperkeratosis. some patients have only palmoplantar keratosis or periodontitis, and in rare individuals the periodontitis is mild and of late onset(3-6). The PLS locus has been mapped to chromosome 11q14-q21 (refs 7-9). Using homozygosity mapping in eight small consanguineous families, we have narrowed the candidate region to a 1.2-cM interval between D11S4082 and D11S931. The gene (CTSC) encoding the lysosomal protease cathepsin C (or dipeptidyl aminopeptidase I) lies within this interval. We defined the genomic structure of CTSC and found mutations in all eight families. In two of these families we used a functional assay to demonstrate an almost total loss of cathepsin C activity in PLS patients and reduced activity in obligate carriers.

Dense fine-mapping study identifies new susceptibility loci for primary biliary cirrhosis

We genotyped 2,861 cases of primary biliary cirrhosis (PBC) from the UK PBC Consortium and 8,514 UK population controls across 196,524 variants within 186 known autoimmune risk loci. We identified 3 loci newly associated with PBC (at P <5 × 10(-8)), increasing the number of known susceptibility loci to 25. The most associated variant at 19p12 is a low-frequency nonsynonymous SNP in TYK2, further implicating JAK-STAT and cytokine signaling in disease pathogenesis. An additional five loci contained nonsynonymous variants in high linkage disequilibrium (LD; r(2) > 0.8) with the most associated variant at the locus. We found multiple independent common, low-frequency and rare variant association signals at five loci. Of the 26 independent non-human leukocyte antigen (HLA) signals tagged on the Immunochip, 15 have SNPs in B-lymphoblastoid open chromatin regions in high LD (r(2) > 0.8) with the most associated variant. This study shows how data from dense fine-mapping arrays coupled with functional genomic data can be used to identify candidate causal variants for functional follow-up.

Genome-wide association study of Alzheimer's disease with psychotic symptoms

Psychotic symptoms occur in ~40% of subjects with Alzheimer's disease (AD) and are associated with more rapid cognitive decline and increased functional deficits. They show heritability up to 61% and have been proposed as a marker for a disease subtype suitable for gene mapping efforts. We undertook a combined analysis of three genome-wide association studies (GWASs) to identify loci that (1) increase susceptibility to an AD and subsequent psychotic symptoms; or (2) modify risk of psychotic symptoms in the presence of neurodegeneration caused by AD. In all, 1299 AD cases with psychosis (AD+P), 735 AD cases without psychosis (AD-P) and 5659 controls were drawn from Genetic and Environmental Risk in AD Consortium 1 (GERAD1), the National Institute on Aging Late-Onset Alzheimer's Disease (NIA-LOAD) family study and the University of Pittsburgh Alzheimer Disease Research Center (ADRC) GWASs. Unobserved genotypes were imputed to provide data on >1.8 million single-nucleotide polymorphisms (SNPs). Analyses in each data set were completed comparing (1) AD+P to AD-P cases, and (2) AD+P cases with controls (GERAD1, ADRC only). Aside from the apolipoprotein E (APOE) locus, the strongest evidence for association was observed in an intergenic region on chromosome 4 (rs753129; 'AD+PvAD-P' P=2.85 × 10(-7); 'AD+PvControls' P=1.11 × 10(-4)). SNPs upstream of SLC2A9 (rs6834555, P=3.0 × 10(-7)) and within VSNL1 (rs4038131, P=5.9 × 10(-7)) showed strongest evidence for association with AD+P when compared with controls. These findings warrant further investigation in larger, appropriately powered samples in which the presence of psychotic symptoms in AD has been well characterized.Molecular Psychiatry advance online publication, 18 October 2011; doi:10.1038/mp.2011.125.

No evidence for linkage or association of neuregulin-1 (NRG1) with disease in the Irish study of high-density schizophrenia families (ISHDSF)

The neuregulin-1 gene (NRG1) at chromosome 8p21-22 has been implicated as a schizophrenia susceptibility gene in Icelandic, Scottish, Irish and mixed UK populations. The shared ancestry between these populations led us to investigate the NRG1 polymorphisms and appropriate marker haplotypes for linkage and/or association to schizophrenia in the Irish study of high-density schizophrenia families (ISHDSF). Neither single-point nor multi-point linkage analysis of NRG1 markers gave evidence for linkage independent of our pre-existing findings telomeric on 8p. Analysis of linkage disequilibrium (LD) across the 252 kb interval encompassing the 7 marker core Icelandic/Scottish NRG1 haplotype revealed two separate regions of modest LD, comprising markers SNP8NRG255133, SNP8NRG249130 and SNP8NRG243177 (telomeric) and microsatellites 478B14-428, 420M9-1395, D8S1810 and 420M9-116I12 (centromeric). From single marker analysis by TRANSMIT and FBAT we found no evidence for association with schizophrenia for any marker. Haplotype analysis for the three SNPs in LD region 1 and, separately, the four microsatellites in LD region 2 (analyzed in overlapping 2-marker windows), showed no evidence for overtransmission of specific haplotypes to affected individuals. We therefore conclude that if NRG1 does contain susceptibility alleles for schizophrenia, they impact quite weakly on risk in the ISHDSF.

Deriving meteorological variables across Africa for the study and control of vector-borne disease:a comparison of remote sensing and spatial interpolation of climate

This paper presents the results of an investigation into the utility of remote sensing (RS) using meteorological satellites sensors and spatial interpolation (SI) of data from meteorological stations, for the prediction of spatial variation in monthly climate across continental Africa in 1990. Information from the Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration's (NOAA) polar-orbiting meteorological satellites was used to estimate land surface temperature (LST) and atmospheric moisture. Cold cloud duration (CCD) data derived from the High Resolution Radiometer (HRR) onboard the European Meteorological Satellite programme's (EUMETSAT) Meteosat satellite series were also used as a RS proxy measurement of rainfall. Temperature, atmospheric moisture and rainfall surfaces were independently derived from SI of measurements from the World Meteorological Organization (WMO) member stations of Africa. These meteorological station data were then used to test the accuracy of each methodology, so that the appropriateness of the two techniques for epidemiological research could be compared. SI was a more accurate predictor of temperature, whereas RS provided a better surrogate for rainfall; both were equally accurate at predicting atmospheric moisture. The implications of these results for mapping short and long-term climate change and hence their potential for the study anti control of disease vectors are considered. Taking into account logistic and analytical problems, there were no clear conclusions regarding the optimality of either technique, but there was considerable potential for synergy.

Connectivity mapping using a combined gene signature from multiple colorectal cancer datasets identified candidate drugs including existing chemotherapies

BACKGROUND: While the discovery of new drugs is a complex, lengthy and costly process, identifying new uses for existing drugs is a cost-effective approach to therapeutic discovery. Connectivity mapping integrates gene expression profiling with advanced algorithms to connect genes, diseases and small molecule compounds and has been applied in a large number of studies to identify potential drugs, particularly to facilitate drug repurposing. Colorectal cancer (CRC) is a commonly diagnosed cancer with high mortality rates, presenting a worldwide health problem. With the advancement of high throughput omics technologies, a number of large scale gene expression profiling studies have been conducted on CRCs, providing multiple datasets in gene expression data repositories. In this work, we systematically apply gene expression connectivity mapping to multiple CRC datasets to identify candidate therapeutics to this disease.

RESULTS: We developed a robust method to compile a combined gene signature for colorectal cancer across multiple datasets. Connectivity mapping analysis with this signature of 148 genes identified 10 candidate compounds, including irinotecan and etoposide, which are chemotherapy drugs currently used to treat CRCs. These results indicate that we have discovered high quality connections between the CRC disease state and the candidate compounds, and that the gene signature we created may be used as a potential therapeutic target in treating the disease. The method we proposed is highly effective in generating quality gene signature through multiple datasets; the publication of the combined CRC gene signature and the list of candidate compounds from this work will benefit both cancer and systems biology research communities for further development and investigations.

Compositonal Analysis of Potentially harmful Elements in Soils: Implications for Epidemiology and Kidney Disease

A substantial proportion of aetiological risks for many cancers and chronic diseases remain unexplained. Using geochemical soil and stream water samples collected as part of the Tellus Project studies, current research is investigating naturally occurring background levels of potentially toxic elements (PTEs) in soils and stream sediments and their possible relationship with progressive chronic kidney disease (CKD). The Tellus geological mapping project, Geological Survey Northern Ireland, collected soil sediment and stream water samples on a grid of one sample site every 2 km2 across the rural areas of Northern Ireland resulting in an excess of 6800 soil sampling locations and more than 5800 locations for stream water sampling. Accumulation of several PTEs including arsenic, cadmium, chromium, lead and mercury have been linked with human health and implicated in renal function decline. The hypothesis is that long-term exposure will result in cumulative exposure to PTEs and act as risk factor(s) for cancer and diabetes related CKD and its progression. The ‘bioavailable’ fraction of total PTE soil concentration depends on the ‘bioaccessible’ proportion through an exposure pathway. Recent work has explored this bioaccessible fraction for a range of PTEs across Northern Ireland. In this study the compositional nature of the multivariate geochemical PTE variables and bioaccessible data is explored to augment the investigation into the potential relationship between PTEs, bioaccessibility and disease data.

Is multidimensional scaling suitable for mapping the input respiratory impedance in subjects and patients?

This paper presents the application of multidimensional scaling (MDS) analysis to data emerging from noninvasive lung function tests, namely the input respiratory impedance. The aim is to obtain a geometrical mapping of the diseases in a 3D space representation, allowing analysis of (dis)similarities between subjects within the same pathology groups, as well as between the various groups. The adult patient groups investigated were healthy, diagnosed chronic obstructive pulmonary disease (COPD) and diagnosed kyphoscoliosis, respectively. The children patient groups were healthy, asthma and cystic fibrosis. The results suggest that MDS can be successfully employed for mapping purposes of restrictive (kyphoscoliosis) and obstructive (COPD) pathologies. Hence, MDS tools can be further examined to define clear limits between pools of patients for clinical classification, and used as a training aid for medical traineeship.

Genome-wide association study of metabolic traits reveals novel gene-metabolite-disease links.

Metabolic traits are molecular phenotypes that can drive clinical phenotypes and may predict disease progression. Here, we report results from a metabolome- and genome-wide association study on (1)H-NMR urine metabolic profiles. The study was conducted within an untargeted approach, employing a novel method for compound identification. From our discovery cohort of 835 Caucasian individuals who participated in the CoLaus study, we identified 139 suggestively significant (P<5×10(-8)) and independent associations between single nucleotide polymorphisms (SNP) and metabolome features. Fifty-six of these associations replicated in the TasteSensomics cohort, comprising 601 individuals from São Paulo of vastly diverse ethnic background. They correspond to eleven gene-metabolite associations, six of which had been previously identified in the urine metabolome and three in the serum metabolome. Our key novel findings are the associations of two SNPs with NMR spectral signatures pointing to fucose (rs492602, P = 6.9×10(-44)) and lysine (rs8101881, P = 1.2×10(-33)), respectively. Fine-mapping of the first locus pinpointed the FUT2 gene, which encodes a fucosyltransferase enzyme and has previously been associated with Crohn's disease. This implicates fucose as a potential prognostic disease marker, for which there is already published evidence from a mouse model. The second SNP lies within the SLC7A9 gene, rare mutations of which have been linked to severe kidney damage. The replication of previous associations and our new discoveries demonstrate the potential of untargeted metabolomics GWAS to robustly identify molecular disease markers.