Exhaustive prediction of disease susceptibility to coding base changes in the human genome

<p>Abstract</p> <p>Background</p> <p>Single Nucleotide Polymorphisms (SNPs) are the most abundant form of genomic variation and can cause phenotypic differences between individuals, including diseases. Bases are subject to various levels of selection pressure, reflected in their inter-species conservation.</p> <p>Results</p> <p>We propose a method that is not dependant on transcription information to score each coding base in the human genome reflecting the disease probability associated with its mutation. Twelve factors likely to be associated with disease alleles were chosen as the input for a support vector machine prediction algorithm. The analysis yielded 83% sensitivity and 84% specificity in segregating disease like alleles as found in the Human Gene Mutation Database from non-disease like alleles as found in the Database of Single Nucleotide Polymorphisms. This algorithm was subsequently applied to each base within all known human genes, exhaustively confirming that interspecies conservation is the strongest factor for disease association. For each gene, the length normalized average disease potential score was calculated. Out of the 30 genes with the highest scores, 21 are directly associated with a disease. In contrast, out of the 30 genes with the lowest scores, only one is associated with a disease as found in published literature. The results strongly suggest that the highest scoring genes are enriched for those that might contribute to disease, if mutated.</p> <p>Conclusion</p> <p>This method provides valuable information to researchers to identify sensitive positions in genes that have a high disease probability, enabling them to optimize experimental designs and interpret data emerging from genetic and epidemiological studies.</p

Improving the prediction of disease-related variants using protein three-dimensional structure

Background: Single Nucleotide Polymorphisms (SNPs) are an important source of human genome variability. Non-synonymous SNPs occurring in coding regions result in single amino acid polymorphisms (SAPs) that may affect protein function and lead to pathology. Several methods attempt to estimate the impact of SAPs using different sources of information. Although sequence-based predictors have shown good performance, the quality of these predictions can be further improved by introducing new features derived from three-dimensional protein structures.Results: In this paper, we present a structure-based machine learning approach for predicting disease-related SAPs. We have trained a Support Vector Machine (SVM) on a set of 3,342 disease-related mutations and 1,644 neutral polymorphisms from 784 protein chains. We use SVM input features derived from the protein's sequence, structure, and function. After dataset balancing, the structure-based method (SVM-3D) reaches an overall accuracy of 85%, a correlation coefficient of 0.70, and an area under the receiving operating characteristic curve (AUC) of 0.92. When compared with a similar sequence-based predictor, SVM-3D results in an increase of the overall accuracy and AUC by 3%, and correlation coefficient by 0.06. The robustness of this improvement has been tested on different datasets and in all the cases SVM-3D performs better than previously developed methods even when compared with PolyPhen2, which explicitly considers in input protein structure information.Conclusion: This work demonstrates that structural information can increase the accuracy of disease-related SAPs identification. Our results also quantify the magnitude of improvement on a large dataset. This improvement is in agreement with previously observed results, where structure information enhanced the prediction of protein stability changes upon mutation. Although the structural information contained in the Protein Data Bank is limiting the application and the performance of our structure-based method, we expect that SVM-3D will result in higher accuracy when more structural date become available. \ua9 2011 Capriotti; licensee BioMed Central Ltd

Novel germline variants identified in the inner mitochondrial membrane transporter TIMM44 and their role in predisposition to oncocytic thyroid carcinomas

Familial Non-Medullary Thyroid Carcinoma (fNMTC) represents 3–7% of all thyroid tumours and is associated with some of the highest familial risks among all cancers, with an inheritance pattern compatible with an autosomal dominant model with reduced penetrance. We previously mapped a predisposing locus, TCO (Thyroid tumour with Cell Oxyphilia) on chromosome 19p13.2, for a particular form of thyroid tumour characterised by cells with an abnormal proliferation of mitochondria (oxyphilic or oncocytic cells). In the present work, we report the systematic screening of 14 candidate genes mapping to the region of linkage in affected TCO members, that led us to identify two novel variants respectively in exon 9 and exon 13 of TIMM44, a mitochondrial inner membrane translocase for the import in the mitochondria of nuclear-encoded proteins. These variants were co-segregating with the TCO phenotype, were not present in a large group of controls and were predicted to negatively affect the protein (exon 9 change) or the transcript (exon 13 change). Functional analysis was performed in vitro for both changes and although no dramatic loss of function effects were identified for the mutant alleles, subtler effects might still be present that could alter Timm44 function and thus promote oncocytic tumour development. Thus we suggest that TIMM44 should be considered for further studies in independent samples of affected individuals with TCO

Cost-Effectiveness of Strategies to Improve HIV Testing and Receipt of Results: Economic Analysis of a Randomized Controlled Trial

The CDC recommends routine voluntary HIV testing of all patients 13-64 years of age. Despite this recommendation, HIV testing rates are low even among those at identifiable risk, and many patients do not return to receive their results. To examine the costs and benefits of strategies to improve HIV testing and receipt of results. Cost-effectiveness analysis based on a Markov model. Acceptance of testing, return rates, and related costs were derived from a randomized trial of 251 patients; long-term costs and health outcomes were derived from the literature. Primary-care patients with unknown HIV status. Comparison of three intervention models for HIV counseling and testing: Model A = traditional HIV counseling and testing; Model B = nurse-initiated routine screening with traditional HIV testing and counseling; Model C = nurse-initiated routine screening with rapid HIV testing and streamlined counseling. Life-years, quality-adjusted life-years (QALYs), costs and incremental cost-effectiveness. Without consideration of the benefit from reduced HIV transmission, Model A resulted in per-patient lifetime discounted costs of $48,650 and benefits of 16.271 QALYs. Model B increased lifetime costs by$53 and benefits by 0.0013 QALYs (corresponding to 0.48 quality-adjusted life days). Model C cost $66 more than Model A with an increase of 0.0018 QALYs (0.66 quality-adjusted life days) and an incremental cost-effectiveness of$36,390/QALY. When we included the benefit from reduced HIV transmission, Model C cost $10,660/QALY relative to Model A. The cost-effectiveness of Model C was robust in sensitivity analyses. In a primary-care population, nurse-initiated routine screening with rapid HIV testing and streamlined counseling increased rates of testing and receipt of test results and was cost-effective compared with traditional HIV testing strategies

Path to Facilitate the Prediction of Functional Amino Acid Substitutions in Red Blood Cell Disorders – A Computational Approach

A major area of effort in current genomics is to distinguish mutations that are functionally neutral from those that contribute to disease. Single Nucleotide Polymorphisms (SNPs) are amino acid substitutions that currently account for approximately half of the known gene lesions responsible for human inherited diseases. As a result, the prediction of non-synonymous SNPs (nsSNPs) that affect protein functions and relate to disease is an important task.In this study, we performed a comprehensive analysis of deleterious SNPs at both functional and structural level in the respective genes associated with red blood cell metabolism disorders using bioinformatics tools. We analyzed the variants in Glucose-6-phosphate dehydrogenase (G6PD) and isoforms of Pyruvate Kinase (PKLR & PKM2) genes responsible for major red blood cell disorders. Deleterious nsSNPs were categorized based on empirical rule and support vector machine based methods to predict the impact on protein functions. Furthermore, we modeled mutant proteins and compared them with the native protein for evaluation of protein structure stability.We argue here that bioinformatics tools can play an important role in addressing the complexity of the underlying genetic basis of Red Blood Cell disorders. Based on our investigation, we report here the potential candidate SNPs, for future studies in human Red Blood Cell disorders. Current study also demonstrates the presence of other deleterious mutations and also endorses with in vivo experimental studies. Our approach will present the application of computational tools in understanding functional variation from the perspective of structure, expression, evolution and phenotype

Computational Refinement of Functional Single Nucleotide Polymorphisms Associated with ATM Gene

gene are the most common forms of genetic variations that account for various forms of cancer. However, the extent to which SNPs interferes with the gene regulation and affects cancer susceptibility remains largely unknown. gene. gene function can aid in better understanding of genetic differences in disease susceptibility

rs1004819 Is the Main Disease-Associated IL23R Variant in German Crohn's Disease Patients: Combined Analysis of IL23R, CARD15, and OCTN1/2 Variants

The IL23R gene has been identified as a susceptibility gene for inflammatory bowel disease (IBD) in the North American population. The aim of our study was to test this association in a large German IBD cohort and to elucidate potential interactions with other IBD genes as well as phenotypic consequences of IL23R variants. Genomic DNA from 2670 Caucasian individuals including 833 patients with Crohn's disease (CD), 456 patients with ulcerative colitis (UC), and 1381 healthy unrelated controls was analyzed for 10 IL23R SNPs. Genotyping included the NOD2 variants p.Arg702Trp, p.Gly908Arg, and p.Leu1007fsX1008 and polymorphisms in SLC22A4/OCTN1 (1672 C-->T) and SLC22A5/OCTN2 (-207 G-->C). All IL23R gene variants analyzed displayed highly significant associations with CD. The strongest association was found for the SNP rs1004819 [P = 1.92x10(-11); OR 1.56; 95 % CI (1.37-1.78)]. 93.2% of the rs1004819 TT homozygous carriers as compared to 78% of CC wildtype carriers had ileal involvement [P = 0.004; OR 4.24; CI (1.46-12.34)]. The coding SNP rs11209026 (p.Arg381Gln) was protective for CD [P = 8.04x10(-8); OR 0.43; CI (0.31-0.59)]. Similar, but weaker associations were found in UC. There was no evidence for epistasis between the IL23R gene and the CD susceptibility genes CARD15 and SLC22A4/5. IL23R is an IBD susceptibility gene, but has no epistatic interaction with CARD15 and SLC22A4/5. rs1004819 is the major IL23R variant associated with CD in the German population, while the p.Arg381Gln IL23R variant is a protective marker for CD and UC

Supernova remnants: the X-ray perspective

Supernova remnants are beautiful astronomical objects that are also of high scientific interest, because they provide insights into supernova explosion mechanisms, and because they are the likely sources of Galactic cosmic rays. X-ray observations are an important means to study these objects.And in particular the advances made in X-ray imaging spectroscopy over the last two decades has greatly increased our knowledge about supernova remnants. It has made it possible to map the products of fresh nucleosynthesis, and resulted in the identification of regions near shock fronts that emit X-ray synchrotron radiation. In this text all the relevant aspects of X-ray emission from supernova remnants are reviewed and put into the context of supernova explosion properties and the physics and evolution of supernova remnants. The first half of this review has a more tutorial style and discusses the basics of supernova remnant physics and thermal and non-thermal X-ray emission. The second half offers a review of the recent advances.The topics addressed there are core collapse and thermonuclear supernova remnants, SN 1987A, mature supernova remnants, mixed-morphology remnants, including a discussion of the recent finding of overionization in some of them, and finally X-ray synchrotron radiation and its consequences for particle acceleration and magnetic fields.Comment: Published in Astronomy and Astrophysics Reviews. This version has 2 column-layout. 78 pages, 42 figures. This replaced version has some minor language edits and several references have been correcte