iHAP – integrated haplotype analysis pipeline for characterizing the haplotype structure of genes

Background  

The advent of genotype data from large-scale efforts that catalog the genetic variants of different populations have given rise to new avenues for multifactorial disease association studies. Recent work shows that genotype data from the International HapMap Project have a high degree of transferability to the wider population. This implies that the design of genotyping studies on local populations may be facilitated through inferences drawn from information contained in HapMap populations.     

Association of common polymorphisms in known susceptibility genes with rheumatoid arthritis in a Slovak population using osteoarthritis patients as controls

Introduction  

Both genetic and environmental factors contribute to rheumatoid arthritis (RA), a common and complex autoimmune disease. As well as the major susceptibility gene HLA-DRB1, recent genome-wide and candidate-gene studies reported additional evidence for association of single nucleotide polymorphism (SNP) markers in the PTPN22, STAT4, OLIG3/TNFAIP3 and TRAF1/C5 loci with RA. This study was initiated to investigate the association between defined genetic markers and RA in a Slovak population. In contrast to recent studies, we included intensively-characterized osteoarthritis (OA) patients as controls.     

Gene Prospector: An evidence gateway for evaluating potential susceptibility genes and interacting risk factors for human diseases

Background  

Millions of single nucleotide polymorphisms have been identified as a result of the human genome project and the rapid advance of high throughput genotyping technology. Genetic association studies, such as recent genome-wide association studies (GWAS), have provided a springboard for exploring the contribution of inherited genetic variation and gene/environment interactions in relation to disease. Given the capacity of such studies to produce a plethora of information that may then be described in a number of publications, selecting possible disease susceptibility genes and identifying related modifiable risk factors is a major challenge. A Web-based application for finding evidence of such relationships is key to the development of follow-up studies and evidence for translational research.     

New application of intelligent agents in sporadic amyotrophic lateral sclerosis identifies unexpected specific genetic background

Background  

Few genetic factors predisposing to the sporadic form of amyotrophic lateral sclerosis (ALS) have been identified, but the pathology itself seems to be a true multifactorial disease in which complex interactions between environmental and genetic susceptibility factors take place. The purpose of this study was to approach genetic data with an innovative statistical method such as artificial neural networks to identify a possible genetic background predisposing to the disease. A DNA multiarray panel was applied to genotype more than 60 polymorphisms within 35 genes selected from pathways of lipid and homocysteine metabolism, regulation of blood pressure, coagulation, inflammation, cellular adhesion and matrix integrity, in 54 sporadic ALS patients and 208 controls. Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis     

Genotype determination for polymorphisms in linkage disequilibrium

Background  

Genome-wide association studies with single nucleotide polymorphisms (SNPs) show great promise to identify genetic determinants of complex human traits. In current analyses, genotype calling and imputation of missing genotypes are usually considered as two separated tasks. The genotypes of SNPs are first determined one at a time from allele signal intensities. Then the missing genotypes, i.e., no-calls caused by not perfectly separated signal clouds, are imputed based on the linkage disequilibrium (LD) between multiple SNPs. Although many statistical methods have been developed to improve either genotype calling or imputation of missing genotypes, treating the two steps independently can lead to loss of genetic information.     

Genetic,clinical and radiographic signs in knee osteoarthritis susceptibility

Introduction

Osteoarthritis (OA) is considered to be a multifactorial and polygenic disease and diagnosis is mainly clinical and radiological. Correlation between radiographic data and clinical status has been reported. However, very few studies, especially in Caucasian people, describe the association between the Kellgren and Lawrence OA grading scale (KL) and genetic alterations to better understand OA etiopathogenesis and susceptibility. In order to update the knee OA grading, in this study we assessed the associations between KL grade, clinical features such as American Knee Society Score (AKSS), age, and polymorphisms in the principal osteoarthritis susceptibility (OS) genes in Sicilian individuals.

Methods

In 66 Sicilian individuals affected by primary knee OA, the clinical and radiographic evaluation was performed using 2 sub-scores of AKSS (knee score (KS) and function score (FS)) and KL. The patients were also classified according to age. Online Mendelian Inheritance in Man (OMIM) and Database of Single Nucleotide Polymorphisms (dbSNP) Short Genetic Variations databases were used to select gene regions containing the following polymorphisms to analyze: FRZB rs288326 and rs7775, MATN3 rs77245812, ASPN D14 repeats, PTHR2 rs76758470, GDF5 rs143383 and DVWA rs11718863. Patient genotypes were obtained using Sanger DNA sequencing analysis.

Results

In our cohort of patients a statistical association between the variables analyzed was reported in all associations tested (KL versus KS, FS and age). We observed that a mild to severe OA radiographic grade is related to severe clinical conditions and loss of articular function and that the severity of symptoms increases with age. Concerning the genotyping analysis, our results revealed a significant statistical association between KL grading and GDF5 rs143383 and DVWA rs11718863 genetic alterations. The latter was also associated with a more severe radiographic grade, displaying its predictive role as OA marker progression. Statistically significant association between clinical, radiographic and genetic signs observed, suggests extending the actual grading of knee OA based mainly on X-ray features.

Conclusions

This work represents a multidisciplinary and translational medicine approach to study OA where clinical, radiological, and OS5 and OS6 SNPs evaluation could contribute to better define grading and progression of OA and to the development of new therapies.     

Genetic Loci Involved in Antibody Response to Mycobacterium avium ssp. paratuberculosis in Cattle

Background

Mycobacterium avium subsp. paratuberculosis (MAP) causes chronic enteritis in a wide range of animal species. In cattle, MAP causes a chronic disease called Johne''s disease, or paratuberculosis, that is not treatable and the efficacy of vaccine control is controversial. The clinical phase of the disease is characterised by diarrhoea, weight loss, drop in milk production and eventually death. Susceptibility to MAP infection is heritable with heritability estimates ranging from 0.06 to 0.10. There have been several studies over the last few years that have identified genetic loci putatively associated with MAP susceptibility, however, with the availability of genome-wide high density SNP maker panels it is now possible to carry out association studies that have higher precision.

Methodology/Principal Findings

The objective of the current study was to localize genes having an impact on Johne''s disease susceptibility using the latest bovine genome information and a high density SNP panel (Illumina BovineSNP50 BeadChip) to perform a case/control, genome-wide association analysis. Samples from MAP case and negative controls were selected from field samples collected in 2007 and 2008 in the province of Lombardy, Italy. Cases were defined as animals serologically positive for MAP by ELISA. In total 966 samples were genotyped: 483 MAP ELISA positive and 483 ELISA negative. Samples were selected randomly among those collected from 119 farms which had at least one positive animal.

Conclusion/Significance

The analysis of the genotype data identified several chromosomal regions associated with disease status: a region on chromosome 12 with high significance (P<5×10⁻⁶), while regions on chromosome 9, 11, and 12 had moderate significance (P<5×10⁻⁵). These results provide evidence for genetic loci involved in the humoral response to MAP. Knowledge of genetic variations related to susceptibility will facilitate the incorporation of this information into breeding programmes for the improvement of health status.     

Using the longest significance run to estimate region-specific p-values in genetic association mapping studies

Background  

Association testing is a powerful tool for identifying disease susceptibility genes underlying complex diseases. Technological advances have yielded a dramatic increase in the density of available genetic markers, necessitating an increase in the number of association tests required for the analysis of disease susceptibility genes. As such, multiple-tests corrections have become a critical issue. However the conventional statistical corrections on locus-specific multiple tests usually result in lower power as the number of markers increases. Alternatively, we propose here the application of the longest significant run (LSR) method to estimate a region-specific p-value to provide an index for the most likely candidate region.     

Genotyping and inflated type I error rate in genome-wide association case/control studies

Background  

One common goal of a case/control genome wide association study (GWAS) is to find SNPs associated with a disease. Traditionally, the first step in such studies is to assign a genotype to each SNP in each subject, based on a statistic summarizing fluorescence measurements. When the distributions of the summary statistics are not well separated by genotype, the act of genotype assignment can lead to more potential problems than acknowledged by the literature.     

Robust joint analysis allowing for model uncertainty in two-stage genetic association studies

Background  

The cost efficient two-stage design is often used in genome-wide association studies (GWASs) in searching for genetic loci underlying the susceptibility for complex diseases. Replication-based analysis, which considers data from each stage separately, often suffers from loss of efficiency. Joint test that combines data from both stages has been proposed and widely used to improve efficiency. However, existing joint analyses are based on test statistics derived under an assumed genetic model, and thus might not have robust performance when the assumed genetic model is not appropriate.     

Association of a BMP5 microsatellite with knee osteoarthritis: case-control study

Introduction

We aimed to explore the involvement of a multiallelic functional polymorphism in knee osteoarthritis (OA) susceptibility as a prototype of possible genetic factors escaping GWAS detection.

Methods

OA patients and controls from three European populations (Greece, Spain and the UK) adding up to 1003 patients (716 women, 287 men) that had undergone total knee joint replacement (TKR) due to severe primary OA and 1543 controls (758 women, 785 men) lacking clinical signs or symptoms of OA were genotyped for the D6S1276 microsatellite in intron 1 of BMP5. Genotype and mutiallelic trend tests were used to compare cases and controls.

Results

Significant association was found between the microsatellite and knee OA in women (P from 3.1 x10^-4 to 4.1 x10^-4 depending on the test), but not in men. Three of the alleles showed significant differences between patients and controls, one of them of increased risk and two of protection. The gender association and the allele direction of change were very concordant with those previously reported for hip OA.

Conclusions

We have found association of knee OA in women with the D6S1276 functional microsatellite that modifies in cis the expression of BMP5 making this a sounder OA genetic factor and extending its involvement to other joints. This result also shows the interest of analysing other multiallelic polymorphisms.     

Significant association of interleukin-4 gene intron 3 VNTR polymorphism with susceptibility to knee osteoarthritis

Objective

Interleukin-4 (IL-4) is a strong chondroprotective cytokine and polymorphisms within this gene may be a risk factor for osteoarthritis (OA). We aimed to investigate genotype and allele frequencies of IL-4 gene intron 3 variable number of tandem repeats (VNTR) polymorphism in patients with knee OA in a Turkish population.

Methods

The study included 202 patients with knee OA and 180 healthy controls. Genomic DNA was isolated and IL-4 gene 70 bp VNTR polymorphism determined by using polymerase chain reaction (PCR) with specific primers followed by restriction fragment length polymorphism (RFLP) analysis.

Results

Our result show that there was statistically significant difference between knee OA patients and control group with respect to IL-4 genotype distribution and allele frequencies (p = 0.000, OR: 0.20, 95% CI: 0.10–0.41, OR: 0.22, 95% CI: 0.12–0.42, respectively).

Conclusions

Our findings suggest that there is an association of IL-4 gene intron 3 VNTR polymorphism with susceptibility of a person for development of knee OA. As a result, IL-4 gene intron 3 VNTR polymorphism could be a genetic marker in OA in a Turkish study population. This is the first association study that evaluates the associations between IL-4 gene VNTR polymorphism and knee OA.     

An FPT haplotyping algorithm on pedigrees with a small number of sites

Background  

Genetic disease studies investigate relationships between changes in chromosomes and genetic diseases. Single haplotypes provide useful information for these studies but extracting single haplotypes directly by biochemical methods is expensive. A computational method to infer haplotypes from genotype data is therefore important. We investigate the problem of computing the minimum number of recombination events for general pedigrees with a small number of sites for all members.     

Function2Gene: A gene selection tool to increase the power of genetic association studies by utilizing public databases and expert knowledge

Background  

Many common disorders have multiple genetic components which convey increased susceptibility. SNPs have been used to identify genetic components which are associated with a disease. Unfortunately, many studies using these methods suffer from low reproducibility due to lack of power.     

FastTagger: an efficient algorithm for genome-wide tag SNP selection using multi-marker linkage disequilibrium

Background  

Human genome contains millions of common single nucleotide polymorphisms (SNPs) and these SNPs play an important role in understanding the association between genetic variations and human diseases. Many SNPs show correlated genotypes, or linkage disequilibrium (LD), thus it is not necessary to genotype all SNPs for association study. Many algorithms have been developed to find a small subset of SNPs called tag SNPs that are sufficient to infer all the other SNPs. Algorithms based on the r ² LD statistic have gained popularity because r ² is directly related to statistical power to detect disease associations. Most of existing r ² based algorithms use pairwise LD. Recent studies show that multi-marker LD can help further reduce the number of tag SNPs. However, existing tag SNP selection algorithms based on multi-marker LD are both time-consuming and memory-consuming. They cannot work on chromosomes containing more than 100 k SNPs using length-3 tagging rules.     

Can Data Science Inform Environmental Justice and Community Risk Screening for Type 2 Diabetes?

Background

Having the ability to scan the entire country for potential “hotspots” with increased risk of developing chronic diseases due to various environmental, demographic, and genetic susceptibility factors may inform risk management decisions and enable better environmental public health policies.

Objectives

Develop an approach for community-level risk screening focused on identifying potential genetic susceptibility hotpots.

Methods

Our approach combines analyses of phenotype-genotype data, genetic prevalence of single nucleotide polymorphisms, and census/geographic information to estimate census tract-level population attributable risks among various ethnicities and total population for the state of California.

Results

We estimate that the rs13266634 single nucleotide polymorphism, a type 2 diabetes susceptibility genotype, has a genetic prevalence of 56.3%, 47.4% and 37.0% in Mexican Mestizo, Caucasian, and Asian populations. Looking at the top quintile for total population attributable risk, 16 California counties have greater than 25% of their population living in hotspots of genetic susceptibility for developing type 2 diabetes due to this single genotypic susceptibility factor.

Conclusions

This study identified counties in California where large portions of the population may bear additional type 2 diabetes risk due to increased genetic prevalence of a susceptibility genotype. This type of screening can easily be extended to include information on environmental contaminants of interest and other related diseases, and potentially enables the rapid identification of potential environmental justice communities. Other potential uses of this approach include problem formulation in support of risk assessments, land use planning, and prioritization of site cleanup and remediation actions.     

A genome wide association scan of bovine tuberculosis susceptibility in Holstein-Friesian dairy cattle

Background

Bovine tuberculosis is a significant veterinary and financial problem in many parts of the world. Although many factors influence infection and progression of the disease, there is a host genetic component and dissection of this may enlighten on the wider biology of host response to tuberculosis. However, a binary phenotype of presence/absence of infection presents a noisy signal for genomewide association study.

Methodology/Principal Findings

We calculated a composite phenotype of genetic merit for TB susceptibility based on disease incidence in daughters of elite sires used for artificial insemination in the Irish dairy herd. This robust measure was compared with 44,426 SNP genotypes in the most informative 307 subjects in a genome wide association analysis. Three SNPs in a 65 kb genomic region on BTA 22 were associated (i.e. p<10⁻⁵, peaking at position 59588069, p = 4.02×10⁻⁶) with tuberculosis susceptibility.

Conclusions/Significance

A genomic region on BTA 22 was suggestively associated with tuberculosis susceptibility; it contains the taurine transporter gene SLC6A6, or TauT, which is known to function in the immune system but has not previously been investigated for its role in tuberculosis infection.     

SNPs3D: Candidate gene and SNP selection for association studies

Background  

The relationship between disease susceptibility and genetic variation is complex, and many different types of data are relevant. We describe a web resource and database that provides and integrates as much information as possible on disease/gene relationships at the molecular level.     

Pharmacogenetic Study of Drug-Metabolising Enzyme Polymorphisms on the Risk of Anti-Tuberculosis Drug-Induced Liver Injury: A Meta-Analysis

Background

Three first-line antituberculosis drugs, isoniazid, rifampicin and pyrazinamide, may induce liver injury, especially isoniazid. This antituberculosis drug-induced liver injury (ATLI) ranges from a mild to severe form, and the associated mortality cases are not rare. In the past decade, many investigations have focused the association between drug-metabolising enzyme (DME) gene polymorphisms and risk for ATLI; however, these studies have yielded contradictory results.

Methods

PubMed, EMBASE, ISI web of science and the Chinese National Knowledge Infrastructure databases were systematically searched to identify relevant studies. A meta-analysis was performed to examine the association between polymorphisms from 4 DME genes (NAT2, CYP2E1, GSTM1 and GSTT1) and susceptibility to ATLI. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Heterogeneity among articles and their publication bias were also tested.

Results

38 studies involving 2,225 patients and 4,906 controls were included. Overall, significantly increased ATLI risk was associated with slow NAT2 genotype and GSTM1 null genotype when all studies were pooled into the meta-analysis. Significantly increased risk was also found for CYP2E1*1A in East Asians when stratified by ethnicity. However, no significant results were observed for GSTT1.

Conclusions

Our results demonstrated that slow NAT2 genotype, CYP2E1*1A and GSTM1 null have a modest effect on genetic susceptibility to ATLI.     

Optimal Step Length EM Algorithm (OSLEM) for the estimation of haplotype frequency and its application in lipoprotein lipase genotyping

Background  

Haplotype based linkage disequilibrium (LD) mapping has become a powerful and cost-effective method for performing genetic association studies, particularly in the search for genetic markers in linkage disequilibrium with complex disease loci. Various methods (e.g. Monte-Carlo (Gibbs sampling); EM (expectation maximization); and Clark's method) have been used to estimate haplotype frequencies from routine genotyping data.