A multicenter study confirms CD226 gene association with systemic sclerosis-related pulmonary fibrosis.

INTRODUCTION CD226 genetic variants have been associated with a number of autoimmune diseases and recently with systemic sclerosis (SSc). The aim of this study was to test the influence of CD226 loci in SSc susceptibility, clinical phenotypes and autoantibody status in a large multicenter European population. METHODS A total of seven European populations of Caucasian ancestry were included, comprising 2,131 patients with SSc and 3,966 healthy controls. Three CD226 single nucleotide polymorphisms (SNPs), rs763361, rs3479968 and rs727088, were genotyped using Taqman 5'allelic discrimination assays. RESULTS Pooled analyses showed no evidence of association of the three SNPs, neither with the global disease nor with the analyzed subphenotypes. However, haplotype block analysis revealed a significant association for the TCG haplotype (SNP order: rs763361, rs34794968, rs727088) with lung fibrosis positive patients (PBonf = 3.18E-02 OR 1.27 (1.05 to 1.54)). CONCLUSION Our data suggest that the tested genetic variants do not individually influence SSc susceptibility but a CD226 three-variant haplotype is related with genetic predisposition to SSc-related pulmonary fibrosis.

Association of genetic variation with systolic and diastolic blood pressure among African Americans: the Candidate Gene Association Resource study.

The prevalence of hypertension in African Americans (AAs) is higher than in other US groups; yet, few have performed genome-wide association studies (GWASs) in AA. Among people of European descent, GWASs have identified genetic variants at 13 loci that are associated with blood pressure. It is unknown if these variants confer susceptibility in people of African ancestry. Here, we examined genome-wide and candidate gene associations with systolic blood pressure (SBP) and diastolic blood pressure (DBP) using the Candidate Gene Association Resource (CARe) consortium consisting of 8591 AAs. Genotypes included genome-wide single-nucleotide polymorphism (SNP) data utilizing the Affymetrix 6.0 array with imputation to 2.5 million HapMap SNPs and candidate gene SNP data utilizing a 50K cardiovascular gene-centric array (ITMAT-Broad-CARe [IBC] array). For Affymetrix data, the strongest signal for DBP was rs10474346 (P= 3.6 × 10(-8)) located near GPR98 and ARRDC3. For SBP, the strongest signal was rs2258119 in C21orf91 (P= 4.7 × 10(-8)). The top IBC association for SBP was rs2012318 (P= 6.4 × 10(-6)) near SLC25A42 and for DBP was rs2523586 (P= 1.3 × 10(-6)) near HLA-B. None of the top variants replicated in additional AA (n = 11 882) or European-American (n = 69 899) cohorts. We replicated previously reported European-American blood pressure SNPs in our AA samples (SH2B3, P= 0.009; TBX3-TBX5, P= 0.03; and CSK-ULK3, P= 0.0004). These genetic loci represent the best evidence of genetic influences on SBP and DBP in AAs to date. More broadly, this work supports that notion that blood pressure among AAs is a trait with genetic underpinnings but also with significant complexity.

Disease-Gene Association Using a Genetic Algorithm

Understanding the relationship between genetic diseases and the genes associated with them is an important problem regarding human health. The vast amount of data created from a large number of high-throughput experiments performed in the last few years has resulted in an unprecedented growth in computational methods to tackle the disease gene association problem. Nowadays, it is clear that a genetic disease is not a consequence of a defect in a single gene. Instead, the disease phenotype is a reflection of various genetic components interacting in a complex network. In fact, genetic diseases, like any other phenotype, occur as a result of various genes working in sync with each other in a single or several biological module(s). Using a genetic algorithm, our method tries to evolve communities containing the set of potential disease genes likely to be involved in a given genetic disease. Having a set of known disease genes, we first obtain a protein-protein interaction (PPI) network containing all the known disease genes. All the other genes inside the procured PPI network are then considered as candidate disease genes as they lie in the vicinity of the known disease genes in the network. Our method attempts to find communities of potential disease genes strongly working with one another and with the set of known disease genes. As a proof of concept, we tested our approach on 16 breast cancer genes and 15 Parkinson's Disease genes. We obtained comparable or better results than CIPHER, ENDEAVOUR and GPEC, three of the most reliable and frequently used disease-gene ranking frameworks.

Disease-Gene Association Using Genetic Programming

As a result of mutation in genes, which is a simple change in our DNA, we will have undesirable phenotypes which are known as genetic diseases or disorders. These small changes, which happen frequently, can have extreme results. Understanding and identifying these changes and associating these mutated genes with genetic diseases can play an important role in our health, by making us able to find better diagnosis and therapeutic strategies for these genetic diseases. As a result of years of experiments, there is a vast amount of data regarding human genome and different genetic diseases that they still need to be processed properly to extract useful information. This work is an effort to analyze some useful datasets and to apply different techniques to associate genes with genetic diseases. Two genetic diseases were studied here: Parkinson’s disease and breast cancer. Using genetic programming, we analyzed the complex network around known disease genes of the aforementioned diseases, and based on that we generated a ranking for genes, based on their relevance to these diseases. In order to generate these rankings, centrality measures of all nodes in the complex network surrounding the known disease genes of the given genetic disease were calculated. Using genetic programming, all the nodes were assigned scores based on the similarity of their centrality measures to those of the known disease genes. Obtained results showed that this method is successful at finding these patterns in centrality measures and the highly ranked genes are worthy as good candidate disease genes for being studied. Using standard benchmark tests, we tested our approach against ENDEAVOUR and CIPHER - two well known disease gene ranking frameworks - and we obtained comparable results.

Promoter- and RNA polymerase II-dependent hsp-16 gene association with nuclear pores in Caenorhabditis elegans.

Some inducible yeast genes relocate to nuclear pores upon activation, but the general relevance of this phenomenon has remained largely unexplored. Here we show that the bidirectional hsp-16.2/41 promoter interacts with the nuclear pore complex upon activation by heat shock in the nematode Caenorhabditis elegans. Direct pore association was confirmed by both super-resolution microscopy and chromatin immunoprecipitation. The hsp-16.2 promoter was sufficient to mediate perinuclear positioning under basal level conditions of expression, both in integrated transgenes carrying from 1 to 74 copies of the promoter and in a single-copy genomic insertion. Perinuclear localization of the uninduced gene depended on promoter elements essential for induction and required the heat-shock transcription factor HSF-1, RNA polymerase II, and ENY-2, a factor that binds both SAGA and the THO/TREX mRNA export complex. After induction, colocalization with nuclear pores increased significantly at the promoter and along the coding sequence, dependent on the same promoter-associated factors, including active RNA polymerase II, and correlated with nascent transcripts.

Association between bipolar disorder and monoamine oxidase A gene polymorphisms: results of a multicenter study

OBJECTIVE: Although genetic factors have been implicated in the etiology of bipolar disorder, no specific gene has been conclusively identified. Given the link between abnormalities in serotonergic neurotransmission and bipolar disorder, a candidate gene association approach was applied to study the involvement of the monoamine oxidase A (MAOA) gene, which codes for a catabolic enzyme of serotonin, in the susceptibility to bipolar disorder. METHOD: In France and Switzerland, 272 patients with bipolar disorder and 122 healthy subjects were typed for three polymorphic markers of the MAOA gene: the MAOA-CA repeat, the MAOA restriction fragment length polymorphism (RFLP), and a repeat directly adjacent to the variable number of tandem repeats (VNTR) locus. RESULTS: A significant difference in the distribution of the alleles for the MAOA-CA repeat was observed between the female bipolar patients and comparison group. CONCLUSIONS: The results obtained in the French and Swiss population confirm findings from two studies conducted in the United Kingdom.

Association of CSSM066 and ILSTS011 microsatellite markers and thyroglobulin gene SNP with backfat in Canchim cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview

Background: DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. Results: Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. Conclusions: DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

No Association Between MTHFR A1298C and MTRR A66G Polymorphisms, and MS in an Australian Cohort

Multiple sclerosis (MS) is a complex neurological disease that affects the central nervous system (CNS) resulting in debilitating neuropathology. Pathogenesis is primarily defined by CNS inflammation and demyelination of nerve axons. Methionine synthase reductase (MTRR) is an enzyme that catalyzes the remethylation of homocysteine (Hcy) to methionine via cobalamin and folate dependant reactions. Cobalamin acts as an intermediate methyl carrier between methylenetetrahydrofolate reductase (MTHFR) and Hcy. MTRR plays a critical role in maintaining cobalamin in an active form and is consequently an important determinant of total plasma Hcy (pHcy) concentrations. Elevated intracellular pHcy levels have been suggested to play a role in CNS dysfunction, neurodegenerative, and cerebrovascular diseases. Our investigation entailed the genotyping of a cohort of 140 cases and matched controls for MTRR and MTHFR, by restriction length polymorphism (RFLP) techniques. Two polymorphisms: MTRR A66G and MTHFR A1298C were investigated in an Australian age and gender matched case-control study. No significant allelic frequency difference was observed between cases and controls at the α = 0.05 level (MTRR χ^2 = 0.005, P = 0.95, MTHFR χ^2 = 1.15, P = 0.28). Our preliminary findings suggest no association between the MTRR A66G and MTHFR A1298C polymorphisms and MS.

Association analysis of human leukocyte antigen class II (DRB1) alleles with leprosy in individuals from São Luís, state of Maranhão, Brazil

Epidemiological studies have demonstrated that the variability of the clinical response to infection caused by Mycobacterium leprae is associated with host genetic factors. The present study investigated the frequency of human leukocyte antigen (HLA) class II (DRB1) alleles in patients with leprosy from São Luís, Maranhão, Brazil. A case-control study was performed in 85 individuals with leprosy and 85 healthy subjects. All samples were analysed via polymerase chain reaction-sequence specific oligonucleotide probes. The HLA-DRB1*16 allele showed a higher frequency in the group with leprosy [(9.41% vs. 4.12%) odds ratio (OR) = 2.41 95% confidence interval (CI) (0.96-6.08) p = 0.05], whereas the HLA-DRB1*11 allele was less frequent in the group with leprosy [(6.47% vs. 11.76%) OR = 0.51 95% CI (0.23-1.12) p = 0.09]. The frequency of HLA-DRB1* alleles between the control group and leprosy patient subgroups presenting different forms of the disease showed that the HLA-DRB1*16 (16.13% vs. 8.24%, OR = 4.10, CI = 1.27-13.27, p = 0.010) and HLA-DRB1*14 (5% vs. 3.53%, OR = 4.63, CI = 1.00-21.08, p = 0.032) alleles were significantly more frequent in patients with different clinical subtypes of leprosy. The sample size was a limitation in this study. Nevertheless, the results demonstrated the existence of a genetic susceptibility associated with the clinical forms of leprosy. The low frequency of the HLA-DRB1*11 allele should be further studied to investigate the possible protective effect of this allele.

A Test of Association between Qualitative Trait and a Set of SNPs

2000 Mathematics Subject Classification: 62P10, 92D10, 92D30, 62F03

Arg72Pro TP53 polymorphism and cancer susceptibility: a comprehensive meta-analysis of 302 case-control studies

Arg72Pro is a common polymorphism in TP53, showing differences in its biological functions. Case-control studies have been performed to elucidate the role of Arg72Pro in cancer, although the results are conflicting and heterogeneous. Here, we analyzed pooled data from case-control studies to determine the role of Arg72Pro in different cancer sites. We performed a systematic review and meta-analysis of 302 case-control studies that analyzed Arg72Pro in cancer susceptibility. Odds ratios were estimated for different tumor sites using distinct genetic models, and the heterogeneity between studies was explored using I(2) values and meta-regression. We adopted quality criteria to classify the studies. Subgroup analyses were done for tumor sites according to ethnicity, histological, and anatomical sites. Results indicated that Arg72Pro is associated with higher susceptibility to cancer in some tumor sites, mainly hepatocarcinoma. For some tumor sites, quality of studies was associated with the size of genetic association, mainly in cervical, head and neck, gastric, and lung cancer. However, study quality did not explain the observed heterogeneity substantially. Meta-regression showed that ethnicity, allelic frequency and genotyping method were responsible for a substantial part of the heterogeneity observed. Our results suggest ethnicity and histological and anatomical sites may modulate the penetrance of Arg72Pro in cancer susceptibility. This meta-analysis denotes the importance for more studies with good quality and that the covariates responsible for heterogeneity should be controlled to obtain a more conclusive response about the function of Arg72Pro in cancer.

Burkitt Lymphoma in Brazil Is Characterized by Geographically Distinct Clinicopathologic Features

Burkitt lymphoma (BL) is a highly aggressive non-Hodgkin lymphoma with a consistent MYC translocation. Epstein-Barr virus (EBV) has been associated with BL at different frequencies, depending on the clinical variant and geographic regions. This is a large-scale study of BL in Brazil, including 234 patients from 5 geographic regions that are widely disparate socioeconomically, including pediatric (61.1%) and adult (37.6%) populations. EBV was present in 52.6% of all BL cases, varying from 29% (12/42) in the South to 76% (13/17) in the North. Most of the cases were EBV type A. The frequency was higher in the pediatric group, and EBV association within this age range predominated in all regions except the South. Expression of p53 protein was observed inn 16.2%, and only rare cases showed p63 expression. BL in Brazil is regionally distinct and has a low incidence of p53 overexpression and a higher-than-expected association with EBV in sporadic cases.

The genetic basis of sleep disorders.

The contribution of genes, environment and gene-environment interactions to sleep disorders is increasingly recognized. Well-documented familial and twin sleep disorder studies suggest an important influence of genetic factors. However, only few sleep disorders have an established genetic basis including four rare diseases that may result from a single gene mutation: fatal familial insomnia, familial advanced sleep-phase syndrome, chronic primary insomnia, and narcolepsy with cataplexy. However, most sleep disorders are complex in terms of their genetic susceptibility together with the variable expressivity of the phenotype even within a same family. Recent linkage, genome-wide and candidate gene association studies resulted in the identification of gene mutations, gene localizations, or evidence for susceptibility genes and/or loci in several sleep disorders. Molecular techniques including mainly genome-wide linkage and association studies are further required to identify the contribution of new genes. These identified susceptibility genetic determinants will provide clues to better understand pathogenesis of sleep disorders, to assess the risk for diseases and also to find new drug targets to treat and to prevent the underlying conditions. We reviewed here the role of genetic basis in most of key sleep disorders.