The influence of genetic polymorphisms in XRCC3 and ADH5 genes on the frequency of genotoxicity biomarkers in workers exposed to formaldehyde

The International Agency for Research on Cancer classified formaldehyde as carcinogenic to humans because there is “sufficient epidemiological evidence that it causes nasopharyngeal cancer in humans”. Genes involved in DNA repair and maintenance of genome integrity are critically involved in protecting against mutations that lead to cancer and/or inherited genetic disease. Association studies have recently provided evidence for a link between DNA repair polymorphisms and micronucleus (MN) induction. We used the cytokinesis-block micronucleus (CBMN assay) in peripheral lymphocytes and MN test in buccal cells to investigate the effects of XRCC3 Thr241Met, ADH5 Val309Ile, and Asp353Glu polymorphisms on the frequency of genotoxicity biomarkers in individuals occupationally exposed to formaldehyde (n = 54) and unexposed workers (n = 82). XRCC3 participates in DNA double-strand break/recombination repair, while ADH5 is an important component of cellular metabolism for the elimination of formaldehyde. Exposed workers had significantly higher frequencies (P < 0.01) than controls for all genotoxicity biomarkers evaluated in this study. Moreover, there were significant associations between XRCC3 genotypes and nuclear buds, namely XRCC3 Met/Met (OR = 3.975, CI 1.053–14.998, P = 0.042) and XRCC3 Thr/Met (OR = 5.632, CI 1.673–18.961, P = 0.005) in comparison with XRCC3 Thr/Thr. ADH5 polymorphisms did not show significant effects. This study highlights the importance of integrating genotoxicity biomarkers and genetic polymorphisms in human biomonitoring studies.

Arrow Plot: a new graphical tool for selecting up and down regulated genes and genes differentially expressed on samples subgroups

Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

Fat intake interacts with polymorphisms of Caspase9, FasLigand and PPARgamma apoptotic genes in modulating Crohn's disease activity

Background & aims: Crohn’s disease (CD) is a multifactorial disease where resistance to apoptosis is one major defect. Also, dietary fat intake has been shown to modulate disease activity. We aimed to explore the interaction between four single nucleotide polymorphisms (SNPs) in apoptotic genes and dietary fat intake in modulating disease activity in CD patients. Methods: Polymerase Chain Reaction (PCR) and Restriction Fragment Length Polymorphism (RFLP) techniques were used to analyze Caspase9þ93C/T, FasLigand-843C/T, Peroxisome Proliferator-Activated Receptor gammaþ161C/T and Peroxisome Proliferator-Activated Receptor gamma Pro12Ala SNPs in 99 patients with CD and 116 healthy controls. Interactions between SNPs and fat intake in modulating disease activity were analyzed using regression analysis. Results: None of the polymorphisms analyzed influenced disease susceptibility and/or activity, but a high intake of total, saturated and monounsaturated fats and a higher ratio of n-6/n-3 polyunsaturated fatty acids (PUFA), was associated with a more active phenotype (p < 0.05). We observed that the detrimental effect of a high intake of total and trans fat was more marked in wild type carriers of the Caspase9þ93C/T polymorphism [O.R (95%CI) 4.64 (1.27e16.89) and O.R (95%CI) 4.84 (1.34e17.50)]. In the Peroxisome Proliferator-Activated Receptor gamma Pro12Ala SNP, we also observed that a high intake of saturated and monounsaturated fat was associated to a more active disease in wild type carriers [OR (95%CI) 4.21 (1.33e13.26) and 4.37 (1.52e12.51)]. Finally, a high intake of n-6 PUFA was associated with a more active disease in wild type carriers for the FasLigand-843C/T polymorphism [O.R (95%CI) 5.15 (1.07e24.74)]. Conclusions: To our knowledge, this is the first study to disclose a synergism between fat intake and SNPs in apoptotic genes in modulating disease activity in CD patients.

The risk-return trade-off in Europe: A temporal and cross-sectional analysis

This paper analyzes the risk-return trade-off in European equities considering both temporal and cross-sectional dimensions. In our analysis, we introduce not only the market portfolio but also 15 industry portfolios comprising the entire market. Several bivariate GARCH models are estimated to obtain the covariance matrix between excess market returns and the industrial portfolios and the existence of a risk-return trade-off is analyzed through a cross-sectional approach using the information in all portfolios. It is obtained evidence for a positive and significant risk-return trade-off in the European market. This conclusion is robust for different GARCH specifications and is even more evident after controlling for the main financial crisis during the sample period.