Influence of host interleukin-10 polymorphisms on development of traveler's diarrhea due to heat-labile enterotoxin-producing Escherichia coli in travelers from the United States who are visiting Mexico.

Up to 60% of U.S. visitors to Mexico develop traveler's diarrhea (TD), mostly due to enterotoxigenic Escherichia coli (ETEC) strains that produce heat-labile (LT) and/or heat-stable (ST) enterotoxins. Distinct single-nucleotide polymorphisms (SNPs) within the interleukin-10 (IL-10) promoter have been associated with high, intermediate, or low production of IL-10. We conducted a prospective study to investigate the association of SNPs in the IL-10 promoter and the occurrence of TD in ETEC LT-exposed travelers. Sera from U.S. travelers to Mexico collected on arrival and departure were studied for ETEC LT seroconversion by using cholera toxin as the antigen. Pyrosequencing was performed to genotype IL-10 SNPs. Stools from subjects who developed diarrhea were also studied for other enteropathogens. One hundred twenty-one of 569 (21.3%) travelers seroconverted to ETEC LT, and among them 75 (62%) developed diarrhea. Symptomatic seroconversion was more commonly seen in subjects who carried a genotype producing high levels of IL-10; it was seen in 83% of subjects with the GG genotype versus 54% of subjects with the AA genotype at IL-10 gene position -1082 (P, 0.02), in 71% of those with the CC genotype versus 33% of those with the TT genotype at position -819 (P, 0.005), and in 71% of those with the CC genotype versus 38% of those with the AA genotype at position -592 (P, 0.02). Travelers with the GCC haplotype were more likely to have symptomatic seroconversion than those with the ATA haplotype (71% versus 38%; P, 0.002). Travelers genetically predisposed to produce high levels of IL-10 were more likely to experience symptomatic ETEC TD.

Gene by BMI Interactions Influencing C-Reactive Protein Levels in European-Americans

C-Reactive Protein (CRP) is a biomarker indicating tissue damage, inflammation, and infection. High-sensitivity CRP (hsCRP) is an emerging biomarker often used to estimate an individual’s risk for future coronary heart disease (CHD). hsCRP levels falling below 1.00 mg/l indicate a low risk for developing CHD, levels ranging between 1.00 mg/l and 3.00 mg/l indicate an elevated risk, and levels exceeding 3.00 mg/l indicate high risk. Multiple Genome-Wide Association Studies (GWAS) have identified a number of genetic polymorphisms which influence CRP levels. SNPs implicated in such studies have been found in or near genes of interest including: CRP, APOE, APOC, IL-6, HNF1A, LEPR, and GCKR. A strong positive correlation has also been found to exist between CRP levels and BMI, a known risk factor for CHD and a state of chronic inflammation. We conducted a series of analyses designed to identify loci which interact with BMI to influence CRP levels in a subsample of European-Americans in the ARIC cohort. In a stratified GWA analysis, 15 genetic regions were identified as having significantly (p-value < 2.00*10-3) distinct effects on hsCRP levels between the two obesity strata: lean (18.50 kg/m2 < BMI < 24.99 kg/m2) and obese (BMI ≥ 30.00 kg/m2). A GWA analysis performed on all individuals combined (i.e. not a priori stratified for obesity status) with the inclusion of an additional parameter for BMI by gene interaction, identified 11 regions which interact with BMI to influence hsCRP levels. Two regions containing the genes GJA5 and GJA8 (on chromosome 1) and FBXO11 (on chromosome 2) were identified in both methods of analysis suggesting that these genes possibly interact with BMI to influence hsCRP levels. We speculate that atrial fibrillation (AF), age-related cataracts and the TGF-β pathway may be the biological processes influenced by the interaction of GJA5, GJA8 and FBXO11, respectively, with BMI to cause changes in hsCRP levels. Future studies should focus on the influence of gene x bmi interaction on AF, age-related cataracts and TGF-β.

THE EXPRESSION PROFILE OF A GWAS DETECTED GENE (NINJ2) IN THE BRAIN OF A MOUSE MODEL OF ISCHEMIC STROKE

Stroke is the third leading cause of death and a major debilitating disease in the United States. Multiple factors, including genetic factors, contribute to the development of the disease. Genome-wide association studies (GWAS) have contributed to the identification of genetic loci influencing risk for complex diseases, such as stroke. In 2010, a GWAS of incident stroke was performed in four large prospective cohorts from the USA and Europe and identified an association of two Single Nucleotide Polymorphisms (SNPs) on chromosome 12p13 with a greater risk of ischemic stroke in individuals of European and African-American ancestry. These SNPs are located 11 Kb upstream of the nerve injury-induced gene 2, Ninjurin2 (NINJ2), suggesting that this gene may be involved in stroke pathogenesis. NINJ2 is a cell adhesion molecule induced in the distal glial cells from a sciatic-nerve injury at 7-days after injury. In an effort to ascribe a possible role of NINJ2 in stroke, we have assessed changes in the level of gene and protein expression of NINJ2 following a time-course from a transiently induced middle cerebral artery ischemic stroke in mice brains. We report an increase in the gene expression of NINJ2 in the ischemic and peri-infarct (ipsilateral) cortical tissues at 7 and 14-days after stroke. We also report an increase in the protein expression of NINJ2 in the cortex of both the ipsilateral and contralateral cortical tissues at the same time-points. We conclude that the expression of NINJ2 is regulated by an ischemic stroke in the cortex and is consistent with NINJ2 being involved in the recovery time-points of stroke.

Prognostic significance of xCT polymorphisms and expression in patients with advanced pancreatic cancer treated with chemotherapy

The plasma membrane xc- cystine/glutamate transporter mediates cellular uptake of cystine in exchange for intracellular glutamate and is highly expressed by pancreatic cancer cells. The xCT gene, encoding the cystine-specific xCT protein subunit of xc-, is important in regulating intracellular glutathione (GSH) levels, critical for cancer cell protection against oxidative stress, tumor growth and resistance to chemotherapeutic agents including platinum. We examined 4 single nucleotide polymorphisms (SNPs) of the xCT gene in 269 advanced pancreatic cancer patients who received first line gemcitabine with or without cisplatin or oxaliplatin. Genotyping was performed using Taqman real-time PCR assays. A statistically significant correlation was noted between the 3' untranslated region (UTR) xCT SNP rs7674870 and overall survival (OS): Median survival time (MST) was 10.9 and 13.6 months, respectively, for the TT and TC/CC genotypes (p = 0.027). Stratified analysis showed the genotype effect was significant in patients receiving gemcitabine in combination with platinum therapy (n = 145): MST was 10.5 versus 14.1 months for the TT and TC/CC genotypes, respectively (p = 0.013). The 3' UTR xCT SNP rs7674870 may correlate with OS in pancreatic cancer patients receiving gemcitabine and platinum combination therapy. Paraffin-embedded core and surgical biopsy tumor specimens from 98 patients with metastatic pancreatic adenocarcinoma were analyzed by immunohistochemistry using an xCT specific antibody. xCT protein IHC expression scores were analyzed in relation to overall survival in 86 patients and genotype in 12 patients and no statistically significant association was found between the level of xCT IHC expression score and overall survival (p = 0.514). When xCT expression was analyzed in terms of treatment response, no statistically significant associations could be determined (p = 0.908). These data suggest that polymorphic variants of xCT may have predictive value, and that the xc- transporter may represent an important target for therapy in pancreatic cancer.

A cladistic analysis of apolipoprotein B gene variation and plasma lipid and apolipoprotein B levels, using familial data

Any functionally important mutation is embedded in an evolutionary matrix of other mutations. Cladistic analysis, based on this, is a method of investigating gene effects using a haplotype phylogeny to define a set of tests which localize causal mutations to branches of the phylogeny. Previous implementations of cladistic analysis have not addressed the issue of analyzing data from related individuals, though in human studies, family data are usually needed to obtain unambiguous haplotypes. In this study, a method of cladistic analysis is described in which haplotype effects are parameterized in a linear model which accounts for familial correlations. The method was used to study the effect of apolipoprotein (Apo) B gene variation on total-, LDL-, and HDL-cholesterol, triglyceride, and Apo B levels in 121 French families. Five polymorphisms defined Apo B haplotypes: the signal peptide Insertion/deletion, Bsp 1286I, XbaI, MspI, and EcoRI. Eleven haplotypes were found, and a haplotype phylogeny was constructed and used to define a set of tests of haplotype effects on lipid and apo B levels.^ This new method of cladistic analysis, the parametric method, found significant effects for single haplotypes for all variables. For HDL-cholesterol, 3 clusters of evolutionarily-related haplotypes affecting levels were found. Haplotype effects accounted for about 10% of the genetic variance of triglyceride and HDL-cholesterol levels. The results of the parametric method were compared to those of a method of cladistic analysis based on permutational testing. The permutational method detected fewer haplotype effects, even when modified to account for correlations within families. Simulation studies exploring these differences found evidence of systematic errors in the permutational method due to the process by which haplotype groups were selected for testing.^ The applicability of cladistic analysis to human data was shown. The parametric method is suggested as an improvement over the permutational method. This study has identified candidate haplotypes for sequence comparisons in order to locate the functional mutations in the Apo B gene which may influence plasma lipid levels. ^

Cytochrome P450 4F isoforms in different species: Identification, gene regulation and putative roles in inflammation

The cytochrome P450 4F subfamily comprises a group of enzymes that metabolize derivatives of arachidonic acid such as prostaglandins, lipoxins leukotrienes and hydroxyeicosatetraenoic acids, which are important mediators involved in the inflammatory response. Therefore, we speculate that CYP4Fs might be able to modulate the extent of the inflammation by controlling of the tissue levels of these inflammatory mediators, especially, leukotriene B4. One way to provide support for this hypothesis is to test whether the expression of CYP4Fs changes under inflammatory conditions, since these changes are required to adjust the levels of inflammatory mediators. ^ A lipopolysacchride (LPS) induced rat inflammation model was used to analyze the expressions of rat CYP4F4 and CYP4F5 in liver and kidney. LPS administration did not change the constitutive expression level of CYP4F4 and CYP4F5. In liver, the expressions of CYP4F4 and CYP4F5 decreased to 50–60% of the untreated level. The same effect of LPS on CYP4F4 and CYP4F5 expression can be mimicked in hepatocyte primary cultures treated with LPS, indicating a direct of effect of LPS on hepatocytes. LPS treatment also decreased the activity of liver microsomes towards chlorpromazine, however, antibody inhibition study revealed that liver CYP4Fs are not the only players in metabolizing chlorpromazine. To study further the underlying mechanism, CYP4F5 gene was isolated, characterized, and the promoter region was defined. ^ Accumulating evidence showed that peroxisome proliferator-activated receptors (PPARs) play an active role in inflammation. To investigate the possible role of PPARα in regulating CYP4F expression by inflammation or by clofibrate treatment, the expressions of two new mouse 4F isoforms were analyzed in PPARα knockout mice upon LPS or clofibrate challenge. A novel induction of CYP4F15 by LPS and clofibrate was observed in kidney, and this effect is totally dependent on the presence of PPARα. Renal CYP4F16 expression was not affected by LPS or clofibrate in both (+/+) and (−/−) mice. In contrast, hepatic expressions of CYP4F15 and CYP4F16 were reduced significantly in (+/+) mice, but much less in (−/−) mice, suggesting that PPARα is partially responsible for this down-regulation. Clofibrate treatment reduced the expression of CYP4F16 in liver, but has no effect on CYP4F15 and PPARα does not have a role in hepatic CYP4F expression regulated by clofibrate. In general, CYP4Fs are regulated in an isoform-, tissue- and species-specific manner. ^ A human CYP4F isoform, CYP4F11, was isolated. The genomic structure was also solved by using database mining and bioinformatics tools. Localization of CYP4F11 to chromosome 19, 16 kb upstream of CYP4F2, suggests that human CYP4F genes may form a cluster on chromosome 19. This novel human 4F is highly expressed in liver, as well as in kidney, heart and skeletal muscle. Further study of the activity and gene regulation on CYP4F11 will provide us more insights into the physiological functions of CYP4F subfamily. ^

Candidate gene identification following linkage: Search for hypertension susceptibility genes

Following up genetic linkage studies to identify the underlying susceptibility gene(s) for complex disease traits is an arduous yet biologically and clinically important task. Complex traits, such as hypertension, are considered polygenic with many genes influencing risk, each with small effects. Chromosome 2 has been consistently identified as a genomic region with genetic linkage evidence suggesting that one or more loci contribute to blood pressure levels and hypertension status. Using combined positional candidate gene methods, the Family Blood Pressure Program has concentrated efforts in investigating this region of chromosome 2 in an effort to identify underlying candidate hypertension susceptibility gene(s). Initial informatics efforts identified the boundaries of the region and the known genes within it. A total of 82 polymorphic sites in eight positional candidate genes were genotyped in a large hypothesis-generating sample consisting of 1640 African Americans, 1339 whites, and 1616 Mexican Americans. To adjust for multiple comparisons, resampling-based false discovery adjustment was applied, extending traditional resampling methods to sibship samples. Following this adjustment for multiple comparisons, SLC4A5, a sodium bicarbonate transporter, was identified as a primary candidate gene for hypertension. Polymorphisms in SLC4A5 were subsequently genotyped and analyzed for validation in two populations of African Americans (N = 461; N = 778) and two of whites (N = 550; N = 967). Again, SNPs within SLC4A5 were significantly associated with blood pressure levels and hypertension status. While not identifying a single causal DNA sequence variation that is significantly associated with blood pressure levels and hypertension status across all samples, the results further implicate SLC4A5 as a candidate hypertension susceptibility gene, validating previous evidence for one or more genes on chromosome 2 that influence hypertension related phenotypes in the population-at-large. The methodology and results reported provide a case study of one approach for following up the results of genetic linkage analyses to identify genes influencing complex traits. ^

Genome-wide gene-gene interaction analysis for cardiovascular disease

Numerous studies have been carried out to try to better understand the genetic predisposition for cardiovascular disease. Although it is widely believed that multifactorial diseases such as cardiovascular disease is the result from effects of many genes which working alone or interact with other genes, most genetic studies have been focused on identifying of cardiovascular disease susceptibility genes and usually ignore the effects of gene-gene interactions in the analysis. The current study applies a novel linkage disequilibrium based statistic for testing interactions between two linked loci using data from a genome-wide study of cardiovascular disease. A total of 53,394 single nucleotide polymorphisms (SNPs) are tested for pair-wise interactions, and 8,644 interactions are found to be significant with p-values less than 3.5×10-11. Results indicate that known cardiovascular disease susceptibility genes tend not to have many significantly interactions. One SNP in the CACNG1 (calcium channel, voltage-dependent, gamma subunit 1) gene and one SNP in the IL3RA (interleukin 3 receptor, alpha) gene are found to have the most significant pair-wise interactions. Findings from the current study should be replicated in other independent cohort to eliminate potential false positive results.^

Estrogen-induced gene expression and patient survival in high-grade serous carcinoma of the ovary

Background. Assessment of estrogen receptor (ER) expression has inconsistent utility as a prognostic marker in epithelial ovarian carcinoma. In breast and endometrial cancers, the use of estrogen-induced gene panels, rather than ER expression alone, has shown improved prognostic capability. Specifically, over-expression of estrogen-induced genes in these tumors is associated with a better prognosis and signifies estrogen sensitivity that can be exploited with hormone antagonizing agents. It was therefore hypothesized that estrogen-induced gene expression in ovarian carcinoma would successfully predict outcomes and differentiate between tumors of varying estrogen sensitivities. Methods. Two hundred nineteen (219) patients with ovarian cancer who underwent surgery at M. D. Anderson between 2004 and 2007 were identified. Of these, eighty-three (83) patients were selected for inclusion because they had advanced stage, high-grade serous carcinoma of the ovary or peritoneum, had not received neoadjuvant chemotherapy, and had readily available frozen tissue for study. All patients had also received adjuvant treatment with platinum and taxane agents. The expression of seven genes known to be induced by estrogen in the female reproductive tract (EIG121, sFRP1, sFRP4, RALDH2, PR, IGF-1, and ER) was measured using qRT-PCR. Unsupervised cluster analyses of multiple gene permutations were used to categorize patients as high or low estrogen-induced gene expressors. QPCR gene expression results were then compared to ER and PR immunohistochemical (IHC) expression. Cox proportional hazards models were used to evaluate the effects of both individual genes and selected gene clusters on patient survival. Results. Median follow-up time was 38.7 months (range 1-68 months). In a multivariate model, overall survival was predicted by sFRP1 expression (HR 1.10 [1.02-1.19], p=0.01) and EIG121 expression (HR 1.28 [1.10-1.49], p<0.01). A cluster defined by EIG121 and ER was further examined because that combination appeared to reasonably segregate tumors into distinct groups of high and low estrogen-induced gene expressors. Shorter overall survival was associated with high estrogen-induced gene expressors (HR 2.84 [1.11-7.30], p=0.03), even after adjustment for race, age, body mass index, and residual disease at debulking. No difference in IHC ER or PR expression was noted between gene clusters. Conclusion. In sharp contrast to breast and endometrial cancers, high estrogen-induced gene expression predicts shorter overall survival in patients with high-grade serous ovarian carcinoma. An estrogen-induced gene biomarker panel may have utility as prognostic indicator and may be useful to guide management with estrogen antagonists in this population.^

Single nucleotide polymorphisms (SNPs) associated with TGF-beta pathway and their significance in systemic sclerosis - A multilevel analysis

Systemic sclerosis (SSc) or Scleroderma is a complex disease and its etiopathogenesis remains unelucidated. Fibrosis in multiple organs is a key feature of SSc and studies have shown that transforming growth factor-β (TGF-β) pathway has a crucial role in fibrotic responses. For a complex disease such as SSc, expression quantitative trait loci (eQTL) analysis is a powerful tool for identifying genetic variations that affect expression of genes involved in this disease. In this study, a multilevel model is described to perform a multivariate eQTL for identifying genetic variation (SNPs) specifically associated with the expression of three members of TGF-β pathway, CTGF, SPARC and COL3A1. The uniqueness of this model is that all three genes were included in one model, rather than one gene being examined at a time. A protein might contribute to multiple pathways and this approach allows the identification of important genetic variations linked to multiple genes belonging to the same pathway. In this study, 29 SNPs were identified and 16 of them located in known genes. Exploring the roles of these genes in TGF-β regulation will help elucidate the etiology of SSc, which will in turn help to better manage this complex disease. ^