197 research outputs found

    IBD genetic risk profile in healthy first-degree relatives of Crohn's disease patients

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    BACKGROUND: Family history provides important information on risk of developing inflammatory bowel disease [IBD], and genetic profiling of first-degree relatives [FDR] of Crohn's disease [CD]- affected individuals might provide additional information. We aimed to delineate the genetic contribution to the increased IBD susceptibility observed in FDR. METHODS: N = 976 Caucasian, healthy, non-related FDR; n = 4997 independent CD; and n = 5000 healthy controls [HC]; were studied. Genotyping for 158 IBD-associated single nucleotide polymorphisms [SNPs] was performed using the Illumina Immunochip. Risk allele frequency [RAF] differences between FDR and HC cohorts were correlated with those between CD and HC cohorts. CD and IBD genetic risk scores [GRS] were calculated and compared between HC, FDR, and CD cohorts. RESULTS: IBD-associated SNP RAF differences in FDR and HC cohorts were strongly correlated with those in CD and HC cohorts, correlation coefficient 0.63 (95% confidence interval [CI] 0.53 - 0.72), p = 9.90 x 10(-19). There was a significant increase in CD-GRS [mean] comparing HC, FDR, and CD cohorts: 0.0244, 0.0250, and 0.0257 respectively [p < 1.00 x 10(-7) for each comparison]. There was no significant difference in the IBD-GRS between HC and FDR cohorts [p = 0.81]; however, IBD-GRS was significantly higher in CD compared with FDR and HC cohorts [p < 1.00 x 10(-10) for each comparison]. CONCLUSION: FDR of CD-affected individuals are enriched with IBD risk alleles compared with HC. Cumulative CD-specific genetic risk is increased in FDR compared with HC. Prospective studies are required to determine if genotyping would facilitate better risk stratification of FDR

    Identifying hypothetical genetic influences on complex disease phenotypes

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    <p>Abstract</p> <p>Background</p> <p>Statistical interactions between disease-associated loci of complex genetic diseases suggest that genes from these regions are involved in a common mechanism impacting, or impacted by, the disease. The computational problem we address is to discover relationships among genes from these interacting regions that may explain the observed statistical interaction and the role of these genes in the disease phenotype.</p> <p>Results</p> <p>We describe a heuristic algorithm for generating hypothetical gene relationships from loci associated with a complex disease phenotype. This approach, called Prioritizing Disease Genes by Analysis of Common Elements (PDG-ACE), mines biomedical keywords from text descriptions of genes and uses them to relate genes close to disease-associated loci. A keyword common to, and significantly over-represented in, a pair of gene descriptions may represent a preliminary hypothesis about the biological relationship between the genes, and suggest the role the genes play in the disease phenotype.</p> <p>Conclusion</p> <p>Our experimentation shows that the approach finds previously published relationships, while failing to find relationships that don't exist. The results also indicate that the approach is robust to differences in keyword vocabulary. We outline a brief case study in which results from a recently published Type 2 Diabetes association study are used to identify potential hypotheses.</p

    Acute Regulation of Cardiac Metabolism by the Hexosamine Biosynthesis Pathway and Protein O-GlcNAcylation

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    OBJECTIVE: The hexosamine biosynthesis pathway (HBP) flux and protein O-linked N-acetyl-glucosamine (O-GlcNAc) levels have been implicated in mediating the adverse effects of diabetes in the cardiovascular system. Activation of these pathways with glucosamine has been shown to mimic some of the diabetes-induced functional and structural changes in the heart; however, the effect on cardiac metabolism is not known. Therefore, the primary goal of this study was to determine the effects of glucosamine on cardiac substrate utilization. METHODS: Isolated rat hearts were perfused with glucosamine (0-10 mM) to increase HBP flux under normoxic conditions. Metabolic fluxes were determined by (13)C-NMR isotopomer analysis; UDP-GlcNAc a precursor of O-GlcNAc synthesis was assessed by HPLC and immunoblot analysis was used to determine O-GlcNAc levels, phospho- and total levels of AMPK and ACC, and membrane levels of FAT/CD36. RESULTS: Glucosamine caused a dose dependent increase in both UDP-GlcNAc and O-GlcNAc levels, which was associated with a significant increase in palmitate oxidation with a concomitant decrease in lactate and pyruvate oxidation. There was no effect of glucosamine on AMPK or ACC phosphorylation; however, membrane levels of the fatty acid transport protein FAT/CD36 were increased and preliminary studies suggest that FAT/CD36 is a potential target for O-GlcNAcylation. CONCLUSION/INTERPRETATION: These data demonstrate that acute modulation of HBP and protein O-GlcNAcylation in the heart stimulates fatty acid oxidation, possibly by increasing plasma membrane levels of FAT/CD36, raising the intriguing possibility that the HBP and O-GlcNAc turnover represent a novel, glucose dependent mechanism for regulating cardiac metabolism

    Screening and association testing of common coding variation in steroid hormone receptor co-activator and co-repressor genes in relation to breast cancer risk: the Multiethnic Cohort

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    <p>Abstract</p> <p>Background</p> <p>Only a limited number of studies have performed comprehensive investigations of coding variation in relation to breast cancer risk. Given the established role of estrogens in breast cancer, we hypothesized that coding variation in steroid receptor coactivator and corepressor genes may alter inter-individual response to estrogen and serve as markers of breast cancer risk.</p> <p>Methods</p> <p>We sequenced the coding exons of 17 genes (<it>EP300, CCND1, NME1, NCOA1, NCOA2, NCOA3, SMARCA4, SMARCA2, CARM1, FOXA1, MPG, NCOR1, NCOR2, CALCOCO1, PRMT1, PPARBP </it>and <it>CREBBP</it>) suggested to influence transcriptional activation by steroid hormone receptors in a multiethnic panel of women with advanced breast cancer (n = 95): African Americans, Latinos, Japanese, Native Hawaiians and European Americans. Association testing of validated coding variants was conducted in a breast cancer case-control study (1,612 invasive cases and 1,961 controls) nested in the Multiethnic Cohort. We used logistic regression to estimate odds ratios for allelic effects in ethnic-pooled analyses as well as in subgroups defined by disease stage and steroid hormone receptor status. We also investigated effect modification by established breast cancer risk factors that are associated with steroid hormone exposure.</p> <p>Results</p> <p>We identified 45 coding variants with frequencies ≥ 1% in any one ethnic group (43 non-synonymous variants). We observed nominally significant positive associations with two coding variants in ethnic-pooled analyses (<it>NCOR2</it>: His52Arg, OR = 1.79; 95% CI, 1.05–3.05; <it>CALCOCO1</it>: Arg12His, OR = 2.29; 95% CI, 1.00–5.26). A small number of variants were associated with risk in disease subgroup analyses and we observed no strong evidence of effect modification by breast cancer risk factors. Based on the large number of statistical tests conducted in this study, the nominally significant associations that we observed may be due to chance, and will need to be confirmed in other studies.</p> <p>Conclusion</p> <p>Our findings suggest that common coding variation in these candidate genes do not make a substantial contribution to breast cancer risk in the general population. Cataloging and testing of coding variants in coactivator and corepressor genes should continue and may serve as a valuable resource for investigations of other hormone-related phenotypes, such as inter-individual response to hormonal therapies used for cancer treatment and prevention.</p

    SNP-SNP interactions in breast cancer susceptibility

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    BACKGROUND: Breast cancer predisposition genes identified to date (e.g., BRCA1 and BRCA2) are responsible for less than 5% of all breast cancer cases. Many studies have shown that the cancer risks associated with individual commonly occurring single nucleotide polymorphisms (SNPs) are incremental. However, polygenic models suggest that multiple commonly occurring low to modestly penetrant SNPs of cancer related genes might have a greater effect on a disease when considered in combination. METHODS: In an attempt to identify the breast cancer risk conferred by SNP interactions, we have studied 19 SNPs from genes involved in major cancer related pathways. All SNPs were genotyped by TaqMan 5'nuclease assay. The association between the case-control status and each individual SNP, measured by the odds ratio and its corresponding 95% confidence interval, was estimated using unconditional logistic regression models. At the second stage, two-way interactions were investigated using multivariate logistic models. The robustness of the interactions, which were observed among SNPs with stronger functional evidence, was assessed using a bootstrap approach, and correction for multiple testing based on the false discovery rate (FDR) principle. RESULTS: None of these SNPs contributed to breast cancer risk individually. However, we have demonstrated evidence for gene-gene (SNP-SNP) interaction among these SNPs, which were associated with increased breast cancer risk. Our study suggests cross talk between the SNPs of the DNA repair and immune system (XPD-[Lys751Gln] and IL10-[G(-1082)A]), cell cycle and estrogen metabolism (CCND1-[Pro241Pro] and COMT-[Met108/158Val]), cell cycle and DNA repair (BARD1-[Pro24Ser] and XPD-[Lys751Gln]), and within carcinogen metabolism (GSTP1-[Ile105Val] and COMT-[Met108/158Val]) pathways. CONCLUSION: The importance of these pathways and their communication in breast cancer predisposition has been emphasized previously, but their biological interactions through SNPs have not been described. The strategy used here has the potential to identify complex biological links among breast cancer genes and processes. This will provide novel biological information, which will ultimately improve breast cancer risk management

    The association of polymorphisms in hormone metabolism pathway genes, menopausal hormone therapy, and breast cancer risk: a nested case-control study in the California Teachers Study cohort

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    Abstract Introduction The female sex steroids estrogen and progesterone are important in breast cancer etiology. It therefore seems plausible that variation in genes involved in metabolism of these hormones may affect breast cancer risk, and that these associations may vary depending on menopausal status and use of hormone therapy. Methods We conducted a nested case-control study of breast cancer in the California Teachers Study cohort. We analyzed 317 tagging single nucleotide polymorphisms (SNPs) in 24 hormone pathway genes in 2746 non-Hispanic white women: 1351 cases and 1395 controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated by fitting conditional logistic regression models using all women or subgroups of women defined by menopausal status and hormone therapy use. P values were adjusted for multiple correlated tests (P ACT). Results The strongest associations were observed for SNPs in SLCO1B1, a solute carrier organic anion transporter gene, which transports estradiol-17β-glucuronide and estrone-3-sulfate from the blood into hepatocytes. Ten of 38 tagging SNPs of SLCO1B1 showed significant associations with postmenopausal breast cancer risk; 5 SNPs (rs11045777, rs11045773, rs16923519, rs4149057, rs11045884) remained statistically significant after adjusting for multiple testing within this gene (P ACT = 0.019-0.046). In postmenopausal women who were using combined estrogen-progestin therapy (EPT) at cohort enrollment, the OR of breast cancer was 2.31 (95% CI = 1.47-3.62) per minor allele of rs4149013 in SLCO1B1 (P = 0.0003; within-gene P ACT = 0.002; overall P ACT = 0.023). SNPs in other hormone pathway genes evaluated in this study were not associated with breast cancer risk in premenopausal or postmenopausal women. Conclusions We found evidence that genetic variation in SLCO1B1 is associated with breast cancer risk in postmenopausal women, particularly among those using EPT

    Iscador Qu inhibits doxorubicin-induced senescence of MCF7 cells

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    Chemotherapy in patients with inoperable or advanced breast cancer inevitably results in low-dose exposure of tumor-cell subset and senescence. Metabolically active senescent cells secrete multiple tumor promoting factors making their elimination a therapeutic priority. Viscum album is one of the most widely used alternative anti-cancer medicines facilitating chemotherapy tolerance of breast cancer patients. The aim of this study was to model and investigate how Viscum album extracts execute additive anti-tumor activity with low-dose Dox using ER + MCF7 breast cancer cells. We report that cotreatment of MCF7 with Viscum album and Dox abrogates G2/M cycle arrest replacing senescence with intrinsic apoptotic program. Mechanistically, this switch was associated with down-regulation of p21, p53/p73 as well as Erk1/2 and p38 activation. Our findings, therefore, identify a novel mechanistic axis of additive antitumor activity of Viscum album and low dose-Dox. In conclusion, ER + breast cancer patients may benefit from addition of Viscum album to low-dose Dox chemotherapy due to suppression of cancer cell senescence and induction of apoptosis
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