276 research outputs found

    Dispelling urban myths about default uncertainty factors in chemical risk assessment - Sufficient protection against mixture effects?

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    Β© 2013 Martin et al.; licensee BioMed Central LtdThis article has been made available through the Brunel Open Access Publishing Fund.Assessing the detrimental health effects of chemicals requires the extrapolation of experimental data in animals to human populations. This is achieved by applying a default uncertainty factor of 100 to doses not found to be associated with observable effects in laboratory animals. It is commonly assumed that the toxicokinetic and toxicodynamic sub-components of this default uncertainty factor represent worst-case scenarios and that the multiplication of those components yields conservative estimates of safe levels for humans. It is sometimes claimed that this conservatism also offers adequate protection from mixture effects. By analysing the evolution of uncertainty factors from a historical perspective, we expose that the default factor and its sub-components are intended to represent adequate rather than worst-case scenarios. The intention of using assessment factors for mixture effects was abandoned thirty years ago. It is also often ignored that the conservatism (or otherwise) of uncertainty factors can only be considered in relation to a defined level of protection. A protection equivalent to an effect magnitude of 0.001-0.0001% over background incidence is generally considered acceptable. However, it is impossible to say whether this level of protection is in fact realised with the tolerable doses that are derived by employing uncertainty factors. Accordingly, it is difficult to assess whether uncertainty factors overestimate or underestimate the sensitivity differences in human populations. It is also often not appreciated that the outcome of probabilistic approaches to the multiplication of sub-factors is dependent on the choice of probability distributions. Therefore, the idea that default uncertainty factors are overly conservative worst-case scenarios which can account both for the lack of statistical power in animal experiments and protect against potential mixture effects is ill-founded. We contend that precautionary regulation should provide an incentive to generate better data and recommend adopting a pragmatic, but scientifically better founded approach to mixture risk assessment. Β© 2013 Martin et al.; licensee BioMed Central Ltd.Oak Foundatio

    A splicing variant of TERT identified by GWAS interacts with menopausal estrogen therapy in risk of ovarian cancer

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    Menopausal estrogen-alone therapy (ET) is a well-established risk factor for serous and endometrioid ovarian cancer. Genetics also plays a role in ovarian cancer, which is partly attributable to 18 confirmed ovarian cancer susceptibility loci identified by genome-wide association studies. The interplay among these loci, ET use and ovarian cancer risk has yet to be evaluated. We analyzed data from 1,414 serous cases, 337 endometrioid cases and 4,051 controls across 10 case-control studies participating in the Ovarian Cancer Association Consortium (OCAC). Conditional logistic regression was used to determine the association between the confirmed susceptibility variants and risk of serous and endometrioid ovarian cancer among ET users and non-users separately and to test for statistical interaction. A splicing variant in TERT, rs10069690, showed a statistically significant interaction with ET use for risk of serous ovarian cancer (pint  = 0.013). ET users carrying the T allele had a 51% increased risk of disease (OR = 1.51, 95% CI 1.19-1.91), which was stronger for long-term ET users of 10+ years (OR = 1.85, 95% CI 1.28-2.66, pint  = 0.034). Non-users showed essentially no association (OR = 1.08, 95% CI 0.96-1.21). Two additional genomic regions harboring rs7207826 (C allele) and rs56318008 (T allele) also had significant interactions with ET use for the endometrioid histotype (pint  = 0.021 and pint  = 0.037, respectively). Hence, three confirmed susceptibility variants were identified whose associations with ovarian cancer risk are modified by ET exposure; follow-up is warranted given that these interactions are not adjusted for multiple comparisons. These findings, if validated, may elucidate the mechanism of action of these loci

    Association Between Menopausal Estrogen-Only Therapy and Ovarian Carcinoma Risk

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    OBJECTIVE: To describe the association between postmenopausal estrogen-only therapy use and risk of ovarian carcinoma, specifically with regard to disease histotype and duration and timing of use. METHODS: We conducted a pooled analysis of 906 women with ovarian carcinoma and 1,220 women in a control group; all 2,126 women included reported having had a hysterectomy. Ten population-based case-control studies participating in the Ovarian Cancer Association Consortium, an international consortium whose goal is to combine data from many studies with similar methods so reliable assessments of risk factors can be determined, were included. Self-reported questionnaire data from each study were harmonized and conditional logistic regression was used to examine estrogen-only therapy's histotype-specific and duration and recency of use associations. RESULTS: Forty-three and a half percent of the women in the control group reported previous use of estrogen-only therapy. Compared with them, current or recent estrogen-only therapy use was associated with an increased risk for the serous (51.4%, odds ratio [OR] 1.63, 95% confidence interval [CI] 1.27-2.09) and endometrioid (48.6%, OR 2.00, 95% CI 1.17-3.41) histotypes. In addition, statistically significant trends in risk according to duration of use were seen among current or recent postmenopausal estrogen-only therapy users for both ovarian carcinoma histotypes (Ptrend<.001 for serous and endometrioid). Compared with women in the control group, current or recent users for 10 years or more had increased risks of serous ovarian carcinoma (36.8%, OR 1.73, 95% CI 1.26-2.38) and endometrioid ovarian carcinoma (34.9%, OR 4.03, 95% CI 1.91-8.49). CONCLUSION: We found evidence of an increased risk of serous and endometrioid ovarian carcinoma associated with postmenopausal estrogen-only therapy use, particularly of long duration. These findings emphasize that risk may be associated with extended estrogen-only therapy use

    High pre-diagnosis inflammation-related risk score associated with decreased ovarian cancer survival

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    BACKGROUND: There is suggestive evidence that inflammation is related to ovarian cancer survival. However, more research is needed to identify inflammation-related factors that are associated with ovarian cancer survival and to determine their combined effects. METHODS: This analysis used pooled data on 8,147 women with invasive epithelial ovarian cancer from the Ovarian Cancer Association Consortium. Pre-diagnosis inflammatory-related exposures of interest included alcohol use, aspirin use, other nonsteroidal anti-inflammatory drug use, body mass index, environmental tobacco smoke exposure, history of pelvic inflammatory disease, polycystic ovarian syndrome, and endometriosis, menopausal hormone therapy use, physical inactivity, smoking status, and talc use. Using Cox proportional hazards (PH) models, the relationship between each exposure and survival was assessed in 50% of the data. A weighted inflammation-related risk score (IRRS) was developed and its association with survival was assessed using Cox PH models in the remaining 50% of the data. RESULTS: There was a statistically significant trend of increasing risk of death per quartile of the IRRS (HR=1.09, 95% CI 1.03-1.14). Women in the upper quartile of the IRRS had 31% higher death rate compared to the lowest quartile (95% CI 1.11-1.54). CONCLUSIONS: A higher pre-diagnosis IRRS was associated with increased mortality risk after an ovarian cancer diagnosis. Further investigation is warranted to evaluate whether post-diagnosis exposures are also associated with survival. IMPACT: Given that pre- and post-diagnosis exposures are often correlated and many are modifiable, our study results can ultimately motivate the development of behavioral recommendations to enhance survival among ovarian cancer patients

    Expanding Our Understanding of Ovarian Cancer Risk: The Role of Incomplete Pregnancies

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    Background: Parity is associated with decreased risk of invasive ovarian cancer; however, the relationship between incomplete pregnancies and invasive ovarian cancer risk is unclear. This relationship was examined using 15 case-control studies from the Ovarian Cancer Association Consortium (OCAC). Histotype-specific associations, which have not been examined previously with large sample sizes, were also evaluated. / Methods: A pooled analysis of 10 470 invasive epithelial ovarian cancer cases and 16 942 controls was conducted. Odds ratios (ORs) and 95% confidence intervals (CIs) for the association between incomplete pregnancies and invasive epithelial ovarian cancer were estimated using logistic regression. All models were conditioned on OCAC study, race and ethnicity, age, and education level and adjusted for number of complete pregnancies, oral contraceptive use, and history of breastfeeding. The same approach was used for histotype-specific analyses. / Results: Ever having an incomplete pregnancy was associated with a 16% reduction in ovarian cancer risk (OR = 0.84, 95% CI = 0.79 to 0.89). There was a trend of decreasing risk with increasing number of incomplete pregnancies (2-sided Ptrend < .001). An inverse association was observed for all major histotypes; it was strongest for clear cell ovarian cancer. / Conclusions: Incomplete pregnancies are associated with a reduced risk of invasive epithelial ovarian cancer. Pregnancy, including incomplete pregnancy, was associated with a greater reduction in risk of clear cell ovarian cancer, but the result was broadly consistent across histotypes. Future work should focus on understanding the mechanisms underlying this reduced risk

    Profiling the immune landscape in mucinous ovarian carcinoma

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    Objective: Mucinous ovarian carcinoma (MOC) is a rare histotype of ovarian cancer, with low response rates to standard chemotherapy, and very poor survival for patients diagnosed at advanced stage. There is a limited understanding of the MOC immune landscape, and consequently whether immune checkpoint inhibitors could be considered for a subset of patients. Methods: We performed multicolor immunohistochemistry (IHC) and immunofluorescence (IF) on tissue microarrays in a cohort of 126 MOC patients. Cell densities were calculated in the epithelial and stromal components for tumor-associated macrophages (CD68+/PD-L1+, CD68+/PD-L1-), T cells (CD3+/CD8-, CD3+/CD8+), putative T-regulatory cells (Tregs, FOXP3+), B cells (CD20+/CD79A+), plasma cells (CD20-/CD79a+), and PD-L1+ and PD-1+ cells, and compared these values with clinical factors. Univariate and multivariable Cox Proportional Hazards assessed overall survival. Unsupervised k-means clustering identified patient subsets with common patterns of immune cell infiltration. Results: Mean densities of PD1+ cells, PD-L1- macrophages, CD4+ and CD8+ T cells, and FOXP3+ Tregs were higher in the stroma compared to the epithelium. Tumors from advanced (Stage III/IV) MOC had greater epithelial infiltration of PD-L1- macrophages, and fewer PD-L1+ macrophages compared with Stage I/II cancers (p = 0.004 and p = 0.014 respectively). Patients with high epithelial density of FOXP3+ cells, CD8+/FOXP3+ cells, or PD-L1- macrophages, had poorer survival, and high epithelial CD79a + plasma cells conferred better survival, all upon univariate analysis only. Clustering showed that most MOC (86%) had an immune depleted (cold) phenotype, with only a small proportion (11/76,14%) considered immune inflamed (hot) based on T cell and PD-L1 infiltrates. Conclusion: In summary, MOCs are mostly immunogenically β€˜cold’, suggesting they may have limited response to current immunotherapies

    Offspring Hormones Reflect the Maternal Prenatal Social Environment: Potential for Foetal Programming?

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    Females of many species adaptively program their offspring to predictable environmental conditions, a process that is often mediated by hormones. Laboratory studies have shown, for instance, that social density affects levels of maternal cortisol and testosterone, leading to fitness-relevant changes in offspring physiology and behaviour. However, the effects of social density remain poorly understood in natural populations due to the difficulty of disentangling confounding influences such as climatic variation and food availability. Colonially breeding marine mammals offer a unique opportunity to study maternal effects in response to variable colony densities under similar ecological conditions. We therefore quantified maternal and offspring hormone levels in 84 Antarctic fur seals (Arctocephalus gazella) from two closely neighbouring colonies of contrasting density. Hair samples were used as they integrate hormone levels over several weeks or months and therefore represent in utero conditions during foetal development. We found significantly higher levels of cortisol and testosterone (both P < 0.001) in mothers from the high density colony, reflecting a more stressful and competitive environment. In addition, offspring testosterone showed a significant positive correlation with maternal cortisol (P < 0.05). Although further work is needed to elucidate the potential consequences for offspring fitness, these findings raise the intriguing possibility that adaptive foetal programming might occur in fur seals in response to the maternal social environment. They also lend support to the idea that hormonally mediated maternal effects may depend more strongly on the maternal regulation of androgen rather than cortisol levels

    Population Structure as Revealed by mtDNA and Microsatellites in Northern Fur Seals, Callorhinus ursinus, throughout Their Range

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    Background: The northern fur seal (Callorhinus ursinus; NFS) is a widely distributed pinniped that has been shown to exhibit a high degree of philopatry to islands, breeding areas on an island, and even to specific segments of breeding areas. This level of philopatry could conceivably lead to highly genetically divergent populations. However, northern fur seals have the potential for dispersal across large distances and have experienced repeated rapid population expansions following glacial retreat and the more recent cessation of intensive harvest pressure. Methodology/Principal Findings: Using microsatellite and mitochondrial loci, we examined population structure in NFS throughout their range. We found only weak population genetic structure among breeding islands including significant FST and W ST values between eastern and western Pacific islands. Conclusions: We conclude that insufficient time since rapid population expansion events (both post glacial and following the cessation of intense harvest pressure) mixed with low levels of contemporary migration have resulted in an absence of genetic structure across the entire northern fur seal range

    Exome genotyping arrays to identify rare and low frequency variants associated with epithelial ovarian cancer risk

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    Rare and low frequency variants are not well covered in most germline genotyping arrays and are understudied in relation to epithelial ovarian cancer (EOC) risk. To address this gap, we used genotyping arrays targeting rarer protein-coding variation in 8,165 EOC cases and 11,619 controls from the international Ovarian Cancer Association Consortium (OCAC). Pooled association analyses were conducted at the variant and gene level for 98,543 variants directly genotyped through two exome genotyping projects. Only common variants that represent or are in strong linkage disequilibrium (LD) with previously-identified signals at established loci reached traditional thresholds for exome-wide significance (P ( )Pβ‰₯5.0 Γ—10 (-)  (7)) were detected for rare and low-frequency variants at 16 novel loci. Four rare missense variants were identified (ACTBL2 rs73757391 (5q11.2), BTD rs200337373 (3p25.1), KRT13 rs150321809 (17q21.2) and MC2R rs104894658 (18p11.21)), but only MC2R rs104894668 had a large effect size (OR = 9.66). Genes most strongly associated with EOC risk included ACTBL2 (PAML = 3.23 Γ— 10 (-)  (5); PSKAT-o = 9.23 × 10 (-)  (4)) and KRT13 (PAML = 1.67 Γ— 10 (-)  (4); PSKAT-o = 1.07 × 10 (-)  (5)), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology, sequencing, and functional assays are needed to further unravel the unexplained heritability and biology of this disease
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