Beatrice Lewis
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PROVIDER: S-EPMC1126346 | biostudies-literature | 2003 Jun
REPOSITORIES: biostudies-literature
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| S-EPMC1440673 | biostudies-literature
Project description:We introduce a novel framework BEATRICE to identify putative causal variants from GWAS summary statistics (https://github.com/sayangsep/Beatrice-Finemapping). Identifying causal variants is challenging due to their sparsity and to highly correlated variants in the nearby regions. To account for these challenges, our approach relies on a hierarchical Bayesian model that imposes a binary concrete prior on the set of causal variants. We derive a variational algorithm for this fine-mapping problem by minimizing the KL divergence between an approximate density and the posterior probability distribution of the causal configurations. Correspondingly, we use a deep neural network as an inference machine to estimate the parameters of our proposal distribution. Our stochastic optimization procedure allows us to simultaneously sample from the space of causal configurations. We use these samples to compute the posterior inclusion probabilities and determine credible sets for each causal variant. We conduct a detailed simulation study to quantify the performance of our framework across different numbers of causal variants and different noise paradigms, as defined by the relative genetic contributions of causal and non-causal variants. Using this simulated data, we perform a comparative analysis against two state-of-the-art baseline methods for fine-mapping. We demonstrate that BEATRICE achieves uniformly better coverage with comparable power and set sizes, and that the performance gain increases with the number of causal variants. Thus, BEATRICE is a valuable tool to identify causal variants from eQTL and GWAS summary statistics across complex diseases and traits.
| S-EPMC10055416 | biostudies-literature
Project description:MotivationWe introduce a novel framework BEATRICE to identify putative causal variants from GWAS statistics. Identifying causal variants is challenging due to their sparsity and high correlation in the nearby regions. To account for these challenges, we rely on a hierarchical Bayesian model that imposes a binary concrete prior on the set of causal variants. We derive a variational algorithm for this fine-mapping problem by minimizing the KL divergence between an approximate density and the posterior probability distribution of the causal configurations. Correspondingly, we use a deep neural network as an inference machine to estimate the parameters of our proposal distribution. Our stochastic optimization procedure allows us to sample from the space of causal configurations, which we use to compute the posterior inclusion probabilities and determine credible sets for each causal variant. We conduct a detailed simulation study to quantify the performance of our framework against two state-of-the-art baseline methods across different numbers of causal variants and noise paradigms, as defined by the relative genetic contributions of causal and noncausal variants.ResultsWe demonstrate that BEATRICE achieves uniformly better coverage with comparable power and set sizes, and that the performance gain increases with the number of causal variants. We also show the efficacy BEATRICE in finding causal variants from the GWAS study of Alzheimer's disease. In comparison to the baselines, only BEATRICE can successfully find the APOE ϵ2 allele, a commonly associated variant of Alzheimer's.Availability and implementationBEATRICE is available for download at https://github.com/sayangsep/Beatrice-Finemapping.
| S-EPMC11496888 | biostudies-literature
Project description:BackgroundBevacizumab is a beneficial therapy in several advanced cancer types. Predictive biomarkers to better understand which patients are destined to benefit or experience toxicity are needed. Associations between bevacizumab induced hypertension and survival have been reported but with conflicting conclusions.MethodsWe performed post-hoc analyses to evaluate the association in 3124 patients from two phase III adjuvant breast cancer trials, E5103 and BEATRICE. Differences in invasive disease-free survival (IDFS) and overall survival (OS) between patients with hypertension and those without were compared. Hypertension was defined as systolic blood pressure (SBP) ≥ 160 mmHg (n = 346) and SBP ≥ 180 mmHg (hypertensive crisis) (n = 69). Genomic analyses were performed to evaluate germline genetic predictors for the hypertensive crisis.ResultsHypertensive crisis was significantly associated with superior IDFS (p = 0.015) and OS (p = 0.042), but only IDFS (p = 0.029; HR = 0.28) remained significant after correction for prognostic factors. SBP ≥ 160 mmHg was not associated with either IDFS or OS. A common single-nucleotide polymorphism, rs6486785, was significantly associated with hypertensive crisis (p = 8.4 × 10-9; OR = 5.2).ConclusionBevacizumab-induced hypertensive crisis is associated with superior outcomes and rs6486785 predicted an increased risk of this key toxicity.
| S-EPMC11014938 | biostudies-literature
Project description:The rhabdoviral genus Tibrovirus currently has three official members assigned to two species: Bivens Arm virus and Tibrogargan virus (species Tibrogargan tibrovirus) and Coastal Plains virus (species Coastal Plains tibrovirus). Here, we report the complete genome sequence of a new putative member of this genus, Beatrice Hill virus. Although relatively closely related to the three classified viruses, Beatrice Hill virus represents a novel Tibrovirus species.
| S-EPMC5270694 | biostudies-literature
Project description:BackgroundLewis antigens such as Sialyl Lewis A (sLeA), Sialyl Lewis X (sLeX), Lewis X (LeX), and Lewis Y (LeY) are a class of carbohydrate molecules that are known to mediate adhesion between tumor cells and endothelium by interacting with its selectin ligands. However, their potential role in miscarriage remains enigmatic. This study aims to analyze the expression pattern of sLeA, sLeX, LeX, and LeY in the placental villi tissue of patients with a medical history of unexplained miscarriages.MethodsParaffin-embedded slides originating from placental tissue were collected from patients experiencing a miscarriage early in their pregnancy (6-13 weeks). Tissues collected from spontaneous (n = 20) and recurrent (n = 15) miscarriages were analyzed using immunohistochemical and immunofluorescent staining. Specimens obtained from legally terminated normal pregnancies were considered as control group (n = 18). Assessment of villous vessel density was performed in another cohort (n = 10 each group) of gestation ages-paired placenta tissue. Protein expression was evaluated with Immunoreactive Score (IRS). Statistical analysis was performed by using Graphpad Prism 8.ResultsExpression of sLeA, sLeX, LeX, and LeY in the syncytiotrophoblast was significantly upregulated in the control group compared with spontaneous and recurrent miscarriage groups. However, no prominent differences between spontaneous and recurrent miscarriage groups were identified. Potential key modulators ST3GAL6 and NEU1 were found to be significantly downregulated in the recurrent miscarriage group and upregulated in the spontaneous group, respectively. Interestingly, LeX and LeY expression was also detected in the endothelial cells of villous vessels in the control group but no significant expression in miscarriage groups. Furthermore, assessment of villous vessel density using CD31 found significantly diminished vessels in all size groups of villi (small villi <200 µm, P = 0.0371; middle villi between 200 and 400 µm, P = 0.0010 and large villi >400 µm, P = 0.0003). Immunofluorescent double staining also indicated the co-localization of LeX/Y and CD31.ConclusionsThe expression of four mentioned carbohydrate Lewis antigens and their potential modulators, ST3GAL6 and NEU1, in the placenta of patients with miscarriages was significantly different from the normal pregnancy. For the first time, their expression pattern in the placenta was illustrated, which might shed light on a novel understanding of Lewis antigens' role in the pathogenesis of miscarriages.
| S-EPMC8202085 | biostudies-literature
Project description:The conjugated dienamine 4 selectively adds Piers' borane [HB(C6F5)2] to give the enamine/borane system 5, which features a boratirane structure by internal enamine carbon Lewis base to boron Lewis acid interaction. Compound 5 behaves as a C/B frustrated Lewis pair and undergoes typical addition reactions to benzaldehyde, several nitriles and to sulfur dioxide.This article is part of the themed issue 'Frustrated Lewis pair chemistry'.
| S-EPMC5540844 | biostudies-literature