Project description:We evaluated the genome-wide mRNA expression profiles in lymphoblastoid cell lines of familial ovarian cancer patients and controls
Project description:We evaluated the genome-wide mRNA expression profiles in lymphoblastoid cell lines of familial ovarian cancer patients and controls Comparing the mRNA expression data of 74 ovarian cancer cases with 47 healthy controls. Genotype information of the 7 risk alleles is linked to the bottom of the Series record.
Project description:This study investigates genomic imbalance in chronic lymphocytic leukemia (CLL) and aims to identify genomic gains and losses with prognostic significance.
Project description:BACKGROUND: Genome-wide association studies prove to be a powerful approach to identify the genetic basis of different human diseases. We studied the relationship between seven diseases characterized in a previous genome-wide association study by the Wellcome Trust Case Control Consortium. Instead of doing a horizontal association of SNPs to diseases, we did a vertical analysis of disease associations by comparing the genetic similarities of diseases. Our analysis was carried out at four levels - the nucleotide level (SNPs), the gene level, the protein level (through protein-protein interaction network), and the phenotype level. RESULTS: Our results show that Crohn's disease, rheumatoid arthritis, and type 1 diabetes share evidence of genetic associations at all levels of analysis, offering strong molecular support for the current grouping of the diseases. On the other hand, coronary artery disease, hypertension, and type 2 diabetes, despite being considered as a natural group with potential aetiological overlap, do not show any evidence of shared genetic basis at all levels. CONCLUSION: Our study is a first attempt on mining of GWA data to examine genetic associations between different diseases. The positive result is apparently not a coincidence and hence demonstrates the promising use of our approach.
Project description:BackgroundMicrobial communities are known to be closely related to many diseases, such as obesity and HIV, and it is of interest to identify differentially abundant microbial species between two or more environments. Since the abundances or counts of microbial species usually have different scales and suffer from zero-inflation or over-dispersion, normalization is a critical step before conducting differential abundance analysis. Several normalization approaches have been proposed, but it is difficult to optimize the characterization of the true relationship between taxa and interesting outcomes. RESULTS: To avoid the challenge of picking an optimal normalization and accommodate the advantages of several normalization strategies, we propose an omnibus approach. Our approach is based on a Cauchy combination test, which is flexible and powerful by aggregating individual p values. We also consider a truncated test statistic to prevent substantial power loss. We experiment with a basic linear regression model as well as recently proposed powerful association tests for microbiome data and compare the performance of the omnibus approach with individual normalization approaches. Experimental results show that, regardless of simulation settings, the new approach exhibits power that is close to the best normalization strategy, while controling the type I error well. CONCLUSIONS: The proposed omnibus test releases researchers from choosing among various normalization methods and it is an aggregated method that provides the powerful result to the underlying optimal normalization, which requires tedious trial and error. While the power may not exceed the best normalization, it is always much better than using a poor choice of normalization.
Project description:BackgroundDetermination of comparative effectiveness in a randomized controlled trial requires consideration of an intervention's comparative uptake (or acceptance) among randomized participants and the intervention's comparative efficacy among participants who use their assigned intervention. If acceptance differs across interventions, then simple randomization of participants can result in post-randomization losses that introduce bias and limit statistical power.MethodsWe develop a novel preference-adaptive randomization procedure in which the allocation probabilities are updated based on the inverse of the relative acceptance rates among randomized participants in each arm. In simulation studies, we determine the optimal frequency with which to update the allocation probabilities based on the number of participants randomized. We illustrate the development and application of preference-adaptive randomization using a randomized controlled trial comparing the effectiveness of different financial incentive structures on prolonged smoking cessation.ResultsSimulation studies indicated that preference-adaptive randomization performed best with frequent updating, accommodated differences in acceptance across arms, and performed well even if the initial values for the allocation probabilities were not equal to their true values. Updating the allocation probabilities after randomizing each participant minimized imbalances in the number of accepting participants across arms over time. In the smoking cessation trial, unexpectedly large differences in acceptance among arms required us to limit the allocation of participants to less acceptable interventions. Nonetheless, the procedure achieved equal numbers of accepting participants in the more acceptable arms, and balanced the characteristics of participants across assigned interventions.ConclusionsPreference-adaptive randomization, coupled with analysis methods based on instrumental variables, can enhance the validity and generalizability of comparative effectiveness studies. In particular, preference-adaptive randomization augments statistical power by maintaining balanced sample sizes in efficacy analyses, while retaining the ability of randomization to balance covariates across arms in effectiveness analyses.Trial registrationClinicalTrials.gov, NCT01526265; 31 January 2012.
Project description:Cannabinoid-based therapies have long been used to treat pain, but there remain questions about their actual mechanisms and efficacy. From an evolutionary perspective, the cannabinoid system would appear to be highly conserved given that the most prevalent endogenous cannabinoid (endocannabinoid) transmitters, 2-arachidonyl glycerol and anandamide, have been found throughout the animal kingdom, at least in the species that have been analysed to date. This review will first examine recent findings regarding the potential conservation across invertebrates and chordates of the enzymes responsible for endocannabinoid synthesis and degradation and the receptors that these transmitters act on. Next, comparisons of how endocannabinoids modulate nociception will be examined for commonalities between vertebrates and invertebrates, with a focus on the medicinal leech Hirudo verbana. Evidence is presented that there are distinct, evolutionarily conserved anti-nociceptive and pro-nociceptive effects. The combined studies across various animal phyla demonstrate the utility of using comparative approaches to understand conserved mechanisms for modulating nociception. This article is part of the Theo Murphy meeting issue 'Evolution of mechanisms and behaviour important for pain'.
Project description:Bifidobacteria are common members of the gastro-intestinal microbiota of a broad range of animal hosts. Their successful adaptation to this particular niche is linked to their saccharolytic metabolism, which is supported by a wide range of glycosyl hydrolases. In the current study a large-scale gene-trait matching (GTM) effort was performed to explore glycan degradation capabilities in B. breve. By correlating the presence/absence of genes and associated genomic clusters with growth/no-growth patterns across a dataset of 20 Bifidobacterium breve strains and nearly 80 different potential growth substrates, we not only validated the approach for a number of previously characterized carbohydrate utilization clusters, but we were also able to discover novel genetic clusters linked to the metabolism of salicin and sucrose. Using GTM, genetic associations were also established for antibiotic resistance and exopolysaccharide production, thereby identifying (novel) bifidobacterial antibiotic resistance markers and showing that the GTM approach is applicable to a variety of phenotypes. Overall, the GTM findings clearly expand our knowledge on members of the B. breve species, in particular how their variable genetic features can be linked to specific phenotypes.
Project description:Notch signaling is critical for vascular morphogenesis by co-determining the sprouting behavior of endothelial cells. Here, we investigate the function of ubiquitin-specific peptidase 10 (USP10) in regulation of the turnover of the NOTCH1 intracellular domain. HUVEC were transfected with scrambled or USP10 targeting siRNA and then stimulated by treatment with DLL4 or control. RNA for analysis was isolated after 24 hours of DLL4 stimulation.