479 research outputs found

    MegaSNPHunter: a learning approach to detect disease predisposition SNPs and high level interactions in genome wide association study

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    <p>Abstract</p> <p>Background</p> <p>The interactions of multiple single nucleotide polymorphisms (SNPs) are highly hypothesized to affect an individual's susceptibility to complex diseases. Although many works have been done to identify and quantify the importance of multi-SNP interactions, few of them could handle the genome wide data due to the combinatorial explosive search space and the difficulty to statistically evaluate the high-order interactions given limited samples.</p> <p>Results</p> <p>Three comparative experiments are designed to evaluate the performance of MegaSNPHunter. The first experiment uses synthetic data generated on the basis of epistasis models. The second one uses a genome wide study on Parkinson disease (data acquired by using Illumina HumanHap300 SNP chips). The third one chooses the rheumatoid arthritis study from Wellcome Trust Case Control Consortium (WTCCC) using Affymetrix GeneChip 500K Mapping Array Set. MegaSNPHunter outperforms the best solution in this area and reports many potential interactions for the two real studies.</p> <p>Conclusion</p> <p>The experimental results on both synthetic data and two real data sets demonstrate that our proposed approach outperforms the best solution that is currently available in handling large-scale SNP data both in terms of speed and in terms of detection of potential interactions that were not identified before. To our knowledge, MegaSNPHunter is the first approach that is capable of identifying the disease-associated SNP interactions from WTCCC studies and is promising for practical disease prognosis.</p

    Detection of regulator genes and eQTLs in gene networks

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    Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure

    Feasibility study of portable technology for weight loss and HbA1c control in type 2 diabetes

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    Background The study investigated the feasibility of conducting a future Randomised Controlled Trial (RCT) of a mobile health (mHealth) intervention for weight loss and HbA1c reduction in Type 2 Diabetes Mellitus (T2DM). Methods The intervention was a small wearable mHealth device used over 12 weeks by overweight people with T2DM with the intent to lose weight and reduce their HbA1c level. A 4 week maintenance period using the device followed. The device records physical activity level and information about food consumption, and provides motivational feedback based on energy balance. Twenty-seven participants were randomised to receive no intervention; intervention alone; or intervention plus weekly motivational support. All participants received advice on diet and exercise at the start of the study. Weight and HbA1c levels were recorded at baseline and weeks 6, 12, and 16. Qualitative interviews were conducted with participants who received the intervention to explore their experiences of using the device and involvement in the study including the training received. Results Overall the device was perceived to be well-liked, acceptable, motivational and easy to use by participants. Some logistical changes were required during the feasibility study, including shortening of the study duration and relaxation of participant inclusion criteria. Descriptive statistics of weight and HbA1c data showed promising trends of weight loss and HbA1c reduction in both intervention groups, although this should be interpreted with caution. Conclusions A number of methodological recommendations for a future RCT emerged from the current feasibility study. The mHealth device was acceptable and promising for helping individuals with T2DM to reduce their HbA1c and lose weight. Devices with similar features should be tested further in larger studies which follow these methodological recommendations

    Fumarate is an epigenetic modifier that elicits epithelial-to-mesenchymal transition.

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    Mutations of the tricarboxylic acid cycle enzyme fumarate hydratase cause hereditary leiomyomatosis and renal cell cancer. Fumarate hydratase-deficient renal cancers are highly aggressive and metastasize even when small, leading to a very poor clinical outcome. Fumarate, a small molecule metabolite that accumulates in fumarate hydratase-deficient cells, plays a key role in cell transformation, making it a bona fide oncometabolite. Fumarate has been shown to inhibit α-ketoglutarate-dependent dioxygenases that are involved in DNA and histone demethylation. However, the link between fumarate accumulation, epigenetic changes, and tumorigenesis is unclear. Here we show that loss of fumarate hydratase and the subsequent accumulation of fumarate in mouse and human cells elicits an epithelial-to-mesenchymal-transition (EMT), a phenotypic switch associated with cancer initiation, invasion, and metastasis. We demonstrate that fumarate inhibits Tet-mediated demethylation of a regulatory region of the antimetastatic miRNA cluster mir-200ba429, leading to the expression of EMT-related transcription factors and enhanced migratory properties. These epigenetic and phenotypic changes are recapitulated by the incubation of fumarate hydratase-proficient cells with cell-permeable fumarate. Loss of fumarate hydratase is associated with suppression of miR-200 and the EMT signature in renal cancer and is associated with poor clinical outcome. These results imply that loss of fumarate hydratase and fumarate accumulation contribute to the aggressive features of fumarate hydratase-deficient tumours.This work was supported by the Medical Research Council (UK). S.F. was supported by a Herchel Smith Research Studentship and K.F. by an MRC Career Development Award. E.R.M is supported by the ERC Advanced Researcher award 323004–ONCOTREAT. P.H.M. is supported by Senior Investigator Awards from the Wellcome Trust and NIHR. The Cambridge Human Research Tissue Bank and A.W. are supported by the NIHR Cambridge Biomedical Research Centre.This is the author accepted manuscript. The final version is available from Nature Publishing at http://dx.doi.org/10.1038/nature19353

    Genetic Variation and Reproductive Timing: African American Women from the Population Architecture Using Genomics and Epidemiology (PAGE) Study

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    Age at menarche (AM) and age at natural menopause (ANM) define the boundaries of the reproductive lifespan in women. Their timing is associated with various diseases, including cancer and cardiovascular disease. Genome-wide association studies have identified several genetic variants associated with either AM or ANM in populations of largely European or Asian descent women. The extent to which these associations generalize to diverse populations remains unknown. Therefore, we sought to replicate previously reported AM and ANM findings and to identify novel AM and ANM variants using the Metabochip (n = 161,098 SNPs) in 4,159 and 1,860 African American women, respectively, in the Women's Health Initiative (WHI) and Atherosclerosis Risk in Communities (ARIC) studies, as part of the Population Architecture using Genomics and Epidemiology (PAGE) Study. We replicated or generalized one previously identified variant for AM, rs1361108/CENPW, and two variants for ANM, rs897798/BRSK1 and rs769450/APOE, to our African American cohort. Overall, generalization of the majority of previously-identified variants for AM and ANM, including LIN28B and MCM8, was not observed in this African American sample. We identified three novel loci associated with ANM that reached significance after multiple testing correction (LDLR rs189596789, p = 5×10-08; KCNQ1 rs79972789, p = 1.9×10-07; COL4A3BP rs181686584, p = 2.9×10-07). Our most significant AM association was upstream of RSF1, a gene implicated in ovarian and breast cancers (rs11604207, p = 1.6×10-06). While most associations were identified in either AM or ANM, we did identify genes suggestively associated with both: PHACTR1 and ARHGAP42. The lack of generalization coupled with the potentially novel associations identified here emphasize the need for additional genetic discovery efforts for AM and ANM in diverse populations. © 2013 Spencer et al

    Physical activity in pregnancy: a qualitative study of the beliefs of overweight and obese pregnant women

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    <p>Abstract</p> <p>Background</p> <p>Whilst there has been increasing research interest in interventions which promote physical activity during pregnancy few studies have yielded detailed insights into the views and experiences of overweight and obese pregnant women themselves. The qualitative study described in this paper aimed to: (i) explore the views and experiences of overweight and obese pregnant women; and (ii) inform interventions which could promote the adoption of physical activity during pregnancy.</p> <p>Methods</p> <p>The study was framed by a combined Subtle Realism and Theory of Planned Behaviour (TPB) approach. This enabled us to examine the hypothetical pathway between beliefs and physical activity intentions within the context of day to day life. The study sample for the qualitative study was chosen by stratified, purposive sampling from a previous study of physical activity measurements in pregnancy. Research participants for the current study were recruited on the basis of Body Mass Index (BMI) at booking and parity. Semi-structured, in-depth interviews were conducted with 14 overweight and obese pregnant women. Data analysis was undertaken using a Framework Approach and was informed by TPB.</p> <p>Results</p> <p>Healthy eating was often viewed as being of greater importance for the health of mother and baby than participation in physical activity. A commonly cited motivator for maintaining physical activity during pregnancy is an aid to reducing pregnancy-related weight gain. However, participants often described how they would wait until the postnatal period to try and lose weight. A wide range of barriers to physical activity during pregnancy were highlighted including both internal (physical and psychological) and external (work, family, time and environmental). The study participants also lacked access to consistent information, advice and support on the benefits of physical activity during pregnancy.</p> <p>Conclusions</p> <p>Interventions to encourage recommended levels of physical activity in pregnancy should be accompanied by accessible and consistent information about the positive effects for mother and baby. More research is required to examine how to overcome barriers to physical activity and to understand which interventions could be most effective for overweight/obese pregnant women. Midwives should be encouraged to do more to promote activity in pregnancy.</p
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