Novel genetic analysis for case-control genome-wide association studies: quantification of power and genomic prediction accuracy

Genome-wide association studies (GWAS) are routinely conducted for both quantitative and binary (disease) traits. We present two analytical tools for use in the experimental design of GWAS. Firstly, we present power calculations quantifying power in a unified framework for a range of scenarios. In this context we consider the utility of quantitative scores (e.g. endophenotypes) that may be available on cases only or both cases and controls. Secondly, we consider, the accuracy of prediction of genetic risk from genome-wide SNPs and derive an expression for genomic prediction accuracy using a liability threshold model for disease traits in a case-control design. The expected values based on our derived equations for both power and prediction accuracy agree well with observed estimates from simulations

Having a lot of a good thing: multiple important group memberships as a source of self-esteem.

Copyright: © 2015 Jetten et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedMembership in important social groups can promote a positive identity. We propose and test an identity resource model in which personal self-esteem is boosted by membership in additional important social groups. Belonging to multiple important group memberships predicts personal self-esteem in children (Study 1a), older adults (Study 1b), and former residents of a homeless shelter (Study 1c). Study 2 shows that the effects of multiple important group memberships on personal self-esteem are not reducible to number of interpersonal ties. Studies 3a and 3b provide longitudinal evidence that multiple important group memberships predict personal self-esteem over time. Studies 4 and 5 show that collective self-esteem mediates this effect, suggesting that membership in multiple important groups boosts personal self-esteem because people take pride in, and derive meaning from, important group memberships. Discussion focuses on when and why important group memberships act as a social resource that fuels personal self-esteem.This study was supported by 1. Australian Research Council Future Fellowship (FT110100238) awarded to Jolanda Jetten (see http://www.arc.gov.au) 2. Australian Research Council Linkage Grant (LP110200437) to Jolanda Jetten and Genevieve Dingle (see http://www.arc.gov.au) 3. support from the Canadian Institute for Advanced Research Social Interactions, Identity and Well-Being Program to Nyla Branscombe, S. Alexander Haslam, and Catherine Haslam (see http://www.cifar.ca)

The diabetes gene Zfp69 modulates hepatic insulin sensitivity in mice

AIMS/HYPOTHESIS: Zfp69 was previously identified by positional cloning as a candidate gene for obesity-associated diabetes. C57BL/6J and New Zealand obese (NZO) mice carry a loss-of-function mutation due to the integration of a retrotransposon. On the NZO background, the Zfp69 locus caused severe hyperglycaemia and loss of beta cells. To provide direct evidence for a causal role of Zfp69, we investigated the effects of its overexpression on both a lean [B6-Tg(Zfp69)] and an obese [NZO/B6-Tg(Zfp69)] background. METHODS: Zfp69 transgenic mice were generated by integrating the cDNA into the ROSA locus of the C57BL/6 genome and characterised. RESULTS: B6-Tg(Zfp69) mice were normoglycaemic, developed hyperinsulinaemia, and exhibited increased expression of G6pc and Pck1 and slightly reduced phospho-Akt levels in the liver. During OGTTs, glucose clearance was normal but insulin levels were significantly higher in the B6-Tg(Zfp69) than in control mice. The liver fat content and plasma triacylglycerol levels were significantly increased in B6-Tg(Zfp69) and NZO/B6-Tg(Zfp69) mice on a high-fat diet compared with controls. Liver transcriptome analysis of B6-Tg(Zfp69) mice revealed a downregulation of genes involved in glucose and lipid metabolism. Specifically, expression of Nampt, Lpin2, Map2k6, Gys2, Bnip3, Fitm2, Slc2a2, Ppargc1α and Insr was significantly decreased in the liver of B6-Tg(Zfp69) mice compared with wild-type animals. However, overexpression of Zfp69 did not induce overt diabetes with hyperglycaemia and beta cell loss. CONCLUSIONS/INTERPRETATION: Zfp69 mediates hyperlipidaemia, liver fat accumulation and mild insulin resistance. However, it does not induce type 2 diabetes, suggesting that the diabetogenic effect of the Zfp69 locus requires synergy with other as yet unidentified genes

Economic evaluation alongside a single RCT of an integrative psychotherapeutic nursing home programme

__Abstract__ There is an 80% prevalence of two or more psychiatric symptoms in psychogeriatric patients. Multiple psychiatric symptoms (MPS) have many negative effects on quality of life of the patient as well as on caregiver burden and competence. Irrespective of the effectiveness of an intervention programme, it is important to take into account its economic aspects

Learning genetic epistasis using Bayesian network scoring criteria

<p>Abstract</p> <p>Background</p> <p>Gene-gene epistatic interactions likely play an important role in the genetic basis of many common diseases. Recently, machine-learning and data mining methods have been developed for learning epistatic relationships from data. A well-known combinatorial method that has been successfully applied for detecting epistasis is <it>Multifactor Dimensionality Reduction </it>(MDR). Jiang et al. created a combinatorial epistasis learning method called <it>BNMBL </it>to learn Bayesian network (BN) epistatic models. They compared BNMBL to MDR using simulated data sets. Each of these data sets was generated from a model that associates two SNPs with a disease and includes 18 unrelated SNPs. For each data set, BNMBL and MDR were used to score all 2-SNP models, and BNMBL learned significantly more correct models. In real data sets, we ordinarily do not know the number of SNPs that influence phenotype. BNMBL may not perform as well if we also scored models containing more than two SNPs. Furthermore, a number of other BN scoring criteria have been developed. They may detect epistatic interactions even better than BNMBL.</p> <p>Although BNs are a promising tool for learning epistatic relationships from data, we cannot confidently use them in this domain until we determine which scoring criteria work best or even well when we try learning the correct model without knowledge of the number of SNPs in that model.</p> <p>Results</p> <p>We evaluated the performance of 22 BN scoring criteria using 28,000 simulated data sets and a real Alzheimer's GWAS data set. Our results were surprising in that the Bayesian scoring criterion with large values of a hyperparameter called α performed best. This score performed better than other BN scoring criteria and MDR at <it>recall </it>using simulated data sets, at detecting the hardest-to-detect models using simulated data sets, and at substantiating previous results using the real Alzheimer's data set.</p> <p>Conclusions</p> <p>We conclude that representing epistatic interactions using BN models and scoring them using a BN scoring criterion holds promise for identifying epistatic genetic variants in data. In particular, the Bayesian scoring criterion with large values of a hyperparameter α appears more promising than a number of alternatives.</p

Inhibition of nuclear factor kappa-B signaling reduces growth in medulloblastoma in vivo

Abstract Background Medulloblastoma is a highly malignant pediatric brain tumor that requires surgery, whole brain and spine irradiation, and intense chemotherapy for treatment. A more sophisticated understanding of the pathophysiology of medulloblastoma is needed to successfully reduce the intensity of treatment and improve outcomes. Nuclear factor kappa-B (NFκB) is a signaling pathway that controls transcriptional activation of genes important for tight regulation of many cellular processes and is aberrantly expressed in many types of cancer. Methods To test the importance of NFκB to medulloblastoma cell growth, the effects of multiple drugs that inhibit NFκB, pyrrolidine dithiocarbamate, diethyldithiocarbamate, sulfasalazine, curcumin and bortezomib, were studied in medulloblastoma cell lines compared to a malignant glioma cell line and normal neurons. Expression of endogenous NFκB was investigated in cultured cells, xenograft flank tumors, and primary human tumor samples. A dominant negative construct for the endogenous inhibitor of NFκB, IκB, was prepared from medulloblastoma cell lines and flank tumors were established to allow specific pathway inhibition. Results We report high constitutive activity of the canonical NFκB pathway, as seen by Western analysis of the NFκB subunit p65, in medulloblastoma tumors compared to normal brain. The p65 subunit of NFκB is extremely highly expressed in xenograft tumors from human medulloblastoma cell lines; though, conversely, the same cells in culture have minimal expression without specific stimulation. We demonstrate that pharmacological inhibition of NFκB in cell lines halts proliferation and leads to apoptosis. We show by immunohistochemical stain that phosphorylated p65 is found in the majority of primary tumor cells examined. Finally, expression of a dominant negative form of the endogenous inhibitor of NFκB, dnIκB, resulted in poor xenograft tumor growth, with average tumor volumes 40% smaller than controls. Conclusions These data collectively demonstrate that NFκB signaling is important for medulloblastoma tumor growth, and that inhibition can reduce tumor size and viability in vivo. We discuss the implications of NFκB signaling on the approach to managing patients with medulloblastoma in order to improve clinical outcomes.</p

Usability, acceptability, and feasibility of two technology-based devices for mental health screening in perinatal care: A comparison of web versus app

The use of Information and Communication Technologies (web pages and apps) in mental health has boosted. However, it is unknown which of these two devices can be better in terms of feasibility and acceptability. Our aim is to compare the feasibility, usability, and user satisfaction of two devices (web vs mobile application) of an online program for perinatal depression screening called HappyMom. In total, 348 and 175 perinatal women registered into HappyMom web and app version, respectively. The assessment protocol included different biopsychosocial evaluations (twice during pregnancy and thrice in the postpartum) and a satisfaction questionnaire. Results showed that a higher percentage of women in the web sample (27.3–51.1%) responded to each assessment compared to the app sample (9.1–53.1%). A smaller proportion of women in web sample never responded to any assessments. By contrast, the percentage of women who responded to all assessments was higher in app sample (longitudinal retention sample was 4.6% of web users and 9.1% of app users). In general, high satisfaction was found in both web and app users. Our result showed that online assessment methods are feasible and acceptable by perinatal women. However, dropout rates are a real problem that urge a solution that will be discussed further in the paper. Web and App devices present different advantages and limitations. The choice of one of them must be made taking into account the study’s objective, the sample characteristics, and the dissemination possibilities

Partner relationship satisfaction and maternal emotional distress in early pregnancy

<p>Abstract</p> <p>Background</p> <p>Recognition of maternal emotional distress during pregnancy and the identification of risk factors for this distress are of considerable clinical- and public health importance. The mental health of the mother is important both for herself, and for the physical and psychological health of her children and the welfare of the family. The first aim of the present study was to identify risk factors for maternal emotional distress during pregnancy with special focus on partner relationship satisfaction. The second aim was to assess interaction effects between relationship satisfaction and the main predictors.</p> <p>Methods</p> <p>Pregnant women enrolled in the Norwegian Mother and Child Cohort Study (n = 51,558) completed a questionnaire with questions about maternal emotional distress, relationship satisfaction, and other risk factors. Associations between 37 predictor variables and emotional distress were estimated by multiple linear regression analysis.</p> <p>Results</p> <p>Relationship dissatisfaction was the strongest predictor of maternal emotional distress (β = 0.25). Other predictors were dissatisfaction at work (β = 0.11), somatic disease (β = 0.11), work related stress (β = 0.10) and maternal alcohol problems in the preceding year (β = 0.09). Relationship satisfaction appeared to buffer the effects of frequent moving, somatic disease, maternal smoking, family income, irregular working hours, dissatisfaction at work, work stress, and mother's sick leave (<it>P </it>< 0.05).</p> <p>Conclusions</p> <p>Dissatisfaction with the partner relationship is a significant predictor of maternal emotional distress in pregnancy. A good partner relationship can have a protective effect against some stressors.</p