Evaluating aggregate effects of rare and common variants in the 1000 Genomes Project exon sequencing data using latent variable structural equation modeling

Methods that can evaluate aggregate effects of rare and common variants are limited. Therefore, we applied a two-stage approach to evaluate aggregate gene effects in the 1000 Genomes Project data, which contain 24,487 single-nucleotide polymorphisms (SNPs) in 697 unrelated individuals from 7 populations. In stage 1, we identified potentially interesting genes (PIGs) as those having at least one SNP meeting Bonferroni correction using univariate, multiple regression models. In stage 2, we evaluate aggregate PIG effects on trait, Q1, by modeling each gene as a latent construct, which is defined by multiple common and rare variants, using the multivariate statistical framework of structural equation modeling (SEM). In stage 1, we found that PIGs varied markedly between a randomly selected replicate (replicate 137) and 100 other replicates, with the exception of FLT1. In stage 1, collapsing rare variants decreased false positives but increased false negatives. In stage 2, we developed a good-fitting SEM model that included all nine genes simulated to affect Q1 (FLT1, KDR, ARNT, ELAV4, FLT4, HIF1A, HIF3A, VEGFA, VEGFC) and found that FLT1 had the largest effect on Q1 (βstd = 0.33 ± 0.05). Using replicate 137 estimates as population values, we found that the mean relative bias in the parameters (loadings, paths, residuals) and their standard errors across 100 replicates was on average, less than 5%. Our latent variable SEM approach provides a viable framework for modeling aggregate effects of rare and common variants in multiple genes, but more elegant methods are needed in stage 1 to minimize type I and type II error

How mothers feel: validation of a measure of maternal mood

© 2019 The Authors. Journal of Evaluation in Clinical Practice published by John Wiley & Sons Ltd Rationale: Low mood may affect developing relationships with a new baby, partner and family. Early identification of mood disturbance is crucial to improve outcomes for women perinatally. Instruments such as the Edinburgh Postnatal Depression Scale (EPDS) are used routinely, with evidence that some women do not feel comfortable with how they are asked about their mental health. Objective: To develop a mood checklist as a user-friendly, effective measure of well-being in post-partum women, for use by health professionals. Methods: Cognitive interviews with women who had recently given birth assessed response format and face validity of a prototype measure. A cross-sectional survey followed. A random split-half instrument development protocol was used. Exploratory factor analysis determined factor structure with the first sample,. The second sample confirmed factor structure and evaluationof key psychometric variables and known-groups discriminant validity (KGDV), requiring a supplementary between-subjects design with stratification based on case negative/case positive classification using EPDSscreening cut-off criteria. Results: Cognitive interview data confirmed the face validity of the measure. Exploratory factor analysis indicated an 18 item two-factor model with two (negatively) correlated factors. Factor 1 loaded with items reflecting positive mood and factor 2 negative items. Confirmatory factor analysis showed a good fit to the two-factor model across the full spectrum of fit indices. Statistically significant differences between groups were observed in relation to as EPDS caseness classification. Cronbach alpha coefficients for the positive and negative subscales revealed acceptable internal consistency of 0.79 and 0.72, respectively. Conclusion: The outcome checklist may be appropriate for use in clinical practice. It demonstrated effective psychometric properties and clear cross-validation with existing commonly used measures

Social network size, loneliness, physical functioning and depressive symptoms among older adults: Examining reciprocal associations in four waves of the Longitudinal Aging Study Amsterdam (LASA)

Previous research indicates that social isolation, loneliness, physical dysfunction and depressive symptoms are interrelated factors, little is known about the potential pathways among them. The aim of the study is to analyse simultaneously reciprocal relationships that could exist between the four factors to clarify potential mediation effects. METHODS Within a large representative sample of older people in the Longitudinal Aging Study Amsterdam (LASA), participants aged 75 and over were followed up over a period of 11 years (four waves). We tested cross-lagged and autoregressive longitudinal associations of social network size, loneliness, physical functioning and depressive symptoms using structural equation modelling (SEM). RESULTS Several statistically significant cross-lagged associations were found: decreasing physical functioning (Coef.=-0.03; p<0.05), as well as social network size (Coef.=-0.02; p<0.05), predicted higher levels of loneliness, which predicted an increase in depressive symptoms (Coef.=0.17; p<0.05) and further reduction of social network (Coef.=-0.20; p<0.05). Decreasing physical functioning also predicted an increase in depressive symptoms (Coef.=-0.08; p<0.05). All autoregressive associations were statistically significant. CONCLUSION Interventions focused on promoting social activities among older adults after negative life events, such as loss of social contacts or declining physical function, may alleviate feelings of loneliness and act as mental health protector

Development and validation of the Australian Aboriginal racial identity and self-esteem survey for 8-12 year old children (IRISE-C)

Introduction: In Australia, there is little empirical research of the racial identity of Indigenous children and youth as the majority of the current literature focuses on adults. Furthermore, there are no instruments developed with cultural appropriateness when exploring the identity and self-esteem of the Australian Aboriginal population, especially children. The IRISE-C (Racial Identity and Self-Esteem of children) inventory was developed to explore the elements of racial identity and self-esteem of urban, rural and regional Aboriginal children. This paper describes the development and validation of the IRISE-C instrument with over 250 Aboriginal children aged 8 to 12 years. Methods: A pilot of the IRISE C instrument was combined with individual interviews and was undertaken with 35 urban Aboriginal children aged 8-12 years. An exploratory factor analysis was performed to refine the survey and reduce redundant items in readiness for the main study. In the main study, the IRISE C was employed to 229 Aboriginal children aged 6-13 years across three sites (rural, regional and urban) in Western Australia. An exploratory factor analysis using Principal axis factoring was used to assess the fit of items and survey structure. A confirmatory factor analysis was then employed using LISREL (diagonally weighted least squares) to assess factor structures across domains. Internal consistency and reliability of subscales were assessed using Cronbach's co-efficient alpha. Results: The pilot testing identified two key concepts - children's knowledge of issues related to their racial identity, and the importance, or salience, that they attach to these issues. In the main study, factor analyses showed two clear factors relating to: Aboriginal culture and traditions; and a sense of belonging to an Aboriginal community. Principal Axis Factoring of the Knowledge items supported a 2-factor solution, which explained 38.7 % of variance. Factor One (Aboriginal culture) had a Cronbach's alpha of 0.835; Factor 2 (racial identity) had a Cronbach's alpha of 0.800, thus demonstrating high internal reliability of the scales. Conclusion: The IRISE-C has been shown to be a valid instrument useful of exploring the development of racial identity of Australian Aboriginal children across the 8-12 year old age range and across urban, rural and regional geographical locations

The conceptualisation and measurement of DSM-5 Internet Gaming Disorder: the development of the IGD-20 Test

Background: Over the last decade, there has been growing concern about ‘gaming addiction’ and its widely documented detrimental impacts on a minority of individuals that play excessively. The latest (fifth) edition of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (DSM-5) included nine criteria for the potential diagnosis of Internet Gaming Disorder (IGD) and noted that it was a condition that warranted further empirical study. Aim: The main aim of this study was to develop a valid and reliable standardised psychometrically robust tool in addition to providing empirically supported cut-off points. Methods: A sample of 1003 gamers (85.2% males; mean age 26 years) from 57 different countries were recruited via online gaming forums. Validity was assessed by confirmatory factor analysis (CFA), criterion-related validity, and concurrent validity. Latent profile analysis was also carried to distinguish disordered gamers from non-disordered gamers. Sensitivity and specificity analyses were performed to determine an empirical cut-off for the test. Results: The CFA confirmed the viability of IGD-20 Test with a six-factor structure (salience, mood modification, tolerance, withdrawal, conflict and relapse) for the assessment of IGD according to the nine criteria from DSM-5. The IGD-20 Test proved to be valid and reliable. According to the latent profile analysis, 5.3% of the total participants were classed as disordered gamers. Additionally, an optimal empirical cut-off of 71 points (out of 100) seemed to be adequate according to the sensitivity and specificity analyses carried

Are autistic traits measured equivalently in individuals with and without an Autism Spectrum Disorder?:An invariance analysis of the Autism Spectrum Quotient Short Form

It is common to administer measures of autistic traits to those without autism spectrum disorders (ASDs) with, for example, the aim of understanding autistic personality characteristics in non-autistic individuals. Little research has examined the extent to which measures of autistic traits actually measure the same traits in the same way across those with and without an ASD. We addressed this question using a multi-group confirmatory factor invariance analysis of the Autism Quotient Short Form (AQ-S: Hoekstra et al. in J Autism Dev Disord 41(5):589-596, 2011) across those with (n = 148) and without (n = 168) ASD. Metric variance (equality of factor loadings), but not scalar invariance (equality of thresholds), held suggesting that the AQ-S measures the same latent traits in both groups, but with a bias in the manner in which trait levels are estimated. We, therefore, argue that the AQ-S can be used to investigate possible causes and consequences of autistic traits in both groups separately, but caution is due when combining or comparing levels of autistic traits across the two group

The De Jong Gierveld short scales for emotional and social loneliness: tested on data from 7 countries in the UN generations and gender surveys

Loneliness concerns the subjective evaluation of the situation individuals are involved in, characterized either by a number of relationships with friends and colleagues which is smaller than is considered desirable (social loneliness), as well as situations where the intimacy in confidant relationships one wishes for has not been realized (emotional loneliness). To identify people who are lonely direct questions are not sufficient; loneliness scales are preferred. In this article, the quality of the three-item scale for emotional loneliness and the three-item scale for social loneliness has been investigated for use in the following countries participating in the United Nations “Generations and Gender Surveys”: France, Germany, the Netherlands, Russia, Bulgaria, Georgia, and Japan. Sample sizes for the 7 countries varied between 8,158 and 12,828. Translations of the De Jong Gierveld loneliness scale have been tested using reliability and validity tests including a confirmatory factor analysis to test the two-dimensional structure of loneliness. Test outcomes indicated for each of the countries under investigation reliable and valid scales for emotional and social loneliness, respectively

Blockade of Hsp90 by 17AAG antagonizes MDMX and synergizes with Nutlin to induce p53-mediated apoptosis in solid tumors

Strategies to induce p53 activation in wtp53-retaining tumors carry high potential in cancer therapy. Nutlin, a potent highly selective MDM2 inhibitor, induces non-genotoxic p53 activation. Although Nutlin shows promise in promoting cell death in hematopoietic malignancies, a major roadblock is that most solid cancers do not undergo apoptosis but merely reversible growth arrest. p53 inhibition by unopposed MDMX is one major cause for apoptosis resistance to Nutlin. The Hsp90 chaperone is ubiquitously activated in cancer cells and supports oncogenic survival pathways, many of which antagonize p53. The Hsp90 inhibitor 17-allylamino-17-demethoxygeldanamycin (17AAG) is known to induce p53-dependent apoptosis. We show here that in multiple difficult-to-kill solid tumor cells 17AAG modulates several critical components that synergize with Nutlin-activated p53 signaling to convert Nutlin's transient cytostatic response into a cytotoxic killing response in vitro and in xenografts. Combined with Nutlin, 17AAG destabilizes MDMX, reduces MDM2, induces PUMA and inhibits oncogenic survival pathways, such as PI3K/AKT, which counteract p53 signaling at multiple levels. Mechanistically, 17AAG interferes with the repressive MDMX–p53 axis by inducing robust MDMX degradation, thereby markedly increasing p53 transcription compared with Nutlin alone. To our knowledge Nutlin+17AAG represents the first effective pharmacologic knockdown of MDMX. Our study identifies 17AAG as a promising synthetic lethal partner for a more efficient Nutlin-based therapy