Statistical Power of Model Selection Strategies for Genome-Wide Association Studies

Genome-wide association studies (GWAS) aim to identify genetic variants related to diseases by examining the associations between phenotypes and hundreds of thousands of genotyped markers. Because many genes are potentially involved in common diseases and a large number of markers are analyzed, it is crucial to devise an effective strategy to identify truly associated variants that have individual and/or interactive effects, while controlling false positives at the desired level. Although a number of model selection methods have been proposed in the literature, including marginal search, exhaustive search, and forward search, their relative performance has only been evaluated through limited simulations due to the lack of an analytical approach to calculating the power of these methods. This article develops a novel statistical approach for power calculation, derives accurate formulas for the power of different model selection strategies, and then uses the formulas to evaluate and compare these strategies in genetic model spaces. In contrast to previous studies, our theoretical framework allows for random genotypes, correlations among test statistics, and a false-positive control based on GWAS practice. After the accuracy of our analytical results is validated through simulations, they are utilized to systematically evaluate and compare the performance of these strategies in a wide class of genetic models. For a specific genetic model, our results clearly reveal how different factors, such as effect size, allele frequency, and interaction, jointly affect the statistical power of each strategy. An example is provided for the application of our approach to empirical research. The statistical approach used in our derivations is general and can be employed to address the model selection problems in other random predictor settings. We have developed an R package markerSearchPower to implement our formulas, which can be downloaded from the Comprehensive R Archive Network (CRAN) or http://bioinformatics.med.yale.edu/group/

Chair based exercise in community settings: a cluster randomised feasibility study

Background: Some older people who find standard exercise programmes too strenuous may be encouraged to exercise while remaining seated - chair based exercises (CBE). We previously developed a consensus CBE programme (CCBE) following a modified Delphi process. We firstly needed to test the feasibility and acceptability of this treatment approach and explore how best to evaluate it before undertaking a definitive trial. Methods: A feasibility study with a cluster randomised controlled trial component was undertaken to 1. Examine the acceptability, feasibility and tolerability of the intervention and 2. Assess the feasibility of running a trial across 12 community settings (4 day centres, 4 care homes, 4 community groups). Centres were randomised to either CCBE, group reminiscence or usual care. Outcomes were collected to assess the feasibility of the trial parameters: level of recruitment interest and eligibility, randomisation, adverse events, retention, completion of health outcomes, missing data and delivery of the CCBE. Semi- structured interviews were conducted with participants and care staff following the intervention to explore acceptability. Results: 48% (89 out of 184 contacted) of eligible centres were interested in participating with 12 recruited purposively. 73% (94) of the 128 older people screened consented to take part with 83 older people then randomised following mobility testing. Recruitment required greater staffing levels and resources due to 49% of participants requiring a consultee declaration. There was a high dropout rate (40%) primarily due to participants no longer attending the centres. The CCBE intervention was delivered once a week in day centres and community groups and twice a week in care homes. Older people and care staff found the CCBE intervention largely acceptable. Conclusion: There was a good level of interest from centres and older people and the CCBE intervention was largely welcomed. The trial design and governance procedures would need to be revised to maximise recruitment and retention. If the motivation for a future trial is physical health then this study has identified that further work to develop the CCBE delivery model is warranted to ensure it can be delivered at a frequency to elicit physiological change. If the motivation for a future trial is psychological outcomes then this study has identified that the current delivery model is feasible

The Plasmodium falciparum STEVOR Multigene Family Mediates Antigenic Variation of the Infected Erythrocyte

Modifications of the Plasmodium falciparum–infected red blood cell (iRBC) surface have been linked to parasite-associated pathology. Such modifications enable the parasite to establish long-lasting chronic infection by evading antibody mediate immune recognition and splenic clearance. With the exception of the well-demonstrated roles of var-encoded PfEMP1 in virulence and immune evasion, the biological significance of other variant surface antigens (rif and stevor) is largely unknown. While PfEMP1 and RIFIN have been located on the iRBC surface, recent studies have located STEVOR at the iRBC membrane where it may be exposed on the erythrocyte surface. To investigate the role of STEVOR in more detail, we have developed antibodies against two putative STEVOR proteins and used a combination of indirect immunofluorescence assays (IFA), live IFA, flow cytometry, as well as agglutination assays, which enable us to demonstrate that STEVOR is clonally variant at the surface of schizont stage parasites. Crucially, expression of different STEVOR on the surface of the iRBC changes the antigenic property of the parasite. Taken together, our data for the first time demonstrate that STEVOR plays a role in creating antigenic diversity of schizont stage parasites, thereby adding additional complexity to the immunogenic properties of the iRBC. Furthermore, it clearly demonstrates that to obtain a complete understanding of how parasite-induced pathology is linked to variation on the surface of the iRBC, focusing the interactions of multiple multigene families needs to be considered

A social engineering model for poverty alleviation

Poverty, the quintessential denominator of a developing nation, has been traditionally defined against an arbitrary poverty line; individuals (or countries) below this line are deemed poor and those above it, not so! This has two pitfalls. First, absolute reliance on a single poverty line, based on basic food consumption, and not on total consumption distribution, is only a partial poverty index at best. Second, a single expense descriptor is an exogenous quantity that does not evolve from income-expenditure statistics. Using extensive income-expenditure statistics from India, here we show how a self-consistent endogenous poverty line can be derived from an agent-based stochastic model of market exchange, combining all expenditure modes (basic food, other food and non-food), whose parameters are probabilistically estimated using advanced Machine Learning tools. Our mathematical study establishes a consumption based poverty measure that combines labor, commodity, and asset market outcomes, delivering an excellent tool for economic policy formulation

Evaluation of a corticotropin releasing hormone type 1 receptor antagonist in women with posttraumatic stress disorder: Study protocol for a randomized controlled trial

Background: Pharmacologic treatment options for posttraumatic stress disorder (PTSD) are limited in number and effectiveness. Medications currently in use to treat PTSD were originally approved based on their efficacy in other disorders, such as major dep