Physical activity and academic achievement across the curriculum (A + PAAC): rationale and design of a 3-year, cluster-randomized trial

Abstract Background Improving academic achievement and reducing the rates of obesity in elementary school students are both of considerable interest. Increased physical activity during academic instruction time during school offers a potential intervention to address both issues. A program titled “Physical Activity Across the Curriculum” (PAAC) was developed in which classroom teachers in 22 elementary schools were trained to deliver academic instruction using physical activity with a primary aim of preventing increased BMI. A secondary analysis of data assessed the impact of PAAC on academic achievement using the Weschler Individual Achievement Test-II and significant improvements were shown for reading, math and spelling in students who participated in PAAC. Based on the results from PAAC, an adequately powered trial will be conducted to assess differences in academic achievement between intervention and control schools called, “Academic Achievement and Physical Activity Across the Curriculum (A + PAAC).” Methods/design Seventeen elementary schools were cluster randomized to A + PAAC or control for a 3-year trial. Classroom teachers were trained to deliver academic instruction through moderate-to-vigorous physical activity with a target of 100+ minutes of A + PAAC activities per week. The primary outcome measure is academic achievement measured by the Weschler Individual Achievement Test-III, which was administered at baseline (Fall 2011) and will be repeated in the spring of each year by assessors blinded to condition. Potential mediators of any association between A + PAAC and academic achievement will be examined on the same schedule and include changes in cognitive function, cardiovascular fitness, daily physical activity, BMI, and attention-to-task. An extensive process analysis will be conducted to document the fidelity of the intervention. School and student recruitment/randomization, teacher training, and baseline testing for A + PAAC have been completed. Nine schools were randomized to the intervention and 8 to control. A random sample of students in each school, stratified by gender and grade (A + PAAC = 370, Control = 317), was selected for outcome assessments from those who provided parental consent/child assent. Baseline data by intervention group are presented. Discussion If successful, the A + PAAC approach could be easily and inexpensively scaled and disseminated across elementary schools to improve both educational quality and health. Funding source: R01- DK85317. Trial registration: US NIH Clinical Trials, http://NCT01699295.Peer Reviewe

Chromosome contacts in activated T cells identify autoimmune disease candidate genes

BACKGROUND: Autoimmune disease-associated variants are preferentially found in regulatory regions in immune cells, particularly CD4+ T cells. Linking such regulatory regions to gene promoters in disease-relevant cell contexts facilitates identification of candidate disease genes. RESULTS: Within four hours, activation of CD4+ T cells invokes changes in histone modifications and enhancer RNA transcription that correspond to altered expression of the interacting genes identified by promoter capture Hi-C (PCHi-C). By integrating PCHi-C data with genetic associations for five autoimmune diseases we prioritised 245 candidate genes with a median distance from peak signal to prioritised gene of 153 kb. Just under half (108/245) prioritised genes related to activation-sensitive interactions. This included IL2RA, where allele-specific expression analyses were consistent with its interaction-mediated regulation, illustrating the utility of the approach. CONCLUSIONS: Our systematic experimental framework offers an alternative approach to candidate causal gene identification for variants with cell state-specific functional effects, with achievable sample sizes.This work was funded by the JDRF (9-2011-253), the Wellcome Trust (089989, 091157, 107881), the UK Medical Research Council (MR/L007150/1, MC_UP_1302/5), the UK Biotechnology and Biological Sciences Research Council (BB/J004480/1) and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre. The research leading to these results has received funding from the European Union’s 7th Framework Programme (FP7/2007-2013) under grant agreement no. 241447 (NAIMIT). The Cambridge Institute for Medical Research (CIMR) is in receipt of a Wellcome Trust Strategic Award (100140)

The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease

Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal.We thank members of the Cambridge BioResource Scientific Advisory Board and Management Committee for their support of our study and the National Institute for Health Research Cambridge Biomedical Research Centre for funding. K.D. is funded as a HSST trainee by NHS Health Education England. M.F. is funded from the BLUEPRINT Grant Code HEALTH-F5-2011-282510 and the BHF Cambridge Centre of Excellence [RE/13/6/30180]. J.R.S. is funded by a MRC CASE Industrial studentship, co-funded by Pfizer. J.D. is a British Heart Foundation Professor, European Research Council Senior Investigator, and National Institute for Health Research (NIHR) Senior Investigator. S.M., S.T, M.H, K.M. and L.D. are supported by the NIHR BioResource-Rare Diseases, which is funded by NIHR. Research in the Ouwehand laboratory is supported by program grants from the NIHR to W.H.O., the European Commission (HEALTH-F2-2012-279233), the British Heart Foundation (BHF) to W.J.A. and D.R. under numbers RP-PG-0310-1002 and RG/09/12/28096 and Bristol Myers-Squibb; the laboratory also receives funding from NHSBT. W.H.O is a NIHR Senior Investigator. The INTERVAL academic coordinating centre receives core support from the UK Medical Research Council (G0800270), the BHF (SP/09/002), the NIHR and Cambridge Biomedical Research Centre, as well as grants from the European Research Council (268834), the European Commission Framework Programme 7 (HEALTH-F2-2012-279233), Merck and Pfizer. DJR and DA were supported by the NIHR Programme ‘Erythropoiesis in Health and Disease’ (Ref. NIHR-RP-PG-0310-1004). N.S. is supported by the Wellcome Trust (Grant Codes WT098051 and WT091310), the EU FP7 (EPIGENESYS Grant Code 257082 and BLUEPRINT Grant Code HEALTH-F5-2011-282510). The INTERVAL study is funded by NHSBT and has been supported by the NIHR-BTRU in Donor Health and Genomics at the University of Cambridge in partnership with NHSBT. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, the Department of Health of England or NHSBT. D.G. is supported by a “la Caixa”-Severo Ochoa pre-doctoral fellowship

A reference map of the human binary protein interactome.

Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships(1,2). Here we present a human 'all-by-all' reference interactome map of human binary protein interactions, or 'HuRI'. With approximately 53,000 protein-protein interactions, HuRI has approximately four times as many such interactions as there are high-quality curated interactions from small-scale studies. The integration of HuRI with genome(3), transcriptome(4) and proteome(5) data enables cellular function to be studied within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying the specific subcellular roles of protein-protein interactions. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases. HuRI is a systematic proteome-wide reference that links genomic variation to phenotypic outcomes