26 research outputs found

    Physical activity attenuates the influence of FTO variants on obesity risk: A meta-analysis of 218,166 adults and 19,268 children

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    Background: The FTO gene harbors the strongest known susceptibility locus for obesity. While many individual studies have suggested that physical activity (PA) may attenuate the effect of FTO on obesity risk, other studies have not been able to confirm this interaction. To confirm or refute unambiguously whether PA attenuates the association of FTO with obesity risk, we meta-analyzed data from 45 studies of adults (n = 218,166) and nine studies of children and adolescents (n = 19,268). Methods and Findings: All studies identified to have data on the FTO rs9939609 variant (or any proxy [r2>0.8]) and PA were invited to participate, regardless of ethnicity or age of the participants. PA was standardized by categorizing it into a dichotomous variable (physically inactive versus active) in each study. Overall, 25% of adults and 13% of children were categorized as inactive. Interaction analyses were performed within each study by including the FTO×PA interaction term in an additive model, adjusting for age and sex. Subsequently, random effects meta-analysis was used to pool the interaction terms. In adults, the minor (A-) allele of rs9939609 increased the odds of obesity by 1.23-fold/allele (95% CI 1.20-1.26), but PA attenuated this effect (pinteraction= 0.001). More specifically, the minor allele of rs9939609 increased the odds of obesity less in the physically active group (odds ratio = 1.22/allele, 95% CI 1.19-1.25) than in the inactive group (odds ratio = 1.30/allele, 95% CI 1.24-1.36). No such interaction was found in children and adolescents. Concl

    Subcortical volumes across the lifespan: data from 18,605 healthy individuals aged 3-90 years

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    Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.Education and Child Studie

    Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns

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    Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike’s information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk

    A Machine Learning Algorithm to Identify Patients at Risk of Unplanned Subsequent Surgery After Intramedullary Nailing for Tibial Shaft Fractures

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    Objectives: In the SPRINT trial, 18% of patients with a tibial shaft fracture (TSF) treated with intramedullary nailing (IMN) had one or more unplanned subsequent surgical procedures. It is clinically relevant for surgeon and patient to anticipate unplanned secondary procedures, other than operations that can be readily expected such as reconstructive procedures for soft tissue defects. Therefore, the objective of this study was to develop a machine learning (ML) prediction model using the SPRINT data that can give individual patients and their care team an estimate of their particular probability of an unplanned second surgery. Methods: Patients from the SPRINT trial with unilateral TSFs were randomly divided into a training set (80%) and test set (20%). Five ML algorithms were trained in recognizing patterns associated with subsequent surgery in the training set based on a subset of variables identified by random forest algorithms. Performance of each ML algorithm was evaluated and compared based on (1) area under the ROC curve, (2) calibration slope and intercept, and (3) the Brier score. Results: Total data set comprised 1198 patients, of whom 214 patients (18%) underwent subsequent surgery. Seven variables were used to train ML algorithms: (1) Gustilo-Anderson classification, (2) Tscherne classification, (3) fracture location, (4) fracture gap, (5) polytrauma, (6) injury mechanism, and (7) OTA/AO classification. The best-performing ML algorithm had an area under the ROC curve, calibration slope, calibration intercept, and the Brier score of 0.766, 0.954, -0.002, and 0.120 in the training set and 0.773, 0.922, 0, and 0.119 in the test set, respectively. Conclusions: An ML algorithm was developed to predict the probability of subsequent surgery after IMN for TSFs. This ML algorithm may assist surgeons to inform patients about the probability of subsequent surgery and might help to identify patients who need a different perioperative plan or a more intensive approach.Orthopaedics, Trauma Surgery and Rehabilitatio

    Measurement of electrons from semileptonic heavy-flavour hadron decays at midrapidity in pp and Pb–Pb collisions at √sNN = 5.02 TeV

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    The differential invariant yield as a function of transverse momentum (pT) of electrons from semileptonic heavy-flavour hadron decays was measured at midrapidity in central (0–10%), semi-central (30–50%) and peripheral (60–80%) lead–lead (Pb–Pb) collisions at √sNN = 5.02 TeV in the pT intervals 0.5–26 GeV/c (0–10% and 30–50%) and 0.5–10 GeV/c (60–80%). The production cross section in proton–proton (pp) collisions at √s = 5.02 TeV was measured as well in 0.5 < pT < 10 GeV/c and it lies close to the upper band of perturbative QCD calculation uncertainties up to pT = 5 GeV/c and close to the mean value for larger pT. The modification of the electron yield with respect to what is expected for an incoherent superposition of nucleon–nucleon collisions is evaluated by measuring the nuclear modification factor RAA. The measurement of the RAA in different centrality classes allows in-medium energy loss of charm and beauty quarks to be investigated. The RAA shows a suppression with respect to unity at intermediate pT, which increases while moving towards more central collisions. Moreover, the measured RAA is sensitive to the modification of the parton distribution functions (PDF) in nuclei, like nuclear shadowing, which causes a suppression of the heavy-quark production at low pT in heavy-ion collisions at LHC

    Study of the Λ–Λ interaction with femtoscopy correlations in pp and p–Pb collisions at the LHC

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    This work presents new constraints on the existence and the binding energy of a possible – bound state, the H-dibaryon, derived from – femtoscopic measurements by the ALICE collaboration. The results are obtained from a new measurement using the femtoscopy technique in pp collisions at √s = 13 TeV and p–Pb collisions at √sNN = 5.02 TeV, combined with previously published results from pp collisions at √s = 7 TeV. The – scattering parameter space, spanned by the inverse scattering length f −1 0 and the effective range d0, is constrained by comparing the measured – correlation function with calculations obtained within the LednickĂœ model. The data are compatible with hypernuclei results and lattice computations, both predicting a shallow attractive interaction, and permit to test different theoretical approaches describing the – interaction. The region in the (f −1 0 ,d0) plane which would accommodate a – bound state is substantially restricted compared to previous studies. The binding energy of the possible – bound state is estimated within an effective-range expansion approach and is found to be B = 3.2+1.6 −2.4(stat)+1.8 −1.0(syst) MeV
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