The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707

Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps

We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci,135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency 2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).Peer reviewe

Modélisation et optimisation du sertissage de connecteurs électriques utilisés dans l'industrie automobile

Crimping is typically a technology used to ensure electrical and mechanical connection between a cable and a connector. Numerical modeling of the process is useful to select and optimize particularly the crimping dimensions. The present study is a discussion of 2D and 3D models made with the finite element method, whether implicit static (ABAQUS / Standard) or explicit dynamics (ABAQUS / Explicit). The results of these models are compared with those derived directly from the industrial process (geometry, shape, surfaces and crimping force). Crimping is a nonlinear problem involving large elastic-plastic deformations and multiple contact conditions with friction. The greatest difficulty lies in the profusion of possible contact between couples strands of the cable. For this reason, the dynamic explicit method is preferred, despite the quasi-static aspect of crimping. However, some 2D simulations have been performed with a static implicit algorithm to compareand to settle some simulation parameters in explicit dynamic approach (spatial and temporal discretization). Finally, we propose a parameter optimization crimping based on the use of experiments and analysis of response surface thus formed.Le sertissage est une technologie classiquement employée pour assurer la liaison électrique et mécanique entre un câble et un connecteur. La modélisation numérique du procédé est utile pour choisir et optimiser en particulier les dimensions du sertissage. L'étude présentée est une discussion des modèles 2D et 3D réalisés avec la méthode des éléments finis, que ce soit en statique implicite (ABAQUS/Standard) ou en dynamique explicite (ABAQUS/Explicit). Les résultats de ces modèles sont comparés à ceux issus directement du procédé industriel (géométrie, forme, surfaces et force de sertissage). Le sertissage est un problème non-linéaire impliquant des grandes déformations élasto-plastiques et des conditions de contact multiples, avec frottement. La plus grande difficulté réside dans la profusion de couples de contact possibles entre les torons du câble. Pour cette raison, la méthode dynamique explicite est préférée, en dépit de l'aspect quasi-statique du sertissage. Toutefois, certaines simulations 2D ont pu être réalisées avec un algorithme statique implicite, pour comparer et pour régler quelques paramètres de simulation dans l'approche dynamique explicite (discrétisation spatiale et temporelle). Enfin, nous proposons une optimisation des paramètres du sertissage reposant sur l'usage de plans d'expériences et d’analyse des surfaces de réponse ainsi constituées

Modélisation et optimisation du sertissage de connecteurs électriques utilisés dans l'industrie automobile

COMPIEGNE-BU (601592101) / SudocSudocFranceF

Objectifs de développement de Code_Aster au service de la stratégie logicielle en mécanique à EDF R&D

International audienc

Une condition de contact locale de type "mortar" implémentable dans un code éléments finis industriel

International audienceOn s'intéresse dans ce travail à la gestion de l'incompatibilité des maillages pour le contact dans un cadre industriel. On introduit une condition de contact en moyenne locale qui permet à la fois de satisfaire les patchs tests courants (à l'instar des méthodes de type ``mortar") et d'obtenir une analyse mathématique optimale tout en conservant un aspect local et une définition analytique des espaces d'approximation utilisés. Ces dernières conditions sont primordiales pour pouvoir réaliser l'implémentation de cette nouvelle méthode dans le code éléments finis industriel Code_Aster développé par EDF R&D

A new mCRE-DDM based approach for model updating in structural dynamics with industrial applications

International audienc

A Hybrid High-Order method for incremental associative plasticity with small deformations

International audienceWe devise and evaluate numerically a Hybrid High-Order (HHO) method for incremental associative plasticity with small deformations. The HHO method uses as discrete unknowns piecewise polynomials of order k ≥ 1 on the mesh skeleton, together with cell-based poly-nomials that can be eliminated locally by static condensation. The HHO method supports polyhedral meshes with non-matching interfaces, is free of volumetric-locking and the integration of the behavior law is performed only at cell-based quadrature nodes. Moreover, the principle of virtual work is satisfied locally with equilibrated tractions. Various two-and three-dimensional test cases from the literature are presented including comparison against known solutions and against results obtained with an industrial software using conforming and mixed finite elements

An efficient mCRE-DDM based approach for model updating in structural dynamics with industrial application

International audienc