Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Successful linkage of French large-scale national registry populations to national reimbursement data: Improved data completeness and minimized loss to follow-up

International audienceBackground: Registries, a cornerstone of contemporary medicine, frequently suffer from incomplete documentation and losses to follow-up. By linking data to a single-payer national claims database, national registries may be enriched and the quality enhanced.Aims: To explore the value of data from the French Système National des Données de Santé (SNDS) as a resource to enhance the quality of registries when combined with data from electronic case report forms, and to assess the power to minimize data gaps and losses to follow-up.Methods: A probabilistic algorithm was developed to link and match records in the SNDS with patient data from the electronic case report forms of two registries on transcatheter aortic valve implantation: FRANCE-2 and FRANCE-TAVI. The algorithm created patient profiles from transcatheter aortic valve implantation procedures in the SNDS, matching them as closely as possible to the profiles in the registry databases. The objective was to achieve 90% linkage of the populations. The linked database was analysed for completeness and loss to follow-up. For validation, mortality curves for the linked registry cohorts were compared with those for the original populations. Results: A total of 34,397 unique registries entries were identified, and 89.9% of patients in the SNDS could be linked. Rates of losses to follow-up over 2 years were 1.0% in the linked FRANCE-TAVI population compared with 40.3% based on electronic case report form documentation. For FRANCE-2, 3-year rates of losses to follow-up were 1.7% and 6.1%, respectively. Mortality curves for populations based on SNDS and electronic case report form data were practically superimposable.Conclusions: Linking data from a single-payer national claims database to national registries using a probabilistic approach is feasible and can close data gaps and practically abolish losses to follow-up in the registry population

Long-Term Prognosis Value of Paravalvular Leak and Patient–Prosthesis Mismatch following Transcatheter Aortic Valve Implantation: Insight from the France-TAVI Registry

International audienceBackground: Transcatheter aortic valve implantation (TAVI) is the preferred treatment for symptomatic severe aortic stenosis (AS) in a majority of patients across all surgical risks. Patients and methods: Paravalvular leak (PVL) and patient–prosthesis mismatch (PPM) are two frequent complications of TAVI. Therefore, based on the large France-TAVI registry, we planned to report the incidence of both complications following TAVI, evaluate their respective risk factors, and study their respective impacts on long-term clinical outcomes, including mortality. Results: We identified 47,494 patients in the database who underwent a TAVI in France between 1 January 2010 and 31 December 2019. Within this population, 17,742 patients had information regarding PPM status (5138 with moderate-to-severe PPM, 29.0%) and 20,878 had information regarding PVL (4056 with PVL ≥ 2, 19.4%). After adjustment, the risk factors for PVL ≥ 2 were a lower body mass index (BMI), a high baseline mean aortic gradient, a higher body surface area, a lower ejection fraction, a smaller diameter of TAVI, and a self-expandable TAVI device, while for moderate-to-severe PPM we identified a younger age, a lower BMI, a larger body surface area, a low aortic annulus area, a low ejection fraction, and a smaller diameter TAVI device (OR 0.85; 95% CI, 0.83–0.86) as predictors. At 6.5 years, PVL ≥ 2 was an independent predictor of mortality and was associated with higher mortality risk. PPM was not associated with increased risk of mortality. Conclusions: Our analysis from the France-TAVI registry showed that both moderate-to-severe PPM and PVL ≥ 2 continue to be frequently observed after the TAVI procedure. Different risk factors, mostly related to the patient’s anatomy and TAVI device selection, for both complications have been identified. Only PVL ≥ 2 was associated with higher mortality during follow-up

Digital rock physics benchmarks. Pt.II: Computing effective properties

This is the second and final part of our digital rock physics (DRP) benchmarking study. We use segmented 3-D images (one for Fontainebleau, three for Berea, three for a carbonate, and one for a sphere pack) to directly compute the absolute permeability, the electrical resistivity, and elastic moduli. The numerical methods tested include a finite-element solver (elastic moduli and electrical conductivity), two finite-difference solvers (elastic moduli and electrical conductivity), a Fourier-based Lippmann-Schwinger solver (elastic moduli), a lattice-Boltzmann solver (hydraulic permeability), and the explicit-jump method (hydraulic permeability and electrical conductivity). The set-ups for these numerical experiments, including the boundary conditions and the total model size, varied as well. The results thus produced vary from each other. For example, the highest computed permeability value may differ from the lowest one by a factor of 1.5. Nevertheless, all these result s fall within the ranges consistent with the relevant laboratory data. Our analysis provides the DRP community with a range of possible outcomes which can be expected depending on the solver and its setup

A dynamic unfolded protein response contributes to the control of cortical neurogenesis

peer reviewedaudience: researcher, professional, studen