Meta-Analyses of Genome-Wide Association Studies for Postpartum Depression.

OBJECTIVE: Postpartum depression (PPD) is a common subtype of major depressive disorder (MDD) that is more heritable, yet is understudied in psychiatric genetics. The authors conducted meta-analyses of genome-wide association studies (GWASs) to investigate the genetic architecture of PPD. METHOD: Meta-analyses were conducted on 18 cohorts of European ancestry (17,339 PPD cases and 53,426 controls), one cohort of East Asian ancestry (975 cases and 3,780 controls), and one cohort of African ancestry (456 cases and 1,255 controls), totaling 18,770 PPD cases and 58,461 controls. Post-GWAS analyses included 1) single-nucleotide polymorphism (SNP)-based heritability ([Formula: see text]), 2) genetic correlations between PPD and other phenotypes, and 3) enrichment of the PPD GWAS findings in 27 human tissues and 265 cell types from the mouse central and peripheral nervous system. RESULTS: No SNP achieved genome-wide significance in the European or the trans-ancestry meta-analyses. The [Formula: see text] of PPD was 0.14 (SE=0.02). Significant genetic correlations were estimated for PPD with MDD, bipolar disorder, anxiety disorders, posttraumatic stress disorder, insomnia, age at menarche, and polycystic ovary syndrome. Cell-type enrichment analyses implicate inhibitory neurons in the thalamus and cholinergic neurons within septal nuclei of the hypothalamus, a pattern that differs from MDD. CONCLUSIONS: While more samples are needed to reach genome-wide levels of significance, the results presented confirm PPD as a polygenic and heritable phenotype. There is also evidence that despite a high correlation with MDD, PPD may have unique genetic components. Cell enrichment results suggest GABAergic neurons, which converge on a common mechanism with the only medication approved by the U.S. Food and Drug Administration for PPD (brexanolone).

Early control of viral load by favipiravir promotes survival to Ebola virus challenge and prevents cytokine storm in non-human primates.

Ebola virus has been responsible for two major epidemics over the last several years and there has been a strong effort to find potential treatments that can improve the disease outcome. Antiviral favipiravir was thus tested on non-human primates infected with Ebola virus. Half of the treated animals survived the Ebola virus challenge, whereas the infection was fully lethal for the untreated ones. Moreover, the treated animals that did not survive died later than the controls. We evaluated the hematological, virological, biochemical, and immunological parameters of the animals and performed proteomic analysis at various timepoints of the disease. The viral load strongly correlated with dysregulation of the biological functions involved in pathogenesis, notably the inflammatory response, hemostatic functions, and response to stress. Thus, the management of viral replication in Ebola virus disease is of crucial importance in preventing the immunopathogenic disorders and septic-like shock syndrome generally observed in Ebola virus-infected patients.

General regression model: A "model-free" association test for quantitative traits allowing to test for the underlying genetic model.

Most genome-wide association studies used genetic-model-based tests assuming an additive mode of inheritance, leading to underpowered association tests in case of departure from additivity. The general regression model (GRM) association test proposed by Fisher and Wilson in 1980 makes no assumption on the genetic model. Interestingly, it also allows formal testing of the underlying genetic model. We conducted a simulation study of quantitative traits to compare the power of the GRM test to the classical linear regression tests, the maximum of the three statistics (MAX), and the allele-based (allelic) tests. Simulations were performed on two samples sizes, using a large panel of genetic models, varying genetic models, minor allele frequencies, and the percentage of explained variance. In case of departure from additivity, the GRM was more powerful than the additive regression tests (power gain reaching 80%) and had similar power when the true model is additive. GRM was also as or more powerful than the MAX or allelic tests. The true simulated model was mostly retained by the GRM test. Application of GRM to HbA1c illustrates its gain in power. To conclude, GRM increases power to detect association for quantitative traits, allows determining the genetic model and is easily applicable.

Immune parameters and outcomes during Ebola virus disease.

BACKGROUND: The West African Ebola virus epidemic from 2014-2016 highlighted the lack of knowledge about the pathogenicity of the virus and the factors responsible for outcome. A performant and rapid diagnosis is of crucial importance, as is overcoming the difficulty of providing high-quality patient management during such an extensive outbreak. Here, we propose to study the role of the immune mediators during Ebola virus disease and to define some molecules of importance in the outcome. METHODS: Plasma from Guinean patients sampled during the outbreak were analyzed using RT-qPCR, magnetic bead assay, ELISA, and high-quality statistical analyses. We also performed a transcriptomic analysis in leukocytes samples. Therefore, we deeply characterized the immune responses involved in Ebola virus disease. RESULTS: We evaluated the immune patterns depending on the outcome of the disease. Survivors presented an efficient and well-balanced immune response, whereas fatalities were characterized by an intense inflammatory response, overexpression of multiple cytokines, and a "chemokine storm." The plasma concentration of most of the parameters tested increased until death. Statistical analyses also allowed us to define a panel of markers highly predictive of outcome. CONCLUSION: The immune response observed in fatalities was highly similar to that characterizing septic shock syndrome. Our results suggest that immune responses can play a major pathogenic role during severe Ebola virus infection and argue in favor of therapeutic approaches that act on both viral replication and the induction of shock syndrome. FUNDING: French Ministry of Foreign Affairs, the Agence Française de Développement, and the Institut Pasteur.

A systematic review of non-genetic predictors and genetic factors of glycated haemoglobin in type 1 diabetes one year after diagnosis.

Type 1 diabetes (T1D) results from autoimmune destruction of the pancreatic ßcells. Although all T1D patients require daily administration of exogenous insulin, their insulin requirement to achieve good glycaemic control may vary significantly. Glycated haemoglobin (HbA1c) level represents a stable indicator of glycaemic control and is a reliable predictor of long-term complications of T1D. The purpose of this article is to systematically review the role of non-genetic predictors and genetic factors of HbA1c level in T1D patients after the first year of T1D, to exclude the honeymoon period. A total of 1974 articles published since January 2011 were identified and 78 were finally included in the analysis of non-genetic predictors. For genetic factors, a total of 277 articles were identified and 14 were included. The most significantly associated factors with HbA1c level are demographic (age, ethnicity, and socioeconomic status), personal (family characteristics, parental care, psychological traits...) and features related to T1D (duration of T1D, adherence to treatment …). Only a few studies have searched for genetic factors influencing HbA1c level, most of which focused on candidate genes using classical genetic statistical methods, with generally limited power and incomplete adjustment for confounding factors and multiple testing. Our review shows the complexity of explaining HbA1c level variations, which involves numerous correlated predictors. Overall, our review underlines the lack of studies investigating jointly genetic and non-genetic factors and their interactions to better understand factors influencing glycaemic control for T1D patients.