Racial discrimination and posttraumatic stress: examining emotion dysregulation as a mediator in an African American community sample

Background: African Americans experience more severe and chronic posttraumatic stress disorder (PTSD) symptoms compared to other racial groups, and thus it is important to examine factors that are relevant for the aetiology of PTSD in this population. Although racial discrimination has been implicated as an exacerbating factor in the development and maintenance of PTSD, relatively less is known about mechanisms through which this process may occur. Objective: The purpose of this study was to examine one such mechanism, emotion dysregulation, in two independent samples of African American adults. Method: Trauma-exposed participants were recruited in a large, urban community hospital setting (initial sample n = 1,841; replication sample n = 294). In the initial sample, participants completed a unidimensional measure of emotion dysregulation and self-reported PTSD symptoms based on the DSM-IV. In the replication sample, participants completed a multidimensional measure of emotion dysregulation and a diagnostic interview of PTSD symptoms based on the DSM-5. Mediation analyses were used to test our hypotheses. Results: Across both samples, results indicated that racial discrimination was indirectly associated with PTSD symptoms through emotion dysregulation (even when trauma load was added as a covariate). Conclusions: Taken together, these results provide strong evidence that the association between racial discrimination and PTSD symptoms may be partially explained by the association between racial discrimination and worse emotion dysregulation. These findings elucidate the impact of racist incidents on mental health and identify modifiable emotion regulatory processes that can be intervened upon to enhance the psychological and social wellbeing of African Americans

Whole-genome sequencing reveals host factors underlying critical COVID-19

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease