Neuroanatomical Correlates of the Income-Achievement Gap

In the United States, the difference in academic achievement between higher- and lower-income students (i.e., the income-achievement gap) is substantial and growing. In the research reported here, we investigated neuroanatomical correlates of this gap in adolescents (N = 58) in whom academic achievement was measured by statewide standardized testing. Cortical gray-matter volume was significantly greater in students from higher-income backgrounds (n = 35) than in students from lower-income backgrounds (n = 23), but cortical white-matter volume and total cortical surface area did not differ significantly between groups. Cortical thickness in all lobes of the brain was greater in students from higher-income than lower-income backgrounds. Greater cortical thickness, particularly in temporal and occipital lobes, was associated with better test performance. These results represent the first evidence that cortical thickness in higher- and lower-income students differs across broad swaths of the brain and that cortical thickness is related to scores on academic-achievement tests.Bill & Melinda Gates FoundationNational Institutes of Health (U.S.) (Grant F32 HD079143-01)National Institutes of Health (U.S.) (Grant F32 MH095354-01

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Cognitive Skills, Student Achievement Tests, and Schools

Cognitive skills predict academic performance, so schools that improve academic performance might also improve cognitive skills. To investigate the impact schools have on both academic performance and cognitive skills, we related standardized achievement-test scores to measures of cognitive skills in a large sample (N = 1,367) of eighth-grade students attending traditional, exam, and charter public schools. Test scores and gains in test scores over time correlated with measures of cognitive skills. Despite wide variation in test scores across schools, differences in cognitive skills across schools were negligible after we controlled for fourth-grade test scores. Random offers of enrollment to oversubscribed charter schools resulted in positive impacts of such school attendance on math achievement but had no impact on cognitive skills. These findings suggest that schools that improve standardized achievement-test scores do so primarily through channels other than improving cognitive skills.Bill & Melinda Gates FoundationNational Institutes of Health (U.S.) (National Research Service Award

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

COVID-19 Host Genetics Initiative. A first update on mapping the human genetic architecture of COVID-19

The COVID-19 pandemic continues to pose a major public health threat, especially in countries with low vaccination rates. To better understand the biological underpinnings of SARS-CoV-2 infection and COVID-19 severity, we formed the COVID-19 Host Genetics Initiative1. Here we present a genome-wide association study meta-analysis of up to 125,584 cases and over 2.5 million control individuals across 60 studies from 25 countries, adding 11 genome-wide significant loci compared with those previously identified2. Genes at new loci, including SFTPD, MUC5B and ACE2, reveal compelling insights regarding disease susceptibility and severity.</p