Identification of regulatory variants associated with genetic susceptibility to meningococcal disease

Non-coding genetic variants play an important role in driving susceptibility to complex diseases but their characterization remains challenging. Here, we employed a novel approach to interrogate the genetic risk of such polymorphisms in a more systematic way by targeting specific regulatory regions relevant for the phenotype studied. We applied this method to meningococcal disease susceptibility, using the DNA binding pattern of RELA - a NF-kB subunit, master regulator of the response to infection - under bacterial stimuli in nasopharyngeal epithelial cells. We designed a custom panel to cover these RELA binding sites and used it for targeted sequencing in cases and controls. Variant calling and association analysis were performed followed by validation of candidate polymorphisms by genotyping in three independent cohorts. We identified two new polymorphisms, rs4823231 and rs11913168, showing signs of association with meningococcal disease susceptibility. In addition, using our genomic data as well as publicly available resources, we found evidences for these SNPs to have potential regulatory effects on ATXN10 and LIF genes respectively. The variants and related candidate genes are relevant for infectious diseases and may have important contribution for meningococcal disease pathology. Finally, we described a novel genetic association approach that could be applied to other phenotypes

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection ar

Early mathematics achievement of boys and girls: Do differences in early self-regulation pathways explain later achievement?

The degree to which a true gender gap exists in mathematics achievement is still debated, and empirically-supported explanations for any gap rarely address very early childhood self-regulatory pathways. This study examines whether mathematics achievement at 8-9 years differs by gender, how achievement is associated with self-regulatory pathways beginning at 2-3 years of age, and whether these pathways differ by gender. Participants were 5,107 children involved in the nationally-representative <i>Longitudinal Study of Australian Children (LSAC)</i>. Boys outperformed girls in mathematics achievement and girls generally had better early attentional and emotional regulation. Path analysis revealed that attentional regulation was directly associated with mathematics achievement from 4-5 years, and emotional regulation was indirectly associated. These self-regulatory pathways to mathematics achievement were not moderated by gender. We discuss the implications for further research and new approaches to early years mathematics education that embed self-regulatory support and development for all children

Early Childhood Screen Use Contexts and Cognitive and Psychosocial Outcomes: A Systematic Review and Meta-analysis

Importance: The multifaceted nature of screen use has been largely overlooked in favor of a simplistic unidimensional measure of overall screen time when evaluating the benefits and risks of screen use to early childhood development. Objective: To conduct a systematic review and meta-analysis to examine associations of screen use contexts in early childhood with cognitive and psychosocial outcomes. Data Sources: PsycINFO, Embase, MEDLINE Ovid, ProQuest, CINAHL, Web of Science, and Scopus were searched from inception to December 31, 2023. Study Selection: A total of 7441 studies were initially identified. Studies were included if they examined associations between a contextual factor of screen use among children aged 0 to 5.99 years and cognitive or psychosocial development. Observational, experimental, and randomized clinical trial study designs were included. Data Extraction and Synthesis: All studies were independently screened in duplicate following PRISMA guidelines. Effect sizes of associations (r) from observational studies were pooled using random-effects 3-level meta-analyses. The remaining study designs were narratively synthesized. Main Outcomes and Measures: Screen use contexts included content (child directed and age inappropriate), type (program viewing and game or app use), co-use (or solo use), background television, caregiver screen use during child routines, and purpose. Outcomes were cognitive (executive functioning, language, and academic skills) or psychosocial (internalizing and externalizing behavior problems and socioemotional competence). Results: Overall, 100 studies (176742 participants) were included, and of these, 64 observational studies (pooled sample sizes ranging from 711 to 69232) were included in meta-analyses. Program viewing (n = 14; k = 48; r, -0.16; 95% CI, -0.24 to -0.08) and background television (n = 8; k = 18; r, -0.10; 95% CI, -0.18 to -0.02) were negatively associated with cognitive outcomes, while program viewing (n = 6; k = 31; r, -0.04; 95% CI, -0.07 to -0.01), age-inappropriate content (n = 9; k = 36; r, -0.11; 95% CI, -0.17 to -0.04), and caregiver screen use during routines (n = 6; k = 14; r, -0.11; 95% CI, -0.20 to -0.03) were negatively associated with psychosocial outcomes. Co-use was positively associated with cognitive outcomes (n = 8; k = 28; r, 0.14; 95% CI, 0.03 to 0.25). Conclusions and Relevance: Findings show small to moderate effect sizes that highlight the need to consider screen use contexts when making recommendations for families, clinicians, and educators beyond screen time limits; including encouraging intentional and productive screen use, age-appropriate content, and co-use with caregivers

Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes

OBJECTIVE - Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired b-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS - We have conducted a meta-analysis of genome-wide association tests of ;2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS - Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10-8). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/ C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 3 10-4), improved b-cell function (P = 1.1 × 10-5), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10-6). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS - We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis

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