Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders

Personality is influenced by genetic and environmental factors1 and associated with mental health. However, the underlying genetic determinants are largely unknown. We identified six genetic loci, including five novel loci2,3, significantly associated with personality traits in a meta-analysis of genome-wide association studies (N = 123,132–260,861). Of these genomewide significant loci, extraversion was associated with variants in WSCD2 and near PCDH15, and neuroticism with variants on chromosome 8p23.1 and in L3MBTL2. We performed a principal component analysis to extract major dimensions underlying genetic variations among five personality traits and six psychiatric disorders (N = 5,422–18,759). The first genetic dimension separated personality traits and psychiatric disorders, except that neuroticism and openness to experience were clustered with the disorders. High genetic correlations were found between extraversion and attention-deficit– hyperactivity disorder (ADHD) and between openness and schizophrenia and bipolar disorder. The second genetic dimension was closely aligned with extraversion–introversion and grouped neuroticism with internalizing psychopathology (e.g., depression or anxiety)

Parental use of the Internet to seek health information and primary care utilisation for their child: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Using the Internet to seek health information is becoming more common. Its consequences on health care utilisation are hardly known in the general population, in particular among children whose parents seek health information on the Internet. Our objective was to investigate the relationship between parental use of the Internet to seek health information and primary care utilisation for their child.</p> <p>Methods</p> <p>This cross-sectional survey has been carried out in a population of parents of pre-school children in France. The main outcome measure was the self-reported number of primary care consultations for the child, according to parental use of the Internet to seek health information, adjusted for the characteristics of the parents and their child respectively, and parental use of other health information sources.</p> <p>Results</p> <p>A total of 1 068 out of 2 197 questionnaires were returned (response rate of 49%). No association was found between parental use of the Internet to seek health information and the number of consultations within the last 12 months for their child. Variables related to the number of primary care consultations were characteristics of the child (age, medical conditions, homeopathic treatment), parental characteristics (occupation, income, stress level) and consultation of other health information sources (advice from pharmacist, relatives).</p> <p>Conclusion</p> <p>We did not find any relationship between parental use of the Internet to seek health information and primary care utilisation for children. The Internet seems to be used as a supplement to health services rather than as a replacement.</p

Search for CP violation in D+→ϕπ+ and D+s→K0Sπ+ decays

A search for CP violation in D + → ϕπ + decays is performed using data collected in 2011 by the LHCb experiment corresponding to an integrated luminosity of 1.0 fb−1 at a centre of mass energy of 7 TeV. The CP -violating asymmetry is measured to be (−0.04 ± 0.14 ± 0.14)% for candidates with K − K + mass within 20 MeV/c 2 of the ϕ meson mass. A search for a CP -violating asymmetry that varies across the ϕ mass region of the D + → K − K + π + Dalitz plot is also performed, and no evidence for CP violation is found. In addition, the CP asymmetry in the D+s→K0Sπ+ decay is measured to be (0.61 ± 0.83 ± 0.14)%

A correction for sample overlap in genome-wide association studies in a polygenic pleiotropy-informed framework.

BACKGROUND: There is considerable evidence that many complex traits have a partially shared genetic basis, termed pleiotropy. It is therefore useful to consider integrating genome-wide association study (GWAS) data across several traits, usually at the summary statistic level. A major practical challenge arises when these GWAS have overlapping subjects. This is particularly an issue when estimating pleiotropy using methods that condition the significance of one trait on the signficance of a second, such as the covariate-modulated false discovery rate (cmfdr). RESULTS: We propose a method for correcting for sample overlap at the summary statistic level. We quantify the expected amount of spurious correlation between the summary statistics from two GWAS due to sample overlap, and use this estimated correlation in a simple linear correction that adjusts the joint distribution of test statistics from the two GWAS. The correction is appropriate for GWAS with case-control or quantitative outcomes. Our simulations and data example show that without correcting for sample overlap, the cmfdr is not properly controlled, leading to an excessive number of false discoveries and an excessive false discovery proportion. Our correction for sample overlap is effective in that it restores proper control of the false discovery rate, at very little loss in power. CONCLUSIONS: With our proposed correction, it is possible to integrate GWAS summary statistics with overlapping samples in a statistical framework that is dependent on the joint distribution of the two GWAS

Genetic variation and exercise-induced muscle damage: implications for athletic performance, injury and ageing.

Prolonged unaccustomed exercise involving muscle lengthening (eccentric) actions can result in ultrastructural muscle disruption, impaired excitation-contraction coupling, inflammation and muscle protein degradation. This process is associated with delayed onset muscle soreness and is referred to as exercise-induced muscle damage. Although a certain amount of muscle damage may be necessary for adaptation to occur, excessive damage or inadequate recovery from exercise-induced muscle damage can increase injury risk, particularly in older individuals, who experience more damage and require longer to recover from muscle damaging exercise than younger adults. Furthermore, it is apparent that inter-individual variation exists in the response to exercise-induced muscle damage, and there is evidence that genetic variability may play a key role. Although this area of research is in its infancy, certain gene variations, or polymorphisms have been associated with exercise-induced muscle damage (i.e. individuals with certain genotypes experience greater muscle damage, and require longer recovery, following strenuous exercise). These polymorphisms include ACTN3 (R577X, rs1815739), TNF (-308 G>A, rs1800629), IL6 (-174 G>C, rs1800795), and IGF2 (ApaI, 17200 G>A, rs680). Knowing how someone is likely to respond to a particular type of exercise could help coaches/practitioners individualise the exercise training of their athletes/patients, thus maximising recovery and adaptation, while reducing overload-associated injury risk. The purpose of this review is to provide a critical analysis of the literature concerning gene polymorphisms associated with exercise-induced muscle damage, both in young and older individuals, and to highlight the potential mechanisms underpinning these associations, thus providing a better understanding of exercise-induced muscle damage

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function : a report from the COGENT consortium

CORRIGENDUM Molecular Psychiatry (2017) 22, 1651–1652 http://www.nature.com/articles/mp2017197.pdfThe complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (similar to 8M single-nucleotide polymorphisms (SNP) with minor allele frequency >= 1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (PPeer reviewe

Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence

Intelligence is highly heritable(1) and a major determinant of human health and well-being(2). Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence3-7, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.Peer reviewe

Updated measurements of exclusive J/ψ and ψ(2S) production cross-sections in pp collisions at √s = 7 TeV

The differential cross-section as a function of rapidity has been measured for the exclusive production of J/ψ and ψ(2S) mesons in proton–proton collisions at √s = 7 TeV, using data collected by the LHCb experiment, corresponding to an integrated luminosity of 930 pb−1. The cross-sections times branching fractions to two muons having pseudorapidities between 2.0 and 4.5 are measured to be where the first uncertainty is statistical and the second is systematic. The measurements agree with next-to-leading order QCD predictions as well as with models that include saturation effects

Measurement of the Λb0, Ξb-, and Ωb- Baryon Masses

Bottom baryons decaying to a J/ψ meson and a hyperon are reconstructed using 1.0  fb-1 of data collected in 2011 with the LHCb detector. Significant Λb0→J/ψΛ, Ξb-→J/ψΞ- and Ωb-→J/ψΩ- signals are observed and the corresponding masses are measured to be M(Λb0)=5619.53±0.13(stat.)±0.45(syst.)  MeV/c2, M(Ξb-)=5795.8±0.9(stat.)±0.4(syst.)  MeV/c2, M(Ωb-)=6046.0±2.2(stat.)±0.5(syst.)  MeV/c2, while the differences with respect to the Λb0 mass are M(Ξb-)-M(Λb0)=176.2±0.9(stat.)±0.1(syst.)  MeV/c2, M(Ωb-)-M(Λb0)=426.4±2.2(stat.)±0.4(syst.)  MeV/c2. These are the most precise mass measurements of the Λb0, Ξb- and Ωb- baryons to date. Averaging the above Λb0 mass measurement with that published by LHCb using 35  pb-1 of data collected in 2010 yields M(Λb0)=5619.44±0.13(stat.)±0.38(syst.)  MeV/c2