Genome-wide meta-analysis of 158,000 individuals of European ancestry identifies three loci associated with chronic back pain

Back pain is the #1 cause of years lived with disability worldwide, yet surprisingly little is known regarding the biology underlying this symptom. We conducted a genome-wide association study (GWAS) meta-analysis of ch

Assessment of Osteoarthritis Candidate Genes in a Meta-Analysis of Nine Genome-Wide Association Studies

Objective To assess candidate genes for association with osteoarthritis (OA) and identify promising genetic factors and, secondarily, to assess the candidate gene approach in OA. Methods A total of 199 candidate genes for association with OA were identified using Human Genome Epidemiology (HuGE) Navigator. All of their single-nucleotide polymorphisms (SNPs) with an allele frequency of >5% were assessed by fixed-effects meta-analysis of 9 genome-wide association studies (GWAS) that included 5,636 patients with knee OA and 16,972 control subjects and 4,349 patients with hip OA and 17,836 control subjects of European ancestry. An additional 5,921 individuals were genotyped for significantly associated SNPs in the meta-analysis. After correction for the number of independent tests, P values less than 1.58 × 10−5 were considered significant. Results SNPs at only 2 of the 199 candidate genes (COL11A1 and VEGF) were associated with OA in the meta-analysis. Two SNPs in COL11A1 showed association with hip OA in the combined analysis: rs4907986 (P = 1.29 × 10−5, odds ratio [OR] 1.12, 95% confidence interval [95% CI] 1.06−1.17) and rs1241164 (P = 1.47 × 10−5, OR 0.82, 95% CI 0.74−0.89). The sex-stratified analysis also showed association of COL11A1 SNP rs4908291 in women (P = 1.29 × 10−5, OR 0.87, 95% CI 0.82−0.92); this SNP showed linkage disequilibrium with rs4907986. A single SNP of VEGF, rs833058, showed association with hip OA in men (P = 1.35 × 10−5, OR 0.85, 95% CI 0.79−0.91). After additional samples were genotyped, association at one of the COL11A1 signals was reinforced, whereas association at VEGF was slightly weakened. Conclusion Two candidate genes, COL11A1 and VEGF, were significantly associated with OA in this focused meta-analysis. The remaining candidate genes were not associated

The genetic epidemiology of joint shape and the development of osteoarthritis

Congruent, low-friction relative movement between the articulating elements of a synovial joint is an essential pre-requisite for sustained, efficient, function. Where disorders of joint formation or maintenance exist, mechanical overloading and osteoarthritis (OA) follow. The heritable component of OA accounts for ~ 50% of susceptible risk. Although almost 100 genetic risk loci for OA have now been identified, and the epidemiological relationship between joint development, joint shape and osteoarthritis is well established, we still have only a limited understanding of the contribution that genetic variation makes to joint shape and how this modulates OA risk. In this article, a brief overview of synovial joint development and its genetic regulation is followed by a review of current knowledge on the genetic epidemiology of established joint shape disorders and common shape variation. A summary of current genetic epidemiology of OA is also given, together with current evidence on the genetic overlap between shape variation and OA. Finally, the established genetic risk loci for both joint shape and osteoarthritis are discussed

The Compact Linear Collider (CLIC) - 2018 Summary Report

The Compact Linear Collider (CLIC) is a TeV-scale high-luminosity linear $e^+e^-$ collider under development at CERN. Following the CLIC conceptual design published in 2012, this report provides an overview of the CLIC project, its current status, and future developments. It presents the CLIC physics potential and reports on design, technology, and implementation aspects of the accelerator and the detector. CLIC is foreseen to be built and operated in stages, at centre-of-mass energies of 380 GeV, 1.5 TeV and 3 TeV, respectively. CLIC uses a two-beam acceleration scheme, in which 12 GHz accelerating structures are powered via a high-current drive beam. For the first stage, an alternative with X-band klystron powering is also considered. CLIC accelerator optimisation, technical developments and system tests have resulted in an increased energy efficiency (power around 170 MW) for the 380 GeV stage, together with a reduced cost estimate at the level of 6 billion CHF. The detector concept has been refined using improved software tools. Significant progress has been made on detector technology developments for the tracking and calorimetry systems. A wide range of CLIC physics studies has been conducted, both through full detector simulations and parametric studies, together providing a broad overview of the CLIC physics potential. Each of the three energy stages adds cornerstones of the full CLIC physics programme, such as Higgs width and couplings, top-quark properties, Higgs self-coupling, direct searches, and many precision electroweak measurements. The interpretation of the combined results gives crucial and accurate insight into new physics, largely complementary to LHC and HL-LHC. The construction of the first CLIC energy stage could start by 2026. First beams would be available by 2035, marking the beginning of a broad CLIC physics programme spanning 25-30 years

eQTL colocalization analysis highlights novel susceptibility genes in Autism Spectrum Disorders (ASD)

Abstract Autism Spectrum Disorders (ASD) are a group of neurodevelopmental disorders (NDDs) characterized by difficulties in social interaction and communication, repetitive behavior, and restricted interests. ASD has proven to have a strong genetic component. However, defining causal genes is still one of the main challenges in GWAS, since the vast majority (>90%) of detected signals lie within the non-coding genome. Expression quantitative trait locus (eQTL) colocalization analysis determines whether a specific variant is responsible for both a local eQTL and GWAS association and has helped leverage data and rendering gene discovery for a wide array of diseases. Here we further mine the largest ASD GWAS performed to date (18,381 cases and 27,969 controls) altogether with GWAS summary statistics from the main PGC studies (Schizophrenia, MD (Major Depression) and ADHD (Attention Deficit/Hyperactivity Disorder)), by using eQTpLot, a newly developed tool that illustrates the colocalization of GWAS and eQTL signals in a locus, and the enrichment of and correlation between the candidate gene eQTLs and trait-significant variants. This analysis points up 8 genes with a significant eQTL colocalization signal in ASD (CRHR1, KANSL1, MANBA, MAPT, MMP12, NKX2-2, PTPRE and WNT3) and one gene (SRPK2) with a marginally significant colocalization signal (r = 0.69, p < 1 × 10−6), and specifically highlights the potentially causal role of MAPT (r = 0.76, p < 1 × 10−6), NKX2-2 (r = 0.71, p-value = 2.26−02) and PTPRE (r = 0.97, p-value = 2.63−04) when restricting the analysis to brain tissue