Near-infrared light increases ATP, extends lifespan and improves mobility in aged Drosophila melanogaster.

Ageing is an irreversible cellular decline partly driven by failing mitochondrial integrity. Mitochondria accumulate DNA mutations and reduce ATP production necessary for cellular metabolism. This is associated with inflammation. Near-infrared exposure increases retinal ATP in old mice via cytochrome c oxidase absorption and reduces inflammation. Here, we expose fruitflies daily to 670 nm radiation, revealing elevated ATP and reduced inflammation with age. Critically, there was a significant increase in average lifespan: 100-175% more flies survived into old age following 670 nm exposure and these had significantly improved mobility. This may be a simple route to extending lifespan and improving function in old age

Identification of a novel susceptibility locus at 13q34 and refinement of the 20p12.2 region as a multi-signal locus associated with bladder cancer risk in individuals of European ancestry

Candidate gene and genome-wide association studies (GWAS) have identified 15 independent genomic regions associated with bladder cancer risk. In search for additional susceptibility variants, we followed up on four promising single-nucleotide polymorphisms (SNPs) that had not achieved genome-wide significance in 6911 cases and 11 814 controls (rs6104690, rs4510656, rs5003154 and rs4907479, P < 1 × 10−6), using additional data from existing GWAS datasets and targeted genotyping for studies that did not have GWAS data. In a combined analysis, which included data on up to 15 058 cases and 286 270 controls, two SNPs achieved genome-wide statistical significance: rs6104690 in a gene desert at 20p12.2 (P = 2.19 × 10−11) and rs4907479 within the MCF2L gene at 13q34 (P = 3.3 × 10−10). Imputation and fine-mapping analyses were performed in these two regions for a subset of 5551 bladder cancer cases and 10 242 controls. Analyses at the 13q34 region suggest a single signal marked by rs4907479. In contrast, we detected two signals in the 20p12.2 region—the first signal is marked by rs6104690, and the second signal is marked by two moderately correlated SNPs (r2 = 0.53), rs6108803 and the previously reported rs62185668. The second 20p12.2 signal is more strongly associated with the risk of muscle-invasive (T2-T4 stage) compared with non-muscle-invasive (Ta, T1 stage) bladder cancer (case–case P ≤ 0.02 for both rs62185668 and rs6108803). Functional analyses are needed to explore the biological mechanisms underlying these novel genetic associations with risk for bladder cancer

Identification of a novel susceptibility locus at 13q34 and refinement of the 20p12.2 region as a multi-signal locus associated with bladder cancer risk in individuals of European ancestry

Contains fulltext : 167299.pdf (publisher's version ) (Closed access)Candidate gene and genome-wide association studies (GWAS) have identified 15 independent genomic regions associated with bladder cancer risk. In search for additional susceptibility variants, we followed up on four promising single-nucleotide polymorphisms (SNPs) that had not achieved genome-wide significance in 6911 cases and 11 814 controls (rs6104690, rs4510656, rs5003154 and rs4907479, P < 1 x 10(-6)), using additional data from existing GWAS datasets and targeted genotyping for studies that did not have GWAS data. In a combined analysis, which included data on up to 15 058 cases and 286 270 controls, two SNPs achieved genome-wide statistical significance: rs6104690 in a gene desert at 20p12.2 (P = 2.19 x 10(-11)) and rs4907479 within the MCF2L gene at 13q34 (P = 3.3 x 10(-10)). Imputation and fine-mapping analyses were performed in these two regions for a subset of 5551 bladder cancer cases and 10 242 controls. Analyses at the 13q34 region suggest a single signal marked by rs4907479. In contrast, we detected two signals in the 20p12.2 region-the first signal is marked by rs6104690, and the second signal is marked by two moderately correlated SNPs (r(2) = 0.53), rs6108803 and the previously reported rs62185668. The second 20p12.2 signal is more strongly associated with the risk of muscle-invasive (T2-T4 stage) compared with non-muscle-invasive (Ta, T1 stage) bladder cancer (case-case P </= 0.02 for both rs62185668 and rs6108803). Functional analyses are needed to explore the biological mechanisms underlying these novel genetic associations with risk for bladder cancer

Identification of a novel susceptibility locus at 13q34 and refinement of the 20p12.2 region as a multi-signal locus associated with bladder cancer risk in individuals of european ancestry

Candidate gene and genome-wide association studies (GWAS) have identified 15 independent genomic regions associated with bladder cancer risk. In search for additional susceptibility variants, we followed up on four promising single-nucleotide polymorphisms (SNPs) that had not achieved genome-wide significance in 6911 cases and 11 814 controls (rs6104690, rs4510656, rs5003154 and rs4907479, P &lt; 1 7 10(-6)), using additional data from existing GWAS datasets and targeted genotyping for studies that did not have GWAS data. In a combined analysis, which included data on up to 15 058 cases and 286 270 controls, two SNPs achieved genome-wide statistical significance: rs6104690 in a gene desert at 20p12.2 (P = 2.19 7 10(-11)) and rs4907479 within the MCF2L gene at 13q34 (P = 3.3 7 10(-10)). Imputation and fine-mapping analyses were performed in these two regions for a subset of 5551 bladder cancer cases and 10 242 controls. Analyses at the 13q34 region suggest a single signal marked by rs4907479. In contrast, we detected two signals in the 20p12.2 region-the first signal is marked by rs6104690, and the second signal is marked by two moderately correlated SNPs (r(2) = 0.53), rs6108803 and the previously reported rs62185668. The second 20p12.2 signal is more strongly associated with the risk of muscle-invasive (T2-T4 stage) compared with non-muscle-invasive (Ta, T1 stage) bladder cancer (case-case P 64 0.02 for both rs62185668 and rs6108803). Functional analyses are needed to explore the biological mechanisms underlying these novel genetic associations with risk for bladder cancer

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.Peer reviewe

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

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Correction: vol 7, 13205, 2016, doi:10.1038/ncomms13205Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in Bone-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2) = 0.18, P value = 0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.Peer reviewe

Adsorption and Reaction of Acetaldehyde on Shape-Controlled CeO₂ Nanocrystals: Elucidation of Structure–Function Relationships

CeO₂ cubes with {100} facets, octahedra with {111} facets, and wires with highly defective structures were utilized to probe the structure-dependent reactivity of acetaldehyde. Using temperature-programmed desorption (TPD), temperature-programmed surface reactions (TPSR), and <i>in situ</i> infrared spectroscopy, it was determined that acetaldehyde desorbs unreacted or undergoes reduction, coupling, or C–C bond scission reactions, depending on the surface structure of CeO₂. Room-temperature FTIR indicates that acetaldehyde binds primarily as η¹-acetaldehyde on the octahedra, in a variety of conformations on the cubes, including coupling products and acetate and enolate species, and primarily as coupling products on the wires. The percent consumption of acetaldehyde ranks in the following order: wires > cubes > octahedra. All the nanoshapes produce the coupling product crotonaldehyde; however, the selectivity to produce ethanol ranks in the following order: wires ≈ cubes ≫ octahedra. The selectivity and other differences can be attributed to the variation in the basicity of the surfaces, defects densities, coordination numbers of surface atoms, and the reducibility of the nanoshapes