Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been... Show moreSmoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations withP < 5 x 10(-8)in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 x 10(-8)) in the discovery samples. Ten novel SNVs, including rs12616219 nearTMEM182, were followed-up and five of them (rs462779 inREV3L, rs12780116 inCNNM2, rs1190736 inGPR101, rs11539157 inPJA1, and rs12616219 nearTMEM182) replicated at a Bonferroni significance threshold (P < 4.5 x 10(-3)) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, inCCDC141and two low-frequency SNVs inCEP350andHDGFRP2. Functional follow-up implied that decreased expression ofREV3Lmay lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation. Show less
The chemical composition and properties of environmental media determine nanomaterial (NM) transport, fate, biouptake, and organism response. To compare and interpret experimental data, it is... Show moreThe chemical composition and properties of environmental media determine nanomaterial (NM) transport, fate, biouptake, and organism response. To compare and interpret experimental data, it is essential that sufficient context be provided for describing the physical and chemical characteristics of the setting in which a nanomaterial may be present. While the nanomaterial environmental, health and safety (NanoEHS) field has begun harmonization to allow data comparison and re-use (e.g. using standardized materials, defining a minimum set of required material characterizations), there is limited guidance for standardizing test media. Since most of the NM properties driving environmental behaviour and toxicity are medium-dependent, harmonization of media is critical. A workshop in March 2016 at Duke University identified five categories of test media: aquatic testing media, soil and sediment testing media, biological testing media, engineered systems testing media and product matrix testing media. For each category of test media, a minimum set of medium characteristics to report in all NM tests is recommended. Definitions and detail level of the recommendations for specific standardized media vary across these media categories. This reflects the variation in the maturity of their use as a test medium and associated measurement techniques, variation in utility and relevance of standardizing medium properties, ability to simplify standardizing reporting requirements, and in the availability of established standard reference media. Adoption of these media harmonization recommendations will facilitate the generation of integrated comparable datasets on NM fate and effects. This will in turn allow testing of the predictive utility of functional assay measurements on NMs in relevant media, support investigation of first principles approaches to understand behavioral mechanisms, and support categorization strategies to guide research, commercial development, and policy. Show less
