Drax, K. | bioRxiv Science

bioRxiv2019

Exploration of the role of CHRNA5-A3-B4 genotype in smoking behaviours

Genome-wide association studies have identified associations between variation at rs16969968/rs1051730 in the CHRNA5-A3-B4 gene cluster and smoking related outcomes. Experiments in rodents have described the nicotinic acetylcholine receptors (nAChRs) subunits encoded by this gene cluster and showed a lack of nicotine aversion in nAChRs deficient animal models. We conducted a nicotine challenge and a smoking topography study in humans, hypothesising that: 1. responses to a nicotine challenge would differ according to the rs16969968/rs1051730 genotype and 2. genotype may influence nicotine intake via smoking topography.\n\nWe used linear regressions to examine associations between rs16969968/rs1051730 genotype and subjective (questionnaires) and objective (physiological parameters) responses following acute nicotine exposure in never smokers (hypothesis 1) or cigarette smoking in current smokers (hypothesis 2). There was evidence to suggest nicotine exposure increases blood pressure and heart rate, and negatively affects mood, but insufficient evidence that these effects differ by genotype. Carriers of the minor allele following smoking one cigarette, exhibited reduced cravings (b=-2.46, 95% CI -4.87 to - 0.06, p=0.04) and inhaled less smoke per cigarette (b=-0.24, 95% CI - 0.43 to - 0.06, p=0.01) and per puff (b=-0.18, 95% CI -0.32 to -0.01, p=0.02). These results suggest that we need to carefully consider the translational value of the findings of aversion behaviour in nAChRs rodent models, and that deeper inhalation does not explain the strong association between rs16969968/rs1051730 genotype and objective biomarkers of tobacco exposure.

neuroscience↗

bioRxiv2019

Is useful research data usually shared? An investigation of genome-wide association study summary statistics

Primary data collected during a research study is increasingly shared and may be re-used for new studies. To assess the extent of data sharing in favourable circumstances and whether such checks can be automated, this article investigates the summary statistics of primary human genome-wide association studies (GWAS). This type of data is highly suitable for sharing because it is a standard research output, is straightforward to use in future studies (e.g., for secondary analysis), and may be already stored in a standard format for internal sharing within multi-site research projects. Manual checks of 1799 articles from 2010 and 2017 matching a simple PubMed query for molecular epidemiology GWAS were used to identify 330 primary human GWAS papers. Of these, only 10.6% reported the location of a complete set of GWAS summary data, increasing from 4.3% in 2010 to 16.8% in 2017. Whilst information about whether data was shared was usually located clearly within a data availability statement, the exact nature of the shared data was usually unspecified. Thus, data sharing is the exception even in suitable research fields with relatively strong norms regarding data sharing. Moreover, the lack of clear data descriptions within data sharing statements greatly complicates the task of automatically characterising shared data sets.

scientific communication and education↗