Biology subjects

Munafo, M. R.

Publications and source records attributed to Munafo, M. R..

28 records · Page 2Linked to original sources

bioRxiv2018

Evidence for genetic correlations and bidirectional, causal effects between smoking and sleep behaviours

IntroductionCigarette smokers are at increased risk of poor sleep behaviours. However, it is largely unknown whether these associations are due to shared (genetic) risk factors and/or causal effects (which may be bi-directional).\n\nMethodsWe obtained summary-level data of genome-wide association studies of smoking (smoking initiation (n=74,035), cigarettes per day (n=38,181) and smoking cessation (n=41,278)) and sleep behaviours (sleep duration and chronotype, or morningness) (n=128,266) and insomnia (n=113,006)). Using LD score regression, we calculated genetic correlations between smoking and sleep behaviours. To investigate causal effects, we employed Mendelian randomization (MR), both with summary-level data and individual level data (n=333,581 UK Biobank participants). For MR with summary-level data, individual genetic variants were combined with inverse-variance weighted meta-analysis, weighted median regression and MR Egger regression methods.\n\nResultsWe found positive genetic correlations between insomnia and smoking initiation (rg=0.27, 95% CI 0.06 to 0.49) and insomnia and cigarettes per day (rg=0.15, 0.01 to 0.28), and negative genetic correlations between sleep duration and smoking initiation (rg=-0.14, -0.26 to -0.01) and chronotype and smoking cessation (rg=-0.18, -0.31 to -0.06). MR analyses provided strong evidence that smoking more cigarettes per day causally decreases the odds of being a morning person, and weak evidence that insomnia causally increases smoking heaviness and decreases smoking cessation odds.\n\nConclusionsSmoking and sleep behaviours show moderate genetic correlation. Heavier smoking seems to causally affect circadian rhythm and there is some indication that insomnia increases smoking heaviness and hampers cessation. Our findings point to sleep as a potentially interesting smoking treatment target.

genetics↗

bioRxiv2018

Cigarette smoking and personality: Investigating causality using Mendelian randomization

BackgroundDespite the well-documented association between smoking and personality traits such as neuroticism and extraversion, little is known about the potential causal nature of these findings. If it were possible to unpick the association between personality and smoking, it may be possible to develop more targeted smoking cessation programmes that could lead to both improved uptake and efficacy.\n\nMethodsRecent genome-wide association studies (GWAS) have identified variants robustly associated with both smoking phenotypes and personality traits. Here we use publicly available GWAS summary statistics in addition to data from UK Biobank to investigate the link between smoking and personality. We first estimated genetic overlap between traits using LD score regression and then applied both one- and two-sample Mendelian randomization methods to unpick the nature of this relationship.\n\nResultsWe found clear evidence of a modest genetic correlation between smoking behaviours and both neuroticism and extraversion, suggesting shared genetic aetiology. We found some evidence to suggest an association between neuroticism and increased smoking initiation. We also found some evidence that personality traits appear to be causally linked to certain smoking phenotypes: higher neuroticism and heavier cigarette consumption, and higher extraversion and increased odds of smoking initiation. The latter finding could lead to more targeted smoking prevention programmes.\n\nConclusionThe association between neuroticism and cigarette consumption lends support to the self-medication hypothesis, while the association between extraversion and smoking initiation could lead to more targeted smoking prevention programmes.

epidemiology↗

bioRxiv2017

Conditioning on a collider may induce spurious associations: Do the results of Gale et al. (2017) support a protective effect of neuroticism in population sub-groups?

Introduction Introduction Methods Results Discussion References Gale and colleagues (Gale et al., 2017) examined the association between neuroticism and mortality in a large sample (N > 300,000) drawn from the UK Biobank study (Sudlow et al., 2015). They observed that neuroticism was associated with an increase in all-cause mortality, but that following adjustment for self-rated health neuroticism was associated with a reduction in all-cause mortality. Further analyses stratified on self-rated health suggested that higher neuroticism was associated with reduced mortality only among those with fair or poor self-rated health. The authors conclude that neuroticism may have protective effects among certain sub-groups, and finding that generated substantial interest (TIME, 2017).\n\nThe availability ...

epidemiology↗

bioRxiv2017

A systematic review of sample size and power in leading neuroscience journals

Adequate sample size is key to reproducible research findings: low statistical power can increase the probability that a statistically significant result is a false positive. Journals are increasingly adopting methods to tackle issues of reproducibility, such as by introducing reporting checklists. We conducted a systematic review comparing articles submitted to Nature Neuroscience in the 3 months prior to checklists (n=36) that were subsequently published with articles submitted to Nature Neuroscience in the 3 months immediately after checklists (n=45), along with a comparison journal Neuroscience in this same 3-month period (n=123). We found that although the proportion of studies commenting on sample sizes increased after checklists (22% vs 53%), the proportion reporting formal power calculations decreased (14% vs 9%). Using sample size calculations for 80% power and a significance level of 5%, we found little evidence that sample sizes were adequate to achieve this level of statistical power, even for large effect sizes. Our analysis suggests that reporting checklists may not improve the use and reporting of formal power calculations.

scientific communication and education↗

bioRxiv2017

The molecular genetics of participation in the Avon Longitudinal Study of Parents and Children

BackgroundIt is often assumed that selection (including participation and dropout) does not represent an important source of bias in genetic studies. However, there is little evidence to date on the effect of genetic factors on participation.\n\nMethodsUsing data on mothers (N=7,486) and children (N=7,508) from the Avon Longitudinal Study of Parents and Children, we 1) examined the association of polygenic risk scores for a range of socio-demographic, lifestyle characteristics and health conditions related to continued participation, 2) investigated whether associations of polygenic scores with body mass index (BMI; derived from self-reported weight and height) and self-reported smoking differed in the largest sample with genetic data and a sub-sample who participated in a recent follow-up and 3) determined the proportion of variation in participation explained by common genetic variants using genome-wide data.\n\nResultsWe found evidence that polygenic scores for higher education, agreeableness and openness were associated with higher participation and polygenic scores for smoking initiation, higher BMI, neuroticism, schizophrenia, ADHD and depression were associated with lower participation. Associations between the polygenic score for education and self-reported smoking differed between the largest sample with genetic data (OR for ever smoking per SD increase in polygenic score:0.85, 95% CI:0.81,0.89) and sub-sample (OR:0.95, 95% CI:0.88,1.02). In genome-wide analysis, single nucleotide polymorphism based heritability explained 17-31% of variability in participation.\n\nConclusionsGenetic association studies, including Mendelian randomization, can be biased by selection, including loss to follow-up. Genetic risk for dropout should be considered in all analyses of studies with selective participation.

genetics↗

bioRxiv2017

Investigating genetic correlations and causal effects between caffeine consumption and sleep behaviours

Study Objectives: Higher caffeine consumption has been linked to poorer sleep and insomnia complaints. We investigated whether these observational associations are the result of genetic risk factors influencing both caffeine consumption and poorer sleep, and/or whether they reflect (possibly bidirectional) causal effects. Methods: Summary-level data were available from genome-wide association studies (GWAS) on caffeine consumption (n=91,462), sleep duration, and chronotype (i.e., being a morning versus an evening person) (both n=128,266), and insomnia complaints (n=113,006). Linkage disequilibrium (LD) score regression was used to calculate genetic correlations, reflecting the extent to which genetic variants influencing caffeine consumption and sleep behaviours overlap. Causal effects were tested with bidirectional, two-sample Mendelian randomization (MR), an instrumental variable approach that utilizes genetic variants robustly associated with an exposure variable as an instrument to test causal effects. Estimates from individual genetic variants were combined using inverse-variance weighted meta-analysis, weighted median regression and MR Egger regression methods. Results: There was no clear evidence for genetic correlation between caffeine consumption and sleep duration (rg=0.000, p=0.998), chronotype (rg=0.086, p=0.192) or insomnia (rg=-0.034, p=0.700). Two-sample Mendelian randomization analyses did not support causal effects from caffeine consumption to sleep behaviours, or the other way around. Conclusions: We found no evidence in support of genetic correlation or causal effects between caffeine consumption and sleep. While caffeine may have acute effects on sleep when taken shortly before habitual bedtime, our findings suggest that a more sustained pattern of high caffeine consumption is likely associated with poorer sleep through shared environmental factors.

genetics↗

bioRxiv2017

Investigating causality in associations between education and smoking: A two-sample Mendelian randomization study

BackgroundLower educational attainment is associated with increased rates of smoking, but ascertaining causality is challenging. We used two-sample Mendelian randomization (MR) analyses of summary statistics to examine whether educational attainment is causally related to smoking.\n\nMethods and FindingsWe used summary statistics from genome-wide association studies of educational attainment and a range of smoking phenotypes (smoking initiation, cigarettes per day, cotinine levels and smoking cessation). Various complementary MR techniques (inverse-variance weighted regression, MR Egger, weighted-median regression) were used to test the robustness of our results. We found broadly consistent evidence across these techniques that higher educational attainment leads to reduced likelihood of smoking initiation, reduced heaviness of smoking among smokers (as measured via self-report and cotinine levels), and greater likelihood of smoking cessation among smokers.\n\nConclusionsOur findings indicate a causal association between low educational attainment and increased risk of smoking, and may explain the observational associations between educational attainment and adverse health outcomes such as risk of coronary heart disease.

epidemiology↗

bioRxiv2017

What exactly is ‘N’ in cell culture and animal experiments?

Biologists establish the existence of experimental effects by applying treatments or interventions to biological entities or units, such as people, animals, slice preparations, or cells. When done appropriately, independent replication of the entity-intervention pair contributes to the sample size (N) and forms the basis of statistical inference. However, sometimes the appropriate entity-intervention pair may not be obvious, and the wrong choice can make an experiment worthless. We surveyed a random sample of published animal experiments from 2011 to 2016 where interventions were applied to parents but effects examined in the offspring, as regulatory authorities have provided clear guidelines on replication with such designs. We found that only 22% of studies (95% CI = 17% to 29%) replicated the correct entity-intervention pair and thus made valid statistical inferences. Approximately half of the studies (46%, 95% CI = 38% to 53%) had pseudoreplication while 32% (95% CI = 26% to 39%) provided insufficient information to make a judgement. Pseudoreplication artificially inflates the sample size, leading to more false positive results and inflating the apparent evidence supporting a scientific claim. It is hard for science to advance when so many experiments are poorly designed and analysed. We argue that distinguishing between biological units, experimental units, and observational units clarifies where replication should occur, describe the criteria for genuine replication, and provide guidelines for designing and analysing in vitro, ex vivo, and in vivo experiments.

neuroscience↗

bioRxiv2017

Cigarette smoking increases coffee consumption: findings from a Mendelian randomisation analysis

BackgroundSmokers tend to consume more coffee than non-smokers and there is evidence for a positive relationship between cigarette and coffee consumption in smokers. Cigarette smoke increases the metabolism of caffeine, so this association may represent a causal effect of smoking on caffeine intake.\n\nMethodsWe performed a Mendelian randomisation analysis in 114,029 individuals from the UK Biobank, 56,664 from the Norwegian HUNT study and 78,650 from the Copenhagen General Population Study. We used a genetic variant in the CHRNA5 nicotinic receptor (rs16969968) as a proxy for smoking heaviness. Coffee and tea consumption were self-reported. Analyses were conducted using linear regression and meta-analysed across studies.\n\nResultsEach additional cigarette per day consumed by current smokers was associated with higher coffee consumption (0.10 cups per day, 95% CI:0.03,0.17). There was weak evidence for an increase in tea consumption per additional cigarette smoked per day (0.04 cups per day, 95% CI:-0.002,0.07). There was strong evidence that each additional copy of the minor allele of rs16969968 (which increases daily cigarette consumption) in current smokers was associated with higher coffee consumption (0.15 cups per day, 95% CI:0.11,0.20), but only weak evidence for an association with tea consumption (0.04 cups per day, 95% CI:- 0.01,0.09). There was no clear evidence that rs16969968 was associated with coffee or tea consumption in never or former smokers.\n\nConclusionThese findings suggest that higher cigarette consumption causally increases coffee intake. This is consistent with faster metabolism of caffeine by smokers, but may also reflect behavioural links between smoking and coffee.

genetics↗

bioRxiv2016

Associations of coffee genetic risk scores with coffee, tea and other beverages in the UK Biobank

BackgroundGenetic variants which determine amount of coffee consumed have been identified in genome-wide association studies (GWAS) of coffee consumption; these may help to further understanding of the effects of coffee on health outcomes. However, there is limited information about how these variants relate to caffeinated beverage consumption more generally.\n\nAimsTo improve phenotype definition for coffee consumption related genetic risk scores by testing their association with coffee, tea and other beverages.\n\nMethodsWe tested the associations of genetic risk scores for coffee consumption with beverage consumption in 114,316 individuals of European ancestry from the UK Biobank. Drinks were self-reported in a baseline questionnaire and in detailed 24 dietary recall questionnaires in a subset.\n\nResultsGenetic risk scores including two and eight single nucleotide polymorphisms (SNPs) explained up to 0.39%, 0.19% and 0.77% of the variance in coffee, tea and combined coffee and tea consumption respectively. A one standard deviation increase in the 8 SNP genetic risk score was associated with a 0.13 cup per day (95% CI: 0.12, 0.14), 0.12 cup per day (95%CI: 0.11, 0.14) and 0.25 cup per day (95% CI: 0.24, 0.27) increase in coffee, tea and combined tea and coffee consumption, respectively. Genetic risk scores also demonstrated positive associations with both caffeinated and decaffeinated coffee and tea consumption. In 48,692 individuals with dietary recall data, the genetic risk scores were positively associated with coffee and tea, (apart from herbal teas) consumption, but did not show clear evidence for positive associations with other beverages. However, there was evidence that the genetic risk scores were associated with lower daily water consumption and lower overall drink consumption.\n\nConclusionsGenetic risk scores created from variants identified in coffee consumption GWAS associate more broadly with caffeinated beverage consumption and also with decaffeinated coffee and tea consumption.

genetics↗