Jennifer J. Ware

A manifesto for reproducible science

Improving the reliability and efficiency of scientific research will increase the credibility of the published scientific literature and accelerate discovery. Here we argue for the adoption of measures to optimize key elements of the scientific process: methods, reporting and dissemination, reproducibility, evaluation and incentives. There is some evidence from both simulations and empirical studies supporting the likely effectiveness of these measures, but their broad adoption by researchers, institutions, funders and journals will require iterative evaluation and improvement. We discuss the goals of these measures, and how they can be implemented, in the hope that this will facilitate action toward improving the transparency, reproducibility and efficiency of scientific research.

Association of the CHRNA5-A3-B4 Gene Cluster With Heaviness of Smoking: A Meta-Analysis

Introduction: Variation in the CHRNA5-A3-B4 gene cluster is a promising candidate region for smoking behavior and has been linked to multiple smoking-related phenotypes (e.g., nicotine dependence) and diseases (e.g., lung cancer). Two single nucleotide polymorphisms (SNPs), rs16969968 in CHRNA5 and rs1051730 in CHRNA3, have generated particular interest. Methods: We evaluated the published evidence for association between rs16969968 (k = 27 samples) and rs1051730 (k = 44 samples) SNPs with heaviness of smoking using meta-analytic techniques. We explored which SNP provided a stronger genetic signal and investigated study-level characteristics (i.e., ancestry, disease state) to establish whether the strength of association differed across populations. We additionally tested for small study bias and explored the impact of year of publication. Results and Conclusions: Meta-analysis indicated compelling evidence of an association between the rs1051730/rs16966968 variants and daily cigarette consumption (fixed effects: B = 0.91, 95% CI = 0.77, 1.06, p < .001; random effects: B = 1.01, 95% CI = 0.81, 1.22, p < .001), equivalent to a per-allele effect of approximately 1 cigarette/day. SNP rs1051730 was found to provide a stronger signal than rs16966968 in stratified analyses (pdiff = .028), although this difference was only qualitatively observed in the subset of samples that provided data on both SNPs. While the functional relevance of rs1051730 is unknown, it may be a strong tagging SNP for functional haplotypes in this region.

Potential Reporting Bias in fMRI Studies of the Brain

Background Functional magnetic resonance imaging (fMRI) studies have reported multiple activation foci associated with a variety of conditions, stimuli or tasks. However, most of these studies used fewer than 40 participants. Methodology After extracting data (number of subjects, condition studied, number of foci identified and threshold) from 94 brain fMRI meta-analyses (k = 1,788 unique datasets) published through December of 2011, we analyzed the correlation between individual study sample sizes and number of significant foci reported. We also performed an analysis where we evaluated each meta-analysis to test whether there was a correlation between the sample size of the meta-analysis and the number of foci that it had identified. Correlation coefficients were then combined across all meta-analyses to obtain a summary correlation coefficient with a fixed effects model and we combine correlation coefficients, using a Fisher’s z transformation. Principal Findings There was no correlation between sample size and the number of foci reported in single studies (r = 0.0050) but there was a strong correlation between sample size and number of foci in meta-analyses (r = 0.62, p<0.001). Only studies with sample sizes <45 identified larger (>40) numbers of foci and claimed as many discovered foci as studies with sample sizes ≥45, whereas meta-analyses yielded a limited number of foci relative to the yield that would be anticipated from smaller single studies. Conclusions These results are consistent with possible reporting biases affecting small fMRI studies and suggest the need to promote standardized large-scale evidence in this field. It may also be that small studies may be analyzed and reported in ways that may generate a larger number of claimed foci or that small fMRI studies with inconclusive, null, or not very promising results may not be published at all.

Mendelian randomization in health research: Using appropriate genetic variants and avoiding biased estimates

Highlights • We model potential biases that may arise in Mendelian randomization analysis.• Genetic variants should robustly associate with exposures in independent samples.• If not, Mendelian randomization can suggest causality despite no true associations.

From men to mice: CHRNA5/CHRNA3, smoking behavior and disease.

Introduction: The nicotinic acetylcholine receptor (nAChR) gene cluster CHRNA5-A3-B4 on chromosome 15 has been the subject of a considerable body of research over recent years. Two highly correlated single nucleotide polymorphisms (SNPs) within this region—rs16969968 in CHRNA5 and rs1051730 in CHRNA3—have generated particular interest. Methods: We reviewed the literature relating to SNPs rs16969968 and rs1051730 and smoking-related phenotypes, and clinical and preclinical studies, which shed light on the mechanisms underlying these associations. Results: Following the initial discovery of an association between this locus and smoking behavior, further associations with numerous phenotypes have been subsequently identified, including smoking-related behaviors, diseases, and cognitive phenotypes. Potential mechanisms thought to underlie these have also been described, as well as possible gene × environment interaction effects. Conclusions: Perhaps counter to the usual route of scientific inquiry, these initial findings, based exclusively on human samples and strengthened by their identification through agnostic genome-wide methods, have led to preclinical research focused on determining the mechanism underlying these associations. Progress has been made using knockout mouse models, highlighting the importance of α5 nAChR subunits in regulating nicotine intake, particularly those localized to the habenula–interpeduncular nucleus pathway. Translational research seeking to evaluate the effect of nicotine challenge on brain activation as a function of rs16969968 genotype using neuroimaging technologies is now called for, which may point to new targets for novel smoking cessation therapies.

Separating neural and vascular effects of caffeine using simultaneous EEG–FMRI: Differential effects of caffeine on cognitive and sensorimotor brain responses

The effects of caffeine are mediated through its non-selective antagonistic effects on adenosine A(1) and A(2A) adenosine receptors resulting in increased neuronal activity but also vasoconstriction in the brain. Caffeine, therefore, can modify BOLD FMRI signal responses through both its neural and its vascular effects depending on receptor distributions in different brain regions. In this study we aim to distinguish neural and vascular influences of a single dose of caffeine in measurements of task-related brain activity using simultaneous EEG-FMRI. We chose to compare low-level visual and motor (paced finger tapping) tasks with a cognitive (auditory oddball) task, with the expectation that caffeine would differentially affect brain responses in relation to these tasks. To avoid the influence of chronic caffeine intake, we examined the effect of 250 mg of oral caffeine on 14 non and infrequent caffeine consumers in a double-blind placebo-controlled cross-over study. Our results show that the task-related BOLD signal change in visual and primary motor cortex was significantly reduced by caffeine, while the amplitude and latency of visual evoked potentials over occipital cortex remained unaltered. However, during the auditory oddball task (target versus non-target stimuli) caffeine significantly increased the BOLD signal in frontal cortex. Correspondingly, there was also a significant effect of caffeine in reducing the target evoked response potential (P300) latency in the oddball task and this was associated with a positive potential over frontal cortex. Behavioural data showed that caffeine also improved performance in the oddball task with a significantly reduced number of missed responses. Our results are consistent with earlier studies demonstrating altered flow-metabolism coupling after caffeine administration in the context of our observation of a generalised caffeine-induced reduction in cerebral blood flow demonstrated by arterial spin labelling (19% reduction over grey matter). We were able to identify vascular effects and hence altered neurovascular coupling through the alteration of low-level task FMRI responses in the face of a preserved visual evoked potential. However, our data also suggest a cognitive effect of caffeine through its positive effect on the frontal BOLD signal consistent with the shortening of oddball EEG response latency. The combined use of EEG-FMRI is a promising methodology for investigating alterations in brain function in drug and disease studies where neurovascular coupling may be altered on a regional basis.

Genome-wide association study of lifetime cannabis use based on a large meta-analytic sample of 32 330 subjects from the International Cannabis Consortium

Cannabis is the most widely produced and consumed illicit psychoactive substance worldwide. Occasional cannabis use can progress to frequent use, abuse and dependence with all known adverse physical, psychological and social consequences. Individual differences in cannabis initiation are heritable (40–48%). The International Cannabis Consortium was established with the aim to identify genetic risk variants of cannabis use. We conducted a meta-analysis of genome-wide association data of 13 cohorts (N=32 330) and four replication samples (N=5627). In addition, we performed a gene-based test of association, estimated single-nucleotide polymorphism (SNP)-based heritability and explored the genetic correlation between lifetime cannabis use and cigarette use using LD score regression. No individual SNPs reached genome-wide significance. Nonetheless, gene-based tests identified four genes significantly associated with lifetime cannabis use: NCAM1, CADM2, SCOC and KCNT2. Previous studies reported associations of NCAM1 with cigarette smoking and other substance use, and those of CADM2 with body mass index, processing speed and autism disorders, which are phenotypes previously reported to be associated with cannabis use. Furthermore, we showed that, combined across the genome, all common SNPs explained 13–20% (P<0.001) of the liability of lifetime cannabis use. Finally, there was a strong genetic correlation (rg=0.83; P=1.85 × 10−8) between lifetime cannabis use and lifetime cigarette smoking implying that the SNP effect sizes of the two traits are highly correlated. This is the largest meta-analysis of cannabis GWA studies to date, revealing important new insights into the genetic pathways of lifetime cannabis use. Future functional studies should explore the impact of the identified genes on the biological mechanisms of cannabis use.

G = E: What GWAS Can Tell Us about the Environment

As our understanding of genetics has improved, genome-wide association studies (GWAS) have identified numerous variants associated with lifestyle behaviours and health outcomes. However, what is sometimes overlooked is the possibility that genetic variants identified in GWAS of disease might reflect the effect of modifiable risk factors as well as direct genetic effects. We discuss this possibility with illustrative examples from tobacco and alcohol research, in which genetic variants that predict behavioural phenotypes have been seen in GWAS of diseases known to be causally related to these behaviours. This consideration has implications for the interpretation of GWAS findings.

Genetic Relationship between Schizophrenia and Nicotine Dependence

It is well known that most schizophrenia patients smoke cigarettes. There are different hypotheses postulating the underlying mechanisms of this comorbidity. We used summary statistics from large meta-analyses of plasma cotinine concentration (COT), Fagerström test for nicotine dependence (FTND) and schizophrenia to examine the genetic relationship between these traits. We found that schizophrenia risk scores calculated at P-value thresholds of 5 × 10−3 and larger predicted FTND and cigarettes smoked per day (CPD), suggesting that genes most significantly associated with schizophrenia were not associated with FTND/CPD, consistent with the self-medication hypothesis. The COT risk scores predicted schizophrenia diagnosis at P-values of 5 × 10−3 and smaller, implying that genes most significantly associated with COT were associated with schizophrenia. These results implicated that schizophrenia and FTND/CPD/COT shared some genetic liability. Based on this shared liability, we identified multiple long non-coding RNAs and RNA binding protein genes (DA376252, BX089737, LOC101927273, LINC01029, LOC101928622, HY157071, DA902558, RBFOX1 and TINCR), protein modification genes (MANBA, UBE2D3, and RANGAP1) and energy production genes (XYLB, MTRF1 and ENOX1) that were associated with both conditions. Further analyses revealed that these shared genes were enriched in calcium signaling, long-term potentiation and neuroactive ligand-receptor interaction pathways that played a critical role in cognitive functions and neuronal plasticity.

Associations between smoking and caffeine consumption in two European cohorts

Abstract Aims To estimate associations between smoking initiation, smoking persistence and smoking heaviness and caffeine consumption in two population‐based samples from the Netherlands and the United Kingdom. Design Observational study employing data on self‐reported smoking behaviour and caffeine consumption. Setting Adults from the general population in the Netherlands and the United Kingdom. Participants Participants from the Netherlands Twin Register [NTR: n = 21 939, mean age 40.8, standard deviation (SD) = 16.9, 62.6% female] and the Avon Longitudinal Study of Parents and Children (ALSPAC: n = 9086, mean age 33.2, SD = 4.7, 100% female). Measurements Smoking initiation (ever versus never smoking), smoking persistence (current versus former smoking), smoking heaviness (number of cigarettes smoked) and caffeine consumption in mg per day through coffee, tea, cola and energy drinks. Findings After correction for age, gender (NTR), education and social class (ALSPAC), smoking initiation was associated with consuming on average 52.8 [95% confidence interval (CI) = 45.6–60.0; NTR] and 59.5 (95% CI = 51.8–67.2; ALSPAC) mg more caffeine per day. Smoking persistence was also associated with consuming more caffeine [+57.9 (95% CI = 45.2–70.5) and +83.2 (95% CI = 70.2–96.3) mg, respectively]. Each additional cigarette smoked per day was associated with 3.7 (95% CI = 1.9–5.5; NTR) and 8.4 (95% CI = 6.9–10.0; ALSPAC) mg higher daily caffeine consumption in current smokers. Smoking was associated positively with coffee consumption and less strongly with cola and energy drinks. For tea, associations were positive in ALSPAC and negative in NTR. Conclusions There appears to be a positive association between smoking and caffeine consumption in the Netherlands and the United Kingdom.