Estimating the health impact of nicotine exposure by dissecting the effects of nicotine versus non-nicotine constituents of tobacco smoke: A multivariable Mendelian randomisation study.

The detrimental health effects of smoking are well-known, but the impact of regular nicotine use without exposure to the other constituents of tobacco is less clear. Given the increasing daily use of alternative nicotine delivery systems, such as e-cigarettes, it is increasingly important to understand and separate the effects of nicotine use from the impact of tobacco smoke exposure. Using a multivariable Mendelian randomisation framework, we explored the direct effects of nicotine compared with the non-nicotine constituents of tobacco smoke on health outcomes (lung cancer, chronic obstructive pulmonary disease [COPD], forced expiratory volume in one second [FEV-1], forced vital capacity [FVC], coronary heart disease [CHD], and heart rate [HR]). We used Genome-Wide Association Study (GWAS) summary statistics from Buchwald and colleagues, the GWAS and Sequencing Consortium of Alcohol and Nicotine, the International Lung Cancer Consortium, and UK Biobank. Increased nicotine metabolism increased the risk of COPD, lung cancer, and lung function in the univariable analysis. However, when accounting for smoking heaviness in the multivariable analysis, we found that increased nicotine metabolite ratio (indicative of decreased nicotine exposure per cigarette smoked) decreases heart rate (b = -0.30, 95% CI -0.50 to -0.10) and lung function (b = -33.33, 95% CI -41.76 to -24.90). There was no clear evidence of an effect on the remaining outcomes. The results suggest that these smoking-related outcomes are not due to nicotine exposure but are caused by the other components of tobacco smoke; however, there are multiple potential sources of bias, and the results should be triangulated using evidence from a range of methodologies.

Testing the causal relationships of physical activity and sedentary behaviour with mental health and substance use disorders: a Mendelian randomisation study.

Observational studies suggest that physical activity can reduce the risk of mental health and substance use disorders. However, it is unclear whether this relationship is causal or explained by confounding bias (e.g., common underlying causes or reverse causality). We investigated the bidirectional causal relationship of physical activity (PA) and sedentary behaviour (SB) with ten mental health and substance use disorders, applying two-sample Mendelian Randomisation (MR). Genetic instruments for the exposures and outcomes were derived from the largest available, non-overlapping genome-wide association studies (GWAS). Summary-level data for objectively assessed PA (accelerometer-based average activity, moderate activity, and walking) and SB and self-reported moderate-to-vigorous PA were obtained from the UK Biobank. Data for mental health/substance use disorders were obtained from the Psychiatric Genomics Consortium and the GWAS and Sequencing Consortium of Alcohol and Nicotine Use. MR estimates were combined using inverse variance weighted meta-analysis (IVW). Sensitivity analyses were conducted to assess the robustness of the results. Accelerometer-based average PA was associated with a lower risk of depression (b = -0.043, 95% CI: -0.071 to -0.016, effect size[OR] = 0.957) and cigarette smoking (b = -0.026; 95% CI: -0.035 to -0.017, effect size[ß] = -0.022). Accelerometer-based SB decreased the risk of anorexia (b = -0.341, 95% CI: -0.530 to -0.152, effect size[OR] = 0.711) and schizophrenia (b = -0.230; 95% CI: -0.285 to -0.175, effect size[OR] = 0.795). However, we found evidence of reverse causality in the relationship between SB and schizophrenia. Further, PTSD, bipolar disorder, anorexia, and ADHD were all associated with increased PA. This study provides evidence consistent with a causal protective effect of objectively assessed but not self-reported PA on reduced depression and cigarette smoking. Objectively assessed SB had a protective relationship with anorexia. Enhancing PA may be an effective intervention strategy to reduce depressive symptoms and addictive behaviours, while promoting sedentary or light physical activities may help to reduce the risk of anorexia in at-risk individuals.

Epigenetic Regulation of F2RL3 Associates With Myocardial Infarction and Platelet Function.

BACKGROUND: DNA hypomethylation at the F2RL3 (F2R like thrombin or trypsin receptor 3) locus has been associated with both smoking and atherosclerotic cardiovascular disease; whether these smoking-related associations form a pathway to disease is unknown. F2RL3 encodes protease-activated receptor 4, a potent thrombin receptor expressed on platelets. Given the role of thrombin in platelet activation and the role of thrombus formation in myocardial infarction, alterations to this biological pathway could be important for ischemic cardiovascular disease. METHODS: We conducted multiple independent experiments to assess whether DNA hypomethylation at F2RL3 in response to smoking is associated with risk of myocardial infarction via changes to platelet reactivity. Using cohort data (N=3205), we explored the relationship between smoking, DNA hypomethylation at F2RL3, and myocardial infarction. We compared platelet reactivity in individuals with low versus high DNA methylation at F2RL3 (N=41). We used an in vitro model to explore the biological response of F2RL3 to cigarette smoke extract. Finally, a series of reporter constructs were used to investigate how differential methylation could impact F2RL3 gene expression. RESULTS: Observationally, DNA methylation at F2RL3 mediated an estimated 34% of the smoking effect on increased risk of myocardial infarction. An association between methylation group (low/high) and platelet reactivity was observed in response to PAR4 (protease-activated receptor 4) stimulation. In cells, cigarette smoke extract exposure was associated with a 4.9% to 9.3% reduction in DNA methylation at F2RL3 and a corresponding 1.7-(95% CI, 1.2-2.4, P=0.04) fold increase in F2RL3 mRNA. Results from reporter assays suggest the exon 2 region of F2RL3 may help control gene expression. CONCLUSIONS: Smoking-induced epigenetic DNA hypomethylation at F2RL3 appears to increase PAR4 expression with potential downstream consequences for platelet reactivity. Combined evidence here not only identifies F2RL3 DNA methylation as a possible contributory pathway from smoking to cardiovascular disease risk but from any feature potentially influencing F2RL3 regulation in a similar manner.

Do Flavour Descriptions Influence Subjective Ratings of Flavoured and Unflavoured E-Liquids among Non-Smoking and Non-Vaping UK Adolescents?

INTRODUCTION: Youth use of electronic cigarettes (e-cigarettes) is rising globally and is associated with health harms. Flavour descriptions on e-liquid packaging may contribute to the appeal of e-cigarettes among youth. This study compared subjective ratings of e-liquid packaging flavour descriptions among non-smoking and non-vaping UK adolescents. METHODS: This was an online observational study in a UK sample of non-smoking and non-vaping adolescents aged 11-17 years. The primary analyses compared flavoured versus unflavoured descriptions and the secondary analyses compared candy/sweet flavour versus fruit flavour descriptions. Outcomes were packaging appraisal, packaging receptivity, perceived harm, and perceived audience. RESULTS: The survey was completed by 120 participants (74% female). Packaging appraisal ratings were higher for e-liquids with flavoured descriptions than unflavoured descriptions (mean difference 5.9, 95% CI 4.2 to 7.6, p<.001). Similarly, packaging receptivity ratings were higher for e-liquids with flavoured descriptions than unflavoured descriptions (mean difference 4.2, 95% CI 2.8 to 5.6, p<.001). Participants also perceived e-liquids with flavoured (versus unflavoured) descriptions as less 'grown-up' (mean difference -5.2, 95% CI -7.3 to -3.1, p<.001). However, ratings of perceived harm were similar for flavoured and unflavoured descriptions (mean difference -1.0, 95% CI -2.6 to 0.5, p=.189). CONCLUSIONS: Although this study found differences in subjective ratings of e-liquids with flavoured and unflavoured descriptions, non-smoking and non-vaping UK adolescents generally had low appraisal and receptivity for e-liquids and they perceived them as being 'grown-up' and harmful. IMPLICATIONS: Youth use of electronic cigarettes (e-cigarettes) is increasing globally, leading to concerns about health harms. This study compared adolescents' ratings of e-liquids with flavoured versus unflavoured descriptions and e-liquids with candy/sweet flavour versus fruit flavour descriptions. This study adds to previous studies that have compared adolescents' ratings of e-liquids with tobacco flavour versus non-tobacco flavour descriptions. Although packaging appraisal and receptivity ratings were higher (more positive) for e-liquids with flavoured versus unflavoured descriptions, overall, adolescents who do not smoke or vape had low appraisal and receptivity for e-liquids, and they perceived them as being 'grown-up' and harmful.

Interventions for smoking cessation in hospitalised patients.

BACKGROUND: In 2020, 32.6% of the world's population used tobacco. Smoking contributes to many illnesses that require hospitalisation. A hospital admission may prompt a quit attempt. Initiating smoking cessation treatment, such as pharmacotherapy and/or counselling, in hospitals may be an effective preventive health strategy. Pharmacotherapies work to reduce withdrawal/craving and counselling provides behavioural skills for quitting smoking. This review updates the evidence on interventions for smoking cessation in hospitalised patients, to understand the most effective smoking cessation treatment methods for hospitalised smokers. OBJECTIVES: To assess the effects of any type of smoking cessation programme for patients admitted to an acute care hospital. SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search date was 7 September 2022. SELECTION CRITERIA: We included randomised and quasi-randomised studies of behavioural, pharmacological or multicomponent interventions to help patients admitted to hospital quit. Interventions had to start in the hospital (including at discharge), and people had to have smoked within the last month. We excluded studies in psychiatric, substance and rehabilitation centres, as well as studies that did not measure abstinence at six months or longer. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our primary outcome was abstinence from smoking assessed at least six months after discharge or the start of the intervention. We used the most rigorous definition of abstinence, preferring biochemically-validated rates where reported. We used GRADE to assess the certainty of the evidence. MAIN RESULTS: We included 82 studies (74 RCTs) that included 42,273 participants in the review (71 studies, 37,237 participants included in the meta-analyses); 36 studies are new to this update. We rated 10 studies as being at low risk of bias overall (low risk in all domains assessed), 48 at high risk of bias overall (high risk in at least one domain), and the remaining 24 at unclear risk. Cessation counselling versus no counselling, grouped by intensity of intervention Hospitalised patients who received smoking cessation counselling that began in the hospital and continued for more than a month after discharge had higher quit rates than patients who received no counselling in the hospital or following hospitalisation (risk ratio (RR) 1.36, 95% confidence interval (CI) 1.24 to 1.49; 28 studies, 8234 participants; high-certainty evidence). In absolute terms, this might account for an additional 76 quitters in every 1000 participants (95% CI 51 to 103). The evidence was uncertain (very low-certainty) about the effects of counselling interventions of less intensity or shorter duration (in-hospital only counselling ≤ 15 minutes: RR 1.52, 95% CI 0.80 to 2.89; 2 studies, 1417 participants; and in-hospital contact plus follow-up counselling support for ≤ 1 month: RR 1.04, 95% CI 0.90 to 1.20; 7 studies, 4627 participants) versus no counselling. There was moderate-certainty evidence, limited by imprecision, that smoking cessation counselling for at least 15 minutes in the hospital without post-discharge support led to higher quit rates than no counselling in the hospital (RR 1.27, 95% CI 1.02 to 1.58; 12 studies, 4432 participants). Pharmacotherapy versus placebo or no pharmacotherapy Nicotine replacement therapy helped more patients to quit than placebo or no pharmacotherapy (RR 1.33, 95% CI 1.05 to 1.67; 8 studies, 3838 participants; high-certainty evidence). In absolute terms, this might equate to an additional 62 quitters per 1000 participants (95% CI 9 to 126). There was moderate-certainty evidence, limited by imprecision (as CI encompassed the possibility of no difference), that varenicline helped more hospitalised patients to quit than placebo or no pharmacotherapy (RR 1.29, 95% CI 0.96 to 1.75; 4 studies, 829 participants). Evidence for bupropion was low-certainty; the point estimate indicated a modest benefit at best, but CIs were wide and incorporated clinically significant harm and clinically significant benefit (RR 1.11, 95% CI 0.86 to 1.43, 4 studies, 872 participants). Hospital-only intervention versus intervention that continues after hospital discharge Patients offered both smoking cessation counselling and pharmacotherapy after discharge had higher quit rates than patients offered counselling in hospital but not offered post-discharge support (RR 1.23, 95% CI 1.09 to 1.38; 7 studies, 5610 participants; high-certainty evidence). In absolute terms, this might equate to an additional 34 quitters per 1000 participants (95% CI 13 to 55). Post-discharge interventions offering real-time counselling without pharmacotherapy (RR 1.23, 95% CI 0.95 to 1.60, 8 studies, 2299 participants; low certainty-evidence) and those offering unscheduled counselling without pharmacotherapy (RR 0.97, 95% CI 0.83 to 1.14; 2 studies, 1598 participants; very low-certainty evidence) may have little to no effect on quit rates compared to control. Telephone quitlines versus control To provide post-discharge support, hospitals may refer patients to community-based telephone quitlines. Both comparisons relating to these interventions had wide CIs encompassing both possible harm and possible benefit, and were judged to be of very low certainty due to imprecision, inconsistency, and risk of bias (post-discharge telephone counselling versus quitline referral: RR 1.23, 95% CI 1.00 to 1.51; 3 studies, 3260 participants; quitline referral versus control: RR 1.17, 95% CI 0.70 to 1.96; 2 studies, 1870 participants). AUTHORS' CONCLUSIONS: Offering hospitalised patients smoking cessation counselling beginning in hospital and continuing for over one month after discharge increases quit rates, compared to no hospital intervention. Counselling provided only in hospital, without post-discharge support, may have a modest impact on quit rates, but evidence is less certain. When all patients receive counselling in the hospital, high-certainty evidence indicates that providing both counselling and pharmacotherapy after discharge increases quit rates compared to no post-discharge intervention. Starting nicotine replacement or varenicline in hospitalised patients helps more patients to quit smoking than a placebo or no medication, though evidence for varenicline is only moderate-certainty due to imprecision. There is less evidence of benefit for bupropion in this setting. Some of our evidence was limited by imprecision (bupropion versus placebo and varenicline versus placebo), risk of bias, and inconsistency related to heterogeneity. Future research is needed to identify effective strategies to implement, disseminate, and sustain interventions, and to ensure cessation counselling and pharmacotherapy initiated in the hospital is sustained after discharge.

Exploring the opinions and potential impact of unflavoured e-liquid on smoking cessation among people who smoke and smoking relapse among people who previously smoked and now use e-cigarettes: findings from a UK-based mixed methods study.

BACKGROUND: Although electronic cigarettes (e-cigarettes) appear to be effective in helping people who smoke to stop smoking, concerns about use of e-cigarettes among young people have led to restrictions on non-tobacco flavoured e-liquids in some countries and some US states. These restrictions could reduce the appeal of these products to non-smoking youth but could have negative consequences for people who smoke or use e-cigarettes. METHODS: In this mixed methods study, we recruited UK adults who smoked or used to smoke and subsequently vaped to explore their opinions of unflavoured e-liquids and their beliefs about how they would be impacted by hypothetical e-liquid flavour restrictions. Participants trialled an unflavoured e-liquid instead of their usual nicotine product for four hours and completed a survey and an online interview. RESULTS: Using Interpretive Phenomenological Analysis and graphically presented data, we found differences in participants' opinions of unflavoured e-liquid. If only unflavoured, tobacco flavoured, and menthol flavoured e-liquids remained on the UK market, some people who smoke or vape may be unaffected, but some may relapse to smoking or continue smoking. Despite most wanting to prevent young people from initiating vaping, participants had varying opinions on whether flavour restrictions would be an effective method. CONCLUSIONS: The findings highlight that people who smoke and vape could be impacted by flavour restrictions in a range of ways, some of which could have a potential adverse impact on harm reduction efforts in the UK (e.g., by making smoking more appealing than vaping).

Impact on alcohol selection and online purchasing of changing the proportion of available non-alcoholic versus alcoholic drinks: A randomised controlled trial.

BACKGROUND: Increasing the availability of non-alcoholic options is a promising population-level intervention to reduce alcohol consumption, currently unassessed in naturalistic settings. This study in an online retail context aimed to estimate the impact of increasing the proportion of non-alcoholic (relative to alcoholic) drinks, on selection and purchasing of alcohol. METHODS AND RESULTS: Adults (n = 737) residing in England and Wales who regularly purchased alcohol online were recruited between March and July 2021. Participants were randomly assigned to one of 3 groups: "25% non-alcoholic/75% alcoholic"; "50% non-alcoholic/50% alcoholic"; and "75% non-alcoholic/25% alcoholic," then selected drinks in a simulated online supermarket, before purchasing them in an actual online supermarket. The primary outcome was the number of alcohol units selected (with intention to purchase); secondary outcomes included actual purchasing. A total of 607 participants (60% female, mean age = 38 years [range: 18 to 76]) completed the study and were included in the primary analysis. In the first part of a hurdle model, a greater proportion of participants in the "75% non-alcoholic" group did not select any alcohol (13.1%) compared to the "25% non-alcoholic" group (3.4%; 95% confidence interval [CI] -2.09, -0.63; p < 0.001). There was no evidence of a difference between the "75% non-alcoholic" and the "50% non-alcoholic" (7.2%) groups (95% CI 0.10, 1.34; p = 0.022) or between the "50% non-alcoholic" and the "25% non-alcoholic" groups (95% CI -1.44, 0.17; p = 0.121). In the second part of a hurdle model in participants (559/607) selecting any drinks containing alcohol, the "75% non-alcoholic" group selected fewer alcohol units compared to the "50% non-alcoholic" (95% CI -0.44, -0.14; p < 0.001) and "25% non-alcoholic" (95% CI -0.54, -0.24; p < 0.001) groups, with no evidence of a difference between the "50% non-alcoholic" and "25% non-alcoholic" groups (95% CI -0.24, 0.05; p = 0.178). Overall, across all participants, 17.46 units (95% CI 15.24, 19.68) were selected in the "75% non-alcoholic" group; 25.51 units (95% CI 22.60, 28.43) in the "50% non-alcoholic" group; and 29.40 units (95% CI 26.39, 32.42) in the "25% non-alcoholic" group. This corresponds to 8.1 fewer units (a 32% reduction) in the "75% non-alcoholic" compared to the "50% non-alcoholic" group, and 11.9 fewer alcohol units (41% reduction) compared to the "25% non-alcoholic" group; 3.9 fewer units (13% reduction) were selected in the "50% non-alcoholic" group than in the "25% non-alcoholic" group. For all other outcomes, alcohol selection and purchasing were consistently lowest in the "75% non-alcoholic" group. Study limitations include the setting not being entirely naturalistic due to using a simulated online supermarket as well as an actual online supermarket, and that there was substantial dropout between selection and purchasing. CONCLUSIONS: This study provides evidence that substantially increasing the proportion of non-alcoholic drinks-from 25% to 50% or 75%-meaningfully reduces alcohol selection and purchasing. Further studies are warranted to assess whether these effects are realised in a range of real-world settings. TRIAL REGISTRATION: ISRCTN: 11004483; OSF: https://osf.io/qfupw.

Associations between health behaviours, fertility and reproductive outcomes: triangulation of evidence in the Norwegian Mother, Father and Child Cohort Study (MoBa).

BACKGROUND: Guidance to improve fertility includes reducing alcohol and caffeine consumption, achieving healthy weight-range and stopping smoking. Advice is informed by observational evidence, which is often biased by confounding. METHODS: This study primarily used data from a pregnancy cohort, the Norwegian Mother, Father and Child Cohort Study. First, we conducted multivariable regression of health behaviours (alcohol and caffeine consumption, body-mass index (BMI), and smoking) on fertility outcomes (e.g. time to conception) and reproductive outcomes (e.g. age at first birth) (n = 84,075 females, 68,002 males), adjusting for birth year, education and attention-deficit and hyperactive-impulsive (ADHD) traits. Second, we used individual-level Mendelian randomisation (MR) to explore possible causal effects of health behaviours on fertility/reproductive outcomes (n = 63,376 females, 45,460 males). Finally, we performed summary-level MR for available outcomes in UK Biobank (n = 91,462-1,232,091) and controlled for education and ADHD liability using multivariable MR. RESULTS: In multivariable regression analyses, higher BMI associated with fertility (longer time to conception, increased odds of infertility treatment and miscarriage), and smoking was associated with longer time to conception. In individual-level MR analyses, there was strong evidence for effects of smoking initiation and higher BMI on younger age at first birth, of higher BMI on increased time to conception, and weak evidence for effects of smoking initiation on increased time to conception. Age at first birth associations were replicated in summary-level MR analysis; however, effects attenuated using multivariable MR. CONCLUSIONS: Smoking behaviour and BMI showed the most consistent associations for increased time to conception and a younger age at first birth. Given that age at first birth and time to conception are positively correlated, this suggests that the mechanisms for reproductive outcomes are distinct to the mechanisms acting on fertility outcomes. Multivariable MR suggested that effects on age at first birth might be explained by underlying liability to ADHD and education.

Self-processing in relation to emotion and reward processing in depression.

BACKGROUND: Depression is characterised by a heightened self-focus, which is believed to be associated with differences in emotion and reward processing. However, the precise relationship between these cognitive domains is not well understood. We examined the role of self-reference in emotion and reward processing, separately and in combination, in relation to depression. METHODS: Adults experiencing varying levels of depression (n = 144) completed self-report depression measures (PHQ-9, BDI-II). We measured self, emotion and reward processing, separately and in combination, using three cognitive tasks. RESULTS: When self-processing was measured independently of emotion and reward, in a simple associative learning task, there was little association with depression. However, when self and emotion processing occurred in combination in a self-esteem go/no-go task, depression was associated with an increased positive other bias [b = 3.51, 95% confidence interval (CI) 1.24-5.79]. When the self was processed in relation to emotion and reward, in a social evaluation learning task, depression was associated with reduced positive self-biases (b = 0.11, 95% CI 0.05-0.17). CONCLUSIONS: Depression was associated with enhanced positive implicit associations with others, and reduced positive learning about the self, culminating in reduced self-favouring biases. However, when self, emotion and reward processing occurred independently there was little evidence of an association with depression. Treatments targeting reduced positive self-biases may provide more sensitive targets for therapeutic intervention and potential biomarkers of treatment responses, allowing the development of more effective interventions.

Statistical power in clinical trials of interventions for mood, anxiety, and psychotic disorders.

BACKGROUND: Previous research has suggested that statistical power is suboptimal in many biomedical disciplines, but it is unclear whether power is better in trials for particular interventions, disorders, or outcome types. We therefore performed a detailed examination of power in trials of psychotherapy, pharmacotherapy, and complementary and alternative medicine (CAM) for mood, anxiety, and psychotic disorders. METHODS: We extracted data from the Cochrane Database of Systematic Reviews (Mental Health). We focused on continuous efficacy outcomes and estimated power to detect predetermined effect sizes (standardized mean difference [SMD] = 0.20-0.80, primary SMD = 0.40) and meta-analytic effect sizes (ESMA). We performed meta-regression to estimate the influence of including underpowered studies in meta-analyses. RESULTS: We included 256 reviews with 10 686 meta-analyses and 47 384 studies. Statistical power for continuous efficacy outcomes was very low across intervention and disorder types (overall median [IQR] power for SMD = 0.40: 0.32 [0.19-0.54]; for ESMA: 0.23 [0.09-0.58]), only reaching conventionally acceptable levels (80%) for SMD = 0.80. Median power to detect the ESMA was higher in treatment-as-usual (TAU)/waitlist-controlled (0.49-0.63) or placebo-controlled (0.12-0.38) trials than in trials comparing active treatments (0.07-0.13). Adequately-powered studies produced smaller effect sizes than underpowered studies (B = -0.06, p ⩽ 0.001). CONCLUSIONS: Power to detect both predetermined and meta-analytic effect sizes in psychiatric trials was low across all interventions and disorders examined. Consistent with the presence of reporting bias, underpowered studies produced larger effect sizes than adequately-powered studies. These results emphasize the need to increase sample sizes and to reduce reporting bias against studies reporting null results to improve the reliability of the published literature.

Objective measures of reward sensitivity and motivation in people with high v. low anhedonia.

BACKGROUND: Anhedonia - a diminished interest or pleasure in activities - is a core self-reported symptom of depression which is poorly understood and often resistant to conventional antidepressants. This symptom may occur due to dysfunction in one or more sub-components of reward processing: motivation, consummatory experience and/or learning. However, the precise impairments remain elusive. Dissociating these components (ideally, using cross-species measures) and relating them to the subjective experience of anhedonia is critical as it may benefit fundamental biology research and novel drug development. METHODS: Using a battery of behavioural tasks based on rodent assays, we examined reward motivation (Joystick-Operated Runway Task, JORT; and Effort-Expenditure for Rewards Task, EEfRT) and reward sensitivity (Sweet Taste Test) in a non-clinical population who scored high (N = 32) or low (N = 34) on an anhedonia questionnaire (Snaith-Hamilton Pleasure Scale). RESULTS: Compared to the low anhedonia group, the high anhedonia group displayed marginal impairments in effort-based decision-making (EEfRT) and reduced reward sensitivity (Sweet Taste Test). However, we found no evidence of a difference between groups in physical effort exerted for reward (JORT). Interestingly, whilst the EEfRT and Sweet Taste Test correlated with anhedonia measures, they did not correlate with each other. This poses the question of whether there are subgroups within anhedonia; however, further work is required to directly test this hypothesis. CONCLUSIONS: Our findings suggest that anhedonia is a heterogeneous symptom associated with impairments in reward sensitivity and effort-based decision-making.

Emotional bias training as a treatment for anxiety and depression: evidence from experimental medicine studies in healthy and medicated samples.

BACKGROUND: Anxiety and depression are leading causes of disability worldwide, yet individuals are often unable to access appropriate treatment. There is a need to develop effective interventions that can be delivered remotely. Previous research has suggested that emotional processing biases are a potential target for intervention, and these may be altered through brief training programs. METHODS: We report two experimental medicine studies of emotional bias training in two samples: individuals from the general population (n = 522) and individuals currently taking antidepressants to treat anxiety or depression (n = 212). Participants, recruited online, completed four sessions of EBT from their own home. Mental health and cognitive functioning outcomes were assessed at baseline, immediately post-training, and at 2-week follow-up. RESULTS: In both studies, our intervention successfully trained participants to perceive ambiguous social information more positively. This persisted at a 2-week follow-up. There was no clear evidence that this change in emotional processing transferred to improvements in symptoms in the primary analyses. However, in both studies, there was weak evidence for improved quality of life following EBT amongst individuals with more depressive symptoms at baseline. No clear evidence of transfer effects was observed for self-reported daily stress, anhedonia or depressive symptoms. Exploratory analyses suggested that younger participants reported greater treatment gains. CONCLUSIONS: These studies demonstrate the effectiveness of delivering a multi-session online training program to promote lasting cognitive changes. Given the inconsistent evidence for transfer effects, EBT requires further development before it can be considered as a treatment for anxiety and depression.

Associations of negative affective biases and depressive symptoms in a community-based sample.

BACKGROUND: Major depressive disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based sample, followed by examining differences between remitted individuals and controls. METHODS: Participants from Generation Scotland (N = 1109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). Individuals were classified as MDD-current (n = 43), MDD-remitted (n = 282), or controls (n = 784). Analyses included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses). RESULTS: For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the sample (individuals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v. controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition [e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)]. Results for remitted-MDD were inconsistent. CONCLUSIONS: This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the sample, over and above those accounted for by non-affective cognition, with no evidence for affective biases in remitted individuals.

Association between inflammation and cognition: Triangulation of evidence using a population-based cohort and Mendelian randomization analyses.

BACKGROUND: Inflammation is associated with cognitive functioning and dementia in older adults, but whether inflammation is related to cognitive functioning in youth and whether these associations are causal remains unclear. METHODS: In a population-based cohort (Avon Longitudinal Study of Parents and Children; ALSPAC), we investigated cross-sectional associations of inflammatory markers (C-reactive protein [CRP], Interleukin-6 [IL-6] and Glycoprotein acetyls [GlycA]) with measures of cold (working memory, response inhibition) and hot (emotion recognition) cognition at age 24 (N = 3,305 in multiple imputation models). Furthermore, we conducted one-sample and two-sample bidirectional Mendelian randomization (MR) analyses to examine potential causal effects of genetically-proxied inflammatory markers (CRP, GlycA, IL-6, IL-6 receptor, soluble IL-6 receptor) on cognitive measures (above) and on general cognitive ability. RESULTS: In the ALSPAC cohort, there was limited evidence of an association between standardised inflammatory markers and standardised cognitive measures at age 24 after adjusting for potential confounders (N = 3,305; beta range, -0.02 [95 % confidence interval (CI) -0.06 to 0.02, p = 0.27] to 0.02 [95 % CI -0.02 to 0.05, p = 0.33]). Similarly, we found limited evidence of potential effects of 1-unit increase in genetically-proxied inflammatory markers on standardised working memory, emotion recognition or response inhibition in one-sample MR using ALSPAC data (beta range, -0.73 [95 % CI -2.47 to 1.01, p = 0.41] to 0.21 [95 % CI -1.42 to 1.84, p = 0.80]; or on standardised general cognitive ability in two-sample MR using the latest Genome-Wide Association Study (GWAS) datasets (inverse-variance weighted beta range, -0.02 [95 % CI -0.05 to 0.01, p = 0.12] to 0.03 [95 % CI -0.01 to 0.07, p = 0.19]). CONCLUSIONS: Our MR findings do not provide strong evidence of a potential causal effect of inflammatory markers (CRP, IL-6, IL-6 receptor, GlycA) on the cognitive functions examined here. Given the large confidence intervals in the one-sample MR, larger GWAS of specific cognitive measures are needed to enable well-powered MR analyses to investigate whether inflammation causally influences specific cognitive domains.

Little evidence for an effect of smoking on multiple sclerosis risk: A Mendelian Randomization study.

The causes of multiple sclerosis (MS) remain unknown. Smoking has been associated with MS in observational studies and is often thought of as an environmental risk factor. We used two-sample Mendelian randomization (MR) to examine whether this association is causal using genetic variants identified in genome-wide association studies (GWASs) as associated with smoking. We assessed both smoking initiation and lifetime smoking behaviour (which captures smoking duration, heaviness, and cessation). There was very limited evidence for a meaningful effect of smoking on MS susceptibility as measured using summary statistics from the International Multiple Sclerosis Genetics Consortium (IMSGC) meta-analysis, including 14,802 cases and 26,703 controls. There was no clear evidence for an effect of smoking on the risk of developing MS (smoking initiation: odds ratio [OR] 1.03, 95% confidence interval [CI] 0.92-1.61; lifetime smoking: OR 1.10, 95% CI 0.87-1.40). These findings suggest that smoking does not have a detrimental consequence on MS susceptibility. Further work is needed to determine the causal effect of smoking on MS progression.

Bounding the average causal effect in Mendelian randomisation studies with multiple proposed instruments: An application to prenatal alcohol exposure and attention deficit hyperactivity disorder.

BACKGROUND: As large-scale observational data become more available, caution regarding causal assumptions remains critically important. This may be especially true for Mendelian randomisation (MR), an increasingly popular approach. Point estimation in MR usually requires strong, often implausible homogeneity assumptions beyond the core instrumental conditions. Bounding, which does not require homogeneity assumptions, is infrequently applied in MR. OBJECTIVES: We aimed to demonstrate computing nonparametric bounds for the causal risk difference derived from multiple proposed instruments in an MR study where effect heterogeneity is expected. METHODS: Using data from the Norwegian Mother, Father and Child Cohort Study (n = 2056) and Avon Longitudinal Study of Parents and Children (n = 6216) to study the average causal effect of maternal pregnancy alcohol use on offspring attention deficit hyperactivity disorder symptoms, we proposed 11 maternal SNPs as instruments. We computed bounds assuming subsets of SNPs were jointly valid instruments, for all combinations of SNPs where the MR model was not falsified. RESULTS: The MR assumptions were violated for all sets with more than 4 SNPs in one cohort and for all sets with more than 2 SNPs in the other. Bounds assuming one SNP was an individually valid instrument barely improved on assumption-free bounds. Bounds tightened as more SNPs were assumed to be jointly valid instruments, and occasionally identified directions of effect, though bounds from different sets varied. CONCLUSIONS: Our results suggest that, when proposing multiple instruments, bounds can contextualise plausible magnitudes and directions of effects. Computing bounds over multiple assumption sets, particularly in large, high-dimensional data, offers a means of triangulating results across different potential sources of bias within a study and may help researchers to better evaluate and emphasise which estimates are compatible with the most plausible assumptions for their specific setting.

Exploring the bidirectional causal pathways between smoking behaviours and headache: A Mendelian randomisation study.

INTRODUCTION: Although observational data suggests a relationship between headache and smoking, there remain questions about causality. Smoking may increase headache risk, individuals may smoke to alleviate headaches, or smoking and headache may share common risk factors. Mendelian randomisation (MR) is a method that uses genetic variants as instruments for making causal inferences about an exposure and an outcome. METHODS: First, we conducted logistic regression of observational data in UK Biobank assessing the association between smoking behaviours (smoking status, cigarettes per day amongst daily smokers and lifetime smoking score) on risk of self-reported headache (in the last month and for more than 3 months). Second, we used genetic instruments for smoking behaviours and headache (identified in independent genome-wide association studies) to perform bidirectional MR analysis. RESULTS: Observationally, there is a weak association between smoking behaviour and experiencing headache, with increased cigarettes per day associated with increased headache risk. In the MR analysis, genetic liability to smoking initiation and lifetime smoking increased odds of headache in the last month but not odds of headaches lasting more than three months. In the opposite direction there was weak evidence for higher genetic liability to headaches decreasing the chance of quitting. CONCLUSION: There was weak evidence for a partially bidirectional causal relationship between smoking behaviours and headache in the last month. Given this relationship is distinct from smoking heaviness, it suggests headache and smoking may share common risk factors such as personality traits. IMPLICATIONS: Using Mendelian Randomisation, this study addresses the uncertainty regarding the observed relationship between headache and smoking. There was evidence for weak causal effects of smoking initiation and lifetime smoking (but not smoking heaviness) on likelihood of experiencing headache in the last month, but not over a prolonged period of more than three months. Those at higher genetic liability for headaches were also less likely to successfully stop smoking. This partially bidirectional causal relationship distinct from smoking heaviness, suggests that observed associations are unlikely due to biological effects of tobacco smoke exposure and may be explained by shared personality traits.

Effects of electronic cigarette e-liquid flavouring on cigarette craving.

BACKGROUND: E-liquid flavour restrictions may discourage electronic cigarette (e-cigarette) uptake among youth. However, possible unintended consequences may include reduced appeal and effectiveness of e-cigarettes for smoking cessation. Non-tobacco flavours appear to be important for smoking cessation, but how and why are currently unclear. METHODS: We conducted an experimental study in a UK sample of adult daily smokers using an independent groups design (N=84). Participants were randomised to use an e-cigarette with nicotine-containing fruit/sweet-flavoured e-liquid (blackcurrant, strawberry, vanilla, caramel) or unflavoured e-liquid for 1 week. The primary outcomes were average, peak and cue-elicited cigarette craving (the latter was assessed using a cue exposure task). The secondary outcomes were smoking lapse occurrence, enjoyment of the e-cigarette, ease of transitioning from smoking to using an e-cigarette, intentions to continue using an e-cigarette, intentions and motivation to quit smoking, return to smoking, and continuation of e-cigarette use. RESULTS: E-liquid flavouring did not appear to have an effect on average cigarette craving (b 0.18, 95% CI -0.44 to 0.79, p=0.57), peak cigarette craving (b -0.12, 95% CI -0.59 to 0.35, p=0.62) or cue-elicited cigarette craving (b -0.21, 95% CI -3.86 to 3.43, p=0.91). We did not find evidence of a difference in secondary outcomes. CONCLUSIONS: We did not find evidence to suggest that nicotine-containing fruit/sweet-flavoured and unflavoured e-liquids have different effects on cigarette cravings after 1 week of use. Further research is needed to establish if differences emerge over longer periods of exposure and extend to smoking cessation outcomes.

Impact of e-cigarette retail displays on attitudes to smoking and vaping in children: an online experimental study.

OBJECTIVES: To estimate the impact of electronic cigarette (e-cigarette) retail display exposure on attitudes to smoking and vaping (susceptibility to tobacco smoking and using e-cigarettes, and perceptions of the harms of smoking and e-cigarette use). DESIGN: Between-subjects randomised experiment using a 2 (e-cigarette retail display visibility: high vs low)×2 (proportion of e-cigarette images: 75% vs 25%) factorial design. SETTING: Online via the Qualtrics survey platform. PARTICIPANTS: UK children aged 13-17 years (n=1034), recruited through a research agency. INTERVENTION: Participants viewed 12 images of retail displays that contained e-cigarette display images or unrelated product images. E-cigarette display images were either high or low visibility, based on a conspicuousness score. Participants were randomised to one of four groups, with e-cigarette display visibility and proportion of e-cigarette images, compared with images of unrelated products, manipulated: (1) 75% e-cigarettes, high visibility; (2) 25% e-cigarettes, high visibility; (3) 75% e-cigarettes, low visibility; (4) 25% e-cigarettes, low visibility. MAIN OUTCOME MEASURES: The primary outcome was susceptibility to smoking (among never smokers only). Secondary outcomes were susceptibility to using e-cigarettes (among never vapers only), and perceptions of smoking and e-cigarette harm (all participants). RESULTS: Neither e-cigarette retail display visibility, nor the proportion of e-cigarette images displayed, appeared to influence susceptibility to smoking (visibility: OR=0.84, 95% CI 0.62 to 1.13, p=0.24; proportion: OR=1.34, 95% CI 1.00 to 1.82, p=0.054 (reference: low visibility, not susceptible)).Planned subgroup analyses indicated that exposure to a higher proportion of e-cigarette images increased susceptibility to smoking among children who visited retail stores more regularly (n=524, OR=1.59, 95% CI 1.04 to 2.43, p=0.034), and those who passed the attention check (n=880, OR=1.43, 95% CI 1.03 to 1.98, p=0.031).In addition, neither e-cigarette retail display visibility nor the proportion of e-cigarette images displayed, appeared to influence susceptibility to using e-cigarettes (visibility: OR=1.07, 95% CI 0.80 to 1.43, p=0.65; proportion: OR=1.22, 95% CI 0.91 to 1.64, p=0.18).Greater visibility of e-cigarette retail displays reduced perceived harm of smoking (mean difference (MD)=-0.19, 95% CI -0.34 to -0.04, p=0.016). There was no evidence that the proportion of e-cigarette images displayed had an effect (MD=-0.07, 95% CI -0.22 to 0.09, p=0.40).Perceived harm of e-cigarette use did not appear to be affected by e-cigarette retail display visibility (MD=-0.12, 95% CI -0.28 to 0.05, p=0.16) or by the proportion of e-cigarette images displayed (MD=-0.10, 95% CI -0.26 to 0.07, p=0.24). CONCLUSIONS: There is no evidence in the full sample to suggest that children's susceptibility to smoking is increased by exposure to higher visibility e-cigarette retail displays, or to a higher proportion of e-cigarette images. However, for regular store visitors or those paying more attention, viewing a higher proportion of e-cigarette images increased susceptibility to smoking. In addition, viewing higher visibility e-cigarette images reduced perceived harm of smoking. A review of the current regulatory discrepancy between tobacco and e-cigarette point-of-sale marketing is warranted. TRIAL REGISTRATION NUMBER: ISRCTN18215632.

Acceptability of integrating smoking cessation treatment into routine care for people with mental illness: A qualitative study.

INTRODUCTION: Improving Access to Psychological Therapies (IAPTs) Services could offer smoking cessation treatment to improve physical and psychological outcomes for service users, but it currently does not. This study aimed to understand participants' views and experiences of receiving a novel smoking cessation intervention as part of the ESCAPE trial (intEgrating Smoking Cessation treatment As part of usual Psychological care for dEpression and anxiety). We used the Capability, Opportunity and Motivation Model of Behaviour (COM-B) to understand the (i) acceptability of the integrated smoking cessation treatment, (ii) views of psychological well-being practitioners' (PWPs) ability to deliver the smoking cessation treatment and (iii) positive and negative impacts of smoking cessation treatment. METHODS: This was a qualitative study embedded within a feasibility randomized-controlled trial (ESCAPE) in primary care services in the United Kingdom (IAPT). Thirty-six participants (53% female) from both usual care and intervention arms of the ESCAPE trial, including both quitters and nonquitters, were interviewed using semi-structured interviews. Data were analysed using a framework approach to thematic analysis, using the COM-B as a theoretical frame. RESULTS: Psychological Capability: Integrated smoking cessation treatment was acceptable and encouraged participants to reflect on their mental health. Some participants found it difficult to understand nicotine withdrawal symptoms. MOTIVATION: Participants were open to change during the event of presenting to IAPT. Some described being motivated to take part in the intervention by curiosity, to see whether quitting smoking would help their mental health. Physical Opportunity: IAPT has a natural infrastructure for supporting integrated treatment, but there were some barriers such as session duration and interventions feeling segmented. Social Opportunity: Participants viewed PWPs as having good interpersonal skills to deliver a smoking cessation intervention. CONCLUSION: People with common mental illness generally accepted integrated smoking cessation and mental health treatment. Smoking cessation treatment fits well within IAPT's structure; however, there are barriers to implementation. PATIENT OR PUBLIC CONTRIBUTION: Before data collection, we consulted with people with lived experience of smoking and/or mental illness and lay public members regarding the aims, design and interview schedules. After analysis, two people with lived experience of smoking and mental illness individually gave feedback on the final themes and quotes.