The dopamine D2 receptor has been extensively studied in relation to alcoholism, substance abuse, and nicotine dependence. The most frequently examined polymorphism linked to this gene is the Taq1A restriction fragment length polymorphism (RFLP) (dbSNP rs1800497; g.32806C>T in GenBank AF050737.1), which has been associated with a reduction in D2 receptor density, although this is not universally accepted. The Taq1A RFLP lies 10 kB downstream of DRD2 and may therefore fall within a different coding region than the DRD2 gene or within a regulatory region. Within this downstream region, we have identified a novel kinase gene, named ankyrin repeat and kinase domain containing 1 (ANKK1), which contains a single serine/threonine kinase domain and is expressed at low levels in placenta and whole spinal cord RNA. This gene is a member of an extensive family of proteins involved in signal transduction pathways. The DRD2 Taq1A RFLP is a single nucleotide polymorphism (SNP) that causes an amino acid substitution within the 11th ankyrin repeat of ANKK1 (p.Glu713Lys), which, while unlikely to affect structural integrity, may affect substrate-binding specificity. If this is the case, then changes in ANKK1 activity may provide an alternative explanation for previously described associations between the DRD2 Taq1A RFLP and neuropsychiatric disorders such as addiction.
ObjectiveSmartphone games that aim to alter health behaviours are common, but there is uncertainty about how to achieve this. We systematically reviewed health apps containing gaming elements analysing their embedded behaviour change techniques.MethodsTwo trained researchers independently coded apps for behaviour change techniques using a standard taxonomy. We explored associations with user ratings and price.Data sourcesWe screened the National Health Service (NHS) Health Apps Library and all top-rated medical, health and wellness and health and fitness apps (defined by Apple and Google Play stores based on revenue and downloads). We included free and paid English language apps using ‘gamification’ (rewards, prizes, avatars, badges, leaderboards, competitions, levelling-up or health-related challenges). We excluded apps targeting health professionals.Results64 of 1680 (4%) health apps included gamification and met inclusion criteria; only 3 of these were in the NHS Library. Behaviour change categories used were: feedback and monitoring (n=60, 94% of apps), reward and threat (n=52, 81%), and goals and planning (n=52, 81%). Individual techniques were: self-monitoring of behaviour (n=55, 86%), non-specific reward (n=49, 82%), social support unspecified (n=48, 75%), non-specific incentive (n=49, 82%) and focus on past success (n=47, 73%). Median number of techniques per app was 14 (range: 5–22). Common combinations were: goal setting, self-monitoring, non-specific reward and non-specific incentive (n=35, 55%); goal setting, self-monitoring and focus on past success (n=33, 52%). There was no correlation between number of techniques and user ratings (p=0.07; rs=0.23) or price (p=0.45; rs=0.10).ConclusionsFew health apps currently employ gamification and there is a wide variation in the use of behaviour change techniques, which may limit potential to improve health outcomes. We found no correlation between user rating (a possible proxy for health benefits) and game content or price. Further research is required to evaluate effective behaviour change techniques and to assess clinical outcomes.Trial registration numberCRD42015029841.
Considerable evidence indicates that smoking behavior is under a degree of genetic influence. We conducted a systematic review of candidate gene studies of smoking behavior and, where sufficient studies existed, combined reported data using meta-analytic techniques. A total of 41 studies were identified by the search strategy, of which 28 contributed to the meta-analysis. The meta-analysis included data on the DRD2, DAT, 5HTT, and CYP2A6 genes and smoking behavior. Categorical data were extracted on smoking status (never-smoker, ex-smoker, current smoker). Continuous data were extracted on number of cigarettes smoked per day. Evidence indicated effects of the DRD2 Taq1A polymorphism and smoking initiation, the 5HTT LPR and CYP2A6 reduced-activity polymorphisms and smoking cessation, and the DRD2 Taq1A and CYP2A6 reduced-activity polymorphisms and cigarette consumption. The evidence for an effect of specific genes was modest, however, and evidence indicated substantial between-study heterogeneity in most cases, with the exception of the effects of the 5HTT and CYP2A6 genes on smoking cessation. When a random-effects model was applied to analyses in which evidence indicated significant heterogeneity, the effects were in all cases no longer statistically significant. The evidence for a contribution of specific genes to smoking behavior remains modest. Implications for the design of future studies are discussed, such as the need for the development of more specific phenotypes to increase the genetic signal in candidate gene studies.
A meta-analysis was conducted on studies reporting data on associations between candidate genes and human personality. Studies reporting data for psychiatric populations (including organic disease and substance abuse) were excluded. A total of 46 studies contributed to the analysis. Pooled data using a fixed-effects model suggested significant associations between the 5HTT LPR, DRD4 c4t, DRD4 length, DRD2 A1/A2, DRD3 A1/A2 polymorphisms and personality traits. A multivariate analysis using a mixed-effects model and including age, sex and predominant ethnicity as covariates was applied to the analyses of 5HTT LPR and DRD4 length polymorphism data. Only the association between the 5HTT LPR polymorphism and avoidance traits remained significant (P ¼ 0.038). However, sensitivity analyses excluding data from studies reporting allele frequencies not in Hardy-Weinberg equilibrium and unpublished data resulted in this association no longer being significant. Implications for the design of future association studies of human personality are discussed, including the likely sample sizes that will be required to achieve sufficient power and the potential role of moderating variables such as sex.
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