Controversies about the enhanced vulnerability of the adolescent brain to develop addiction.

Adolescence, defined as a transition phase toward autonomy and independence, is a natural time of learning and adjustment, particularly in the setting of long-term goals and personal aspirations. It also is a period of heightened sensation seeking, including risk taking and reckless behaviors, which is a major cause of morbidity and mortality among teenagers. Recent observations suggest that a relative immaturity in frontal cortical neural systems may underlie the adolescent propensity for uninhibited risk taking and hazardous behaviors. However, converging preclinical and clinical studies do not support a simple model of frontal cortical immaturity, and there is substantial evidence that adolescents engage in dangerous activities, including drug abuse, despite knowing and understanding the risks involved. Therefore, a current consensus considers that much brain development during adolescence occurs in brain regions and systems that are critically involved in the perception and evaluation of risk and reward, leading to important changes in social and affective processing. Hence, rather than naive, immature and vulnerable, the adolescent brain, particularly the prefrontal cortex, should be considered as prewired for expecting novel experiences. In this perspective, thrill seeking may not represent a danger but rather a window of opportunities permitting the development of cognitive control through multiple experiences. However, if the maturation of brain systems implicated in self-regulation is contextually dependent, it is important to understand which experiences matter most. In particular, it is essential to unveil the underpinning mechanisms by which recurrent adverse episodes of stress or unrestricted access to drugs can shape the adolescent brain and potentially trigger life-long maladaptive responses.

Addiction and arousal: the hypocretin connection

The hypocretins, also known as orexins, are two neuropeptides now commonly described as critical components to maintain and regulate the stability of arousal. Several lines of evidence have raised the hypothesis that hypocretin-producing neurons are part of the circuitries that mediate the hypothalamic response to acute stress. Intracerebral administration of hypocretin leads to a dose-related reinstatement of drug and food seeking behaviors. Furthermore, stress-induced reinstatement can be blocked with hypocretin receptor 1 antagonism. These results, together with recent data showing that hypocretin is critically involved in cocaine sensitization through the recruitment of NMDA receptors in the ventral tegmental area, strongly suggest that activation of hypocretin neurons play a critical role in the development of the addiction process. The activity of hypocretin neurons may affect addictive behavior by contributing to brain sensitization or by modulating the brain reward system. Hypocretinergic cells, in coordination with brain stress systems may lead to a vulnerable state that facilitates the resumption of drug seeking behavior. Hence, the hypocretinergic system is a new drug target that may be used to prevent relapse of drug seeking

Cognitive and structural aspects of addiction: Relation between iris patterns, time perception, eyeblink rate, impulsivity and cigarette addiction

Objectif : Le but de ce travail est d'étudier les corrélations existantes entre les patterns de l'iris, la perception du temps et la fréquence de clignement des paupières (eye blink rate) et ceci en relation avec l'addiction à la cigarette. Méthodologie: Revue de la littérature existante. Expériences sur une cohorte d'au moins trente sujets fumeurs/non-fumeurs. Analyses statistiques. Résultats: Nos résultats confirment qu'il existe des relations entre l'impulsivité, les patterns d'iris, l'eye blink rate spontané et la perception du temps. Nous observons également que l'addiction à la cigarette et son niveau de dépendance ont une influence sur ces différentes mesures. En effet, les sujets fumeurs tendent à avoir une personnalité plus impulsive par rapport aux sujets contrôles. On remarque également une nette diminution de l'eye blink rate dans le groupe des fumeurs et une tendance à la sur-estimation du temps qui passe. Conclusion : Ce travail nous permet de mieux comprendre les différentes corrélations qui existent entre les différentes variables que nous avons mesurées (patterns d'iris, score d'impulsivité et eye blink rate) ainsi que leur relation à l'addiction à la cigarette. Dès lors qu'il est avéré que les fumeurs peuvent avoir une perception du temps altérée par rapport au groupe contrôle, il serait intéressant d'en étudier l'évolution sur le long terme (aggravation avec la durée du tabagisme actif) ainsi que les conséquences qui en découlent écologiquement au moyen d'études longitudinales et de terrain.

Biomedical risk assessment as an aid for smoking cessation.

BACKGROUND: A possible strategy for increasing smoking cessation rates could be to provide smokers who have contact with healthcare systems with feedback on the biomedical or potential future effects of smoking, e.g. measurement of exhaled carbon monoxide (CO), lung function, or genetic susceptibility to lung cancer. OBJECTIVES: To determine the efficacy of biomedical risk assessment provided in addition to various levels of counselling, as a contributing aid to smoking cessation. SEARCH STRATEGY: We systematically searched the Cochrane Collaboration Tobacco Addiction Group Specialized Register, Cochrane Central Register of Controlled Trials 2008 Issue 4, MEDLINE (1966 to January 2009), and EMBASE (1980 to January 2009). We combined methodological terms with terms related to smoking cessation counselling and biomedical measurements. SELECTION CRITERIA: Inclusion criteria were: a randomized controlled trial design; subjects participating in smoking cessation interventions; interventions based on a biomedical test to increase motivation to quit; control groups receiving all other components of intervention; an outcome of smoking cessation rate at least six months after the start of the intervention. DATA COLLECTION AND ANALYSIS: Two assessors independently conducted data extraction on each paper, with disagreements resolved by consensus. Results were expressed as a relative risk (RR) for smoking cessation with 95% confidence intervals (CI). Where appropriate a pooled effect was estimated using a Mantel-Haenszel fixed effect method. MAIN RESULTS: We included eleven trials using a variety of biomedical tests. Two pairs of trials had sufficiently similar recruitment, setting and interventions to calculate a pooled effect; there was no evidence that CO measurement in primary care (RR 1.06, 95% CI 0.85 to 1.32) or spirometry in primary care (RR 1.18, 95% CI 0.77 to 1.81) increased cessation rates. We did not pool the other seven trials. One trial in primary care detected a significant benefit of lung age feedback after spirometry (RR 2.12; 95% CI 1.24 to 3.62). One trial that used ultrasonography of carotid and femoral arteries and photographs of plaques detected a benefit (RR 2.77; 95% CI 1.04 to 7.41) but enrolled a population of light smokers. Five trials failed to detect evidence of a significant effect. One of these tested CO feedback alone and CO + genetic susceptibility as two different intervention; none of the three possible comparisons detected significant effects. Three others used a combination of CO and spirometry feedback in different settings, and one tested for a genetic marker. AUTHORS' CONCLUSIONS: There is little evidence about the effects of most types of biomedical tests for risk assessment. Spirometry combined with an interpretation of the results in terms of 'lung age' had a significant effect in a single good quality trial. Mixed quality evidence does not support the hypothesis that other types of biomedical risk assessment increase smoking cessation in comparison to standard treatment. Only two pairs of studies were similar enough in term of recruitment, setting, and intervention to allow meta-analysis.

D-amphetamine fails to increase extracellular dopamine levels in mice lacking alpha 1b-adrenergic receptors: relationship between functional and nonfunctional dopamine release.

It was found recently that locomotor and rewarding effects of psychostimulants and opiates were dramatically decreased or suppressed in mice lacking alpha1b-adrenergic receptors [alpha1b-adrenergic receptor knock-outs (alpha1bAR-KOs)] (Drouin et al., 2002). Here we show that blunted locomotor responses induced by 3 and 6 mg/kg d-amphetamine in alpha1bAR-KO mice [-84 and -74%, respectively, when compared with wild-type (WT) mice] are correlated with an absence of d-amphetamine-induced increase in extracellular dopamine (DA) levels in the nucleus accumbens of alpha1bAR-KO mice. Moreover, basal extracellular DA levels in the nucleus accumbens are lower in alpha1bAR-KO than in WT littermates (-28%; p < 0.001). In rats however, prazosin, an alpha1-adrenergic antagonist, decreases d-amphetamine-induced locomotor hyperactivity without affecting extracellular DA levels in the nucleus accumbens, a finding related to the presence of an important nonfunctional release of DA (Darracq et al., 1998). We show here that local d-amphetamine releases nonfunctional DA with the same affinity but a more than threefold lower amplitude in C57BL6/J mice than in Sprague Dawley rats. Altogether, this suggests that a trans-synaptic mechanism amplifies functional DA into nonfunctional DA release. Our data confirm the presence of a powerful coupling between noradrenergic and dopaminergic neurons through the stimulation of alpha1b-adrenergic receptors and indicate that nonfunctional DA release is critical in the interpretation of changes in extracellular DA levels. These results suggest that alpha1b-adrenergic receptors may be important therapeutic pharmacological targets not only in addiction but also in psychosis because most neuroleptics possess anti-alpha1-adrenergic properties.

Systematic identification of genomic markers of drug sensitivity in cancer cells.

Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers for responses to targeted agents. Here, to uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we screened a panel of several hundred cancer cell lines--which represent much of the tissue-type and genetic diversity of human cancers--with 130 drugs under clinical and preclinical investigation. In aggregate, we found that mutated cancer genes were associated with cellular response to most currently available cancer drugs. Classic oncogene addiction paradigms were modified by additional tissue-specific or expression biomarkers, and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. Unexpected relationships were revealed, including the marked sensitivity of Ewing's sarcoma cells harbouring the EWS (also known as EWSR1)-FLI1 gene translocation to poly(ADP-ribose) polymerase (PARP) inhibitors. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.

Alcohol-attributable mortality in Switzerland in 2011--age-specific causes of death and impact of heavy versus non-heavy drinking.

BACKGROUND: Alcohol use causes high burden of disease and injury globally. Switzerland has a high consumption of alcohol, almost twice the global average. Alcohol-attributable deaths and years of life lost in Switzerland were estimated by age and sex for the year 2011. Additionally, the impact of heavy drinking (40+grams/day for women and 60+g/day for men) was estimated. METHODS: Alcohol consumption estimates were based on the Addiction Monitoring in Switzerland study and were adjusted to per capita consumption based on sales data. Mortality data were taken from the Swiss mortality register. Methodology of the Comparative Risk Assessment for alcohol was used to estimate alcohol-attributable fractions. RESULTS: Alcohol use caused 1,600 (95% CI: 1,472 - 1,728) net deaths (1,768 deaths caused, 168 deaths prevented) among 15 to 74 year olds, corresponding to 8.7% of all deaths (men: 1,181 deaths; women: 419 deaths). Overall, 42,627 years of life (9.7%, 95% CI: 40,245 - 45,008) were lost due to alcohol. Main causes of alcohol-attributable mortality were injuries at younger ages (15-34 years), with increasing age digestive diseases (mainly liver cirrhosis) and cancers (particularly breast cancers among women). The majority (62%) of all alcohol-attributable deaths was caused by chronic heavy drinking (men: 67%; women: 48 %). CONCLUSION: Alcohol is a major cause of premature mortality in Switzerland. Its impact, among young people mainly via injuries, among men mainly through heavy drinking, calls for a mix of preventive actions targeting chronic heavy drinking, binge drinking and mean consumption.

Biomedical risk assessment as an aid for smoking cessation.

BACKGROUND: A possible strategy for increasing smoking cessation rates could be to provide smokers who have contact with healthcare systems with feedback on the biomedical or potential future effects of smoking, e.g. measurement of exhaled carbon monoxide (CO), lung function, or genetic susceptibility to lung cancer. We reviewed systematically data on smoking cessation rates from controlled trials that used biomedical risk assessment and feedback. OBJECTIVES: To determine the efficacy of biomedical risk assessment provided in addition to various levels of counselling, as a contributing aid to smoking cessation. SEARCH STRATEGY: We systematically searched he Cochrane Collaboration Tobacco Addiction Group Specialized Register, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (1966 to 2004), and EMBASE (1980 to 2004). We combined methodological terms with terms related to smoking cessation counselling and biomedical measurements. SELECTION CRITERIA: Inclusion criteria were: a randomized controlled trial design; subjects participating in smoking cessation interventions; interventions based on a biomedical test to increase motivation to quit; control groups receiving all other components of intervention; an outcome of smoking cessation rate at least six months after the start of the intervention. DATA COLLECTION AND ANALYSIS: Two assessors independently conducted data extraction on each paper, with disagreements resolved by consensus. MAIN RESULTS: From 4049 retrieved references, we selected 170 for full text assessment. We retained eight trials for data extraction and analysis. One of the eight used CO alone and CO + Genetic Susceptibility as two different intervention groups, giving rise to three possible comparisons. Three of the trials isolated the effect of exhaled CO on smoking cessation rates resulting in the following odds ratios (ORs) and 95% confidence intervals (95% CI): 0.73 (0.38 to 1.39), 0.93 (0.62 to 1.41), and 1.18 (0.84 to 1.64). Combining CO measurement with genetic susceptibility gave an OR of 0.58 (0.29 to 1.19). Exhaled CO measurement and spirometry were used together in three trials, resulting in the following ORs (95% CI): 0.6 (0.25 to 1.46), 2.45 (0.73 to 8.25), and 3.50 (0.88 to 13.92). Spirometry results alone were used in one other trial with an OR of 1.21 (0.60 to 2.42).Two trials used other motivational feedback measures, with an OR of 0.80 (0.39 to 1.65) for genetic susceptibility to lung cancer alone, and 3.15 (1.06 to 9.31) for ultrasonography of carotid and femoral arteries performed in light smokers (average 10 to 12 cigarettes a day). AUTHORS' CONCLUSIONS: Due to the scarcity of evidence of sufficient quality, we can make no definitive statements about the effectiveness of biomedical risk assessment as an aid for smoking cessation. Current evidence of lower quality does not however support the hypothesis that biomedical risk assessment increases smoking cessation in comparison with standard treatment. Only two studies were similar enough in term of recruitment, setting, and intervention to allow pooling of data and meta-analysis.