Nucleotide Sequence Variation within the PI3K p85 Alpha Gene Associates with Alcohol Risk Drinking Behaviour in Adolescents

While the phosphatidylinositol 3-kinase (PI3K)-dependent signaling pathway is typically known to regulate cell growth and survival, emerging evidence suggest a role for this pathway in regulating the behavioural responses to addictive drugs.To investigate whether PI3K contributes to patterns of risky alcohol drinking in human, we investigated genetic variations in PIK3R1, encoding the 85 kD regulatory subunit of PIK, in 145 family trios consisting of 15-16 year old adolescents and their parents. Screening for mutations in exons, exon-intron boundaries and regulatory sequences, we identified 14 single nucleotide polymorphisms (SNPs) in the PIK3R1 gene region from exon 1 to the beginning of the 3' untranslated region (UTR). These SNPs defined haplotypes for the respective PIK3R1 region. Four haplotype tagging (ht)SNPs (rs706713, rs2302975, rs171649 and rs1043526), discriminating all haplotypes with a frequency >or=4.5% were identified. These htSNPs were used to genotype adolescents from the "Mannheim Study of Risk Children" (MARC). Transmission disequilibrium tests in these adolescents and their parents demonstrated sex-specific association of two SNPs, rs2302975 and rs1043526, with patterns of risky alcohol consumption in male adolescents, including lifetime prevalence of drunkenness (p = 0.0019 and 0.0379, respectively) and elevated maximum amount of drinking (p = 0.0020 and 0.0494, respectively), as a measure for binge drinking pattern.Our findings highlight a previously unknown relevance of PIK3R1 genotypes for alcohol use disorders and might help discriminate individuals at risk for alcoholism

The empirical replicability of task-based fMRI as a function of sample size

Replicating results (i.e. obtaining consistent results using a new independent dataset) is an essential part of good science. As replicability has consequences for theories derived from empirical studies, it is of utmost importance to better understand the underlying mechanisms influencing it. A popular tool for non-invasive neuroimaging studies is functional magnetic resonance imaging (fMRI). While the effect of underpowered studies is well documented, the empirical assessment of the interplay between sample size and replicability of results for task-based fMRI studies remains limited. In this work, we extend existing work on this assessment in two ways. Firstly, we use a large database of 1400 subjects performing four types of tasks from the IMAGEN project to subsample a series of independent samples of increasing size. Secondly, replicability is evaluated using a multi-dimensional framework consisting of 3 different measures: (un)conditional test-retest reliability, coherence and stability. We demonstrate not only a positive effect of sample size, but also a trade-off between spatial resolution and replicability. When replicability is assessed voxelwise or when observing small areas of activation, a larger sample size than typically used in fMRI is required to replicate results. On the other hand, when focussing on clusters of voxels, we observe a higher replicability. In addition, we observe variability in the size of clusters of activation between experimental paradigms or contrasts of parameter estimates within these

EDIFY (Eating disorders: delineating illness and recovery trajectories to inform personalised prevention and early intervention in young people):Project outline

EDIFY (Eating Disorders: Delineating Illness and Recovery Trajectories to Inform Personalised Prevention and Early Intervention in Young People) is an ambitious research project aiming to revolutionise how eating disorders are perceived, prevented and treated. Six integrated workstreams will address key questions, including: What are young people's experiences of eating disorders and recovery? What are the unique and shared risk factors in different groups? What helps or hinders recovery? How do the brain and behaviour change from early- to later-stage illness? How can we intervene earlier, quicker and in a more personalised way? This 4-year project, involving over 1000 participants, integrates arts, design and humanities with advanced neurobiological, psychosocial and bioinformatics approaches. Young people with lived experience of eating disorders are at the heart of EDIFY, serving as advisors and co-producers throughout. Ultimately, this work will expand public and professional perceptions of eating disorders, uplift under-represented voices and stimulate much-needed advances in policy and practice

A model-based approach to assess reproducibility for large-scale high-throughput MRI-based studies

Magnetic Resonance Imaging (MRI) technology has been increasingly used in neuroscience studies. Reproducibility of statistically significant findings generated by MRI-based studies, especially association studies (phenotype vs. MRI metric) and task-induced brain activation, has been recently heavily debated. However, most currently available reproducibility measures depend on thresholds for the test statistics and cannot be use to evaluate overall study reproducibility. It is also crucial to elucidate the relationship between overall study reproducibility and sample size in an experimental design. In this study, we proposed a model-based reproducibility index to quantify reproducibility which could be used in large-scale high-throughput MRI-based studies including both association studies and task-induced brain activation. We performed the model-based reproducibility assessments for a few association studies and task-induced brain activation by using several recent large sMRI/fMRI databases. For large sample size association studies between brain structure/function features and some basic physiological phenotypes (i.e. Sex, BMI), we demonstrated that the model-based reproducibility of these studies is more than 0.99. For MID task activation, similar results could be observed. Furthermore, we proposed a model-based analytical tool to evaluate minimal sample size for the purpose of achieving a desirable model-based reproducibility. Additionally, we evaluated the model-based reproducibility of gray matter volume (GMV) changes for UK Biobank (UKB) vs. Parkinson Progression Marker Initiative (PPMI) and UK Biobank (UKB) vs. Human Connectome Project (HCP). We demonstrated that both sample size and study-specific experimental factors play important roles in the model-based reproducibility assessments for different experiments. In summary, a systematic assessment of reproducibility is fundamental and important in the current large-scale high-throughput MRI-based studies

Differential predictors for alcohol use in adolescents as a function of familial risk.

Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions

Ventral striatum connectivity during reward anticipation in adolescent smokers

Substance misusers, including adolescent smokers, often have reduced reward system activity during processing of non-drug rewards. Using a psychophysiological interaction approach, we examined functional connectivity with the ventral striatum during reward anticipation in a large (N = 206) sample of adolescent smokers. Increased smoking frequency was associated with (1) increased connectivity with regions involved in saliency and valuation, including the orbitofrontal cortex and (2) reduced connectivity between the ventral striatum and regions associated with inhibition and risk aversion, including the right inferior frontal gyrus. These results demonstrate that functional connectivity during reward processing is relevant to adolescent addiction

Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence

Background Autistic traits are commonly viewed as dimensional in nature, and as continuously distributed in the general population. In this respect, the identification of predictive values of markers such as subtle autism-related alterations in brain morphology for parameter values of autistic traits could increase our understanding of this dimensional occasion. However, currently, very little is known about how these traits correspond to alterations in brain morphology in typically developing individuals, particularly during a time period where changes due to brain development processes do not provide a bias. Therefore, in the present study, we analyzed brain volume, cortical thickness (CT) and surface area (SA) in a cohort of 14-15-year-old adolescents (N = 285, female: N = 162) and tested their predictive value for autistic traits, assessed with the social responsiveness scale (SRS) two years later at the age of 16-17 years, using a regression-based approach. We found that autistic traits were significantly predicted by volumetric changes in the amygdala (r = 0.181), cerebellum (r = 0.128) and hippocampus (r = -0.181, r = -0.203), both in boys and girls. Moreover, the CT of the superior frontal region was negatively correlated (r = -0.144) with SRS scores. Furthermore, we observed a significant association between the SRS total score and smaller left putamen volume, specifically in boys (r = -0.217), but not in girls. Our findings suggest that neural correlates of autistic traits also seem to lie on a continuum in the general population, are determined by limbic-striatal neuroanatomical brain areas, and are partly dependent on sex. As we imaged adolescents from a large population-based cohort within a small age range, these data may help to increase the understanding of autistic-like occasions in otherwise typically developing individuals

Drinking motives, personality traits and life stressors-identifying pathways to harmful alcohol use in adolescence using a panel network approach

BACKGROUND AND AIMS: Models of alcohol use risk suggest that drinking motives represent the most proximal risk factors on which more distal factors converge. However, little is known about how distinct risk factors influence each other and alcohol use on different temporal scales (within a given moment versus over time). We aimed to estimate the dynamic associations of distal (personality and life stressors) and proximal (drinking motives) risk factors, and their relationship to alcohol use in adolescence and early adulthood using a novel graphical vector autoregressive (GVAR) panel network approach.DESIGN, SETTING AND CASES: We estimated panel networks on data from the IMAGEN study, a longitudinal European cohort study following adolescents across three waves (aged 16, 19 and 22 years). Our sample consisted of 1829 adolescents (51% females) who reported alcohol use on at least one assessment wave.MEASUREMENTS: Risk factors included personality traits (NEO-FFI: neuroticism, extraversion, openness, agreeableness and conscientiousness; SURPS: impulsivity and sensation-seeking), stressful life events (LEQ: sum scores of stressful life events), and drinking motives [drinking motives questionnaire (DMQ): social, enhancement, conformity, coping anxiety and coping depression]. We assessed alcohol use [alcohol use disorders identification test (AUDIT): quantity and frequency] and alcohol-related problems (AUDIT: related problems).FINDINGS: Within a given moment, social [partial correlation (pcor) = 0.17] and enhancement motives (pcor = 0.15) co-occurred most strongly with drinking quantity and frequency, while coping depression motives (pcor = 0.13), openness (pcor = 0.05) and impulsivity (pcor = 0.09) were related to alcohol-related problems. The temporal network showed no predictive associations between distal risk factors and drinking motives. Social motives (beta = 0.21), previous alcohol use (beta = 0.11) and openness (beta = 0.10) predicted alcohol-related problems over time (all P  &lt; 0.01).CONCLUSIONS: Heavy and frequent alcohol use, along with social drinking motives, appear to be key targets for preventing the development of alcohol-related problems throughout late adolescence. We found no evidence for personality traits and life stressors predisposingtowards distinct drinking motives over time.</div