Heritability of risk-taking in adolescence: A longitudinal twin study

Adolescents are prone to risk-taking behaviors leading to adverse consequences such as substance abuse, accidents, violence, and victimization. However, little is known about the contribution of genetic and environmental factors to individual differences in the propensity for risk-taking. This study investigated developmental changes, longitudinal stability, and heritability of risk-taking using data from 752 adolescent twins including 169 MZ and 203 DZ pairs. The Balloon Analogue Risk Task (BART), an experimental behavioral measure of risk taking, was administered to the twins at age 12 and then re-administered to a part of this sample at age 14. Risk-taking increased with age, but individual differences showed a significant longitudinal stability. Genetic model fitting showed that at age 12, heritability of risk-taking was modest but significant in both sexes, whereas at age 14, heritability increased to 55% in males and became non-significant in females. The findings suggest that propensity for risk-taking as measured by BART can be a useful endophenotype for genetic studies of adolescent externalizing psychopathology, however, the utility of this measure may be limited by sex differences in heritability

Age-related changes and longitudinal stability of individual differences in ABCD Neurocognition measures

Temporal stability of individual differences is an important prerequisite for accurate tracking of prospective relationships between neurocognition and real-world behavioral outcomes such as substance abuse and psychopathology. Here we report age-related changes and longitudinal test-retest stability (TRS) for the Neurocognition battery of the Adolescent Brain and Cognitive Development (ABCD) study, which included the NIH Toolbox (TB) Cognitive Domain and additional memory and visuospatial processing tests administered at baseline (ages 9-11) and two-year follow-up. As expected, performance improved significantly with age, but the effect size varied broadly, with Pattern Comparison and the Crystallized Cognition Composite showing the largest age-related gain (Cohen\u27s d:.99 and.97, respectively). TRS ranged from fair (Flanker test: r = 0.44) to excellent (Crystallized Cognition Composite: r = 0.82). A comparison of longitudinal changes and cross-sectional age-related differences within baseline and follow-up assessments suggested that, for some measures, longitudinal changes may be confounded by practice effects and differences in task stimuli or procedure between baseline and follow-up. In conclusion, a subset of measures showed good stability of individual differences despite significant age-related changes, warranting their use as prospective predictors. However, caution is needed in the interpretation of observed longitudinal changes as indicators of neurocognitive development

Test-retest reliability of fMRI-measured brain activity during decision making under risk

Neural correlates of decision making under risk are being increasingly utilized as biomarkers of risk for substance abuse and other psychiatric disorders, treatment outcomes, and brain development. This research relies on the basic assumption that fMRI measures of decision making represent stable, trait-like individual differences. However, reliability needs to be established for each individual construct. Here we assessed long-term test-retest reliability (TRR) of regional brain activations related to decision making under risk using the Balloon Analogue Risk Taking task (BART) and identified regions with good TRRs and familial influences, an important prerequisite for the use of fMRI measures in genetic studies. A secondary goal was to examine the factors potentially affecting fMRI TRRs in one particular risk task, including the magnitude of neural activation, data analytical approaches, different methods of defining boundaries of a region, and participant motion. For the average BOLD response, reliabilities ranged across brain regions from poor to good (ICCs of 0 to 0.8, with a mean ICC of 0.17) and highest reliabilities were observed for parietal, occipital, and temporal regions. Among the regions that were of a priori theoretical importance due to their reported associations with decision making, the activation of left anterior insula and right caudate during the decision period showed the highest reliabilities (ICCs of 0.54 and 0.63, respectively). Among the regions with highest reliabilities, the right fusiform, right rostral anterior cingulate and left superior parietal regions also showed high familiality as indicated by intrapair monozygotic twin correlations (ranging from 0.66 to 0.69). Overall, regions identified by modeling the average BOLD response to a specific event type (rather than its modulation by a parametric regressor), regions including significantly activated vertices (compared to a whole parcel), and regions with greater magnitude of task-related activations showed greater reliabilities. Participant motion had a moderate negative effect on TRR. Regions activated during decision period rather than outcome period of risky decisions showed the greatest TRR and familiality. Regions with reliable activations can be utilized as neural markers of individual differences or endophenotypes in future clinical neuroscience and genetic studies of risk-taking

Test-retest reliability of neural correlates of response inhibition and error monitoring: An fMRI study of a stop-signal task

Response inhibition (RI) and error monitoring (EM) are important processes of adaptive goal-directed behavior, and neural correlates of these processes are being increasingly used as transdiagnostic biomarkers of risk for a range of neuropsychiatric disorders. Potential utility of these purported biomarkers relies on the assumption that individual differences in brain activation are reproducible over time; however, available data on test-retest reliability (TRR) of task-fMRI are very mixed. This study examined TRR of RI and EM-related activations using a stop signal task in young adults

Predicting alcohol-related memory problems in older adults: A machine learning study with multi-domain features

Memory problems are common among older adults with a history of alcohol use disorder (AUD). Employing a machine learning framework, the current study investigates the use of multi-domain features to classify individuals with and without alcohol-induced memory problems. A group of 94 individuals (ages 50-81 years) with alcohol-induced memory problems (the memory group) were compared with a matched control group who did not have memory problems. The random forests model identified specific features from each domain that contributed to the classification of the memory group vs. the control group (AUC = 88.29%). Specifically, individuals from the memory group manifested a predominant pattern of hyperconnectivity across the default mode network regions except for some connections involving the anterior cingulate cortex, which were predominantly hypoconnected. Other significant contributing features were: (i) polygenic risk scores for AUD, (ii) alcohol consumption and related health consequences during the past five years, such as health problems, past negative experiences, withdrawal symptoms, and the largest number of drinks in a day during the past twelve months, and (iii) elevated neuroticism and increased harm avoidance, and fewer positive uplift life events. At the neural systems level, hyperconnectivity across the default mode network regions, including the connections across the hippocampal hub regions, in individuals with memory problems may indicate dysregulation in neural information processing. Overall, the study outlines the importance of utilizing multidomain features, consisting of resting-state brain connectivity data collected ~18 years ago, together with personality, life experiences, polygenic risk, and alcohol consumption and related consequences, to predict the alcohol-related memory problems that arise in later life