Evidence for strong genetic correlations among internalizing psychopathology and related self-reported measures using both genomic and twin/adoptive approaches.

The internalizing construct captures shared variance underlying risk for mood and anxiety disorders. Internalizing factors based on diagnoses (or symptoms) of major depressive disorder (MDD) and generalized anxiety disorder (GAD) are well established. Studies have also integrated self-reported measures of associated traits (e.g., questionnaires assessing neuroticism, worry, and rumination) onto these factors, despite having not tested the assumption that these measures truly capture the same sets of risk factors. This study examined the overlap among both sets of measures using converging approaches. First, using genomic structural equation modeling, we constructed internalizing factors based on genome-wide association studies (GWASs) of internalizing diagnoses (e.g., MDD) and traits associated with internalizing (neuroticism, loneliness, and reverse-scored subjective well-being). Results indicated the two factors were highly (rg = .79) but not perfectly genetically correlated (rg < 1.0, p < .001). Second, we constructed similar latent factors in a combined twin/adoption sample of adults from the Colorado Adoption/Twin Study of Lifespan Behavioral Development and Cognitive Aging. Again, both factors demonstrated strong overlap at the level of genetic (rg = .76, 95% confidence interval [CI] [0.40, 0.97]) and nonshared environmental influences (re = .80, 95% CI [0.53, 1.0]). Shared environmental influences were estimated near zero for both factors. Our findings are consistent with current frameworks of psychopathology, though they suggest there are some unique genetic influences captured by internalizing diagnosis compared to trait measures, with potentially more nonadditive genetic influences on trait measures. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Systematic review of structural and functional neuroimaging studies of cannabis use in adolescence and emerging adulthood: evidence from 90 studies and 9441 participants.

Cannabis use peaks in adolescence, and adolescents may be more vulnerable to the neural effects of cannabis and cannabis-related harms due to ongoing brain development during this period. In light of ongoing cannabis policy changes, increased availability, reduced perceptions of harm, heightened interest in medicinal applications of cannabis, and drastic increases in cannabis potency, it is essential to establish an understanding of cannabis effects on the developing adolescent brain. This systematic review aims to: (1) synthesize extant literature on functional and structural neural alterations associated with cannabis use during adolescence and emerging adulthood; (2) identify gaps in the literature that critically impede our ability to accurately assess the effect of cannabis on adolescent brain function and development; and (3) provide recommendations for future research to bridge these gaps and elucidate the mechanisms underlying cannabis-related harms in adolescence and emerging adulthood, with the long-term goal of facilitating the development of improved prevention, early intervention, and treatment approaches targeting adolescent cannabis users (CU). Based on a systematic search of Medline and PsycInfo and other non-systematic sources, we identified 90 studies including 9441 adolescents and emerging adults (n = 3924 CU, n = 5517 non-CU), which provide preliminary evidence for functional and structural alterations in frontoparietal, frontolimbic, frontostriatal, and cerebellar regions among adolescent cannabis users. Larger, more rigorous studies are essential to reconcile divergent results, assess potential moderators of cannabis effects on the developing brain, disentangle risk factors for use from consequences of exposure, and elucidate the extent to which cannabis effects are reversible with abstinence. Guidelines for conducting this work are provided.

Electroencephalographic Correlates and Predictors of Treatment Outcome in OCD: A Brief Narrative Review.

Electroencephalography (EEG) measures the brain's electrical activity with high temporal resolution. In comparison to neuroimaging modalities such as MRI or PET, EEG is relatively cheap, non-invasive, portable, and simple to administer, making it an attractive tool for clinical deployment. Despite this, studies utilizing EEG to investigate obsessive-compulsive disorder (OCD) are relatively sparse. This contrasts with a robust literature using other brain imaging methodologies. The present review examines studies that have used EEG to examine predictors and correlates of response in OCD and draws tentative conclusions that may guide much needed future work. Key findings include a limited literature base; few studies have attempted to predict clinical change from EEG signals, and they are confounded by the effects of both pharmacotherapy and psychotherapy. The most robust literature, consisting of several studies, has examined event-related potentials, including the P300, which several studies have reported to be abnormal at baseline in OCD and to normalize with treatment; but even here the literature is quite heterogeneous, and more work is needed. With more robust research, we suggest that the relatively low cost and convenience of EEG, especially in comparison to fMRI and PET, make it well-suited to the development of feasible personalized treatment algorithms.