Publications by authors named "Cupertino R"

Background And Aim: Cannabis use disorder (CUD) is strongly influenced by genetic factors; however the mechanisms underpinning this association are not well understood. This study investigated whether a polygenic risk score (PRS) based on a genome-wide association study for CUD in adults predicts cannabis use in adolescents and whether the association can be explained by inter-individual variation in structural properties of brain white matter or risk-taking behaviors.

Design And Setting: Longitudinal and cross-sectional analyses using data from the IMAGEN cohort, a European longitudinal study integrating genetic, neuroimaging and behavioral measures.

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Many psychopathologies tied to internalizing symptomatology emerge during adolescence, therefore identifying neural markers of internalizing behavior in childhood may allow for early intervention. We utilized data from the Adolescent Brain and Cognitive Development (ABCD) Study® to evaluate associations between cortico-amygdalar functional connectivity, polygenic risk for depression (PRS), traumatic events experienced, internalizing behavior, and internalizing subscales: withdrawn/depressed behavior, somatic complaints, and anxious/depressed behaviors. Data from 6371 children (ages 9-11) were used to analyze amygdala resting-state fMRI connectivity to Gordon parcellation based whole-brain regions of interest (ROIs).

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Article Synopsis
  • Cannabis is among the most widely used drugs around the world, and its decriminalization has led to increased consumption rates.
  • Genome-wide association studies (GWAS) on lifetime and frequency of cannabis use revealed genetic links to specific loci associated with these traits, indicating that both are heritable.
  • The findings suggest that genetic predispositions for cannabis use correlate with other substance use and mood disorders, highlighting the importance of understanding these genetic factors in the context of cannabis use disorder.
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Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder associated with brain differences in children, but not in adults. A combined evaluation of the regional brain differences could improve statistical power and, consequently, allow the detection of possible effects in adults. Thus, our aim is to verify whether Neuroimaging Association Scores (NAS) are associated with adulthood ADHD and clinical trajectories of the disorder in midlife.

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The default mode network (DMN) is atypically active in patients with ADHD, likely contributing to the inattention patterns observed in patients with the disorder. Nonetheless, magnetic resonance spectroscopy (MRS) studies have rarely targeted the posterior cingulate cortex, a key DMN region, and little is known about the biochemical setting within this network in patients with ADHD. We aimed to assess the differences in metabolite profiles of the posterior cingulate cortex-a key region of the DMN-between patients with ADHD and controls.

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Correlating transcriptional profiles with imaging-derived phenotypes has the potential to reveal possible molecular architectures associated with cognitive functions, brain development and disorders. Competitive null models built by resampling genes and self-contained null models built by spinning brain regions, along with varying test statistics, have been used to determine the significance of transcriptional associations. However, there has been no systematic evaluation of their performance in imaging transcriptomics analyses.

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Background: Alcohol consumption is associated with numerous negative social and health outcomes. These associations may be direct consequences of drinking, or they may reflect common genetic factors that influence both alcohol consumption and other outcomes.

Methods: We performed exploratory phenome-wide association studies (PheWAS) of three of the best studied protective single nucleotide polymorphisms (SNPs) in genes encoding ethanol metabolising enzymes (ADH1B: rs1229984-T, rs2066702-A; ADH1C: rs698-T) using up to 1109 health outcomes across 28 phenotypic categories (e.

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Article Synopsis
  • Scientists are worried about wrong size estimates (called effect sizes) in small studies about how different drugs affect the brain, so they designed a new model to fix this.
  • They looked at differences in brain features between people who are addicted to certain drugs and those who aren’t, using data from 21 studies with almost 2,000 participants.
  • The study found that smaller studies often had bigger changes in their results when adjusted, showing that using information from other studies can help make results more accurate.
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  • The study confirmed that structural covariance networks (SCN) from MRI data can identify heavy alcohol users and predict problematic drinking behavior in adolescents and young adults.
  • It utilized data from three independent studies with participants aged 14 to 37, comparing heavy drinkers (cases) to those with low or no alcohol use (controls).
  • Key findings showed that heavy drinkers had distinct brain network characteristics, indicating differences in brain region thickness and connectivity, which could help in understanding alcohol use disorders.
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Leveraging ~10 years of prospective longitudinal data on 704 participants, we examined the effects of adolescent versus young adult cannabis initiation on MRI-assessed cortical thickness development and behavior. Data were obtained from the IMAGEN study conducted across eight European sites. We identified IMAGEN participants who reported being cannabis-naïve at baseline and had data available at baseline, 5-year, and 9-year follow-up visits.

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Several GWAS reported Myocyte Enhancer Factor 2 C (MEF2C) gene associations with white matter microstructure and psychiatric disorders, and MEF2C involvement in pathways related to neuronal development suggests a common biological factor underlying these phenotypes. We aim to refine the MEF2C effects in the brain relying on an integrated analysis of white matter and psychiatric phenotypes in an extensively characterized sample. This study included 870 Brazilian adults (47% from an attention-deficit/hyperactivity disorder outpatient clinic) assessed through standardized psychiatric interviews, 139 of which underwent a magnetic resonance imaging scan.

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The course of ADHD from childhood up to young adulthood has been characterized in several studies. However, little is known about the course of symptoms into middle age and beyond. This study aims to evaluate predictors of ADHD trajectories in midlife based on three assessments.

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The neurobiological bases of the association between development and psychopathology remain poorly understood. Here, we identify a shared spatial pattern of cortical thickness (CT) in normative development and several psychiatric and neurological disorders. Principal component analysis (PCA) was applied to CT of 68 regions in the Desikan-Killiany atlas derived from three large-scale datasets comprising a total of 41,075 neurotypical participants.

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Importance: Past studies have identified associations between brain macrostructure and alcohol use behaviors. However, identifying directional associations between these phenotypes is difficult due to the limitations of observational studies.

Objective: To use mendelian randomization (MR) to identify directional associations between brain structure and alcohol use and elucidate the transcriptomic and cellular underpinnings of identified associations.

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While there is substantial evidence that cannabis use is associated with differences in human brain development, most of this evidence is correlational in nature. Bayesian causal network (BCN) modeling attempts to identify probable causal relationships in correlational data using conditional probabilities to estimate directional associations between a set of interrelated variables. In this study, we employed BCN modeling in 637 adolescents from the IMAGEN study who were cannabis naïve at age 14 to provide evidence that the accelerated prefrontal cortical thinning found previously in adolescent cannabis users by Albaugh et al.

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Article Synopsis
  • The study examines the differences in the morphology of the human cerebral cortex across various psychiatric disorders, suggesting that early growth patterns in the cortex may influence later variations in surface area and mental health outcomes.
  • Using data from over 27,000 MRI scans, researchers identified significant differences in cortical area among individuals with conditions like ADHD, schizophrenia, and major depression, particularly in association cortices linked to cognitive processing.
  • The findings indicate a correlation between these structural differences and prenatal gene expression related to cell types important for brain development, highlighting how prenatal factors may play a crucial role in the risk of developing mental illnesses.
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One of the main challenges in investigating the neurobiology of ADHD is our limited capacity to study its neurochemistry in vivo. Magnetic resonance spectroscopy (MRS) estimates metabolite concentrations within the brain, but approaches and findings have been heterogeneous. To assess differences in brain metabolites between patients with ADHD and healthy controls, we searched 12 databases screening for MRS studies.

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The Forkhead box P2 (FOXP2) encodes for a transcription factor with a broad role in embryonic development. It is especially represented among GWAS hits for neurodevelopmental disorders and related traits, including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, neuroticism, and risk-taking behaviors. While several functional studies are underway to understand the consequences of FOXP2 variation, this study aims to expand previous findings to clinically and genetically related phenotypes and neuroanatomical features among subjects with ADHD.

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Mixed findings exist in studies comparing brain responses to reward in adolescents and adults. Here we examined the trajectories of brain response, functional connectivity and task-modulated network properties during reward processing with a large-sample longitudinal design. Participants from the IMAGEN study performed a Monetary Incentive Delay task during fMRI at timepoint 1 (T1; n = 1304, mean age=14.

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Background: Nicotine and illicit stimulants are very addictive substances. Although associations between grey matter and dependence on stimulants have been frequently reported, white matter correlates have received less attention.

Methods: Eleven international sites ascribed to the ENIGMA-Addiction consortium contributed data from individuals with dependence on cocaine (n = 147), methamphetamine (n = 132) and nicotine (n = 189), as well as non-dependent controls (n = 333).

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Article Synopsis
  • ADHD can make certain parts of the brain smaller, especially in kids compared to adults.
  • The study looked at a specific gene (NR3C1) that might help explain why these brain changes happen in adults with ADHD.
  • Researchers found two specific gene variations that seem to affect brain areas linked to ADHD and could influence how the body's stress response works.
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White matter (WM) abnormalities in patients with cocaine use disorder (CUD) have been studied; however, the reported effects on the human brain are heterogenous and most results have been obtained from male participants. In addition, biological data supporting the imaging findings and revealing possible mechanisms underlying the neurotoxic effects of chronic cocaine use (CU) on WM are largely restricted to animal studies. To evaluate the neurotoxic effects of CU in the WM, we performed an in vivo diffusion tensor imaging assessment of male and female cocaine users (n = 75) and healthy controls (HC) (n = 58).

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Objective: Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium.

Methods: We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls.

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Despite major advances in the study of the brain, investigations on neurochemistry in vivo still lack the solid ground of more established methods, such as structural and functional magnetic resonance imaging. Proton magnetic resonance spectroscopy (MRS) is a technique that might potentially fill in this gap. Nevertheless, studies using this approach feature great methodological heterogeneity, such as varying voxel of choice, differences on emphasized metabolites, and absence of a standardized unit.

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Brain asymmetry reflects left-right hemispheric differentiation, which is a quantitative brain phenotype that develops with age and can vary with psychiatric diagnoses. Previous studies have shown that substance dependence is associated with altered brain structure and function. However, it is unknown whether structural brain asymmetries are different in individuals with substance dependence compared with nondependent participants.

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