RESUMO
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. Here, we evaluated the performance of eight different test statistics (mean, mean absolute value, mean squared value, max mean, median, Kolmogorov-Smirnov (KS), Weighted KS and the number of significant correlations) in both competitive null models and self-contained null models. Simulated brain maps (n = 1,000) and gene sets (n = 500) were used to calculate the probability of significance (Psig) for each statistical test. Our results suggested that competitive null models may result in false positive results driven by co-expression within gene sets. Furthermore, we demonstrated that the self-contained null models may fail to account for distribution characteristics (e.g., bimodality) of correlations between all available genes and brain phenotypes, leading to false positives. These two confounding factors interacted differently with test statistics, resulting in varying outcomes. Specifically, the sign-sensitive test statistics (i.e., mean, median, KS, Weighted KS) were influenced by co-expression bias in the competitive null models, while median and sign-insensitive test statistics were sensitive to the bimodality bias in the self-contained null models. Additionally, KS-based statistics produced conservative results in the self-contained null models, which increased the risk of false negatives. Comprehensive supplementary analyses with various configurations, including realistic scenarios, supported the results. These findings suggest utilizing sign-insensitive test statistics such as mean absolute value, max mean in the competitive null models and the mean as the test statistic for the self-contained null models. Additionally, adopting the confounder-matched (e.g., coexpression-matched) null models as an alternative to standard null models can be a viable strategy. Overall, the present study offers insights into the selection of statistical tests for imaging transcriptomics studies, highlighting areas for further investigation and refinement in the evaluation of novel and commonly used tests.
Assuntos
Encéfalo , Fenótipo , Encéfalo/diagnóstico por imagem , Encéfalo/anatomia & histologia , Humanos , Transcriptoma , Modelos Estatísticos , Perfilação da Expressão Gênica/métodosRESUMO
Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.
Assuntos
Transtorno Bipolar , Imageamento por Ressonância Magnética , Obesidade , Análise de Componente Principal , Humanos , Transtorno Bipolar/diagnóstico por imagem , Transtorno Bipolar/tratamento farmacológico , Transtorno Bipolar/patologia , Adulto , Feminino , Masculino , Imageamento por Ressonância Magnética/métodos , Pessoa de Meia-Idade , Obesidade/diagnóstico por imagem , Esquizofrenia/diagnóstico por imagem , Esquizofrenia/patologia , Esquizofrenia/tratamento farmacológico , Esquizofrenia/fisiopatologia , Córtex Cerebral/diagnóstico por imagem , Córtex Cerebral/patologia , Análise por Conglomerados , Adulto Jovem , Encéfalo/diagnóstico por imagem , Encéfalo/patologiaRESUMO
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. Cannabis use was assessed with the European School Survey Project on Alcohol and Drugs. T1-weighted MR images were processed through the CIVET pipeline. Cannabis initiation occurring during adolescence (14-19 years) and young adulthood (19-22 years) was associated with differing patterns of longitudinal cortical thickness change. Associations between adolescent cannabis initiation and cortical thickness change were observed primarily in dorso- and ventrolateral portions of the prefrontal cortex. In contrast, cannabis initiation occurring between 19 and 22 years of age was associated with thickness change in temporal and cortical midline areas. Follow-up analysis revealed that longitudinal brain change related to adolescent initiation persisted into young adulthood and partially mediated the association between adolescent cannabis use and past-month cocaine, ecstasy, and cannabis use at age 22. Extent of cannabis initiation during young adulthood (from 19 to 22 years) had an indirect effect on psychotic symptoms at age 22 through thickness change in temporal areas. Results suggest that developmental timing of cannabis exposure may have a marked effect on neuroanatomical correlates of cannabis use as well as associated behavioral sequelae. Critically, this work provides a foundation for neurodevelopmentally informed models of cannabis exposure in humans.
RESUMO
Emerging evidence suggests distinct neurobiological correlates of alcohol use disorder (AUD) between sexes, which however remain largely unexplored. This work from ENIGMA Addiction Working Group aimed to characterize the sex differences in gray matter (GM) and white matter (WM) correlates of AUD using a whole-brain, voxel-based, multi-tissue mega-analytic approach, thereby extending our recent surface-based region of interest findings on a nearly matching sample using a complementary methodological approach. T1-weighted magnetic resonance imaging (MRI) data from 653 people with AUD and 326 controls was analyzed using voxel-based morphometry. The effects of group, sex, group-by-sex, and substance use severity in AUD on brain volumes were assessed using General Linear Models. Individuals with AUD relative to controls had lower GM volume in striatal, thalamic, cerebellar, and widespread cortical clusters. Group-by-sex effects were found in cerebellar GM and WM volumes, which were more affected by AUD in females than males. Smaller group-by-sex effects were also found in frontotemporal WM tracts, which were more affected in AUD females, and in temporo-occipital and midcingulate GM volumes, which were more affected in AUD males. AUD females but not males showed a negative association between monthly drinks and precentral GM volume. Our results suggest that AUD is associated with both shared and distinct widespread effects on GM and WM volumes in females and males. This evidence advances our previous region of interest knowledge, supporting the usefulness of adopting an exploratory perspective and the need to include sex as a relevant moderator variable in AUD.
Assuntos
Alcoolismo , Humanos , Feminino , Masculino , Alcoolismo/diagnóstico por imagem , Encéfalo/diagnóstico por imagem , Encéfalo/patologia , Substância Cinzenta/diagnóstico por imagem , Substância Cinzenta/patologia , Consumo de Bebidas Alcoólicas , Imageamento por Ressonância Magnética/métodosRESUMO
Alcohol use disorder (AUD) and cannabis use disorder (CUD) are associated with brain alterations particularly involving fronto-cerebellar and meso-cortico-limbic circuitry. However, such abnormalities have additionally been reported in other psychiatric conditions, and until recently there has been few large-scale investigations to compare such findings. The current study uses the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium method of standardising structural brain measures to quantify case-control differences and to compare brain-correlates of substance use disorders with those published in relation to other psychiatric disorders. Using the ENIGMA protocols, we report effect sizes derived from a meta-analysis of alcohol (seven studies, N = 798, 54% are cases) and cannabis (seven studies, N = 447, 45% are cases) dependent cases and age- and sex-matched controls. We conduct linear analyses using harmonised methods to process and parcellate brain data identical to those reported in the literature for ENIGMA case-control studies of major depression disorder (MDD), schizophrenia (SCZ) and bipolar disorder so that effect sizes are optimally comparable across disorders. R elationships between substance use disorder diagnosis and subcortical grey matter volumes and cortical thickness were assessed with intracranial volume, age and sex as co-variates . After correcting for multiple comparisons, AUD case-control meta-analysis of subcortical regions indicated significant differences in the thalamus, hippocampus, amygdala and accumbens, with effect sizes (0.23) generally equivalent to, or larger than |0.23| those previously reported for other psychiatric disorders (except for the pallidum and putamen). On measures of cortical thickness, AUD was associated with significant differences bilaterally in the fusiform gyrus, inferior temporal gyrus, temporal pole, superior frontal gyrus, and rostral and caudal anterior cingulate gyri. Meta-analysis of CUD case-control studies indicated reliable reductions in amygdala, accumbens and hippocampus volumes, with the former effect size comparable to, and the latter effect size around half of that reported for alcohol and SCZ. CUD was associated with lower cortical thickness in the frontal regions, particularly the medial orbitofrontal region, but this effect was not significant after correcting for multiple testing. This study allowed for an unbiased cross-disorder comparison of brain correlates of substance use disorders and showed alcohol-related brain anomalies equivalent in effect size to that found in SCZ in several subcortical and cortical regions and significantly greater alterations than those found in MDD in several subcortical and cortical regions. Although modest, CUD results overlapped with findings reported for AUD and other psychiatric conditions, but appear to be most robustly related to reduce thickness of the medial orbitofrontal cortex.
Assuntos
Transtorno Bipolar/patologia , Encéfalo/patologia , Transtorno Depressivo Maior/patologia , Imageamento por Ressonância Magnética , Neuroimagem , Esquizofrenia/patologia , Transtornos Relacionados ao Uso de Substâncias/patologia , Transtorno Bipolar/diagnóstico por imagem , Encéfalo/diagnóstico por imagem , Transtorno Depressivo Maior/diagnóstico por imagem , Humanos , Esquizofrenia/diagnóstico por imagem , Transtornos Relacionados ao Uso de Substâncias/diagnóstico por imagemRESUMO
Gray matter volume (GMV) in frontal cortical and limbic regions is susceptible to cocaine-associated reductions in cocaine-dependent individuals (CD) and is negatively associated with duration of cocaine use. Gender differences in CD individuals have been reported clinically and in the context of neural responses to cue-induced craving and stress reactivity. The variability of GMV in select brain areas between men and women (e.g., limbic regions) underscores the importance of exploring interaction effects between gender and cocaine dependence on brain structure. Therefore, voxel-based morphometry data derived from the ENIGMA Addiction Consortium were used to investigate potential gender differences in GMV in CD individuals compared to matched controls (CTL). T1-weighted MRI scans and clinical data were pooled from seven sites yielding 420 gender- and age-matched participants: CD men (CDM, n = 140); CD women (CDW, n = 70); control men (CTLM, n = 140); and control women (CTLW, n = 70). Differences in GMV were assessed using a 2 × 2 ANCOVA, and voxelwise whole-brain linear regressions were conducted to explore relationships between GMV and duration of cocaine use. All analyses were corrected for age, total intracranial volume, and site. Diagnostic differences were predominantly found in frontal regions (CD < CTL). Interestingly, gender × diagnosis interactions in the left anterior insula and left lingual gyrus were also documented, driven by differences in women (CDW < CTLW). Further, lower right hippocampal GMV was associated with greater cocaine duration in CDM. Given the importance of the anterior insula to interoception and the hippocampus to learning contextual associations, results may point to gender-specific mechanisms in cocaine addiction.
Assuntos
Córtex Cerebral/patologia , Transtornos Relacionados ao Uso de Cocaína/patologia , Substância Cinzenta/patologia , Imageamento por Ressonância Magnética , Neuroimagem , Caracteres Sexuais , Adulto , Córtex Cerebral/diagnóstico por imagem , Transtornos Relacionados ao Uso de Cocaína/diagnóstico por imagem , Feminino , Substância Cinzenta/diagnóstico por imagem , Humanos , Masculino , Pessoa de Meia-IdadeRESUMO
To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification models that are explicitly generalizable to unseen sites and populations. This problem was explored in a mega-analysis of previously published datasets from 2,034 AD and comparison participants spanning 27 sites curated by the ENIGMA Addiction Working Group. Data were grouped into a training set used for internal validation including 1,652 participants (692 AD, 24 sites), and a test set used for external validation with 382 participants (146 AD, 3 sites). An exploratory data analysis was first conducted, followed by an evolutionary search based feature selection to site generalizable and high performing subsets of brain measurements. Exploratory data analysis revealed that inclusion of case- and control-only sites led to the inadvertent learning of site-effects. Cross validation methods that do not properly account for site can drastically overestimate results. Evolutionary-based feature selection leveraging leave-one-site-out cross-validation, to combat unintentional learning, identified cortical thickness in the left superior frontal gyrus and right lateral orbitofrontal cortex, cortical surface area in the right transverse temporal gyrus, and left putamen volume as final features. Ridge regression restricted to these features yielded a test-set area under the receiver operating characteristic curve of 0.768. These findings evaluate strategies for handling multi-site data with varied underlying class distributions and identify potential biomarkers for individuals with current AD.
Assuntos
Alcoolismo/diagnóstico por imagem , Córtex Cerebral/diagnóstico por imagem , Aprendizado de Máquina , Imageamento por Ressonância Magnética , Estudos Multicêntricos como Assunto , Neuroimagem , Putamen/diagnóstico por imagem , Córtex Cerebral/patologia , Humanos , Imageamento por Ressonância Magnética/métodos , Imageamento por Ressonância Magnética/normas , Estudos Multicêntricos como Assunto/métodos , Estudos Multicêntricos como Assunto/normas , Neuroimagem/métodos , Neuroimagem/normas , Putamen/patologia , Reprodutibilidade dos TestesRESUMO
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. Here, a mega-analysis was performed using a collection of 22 structural brain MRI datasets from the ENIGMA Addiction Working Group. Structural asymmetries of cortical and subcortical regions were compared between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis (n = 1,796) and nondependent participants (n = 996). Substance-general and substance-specific effects on structural asymmetry were examined using separate models. We found that substance dependence was significantly associated with differences in volume asymmetry of the nucleus accumbens (NAcc; less rightward; Cohen's d = 0.15). This effect was driven by differences from controls in individuals with alcohol dependence (less rightward; Cohen's d = 0.10) and nicotine dependence (less rightward; Cohen's d = 0.11). These findings suggest that disrupted structural asymmetry in the NAcc may be a characteristic of substance dependence.
Assuntos
Córtex Cerebelar/patologia , Transtornos Relacionados ao Uso de Substâncias/diagnóstico por imagem , Adulto , Alcoolismo/diagnóstico por imagem , Comportamento Aditivo/diagnóstico por imagem , Encéfalo/patologia , Espessura Cortical do Cérebro , Feminino , Humanos , Imageamento por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Neuroimagem , Núcleo Accumbens/patologia , Tabagismo/diagnóstico por imagem , Adulto JovemRESUMO
Rates of cannabis use among adolescents are high, and are increasing concurrent with changes in the legal status of marijuana and societal attitudes regarding its use. Recreational cannabis use is understudied, especially in the adolescent period when neural maturation may make users particularly vulnerable to the effects of Δ-9-tetrahydrocannabinol (THC) on brain structure. In the current study, we used voxel-based morphometry to compare gray matter volume (GMV) in forty-six 14-year-old human adolescents (males and females) with just one or two instances of cannabis use and carefully matched THC-naive controls. We identified extensive regions in the bilateral medial temporal lobes as well as the bilateral posterior cingulate, lingual gyri, and cerebellum that showed greater GMV in the cannabis users. Analysis of longitudinal data confirmed that GMV differences were unlikely to precede cannabis use. GMV in the temporal regions was associated with contemporaneous performance on the Perceptual Reasoning Index and with future generalized anxiety symptoms in the cannabis users. The distribution of GMV effects mapped onto biomarkers of the endogenous cannabinoid system providing insight into possible mechanisms for these effects.SIGNIFICANCE STATEMENT Almost 35% of American 10th graders have reported using cannabis and existing research suggests that initiation of cannabis use in adolescence is associated with long-term neurocognitive effects. We understand very little about the earliest effects of cannabis use, however, because most research is conducted in adults with a heavy pattern of lifetime use. This study presents evidence suggesting structural brain and cognitive effects of just one or two instances of cannabis use in adolescence. Converging evidence suggests a role for the endocannabinoid system in these effects. This research is particularly timely as the legal status of cannabis is changing in many jurisdictions and the perceived risk by youth associated with smoking cannabis has declined in recent years.
Assuntos
Encéfalo/patologia , Substância Cinzenta/patologia , Fumar Maconha/patologia , Adolescente , Cerebelo/patologia , Feminino , Giro do Cíngulo/patologia , Humanos , Masculino , Lobo Temporal/patologiaRESUMO
Youths with attention-deficit/hyperactivity disorder symptomatology often exhibit residual inattention and/or hyperactivity in adulthood; however, this is not true for all individuals. We recently reported that dimensional, multi-informant ratings of hyperactive/inattentive symptoms are associated with ventromedial prefrontal cortex (vmPFC) structure. Herein, we investigate the degree to which vmPFC structure during adolescence predicts hyperactive/inattentive symptomatology at 5-year follow-up. Structural equation modeling was used to test the extent to which adolescent vmPFC volume predicts hyperactive/inattentive symptomatology 5 years later in early adulthood. 1104 participants (M = 14.52 years, standard deviation = 0.42; 583 females) possessed hyperactive/inattentive symptom data at 5-year follow-up, as well as quality controlled neuroimaging data and complete psychometric data at baseline. Self-reports of hyperactive/inattentive symptomatology were obtained during adolescence and at 5-year follow-up using the Strengths and Difficulties Questionnaire (SDQ). At baseline and 5-year follow-up, a hyperactive/inattentive latent variable was derived from items on the SDQ. Baseline vmPFC volume predicted adult hyperactive/inattentive symptomatology (standardized coefficient = -0.274, P < 0.001) while controlling for baseline hyperactive/inattentive symptomatology. These results are the first to reveal relations between adolescent brain structure and adult hyperactive/inattentive symptomatology, and suggest that early structural development of the vmPFC may be consequential for the subsequent expression of hyperactive/inattentive symptoms.
Assuntos
Transtorno do Deficit de Atenção com Hiperatividade/diagnóstico por imagem , Transtorno do Deficit de Atenção com Hiperatividade/patologia , Córtex Pré-Frontal/diagnóstico por imagem , Córtex Pré-Frontal/patologia , Adolescente , Adulto , Atenção/fisiologia , Feminino , Humanos , Estudos Longitudinais , Imageamento por Ressonância Magnética , Masculino , Tamanho do Órgão , Agitação Psicomotora/diagnóstico por imagem , Agitação Psicomotora/patologia , Adulto JovemRESUMO
While imaging studies have demonstrated volumetric differences in subcortical structures associated with dependence on various abused substances, findings to date have not been wholly consistent. Moreover, most studies have not compared brain morphology across those dependent on different substances of abuse to identify substance-specific and substance-general dependence effects. By pooling large multinational datasets from 33 imaging sites, this study examined subcortical surface morphology in 1628 nondependent controls and 2277 individuals with dependence on alcohol, nicotine, cocaine, methamphetamine, and/or cannabis. Subcortical structures were defined by FreeSurfer segmentation and converted to a mesh surface to extract two vertex-level metrics-the radial distance (RD) of the structure surface from a medial curve and the log of the Jacobian determinant (JD)-that, respectively, describe local thickness and surface area dilation/contraction. Mega-analyses were performed on measures of RD and JD to test for the main effect of substance dependence, controlling for age, sex, intracranial volume, and imaging site. Widespread differences between dependent users and nondependent controls were found across subcortical structures, driven primarily by users dependent on alcohol. Alcohol dependence was associated with localized lower RD and JD across most structures, with the strongest effects in the hippocampus, thalamus, putamen, and amygdala. Meanwhile, nicotine use was associated with greater RD and JD relative to nonsmokers in multiple regions, with the strongest effects in the bilateral hippocampus and right nucleus accumbens. By demonstrating subcortical morphological differences unique to alcohol and nicotine use, rather than dependence across all substances, results suggest substance-specific relationships with subcortical brain structures.
Assuntos
Encéfalo/diagnóstico por imagem , Neuroimagem , Transtornos Relacionados ao Uso de Substâncias/diagnóstico por imagem , Adolescente , Adulto , Cannabis/efeitos adversos , Cocaína/efeitos adversos , Etanol/efeitos adversos , Feminino , Humanos , Imageamento por Ressonância Magnética , Masculino , Metanfetamina/efeitos adversos , Nicotina/efeitos adversos , Adulto JovemRESUMO
Cannabis use initiated during adolescence might precipitate negative consequences in adulthood. Thus, predicting adolescent cannabis use prior to any exposure will inform the aetiology of substance abuse by disentangling predictors from consequences of use. In this prediction study, data were drawn from the IMAGEN sample, a longitudinal study of adolescence. All selected participants (n = 1,581) were cannabis-naïve at age 14. Those reporting any cannabis use (out of six ordinal use levels) by age 16 were included in the outcome group (N = 365, males n = 207). Cannabis-naïve participants at age 14 and 16 were included in the comparison group (N = 1,216, males n = 538). Psychosocial, brain and genetic features were measured at age 14 prior to any exposure. Cross-validated regularized logistic regressions for each use level by sex were used to perform feature selection and obtain prediction error statistics on independent observations. Predictors were probed for sex- and drug-specificity using post-hoc logistic regressions. Models reliably predicted use as indicated by satisfactory prediction error statistics, and contained psychosocial features common to both sexes. However, males and females exhibited distinct brain predictors that failed to predict use in the opposite sex or predict binge drinking in independent samples of same-sex participants. Collapsed across sex, genetic variation on catecholamine and opioid receptors marginally predicted use. Using machine learning techniques applied to a large multimodal dataset, we identified a risk profile containing psychosocial and sex-specific brain prognostic markers, which were likely to precede and influence cannabis initiation.
Assuntos
Comportamento do Adolescente/psicologia , Encéfalo/diagnóstico por imagem , Uso da Maconha/genética , Uso da Maconha/psicologia , Caracteres Sexuais , Comportamento Social , Adolescente , Comportamento do Adolescente/fisiologia , Feminino , Previsões , Humanos , Estudos Longitudinais , Imageamento por Ressonância Magnética/métodos , Imageamento por Ressonância Magnética/tendências , MasculinoRESUMO
BACKGROUND: Research suggests that substance use disorders and disordered eating are often comorbid. In light of the ongoing opioid epidemic, the purpose of the current study was to understand the prevalence and health-related correlates of loss of control (LOC) eating in adults seeking methadone maintenance treatment primarily for addiction to heroin and/or painkillers. METHODS: Participants were 447 adults surveyed at presentation for methadone maintenance treatment who responded to survey items on LOC eating. Descriptive statistics were used to investigate the prevalence of engaging in LOC eating in the past 2 weeks. Chi-square tests, t tests, and analyses of covariance were used to compare individuals with (LOC+; n = 164) and without (LOC-; n = 283) recent LOC eating on psychosocial, pain-related, and weight-related characteristics. RESULTS: Approximately one third of respondents endorsed LOC eating in the past 2 weeks. These participants reported greater affective symptoms, interpersonal dysfunction, pain intensity, and pain interference than the LOC- group (Cohen's d effect size range = .24-.94). LOC+ was also more likely to have engaged in recent illicit drug use and to report having concurrent overweight/obesity (φ effect size range = .09-.10). CONCLUSION: The prevalence of LOC eating in adults seeking methadone maintenance treatment was more than triple what has been reported in previous studies using community samples. Given its associations with other health-related variables, the presence of LOC eating may be a marker for more severe psychopathology in individuals seeking methadone maintenance treatment. Future research is needed to understand mechanisms explaining this comorbidity and to develop novel ways to prevent and treat their co-occurrence.
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Ingestão de Alimentos/psicologia , Transtornos da Alimentação e da Ingestão de Alimentos/epidemiologia , Metadona/administração & dosagem , Transtornos Relacionados ao Uso de Substâncias/reabilitação , Adulto , Comorbidade , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Obesidade/epidemiologia , Sobrepeso/epidemiologia , Dor/epidemiologia , Prevalência , Inquéritos e QuestionáriosRESUMO
In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) - a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date - of schizophrenia and major depression - ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others1, ENIGMA's genomic screens - now numbering over 30,000 MRI scans - have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants - and genetic variants in general - may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures - from tens of thousands of people - that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far.
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Encefalopatias , Estudo de Associação Genômica Ampla , Transtornos Mentais , Estudos Multicêntricos como Assunto , Encefalopatias/diagnóstico por imagem , Encefalopatias/genética , Encefalopatias/patologia , Encefalopatias/fisiopatologia , Humanos , Transtornos Mentais/diagnóstico por imagem , Transtornos Mentais/genética , Transtornos Mentais/patologia , Transtornos Mentais/fisiopatologiaRESUMO
[11C]-dihydrotetrabenazine (DTBZ) Positron Emission Tomography was used to evaluate the vesicular monoamine transporter type 2 as an index of dopaminergic function in the striatum of adult Sprague-Dawley rats obtained from two different animal sources (Charles River Laboratories [CR] or UBC's Animal Care Centre [ACC]) and later submitted to two different unilateral lesions of the nigro-striatal pathway. The results showed a significant difference in the striatal binding potential (BP(ND)) at baseline (before lesioning) between the CR and ACC groups providing evidence that the origin of the animals, possibly due to differences in early environmental factors or breeding conditions associated with different animal vendors plays a role in the development of the adult dopaminergic system. Further, in both animal models, an increase in DTBZ BP(ND) was observed, after unilateral intervention, in the striatum contralateral to the lesion, likely reflecting compensatory effects. Based on these findings, we conclude that in unilateral models, the unlesioned side/hemisphere may not be an appropriate control and that care should be taken to control for the origin of the animals in any given study, especially in longitudinal and replication studies.
Assuntos
Compostos Radiofarmacêuticos/farmacocinética , Tetrabenazina/análogos & derivados , Proteínas Vesiculares de Transporte de Monoamina/metabolismo , Análise de Variância , Animais , Corpo Estriado/diagnóstico por imagem , Corpo Estriado/metabolismo , Interpretação Estatística de Dados , Tomografia por Emissão de Pósitrons/métodos , Tomografia por Emissão de Pósitrons/normas , Ligação Proteica , Ratos , Ratos Sprague-Dawley , Especificidade da Espécie , Tetrabenazina/farmacocinéticaRESUMO
A previous report identified the location of comparable architectonic areas in the ventral frontal cortex of the human and macaque brains [S. Mackey & M. Petrides (2010) Eur. J. Neurosci., 32, 1940-1950]. The present article provides greater detail with regard to the definition of architectonic areas within the ventromedial part of the human ventral frontal cortex and describes their location: (i) in Montreal Neurological Institute proportional stereotactic space; and (ii) in relation to sulcal landmarks. Structural magnetic resonance scans of four brains were obtained before the preparation of the histological specimens, so that the architectonic parcellation could be reconstructed in its original three-dimensional volume. The areal density of individual cortical layers was sampled quantitatively in the ventromedial prefrontal cortex of eight brains (16 hemispheres). The agranular cortex along the ventral edge of the corpus callosum and posterior margin of the ventromedial surface is replaced by a graded series of increasingly granular and more complexly laminated areas that succeed one another in a posterior-to-anterior direction. In parallel, the width of the supragranular layers (i.e. layers II and III) increases as compared with the infragranular layers (i.e. layers V and VI) from posterior to anterior. A measure of how rapidly cortical features change at areal boundaries also showed that the rate of change in the granule and pyramidal cell densities of layers IV and V, respectively, was greater at the borders between posterior areas than between anterior areas. This article will facilitate the anatomical identification and comparison of experimental data involving the human vmPFC.
Assuntos
Córtex Pré-Frontal/anatomia & histologia , Idoso , Feminino , Humanos , Imageamento por Ressonância Magnética , Masculino , Neurônios/citologia , FotomicrografiaRESUMO
The extent to which neuroanatomical variability associated with substance involvement reflects pre-existing risk and/or consequences of substance exposure remains poorly understood. In the Adolescent Brain Cognitive DevelopmentSM (ABCD®) Study, we identify associations between global and regional differences in brain structure and early substance use initiation (i.e., occurring <15 years of age; nsanalytic=6,556-9,804), with evidence that associations precede initiation. Neurodevelopmental variability in brain structure may confer risk for substance involvement.
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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 (PRSD), 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). Internalizing behaviors were measured using the parent-reported Child Behavior Checklist. Linear mixed-effects models were used to identify patterns of cortico-amygdalar connectivity associated with internalizing behaviors. Results indicated left amygdala connections to auditory, frontoparietal network (FPN), and dorsal attention network (DAN) ROIs were significantly associated with withdrawn/depressed symptomatology. Connections relevant for withdrawn/depressed behavior were linked to social behaviors. Specifically, amygdala connections to DAN were associated with social anxiety, social impairment, and social problems. Additionally, an amygdala connection to the FPN ROI and the auditory network ROI was associated with social anxiety and social problems, respectively. Therefore, it may be important to account for social behaviors when looking for brain correlates of depression.
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BACKGROUND AND AIMS: The brain age gap (BAG), calculated as the difference between a machine learning model-based predicted brain age and chronological age, has been increasingly investigated in psychiatric disorders. Tobacco and alcohol use are associated with increased BAG; however, no studies have compared global and regional BAG across substances other than alcohol and tobacco. This study aimed to compare global and regional estimates of brain age in individuals with substance use disorders and healthy controls. DESIGN: This was a cross-sectional study. SETTING: This is an Enhancing Neuro Imaging through Meta-Analysis Consortium (ENIGMA) Addiction Working Group study including data from 38 global sites. PARTICIPANTS: This study included 2606 participants, of whom 1725 were cases with a substance use disorder and 881 healthy controls. MEASUREMENTS: This study used the Kaufmann brain age prediction algorithms to generate global and regional brain age estimates using T1 weighted magnetic resonance imaging (MRI) scans. We used linear mixed effects models to compare global and regional (FreeSurfer lobestrict output) BAG (i.e. predicted minus chronological age) between individuals with one of five primary substance use disorders as well as healthy controls. FINDINGS: Alcohol use disorder (ß = -5.49, t = -5.51, p < 0.001) was associated with higher global BAG, whereas amphetamine-type stimulant use disorder (ß = 3.44, t = 2.42, p = 0.02) was associated with lower global BAG in the separate substance-specific models. CONCLUSIONS: People with alcohol use disorder appear to have a higher brain-age gap than people without alcohol use disorder, which is consistent with other evidence of the negative impact of alcohol on the brain.
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Background: Males and females who consume cannabis can experience different mental health and cognitive problems. Neuroscientific theories of addiction postulate that dependence is underscored by neuroadaptations, but do not account for the contribution of distinct sexes. Further, there is little evidence for sex differences in the neurobiology of cannabis dependence as most neuroimaging studies have been conducted in largely male samples in which cannabis dependence, as opposed to use, is often not ascertained. Methods: We examined subregional hippocampus and amygdala volumetry in a sample of 206 people recruited from the ENIGMA Addiction Working Group. They included 59 people with cannabis dependence (17 females), 49 cannabis users without cannabis dependence (20 females), and 98 controls (33 females). Results: We found no group-by-sex effect on subregional volumetry. The left hippocampal cornu ammonis subfield 1 (CA1) volumes were lower in dependent cannabis users compared with non-dependent cannabis users (p<0.001, d=0.32) and with controls (p=0.022, d=0.18). Further, the left cornu ammonis subfield 3 (CA3) and left dentate gyrus volumes were lower in dependent versus non-dependent cannabis users but not versus controls (p=0.002, d=0.37, and p=0.002, d=0.31, respectively). All models controlled for age, intelligence quotient (IQ), alcohol and tobacco use, and intracranial volume. Amygdala volumetry was not affected by group or group-by-sex, but was smaller in females than males. Conclusions: Our findings suggest that the relationship between cannabis dependence and subregional volumetry was not moderated by sex. Specifically, dependent (rather than non-dependent) cannabis use may be associated with alterations in selected hippocampus subfields high in cannabinoid type 1 (CB1) receptors and implicated in addictive behavior. As these data are cross-sectional, it is plausible that differences predate cannabis dependence onset and contribute to the initiation of cannabis dependence. Longitudinal neuroimaging work is required to examine the time-course of the onset of subregional hippocampal alterations in cannabis dependence, and their progression as cannabis dependence exacerbates or recovers over time.