Anxiety onset in adolescents: a machine-learning prediction

Recent longitudinal studies in youth have reported MRI correlates of prospective anxiety symptoms during adolescence, a vulnerable period for the onset of anxiety disorders. However, their predictive value has not been established. Individual prediction through machine-learning algorithms might help bridge the gap to clinical relevance. A voting classifier with Random Forest, Support Vector Machine and Logistic Regression algorithms was used to evaluate the predictive pertinence of gray matter volumes of interest and psychometric scores in the detection of prospective clinical anxiety. Participants with clinical anxiety at age 18-23 (N = 156) were investigated at age 14 along with healthy controls (N = 424). Shapley values were extracted for in-depth interpretation of feature importance. Prospective prediction of pooled anxiety disorders relied mostly on psychometric features and achieved moderate performance (area under the receiver operating curve = 0.68), while generalized anxiety disorder (GAD) prediction achieved similar performance. MRI regional volumes did not improve the prediction performance of prospective pooled anxiety disorders with respect to psychometric features alone, but they improved the prediction performance of GAD, with the caudate and pallidum volumes being among the most contributing features. To conclude, in non-anxious 14 year old adolescents, future clinical anxiety onset 4-8 years later could be individually predicted. Psychometric features such as neuroticism, hopelessness and emotional symptoms were the main contributors to pooled anxiety disorders prediction. Neuroanatomical data, such as caudate and pallidum volume, proved valuable for GAD and should be included in prospective clinical anxiety prediction in adolescents.

Arc controls alcohol cue relapse by a central amygdala mechanism

Alcohol use disorder (AUD) is a chronic and fatal disease. The main impediment of the AUD therapy is a high probability of relapse to alcohol abuse even after prolonged abstinence. The molecular mechanisms of cue-induced relapse are not well established, despite the fact that they may offer new targets for the treatment of AUD. Using a comprehensive animal model of AUD, virally-mediated and amygdala-targeted genetic manipulations by CRISPR/Cas9 technology and ex vivo electrophysiology, we identify a mechanism that selectively controls cue-induced alcohol relapse and AUD symptom severity. This mechanism is based on activity-regulated cytoskeleton-associated protein (Arc)/ARG3.1-dependent plasticity of the amygdala synapses. In humans, we identified single nucleotide polymorphisms in the ARC gene and their methylation predicting not only amygdala size, but also frequency of alcohol use, even at the onset of regular consumption. Targeting Arc during alcohol cue exposure may thus be a selective new mechanism for relapse prevention.

Air-conducted ultrasound below the hearing threshold elicits functional changes in the cognitive control network

Air-conducted ultrasound (> 17.8 kHz; US) is produced by an increasing number of technical devices in our daily environment. While several studies indicate that exposure to US in public spaces can lead to subjective symptoms such as 'annoyance' or 'difficulties in concentration', the effects of US on brain activity are poorly understood. In the present study, individual hearing thresholds (HT) for sounds in the US frequency spectrum were assessed in 21 normal-hearing participants. The effects of US were then investigated by means of functional magnetic resonance imaging (fMRI). 15 of these participants underwent three resting-state acquisitions, two with a 21.5 kHz tone presented monaurally at 5 dB above (ATC) and 10 dB below (BTC) the HT and one without auditory stimulation (NTC), as well as three runs of an n-back working memory task involving similar stimulus conditions (n-ATC, n-BTC, n-NTC). Comparing data gathered during n-NTC vs. fixation, we found that task performance was associated with the recruitment of regions within the cognitive control network, including prefrontal and parietal areas as well as the cerebellum. Direct contrasts of the two stimulus conditions (n-ATC & n-BTC) vs. n-NTC showed no significant differences in brain activity, irrespective of whether a whole-brain or a region of interest approach with primary auditory cortex as the seed was used. Likewise, no differences were found when the resting-state runs were compared. However, contrast analysis (n-BTC vs. n-ATC) revealed a strong activation in bilateral inferior frontal gyrus (IFG, triangular part) only when US was presented below the HT (p < 0.001, cluster > 30). In addition, IFG activation was also associated with faster reaction times during n-BTC (p = 0.033) as well as with verbal reports obtained after resting-state, i.e., the more unpleasant sound was perceived during BTC vs. ATC, the higher activation in bilateral IFG was and vice versa (p = 0.003). While this study provides no evidence for activation of primary auditory cortex in response to audible US (even though participants heard the sounds), it indicates that US can lead to changes in the cognitive control network and affect cognitive performance only when presented below the HT. Activation of bilateral IFG could reflect an increase in cognitive demand when focusing on task performance in the presence of slightly unpleasant and/or distracting US that may not be fully controllable by attentional mechanisms.

A causal association of ANKRD37 with human hippocampal volume

Human hippocampal volume has been separately associated with single nucleotide polymorphisms (SNPs), DNA methylation and gene expression, but their causal relationships remain largely unknown. Here, we aimed at identifying the causal relationships of SNPs, DNA methylation, and gene expression that are associated with hippocampal volume by integrating cross-omics analyses with genome editing, overexpression and causality inference. Based on structural neuroimaging data and blood-derived genome, transcriptome and methylome data, we prioritized a possibly causal association across multiple molecular phenotypes: rs1053218 mutation leads to cg26741686 hypermethylation, thus leads to overactivation of the associated ANKRD37 gene expression in blood, a gene involving hypoxia, which may result in the reduction of human hippocampal volume. The possibly causal relationships from rs1053218 to cg26741686 methylation to ANKRD37 expression obtained from peripheral blood were replicated in human hippocampal tissue. To confirm causality, we performed CRISPR-based genome and epigenome-editing of rs1053218 homologous alleles and cg26741686 methylation in mouse neural stem cell differentiation models, and overexpressed ANKRD37 in mouse hippocampus. These in-vitro and in-vivo experiments confirmed that rs1053218 mutation caused cg26741686 hypermethylation and ANKRD37 overexpression, and cg26741686 hypermethylation favored ANKRD37 overexpression, and ANKRD37 overexpression reduced hippocampal volume. The pairwise relationships of rs1053218 with hippocampal volume, rs1053218 with cg26741686 methylation, cg26741686 methylation with ANKRD37 expression, and ANKRD37 expression with hippocampal volume could be replicated in an independent healthy young (n = 443) dataset and observed in elderly people (n = 194), and were more significant in patients with late-onset Alzheimer's disease (n = 76). This study revealed a novel causal molecular association mechanism of ANKRD37 with human hippocampal volume, which may facilitate the design of prevention and treatment strategies for hippocampal impairment.

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.

Structural differences in adolescent brains can predict alcohol misuse

Alcohol misuse during adolescence (AAM) has been associated with disruptive development of adolescent brains. In this longitudinal machine learning (ML) study, we could predict AAM significantly from brain structure (T1-weighted imaging and DTI) with accuracies of 73 -78% in the IMAGEN dataset (n∼1182). Our results not only show that structural differences in brain can predict AAM, but also suggests that such differences might precede AAM behavior in the data. We predicted 10 phenotypes of AAM at age 22 using brain MRI features at ages 14, 19, and 22. Binge drinking was found to be the most predictable phenotype. The most informative brain features were located in the ventricular CSF, and in white matter tracts of the corpus callosum, internal capsule, and brain stem. In the cortex, they were spread across the occipital, frontal, and temporal lobes and in the cingulate cortex. We also experimented with four different ML models and several confound control techniques. Support Vector Machine (SVM) with rbf kernel and Gradient Boosting consistently performed better than the linear models, linear SVM and Logistic Regression. Our study also demonstrates how the choice of the predicted phenotype, ML model, and confound correction technique are all crucial decisions in an explorative ML study analyzing psychiatric disorders with small effect sizes such as AAM.

Bayesian causal network modeling suggests adolescent cannabis use accelerates prefrontal cortical thinning

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. [1] is a result of cannabis use causally affecting neurodevelopment. BCNs incorporated data on cannabis use, prefrontal cortical thickness, and other factors related to both brain development and cannabis use, including demographics, psychopathology, childhood adversity, and other substance use. All BCN algorithms strongly suggested a directional relationship from adolescent cannabis use to accelerated cortical thinning. While BCN modeling alone does not prove a causal relationship, these results are consistent with a body of animal and human research suggesting that adolescent cannabis use adversely affects brain development.

Associations of delay discounting and drinking trajectories from ages 14 to 22

BACKGROUND

While drinking alcohol, one must choose between the immediate rewarding effects and the delayed reward of a healthier lifestyle. Individuals differ in their devaluation of a delayed reward based on the time required to receive it, i.e., delay discounting (DD). Previous studies have shown that adolescents discount more steeply than adults and that steeper DD is associated with heavier alcohol use in both groups.

METHODS

In a large-scale longitudinal study, we investigated whether higher rates of DD are an antecedent or a consequence of alcohol use during adolescent development. As part of the IMAGEN project, 2220 adolescents completed the Monetary Choice Questionnaire as a DD measure, the Alcohol Use Disorders Identification Test, and the Timeline Follow Back interview at ages 14, 16, 18, and 22. Bivariate latent growth curve models were applied to investigate the relationship between DD and drinking. To explore the consequences of drinking, we computed the cumulative alcohol consumption and correlated it with the development of discounting. A subsample of 221 participants completed an intertemporal choice task (iTeCh) during functional magnetic resonance imaging at ages 14, 16, and 18. Repeated-measures ANOVA was used to differentiate between high-risk and low-risk drinkers on the development of neural processing during intertemporal choices.

RESULTS

Overall, high rates of DD at age 14 predicted a greater increase in drinking over 8 years. In contrast, on average, moderate alcohol use did not affect DD from ages 14 to 22. Of note, we found indicators for less brain activity in top-down control areas during intertemporal choices in the participants who drank more.

CONCLUSIONS

Steep DD was shown to be a predictor rather than a consequence of alcohol use in low-level drinking adolescents. Important considerations for future longitudinal studies are the sampling strategies to be used and the reliability of the assessments.

Predicting Depression Onset in Young People Based on Clinical, Cognitive, Environmental, and Neurobiological Data

BACKGROUND

Adolescent onset of depression is associated with long-lasting negative consequences. Identifying adolescents at risk for developing depression would enable the monitoring of risk factors and the development of early intervention strategies. Using machine learning to combine several risk factors from multiple modalities might allow prediction of depression onset at the individual level.

METHODS

A subsample of a multisite longitudinal study in adolescents, the IMAGEN study, was used to predict future (subthreshold) major depressive disorder onset in healthy adolescents. Based on 2-year and 5-year follow-up data, participants were grouped into the following: 1) those developing a diagnosis of major depressive disorder or subthreshold major depressive disorder and 2) healthy control subjects. Baseline measurements of 145 variables from different modalities (clinical, cognitive, environmental, and structural magnetic resonance imaging) at age 14 years were used as input to penalized logistic regression (with different levels of penalization) to predict depression onset in a training dataset (n = 407). The features contributing the highest to the prediction were validated in an independent hold-out sample (three independent IMAGEN sites; n = 137).

RESULTS

The area under the receiver operating characteristic curve for predicting depression onset ranged between 0.70 and 0.72 in the training dataset. Baseline severity of depressive symptoms, female sex, neuroticism, stressful life events, and surface area of the supramarginal gyrus contributed most to the predictive model and predicted onset of depression, with an area under the receiver operating characteristic curve between 0.68 and 0.72 in the independent validation sample.

CONCLUSIONS

This study showed that depression onset in adolescents can be predicted based on a combination multimodal data of clinical characteristics, life events, personality traits, and brain structure variables.

Transforming and comparing data between standard SQUID and OPM-MEG systems

Optically pumped magnetometers (OPMs) have recently become so sensitive that they are suitable for use in magnetoencephalography (MEG). These sensors solve operational problems of the current standard MEG, where superconducting quantum interference device (SQUID) gradiometers and magnetometers are being used. The main advantage of OPMs is that they do not require cryogenics for cooling. Therefore, they can be placed closer to the scalp and are much easier to use. Here, we measured auditory evoked fields (AEFs) with both SQUID- and OPM-based MEG systems for a group of subjects to better understand the usage of a limited sensor count OPM-MEG. We present a theoretical framework that transforms the within subject data and equivalent simulation data from one MEG system to the other. This approach works on the principle of solving the inverse problem with one system, and then using the forward model to calculate the magnetic fields expected for the other system. For the source reconstruction, we used a minimum norm estimate (MNE) of the current distribution. Two different volume conductor models were compared: the homogeneous conducting sphere and the three-shell model of the head. The transformation results are characterized by a relative error and cross-correlation between the measured and the estimated magnetic field maps of the AEFs. The results for both models are encouraging. Since some commercial OPMs measure multiple components of the magnetic field simultaneously, we additionally analyzed the effect of tangential field components. Overall, our dual-axis OPM-MEG with 15 sensors yields similar information to a 62-channel SQUID-MEG with its field of view restricted to the right hemisphere.

Global urbanicity is associated with brain and behaviour in young people

Urbanicity is a growing environmental challenge for mental health. Here, we investigate correlations of urbanicity with brain structure and function, neuropsychology and mental illness symptoms in young people from China and Europe (total n = 3,867). We developed a remote-sensing satellite measure (UrbanSat) to quantify population density at any point on Earth. UrbanSat estimates of urbanicity were correlated with brain volume, cortical surface area and brain network connectivity in the medial prefrontal cortex and cerebellum. UrbanSat was also associated with perspective-taking and depression symptoms, and this was mediated by neural variables. Urbanicity effects were greatest when urban exposure occurred in childhood for the cerebellum, and from childhood to adolescence for the prefrontal cortex. As UrbanSat can be generalized to different geographies, it may enable assessments of correlations of urbanicity with mental illness and resilience globally.

Characterizing reward system neural trajectories from adolescence to young adulthood

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=14.44 years old) and timepoint 2 (T2; n = 1241, mean age=19.09 years). The Alcohol Use Disorders Identification Test (AUDIT) was administrated at both T1 and T2 to assess a participant’s alcohol use during the past year. Voxel-wise linear mixed effect models were used to compare whole brain response as well as functional connectivity of the ventral striatum (VS) during reward anticipation (large reward vs no-reward cue) between T1 and T2. In addition, task-modulated networks were constructed using generalized psychophysiological interaction analysis and summarized with graph theory metrics. To explore alcohol use in relation to development, participants with no/low alcohol use at T1 but increased alcohol use to hazardous use level at T2 (i.e., participants with AUDIT≤2 at T1 and ≥8 at T2) were compared against those with consistently low scores (i.e., participants with AUDIT≤2 at T1 and ≤7 at T2). Across the whole sample, lower brain response during reward anticipation was observed at T2 compared with T1 in bilateral caudate nucleus, VS, thalamus, midbrain, dorsal anterior cingulate as well as left precentral and postcentral gyrus. Conversely, greater response was observed bilaterally in the inferior and middle frontal gyrus and right precentral and postcentral gyrus at T2 (vs. T1). Increased functional connectivity with VS was found in frontal, temporal, parietal and occipital regions at T2. Graph theory metrics of the task-modulated network showed higher inter-regional connectivity and topological efficiency at T2. Interactive effects between time (T1 vs. T2) and alcohol use group (low vs. high) on the functional connectivity were observed between left middle temporal gyrus and right VS and the characteristic shortest path length of the task-modulated networks. Collectively, these results demonstrate the utility of the MID task as a probe of typical brain response and network properties during development and of differences in these features related to adolescent drinking, a reward-related behaviour associated with heightened risk for future negative health outcomes.

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Imaging data during reward anticipation at T1 (age 14) and T2 (age 19) was compared.

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Brain response decreased in subcortical areas and increased in cortical areas at T2.

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Functional connectivity (FC) with the ventral striatum increased at T2.

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Topological efficiency of task-modulated network increased at T2.

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The developmental pattern was altered in those who increased drinking most at T2.

Assessment of measurement precision in single-voxel spectroscopy at 7 T: Toward minimal detectable changes of metabolite concentrations in the human brain in vivo

PURPOSE

To introduce a study design and statistical analysis framework to assess the repeatability, reproducibility, and minimal detectable changes (MDCs) of metabolite concentrations determined by in vivo MRS.

METHODS

An unbalanced nested study design was chosen to acquire in vivo MRS data within different repeatability and reproducibility scenarios. A spin-echo, full-intensity acquired localized (SPECIAL) sequence was employed at 7 T utlizing three different inversion pulses: a hyperbolic secant (HS), a gradient offset independent adiabaticity (GOIA), and a wideband, uniform rate, smooth truncation (WURST) pulse. Metabolite concentrations, Cramér-Rao lower bounds (CRLBs) and coefficients of variation (CVs) were calculated. Both Bland-Altman analysis and a restricted maximum-likelihood estimation (REML) analysis were performed to estimate the different variance contributions of the repeatability and reproducibility of the measured concentration. A Bland-Altmann analysis of the spectral shape was performed to assess the variance of the spectral shape, independent of quantification model influences.

RESULTS

For the used setup, minimal detectable changes of brain metabolite concentrations were found to be between 0.40 µmol/g and 2.23 µmol/g. CRLBs account for only 16 % to 74 % of the total variance of the metabolite concentrations. The application of gradient-modulated inversion pulses in SPECIAL led to slightly improved repeatability, but overall reproducibility appeared to be limited by differences in positioning, calibration, and other day-to-day variations throughout different sessions.

CONCLUSION

A framework is introduced to estimate the precision of metabolite concentrations obtained by MRS in vivo, and the minimal detectable changes for 13 metabolite concentrations measured at 7 T using SPECIAL are obtained.

Immune-Related Genetic Overlap Between Regional Gray Matter Reductions and Psychiatric Symptoms in Adolescents, and Gene-Set Validation in a Translational Model

Adolescence is a period of vulnerability for the maturation of gray matter (GM) and also for the onset of psychiatric disorders such as major depressive disorder (MDD), bipolar disorder and schizophrenia. Chronic neuroinflammation is considered to play a role in the etiology of these illnesses. However, the involvement of neuroinflammation in the observed link between regional GM volume reductions and psychiatric symptoms is not established yet. Here, we investigated a possible common immune-related genetic link between these two phenomena in european adolescents recruited from the community. Hippocampal and medial prefrontal cortex (mPFC) were defined a priori as regions of interest (ROIs). Their GM volumes were extracted in 1,563 14-year-olds from the IMAGEN database. We found a set of 26 SNPs that correlated with the hippocampal volumes and 29 with the mPFC volumes at age 14. We formed two ROI-Related Immune-gene scores (RRI) with the inflammation SNPs that correlated to hippocampal GM volume and to mPFC GM volume. The predictive ability of both RRIs with regards to the presence of psychiatric symptoms at age 18 was investigated by correlating the RRIs with psychometric questionnaires obtained at age 18. The RRIs (but not control scores constructed with random SNPs) correlated with the presence of depressive symptoms, positive psychotic symptoms, and externalizing symptoms in later adolescence. In addition, the effect of childhood maltreatment, one of the major environmental risk factors for depression and other mental disorders, interacted with the RRI effect. We next sought to validate this finding by investigating our set of inflammatory genes in a translational animal model of early life adversity. Mice were subjected to a protocol of maternal separation at an early post-natal age. We evaluated depressive behaviors in separated and non-separated mice at adolescence and their correlations with the concomitant expression of our genes in whole blood samples. We show that in mice, early life adversity affected the expression of our set of genes in peripheral blood, and that levels of expression correlated with symptoms of negative affect in adolescence. Overall, our translational findings in adolescent mice and humans provide a novel validated gene-set of immune-related genes for further research in the early stages of mood disorders.

The interaction of child abuse and rs1360780 of the FKBP5 gene is associated with amygdala resting-state functional connectivity in young adults

Extensive research has demonstrated that rs1360780, a common single nucleotide polymorphism within the FKBP5 gene, interacts with early-life stress in predicting psychopathology. Previous results suggest that carriers of the TT genotype of rs1360780 who were exposed to child abuse show differences in structure and functional activation of emotion-processing brain areas belonging to the salience network. Extending these findings on intermediate phenotypes of psychopathology, we examined if the interaction between rs1360780 and child abuse predicts resting-state functional connectivity (rsFC) between the amygdala and other areas of the salience network. We analyzed data of young European adults from the general population (N = 774; mean age = 18.76 years) who took part in the IMAGEN study. In the absence of main effects of genotype and abuse, a significant interaction effect was observed for rsFC between the right centromedial amygdala and right posterior insula (p < .025, FWE-corrected), which was driven by stronger rsFC in TT allele carriers with a history of abuse. Our results suggest that the TT genotype of rs1360780 may render individuals with a history of abuse more vulnerable to functional changes in communication between brain areas processing emotions and bodily sensations, which could underlie or increase the risk for psychopathology.

Heating of hip joint implants in MRI: The combined effect of RF and switched-gradient fields

PURPOSE

To investigate how the simultaneous exposure to gradient and RF fields affects the temperature rise in patients with a metallic hip prosthesis during an MRI session.

METHODS

In silico analysis was performed with an anatomically realistic human model with CoCrMo hip implant in 12 imaging positions. The analysis was performed at 1.5 T and 3 T, considering four clinical sequences: turbo spin-echo, EPI, gradient-echo, and true fast imaging sequence with steady precession. The exposure to gradient and RF fields was evaluated separately and superposed, by adopting an ad hoc computational algorithm. Temperature increase within the body, rather than specific absorption rate, was used as a safety metric.

RESULTS

With the exception of gradient-echo, all investigated sequences produced temperature increases higher than 1 K after 360 seconds, at least for one body position. In general, RF-induced heating dominates the turbo spin-echo sequence, whereas gradient-induced heating prevails with EPI; the situation with fast imaging sequence with steady precession is more diversified. The RF effects are enhanced when the implant is within the RF coil, whereas the effects of gradient fields are maximized if the prosthesis is outside the imaging region. Cases for which temperature-increase thresholds were exceeded were identified, together with the corresponding amount of tissue mass involved and the exposure time needed to reach these limits.

CONCLUSION

The analysis confirms that risky situations may occur when a patient carrying a hip implant undergoes an MRI exam and that, in some cases, the gradient field heating may be significant. In general, exclusion criteria only based on whole-body specific absorption rate may not be sufficient to ensure patients' safety.

Endocannabinoid Gene × Gene Interaction Association to Alcohol Use Disorder in Two Adolescent Cohorts

Genetic markers of the endocannabinoid system have been linked to a variety of addiction-related behaviors that extend beyond cannabis use. In the current study we investigate the relationship between endocannabinoid (eCB) genetic markers and alcohol use disorder (AUD) in European adolescents (14-18 years old) followed in the IMAGEN study (n = 2,051) and explore replication in a cohort of North American adolescents from Canadian Saguenay Youth Study (SYS) (n = 772). Case-control status is represented by a score of more than 7 on the Alcohol Use Disorder Identification Test (AUDIT). First a set-based test method was used to examine if a relationship between the eCB system and AUDIT case/control status exists at the gene level. Using only SNPs that are both independent and significantly associated to case-control status, we perform Fisher's exact test to determine SNP level odds ratios in relation to case-control status and then perform logistic regressions as post-hoc analysis, while considering various covariates. Generalized multifactor dimensionality reduction (GMDR) was used to analyze the most robust SNP×SNP interaction of the five eCB genes with positive AUDIT screen. While no gene-sets were significantly associated to AUDIT scores after correction for multiple tests, in the case/control analysis, 7 SNPs were significantly associated with AUDIT scores of > 7 (p < 0.05; OR<1). Two SNPs remain significant after correction by false discovery rate (FDR): rs9343525 in CNR1 (pcorrected =0.042, OR = 0.73) and rs507961 in MGLL (pcorrected = 0.043, OR = 0.78). Logistic regression showed that both rs9353525 (CNR1) and rs507961 (MGLL) remained significantly associated with positive AUDIT screens (p < 0.01; OR < 1) after correction for multiple covariables and interaction of covariable × SNP. This result was not replicated in the SYS cohort. The GMDR model revealed a significant three-SNP interaction (p = 0.006) involving rs484061 (MGLL), rs4963307 (DAGLA), and rs7766029 (CNR1) predicted case-control status, after correcting for multiple covariables in the IMAGEN sample. A binomial logistic regression of the combination of these three SNPs by phenotype in the SYS cohort showed a result in the same direction as seen in the IMAGEN cohort (BETA = 0.501, p = 0.06). While preliminary, the present study suggests that the eCB system may play a role in the development of AUD in adolescents.

Are psychotic-like experiences related to a discontinuation of cannabis consumption in young adults?

OBJECTIVE

To assess changes in cannabis use in young adults as a function of psychotic-like experiences.

METHOD

Participants were initially recruited at age 14 in high schools for the longitudinal IMAGEN study. All measures presented here were assessed at follow-ups at age 19 and at age 22, respectively. Perceived stress was only assessed once at age 22. Ever users of cannabis (N = 552) gave qualitative and quantitative information on cannabis use and psychotic-like experiences using the Community Assessment of Psychic Experiences (CAPE). Of those, nearly all n = 549 reported to have experienced at least one psychotic experience of any form at age 19.

RESULTS

Mean cannabis use increased from age 19 to 22 and age of first use of cannabis was positively associated with a change in cannabis use between the two time points. Change in cannabis use was not significantly associated with psychotic-like experiences at age 19 or 22. In exploratory analysis, we observed a positive association between perceived stress and the experience of psychotic experiences at age 22.

CONCLUSION

Age of first use of cannabis influenced trajectories of young cannabis users with later onset leading to higher increase, whereas the frequency of psychotic-like experiences was not associated with a change in cannabis use. The observed association between perceived stress and psychotic-like experiences at age 22 emphasizes the importance of stress experiences in developing psychosis independent of cannabis use.

Ventromedial Prefrontal Volume in Adolescence Predicts Hyperactive/Inattentive Symptoms in Adulthood

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.

T1 mapping performance and measurement repeatability: results from the multi-national T1 mapping standardization phantom program (T1MES)

BACKGROUND

The T1 Mapping and Extracellular volume (ECV) Standardization (T1MES) program explored T1 mapping quality assurance using a purpose-developed phantom with Food and Drug Administration (FDA) and Conformité Européenne (CE) regulatory clearance. We report T1 measurement repeatability across centers describing sequence, magnet, and vendor performance.

METHODS

Phantoms batch-manufactured in August 2015 underwent 2 years of structural imaging, B0 and B1, and "reference" slow T1 testing. Temperature dependency was evaluated by the United States National Institute of Standards and Technology and by the German Physikalisch-Technische Bundesanstalt. Center-specific T1 mapping repeatability (maximum one scan per week to minimum one per quarter year) was assessed over mean 358 (maximum 1161) days on 34 1.5 T and 22 3 T magnets using multiple T1 mapping sequences. Image and temperature data were analyzed semi-automatically. Repeatability of serial T1 was evaluated in terms of coefficient of variation (CoV), and linear mixed models were constructed to study the interplay of some of the known sources of T1 variation.

RESULTS

Over 2 years, phantom gel integrity remained intact (no rips/tears), B0 and B1 homogenous, and "reference" T1 stable compared to baseline (% change at 1.5 T, 1.95 ± 1.39%; 3 T, 2.22 ± 1.44%). Per degrees Celsius, 1.5 T, T1 (MOLLI 5s(3s)3s) increased by 11.4 ms in long native blood tubes and decreased by 1.2 ms in short post-contrast myocardium tubes. Agreement of estimated T1 times with "reference" T1 was similar across Siemens and Philips CMR systems at both field strengths (adjusted R2 ranges for both field strengths, 0.99-1.00). Over 1 year, many 1.5 T and 3 T sequences/magnets were repeatable with mean CoVs < 1 and 2% respectively. Repeatability was narrower for 1.5 T over 3 T. Within T1MES repeatability for native T1 was narrow for several sequences, for example, at 1.5 T, Siemens MOLLI 5s(3s)3s prototype number 448B (mean CoV = 0.27%) and Philips modified Look-Locker inversion recovery (MOLLI) 3s(3s)5s (CoV 0.54%), and at 3 T, Philips MOLLI 3b(3s)5b (CoV 0.33%) and Siemens shortened MOLLI (ShMOLLI) prototype 780C (CoV 0.69%). After adjusting for temperature and field strength, it was found that the T1 mapping sequence and scanner software version (both P < 0.001 at 1.5 T and 3 T), and to a lesser extent the scanner model (P = 0.011, 1.5 T only), had the greatest influence on T1 across multiple centers.

CONCLUSION

The T1MES CE/FDA approved phantom is a robust quality assurance device. In a multi-center setting, T1 mapping had performance differences between field strengths, sequences, scanner software versions, and manufacturers. However, several specific combinations of field strength, sequence, and scanner are highly repeatable, and thus, have potential to provide standardized assessment of T1 times for clinical use, although temperature correction is required for native T1 tubes at least.

Heavy drinking in adolescents is associated with change in brainstem microstructure and reward sensitivity

Heavy drinker adolescents: altered brainstem microstructure.

Identifying biological markers for improved precision medicine in psychiatry

Mental disorders represent an increasing personal and financial burden and yet treatment development has stagnated in recent decades. Current disease classifications do not reflect psychobiological mechanisms of psychopathology, nor the complex interplay of genetic and environmental factors, likely contributing to this stagnation. Ten years ago, the longitudinal IMAGEN study was designed to comprehensively incorporate neuroimaging, genetics, and environmental factors to investigate the neural basis of reinforcement-related behavior in normal adolescent development and psychopathology. In this article, we describe how insights into the psychobiological mechanisms of clinically relevant symptoms obtained by innovative integrative methodologies applied in IMAGEN have informed our current and future research aims. These aims include the identification of symptom groups that are based on shared psychobiological mechanisms and the development of markers that predict disease course and treatment response in clinical groups. These improvements in precision medicine will be achieved, in part, by employing novel methodological tools that refine the biological systems we target. We will also implement our approach in low- and medium-income countries to understand how distinct environmental, socioeconomic, and cultural conditions influence the development of psychopathology. Together, IMAGEN and related initiatives strive to reduce the burden of mental disorders by developing precision medicine approaches globally.

Does airborne ultrasound lead to activation of the auditory cortex?

As airborne ultrasound can be found in many technical applications and everyday situations, the question as to whether sounds at these frequencies can be heard by human beings or whether they present a risk to their hearing system is of great practical relevance. To objectively study these issues, the monaural hearing threshold in the frequency range from 14 to 24 kHz was determined for 26 test subjects between 19 and 33 years of age using pure tone audiometry. The hearing threshold values increased strongly with increasing frequency up to around 21 kHz, followed by a range with a smaller slope toward 24 kHz. The number of subjects who could respond positively to the threshold measurements decreased dramatically above 21 kHz. Brain activation was then measured by means of magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) and with acoustic stimuli at the same frequencies, with sound pressure levels (SPLs) above and below the individual threshold. No auditory cortex activation was found for levels below the threshold. Although test subjects reported audible sounds above the threshold, no brain activity was identified in the above-threshold case under current experimental conditions except at the highest sensation level, which was presented at the lowest test frequency.

Modulation of orbitofrontal-striatal reward activity by dopaminergic functional polymorphisms contributes to a predisposition to alcohol misuse in early adolescence

BACKGROUND

Abnormalities in reward circuit function are considered a core feature of addiction. Yet, it is still largely unknown whether these abnormalities stem from chronic drug use, a genetic predisposition, or both.

METHODS

In the present study, we investigated this issue using a large sample of adolescent children by applying structural equation modeling to examine the effects of several dopaminergic polymorphisms of the D1 and D2 receptor type on the reward function of the ventral striatum (VS) and orbital frontal cortex (OFC), and whether this relationship predicted the propensity to engage in early alcohol misuse behaviors at 14 years of age and again at 16 years of age.

RESULTS

The results demonstrated a regional specificity with which the functional polymorphism rs686 of the D1 dopamine receptor (DRD1) gene and Taq1A of the ANKK1 gene influenced medial and lateral OFC activation during reward anticipation, respectively. Importantly, our path model revealed a significant indirect relationship between the rs686 of the DRD1 gene and early onset of alcohol misuse through a medial OFC × VS interaction.

CONCLUSIONS

These findings highlight the role of D1 and D2 in adjusting reward-related activations within the mesocorticolimbic circuitry, as well as in the susceptibility to early onset of alcohol misuse.