Common genetic factors for uncontrolled eating mechanisms.

OBJECTIVE: Reward-based eating drives are putative mechanisms of uncontrolled eating implicated in obesity and disordered eating (e.g., binge eating). Uncovering the genetic and environmental contributions to reward-related eating, and their genetic correlation with BMI, could shed light on key mechanisms underlying eating and weight-related disorders. METHOD: We conducted a classical twin study to examine how much variance in uncontrolled eating phenotypes and body mass index (BMI) was explained by genetic factors, and the extent that these phenotypes shared common genetic factors. 353 monozygotic twins and 128 dizygotic twins completed the Reward-based Eating Drive 13 scale, which measures three distinct uncontrolled eating phenotypes (loss of control over eating, preoccupation with thoughts about food, and lack of satiety), and a demographic questionnaire which included height and weight for BMI calculation. We estimated additive genetic (A), common environmental (C), and unique environmental (E) factors for each phenotype, as well as their genetic correlations, with a multivariate ACE model. A common pathway model also estimated whether genetic variance in the uncontrolled eating phenotypes was better explained by a common latent uncontrolled eating factor. RESULTS: There were moderate genetic correlations between uncontrolled eating phenotypes and BMI (.26-.41). Variance from the uncontrolled eating phenotypes was also best explained by a common latent uncontrolled eating factor that was explained by additive genetic factors (52%). DISCUSSION: These results suggest that uncontrolled eating phenotypes are heritable traits that also share genetic variance with BMI. This has implications for understanding the cognitive mechanisms that underpin obesity and disordered eating. PUBLIC SIGNIFICANCE: Our study clarifies the degree to which uncontrolled eating phenotypes and BMI are influenced by shared genetics and shows that vulnerability to uncontrolled eating traits is impacted by common genetic factors.

Model-based and model-free mechanisms in methamphetamine use disorder.

People with methamphetamine use disorder (MUD) struggle to shift their behaviour from methamphetamine-orientated habits to goal-oriented choices. The model-based/model-free framework is well suited to understand this difficulty by unpacking the computational mechanisms that support experienced-based (model-free) and goal-directed (model-based) choices. We aimed to examine whether 1) participants with MUD differed from controls on behavioural proxies and/or computational mechanisms of model-based/model-free choices; 2) model-based/model-free decision-making correlated with MUD symptoms; and 3) model-based/model-free deficits improved over six weeks in the group with MUD. Participants with MUD and controls with similar age, IQ and socioeconomic status completed the Two-Step Task at treatment commencement (MUD n = 30, Controls n = 31) and six weeks later (MUD n = 23, Controls n = 26). We examined behavioural proxies of model-based/model-free decisions using mixed logistic regression, and their underlying mechanisms using computational modelling. At a behavioural level, participants with MUD were more likely to switch their choices following rewarded actions, although this pattern improved at follow up. At a computational level, groups were similar in their use of model-based mechanisms, but participants with MUD were less likely to apply model-free mechanisms and less likely to repeat rewarded actions. We did not find evidence that individual differences in model-based or model-free parameters were associated with greater severity of methamphetamine dependence, nor did we find that group differences in computational parameters changed between baseline and follow-up assessment. Decision-making challenges in people with MUD are likely related to difficulties in pursuing choices previously associated with positive outcomes.

A three-arm randomised controlled trial of a telehealth intervention targeting improvement in addictive eating for Australian adults (the TRACE program).

There is a substantial research base for addictive eating with development of interventions. The current 3-arm RCT aimed to investigate the efficacy of the TRACE (Targeted Research for Addictive and Compulsive Eating) program to decrease addictive eating symptoms and improve mental health. Participants (18-85 yrs) endorsing ≥3 addictive eating symptoms were randomly allocated to 1) active intervention, 2) passive intervention, or 3) control group. Primary outcome was change in addictive eating symptoms 3-months post-baseline measured by the Yale Food Addiction Scale. Depression, anxiety and stress were also assessed. A total of 175 individuals were randomised. Using Linear Mixed Models, from baseline to 3-months, there was significant improvement in symptom scores in all groups with mean decrease of 4.7 (95% CI: -5.8, -3.6; p < 0.001), 3.8 (95% CI: -5.2, -2.4; p < 0.001) and 1.5 (95% CI: -2.6, -0.4; p = 0.01) respectively. Compared with the control group, participants in the active intervention were five times more likely to achieve a clinically significant change in symptom scores. There was a significant reduction in depression scores in the active and passive intervention groups, but not control group [-2.9 (95% CI: -4.5, -1.3); -2.3 (95% CI: -4.3, -0.3); 0.5 (95% CI: -1.1, 2.1), respectively]; a significant reduction in stress scores within the active group, but not passive intervention or control groups [-1.3 (95% CI: -2.2, -0.5); -1.0 (95% CI: -2.1, 0.1); 0.4 (95% CI: -0.5, 1.2), respectively]; and the reduction in anxiety scores over time was similar for all groups. A dietitian-led telehealth intervention for addictive eating in adults was more effective than a passive or control condition in reducing addictive eating scores from baseline to 6 months. Trial registration: Australia New Zealand Clinical Trial Registry ACTRN12621001079831.

The effectiveness of the TRACE online nutrition intervention in improving dietary intake, sleep quality and physical activity levels for Australian adults with food addiction: a randomised controlled trial.

BACKGROUND: Few interventions for food addiction (FA) report on dietary intake variables. The present study comprised a three-arm randomised controlled trial in adults with symptoms of FA. The aim was to evaluate dietary intake, sleep and physical activity resulting from a dietitian-led telehealth intervention at 3 months. METHODS: Adults with ≥3 symptoms of FA and a body mass index > 18.5 kg/m2 were recruited. Dietary intake including energy, nutrients and diet quality were assessed by a validated food frequency questionnaire in addition to sleep quality and physical activity (total min) and compared between groups and over time. Personalised dietary goals set by participants were examined to determine whether improvements in percent energy from core and non-core foods were reported. RESULTS: The active intervention group was superior compared to the passive intervention and control groups for improvements in percent energy from core (6.4%/day [95% confidence interval (CI) -0.0 to 12.9], p = 0.049), non-core foods (-6.4%/day [95% CI -12.9 to 0.0], p = 0.049), sweetened drinks (-1.7%/day [95% CI -2.9 to -0.4], p = 0.013), takeaway foods (-2.3%/day [95% CI -4.5 to -0.1], p = 0.045) and sodium (-478 mg/day [95% CI -765 to -191 mg], p = 0.001). CONCLUSIONS: A dietitian-led telehealth intervention for Australian adults with FA found significant improvements in dietary intake variables. Setting personalised goals around nutrition and eating behaviours was beneficial for lifestyle change.

The influence of stress on the neural underpinnings of disinhibited eating: a systematic review and future directions for research.

Disinhibited eating involves overconsumption and loss of control over food intake, and underpins many health conditions, including obesity and binge-eating related disorders. Stress has been implicated in the development and maintenance of disinhibited eating behaviours, but the mechanisms underlying this relationship are unclear. In this systematic review, we examined how the impact of stress on the neurobiological substrates of food-related reward sensitivity, interoception and cognitive control explains its role in disinhibited eating behaviours. We synthesised the findings of functional magnetic resonance imaging studies including acute and/or chronic stress exposures in participants with disinhibited eating. A systematic search of existing literature conducted in alignment with the PRISMA guidelines identified seven studies investigating neural impacts of stress in people with disinhibited eating. Five studies used food-cue reactivity tasks, one study used a social evaluation task, and one used an instrumental learning task to probe reward, interoception and control circuitry. Acute stress was associated with deactivation of regions in the prefrontal cortex implicated in cognitive control and the hippocampus. However, there were mixed findings regarding differences in reward-related circuitry. In the study using a social task, acute stress associated with deactivation of prefrontal cognitive control regions in response to negative social evaluation. In contrast, chronic stress was associated with both deactivation of reward and prefrontal regions when viewing palatable food-cues. Given the small number of identified publications and notable heterogeneity in study designs, we propose several recommendations to strengthen future research in this emerging field.

Early life factors and structural brain network in children with overweight/obesity: The ActiveBrains project.

BACKGROUND: The aims of this study were to investigate the association of early life factors, including birth weight, birth length, and breastfeeding practices, with structural brain networks; and to test whether structural brain networks associated with early life factors were also associated with academic performance in children with overweight/obesity (OW/OB). METHOD: 96 children with OW/OB aged 8-11 years (10.03 ± 1.16) from the ActiveBrains project were included. Early life factors were collected from birth records and reported by parents as weight, height, and months of breastfeeding. T1-weighted images were used to identify structural networks using a non-negative matrix factorization (NNMF) approach. Academic performance was evaluated by the Woodcock-Muñoz standardized test battery. RESULTS: Birth weight and birth length were associated with seven networks involving the cerebellum, cingulate gyrus, occipital pole, and subcortical structures including hippocampus, caudate nucleus, putamen, pallidum, nucleus accumbens, and amygdala. No associations were found for breastfeeding practices. None of the networks linked to birth weight and birth length were linked to academic performance. CONCLUSIONS: Birth weight and birth length, but not breastfeeding, were associated with brain structural networks in children with OW/OB. Thus, early life factors are related to brain networks, yet a link with academic performance was not observed. IMPACT: Birth weight and birth length, but not breastfeeding, were associated with several structural brain networks involving the cerebellum, cingulate gyrus, occipital pole, and subcortical structures including hippocampus, caudate, putamen, pallidum, accumbens and amygdala in children with overweight/obesity, playing a role for a normal brain development. Despite no academic consequences, other behavioral consequences should be investigated. Interventions aimed at improving optimal intrauterine growth and development may be of importance to achieve a healthy brain later in life.

Episodic future thinking and compassion reduce non-compliance urges regarding public health guidelines: a randomised controlled trial.

BACKGROUND: People often feel urges to engage in activities that violate pandemic public health guidelines. Research on these urges has been reliant on measures of typical behaviour, which fail to capture these urges as they unfold. Guideline adherence could be improved through interventions, but few methods allow for ecologically valid observation of the range of behaviours that pandemic guidelines prescribe. METHODS: In this preregistered parallel randomised trial, 95 participants aged 18-65 from the UK were assigned to three groups using blinded block randomisation, and engaged in episodic future thinking (n = 33), compassion exercises (n = 31), or a control procedure (n = 31). Following an ecological momentary assessment procedure, participants report on the intensity of their occurrent urges (min. 1, max. 10) and their ability to control them. The study further investigates whether, and through which mechanism, state impulsivity and vaccine attitudes affect guideline adherence. RESULTS: Episodic future thinking (b = -1.80) and compassion exercises (b = -1.45) reduced the intensity of urges. State impulsivity is associated with stronger urges, but we found no evidence that vaccine hesitancy predicts lesser self-control. CONCLUSIONS: We conclude that episodic future thinking exercises and compassion training may be used to decrease non-compliance urges of individuals who are an acute public health risk for the community, such as those in voluntary isolation.

Combining novel trait and neurocognitive frameworks to parse heterogeneity in borderline personality disorder.

OBJECTIVE: Borderline Personality Disorder (BPD) diagnosis comprises several constellations of trait, neurocognitive, and psychosocial alterations. Dimensional models of psychopathology provide new opportunities to parse heterogeneity and create a stronger interface between individual characterization and psychosocial outcomes. However, dimensional models have focused on either traits or neurocognitive features, lacking integration to capture the multifaceted nature of BPD. METHOD: We assessed 100 participants with BPD using a combination of tools stemming from trait (Alternative Model for Personality Disorders) and neurocognitive models (Research Domain Criteria; RDoC) to examine if trait-derived subgroups display distinctive social-processing and psychosocial profiles. We used two complementary analytical approaches: person-centered (k-means clustering) and construct-based (multiple factor analysis). RESULTS: Our person-centered approach identified four subgroups with separable internalizing, detached, externalizing, and low psychopathology trait profiles. These profiles revealed distinctive patterns of affiliation, emotion recognition and mentalization performance in RDoC tasks, and psychosocial measures of quality of life and social connectedness. RDoC-based measures showed close construct proximity with negative affectivity, disinhibition, and antagonism trait domains, relative to the detachment domain, which had close proximity with self-knowledge. CONCLUSIONS: Altogether, findings support consilience between trait-based and neurobiological frameworks and suggest that trait models are useful to parse BPD heterogeneity leading to unique social functioning profiles.

Computational mechanisms underpinning greater exploratory behaviour in excess weight relative to healthy weight adolescents.

Obesity in adolescence is associated with cognitive changes that lead to difficulties in shifting unhealthy habits in favour of alternative healthy behaviours, similar to addictive behaviours. An outstanding question is whether this shift in goal-directed behaviour is driven by over-exploitation or over-exploration of rewarding outcomes. Here, we addressed this question by comparing explore/exploit behaviour on the Iowa Gambling Task in 43 adolescents with excess weight against 38 adolescents with healthy weight. We computationally modelled both exploitation behaviour (e.g., reinforcement sensitivity and inverse decay parameters), and explorative behaviour (e.g., maximum directed exploration value). We found that overall, adolescents with excess weight displayed more behavioural exploration than their healthy-weight counterparts - specifically, demonstrating greater overall switching behaviour. Computational models revealed that this behaviour was driven by a higher maximum directed exploration value in the excess-weight group (U = 520.00, p = .005, BF10 = 5.11). Importantly, however, we found substantial evidence that groups did not differ in reinforcement sensitivity (U = 867.00, p = .641, BF10 = 0.30). Overall, our study demonstrates a preference for exploratory behaviour in adolescents with excess weight, independent of sensitivity to reward. This pattern could potentially underpin an intrinsic desire to explore energy-dense unhealthy foods - an as-yet untapped mechanism that could be targeted in future treatments of obesity in adolescents.

Neural underpinnings of food choice and consumption in obesity.

BACKGROUND/OBJECTIVES: Obesity is associated with unhealthy food choices. Food selection is driven by the subjective valuation of available options, and the perceived and actual rewards accompanying consumption. These cognitive operations are mediated by brain regions including the ventromedial prefrontal cortex (vmPFC), dorsal anterior cingulate cortex (dACC), and ventral striatum (vStr). This study investigated the relationship between body mass index (BMI) and functional activations in the vmPFC, dACC, and vStr during food selection and consumption. SUBJECTS/METHODS: After overnight fasting, 26 individuals (BMI: 18-40 kg/m2) performed a food choice task while being scanned with functional magnetic resonance imaging (fMRI). Each trial involved selecting one beverage from a pair of presented options, followed by delivery of a 3 mL aliquot of the selected option using an MR-compatible gustometer. We also tracked subjective preference for each beverage throughout the experiment. RESULTS: During food choice, individuals with greater BMI had less activation in the dorsolateral prefrontal cortex when selecting a high-value option and less vmPFC activation upon its consumption. Independent of BMI, during food choice the dACC and anterior insula elicited higher activation when a less preferred beverage was selected. Activation of the dACC and a broader frontoparietal network was also observed when deciding between options more similar in value. During consumption, receipt of a more preferred beverage was associated with greater vmPFC response, and attenuation of the dACC. CONCLUSIONS: An individual's preference for a food option modulates the brain activity associated with choosing and consuming it. The relationship between food preference and underlying brain activity is altered in obesity, with reduced engagement of cognition-related regions when presented with a highly valued option, but a blunted response in reward-related regions upon consumption.

Computational models of exploration and exploitation characterise onset and efficacy of treatment in methamphetamine use disorder.

People with Methamphetamine Use Disorder (PwMUD) spend substantial time and resources on substance use, which hinders their ability to explore alternate reinforcers. Gold-standard behavioural treatments attempt to remedy this by encouraging action towards non-drug reinforcers, but substance use often persists. We aimed to unravel the mechanistic drivers of this behaviour by applying a computational model of explore/exploit behaviour to decision-making data (Iowa Gambling Task) from 106 PwMUD and 48 controls. We then examined the longitudinal link between explore/exploit mechanisms and changes in methamphetamine use 6 weeks later. Exploitation parameters included reinforcement sensitivity and inverse decay (i.e., number of past outcomes used to guide choices). Exploration parameters included maximum directed exploration value (i.e., value of trying novel actions). The Timeline Follow Back measured changes in methamphetamine use. Compared to controls, PwMUD showed deficits in exploitative decision-making, characterised by reduced reinforcement sensitivity, U = 3065, p = 0.009, and less use of previous choice outcomes, U = 3062, p = 0.010. This was accompanied by a behavioural pattern of frequent shifting between choices, which appeared consistent with random exploration. Furthermore, PwMUD with greater reductions of methamphetamine use at 6 weeks had increased directed exploration (ß = 0.22, p = 0.045); greater use of past choice outcomes (ß = -0.39, p = 0.002) and greater choice consistency (ß = -0.39, p = 0.002). Therefore, limited computational exploitation and increased behavioural exploration characterise PwMUD's presentation to treatment, while increased directed exploration, use of past choice outcomes and choice consistency predict greater reductions of methamphetamine use.

Latent classes of maladaptive personality traits exhibit differences in social processing.

OBJECTIVE: Social processing (SP) deficits manifest across numerous mental disorders. However, this research has been plagued by heterogeneity and a piecemeal approach whereby skills are examined in isolation rather than as part of an integrated cognitive system. Here, we combined two dimensional frameworks of psychopathology to address these limitations. METHOD: We utilized the Alternative Model for Personality Disorders (AMPD) to distill trait-related heterogeneity within a community sample (n = 200), and the Research Domain Criteria (RDoC) 'Systems for Social Processes' to comprehensively assess SP. We first applied latent class analyses (LCA) to derive AMPD-based groups and subsequently contrasted the performance of these groups on a SP test battery that we developed to align with the RDoC SP constructs. RESULTS: Our LCA yielded four distinct subgroups. The recognizable trait profiles and psychopathological symptoms of these classes suggested they were clinically meaningful. The subgroups differed in their SP profiles: one displayed deficits regarding the self, a second displayed deficits in understanding others, a third displayed more severe deficits including affiliation problems, whilst the fourth showed normal performance. CONCLUSIONS: Our results support the link between clusters of maladaptive personality traits and distinctive profiles of SP deficits, which may inform research on disorders involving SP dysfunctions.

Neural network modelling reveals changes in directional connectivity between cortical and hypothalamic regions with increased BMI.

BACKGROUND/OBJECTIVES: Obesity has been ascribed to corticostriatal regions taking control over homeostatic areas. To test this assumption, we applied an effective connectivity approach to reveal the direction of information flow between brain regions and the valence of connections (excitatory versus inhibitory) as a function of increased BMI and homeostatic state. SUBJECTS/METHODS: Forty-one participants (21 overweight/obese) underwent two resting-state fMRI scans: after overnight fasting (hunger) and following a standardised meal (satiety). We used spectral dynamic causal modelling to unravel hunger and increased BMI-related changes in directed connectivity between cortical, insular, striatal and hypothalamic regions. RESULTS: During hunger, as compared to satiety, we found increased excitation of the ventromedial prefrontal cortex over the ventral striatum and hypothalamus, suggesting enhanced top-down modulation compensating energy depletion. Increased BMI was associated with increased excitation of the anterior insula over the hypothalamus across the hunger and satiety conditions. The interaction of hunger and increased BMI yielded decreased intra-cortical excitation from the dorso-lateral to the ventromedial prefrontal cortex. CONCLUSIONS: Our findings suggest that excess weight and obesity is associated with persistent top-down excitation of the hypothalamus, regardless of homeostatic state, and hunger-related reductions of dorso-lateral to ventromedial prefrontal inputs. These findings are compatible with eating without hunger and reduced self-regulation views of obesity.

Are methamphetamine users compulsive? Faulty reinforcement learning, not inflexibility, underlies decision making in people with methamphetamine use disorder.

Methamphetamine use disorder involves continued use of the drug despite negative consequences. Such 'compulsivity' can be measured by reversal learning tasks, which involve participants learning action-outcome task contingencies (acquisition-contingency) and then updating their behaviour when the contingencies change (reversal). Using these paradigms, animal models suggest that people with methamphetamine use disorder (PwMUD) may struggle to avoid repeating actions that were previously rewarded but are now punished (inflexibility). However, difficulties in learning task contingencies (reinforcement learning) may offer an alternative explanation, with meaningful treatment implications. We aimed to disentangle inflexibility and reinforcement learning deficits in 35 PwMUD and 32 controls with similar sociodemographic characteristics, using novel trial-by-trial analyses on a probabilistic reversal learning task. Inflexibility was defined as (a) weaker reversal phase performance, compared with the acquisition-contingency phases, and (b) persistence with the same choice despite repeated punishments. Conversely, reinforcement learning deficits were defined as (a) poor performance across both acquisition-contingency and reversal phases and (b) inconsistent postfeedback behaviour (i.e., switching after reward). Compared with controls, PwMUD exhibited weaker learning (odds ratio [OR] = 0.69, 95% confidence interval [CI] [0.63-0.77], p < .001), though no greater accuracy reduction during reversal. Furthermore, PwMUD were more likely to switch responses after one reward/punishment (OR = 0.83, 95% CI [0.77-0.89], p < .001; OR = 0.82, 95% CI [0.72-0.93], p = .002) but just as likely to switch after repeated punishments (OR = 1.03, 95% CI [0.73-1.45], p = .853). These results indicate that PwMUD's reversal learning deficits are driven by weaker reinforcement learning, not inflexibility.

Lack of longitudinal changes in cognition in individuals with methamphetamine use disorder during the first 6 weeks after commencing treatment.

Background: Methamphetamine use disorder (MUD) associates with cognitive impulsivity deficits. However, few studies have examined longitudinal changes in cognition, and it remains unclear if deficits resolve during early recovery.Objectives: To compare: (1) cognitive function of individuals with MUD at treatment onset and six-weeks later with controls tested over the same period; (2) cognitive changes in MUD-individuals who remained abstinent versus relapsed.Method: We recruited 108 participants meeting DSM-IV-TR criteria for methamphetamine dependence (81 males) and 50 demographically matched controls (38 males); 77 methamphetamine- dependent participants (59 males) and 48 controls (36 males) were retained at follow-up. We administered response inhibition, delay discounting and uncertainty-based decision-making tests at both endpoints. Relapse was defined as methamphetamine concentrations >0.4 ng/mg at follow-up in hair toxicology.Results: We found a significant time-by-group interaction on uncertainty-based decision-making (effect size: η2 = .05), although post-hoc tests to disentangle this interaction yielded inconclusive results (p-range = .14-.40; BF10-range = 0.43-1.67). There were no significant time-by-group interactions on response inhibition or delay discounting, with the former likely a null effect (η2-interaction = .003 and .02; BFincl = 0.23 and 0.71). There were no significant differences in cognitive recovery between individuals who maintained abstinence (n = 12) versus relapsed (n = 65) (η2-range = .003-.04), although evidence was inconclusive toward whether findings reflected true null effects (BFincl-range = 0.33-0.75).Conclusion: We did not find evidence that MUD-related cognitive impulsivity deficits improve beyond practice effects over 6 weeks. Findings do not support previous, albeit conflicting, evidence of early recovery of cognitive deficits in MUD.

Factors associated with the absence of cocaine craving in treatment-seeking individuals during inpatient cocaine detoxification.

BACKGROUND: Anecdotal evidence suggests a substantial proportion of individuals with cocaine use disorder do not report craving during inpatient detoxification. OBJECTIVE: To examine prevalence and clinical correlates of consistent absence of cocaine craving among inpatients during detoxification. We hypothesized that craving absence would be associated with less severity of cocaine use, depression, and anxiety. Alternative explanations were also explored. METHODS: Craving absence (i.e., non-cravers) was defined as a daily score of zero across two separate craving visual analogue scales in each of the inpatient days. Participants scoring ≥1 on ≥1 day were considered cravers. Severity of cocaine use disorder as well as in-treatment depression and anxiety were assessed. Alternative contributors included presence of cocaine and other substances in urine at admission, in-treatment prescription of psychotropic medications, treatment motivation, executive function, interoception, and social desirability. RESULTS: Eighty-seven participants (78.2% males) met criteria as either non-cravers (n = 29; 33.3%) or cravers (n = 58; 66.7%). Mean length of admission in non-cravers and cravers was, respectively, 10.83 and 13.16 days. Binary logistic regression model showed that non-cravers scored significantly lower than cravers on cocaine use during last month before treatment (OR, 95% CI; 0.902, 0.839-0.970), in-treatment depression (OR, 95% CI; 0.794, 0.659-0.956), and in-treatment prescribing of antipsychotics (OR, 95% CI; 0.109, 0.014-0.823). Model prediction accuracy was 88.9%. CONCLUSIONS: One in three patients undergoing inpatient detoxification experienced absence of craving, linked to less pretreatment cocaine use, better mood, and decreased administration of antipsychotics. Findings may inform pretreatment strategies and improve treatment cost-effectiveness.

Stressing diets? Amygdala networks, cumulative cortisol, and weight loss in adolescents with excess weight.

OBJECTIVE: The amygdala is importantly involved in stress and obesity, but its role on weight change and diet-related stress remains unexplored among adolescents with excess weight. We aimed to examine the functional connectivity of the Central and Basolateral amygdala nuclei (CeA and BLA) among adolescents, and to explore the longitudinal association between brain connectivity measures and diet-related cortisol and weight loss in adolescents with excess weight. METHODS: We compared resting-state functional connectivity between adolescents with excess (EW, N = 34; Age = 16.44 ± 1.66) and normal weight (NW, N = 36; Age = 16.50 ± 1.40) using a seed-based (CeA and BLA) whole-brain approach. Then, in a subset of 30 adolescents with EW, followed-up after 3-months of dietary/lifestyle intervention, we explored for interactions between connectivity in the CeA/BLA networks and weight loss. Regression analyses were performed to explore the relationship between accumulated cortisol and weight loss, and to test the potential effect of the amygdala networks on such association. RESULTS: In EW compared with NW, the CeA regions showed higher functional connectivity with anterior portions, and lower connectivity with posterior portions of the cingulate cortex, while the left BLA regions showed lower connectivity with the dorsal caudate and angular gyrus. In addition, higher connectivity between the left CeA-midbrain network was negatively associated with weight loss. Hair cortisol significantly predicted weight change (p = 0.012). However, this association was no longer significant (p = 0.164) when considering the CeA-midbrain network in the model as an additional predictor. CONCLUSIONS: Adolescents with EW showed functional connectivity alterations within the BLA/CeA networks. The CeA-midbrain network might constitute an important brain pathway regulating weight change.

Subcortical surface morphometry in substance dependence: An ENIGMA addiction working group study.

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.

Neuroanatomical alterations in people with high and low cannabis dependence.

OBJECTIVES: We aimed to investigate whether severity of cannabis dependence is associated with the neuroanatomy of key brain regions of the stress and reward brain circuits. METHODS: To examine dependence-specific regional brain alterations, we compared the volumes of regions relevant to reward and stress, between high-dependence cannabis users (CD+, n = 25), low-dependence cannabis users (CD-, n = 20) and controls (n = 37). RESULTS: Compared to CD- and/or controls, the CD+ group had lower cerebellar white matter and hippocampal volumes, and deflation of the right hippocampus head and tail. CONCLUSION: These findings provide initial support for neuroadaptations involving stress and reward circuits that are specific to high-dependence cannabis users.

A transdiagnostic perspective of constructs underlying obsessive-compulsive and related disorders: An international Delphi consensus study.

BACKGROUND: The Research Domain Criteria seeks to bridge knowledge from neuroscience with clinical practice by promoting research into valid neurocognitive phenotypes and dimensions, irrespective of symptoms and diagnoses as currently conceptualized. While the Research Domain Criteria offers a vision of future research and practice, its 39 functional constructs need refinement to better target new phenotyping efforts. This study aimed to determine which Research Domain Criteria constructs are most relevant to understanding obsessive-compulsive and related disorders, based on a consensus between experts in the field of obsessive-compulsive and related disorders. METHODS: Based on a modified Delphi method, 46 experts were recruited from Australia, Africa, Asia, Europe and the Americas. Over three rounds, experts had the opportunity to review their opinion in light of feedback from the previous round, which included how their response compared to other experts and a summary of comments given. RESULTS: Thirty-four experts completed round one, of whom 28 (82%) completed round two and 24 (71%) completed round three. At the final round, four constructs were endorsed by ⩾75% of experts as 'primary constructs' and therefore central to understanding obsessive-compulsive and related disorders. Of these constructs, one came from the Positive Valence System (Habit), two from the Cognitive Control System (Response Selection/Inhibition and Performance Monitoring) and the final construct was an additional item suggested by experts (Compulsivity). CONCLUSION: This study identified four Research Domain Criteria constructs that, according to experts, cut across different obsessive-compulsive and related disorders. These constructs represent key areas for future investigation, and may have potential implications for clinical practice in terms of diagnostic processes and therapeutic management of obsessive-compulsive and related disorders.