Mega-analysis of the brain-age gap in substance use disorder: An ENIGMA Addiction working group study.

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.

Estimating biological age from retinal imaging: a scoping review.

BACKGROUND/AIMS: The emerging concept of retinal age, a biomarker derived from retinal images, holds promise in estimating biological age. The retinal age gap (RAG) represents the difference between retinal age and chronological age, which serves as an indicator of deviations from normal ageing. This scoping review aims to collate studies on retinal age to determine its potential clinical utility and to identify knowledge gaps for future research. METHODS: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist, eligible non-review, human studies were identified, selected and appraised. PubMed, Scopus, SciELO, PsycINFO, Google Scholar, Cochrane, CINAHL, Africa Wide EBSCO, MedRxiv and BioRxiv databases were searched to identify literature pertaining to retinal age, the RAG and their associations. No restrictions were imposed on publication date. RESULTS: Thirteen articles published between 2022 and 2023 were analysed, revealing four models capable of determining biological age from retinal images. Three models, 'Retinal Age', 'EyeAge' and a 'convolutional network-based model', achieved comparable mean absolute errors: 3.55, 3.30 and 3.97, respectively. A fourth model, 'RetiAGE', predicting the probability of being older than 65 years, also demonstrated strong predictive ability with respect to clinical outcomes. In the models identified, a higher predicted RAG demonstrated an association with negative occurrences, notably mortality and cardiovascular health outcomes. CONCLUSION: This review highlights the potential clinical application of retinal age and RAG, emphasising the need for further research to establish their generalisability for clinical use, particularly in neuropsychiatry. The identified models showcase promising accuracy in estimating biological age, suggesting its viability for evaluating health status.

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder: a mega-analysis by the ENIGMA-PGC PTSD workgroup.

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p-FDR < 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.

Age of onset of obsessive-compulsive disorder differentially affects white matter microstructure.

Previous diffusion MRI studies have reported mixed findings on white matter microstructure alterations in obsessive-compulsive disorder (OCD), likely due to variation in demographic and clinical characteristics, scanning methods, and underpowered samples. The OCD global study was created across five international sites to overcome these challenges by harmonizing data collection to identify consistent brain signatures of OCD that are reproducible and generalizable. Single-shell diffusion measures (e.g., fractional anisotropy), multi-shell Neurite Orientation Dispersion and Density Imaging (NODDI) and fixel-based measures, were extracted from skeletonized white matter tracts in 260 medication-free adults with OCD and 252 healthy controls. We additionally performed structural connectome analysis. We compared cases with controls and cases with early (<18) versus late (18+) OCD onset using mixed-model and Bayesian multilevel analysis. Compared with healthy controls, adult OCD individuals showed higher fiber density in the sagittal stratum (B[SE] = 0.10[0.05], P = 0.04) and credible evidence for higher fiber density in several other tracts. When comparing early (n = 145) and late-onset (n = 114) cases, converging evidence showed lower integrity of the posterior thalamic radiation -particularly radial diffusivity (B[SE] = 0.28[0.12], P = 0.03)-and lower global efficiency of the structural connectome (B[SE] = 15.3[6.6], P = 0.03) in late-onset cases. Post-hoc analyses indicated divergent direction of effects of the two OCD groups compared to healthy controls. Age of OCD onset differentially affects the integrity of thalamo-parietal/occipital tracts and the efficiency of the structural brain network. These results lend further support for the role of the thalamus and its afferent fibers and visual attentional processes in the pathophysiology of OCD.

Examining the association between posttraumatic stress disorder and disruptions in cortical networks identified using data-driven methods.

Posttraumatic stress disorder (PTSD) is associated with lower cortical thickness (CT) in prefrontal, cingulate, and insular cortices in diverse trauma-affected samples. However, some studies have failed to detect differences between PTSD patients and healthy controls or reported that PTSD is associated with greater CT. Using data-driven dimensionality reduction, we sought to conduct a well-powered study to identify vulnerable networks without regard to neuroanatomic boundaries. Moreover, this approach enabled us to avoid the excessive burden of multiple comparison correction that plagues vertex-wise methods. We derived structural covariance networks (SCNs) by applying non-negative matrix factorization (NMF) to CT data from 961 PTSD patients and 1124 trauma-exposed controls without PTSD. We used regression analyses to investigate associations between CT within SCNs and PTSD diagnosis (with and without accounting for the potential confounding effect of trauma type) and symptom severity in the full sample. We performed additional regression analyses in subsets of the data to examine associations between SCNs and comorbid depression, childhood trauma severity, and alcohol abuse. NMF identified 20 unbiased SCNs, which aligned closely with functionally defined brain networks. PTSD diagnosis was most strongly associated with diminished CT in SCNs that encompassed the bilateral superior frontal cortex, motor cortex, insular cortex, orbitofrontal cortex, medial occipital cortex, anterior cingulate cortex, and posterior cingulate cortex. CT in these networks was significantly negatively correlated with PTSD symptom severity. Collectively, these findings suggest that PTSD diagnosis is associated with widespread reductions in CT, particularly within prefrontal regulatory regions and broader emotion and sensory processing cortical regions.

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

A Systematic Review of the Efficacy of Contingency Management for Substance Use Disorders in Low and Middle Income Countries.

BACKGROUND: The impact of illicit substance use is especially devastating in low-resourced countries where factors such as poverty, unemployment, and inadequate services impede successful treatment. Contingency management (CM) is a treatment for substance use disorders that has shown to be effective in eliciting behaviour change. The efficacy of CM interventions in low and middle income countries (LMICs) has been under explored. METHODS: The aim of this systematic review of randomized controlled trials was to assess measures of CM efficacy in addressing substance use disorders, while also considering contextual moderators of CM in LMICs. A search of PubMed, Scopus, and Cochrane library databases yielded 18 studies for inclusion, from which relevant data were extracted using modified versions of the Cochrane Characteristics of Studies tool. RESULTS: Two studies were located in a low-income country, two in lower-middle income countries, and fourteen in upper middle-income countries. Overall, estimated efficacy estimates were similar to those from higher income countries. However, context-specific challenges that warrant further investigation included limited access to trained staff and structural and financial constraints. CONCLUSIONS: While CM in LMICs is in its early stages of development, efficacy estimates were not substantially different compared to high income countries. Challenges such as costs, willingness to implement, and the stigma associated with addiction sets the stage for further research in these contexts.

Contextualizing the impact of prenatal alcohol and tobacco exposure on neurodevelopment in a South African birth cohort: an analysis from the socioecological perspective.

Background: Alcohol and tobacco are known teratogens. Historically, more severe prenatal alcohol exposure (PAE) and prenatal tobacco exposure (PTE) have been examined as the principal predictor of neurodevelopmental alterations, with little incorporation of lower doses or ecological contextual factors that can also impact neurodevelopment, such as socioeconomic resources (SER) or adverse childhood experiences (ACEs). Here, a novel analytical approach informed by a socio-ecological perspective was used to examine the associations between SER, PAE and/or PTE, and ACEs, and their effects on neurodevelopment. Methods: N = 313 mother-child dyads were recruited from a prospective birth cohort with maternal report of PAE and PTE, and cross-sectional structural brain neuroimaging of child acquired via 3T scanner at ages 8-11 years. In utero SER was measured by maternal education, household income, and home utility availability. The child's ACEs were measured by self-report assisted by the researcher. PAE was grouped into early exposure (<12 weeks), continued exposure (>=12 weeks), and no exposure controls. PTE was grouped into exposed and non-exposed controls. Results: Greater access to SER during pregnancy was associated with fewer ACEs (maternal education: ß = -0.293,p = 0.01; phone access: ß = -0.968,p = 0.05). PTE partially mediated the association between SER and ACEs, where greater SER reduced the likelihood of PTE, which was positively associated with ACEs (ß = 1.110,p = 0.01). SER was associated with alterations in superior frontal (ß = -1336.036, q = 0.046), lateral orbitofrontal (ß = -513.865, q = 0.046), caudal anterior cingulate volumes (ß = -222.982, q = 0.046), with access to phone negatively associated with all three brain volumes. Access to water was positively associated with superior frontal volume (ß=1569.527, q = 0.013). PTE was associated with smaller volumes of lateral orbitofrontal (ß = -331.000, q = 0.033) and nucleus accumbens regions (ß = -34.800, q = 0.033). Conclusion: Research on neurodevelopment following community-levels of PAE and PTE should more regularly consider the ecological context to accelerate understanding of teratogenic outcomes. Further research is needed to replicate this novel conceptual approach with varying PAE and PTE patterns, to disentangle the interplay between dose, community-level and individual-level risk factors on neurodevelopment.

PTSD and comorbid MDD is associated with activation of the right frontoparietal network.

There is growing evidence of abnormalities in intrinsic functional connectivity (FC) in posttraumatic stress disorder (PTSD) and major depressive disorder (MDD). However, there has been less work on the commonly occurring co-presentation of PTSD and MDD. Characterising intrinsic FC abnormalities in this clinical population is important for understanding how they may contribute towards impairments underpinned by different networks. Participants were mothers enroled in the Drakenstein Child Health Study from Western Cape, South Africa. Mothers between 18 and 50 years of age were recruited and divided into 4 groups: PTSD, MDD, PTSD with MDD, and healthy controls. Participants underwent resting-state fMRI at the 18-month postpartum time point. Functional connectivity within and between higher order cognitive control networks, including the salience, dorsal attention, frontoparietal, and default mode networks were compared across the 4 groups. PTSD with comorbid MDD was associated with greater intrinsic FC within the R FPAR, relative to controls and the mono-diagnostic groups. Intrinsic FC differences were observed within the default mode network for the MDD group. No group differences in connectivity between networks were observed. Differential intrinsic connectivity in participants with comorbidity are consistent with evidence that such individuals have more severe illness and require more robust intervention.

Genetic Influences on the Developing Young Brain and Risk for Neuropsychiatric Disorders.

Imaging genetics provides an opportunity to discern associations between genetic variants and brain imaging phenotypes. Historically, the field has focused on adults and adolescents; very few imaging genetics studies have focused on brain development in infancy and early childhood (from birth to age 6 years). This is an important knowledge gap because developmental changes in the brain during the prenatal and early postnatal period are regulated by dynamic gene expression patterns that likely play an important role in establishing an individual's risk for later psychiatric illness and neurodevelopmental disabilities. In this review, we summarize findings from imaging genetics studies spanning from early infancy to early childhood, with a focus on studies examining genetic risk for neuropsychiatric disorders. We also introduce the Organization for Imaging Genomics in Infancy (ORIGINs), a working group of the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium, which was established to facilitate large-scale imaging genetics studies in infancy and early childhood.

Advanced brain ageing in adult psychopathology: A systematic review and meta-analysis of structural MRI studies.

Evidence suggests that psychopathology is associated with an advanced brain ageing process, typically mapped using machine learning models that predict an individual's age based on structural neuroimaging data. The brain predicted age difference (brain-PAD) captures the deviation of brain age from chronological age. Substantial heterogeneity between studies has introduced uncertainty regarding the magnitude of the brain-PAD in adult psychopathology. The present meta-analysis aimed to quantify structural MRI-based brain-PAD in adult psychotic and mood disorders, while addressing possible sources of heterogeneity related to diagnosis subtypes, segmentation method, age and sex. Clinical factors influencing brain ageing in axis 1 psychiatric disorders were systematically reviewed. Thirty-three studies were included for review. A random-effects meta-analysis revealed a brain-PAD of +3.12 (standard error = 0.49) years in psychotic disorders (n = 16 studies), +2.04 (0.10) years in bipolar disorder (n = 5), and +0.90 (0.20) years in major depression (n = 7). An exploratory meta-analysis found a brain-PAD of +1.57 (0.67) in first episode psychosis (n = 4), which was smaller than that observed in psychosis and schizophrenia (n = 10, +3.87 (0.61)). Patient mean age significantly explained heterogeneity in effect size estimates in psychotic disorders, but not mood disorders. The systematic review determined that clinical factors, such as higher symptom severity, may be associated with a larger brain-PAD in psychopathology. In conclusion, larger structural MRI-based brain-PAD was confirmed in adult psychopathology. Preliminary evidence was obtained that brain ageing is greater in those with prolonged duration of psychotic disorders. Accentuated brain ageing may underlie the cognitive difficulties experienced by some patients, and may be progressive in nature.

Global multi-center and multi-modal magnetic resonance imaging study of obsessive-compulsive disorder: Harmonization and monitoring of protocols in healthy volunteers and phantoms.

OBJECTIVES: We describe the harmonized MRI acquisition and quality assessment of an ongoing global OCD study, with the aim to translate representative, well-powered neuroimaging findings in neuropsychiatric research to worldwide populations. METHODS: We report on T1-weighted structural MRI, resting-state functional MRI, and multi-shell diffusion-weighted imaging of 140 healthy participants (28 per site), two traveling controls, and regular phantom scans. RESULTS: Human image quality measures (IQMs) and outcome measures showed smaller within-site variation than between-site variation. Outcome measures were less variable than IQMs, especially for the traveling controls. Phantom IQMs were stable regarding geometry, SNR, and mean diffusivity, while fMRI fluctuation was more variable between sites. CONCLUSIONS: Variation in IQMs persists, even for an a priori harmonized data acquisition protocol, but after pre-processing they have less of an impact on the outcome measures. Continuous monitoring IQMs per site is valuable to detect potential artifacts and outliers. The inclusion of both cases and healthy participants at each site remains mandatory.

The impact of prenatal alcohol and/or tobacco exposure on brain structure in a large sample of children from a South African birth cohort.

BACKGROUND: Neuroimaging studies have emphasized the impact of prenatal alcohol exposure (PAE) on brain development, traditionally in heavily exposed participants. However, less is known about how naturally occurring community patterns of PAE (including light to moderate exposure) affect brain development, particularly in consideration of commonly occurring concurrent impacts of prenatal tobacco exposure (PTE). METHODS: Three hundred thirty-two children (ages 8 to 12) living in South Africa's Cape Flats townships underwent structural magnetic resonance imaging. During pregnancy, their mothers reported alcohol and tobacco use, which was used to evaluate PAE and PTE effects on their children's brain structure. Analyses involved the main effects of PAE and PTE (and their interaction) and the effects of PAE and PTE quantity on cortical thickness, surface area, and volume. RESULTS: After false-discovery rate (FDR) correction, PAE was associated with thinner left parahippocampal cortices, while PTE was associated with smaller cortical surface area in the bilateral pericalcarine, left lateral orbitofrontal, right posterior cingulate, right rostral anterior cingulate, left caudal middle frontal, and right caudal anterior cingulate gyri. There were no PAE × PTE interactions nor any associations of PAE and PTE exposure on volumetrics that survived FDR correction. CONCLUSION: PAE was associated with reduction in the structure of the medial temporal lobe, a brain region critical for learning and memory. PTE had stronger and broader associations, including with regions associated with executive function, reward processing, and emotional regulation, potentially reflecting continued postnatal exposure to tobacco (i.e., second-hand smoke exposure). These differential effects are discussed with respect to reduced PAE quantity in our exposed group versus prior studies within this geographical location, the deep poverty in which participants live, and the consequences of apartheid and racially and economically driven payment practices that contributed to heavy drinking in the region. Longer-term follow-up is needed to determine potential environmental and other moderators of the brain findings here and assess the extent to which they endure over time.

A comparison of methods to harmonize cortical thickness measurements across scanners and sites.

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants' demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2-81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3-85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects.

Limited evidence for a moderating effect of HIV status on brain age in heavy episodic drinkers.

We set out to test the hypothesis that greater brain ageing will be observed in people with HIV (PWH) and those who engage in heavy episodic drinking (HED), with their combined effects being especially detrimental in cognitive control brain networks. We correlated measures of "brain age gap" (BAG) and neurocognitive impairment in participants with and without HIV and HED. Sixty-nine participants were recruited from a community health centre in Cape Town: HIV - /HED - (N = 17), HIV + /HED - (N = 14), HIV - /HED + (N = 21), and HIV + /HED + (N = 17). Brain age was modelled using structural MRI features from the whole brain or one of six brain regions. Linear regression models were employed to identify differences in BAG between patient groups and controls. Associations between BAG and clinical data were tested using bivariate statistical methods. Compared to controls, greater global BAG was observed in heavy drinkers, both with (Cohen's d = 1.52) and without (d = 1.61) HIV. Differences in BAG between HED participants and controls were observed for the cingulate and parietal cortex, as well as subcortically. A larger BAG was associated with higher total drinking scores but not nadir CD4 count or current HIV viral load. The association between heavy episodic drinking and BAG, independent of HIV status, points to the importance of screening for alcohol use disorders in primary care. The relatively large contribution of cognitive control brain regions to BAG highlights the utility of assessing the contribution of different brain regions to brain age.

Remodeling of the Cortical Structural Connectome in Posttraumatic Stress Disorder: Results From the ENIGMA-PGC Posttraumatic Stress Disorder Consortium.

BACKGROUND: Posttraumatic stress disorder (PTSD) is accompanied by disrupted cortical neuroanatomy. We investigated alteration in covariance of structural networks associated with PTSD in regions that demonstrate the case-control differences in cortical thickness (CT) and surface area (SA). METHODS: Neuroimaging and clinical data were aggregated from 29 research sites in >1300 PTSD cases and >2000 trauma-exposed control subjects (ages 6.2-85.2 years) by the ENIGMA-PGC (Enhancing Neuro Imaging Genetics through Meta Analysis-Psychiatric Genomics Consortium) PTSD working group. Cortical regions in the network were rank ordered by the effect size of PTSD-related cortical differences in CT and SA. The top-n (n = 2-148) regions with the largest effect size for PTSD > non-PTSD formed hypertrophic networks, the largest effect size for PTSD < non-PTSD formed atrophic networks, and the smallest effect size of between-group differences formed stable networks. The mean structural covariance (SC) of a given n-region network was the average of all positive pairwise correlations and was compared with the mean SC of 5000 randomly generated n-region networks. RESULTS: Patients with PTSD, relative to non-PTSD control subjects, exhibited lower mean SC in CT-based and SA-based atrophic networks. Comorbid depression, sex, and age modulated covariance differences of PTSD-related structural networks. CONCLUSIONS: Covariance of structural networks based on CT and cortical SA are affected by PTSD and further modulated by comorbid depression, sex, and age. The SC networks that are perturbed in PTSD comport with converging evidence from resting-state functional connectivity networks and networks affected by inflammatory processes and stress hormones in PTSD.

Pharmacotherapy for post traumatic stress disorder (PTSD).

BACKGROUND: Posttraumatic stress disorder (PTSD) is a prevalent and disabling disorder. Evidence that PTSD is characterised by specific psychobiological dysfunctions has contributed to a growing interest in the use of medication in its treatment. OBJECTIVES: To assess the effects of medication for reducing PTSD symptoms in adults with PTSD. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL; Issue 11, November 2020); MEDLINE (1946-), Embase (1974-), PsycINFO (1967-) and PTSDPubs (all available years) either directly or via the Cochrane Common Mental Disorders Controlled Trials Register (CCMDCTR). We also searched international trial registers. The date of the latest search was 13 November 2020. SELECTION CRITERIA: All randomised controlled trials (RCTs) of pharmacotherapy for adults with PTSD. DATA COLLECTION AND ANALYSIS: Three review authors (TW, JI, and NP) independently assessed RCTs for inclusion in the review, collated trial data, and assessed trial quality. We contacted investigators to obtain missing data. We stratified summary statistics by medication class, and by medication agent for all medications. We calculated dichotomous and continuous measures using a random-effects model, and assessed heterogeneity. MAIN RESULTS: We include 66 RCTs in the review (range: 13 days to 28 weeks; 7442 participants; age range 18 to 85 years) and 54 in the meta-analysis.  For the primary outcome of treatment response, we found evidence of beneficial effect for selective serotonin reuptake inhibitors (SSRIs) compared with placebo (risk ratio (RR) 0.66, 95% confidence interval (CI) 0.59 to 0.74; 8 studies, 1078 participants), which improved PTSD symptoms in 58% of SSRI participants compared with 35% of placebo participants, based on moderate-certainty evidence.  For this outcome we also found evidence of beneficial effect for the noradrenergic and specific serotonergic antidepressant (NaSSA) mirtazapine: (RR 0.45, 95% CI 0.22 to 0.94; 1 study, 26 participants) in 65% of people on mirtazapine compared with 22% of placebo participants, and for the tricyclic antidepressant (TCA) amitriptyline (RR 0.60, 95% CI 0.38 to 0.96; 1 study, 40 participants) in 50% of amitriptyline participants compared with 17% of placebo participants, which improved PTSD symptoms. These outcomes are based on low-certainty evidence. There was however no evidence of beneficial effect for the number of participants who improved with the antipsychotics (RR 0.51, 95% CI 0.16 to 1.67; 2 studies, 43 participants) compared to placebo, based on very low-certainty evidence. For the outcome of treatment withdrawal, we found evidence of a harm for the individual SSRI agents compared with placebo (RR 1.41, 95% CI 1.07 to 1.87; 14 studies, 2399 participants). Withdrawals were also higher for the separate SSRI paroxetine group compared to the placebo group (RR 1.55, 95% CI 1.05 to 2.29; 5 studies, 1101 participants). Nonetheless, the absolute proportion of individuals dropping out from treatment due to adverse events in the SSRI groups was low (9%), based on moderate-certainty evidence. For the rest of the medications compared to placebo, we did not find evidence of harm for individuals dropping out from treatment due to adverse events. AUTHORS' CONCLUSIONS: The findings of this review support the conclusion that SSRIs improve PTSD symptoms; they are first-line agents for the pharmacotherapy of PTSD, based on moderate-certainty evidence. The NaSSA mirtazapine and the TCA amitriptyline may also improve PTSD symptoms, but this is based on low-certainty evidence. In addition, we found no evidence of benefit for the number of participants who improved following treatment with the antipsychotic group compared to placebo, based on very low-certainty evidence. There remain important gaps in the evidence base, and a continued need for more effective agents in the management of PTSD.

Pharmacotherapy for trichotillomania.

BACKGROUND: Trichotillomania (TTM; hair-pulling disorder) is a prevalent and disabling disorder characterised by recurrent hair-pulling. Here we update a previous Cochrane Review on the effects of medication for TTM. OBJECTIVES: To assess the effects of medication for trichotillomania (TTM) in adults, children and adolescents compared with placebo or other medication. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, PsycINFO, eleven other bibliographic databases, trial registries and grey literature sources (to 26 November 2020). We checked reference lists and contacted subject experts. SELECTION CRITERIA: We selected randomised controlled trials of medication versus placebo or other medication for TTM in adults, children and adolescents. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane. MAIN RESULTS: Twelve studies were included. We identified 10 studies in adults (286 participants) with a mean sample size of 29 participants per trial; one study in children and adolescents (39 participants); and, one study in adults and adolescents (22 participants: 18 adults and 4 adolescents). All studies were single-centre, outpatient trials. Eleven studies compared medication and placebo (334 participants); one study compared two medications (13 participants). Studies were 5 to 13 weeks duration. We undertook meta-analysis only for opioid antagonists as other comparisons contained a single study, or reported insufficient data. Antioxidants versus placebo in adults There was little to no difference in treatment response between antioxidant (35.7%) and placebo groups (28.6%) after six weeks, based on a single trial of silymarin (risk ratio (RR) 2.25, 95% confidence interval (CI) 0.84 to 5.99; 36 participants; low-certainty evidence). We could not calculate differences in number of dropouts as there were no events in either group (18 participants; low-certainty evidence). Antioxidants versus placebo in adolescents There was little to no difference in treatment response between antioxidant (50%) and placebo groups (25%) after six weeks, based on a single trial of silymarin (RR 2.00, 95% CI 0.28 to 14.20; 8 participants; low-certainty evidence). We could not calculate differences in number of dropouts as there were no events in either group (8 participants; low-certainty evidence). Antipsychotics versus placebo in adults There may be greater treatment response in the antipsychotic group (85%) compared to the placebo group (17%) after 12 weeks, based on a single trial of olanzapine (RR 5.08, 95% CI 1.4 to 18.37; 25 participants; low-certainty evidence). We could not calculate differences in number of dropouts as there were no events in either group (25 participants; low-certainty evidence). Cell signal transducers versus placebo in adults There was little to no difference in treatment response between cell signal transducer (42.1%) and placebo groups (31.6%) after 10 weeks, based on a single trial of inositol (RR 1.33, 95% CI 0.57 to 3.11; 38 participants; low-certainty evidence). We could not calculate differences in number of dropouts as there were no events in either group (38 participants; low-certainty evidence). Glutamate modulators versus placebo in adults There is probably greater treatment response in the glutamate modulator group (56%) compared to the placebo group (16%) after 12 weeks, based on a single trial of N-acetylcysteine (RR 3.5, 95% CI 1.34 to 9.17; 50 participants; moderate-certainty evidence). We could not calculate differences in number of dropouts as there were no events in either group (50 participants; low-certainty evidence). Glutamate modulators versus placebo in children and adolescents There was little to no difference in treatment response between the glutamate modulator (25%) and placebo groups (21.1%) in children and adolescents, based on a single trial of N-acetylcysteine (RR 1.19, 95% CI 0.37 to 3.77; 39 participants; low-certainty evidence). There was little to no difference in dropouts due to adverse events between glutamate modulator (5%) and placebo (0%) groups, based on a single trial (RR 2.86, 95% CI 0.12 to 66.11; 39 participants; low-certainty evidence). Opioid antagonists versus placebo in adults There may be little to no difference in treatment response between opioid antagonist (37.5%) and placebo groups (25%) after six to eight weeks, based on two studies of naltrexone, but the evidence is very uncertain (RR 2.14, 95% CI 0.25 to 18.17; 2 studies, 68 participants; very low-certainty evidence). No data were available regarding dropouts due to adverse events. Selective serotonin reuptake inhibitors (SSRIs) versus placebo in adults There were no data available for treatment response to SSRIs. There was little to no difference in dropouts due to adverse events in the SSRI group (5.1%) compared to the placebo group (0%) after 6 to 12 weeks, based on two trials of fluoxetine (RR 3.00, 95% CI 0.33 to 27.62; 2 studies, 78 participants; low-certainty evidence). Tricyclic antidepressants (TCAs) with predominantly serotonin reuptake inhibitor (SRI) actions versus placebo in adults There may be greater treatment response in the TCAs with predominantly SRI actions group (40%) compared to the placebo group (0%) after nine weeks, but the evidence is very uncertain, based on a single trial of clomipramine (RR 5.73, 95% CI 0.36 to 90.83; 16 participants; very low-certainty evidence). There may be increased dropouts due to adverse events in the TCAs with predominantly SRI actions group (30%) compared to the placebo group (0%), but the evidence is very uncertain (RR 4.45, 95% CI 0.27 to 73.81; 16 participants; very low-certainty evidence). TCAs with predominantly SRI actions versus other TCAs in adults There may be greater treatment response in the TCAs with predominantly SRI actions group compared to the other TCAs group after five weeks, based on a single trial comparing clomipramine to desipramine (mean difference (MD) -4.00, 95% CI -6.13 to -1.87; 26 participants; low-certainty evidence). We could not calculate differences in number of dropouts as there were no events in either group (26 participants; low-certainty evidence). AUTHORS' CONCLUSIONS: There was insufficient evidence from meta-analysis to confirm or refute the efficacy of any agent or class of medication for the treatment of TTM in adults, children or adolescents. Preliminary evidence suggests there may be beneficial treatment effects for N-acetylcysteine, clomipramine and olanzapine in adults based on four trials, albeit with relatively small sample sizes.

Executive Function and Contingency Management in Methamphetamine Use Disorder.

OBJECTIVES: Contingency management is a promising intervention for Methamphetamine Use Disorder (MUD).Impaired executive function may decrease adherence to such treatment, but there are few data on whether impairment in executive function predicts treatment outcomes. We therefore evaluated whether baseline performance on tests of executive function predicted treatment response in a trial of contingency management for MUD. METHODS: Thirty participants with MUD and 23 healthy controls performed the Connors Continuous Performance Task (CPT) and the Trail Making Task. MUD participants then entered an 8-week contingency management trial. Participants were categorized as responders (n=17; no methamphetamine-positive urine tests) or non-responders (n=13; >1 positive test). The Kruskal-Wallis test was used to compare scores in participants with MUD and healthy controls, and in responders versus non-responders. RESULTS: Participants withMUD performed worse than controls on the CPT (d-prime) (p=0.012); non-responders performed worse than responders (p = 0.034). Performance of MUD participants did not differ significantly from controls on the Trail Making Task B (time to completion), but variation was high with non-responders performing worse than responders (p=0.013). CONCLUSION: These findings suggest that tests of executive function at baseline may be useful in predicting treatment response in MUD. Future work in larger samples may ultimately allow a more personalized treatment approach to methamphetamine use disorder.