Rare coding variants in ten genes confer substantial risk for schizophrenia.

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, P < 2.14 × 10-6) and 32 genes at a false discovery rate of <5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure and function of the synapse. The associations of the NMDA (N-methyl-D-aspartate) receptor subunit GRIN2A and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptor subunit GRIA3 provide support for dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We observe an overlap of rare variant risk among schizophrenia, autism spectrum disorders1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach.

Individualized prediction models in ADHD: a systematic review and meta-regression.

There have been increasing efforts to develop prediction models supporting personalised detection, prediction, or treatment of ADHD. We overviewed the current status of prediction science in ADHD by: (1) systematically reviewing and appraising available prediction models; (2) quantitatively assessing factors impacting the performance of published models. We did a PRISMA/CHARMS/TRIPOD-compliant systematic review (PROSPERO: CRD42023387502), searching, until 20/12/2023, studies reporting internally and/or externally validated diagnostic/prognostic/treatment-response prediction models in ADHD. Using meta-regressions, we explored the impact of factors affecting the area under the curve (AUC) of the models. We assessed the study risk of bias with the Prediction Model Risk of Bias Assessment Tool (PROBAST). From 7764 identified records, 100 prediction models were included (88% diagnostic, 5% prognostic, and 7% treatment-response). Of these, 96% and 7% were internally and externally validated, respectively. None was implemented in clinical practice. Only 8% of the models were deemed at low risk of bias; 67% were considered at high risk of bias. Clinical, neuroimaging, and cognitive predictors were used in 35%, 31%, and 27% of the studies, respectively. The performance of ADHD prediction models was increased in those models including, compared to those models not including, clinical predictors (ß = 6.54, p = 0.007). Type of validation, age range, type of model, number of predictors, study quality, and other type of predictors did not alter the AUC. Several prediction models have been developed to support the diagnosis of ADHD. However, efforts to predict outcomes or treatment response have been limited, and none of the available models is ready for implementation into clinical practice. The use of clinical predictors, which may be combined with other type of predictors, seems to improve the performance of the models. A new generation of research should address these gaps by conducting high quality, replicable, and externally validated models, followed by implementation research.

A primer on the use of machine learning to distil knowledge from data in biological psychiatry.

Applications of machine learning in the biomedical sciences are growing rapidly. This growth has been spurred by diverse cross-institutional and interdisciplinary collaborations, public availability of large datasets, an increase in the accessibility of analytic routines, and the availability of powerful computing resources. With this increased access and exposure to machine learning comes a responsibility for education and a deeper understanding of its bases and bounds, borne equally by data scientists seeking to ply their analytic wares in medical research and by biomedical scientists seeking to harness such methods to glean knowledge from data. This article provides an accessible and critical review of machine learning for a biomedically informed audience, as well as its applications in psychiatry. The review covers definitions and expositions of commonly used machine learning methods, and historical trends of their use in psychiatry. We also provide a set of standards, namely Guidelines for REporting Machine Learning Investigations in Neuropsychiatry (GREMLIN), for designing and reporting studies that use machine learning as a primary data-analysis approach. Lastly, we propose the establishment of the Machine Learning in Psychiatry (MLPsych) Consortium, enumerate its objectives, and identify areas of opportunity for future applications of machine learning in biological psychiatry. This review serves as a cautiously optimistic primer on machine learning for those on the precipice as they prepare to dive into the field, either as methodological practitioners or well-informed consumers.

Association between ADHD and vision problems. A systematic review and meta-analysis.

AIM: To conduct the first systematic review and meta-analysis assessing whether attention-deficit/hyperactivity disorder (ADHD) is associated with disorders of the eye, and/or altered measures of visual function. METHOD: Based on a pre-registered protocol (PROSPERO: CRD42021256352), we searched PubMed, Web of Knowledge/Science, Ovid Medline, Embase and APA PsycINFO up to 16th November 2021, with no language/type of document restrictions. We included observational studies reporting at least one measure of vision in people of any age meeting DSM/ICD criteria for ADHD and in people without ADHD; or the prevalence of ADHD in people with and without vision disorders. Study quality was assessed with the Appraisal tool for Cross-Sectional Studies (AXIS). Random effects meta-analyses were used for data synthesis. RESULTS: We included 42 studies in the narrative synthesis and 35 studies in the meta-analyses (3,250,905 participants). We found meta-analytic evidence of increased risk of astigmatism (OR = 1.79 [CI: 1.50, 2.14]), hyperopia and hypermetropia (OR = 1.79 [CI: 1.66, 1.94]), strabismus (OR = 1.93 [CI: 1.75, 2.12]), unspecified vision problems (OR = 1.94 [CI: 1.38, 2.73]) and reduced near point of convergence (OR = 5.02 [CI: 1.78, 14.11]); increased lag (Hedge's g = 0.63 [CI: 0.30, 0.96]) and variability (Hedge's g = 0.40 [CI: 0.17, 0.64]) of the accommodative response; and increased self-reported vision problems (Hedge's g = 0.63 [CI: 0.44, 0.82]) in people with ADHD compared to those without ADHD (with no significant heterogeneity). We also found meta-analytic evidence of no differences between people with and without ADHD on retinal nerve fiber layer thickness (Hedge's g = -0.19 [CI: -0.41, 0.02]) and refractive error (Hedge's g = 0.08 [CI: -0.26, 0.42]) (with no significant heterogeneity). DISCUSSION: ADHD is associated with some self-reported and objectively ascertained functional vision problems, but not with structural alterations of the eye. Further studies should clarify the causal relationship, if any, between ADHD and problems of vision. TRIAL REGISTRATION: PROSPERO registration: CRD42021256352.

Association between Autism Spectrum Disorder (ASD) and vision problems. A systematic review and meta-analysis.

AIM: To conduct a systematic review and meta-analysis assessing whether vision and/or eye disorders are associated with Autism Spectrum Disorder (ASD). METHOD: Based on a pre-registered protocol (PROSPERO: CRD42022328485), we searched PubMed, Web of Knowledge/Science, Ovid Medline, Embase and APA PsycINFO up to 5th February 2022, with no language/type of document restrictions. We included observational studies 1) reporting at least one measure of vision in people of any age with a diagnosis of ASD based on DSM or ICD criteria, or ADOS; or 2) reporting the prevalence of ASD in people with and without vision disorders. Study quality was assessed with the Appraisal tool for Cross-Sectional Studies (AXIS). Random-effects meta-analyses were used for data synthesis. RESULTS: We included 49 studies in the narrative synthesis and 46 studies in the meta-analyses (15,629,159 individuals distributed across multiple different measures). We found meta-analytic evidence of increased prevalence of strabismus (OR = 4.72 [95% CI: 4.60, 4.85]) in people with versus those without ASD (non-significant heterogeneity: Q = 1.0545, p = 0.7881). We also found evidence of increased accommodation deficits (Hedge's g = 0.68 [CI: 0.28, 1.08]) (non-significant heterogeneity: Q = 6.9331, p = 0.0741), reduced peripheral vision (-0.82 [CI: -1.32, -0.33]) (non-significant heterogeneity: Q = 4.8075, p = 0.4398), reduced stereoacuity (0.73 [CI: -1.14, -0.31]) (non-significant heterogeneity: Q = 0.8974, p = 0.3435), increased color discrimination difficulties (0.69 [CI: 0.27,1.10]) (non-significant heterogeneity: Q = 9.9928, p = 0.1890), reduced contrast sensitivity (0.45 [CI: -0.60, -0.30]) (non-significant heterogeneity: Q = 9.9928, p = 0.1890) and increased retinal thickness (=0.29 [CI: 0.07, 0.51]) (non-significant heterogeneity: Q = 0.8113, p = 0.9918) in ASD. DISCUSSION: ASD is associated with some self-reported and objectively measured functional vision problems, and structural alterations of the eye, even though we observed several methodological limitations in the individual studies included in our meta-analyses. Further research should clarify the causal relationship, if any, between ASD and problems of vision during early life. PROSPERO REGISTRATION: CRD42022328485.

Predicting childhood and adolescent attention-deficit/hyperactivity disorder onset: a nationwide deep learning approach.

Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous disorder with a high degree of psychiatric and physical comorbidity, which complicates its diagnosis in childhood and adolescence. We analyzed registry data from 238,696 persons born and living in Sweden between 1995 and 1999. Several machine learning techniques were used to assess the ability of registry data to inform the diagnosis of ADHD in childhood and adolescence: logistic regression, random Forest, gradient boosting, XGBoost, penalized logistic regression, deep neural network (DNN), and ensemble models. The best fitting model was the DNN, achieving an area under the receiver operating characteristic curve of 0.75, 95% CI (0.74-0.76) and balanced accuracy of 0.69. At the 0.45 probability threshold, sensitivity was 71.66% and specificity was 65.0%. There was an overall agreement in the feature importance among all models (τ > .5). The top 5 features contributing to classification were having a parent with criminal convictions, male sex, having a relative with ADHD, number of academic subjects failed, and speech/learning disabilities. A DNN model predicting childhood and adolescent ADHD trained exclusively on Swedish register data achieved good discrimination. If replicated and validated in an external sample, and proven to be cost-effective, this model could be used to alert clinicians to individuals who ought to be screened for ADHD and to aid clinicians' decision-making with the goal of decreasing misdiagnoses. Further research is needed to validate results in different populations and to incorporate new predictors.

Incidence, prevalence, and global burden of ADHD from 1990 to 2019 across 204 countries: data, with critical re-analysis, from the Global Burden of Disease study.

Data on incidence, prevalence and burden of ADHD are crucial for clinicians, patients, and stakeholders. We present the incidence, prevalence, and burden of ADHD globally and across countries from 1990 to 2019 from the Global Burden of Disease (GBD) study. We also: (1) calculated the ADHD prevalence based on data actually collected as opposed to the prevalence estimated by the GBD with data imputation for countries without prevalence data; (2) discussed the GBD estimated ADHD burden in the light of recent meta-analytic evidence on ADHD-related mortality. In 2019, GBD estimated global age-standardized incidence and prevalence of ADHD across the lifespan at 0.061% (95%UI = 0.040-0.087) and 1.13% (95%UI = 0.831-1.494), respectively. ADHD accounted for 0.8% of the global mental disorder DALYs, with mortality set at zero by the GBD. From 1990 to 2019 there was a decrease of -8.75% in the global age-standardized prevalence and of -4.77% in the global age-standardized incidence. The largest increase in incidence, prevalence, and burden from 1990 to 2019 was observed in the USA; the largest decrease occurred in Finland. Incidence, prevalence, and DALYs remained approximately 2.5 times higher in males than females from 1990 to 2019. Incidence peaked at age 5-9 years, and prevalence and DALYs at age 10-14 years. Our re-analysis of data prior to 2013 showed a prevalence in children/adolescents two-fold higher (5.41%, 95% CI: 4.67-6.15%) compared to the corresponding GBD estimated prevalence (2.68%, 1.83-3.72%), with no significant differences between low- and middle- and high-income countries. We also found meta-analytic evidence of significantly increased ADHD-related mortality due to unnatural causes. While it provides the most detailed evidence on temporal trends, as well as on geographic and sex variations in incidence, prevalence, and burden of ADHD, the GBD may have underestimated the ADHD prevalence and burden. Given the influence of the GBD on research and policies, methodological issues should be addressed in its future editions.

ADHD medicine consumption in Europe after COVID-19: catch-up or trend change?

BACKGROUND: Although the COVID-19 pandemic and its implications have been associated with mental health services utilization and medication consumption, there is no longitudinal study on the long-term impact on ADHD medication use trends. METHODS: This study examines the European ADHD medication consumption in 2020 to 2022 compared to the predicted consumption assuming the persistence of pre-pandemic trends. Predictions are calculated using Seasonal Autoregressive Integrated Moving Average (SARIMA) models. RESULTS: While European ADHD medication sales recorded a drop in 2020, they returned to the predicted level in 2021, even slightly exceeding it. In 2022, we found a clear exceedance of the predicted level by 16.4% on average at country level. Furthermore, the increase in consumption growth in the post-pandemic period (2021-2022) compared to the pre-pandemic period (2014-2019) was significant in 26 of the 28 European countries under consideration. CONCLUSION: There is strong evidence of a trend change in the ADHD medicine consumption growth throughout Europe after the COVID-19 pandemic.

Understanding Environmental Exposures and ADHD: a Pathway Forward.

This commentary addresses a series of articles in Prevention Science about environmental causes of attention deficit hyperactivity disorder (ADHD). It provides an overview of their key findings and places them in a broader context to facilitate their interpretation. Each of the articles included in the special issue is a meta-analysis assessing the association of ADHD with several environmental exposures. Each of the author teams systematically searched for articles and defined eligibility criteria. They assured that the measurement of risk factors preceded the measurement of ADHD. Most of the analyses are based on many studies with many participants in the constituent studies. As is typical of any observational epidemiologic study, the constituent studies could not correct for all possible confounds because some were not measured, and some are unknown. For this reason, these meta-analyses may have documented confounded associations, which calls for cautious interpretations. None of the constituent studies assessed what might be the most important type of confounding, familial, and genetic confounding, which occurs when the environmental exposure being studied is correlated with the genetic risk of the disorder being studied or other familial risk factors. Addressing familial/genetic confounding requires a genetically informed study. Because of these issues, the results presented here are intriguing but require further examination before one can conclude that the reported associations correspond to causal events for ADHD. A pathway forward is suggested by drawing parallels between genomic and exposure research.

A polygenic resilience score moderates the genetic risk for schizophrenia: Replication in 18,090 cases and 28,114 controls from the Psychiatric Genomics Consortium.

Identifying heritable factors that moderate the genetic risk for schizophrenia (SCZ) could help clarify why some individuals remain unaffected despite having relatively high genetic liability. Previously, we developed a framework to mine genome-wide association (GWAS) data for common genetic variants that protect high-risk unaffected individuals from SCZ, leading to derivation of the first-ever "polygenic resilience score" for SCZ (resilient controls n = 3786; polygenic risk score-matched SCZ cases n = 18,619). Here, we performed a replication study to verify the moderating effect of our polygenic resilience score on SCZ risk (OR = 1.09, p = 4.03 × 10-5 ) using newly released GWAS data from 23 independent case-control studies collated by the Psychiatric Genomics Consortium (PGC) (resilient controls n = 2821; polygenic risk score-matched SCZ cases n = 5150). Additionally, we sought to optimize our polygenic resilience-scoring formula to improve subsequent modeling of resilience to SCZ and other complex disorders. We found significant replication of the polygenic resilience score, and found that strict pruning of SNPs based on linkage disequilibrium to known risk SNPs and their linked loci optimizes the performance of the polygenic resilience score.

Placebo and nocebo responses in randomised, controlled trials of medications for ADHD: a systematic review and meta-analysis.

The nature and magnitude of placebo and nocebo responses to ADHD medications and the extent to which response to active medications and placebo are inter-correlated is unclear. To assess the magnitude of placebo and nocebo responses to ADHD and their association with active treatment response. We searched literature until June 26, 2019, for published/unpublished double-blind, randomised placebo-controlled trials (RCTs) of ADHD medication. Authors were contacted for additional data. We assessed placebo effects on efficacy and nocebo effects on tolerability using random effects meta-analysis. We assessed the association of study design and patient features with placebo/nocebo response. We analysed 128 RCTs (10,578 children/adolescents and 9175 adults) and found significant and heterogenous placebo effects for all efficacy outcomes, with no publication bias. The placebo effect was greatest for clinician compared with other raters. We found nocebo effects on tolerability outcomes. Efficacy outcomes from most raters showed significant positive correlations between the baseline to endpoint placebo effects and the baseline to endpoint drug effects. Placebo and nocebo effects did not differ among drugs. Baseline severity and type of rating scale influenced the findings. Shared non-specific factors influence response to both placebo and active medication. Although ADHD medications are superior to placebo, and placebo treatment in clinical practice is not feasible, clinicians should attempt to incorporate factors associated with placebo effects into clinical care. Future studies should explore how such effects influence response to medication treatment. Upon publication, data will be available in Mendeley Data: PROSPERO (CRD42019130292).

A post hoc analysis of the effect of viloxazine extended-release capsules on learning and school problems in children and adolescents with attention-deficit/hyperactivity disorder.

Improvement in attention-deficit/hyperactivity disorder (ADHD) symptoms vs. placebo was reported in a series of pediatric clinical trials of viloxazine extended-release capsules (viloxazine ER; Qelbree™). This post hoc analysis of those studies evaluated the effect of viloxazine ER on learning and school problems (LSPs). We used data from four Phase 3 placebo-controlled trials of 100-600 mg/day viloxazine ER (N = 1354; 6-17 years of age). LSPs were evaluated using the School domain of the Weiss Functional Impairment Rating Scale-Parent Report (WFIRS-P-S) and the Learning Problems content scale of the Conners 3rd Edition-Parent Short Form (C3PS-LP) at baseline and end of study (≥ Week 6). ADHD symptoms were assessed weekly using the ADHD Rating Scale 5th Edition. The analyses were performed using the general linear mixed model with participant as a random effect. The responder analyses were performed using the Chi-square test. Viloxazine ER demonstrated significantly greater improvements in WFIRS-P-S (p < 0.0001) and C3PS-LP (p = 0.0113) scores vs. placebo. The response rate for the WFIRS-P-S was significantly greater for viloxazine ER vs. placebo (p = 0.001), and the number needed to treat (NNT) was 10.3 (effect size 0.7). Conversely, response rates for C3PS-LP did not differ between groups (p = 0.9069). In addition to ADHD symptoms improvement demonstrated in previous studies, viloxazine ER significantly reduced LSPs in pediatric subjects with ADHD. The responder analyses and NNT estimates indicate that a substantial number of children and adolescents with ADHD treated with viloxazine ER improved in clinically assessed LSPs.

Novel genome-wide associations for effort valuation and psychopathology in children and adults.

The Research Domain Criteria (RDoC) initiative was established by the US National Institute of Mental Health as a multilevel, disorder-agnostic framework for analysis of human psychopathology through designated domains and constructs, including the "Positive Valence Systems" domain focused on reward-related behavior. This study investigates the reward valuation subconstruct of "effort" and its association with genetic markers, functional neurobiological pathways, and polygenic risk scores for psychopathology in 1215 children aged 6-12 and their parents (n = 1044). All participants completed the effort expenditure for rewards task (EEfRT), which assesses "effort" according to two quantitative measures: hard-task choice and reward sensitivity. Genetic association analyses were undertaken in MAGMA, utilizing EEfRT outcome variables as genome-wide association studies phenotypes to compute SNP and gene-level associations. Genome-wide association analyses found two distinct genetic loci that were significantly associated with measures of reward sensitivity and a separate genetic locus associated with hard task choice. Gene-set enrichment analysis yielded significant associations between "effort" and multiple gene sets involved in reward processing-related pathways, including dopamine receptor signaling, limbic system and forebrain development, and biological response to cocaine. These results serve to establish "effort" as a relevant construct for understanding reward-related behavior at the genetic level and support the RDoC framework for assessing disorder-agnostic psychopathology.

Polygenic association between attention-deficit/hyperactivity disorder liability and cognitive impairments.

BACKGROUND: A recent genome-wide association study (GWAS) identified 12 independent loci significantly associated with attention-deficit/hyperactivity disorder (ADHD). Polygenic risk scores (PRS), derived from the GWAS, can be used to assess genetic overlap between ADHD and other traits. Using ADHD samples from several international sites, we derived PRS for ADHD from the recent GWAS to test whether genetic variants that contribute to ADHD also influence two cognitive functions that show strong association with ADHD: attention regulation and response inhibition, captured by reaction time variability (RTV) and commission errors (CE). METHODS: The discovery GWAS included 19 099 ADHD cases and 34 194 control participants. The combined target sample included 845 people with ADHD (age: 8-40 years). RTV and CE were available from reaction time and response inhibition tasks. ADHD PRS were calculated from the GWAS using a leave-one-study-out approach. Regression analyses were run to investigate whether ADHD PRS were associated with CE and RTV. Results across sites were combined via random effect meta-analyses. RESULTS: When combining the studies in meta-analyses, results were significant for RTV (R2 = 0.011, ß = 0.088, p = 0.02) but not for CE (R2 = 0.011, ß = 0.013, p = 0.732). No significant association was found between ADHD PRS and RTV or CE in any sample individually (p > 0.10). CONCLUSIONS: We detected a significant association between PRS for ADHD and RTV (but not CE) in individuals with ADHD, suggesting that common genetic risk variants for ADHD influence attention regulation.

Autophagy, apoptosis, and neurodevelopmental genes might underlie selective brain region vulnerability in attention-deficit/hyperactivity disorder.

Large-scale brain imaging studies by the ENIGMA Consortium identified structural changes associated with attention-deficit/hyperactivity disorder (ADHD). It is not clear why some brain regions are impaired and others spared by the etiological risks for ADHD. We hypothesized that spatial variation in brain cell organization and/or pathway expression levels contribute to selective brain region vulnerability (SBRV) in ADHD. In this study, we used the largest available collection of magnetic resonance imaging (MRI) results from the ADHD ENIGMA Consortium (subcortical MRI n = 3242; cortical MRI n = 4180) along with high-resolution postmortem brain microarray data from Allen Brain Atlas (donors n = 6) from 22 brain regions to investigate our SBRV hypothesis. We performed deconvolution of the bulk transcriptomic data to determine abundances of neuronal and nonneuronal cells in the brain. We assessed the relationships between gene-set expression levels, cell abundance, and standardized effect sizes representing regional changes in brain sizes in cases of ADHD. Our analysis yielded significant correlations between apoptosis, autophagy, and neurodevelopment genes with smaller brain sizes in ADHD, along with associations to regional abundances of astrocytes and oligodendrocytes. The lack of enrichment of common genetic risk variants for ADHD within implicated gene sets suggests an environmental etiology to these differences. This work provides novel mechanistic clues about SBRV in ADHD.

Druggable genome in attention deficit/hyperactivity disorder and its co-morbid conditions. New avenues for treatment.

Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder with only symptomatic care available. Genome-wide association (GWA) studies can provide a starting point in the search for novel drug targets and possibilities of drug repurposing. Here, we explored the druggable genome in ADHD by utilising GWA studies on ADHD and its co-morbid conditions. First, we explored whether the genes targeted by current ADHD drugs show association with the disorder and/or its co-morbidities. Second, we aimed to identify genes and pathways involved in the biological processes underlying ADHD that can be targeted by pharmacological agents. These ADHD-associated druggable genes and pathways were also examined in co-morbidities of ADHD, as commonalities in their aetiology and management may lead to novel pharmacological insights. Strikingly, none of the genes encoding targets of first-line pharmacotherapeutics for ADHD were significantly associated with the disorder, suggesting that FDA-approved ADHD drugs may act through different mechanisms than those underlying ADHD. In the examined druggable genome, three loci on chromosomes 1, 4 and 12 revealed significant association with ADHD and contained nine druggable genes, five of which encode established drug targets for malignancies, autoimmune and neurodevelopmental disorders. To conclude, we present a framework to assess the druggable genome in a disorder, exemplified by ADHD. We highlight signal transduction and cell adhesion as potential novel avenues for ADHD treatment. Our findings add to knowledge on known ADHD drugs and present the exploration of druggable genome associated with ADHD, which may offer interventions at the aetiological level of the disorder.

Structural brain imaging studies offer clues about the effects of the shared genetic etiology among neuropsychiatric disorders.

Genomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology. From the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD), and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls. The SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.494). Our results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures.

A polygenic resilience score moderates the genetic risk for schizophrenia.

Based on the discovery by the Resilience Project (Chen R. et al. Nat Biotechnol 34:531-538, 2016) of rare variants that confer resistance to Mendelian disease, and protective alleles for some complex diseases, we posited the existence of genetic variants that promote resilience to highly heritable polygenic disorders1,0 such as schizophrenia. Resilience has been traditionally viewed as a psychological construct, although our use of the term resilience refers to a different construct that directly relates to the Resilience Project, namely: heritable variation that promotes resistance to disease by reducing the penetrance of risk loci, wherein resilience and risk loci operate orthogonal to one another. In this study, we established a procedure to identify unaffected individuals with relatively high polygenic risk for schizophrenia, and contrasted them with risk-matched schizophrenia cases to generate the first known "polygenic resilience score" that represents the additive contributions to SZ resistance by variants that are distinct from risk loci. The resilience score was derived from data compiled by the Psychiatric Genomics Consortium, and replicated in three independent samples. This work establishes a generalizable framework for finding resilience variants for any complex, heritable disorder.

Findings from a pilot open-label trial of N-acetylcysteine for the treatment of pediatric mania and hypomania.

BACKGROUND: Pediatric bipolar disorder is a highly prevalent and morbid disorder and is considered a prevalent public health concern. Currently approved treatments often pose the risk of serious side effects. Therefore, this study assessed the efficacy and tolerability of N-acetylcysteine (NAC), in children and adolescents with bipolar spectrum disorder. METHODS: We conducted a 12-week open-label trial of NAC for treatment of mania and hypomania in children and adolescents ages 5-17 with bipolar spectrum disorder including participants with full and subthreshold manic symptoms, accepting those with and without mixed states with co-occurring depression, and Young Mania Rating Scale scores ≥ 20 and < 40. Symptoms of mania and depression were assessed using the Young Mania Rating Scale (YMRS), Hamilton Depression Rating Scale (HDRS), Children's Depression Rating Scale (CDRS), and Clinical Global Impression (CGI) Severity (CGI-S) and Improvement (CGI-I) scales for mania and depression. RESULTS: This study had a high drop-out rate with only 53% completing all 12 weeks. There was a significant reduction in YMRS, HDRS, and CDRS mean scores from baseline to endpoint. Of the 24 exposed participants, 54% had an anti-manic response measured by a reduction in YMRS ≥ 30% and 46% had a CGI-I mania score ≤ 2 at endpoint. Additionally, 62% of participants had an anti-depressive response measured by a reduction in HDRS ≥ 30%, 31% had an anti-depressive response measured by a reduction in CDRS ≥ 30%, and 38% had a CGI-I depression score ≤ 2 at endpoint. CONCLUSIONS: These pilot open-label findings in a small sample provide preliminary data supporting the tolerability and safety of NAC in a pediatric population. The findings of this pilot scale study indicating improvement in mania and depression are promising, but require replication with a monotherapy randomized placebo controlled clinical trial and larger sample. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02357290 . First Registration 06/02/2015.

Web-Based Mindfulness-Based Interventions for Well-being: Randomized Comparative Effectiveness Trial.

BACKGROUND: Mindfulness can improve overall well-being by training individuals to focus on the present moment without judging their thoughts. However, it is unknown how much mindfulness practice and training are necessary to improve well-being. OBJECTIVE: The primary aim of this study was to determine whether a standard 8-session web-based mindfulness-based cognitive therapy (MBCT) program, compared with a brief 3-session mindfulness intervention, improved overall participant well-being. In addition, we sought to explore whether the treatment effects differed based on the baseline characteristics of the participants (ie, moderators). METHODS: Participants were recruited from 17 patient-powered research networks, web-based communities of stakeholders interested in a common research area. Participants were randomized to either a standard 8-session MBCT or a brief 3-session mindfulness training intervention accessed on the web. The participants were followed for 12 weeks. The primary outcome of the study was well-being, as measured by the World Health Organization-Five Well-Being Index. We hypothesized that MBCT would be superior to a brief mindfulness training. RESULTS: We randomized 4411 participants, 3873 (87.80%) of whom were White and 3547 (80.41%) of female sex assigned at birth. The mean baseline World Health Organization-Five Well-Being Index score was 50.3 (SD 20.7). The average self-reported well-being in each group increased over the intervention period (baseline to 8 weeks; model-based slope for the MBCT group: 0.78, 95% CI 0.63-0.93, and brief mindfulness group: 0.76, 95% CI 0.60-0.91) as well as the full study period (ie, intervention plus follow-up; baseline to 20 weeks; model-based slope for MBCT group: 0.41, 95% CI 0.34-0.48; and brief mindfulness group: 0.33, 95% CI 0.26-0.40). Changes in self-reported well-being were not significantly different between MBCT and brief mindfulness during the intervention period (model-based difference in slopes: -0.02, 95% CI -0.24 to 0.19; P=.80) or during the intervention period plus 12-week follow-up (-0.08, 95% CI -0.18 to 0.02; P=.10). During the intervention period, younger participants (P=.05) and participants who completed a higher percentage of intervention sessions (P=.005) experienced greater improvements in well-being across both interventions, with effects that were stronger for participants in the MBCT condition. Attrition was high (ie, 2142/4411, 48.56%), which is an important limitation of this study. CONCLUSIONS: Standard MBCT improved well-being but was not superior to a brief mindfulness intervention. This finding suggests that shorter mindfulness programs could yield important benefits across the general population of individuals with various medical conditions. Younger people and participants who completed more intervention sessions reported greater improvements in well-being, an effect that was more pronounced for participants in the MBCT condition. This finding suggests that standard MBCT may be a better choice for younger people as well as treatment-adherent individuals. TRIAL REGISTRATION: ClinicalTrials.gov NCT03844321; https://clinicaltrials.gov/ct2/show/NCT03844321.