Showing papers by "Stephen V. Faraone published in 2020"

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

Abstract: This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

A novel digital intervention for actively reducing severity of paediatric ADHD (STARS-ADHD): a randomised controlled trial.

Abstract: Summary Background Attention-deficit hyperactivity disorder (ADHD) is a common paediatric neurodevelopmental disorder with substantial effect on families and society. Alternatives to traditional care, including novel digital therapeutics, have shown promise to remediate cognitive deficits associated with this disorder and may address barriers to standard therapies, such as pharmacological interventions and behavioural therapy. AKL-T01 is an investigational digital therapeutic designed to target attention and cognitive control delivered through a video game-like interface via at-home play for 25 min per day, 5 days per week for 4 weeks. This study aimed to assess whether AKL-T01 improved attentional performance in paediatric patients with ADHD. Methods The Software Treatment for Actively Reducing Severity of ADHD (STARS-ADHD) was a randomised, double-blind, parallel-group, controlled trial of paediatric patients (aged 8–12 years, without disorder-related medications) with confirmed ADHD and Test of Variables of Attention (TOVA) Attention Performance Index (API) scores of −1·8 and below done by 20 research institutions in the USA. Patients were randomly assigned 1:1 to AKL-T01 or a digital control intervention. The primary outcome was mean change in TOVA API from pre-intervention to post-intervention. Safety, tolerability, and compliance were also assessed. Analyses were done in the intention-to-treat population. This trial is registered with ClinicalTrials.gov, NCT02674633 and is completed. Findings Between July 15, 2016, and Nov 30, 2017, 857 patients were evaluated and 348 were randomly assigned to receive AKL-T01 or control. Among patients who received AKL-T01 (n=180 [52%]; mean [SD] age, 9·7 [1·3] years) or control (n=168 [48%]; mean [SD] age, 9·6 [1·3] years), the non-parametric estimate of the population median change from baseline TOVA API was 0·88 (95% CI 0·24–1·49; p=0·0060). The mean (SD) change from baseline on the TOVA API was 0·93 (3·15) in the AKL-T01 group and 0·03 (3·16) in the control group. There were no serious adverse events or discontinuations. Treatment-related adverse events were mild and included frustration (5 [3%] of 180) and headache (3 [2%] of 180). Patient compliance was a mean of 83 (83%) of 100 expected sessions played (SD, 29·2 sessions). Interpretation Although future research is needed for this digital intervention, this study provides evidence that AKL-T01 might be used to improve objectively measured inattention in paediatric patients with ADHD, while presenting minimal adverse events. Funding Sponsored by Akili Interactive Labs.

Exome sequencing in schizophrenia-affected parent-offspring trios reveals risk conferred by protein-coding de novo mutations.

Abstract: Protein-coding de novo mutations (DNMs) are significant risk factors in many neurodevelopmental disorders, whereas schizophrenia (SCZ) risk associated with DNMs has thus far been shown to be modest. We analyzed DNMs from 1,695 SCZ-affected trios and 1,077 published SCZ-affected trios to better understand the contribution to SCZ risk. Among 2,772 SCZ probands, exome-wide DNM burden remained modest. Gene set analyses revealed that SCZ DNMs were significantly concentrated in genes that were highly expressed in the brain, that were under strong evolutionary constraint and/or overlapped with genes identified in other neurodevelopmental disorders. No single gene surpassed exome-wide significance; however, 16 genes were recurrently hit by protein-truncating DNMs, corresponding to a 3.15-fold higher rate than the mutation model expectation (permuted 95% confidence interval: 1-10 genes; permuted P = 3 × 10-5). Overall, DNMs explain a small fraction of SCZ risk, and larger samples are needed to identify individual risk genes, as coding variation across many genes confers risk for SCZ in the population.

Systematic Review: Nonmedical Use of Prescription Stimulants: Risk Factors, Outcomes, and Risk Reduction Strategies

Abstract: Objective To review all literature on the nonmedical use (NMU) and diversion of prescription stimulants to better understand the characteristics, risk factors, and outcomes of NMU and to review risk-reduction strategies. Method We systematically searched PubMed, PsycINFO, and SCOPUS from inception to May 2018 for studies containing empirical data about NMU and diversion of prescription stimulants. Additional references identified by the authors were also assessed for inclusion. Results A total of 111 studies met inclusion criteria. NMU and diversion of stimulants are highly prevalent; self-reported rates among population samples range from 2.1% to 58.7% and from 0.7% to 80.0%, respectively. A variety of terms are used to describe NMU, and most studies have examined college students. Although most NMU is oral, non-oral NMU also occurs. The majority of NMU is associated with no, or minor, medical effects; however, adverse medical outcomes, including death, occur in some individuals, particularly when administered by non-oral routes. Although academic and occupational performance enhancement are the most commonly cited motivations, there is little evidence that academic performance is improved by NMU in individuals without attention-deficit/hyperactivity disorder. Conclusion NMU of stimulants is a significant public health problem, especially in college students, but variations in the terms used to describe NMU and inconsistencies in the available data limit a better understanding of this problem. Further research is needed to develop methods to detect NMU, identify individuals at greatest risk, study routes of administration, and devise educational and other interventions to help reduce occurrence of NMU. Colleges should consider including NMU in academic integrity policies.

Brain scans from 21,297 individuals reveal the genetic architecture of hippocampal subfield volumes.

Abstract: The hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and patter ...

Subcortical Brain Volume, Regional Cortical Thickness, and Cortical Surface Area Across Disorders: Findings From the ENIGMA ADHD, ASD, and OCD Working Groups

Abstract: OBJECTIVE: Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data. METHODS: Structural T1-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures). RESULTS: No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood. CONCLUSIONS: The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.

Physical Health, Media Use, and Mental Health in Children and Adolescents With ADHD During the COVID-19 Pandemic in Australia.

Abstract: Objective: To examine the impact of COVID-19 restrictions among children with attention-deficit/hyperactivity disorder (ADHD). Methods: Parents of 213 Australian children (5–17 years) with ADHD completed a survey in May 2020 when COVID-19 restrictions were in place (i.e., requiring citizens to stay at home except for essential reasons). Results: Compared to pre-pandemic, children had less exercise (Odds Ratio (OR) = 0.4; 95% CI 0.3–0.6), less outdoor time (OR = 0.4; 95% 0.3–0.6), and less enjoyment in activities (OR = 6.5; 95% CI 4.0–10.4), while television (OR = 4.0; 95% CI 2.5–6.5), social media (OR = 2.4; 95% CI 1.3–4.5), gaming (OR = 2.0; 95% CI 1.3–3.0), sad/depressed mood (OR = 1.8; 95% CI 1.2–2.8), and loneliness (OR = 3.6; 95% CI 2.3–5.5) were increased. Child stress about COVID-19 restrictions was associated with poorer functioning across most domains. Most parents (64%) reported positive changes for their child including more family time. Conclusions: COVID-19 restrictions were associated with both negative and positive impacts among children with ADHD.

The Relationship Between Executive Function Deficits and DSM-5-Defined ADHD Symptoms:

Abstract: Objectives: To identify the relationship between the core Diagnostic and Statistical Manual of Mental Disorders (5th ed.) ADHD symptoms and executive function deficits (EFDs), to evaluate ADHD characteristics of those with executive dysfunction (ED), and to examine the predictive utility of the Adult ADHD Investigator Symptom Rating Scale (AISRS) in identifying those with adult ADHD and ED. Method: Two samples (referred and primary care practice) were pooled together for present analysis. Results: Final analysis included 297 respondents, 171 with adult ADHD. Spearman correlation coefficients and binary logistic regressions demonstrated that ADHD inattentive (IA) and hyperactive-impulsive (H-I) symptoms were moderately to strongly correlated with and highly predictive of EFDs. Receiver operating characteristic curve analysis showed that an AISRS DSM 18-item score of ⩾ 28 was most predictive of clinical ED. Conclusion: ADHD symptoms were strongly correlated with and predictive of EFDs, clinicians should screen adults with ADHD for EFDs and ADHD treatment providers should track EFD improvement in addition to DSM-5 ADHD symptoms.

Evaluating chronic emotional dysregulation and irritability in relation to ADHD and depression genetic risk in children with ADHD.

Abstract: BACKGROUND A central nosological problem concerns the etiological relationship of emotional dysregulation with ADHD. Molecular genetic risk scores provide a novel method for informing this question. METHODS Participants were 514 community-recruited children of Northern European descent age 7-11 defined as ADHD or non-ADHD by detailed research evaluation. Parents-rated ADHD on standardized ratings and child temperament on the Temperament in Middle Childhood Questionnaire (TMCQ) and reported on ADHD and comorbid disorders by semi-structured clinical interview. Categorical and dimensional variables were created for ADHD, emotional dysregulation (implicating disruption of regulation of both anger-irritability and of positive valence surgency-sensation seeking), and irritability alone (anger dysregulation). Genome-wide polygenic risk scores (PRS) were computed for ADHD and depression genetic liability. Structural equation models and computationally derived emotion profiles guided analysis. RESULTS The ADHD PRS was associated in variable-centered analyses with irritability (β = .179, 95% CI = 0.087-0.280; ΔR2 = .034, p < .0002), but also with surgency/sensation seeking (B = .146, 95%CI = 0.052-0.240, ΔR2 =.022, p = .002). In person-centered analysis, the ADHD PRS was elevated in the emotion dysregulation ADHD group versus other ADHD children (OR = 1.44, 95% CI = 1.03-2.20, Nagelkerke ΔR2 = .013, p = .033) but did not differentiate irritable from surgent ADHD profiles. All effects were independent of variation in ADHD severity across traits or groups. The depression PRS was related to oppositional defiant disorder but not to ADHD emotion dysregulation. CONCLUSIONS Irritability-anger and surgency-sensation seeking, as forms of negative and positively valenced dysregulated affect in ADHD populations, both relate principally to ADHD genetic risk and not mood-related genetic risk.

Attention-deficit/hyperactivity disorder and lifetime cannabis use: genetic overlap and causality.

Abstract: Attention-deficit/hyperactivity disorder (ADHD) is a severely impairing neurodevelopmental disorder with a prevalence of 5% in children and adolescents and of 2.5% in adults. Comorbid conditions in ADHD play a key role in symptom progression, disorder course and outcome. ADHD is associated with a significantly increased risk for substance use, abuse and dependence. ADHD and cannabis use are partly determined by genetic factors; the heritability of ADHD is estimated at 70–80% and of cannabis use initiation at 40–48%. In this study, we used summary statistics from the largest available meta-analyses of genome-wide association studies (GWAS) of ADHD (n = 53,293) and lifetime cannabis use (n = 32,330) to gain insights into the genetic overlap and causal relationship of these two traits. We estimated their genetic correlation to be r2 = 0.29 (P = 1.63 × 10−5) and identified four new genome-wide significant loci in a cross-trait analysis: two in a single variant association analysis (rs145108385, P = 3.30 × 10−8 and rs4259397, P = 4.52 × 10−8) and two in a gene-based association analysis (WDPCP, P = 9.67 × 10−7 and ZNF251, P = 1.62 × 10−6). Using a two-sample Mendelian randomization approach we found support that ADHD is causal for lifetime cannabis use, with an odds ratio of 7.9 for cannabis use in individuals with ADHD in comparison to individuals without ADHD (95% CI (3.72, 15.51), P = 5.88 × 10−5). These results substantiate the temporal relationship between ADHD and future cannabis use and reinforce the need to consider substance misuse in the context of ADHD in clinical interventions.

Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: The ENIGMA adventure

Abstract: Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses.

Predicting suicide attempt or suicide death following a visit to psychiatric specialty care: A machine learning study using Swedish national registry data

Abstract: Background Suicide is a major public health concern globally. Accurately predicting suicidal behavior remains challenging. This study aimed to use machine learning approaches to examine the potential of the Swedish national registry data for prediction of suicidal behavior. Methods and findings The study sample consisted of 541,300 inpatient and outpatient visits by 126,205 Sweden-born patients (54% female and 46% male) aged 18 to 39 (mean age at the visit: 27.3) years to psychiatric specialty care in Sweden between January 1, 2011 and December 31, 2012. The most common psychiatric diagnoses at the visit were anxiety disorders (20.0%), major depressive disorder (16.9%), and substance use disorders (13.6%). A total of 425 candidate predictors covering demographic characteristics, socioeconomic status (SES), electronic medical records, criminality, as well as family history of disease and crime were extracted from the Swedish registry data. The sample was randomly split into an 80% training set containing 433,024 visits and a 20% test set containing 108,276 visits. Models were trained separately for suicide attempt/death within 90 and 30 days following a visit using multiple machine learning algorithms. Model discrimination and calibration were both evaluated. Among all eligible visits, 3.5% (18,682) were followed by a suicide attempt/death within 90 days and 1.7% (9,099) within 30 days. The final models were based on ensemble learning that combined predictions from elastic net penalized logistic regression, random forest, gradient boosting, and a neural network. The area under the receiver operating characteristic (ROC) curves (AUCs) on the test set were 0.88 (95% confidence interval [CI] = 0.87–0.89) and 0.89 (95% CI = 0.88–0.90) for the outcome within 90 days and 30 days, respectively, both being significantly better than chance (i.e., AUC = 0.50) (p < 0.01). Sensitivity, specificity, and predictive values were reported at different risk thresholds. A limitation of our study is that our models have not yet been externally validated, and thus, the generalizability of the models to other populations remains unknown. Conclusions By combining the ensemble method of multiple machine learning algorithms and high-quality data solely from the Swedish registers, we developed prognostic models to predict short-term suicide attempt/death with good discrimination and calibration. Whether novel predictors can improve predictive performance requires further investigation.

Shared polygenic risk for ADHD, executive dysfunction and other psychiatric disorders

Abstract: Many psychiatric disorders are associated with impaired executive functioning (EF). The associated EF component varies by psychiatric disorders, and this variation might be due to genetic liability. We explored the genetic association between five psychiatric disorders and EF in clinically-recruited attention deficit hyperactivity disorder (ADHD) children using polygenic risk score (PRS) methodology. Genome-wide association study (GWAS) summary data for ADHD, major depressive disorder (MDD), schizophrenia (SZ), bipolar disorder (BIP) and autism were used to calculate the PRSs. EF was evaluated by the Stroop test for inhibitory control, the trail-making test for cognitive flexibility, and the digital span test for working memory in a Chinese ADHD cohort (n = 1147). Exploratory factor analysis of the three measures identified one principal component for EF (EF-PC). Linear regression models were used to analyze the association between each PRS and the EF measures. The role of EF measures in mediating the effects of the PRSs on ADHD symptoms was also analyzed. The result showed the PRSs for MDD, ADHD and BIP were all significantly associated with the EF-PC. For each EF component, the association results were different for the PRSs of the five psychiatric disorders: the PRSs for ADHD and MDD were associated with inhibitory control (adjusted P = 0.0183 and 0.0313, respectively), the PRS for BIP was associated with working memory (adjusted P = 0.0416), and the PRS for SZ was associated with cognitive flexibility (adjusted P = 0.0335). All three EF measures were significantly correlated with ADHD symptoms. In mediation analyses, the ADHD and MDD PRSs, which were associated with inhibitory control, had significant indirect effects on ADHD symptoms through the mediation of inhibitory control. These findings indicate that the polygenic risks for several psychiatric disorders influence specific executive dysfunction in children with ADHD. The results helped to clarify the relationship between risk genes of each mental disorder and the intermediate cognitive domain, which may further help elucidate the risk genes and motivate efforts to develop EF measures as a diagnostic marker and future treatment target.

Neurocognitive Deficits in Attention-Deficit/Hyperactivity Disorder With and Without Comorbid Oppositional Defiant Disorder

Abstract: Objective: Oppositional Defiant Disorder (ODD) is highly prevalent in Attention-Deficit/Hyperactivity Disorder (ADHD) and may account for inconsistencies in findings on neurocognitive functioning in ADHD. Our aim was to assess cool and hot executive functioning (EF) and temporal processing in ADHD with and without comorbid ODD to elucidate the effects of comorbid ODD. Method: ADHD-only (n = 82), ADHD + ODD (n = 82), and controls (n = 82), with mean age 16 years (SD = 3.1), matched for age, gender, IQ, and ADHD type (clinical groups) were assessed on cool EF (inhibition, working memory), hot EF (reinforcement processing, emotion recognition), and temporal processing (time production and reproduction). Results: Individuals with ADHD + ODD showed abnormalities in inhibition, working memory, facial emotion recognition, and temporal processing, whereas individuals with ADHD-only were solely impaired in working memory and time production. Conclusion: Findings suggest that ODD carries a substantial part of the EF deficits observed in ADHD and contrast with current theories of neurocognitive impairments in ADHD.

Examining sex-differentiated genetic effects across neuropsychiatric and behavioral traits

Abstract: Background The origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations across these traits, we tested for a sex-differentiated genetic architecture within and between traits. Methods Using genome-wide association study (GWAS) summary statistics for 20 neuropsychiatric and behavioral traits, we tested for differences in SNP-based heritability (h2) and genetic correlation (rg Results With current sample sizes (and power), we found no significant, consistent sex differences in SNP-based h2. Between-sex, within-trait genetic correlations were consistently high, although significantly less than 1 for educational attainment and risk-taking behavior. We identified genome-wide significant genes with sex-differentiated effects for eight traits. Several trait pairs shared sex-differentiated effects. The top 0.1% of genes with sex-differentiated effects across traits overlapped with neuron- and synapse-related gene sets. Most between-trait genetic correlation estimates were similar across sex, with several exceptions (e.g. educational attainment & risk-taking behavior). Conclusions Sex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic, requiring large sample sizes. Genes with sex-differentiated effects are enriched for neuron-related gene sets. This work motivates further investigation of genetic, as well as environmental, influences on sex differences.

DRD4 48 bp multiallelic variants as age-population-specific biomarkers in attention-deficit/hyperactivity disorder.

Abstract: The identification of biomarkers to support the diagnosis and prediction of treatment response for attention-deficit/hyperactivity disorder (ADHD) is still a challenge. Our previous works highlighted the DRD4 (dopamine receptor D4) as the best potential genetic marker for childhood diagnosis and methylphenidate (MPH) response. Here, we aimed to provide additional evidence on biomarkers for ADHD diagnosis and treatment response, by using more specific approaches such as meta-analytic and bioinformatics tools. Via meta-analytic approaches including over 3000 cases and 16,000 controls, we demonstrated that, among the different variants studied in DRD4 gene, the 48-base pair, Variable Tandem Repeat Polymorphism, VNTR in exon 3 showed an age/population-specificity and an allelic heterogeneity. In particular, the 7R/“long” allele was identified as an ADHD risk factor in European-Caucasian populations (d = 1.31, 95%CI: 1.17–1.47, Z = 4.70/d = 1.36, 95%CI: 1.20–1.55, Z = 4.78, respectively), also, from the results of last meta-analysis, linked to the poor MPH efficacy. The 4R/“short” allele was a protective factor in European-Caucasian and South American populations (d = 0.83, 95%CI: 0.75–0.92, Z = 3.58), and was also associated to positive MPH response. These results refer to children with ADHD. No evidence of such associations was detected for adults with persistent ADHD (data from the last meta-analysis). Moreover, we found evidence that the 4R allele leads to higher receptor expression and increased sensitivity to dopamine, as compared with the 7R allele (d = 1.20, 95%CI: 0.71–1.69, Z = 4.81), and this is consistent with the ADHD protection/susceptibility effects of the respective alleles. Using bioinformatics tools, based on the latest genome-wide association (GWAS) meta-analysis of the Psychiatry Genomic Consortium (PGC), we demonstrated that the 48 bp VNTR is not in Linkage Disequilibrium with the DRD4 SNPs (Single Nucleotide Polymorphisms), which were not found to be associated with ADHD. Moreover, a DRD4 expression downregulation was found in ADHD specific brain regions (Putamen, Z score = −3.02, P = 0.00252). Overall, our results suggest that DRD4 48 bp VNTR variants should be considered as biomarkers to support the diagnosis of ADHD and to predict MPH response, although the accuracy of such a biomarker remains to be further elucidated.

Machine-Learning prediction of comorbid substance use disorders in ADHD youth using Swedish registry data.

Abstract: BACKGROUND Children with attention-deficit/hyperactivity disorder (ADHD) have a high risk for substance use disorders (SUDs). Early identification of at-risk youth would help allocate scarce resources for prevention programs. METHODS Psychiatric and somatic diagnoses, family history of these disorders, measures of socioeconomic distress, and information about birth complications were obtained from the national registers in Sweden for 19,787 children with ADHD born between 1989 and 1993. We trained (a) a cross-sectional random forest (RF) model using data available by age 17 to predict SUD diagnosis between ages 18 and 19; and (b) a longitudinal recurrent neural network (RNN) model with the Long Short-Term Memory (LSTM) architecture to predict new diagnoses at each age. RESULTS The area under the receiver operating characteristic curve (AUC) was 0.73(95%CI 0.70-0.76) for the random forest model (RF). Removing prior diagnosis from the predictors, the RF model was still able to achieve significant AUCs when predicting all SUD diagnoses (0.69, 95%CI 0.66-0.72) or new diagnoses (0.67, 95%CI: 0.64, 0.71) during age 18-19. For the model predicting new diagnoses, model calibration was good with a low Brier score of 0.086. Longitudinal LSTM model was able to predict later SUD risks at as early as 2 years age, 10 years before the earliest diagnosis. The average AUC from longitudinal models predicting new diagnoses 1, 2, 5 and 10 years in the future was 0.63. CONCLUSIONS Population registry data can be used to predict at-risk comorbid SUDs in individuals with ADHD. Such predictions can be made many years prior to age of the onset, and their SUD risks can be monitored using longitudinal models over years during child development. Nevertheless, more work is needed to create prediction models based on electronic health records or linked population registers that are sufficiently accurate for use in the clinic.

International Consensus Statement for the Screening, Diagnosis, and Treatment of Adolescents with Concurrent Attention-Deficit/Hyperactivity Disorder and Substance Use Disorder

Abstract: BACKGROUND: Childhood attention-deficit/hyperactivity disorder (ADHD) is a risk factor for substance misuse and substance use disorder (SUD) in adolescence and (early) adulthood. ADHD and SUD also frequently co-occur in treatment-seeking adolescents, which complicates diagnosis and treatment and is associated with poor treatment outcomes. Research on the effect of treatment of childhood ADHD on the prevention of adolescent SUD is inconclusive, and studies on the diagnosis and treatment of adolescents with ADHD and SUD are scarce. Thus, the available evidence is generally not sufficient to justify robust treatment recommendations. OBJECTIVE: The aim of the study was to obtain a consensus statement based on a combination of scientific data and clinical experience. METHOD: A modified Delphi study to reach consensus based upon the combination of scientific data and clinical experience with a multidisciplinary group of 55 experts from 17 countries. The experts were asked to rate a set of statements on the effect of treatment of childhood ADHD on adolescent SUD and on the screening, diagnosis, and treatment of adolescents with comorbid ADHD and SUD. RESULTS: After 3 iterative rounds of rating and adapting 37 statements, consensus was reached on 36 of these statements representing 6 domains: general (n = 4), risk of developing SUD (n = 3), screening and diagnosis (n = 7), psychosocial treatment (n = 5), pharmacological treatment (n = 11), and complementary treatments (n = 7). Routine screening is recommended for ADHD in adolescent patients in substance abuse treatment and for SUD in adolescent patients with ADHD in mental healthcare settings. Long-acting stimulants are recommended as the first-line treatment of ADHD in adolescents with concurrent ADHD and SUD, and pharmacotherapy should preferably be embedded in psychosocial treatment. The only remaining no-consensus statement concerned the requirement of abstinence before starting pharmacological treatment in adolescents with ADHD and concurrent SUD. In contrast to the majority, some experts required full abstinence before starting any pharmacological treatment, some were against the use of stimulants in the treatment of these patients (independent of abstinence), while some were against the alternative use of bupropion. CONCLUSION: This international consensus statement can be used by clinicians and patients together in a shared decision-making process to select the best interventions and to reach optimal outcomes in adolescent patients with concurrent ADHD and SUD.

Genomic analysis of the natural history of attention-deficit/hyperactivity disorder using Neanderthal and ancient Homo sapiens samples.

Abstract: Attention-deficit/hyperactivity disorder (ADHD) is an impairing neurodevelopmental condition highly prevalent in current populations. Several hypotheses have been proposed to explain this paradox, mainly in the context of the Paleolithic versus Neolithic cultural shift but especially within the framework of the mismatch theory. This theory elaborates on how a particular trait once favoured in an ancient environment might become maladaptive upon environmental changes. However, given the lack of genomic data available for ADHD, these theories have not been empirically tested. We took advantage of the largest GWAS meta-analysis available for this disorder consisting of over 20,000 individuals diagnosed with ADHD and 35,000 controls, to assess the evolution of ADHD-associated alleles in European populations using archaic, ancient and modern human samples. We also included Approximate Bayesian computation coupled with deep learning analyses and singleton density scores to detect human adaptation. Our analyses indicate that ADHD-associated alleles are enriched in loss of function intolerant genes, supporting the role of selective pressures in this early-onset phenotype. Furthermore, we observed that the frequency of variants associated with ADHD has steadily decreased since Paleolithic times, particularly in Paleolithic European populations compared to samples from the Neolithic Fertile Crescent. We demonstrate this trend cannot be explained by African admixture nor Neanderthal introgression, since introgressed Neanderthal alleles are enriched in ADHD risk variants. All analyses performed support the presence of long-standing selective pressures acting against ADHD-associated alleles until recent times. Overall, our results are compatible with the mismatch theory for ADHD but suggest a much older time frame for the evolution of ADHD-associated alleles compared to previous hypotheses.

Translating Discoveries in Attention-Deficit/Hyperactivity Disorder Genomics to an Outpatient Child and Adolescent Psychiatric Cohort.

Abstract: Objective Genomic discoveries should be investigated in generalizable child psychiatric samples in order to justify and inform studies that will evaluate their use for specific clinical purposes. In youth consecutively referred for neuropsychiatric evaluation, we examined 1) the convergent and discriminant validity of attention-deficit/hyperactivity disorder (ADHD) polygenic risk scores (PRSs) in relation to DSM-based ADHD phenotypes; 2) the association of ADHD PRSs with phenotypes beyond ADHD that share its liability and have implications for outcome; and 3) the extent to which youth with high ADHD PRSs manifest a distinctive clinical profile. Method Participants were 433 youth, ages 7–18 years, from the Longitudinal Study of Genetic Influences on Cognition. We used logistic/linear regression and mixed effects models to examine associations with ADHD-related polygenic variation from the largest ADHD genome-wide association study to date. We replicated key findings in 5,140 adult patients from a local health system biobank. Results Among referred youth, ADHD PRSs were associated with ADHD diagnoses, cross-diagnostic ADHD symptoms and academic impairment (odds ratios ∼1.4; R2 values ∼2%–3%), as well as cross-diagnostic variation in aggression and working memory. In adults, ADHD PRSs were associated with ADHD and phenotypes beyond the condition that have public health implications. Finally, youth with a high ADHD polygenic burden showed a more severe clinical profile than youth with a low burden (β coefficients ∼.2). Conclusion Among child and adolescent outpatients, ADHD polygenic risk was associated with ADHD and related phenotypes as well as clinical severity. These results extend the scientific foundation for studies of ADHD polygenic risk in the clinical setting and highlight directions for further research.

Evidence for Similar Structural Brain Anomalies in Youth and Adult Attention-Deficit/Hyperactivity Disorder: A Machine Learning Analysis

Abstract: ADHD affects 5% of children world-wide. Of these, two-thirds continue to have impairing symptoms of ADHD into adulthood. Although a large literature implicates structural brain differences in the pathophysiology of the disorder, it is not clear if adults with ADHD have similar neuroanatomical impairments as those seen in children with recent reports from the large ENIGMA-ADHD consortium finding structural abnormalities for children but not for adults. This paper uses deep learning neural network classification models to determine if there are neuroanatomical changes in the brains of children with ADHD that are also observed for adult ADHD, and vice versa. We found that structural MRI data can significantly separate ADHD from control participants for both children and adults. Consistent with the prior reports from ENIGMA-ADHD, prediction performance and effect sizes were better for the child than the adult samples. The model trained on adult samples significantly predicted ADHD in the child sample, suggesting that our model learned anatomical features that common to ADHD in childhood and adulthood. These results support the continuity of ADHD’s pathophysiology from childhood to adulthood. In addition, our work demonstrates a novel use of neural network classification models to test hypotheses about developmental continuity.

Is Paternal Smoking at Conception a Risk for ADHD? A Controlled Study in Youth With and Without ADHD.

Abstract: Objective: Based on emerging preclinical findings suggesting that paternal smoking at conception may be a risk for ADHD in the offspring, we investigated whether a similar effect can be observed in...

Predictive utility of autistic traits in youth with ADHD: a controlled 10-year longitudinal follow-up study

Abstract: The objective of this study was to investigate the stability and predictive utility of autistic traits (ATs) in youth with attention-deficit/hyperactivity disorder (ADHD). Participants were referred youth with and without ADHD, without a diagnosis of autism spectrum disorder, and their siblings, derived from identically designed longitudinal case–control family studies of boys and girls with ADHD. Subjects were assessed with structured diagnostic interviews and measures of social, cognitive, and educational functioning. The presence of ATs at baseline was operationalized using a unique profile of the Child Behavior Checklist (CBCL) consisting of an aggregate T score of ≥ 195 on the Withdrawn, Social, and Thought Problems subscales (CBCL-AT profile). At the follow-up, 83% of the ADHD youth with a positive AT profile at baseline continued to have a positive CBCL-AT profile. The presence of a positive CBCL-AT profile at baseline in youth with ADHD heralded a more compromised course characterized by a greater burden of psychopathology that emerged at an earlier age, along with poorer interpersonal, educational, and neurocognitive outcomes. Findings indicate a high level of persisting ATs in ADHD youth over time, as indexed through the CBCL-AT profile, and the presence of this profile prognosticates a compromised course in adult life in multiple domains of functioning.

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

Abstract: 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.