Faculty Bibliography

BACKGROUND:Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are biologically heterogeneous and often co-occur. As within-diagnosis heterogeneity and overlapping diagnoses are challenging for researchers and clinicians, identifying biologically homogenous subgroups, independent of diagnosis, is an urgent need. METHODS:MRI data from 148 adult males with developmental disorders (99 primary ASD, mean age = 31.7 ± 8.0, 49 primary ADHD; mean age = 31.7 ± 9.6) and 105 neurotypical controls (NTC; mean age = 30.6 ± 6.8) were analyzed. We extracted mean cortical thickness (CT) and surface area (SA) values using a functional atlas. Then, we conducted HeterogeneitY through DiscRiminant Analysis (HYDRA) to transdiagnostically cluster and classify individuals. Differences in diagnostic likelihood and clinical symptoms between subtypes were tested. Sensitivity analyses tested the stability of the number of subtypes and their membership by excluding 13 participants diagnosed with both ASD and ADHD and by using a different atlas. RESULTS:In relation to both CT and SA, HYDRA identified two subtypes. The likelihood of ASD or ADHD was not significantly different from the chance of belonging to any of these two subtypes. Clinical characteristics did not differ between subtypes in either CT or SA based analyses. The high consistency in membership was replicated when utilizing a different atlas or excluding people with dual diagnoses in CT (dice coefficients > 0.94) and in SA (>0.88). CONCLUSION/CONCLUSIONS:Although the brain-derived subtypes do not match diagnostic groups, individuals with developmental disorders were successfully and stably subtyped using either CT or SA.

BACKGROUND:Antidepressants may be used to manage a number of conditions in children and young people including depression, anxiety, and obsessive-compulsive disorder. UK guidelines for the treatment of depression in children and young people recommend that antidepressants should only be initiated following assessment and diagnosis by a child and adolescent psychiatrist. The aim of this study was to summarise visits to mental health specialists and indications recorded around the time of antidepressant initiation in children and young people in UK primary care. METHODS:The study used linked English primary care electronic health records and Hospital Episode Statistics secondary care data. The study included 5-17-year-olds first prescribed antidepressants between January 2006 and December 2017. Records of visits to paediatric or psychiatric specialists and potential indications (from a pre-specified list) were extracted. Events were counted if recorded less than 12 months before or 6 months after the first antidepressant prescription. Results were stratified by first antidepressant type (all, selective serotonin reuptake inhibitors (SSRIs), tricyclic and related antidepressants) and by age group (5-11 years, 12-17 years). RESULTS:In total, 33,031 5-17-year-olds were included. Of these, 12,149 (37%) had a record of visiting a paediatrician or a psychiatric specialist in the specified time window. The majority of recorded visits (7154, 22%) were to paediatricians. Of those prescribed SSRIs, 5463/22,130 (25%) had a record of visiting a child and adolescent psychiatrist. Overall, 17,972 (54%) patients had a record of at least one of the pre-specified indications. Depression was the most frequently recorded indication (12,501, 38%), followed by anxiety (4155, 13%). CONCLUSIONS:The results suggest many children and young people are being prescribed antidepressants without the recommended involvement of a relevant specialist. These findings may justify both greater training for GPs in child and adolescent mental health and greater access to specialist care and non-pharmacological treatments. Further research is needed to explore factors that influence how and why GPs prescribe antidepressants to children and young people and the real-world practice barriers to adherence to clinical guidelines.

Drawing on data from the Clinical Practice Research Datalink, Price et al reported UK regional variations in primary care prescribing and referral rates to adult mental health services for young people with attention-deficit hyperactivity disorder (ADHD) in transition from child and adolescent mental health services. Overall, considering that around 65% of young adults with childhood ADHD present with impairing ADHD symptoms and up to 90% of individuals with ADHD may benefit from ADHD medications, the study by Price et al shows that the rate of appropriate treatment for youngsters in the transition period varies from low to very low across the UK. As such, there is a continuous need for education and training for patients, their families, mental health professionals and commissioners, to eradicate the misconception that, in the majority of the cases, ADHD remits during adolescence and to support the devolvement of appropriate services for the evidence-based management of adult ADHD across the UK.

BACKGROUND:Emotional dysregulation (ED) and callous unemotional (CU) traits can be associated with ADHD in youth, influencing its natural history and outcome, but their effect on medication efficacy is unexplored. We examined whether two measures of baseline ED and CU traits, the Child Behavior Checklist-Dysregulation Profile (CBCL-DP) and the Antisocial Process Screening Device (APSD), respectively, were predictors of change of ADHD-Rating Scale (ADHD-RS) after a 4-week methylphenidate (MPH) monotherapy. METHODS:43 patients (37 males, 8-16 years, mean 9.9 ± 2.7 years) were included. Hierarchical linear regression models were used to explore whether CBCL-DP and APSD might predict ADHD-RS score, controlling for baseline severity. RESULTS:Baseline CBCL-DP predicted higher post-treatment ADHD-RS scores in total and hyperactivity-impulsivity, but not in inattention subscale. Baseline APSD was not significantly related to ADHD-RS scores at the follow-up. LIMITATIONS/CONCLUSIONS:Small sample size, lack of gender diversity, non-blind design and short period of observation. CONCLUSION/CONCLUSIONS:ED, assessed with that CBCL-DP, might be a negative predictor of change of hyperactive-impulsive symptoms after MPH treatment and should be systematically assessed at baseline.

Sleep problems are a common complaint in children/adolescents with autism spectrum disorder (ASD). Correctly diagnosing and treating sleep problems in individuals with ASD is key, as they can add to the psychosocial burden of the disorder and exacerbate associated symptoms, such as inattention or irritability. Here, we provide an overview of the epidemiology, diagnosis, and management of sleep problems/disorders in children and adolescents with ASD. This narrative review is mainly informed by a systematic search in PubMed and PsycInfo (last search: 10 October 2019) of available pertinent meta-analyses. We also searched for randomized controlled trials (RCTs) published after the search date of available meta-analyses. As for the epidemiology of sleep disorders in ASD, recent meta-analytic evidence shows a pooled prevalence of 13% (95% confidence interval [CI] 9-17) in the ASD population, compared with 3.7% in the general population. In terms of diagnosis of sleep disorders, it should be based on standardized criteria [e.g., the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) or third edition of the International Classification of Sleep Disorders (ICSD)]; clinicians should bear in mind that the communication difficulties presented by individuals with ASD may make the diagnostic process more challenging. Regarding the treatment, a meta-analysis of behavioral interventions, including only three RCTs, found significant effects in terms of increase in total sleep time (24.41 min, 95% CI 5.71-43.11, P = 0.01), decrease in sleep-onset latency (- 18.31 min, 95% CI - 30.84 to - 5.77, P = 0.004), and a significant effect on sleep efficiency (5.59, 95% CI 0.87-10.31, P = 0.02), albeit the risk of bias of the included studies was rated "high" in relation to issues with the blinding. The bulk of the evidence for the pharmacological treatment is for melatonin, with a meta-analysis of five double-blind RCTs showing a large effect size, favoring melatonin, in sleep duration (44 min compared with placebo, Hedge's g 1.07 [95% CI 0.49-1.65]) and sleep-onset latency (39 min compared with placebo, Hedge's g - 2.46 [95% CI - 1.96 to - 2.98]). We conclude that additional RCTs are desperately needed to support the management of sleep disorders in ASD with an evidence-based, precision medicine approach.

OBJECTIVE:Previous research on adults with ADHD revealed high rates of overweight and obesity, as well as unhealthy diet habits. Other studies demonstrated that social-affective contexts can influence food choice. This study examines the sensitivity of adults with ADHD to cues of food attractiveness and convenience, for healthy and unhealthy foods. METHOD/METHODS:One hundred and seventy-two university students with (n = 59) and without (n = 113) ADHD, aged 19-40, participated in the study. Participants rated the level of appeal of 32 pictures of healthy and unhealthy foods, which varied in the degree of attractiveness and convenience. RESULTS:The findings reveal a higher level of appeal of attractive food items compared to non-attractive ones (p < .001), as well as of convenient compared to non-convenient food items (p = .005). Type of diagnostic group did not have an effect on the level of appeal. CONCLUSION/CONCLUSIONS:Increasing the attractiveness and convenience of food items increased the level of appeal for both students with and without ADHD. These findings emphasize the importance of environmental health intervention to potentially reduce abnormal eating pattern in the ADHD adult population, which may contribute in preventing the reported higher risk of obesity in this population.

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.