The overlap of disordered eating, autism and ADHD: future research priorities as identified by adults with lived experience.

The focus of mental health research in emerging fields should be driven by the priorities of people with relevant lived experience. Autism and ADHD are childhood-onset neurodevelopmental conditions that are associated with a range of health inequalities, including increased risk for eating disorders. The evidence base for how best to support neurodivergent individuals who experience disordered eating is still in its infancy, but research suggests that existing clinical approaches are not currently fit for purpose. In this Personal View, through community consultation with autistic people and people with ADHD who have experienced disordered eating, we present a comprehensive ranked list of research topics that people with lived experience prioritise. These priorities could be clustered into two areas: improving outcomes and identifying causal mechanisms. Within the theme of improving disordered eating outcomes, priorities are the improvement of treatment, the need for neurodiversity training in clinical services, and the identification and minimisation of unintended adverse effects of psychological intervention. Within the theme of identifying causal mechanisms, priorities are the identification of risk factors and a better understanding of the effect of autistic or ADHD neurocognitive profiles as potential contributors to eating disorder vulnerability. The final top ten research priorities are contextualised in terms of how they compare to the existing literature on the overlap between autism or ADHD and eating disorders, and concrete suggestions are made for how to implement these research priorities as testable hypotheses. Research informed by these priorities will build necessary understanding of the reasons behind the increased risk for eating disorders in neurodivergent people, and how to best support people who are affected by disordered eating to live positive and fulfilling lives.

The importance of decomposing periodic and aperiodic EEG signals for assessment of brain function in a global context.

Measures of early neuro-cognitive development that are suitable for use in low-resource settings are needed to enable studies of the effects of early adversity on the developing brain in a global context. These measures should have high acquisition rates and good face and construct validity. Here, we investigated the feasibility of a naturalistic electroencephalography (EEG) paradigm in a low-resource context during childhood. Additionally, we examined the sensitivity of periodic and aperiodic EEG metrics to social and non-social stimuli. We recorded simultaneous 20-channel EEG and eye-tracking in 72 children aged 4-12 years (45 females) while they watched videos of women singing nursery rhymes and moving toys, selected to represent familiar childhood experiences. These measures were part of a feasibility study that assessed the feasibility and acceptability of a follow-up data collection of the South African Safe Passage Study, which tracks environmental adversity and brain and cognitive development from before birth up until childhood. We examined whether data quantity and quality varied with child characteristics and the sensitivity of varying EEG metrics (canonical band power in the theta and alpha band and periodic and aperiodic features of the power spectra). We found that children who completed the EEG and eye-tracking assessment were, in general, representative of the full cohort. Data quantity was higher in children with greater visual attention to the stimuli. Out of the tested EEG metrics, periodic measures in the theta frequency range were most sensitive to condition differences, compared to alpha range measures and canonical and aperiodic EEG measures. Our results show that measuring EEG during ecologically valid social and non-social stimuli is feasible in low-resource settings, is feasible for most children, and produces robust indices of social brain function. This work provides preliminary support for testing longitudinal links between social brain function, environmental factors, and emerging behaviors.

Candidate diagnostic biomarkers for neurodevelopmental disorders in children and adolescents: a systematic review.

Neurodevelopmental disorders - including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, communication disorders, intellectual disability, motor disorders, specific learning disorders, and tic disorders - manifest themselves early in development. Valid, reliable and broadly usable biomarkers supporting a timely diagnosis of these disorders would be highly relevant from a clinical and public health standpoint. We conducted the first systematic review of studies on candidate diagnostic biomarkers for these disorders in children and adolescents. We searched Medline and Embase + Embase Classic with terms relating to biomarkers until April 6, 2022, and conducted additional targeted searches for genome-wide association studies (GWAS) and neuroimaging or neurophysiological studies carried out by international consortia. We considered a candidate biomarker as promising if it was reported in at least two independent studies providing evidence of sensitivity and specificity of at least 80%. After screening 10,625 references, we retained 780 studies (374 biochemical, 203 neuroimaging, 133 neurophysiological and 65 neuropsychological studies, and five GWAS), including a total of approximately 120,000 cases and 176,000 controls. While the majority of the studies focused simply on associations, we could not find any biomarker for which there was evidence - from two or more studies from independent research groups, with results going into the same direction - of specificity and sensitivity of at least 80%. Other important metrics to assess the validity of a candidate biomarker, such as positive predictive value and negative predictive value, were infrequently reported. Limitations of the currently available studies include mostly small sample size, heterogeneous approaches and candidate biomarker targets, undue focus on single instead of joint biomarker signatures, and incomplete accounting for potential confounding factors. Future multivariable and multi-level approaches may be best suited to find valid candidate biomarkers, which will then need to be validated in external, independent samples and then, importantly, tested in terms of feasibility and cost-effectiveness, before they can be implemented in daily clinical practice.

Psychiatric conditions in autistic adolescents: longitudinal stability from childhood and associated risk factors.

Autistic people experience high rates of co-occurring psychiatric diagnoses. Current prevalence estimates vary considerably due to an over-reliance on clinical cohorts and the longitudinal stability of diagnoses from childhood into adolescence is poorly understood. This study aims to provide prevalence rates of co-occurring DSM-5 psychiatric diagnosis for autistic adolescence and investigate, for the first time, the stability of diagnoses from childhood. Using a longitudinal stratified sample of autistic youth (N = 77; 13-17 years; 60% male), selected from a larger community-derived sample of those with pre-existing autism diagnoses (N = 277) weighted prevalence estimates of emotional (anxiety, depression), behavioural (oppositional and conduct disorders) and ADHD diagnoses were calculated based on semi-structured psychiatric interview. Prediction of adolescent psychiatric diagnosis based on childhood diagnostic status, sex, childhood IQ (both assessed at age 4-10 years) was tested. Emotional and behavioural disorders in adolescence were particularly prevalent, and significantly predicted by childhood disorder status. Attention-deficit/hyperactivity-disorder (ADHD) was prevalent but not predicted by childhood ADHD diagnosis. Neither sex nor childhood IQ predicted diagnostic outcomes. Autistic youth have high levels of co-occurring psychiatric conditions, which are broadly persistent across childhood and adolescence. Emotional disorders are particularly prevalent and remain persistent from childhood to adolescence. Greater diagnostic variability was found for ADHD with more adolescents moving across diagnostic thresholds.