TRAILS consists of a population cohort (N=2230) and a clinical cohort (N=543), both of which were followed from about age 11 years onwards. To date, the population cohort has been assessed five times ...over a period of 11 years, with retention rates ranging between 80% and 96%. The clinical cohort has been assessed four times over a period of 8 years, with retention rates ranging between 77% and 85%. Since the IJE published a cohort profile on the TRAILS in 2008, the participants have matured from adolescents into young adults. The focus shifted from parents and school to entry into the labour market and family formation, including offspring. Furthermore, psychiatric diagnostic interviews were administered, the database was linked to a Psychiatric Case Registry, and the availability of genome-wide SNP variations opened the door to genome-wide association studies regarding a wide range of (endo)phenotypes. With some delay, TRAILS data are available to researchers outside the TRAILS consortium without costs; access can be obtained by submitting a publication proposal (see www.trails.nl).
In his first description of Autism Spectrum Disorders (ASD), Kanner emphasized emotional impairments by characterizing children with ASD as indifferent to other people, self-absorbed, emotionally ...cold, distanced, and retracted. Thereafter, emotional impairments became regarded as part of the social impairments of ASD, and research mostly focused on understanding how individuals with ASD recognize visual expressions of emotions from faces and body postures. However, it still remains unclear how emotions are processed outside of the visual domain. This systematic review aims to fill this gap by focusing on impairments of emotional language processing in ASD. We systematically searched PubMed for papers published between 1990 and 2013 using standardized search terms. Studies show that people with ASD are able to correctly classify emotional language stimuli as emotionally positive or negative. However, processing of emotional language stimuli in ASD is associated with atypical patterns of attention and memory performance, as well as abnormal physiological and neural activity. Particularly, younger children with ASD have difficulties in acquiring and developing emotional concepts, and avoid using these in discourse. These emotional language impairments were not consistently associated with age, IQ, or level of development of language skills. We discuss how emotional language impairments fit with existing cognitive theories of ASD, such as central coherence, executive dysfunction, and weak Theory of Mind. We conclude that emotional impairments in ASD may be broader than just a mere consequence of social impairments, and should receive more attention in future research.
Predictive Processing accounts of autism claim that autistic individuals assign higher precision to their prediction errors than non‐autistic individuals, that is, autistic individuals update their ...predictions more readily when faced with unexpected sensory input. Since setting the level of precision is a fundamental part of perception and learning, we propose that such differences should be detectable in various domains at a very early age, before clinical symptoms have fully emerged. We therefore tested 3‐year‐old younger siblings of autistic children, with a high likelihood of later receiving an autism diagnosis themselves, and low‐likelihood children with an older sibling without autism. We used a novel implicit learning paradigm to examine the effect of sensory noise on the predictions participants built. In order to learn a sequence, our participants had to select which visual information to attend to and disregard low‐level prediction errors caused by the sensory noise, which the theory claims is more difficult for autistic individuals. Contrary to the proposed higher precision‐weighting of prediction errors in autism, the high‐likelihood children did not show signs of updating their predictions more readily when we added sensory noise compared to the low‐likelihood children, either in their reaction times or in the recurrence and determinism of their response locations. These results raise challenges for Predictive Processing theories of autism, specifically for the notion that prediction errors are inflexibly highly weighted by individuals with autism.
Summary Background The effects of a restricted elimination diet in children with attention-deficit hyperactivity disorder (ADHD) have mainly been investigated in selected subgroups of patients. We ...aimed to investigate whether there is a connection between diet and behaviour in an unselected group of children. Methods The Impact of Nutrition on Children with ADHD (INCA) study was a randomised controlled trial that consisted of an open-label phase with masked measurements followed by a double-blind crossover phase. Patients in the Netherlands and Belgium were enrolled via announcements in medical health centres and through media announcements. Randomisation in both phases was individually done by random sampling. In the open-label phase (first phase), children aged 4–8 years who were diagnosed with ADHD were randomly assigned to 5 weeks of a restricted elimination diet (diet group) or to instructions for a healthy diet (control group). Thereafter, the clinical responders (those with an improvement of at least 40% on the ADHD rating scale ARS) from the diet group proceeded with a 4-week double-blind crossover food challenge phase (second phase), in which high-IgG or low-IgG foods (classified on the basis of every child's individual IgG blood test results) were added to the diet. During the first phase, only the assessing paediatrician was masked to group allocation. During the second phase (challenge phase), all persons involved were masked to challenge allocation. Primary endpoints were the change in ARS score between baseline and the end of the first phase (masked paediatrician) and between the end of the first phase and the second phase (double-blind), and the abbreviated Conners' scale (ACS) score (unmasked) between the same timepoints. Secondary endpoints included food-specific IgG levels at baseline related to the behaviour of the diet group responders after IgG-based food challenges. The primary analyses were intention to treat for the first phase and per protocol for the second phase. INCA is registered as an International Standard Randomised Controlled Trial, number ISRCTN 76063113. Findings Between Nov 4, 2008, and Sept 29, 2009, 100 children were enrolled and randomly assigned to the control group (n=50) or the diet group (n=50). Between baseline and the end of the first phase, the difference between the diet group and the control group in the mean ARS total score was 23·7 (95% CI 18·6–28·8; p<0·0001) according to the masked ratings. The difference between groups in the mean ACS score between the same timepoints was 11·8 (95% CI 9·2–14·5; p<0·0001). The ARS total score increased in clinical responders after the challenge by 20·8 (95% CI 14·3–27·3; p<0·0001) and the ACS score increased by 11·6 (7·7–15·4; p<0·0001). In the challenge phase, after challenges with either high-IgG or low-IgG foods, relapse of ADHD symptoms occurred in 19 of 30 (63%) children, independent of the IgG blood levels. There were no harms or adverse events reported in both phases. Interpretation A strictly supervised restricted elimination diet is a valuable instrument to assess whether ADHD is induced by food. The prescription of diets on the basis of IgG blood tests should be discouraged. Funding Foundation of Child and Behaviour, Foundation Nuts Ohra, Foundation for Children's Welfare Stamps Netherlands, and the KF Hein Foundation.
Background
Family mindfulness‐based intervention (MBI) for child attention‐deficit/hyperactivity disorder (ADHD) targets child self‐control, parenting and parental mental health, but its ...effectiveness is still unclear.
Methods
MindChamp is a pre‐registered randomised controlled trial comparing an 8‐week family MBI (called ‘MYmind’) in addition to care‐as‐usual (CAU) (n = 55) with CAU‐only (n = 48). Children aged 8–16 years with remaining ADHD symptoms after CAU were enrolled together with a parent. Primary outcome was post‐treatment parent‐rated child self‐control deficits (BRIEF); post hoc, Reliable Change Indexes were explored. Secondary child outcomes included ADHD symptoms (parent/teacher‐rated Conners’ and SWAN; teacher‐rated BRIEF), other psychological symptoms (parent/teacher‐rated), well‐being (parent‐rated) and mindfulness (self‐rated). Secondary parent outcomes included self‐ratings of ADHD symptoms, other psychological symptoms, well‐being, self‐compassion and mindful parenting. Assessments were conducted at post‐treatment, 2‐ and 6‐month follow‐up.
Results
Relative to CAU‐only, MBI+CAU resulted in a small, statistically non‐significant post‐treatment improvement on the BRIEF (intention‐to‐treat: d = 0.27, p = .18; per protocol: d = 0.33, p = .11). Significantly more children showed reliable post‐treatment improvement following MBI+CAU versus CAU‐only (32% versus 11%, p < .05, Number‐Needed‐to‐Treat = 4.7). ADHD symptoms significantly reduced post‐treatment according to parent (Conners’ and SWAN) and teacher ratings (BRIEF) per protocol. Only parent‐rated hyperactivity impulsivity (SWAN) remained significantly reduced at 6‐month follow‐up. Post‐treatment group differences on other secondary child outcomes were consistently favour of MBI+CAU, but mostly non‐significant; no significant differences were found at follow‐ups. Regarding parent outcomes, significant post‐treatment improvements were found for their own ADHD symptoms, well‐being and mindful parenting. At follow‐ups, some significant effects remained (ADHD symptoms, mindful parenting), some additional significant effects appeared (other psychological symptoms, self‐compassion) and others disappeared/remained non‐significant.
Conclusions
Family MBI+CAU did not outperform CAU‐only in reducing child self‐control deficits on a group level but more children reliably improved. Effects on parents were larger and more durable. When CAU for ADHD is insufficient, family MBI could be a valuable addition.
Background: Autism spectrum disorder (ASD) and attention‐deficit/hyperactivity disorder (ADHD) share about 50–72% of their genetic factors, which is the most likely explanation for their frequent ...co‐occurrence within the same patient or family. An additional or alternative explanation for the co‐occurrence may be (cross‐)assortative mating, e.g., the tendency to choose a partner that is similar or dissimilar to oneself. Another issue is that of parent‐of‐origin effect which refers to the possibility of parents differing in the relative quantity of risk factors they transmit to the offspring. The current study sets out to examine (cross‐)assortative mating and (cross‐)parent‐of‐origin effects of ASD and ADHD in parents of children with either ASD or ASD with ADHD diagnosis.
Methods: In total, 121 families were recruited in an ongoing autism‐ADHD family genetics project. Participating families consisted of parents and at least one child aged between 2 and 20 years, with either autistic disorder, Asperger disorder or PDD‐NOS, and one or more biological siblings. All children and parents were carefully screened for the presence of ASD and ADHD.
Results: No correlations were found between maternal and paternal ASD and ADHD symptoms. Parental ASD and ADHD symptoms were predictive for similar symptoms in the offspring, but with maternal hyperactive‐impulsive symptoms, but not paternal symptoms, predicting similar symptoms in daughters. ASD pathology in the parents was not predictive for ADHD pathology in the offspring, but mother’s ADHD pathology was predictive for offspring ASD pathology even when corrected for maternal ASD pathology.
Conclusions: Cross‐assortative mating for ASD and ADHD does not form an explanation for the frequent co‐occurrence of these disorders within families. Given that parental ADHD is predictive of offspring’ ASD but not vice versa, risk factors underlying ASD may overlap to a larger degree with risk factors underlying ADHD than vice versa. However, future research is needed to clarify this issue.
Attention-deficit hyperactivity disorder (ADHD) is linked to increased risk for substance use disorders and nicotine dependence.
To examine the effects of stimulant treatment on subsequent risk for ...substance use disorder and nicotine dependence in a prospective longitudinal ADHD case-control study.
At baseline we assessed ADHD, conduct disorder and oppositional defiant disorder. Substance use disorders, nicotine dependence and stimulant treatment were assessed retrospectively after a mean follow-up of 4.4 years, at a mean age of 16.4 years.
Stimulant treatment of ADHD was linked to a reduced risk for substance use disorders compared with no stimulant treatment, even after controlling for conduct disorder and oppositional defiant disorder (hazard ratio (HR) = 1.91, 95% CI 1.10-3.36), but not to nicotine dependence (HR = 1.12, 95% CI 0.45-2.96). Within the stimulant-treated group, a protective effect of age at first stimulant use on substance use disorder development was found, which diminished with age, and seemed to reverse around the age of 18.
Stimulant treatment appears to lower the risk of developing substance use disorders and does not have an impact on the development of nicotine dependence in adolescents with ADHD.
The neuroanatomical basis of autism spectrum disorder (ASD) has remained elusive, mostly owing to high biological and clinical heterogeneity among diagnosed individuals. Despite considerable effort ...toward understanding ASD using neuroimaging biomarkers, heterogeneity remains a barrier, partly because studies mostly employ case-control approaches, which assume that the clinical group is homogeneous.
Here, we used an innovative normative modeling approach to parse biological heterogeneity in ASD. We aimed to dissect the neuroanatomy of ASD by mapping the deviations from a typical pattern of neuroanatomical development at the level of the individual and to show the necessity to look beyond the case-control paradigm to understand the neurobiology of ASD. We first estimated a vertexwise normative model of cortical thickness development using Gaussian process regression, then mapped the deviation of each participant from the typical pattern. For this, we employed a heterogeneous cross-sectional sample of 206 typically developing individuals (127 males) and 321 individuals with ASD (232 males) (6–31 years of age).
We found few case-control differences, but the ASD cohort showed highly individualized patterns of deviations in cortical thickness that were widespread across the brain. These deviations correlated with severity of repetitive behaviors and social communicative symptoms, although only repetitive behaviors survived corrections for multiple testing.
Our results 1) reinforce the notion that individuals with ASD show distinct, highly individualized trajectories of brain development and 2) show that by focusing on common effects (i.e., the “average ASD participant”), the case-control approach disguises considerable interindividual variation crucial for precision medicine.
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