Diagnostic Associations of Processing Speed in a Transdiagnostic, Pediatric Sample

The association of manganese overexposure and neurobehavioral function is moderated by arsenic: A metal mixture analysis of children living near coal ash storage sites

Manganese is an essential element but can be neurotoxic if overexposed. Our previous study found that a higher level of manganese in nail biomarkers from children living near coal ash storage sites was associated with poorer neurobehavioral function. Children living near this type of pollution may be exposed to other metal neurotoxicants and a better understanding of manganese in the context of multiple exposures is needed. Mixture analyses were completed using nail samples from 251 children aged 6-14 years old. These biomarkers containing metals known to impact brain functioning were investigated to test our hypothesis that a mixture of metals including manganese impacts the development of children living near coal ash sites. Nails collected from children were analyzed using ICP-MS for manganese, arsenic, cadmium, lead, and zinc based on previous research on neurotoxicity. Bayesian kernel machine regression (BKMR) was used while adjusting for age, sex, and maternal education as potential covariates. Children also completed the Behavioral Assessment Research System (BARS) to provide neurobehavioral measures of attention and processing speed as outcomes for mixture analyses. Metal mixture analyses indicated that the relationship of manganese concentration and attention and processing speed was moderated by arsenic.,. When nail biomarkers for arsenic were highest (90th percentile), manganese was associated with poorer neurobehavioral performance on the BARS, measured by CPT hit latency. At low levels of arsenic (10th percentile), there was no evidence of harmful effects from overexposure to manganese on CPT hit latency based on BKMR analysis. Previously reported effects of manganese on neurobehavioral function may be moderated by arsenic exposure. Metal exposures and behavior outcomes can be studied with mixture analyses such as BKMR to evaluate effects of simultaneous exposures on children exposed to pollution.

Processing Speed Deficit and Its Relationship with Math Fluency in Children with Attention-Deficit/Hyperactivity Disorder

OBJECTIVES

(1) To determine the processing speed (PS) deficit in children with ADHD; and (2) To investigate if PS deficit was the primary cause of daily dysfunction in ADHD by testing the direct and indirect effects via working memory (WM) of PS on math fluency (MF).

METHOD

Seventy-eight children (52 children with ADHD and 26 controls) were tested on their motor, perceptual, cognitive, and verbal PS, WM, and MF.

RESULTS

Children with ADHD performed worse than controls on all PS, suggesting a general PS deficit. Moreover, cognitive PS was a significant predictor for MF. Mediation analysis showed that cognitive PS had direct and indirect effects via WM on MF, suggesting PS deficit might be the primary cause of MF difficulties in ADHD.

CONCLUSION

Findings of this study suggested a general PS deficit in ADHD. Due to the importance of PS in MF, interventions for MF underachievers should include assessment and training of PS.

Association Between Intellectual Functioning and Autistic Traits in the General Population of Children

Autistic traits are continuously distributed in the general population. The associations between autistic traits and intellectual functioning and/or behavioural difficulties, and the impact of intellectual functioning on behavioural difficulties are unclear. The study aims to describe the distribution of autistic traits in a population-based cross-sectional sample of children. Further aims are to examine the association between intellectual functioning and autistic traits, and between autistic traits and behavioural difficulties. Wechsler scales and ratings of autistic traits and behavioural problems in 874 children aged 7-9 years in the Swedish Environmental Longitudinal Mother and Child, Asthma and Allergy (SELMA) study were assessed. We found a continuous distribution of autistic traits. Intellectual functioning was negatively associated with autistic traits but not with behavioural difficulties. Behavioural difficulties were associated with autistic traits.

Is WISC-IV Working Memory Index associated with ADHD symptoms in 7-8-year-olds?

The Working Memory Index (WMI) in the Wechsler Intelligence Scale for Children (WISC) has been suggested to be associated with ADHD symptoms. The relationship between WMI and ADHD symptoms in the general population is not clear. The study aimed to examine the association between working memory (WM) and behavioral regulation (BR), and hyperactivity/inattention (HI) in a general population sample of 7-8-year-olds, and whether general intellectual functioning is associated with BR and HI. The study also examined if those with low WMI also fulfill elevated ADHD criteria. The study group (N = 865) was assessed with the WISC (Fourth edition), the Behavior Rating Inventory of Executive Function, the Strengths and Difficulties Questionnaire, and the Five to Fifteen Questionnaire, and divided into three groups based on WM function, and in relation to BR and/or HI problems. The associations between WM and BR, and WM and HI, including intellectual functioning as covariate, were examined. WM deficits were found in 22%, but the majority of those had no BR or HI problems. Four percent in the study group had WM deficits combined with BR and/or HI problems, and in about one third of those inattentive ADHD criteria were fulfilled. WM and prosocial behavior were associated with BR and HI. WM deficits measured with WISC WMI in 7-8-year-olds do not always signal BR and/or HI problems.

The comparison of sluggish cognitive tempo, processing speed, and executive functions in female children with specific learning disabilities and typically developing female children: A pilot study

This study investigated the association of sluggish cognitive tempo (SCT), processing speed, and executive function (EF) in children with specific learning disabilities (SLD), and the typically developing children (TD) (60 female students aged between 8 and 10). Child and Adolescent Behavior Inventory-Parent Version (CABI), the Barkley Deficits in Executive Functioning Scale-Children and Adolescents (BDEFS-CA), and Wechsler Intelligence Scale for Children-IV (the Processing Speed Index (PSI) were used to assess SCT, processing speed, and EF. The results showed that SCT problems were higher in children with SLD (p < 0.001). In addition, results showed that children with SLD had poorer performance on processing speed (p < 0.001) compared to the TD group. Executive dysfunctioning in self-management to time, self-organization, problem-solving, self-restraint, self-motivation, and self-regulation of emotions were poorer in children with SLD than TD group (p < 0.05). This study provides initial evidence that SCT symptoms are poor in female children with SLD, and associated with executive dysfunction and poor processing speed.

Training a machine learning classifier to identify ADHD based on real-world clinical data from medical records

The diagnostic process of attention deficit hyperactivity disorder (ADHD) is complex and relies on criteria sensitive to subjective biases. This may cause significant delays in appropriate treatment initiation. An automated analysis relying on subjective and objective measures might not only simplify the diagnostic process and reduce the time to diagnosis, but also improve reproducibility. While recent machine learning studies have succeeded at distinguishing ADHD from healthy controls, the clinical process requires differentiating among other or multiple psychiatric conditions. We trained a linear support vector machine (SVM) classifier to detect participants with ADHD in a population showing a broad spectrum of psychiatric conditions using anonymized data from clinical records (N = 299 participants). We differentiated children and adolescents with ADHD from those not having the condition with an accuracy of 66.1%. SVM using single features showed slight differences between features and overlapping standard deviations of the achieved accuracies. An automated feature selection achieved the best performance using a combination 19 features. Real-world clinical data from medical records can be used to automatically identify individuals with ADHD among help-seeking individuals using machine learning. The relevant diagnostic information can be reduced using an automated feature selection without loss of performance. A broad combination of symptoms across different domains, rather than specific domains, seems to indicate an ADHD diagnosis.

The Influence of Socioeconomic Status (SES) and Processing Speed on the Psychological Adjustment and Wellbeing of Pediatric Brain Tumor Survivors

Simple Summary

Processing speed (PS) is one of the most impaired functions in pediatric brain tumor survivors (PBTSs) and it has been linked to difficulties in their psychological functioning, together with other non-insult-related risk factors, such as socio-economic status (SES). Given the psychological adjustment difficulties observed in PBTS, the aim of the current study was to explore the relationship between SES and psychological functioning, measured with the Child Behavioral Checklist (CBCL) and the Strengths and Difficulties Questionnaire, and considering the contribution of PS as a mediator. The results demonstrated that the influence of SES on the CBCL total index was mediated by PS. Furthermore, PS was found to have a mediating effect on the SES–internalizing problems relationship but not on the SES–externalizing problems relationship. These findings suggest that PS may be a rehabilitation target to prevent psychological distress and should be addressed, especially for PBTSs who live in a disadvantaged situation.

Abstract

(1) Background: The relationship between processing speed (PS) and psychological adjustment in the healthy population is well established, as is that between low socio-economic status (SES) and psychological distress. While PS is one of the most impaired functions in pediatric brain tumor survivors (PBTSs), previous research has demonstrated that low SES may be a predictor of increased psychosocial risk in PBTSs. Given the psychological adjustment difficulties observed in PBTS, in the current study we aimed to explore the relationship between SES and psychological functioning, considering the contribution of PS as a mediator. (2) Methods: demographic and clinical data of 80 children (age range: 4–17 y.o.) were retrospectively collected. Psychological measures were the parent-compiled versions of the Child Behavioral Checklist (CBCL) and the Strengths and Difficulties Questionnaire (SDQ). Mediation analysis models were performed on psychological measures with and without the inclusion of covariates. (3) Results: The influence of SES on the CBCL total index was mediated by PS. Furthermore, PS was found to have a mediating effect on the relationship between SES and internalizing problems but not on the relationship between SES and externalizing problems. (4) Conclusions: The results suggest that PS may be a rehabilitation target for the prevention of psychological distress and should be addressed especially for PBTSs who live in a disadvantaged situation.

Developmental Changes of Autistic Symptoms, ADHD Symptoms, and Attentional Performance in Children and Adolescents with Autism Spectrum Disorder

This study followed up ADHD/autistic symptoms and attentional performance in children/adolescents with ASD and typically developing ones (TD) over 5-7 years. The participants were stratified by age at baseline into child (< 12 years) and adolescent (12-19 years) groups. ADHD symptoms, especially hyperactivity, and attentional functions significantly improved during follow-up, more in children than in adolescents, in both ASD and TD. Significantly more omission errors and perseverations were noted in ASD than TD through the follow-up. Children with ASD had more improvement in reaction time while adolescents with ASD had less improvement in commission errors and detectability than TD. No correlation of attentional functions and ADHD symptoms in ASD implied different neural mechanisms of ADHD symptoms between ASD and ADHD.

Transdiagnostic and sex differences in cognitive profiles of autism spectrum disorder and attention-deficit/hyperactivity disorder

An increasing number of studies have shown that autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) share symptoms and aetiologies. However, transdiagnostic comparisons between ASD and ADHD is complicated due to the sex differences within each condition. To clarify the similarities and differences in the cognitive functioning between ASD and ADHD, while considering potential sex differences, this study compared cognitive profiles assessed by the WAIS-III between the four groups created by orthogonally combining diagnosis and sex based on the data from 277 ASD males, 86 ASD females, 99 ADHD males and 64 ADHD females. The analysis revealed three major findings. First, performance IQ and perceptual organization index were higher in ADHD males than in ASD males and ADHD females. Second, Gaussian mixture model fitting revealed two clusters underlying the distribution of subindex scores. The percentage of being classified into the cluster that scored lower in all the subindices was higher in females than in males irrespective of diagnosis. Third, feature importance for classification of ASD and ADHD yielded by random forest classifier, a supervised machine learning algorithm, revealed that autism quotient was most informative feature in classifying ASD and ADHD in males, while the discrepancy between verbal and performance intelligence quotient was in females, indicating that the set of behavioral features contributing to classification differs between males and females. Thus, these findings indicate that sex as well as diagnosis is critical in determining the cognitive profiles of people with ASD and ADHD. LAY SUMMARY: The present study compared profiles of cognitive functions measured by Wechsler Adult Intelligence Scale between males and females with ASD and ADHD. The analyses revealed clear sex differences in cognitive functions in both ASD and ADHD and that the set of cognitive functions useful in classifying ASD and ADHD differed between males and females. Thus, biological sex seems to be a critical factor in determining the cognitive profiles of people with ASD and ADHD.

Novel Oppositional Defiant Disorder 6 Months After Traumatic Brain Injury in Children and Adolescents

OBJECTIVE

The investigators aimed to assess predictive factors of novel oppositional defiant disorder (ODD) among children and adolescents in the first 6 months following traumatic brain injury (TBI).

METHODS

Children ages 5-14 years who experienced a TBI were recruited from consecutive admissions to five hospitals. Testing of a biopsychosocial model that may elucidate the development of novel ODD included assessment soon after injury (baseline) of preinjury characteristics, including psychiatric disorders, adaptive function, family function, psychosocial adversity, family psychiatric history, socioeconomic status, injury severity, and postinjury processing speed (which may be a proxy for brain injury). MRI analyses were also conducted to examine potential brain lesions. Psychiatric outcome, including that of novel ODD, was assessed 6 months after the injury.

RESULTS

A total of 177 children and adolescents were recruited for the study, and 134 who were without preinjury ODD, conduct disorder, or disruptive behavior disorder not otherwise specified (DBD NOS) returned for the 6-month assessment. Of those who returned 6 months postinjury, 11 (8.2%) developed novel ODD, and none developed novel conduct disorder or DBD NOS. Novel ODD was significantly associated with socioeconomic status, preinjury family functioning, psychosocial adversity, and processing speed.

CONCLUSIONS

These findings show that an important minority of children with TBI developed ODD. Psychosocial and injury-related variables, including socioeconomic status, lower family function, psychosocial adversity, and processing speed, significantly increase risk for this outcome.

Children and adolescents with neurodevelopmental disorders show cognitive heterogeneity and require a person-centered approach

We aimed to identify patterns of cognitive differences and characterize subgroups of Mexican children and adolescents with three neurodevelopmental disorders (NDD): intellectual disability (ID), autism spectrum disorders (ASD) and attention deficit/hyperactivity disorder (ADHD). The sample included 74 children and adolescents 6–15 years; 34% had ID, ASD or ADHD, 47% had ID in comorbidity with ASD, ADHD or both, 11% had ASD + ADHD, 8% were children without NDD. We applied WISC-IV, Autism Diagnostic Interview-Revised, Mini-International Neuropsychiatric Structured Interview, Child Behavior Checklist, and UNICEF Child Functioning Module. We evaluated the normality of the WISC-IV sub-scales using the Shapiro-Francia test, then conducted a latent class analysis and assessed inter-class differences in terms of household, parent and child characteristics. The following four-class solution best fit the data: “Lower Cognitive Profile” (LCP), “Lower Working Memory” (LWM), “Higher Working Memory” (HWM), “Higher Cognitive Profile” (HCP). LCP included most of the children with ID, who had a low Working Memory (WM) index score. LWM included mainly children with ASD or ID + ADHD; their Perceptual Reasoning (PR) and Processing Speed (PS) index scores were much higher than those for Verbal Comprehension (VC) and WM. HWM included children with ASD or ADHD; their scores for PR, PS and VC were high with lower WM (although higher than for LWM). HCP included children without NDD and with ASD or ADHD or both and had the highest scores on all indices. Children with NDD show cognitive heterogeneity and thus require individualized treatment plans.

Predicting brain age during typical and atypical development based on structural and functional neuroimaging

Exploring typical and atypical brain developmental trajectories is very important for understanding the normal pace of brain development and the mechanisms by which mental disorders deviate from normal development. A precise and sex-specific brain age prediction model is desirable for investigating the systematic deviation and individual heterogeneity of disorders associated with atypical brain development, such as autism spectrum disorders. In this study, we used partial least squares regression and the stacking algorithm to establish a sex-specific brain age prediction model based on T1-weighted structural magnetic resonance imaging and resting-state functional magnetic resonance imaging. The model showed good generalization and high robustness on four independent datasets with different ethnic information and age ranges. A predictor weights analysis showed the differences and similarities in changes in structure and function during brain development. At the group level, the brain age gap estimation for autistic patients was significantly smaller than that for healthy controls in both the ABIDE dataset and the healthy brain network dataset, which suggested that autistic patients as a whole exhibited the characteristics of delayed development. However, within the ABIDE dataset, the premature development group had significantly higher Autism Diagnostic Observation Schedule (ADOS) scores than those of the delayed development group, implying that individuals with premature development had greater severity. Using these findings, we built an accurate typical brain development trajectory and developed a method of atypical trajectory analysis that considers sex differences and individual heterogeneity. This strategy may provide valuable clues for understanding the relationship between brain development and mental disorders.

Maternal prenatal choline and inflammation effects on 4-year-olds' performance on the Wechsler Preschool and Primary Scale of Intelligence-IV

Maternal gestational inflammation from infection, obesity, depression, and adverse childhood experiences negatively affects offspring cognitive development. Choline is a key nutrient in fetal brain development. We investigated whether higher maternal plasma choline concentrations have a positive association with offspring cognition, specifically processing speed, in the presence of inflammation. Forty-eight children were evaluated at 4 years of age. Processing Speed Composite Score on the Wechsler Preschool & Primary Scales of Intelligence was the principal outcome. Maternal C-reactive protein (CRP), a marker of inflammation, and choline plasma concentration had been measured at 16 weeks' gestation. Choline concentrations >7.07μM were compared to lower levels. Mothers with lower choline levels reported more depression and stress. Head circumference was larger for neonates of mothers with higher choline levels. In analyses with maternal CRP, higher maternal choline was associated with higher offspring Processing Speed Composite Scores for both sexes. For males, higher maternal choline competed with the negative association of maternal CRP on Processing Speed. Higher Processing Speed was related to the child's behavioral ratings, with fewer Withdrawn Problems on the Child Behavior Checklist 1 ½-5 years at 4 years and higher Infant Behavior Questionnaire Orienting/Regulation at 3 months of age, consistent with persistent developmental effects. Higher processing speed and decreased problems in social withdrawal are positively associated with prenatal maternal choline. Both lower processing speed and social withdrawal problems are precursors to later mental difficulties. Choline supplementation in pregnancy may mitigate effects of maternal inflammation that contribute to problems in offspring's' cognition and behavior.

Clinical presentations of attention-deficit/hyperactivity disorder (ADHD) in children and adolescents: comparison of neurocognitive performance

This study aimed to compare performance in working memory (WM), processing speed (PRS), and attention measures in children and adolescents with typical development (TD) and with Attention deficit hyperactivity disorder (inattentive [ADHD-I] or combined [ADHD-C]) presentations, and to determine the predictive ability of the measures mentioned to discriminate between ADHD presentations and TD. 260 children and adolescents, 138 with ADHD (70 ADHD-I and 68 ADHD-C) and 122 TD in two age cohorts (8-12 years; 13-16 years), were assessed with WM and PRS indexes of Wechsler Intelligence Scale for Children (WISC-IV) and the d2 attention test. Significant differences between ADHD and TD groups in the WISC-IV GAI scores were found in children but not in adolescents. Children and adolescents with both ADHD presentations performed poorly on the PRS index, while on the WM index only children exhibited difficulties. In the attention test, children with ADHD-C showed more impulsivity and more difficulties for processing speed, concentration and accuracy than ADHD-I and TD. In addition, both ADHD presentations had higher inattention scores than TD. ADHD adolescents performed worse than TD in processing speed, concentration and accuracy. ADHD groups showed more impulsivity and inattention than TD. Digit Span and Symbol Search (WISC-IV) and processing speed and accuracy (d2) successfully classified ADHD and TD in children, but in adolescents, only coding (WISC-IV) and accuracy (d2) successfully classified ADHD presentations and TD. The WISC-IV and d2 yield neuropsychological profiles which reflect age-related cognitive changes and may allow the adaptation of more tailored early interventions for ADHD.