Environmental and Genetic Influences on Neurocognitive Development: The Importance of Multiple Methodologies and Time-Dependent Intervention

Mapping the duration and severity of preschool-aged children's depressive moods and behaviors

BACKGROUND

Depressive moods and behaviors are developmentally normative, yet potentially impairing, in preschool-aged children. In addition to frequency, duration of behavior is an important parameter to consider when characterizing risk for worsening mood dysregulation. The goal of this study was to identify the duration and severity of depressive moods and behaviors and associations with impairment in a large community sample of preschool-aged children using an online parent-report daily diary.

METHODS

Primary caregivers (N = 900) of 3-5-year-old children reported the daily duration of each instance of seven depressive moods and behaviors for 14 days. We used item response theory analyses to examine duration item characteristics.

RESULTS

Moods and behaviors occurred at specific durations to be considered psychometrically severe/rare; for example, instances of sadness had to last an average total of 32 min per day or more, irritability at least 38 min, tantrums at least 30 min, and tearfulness/sensitivity at least 35 min. Longer durations of mood and behavior were associated with daily impairment, as well as older child age and less parental education.

CONCLUSIONS

To our knowledge, this is the first study to delineate specific duration ranges for depressive moods and behaviors in preschool-aged children. These data, coupled with information about the frequency of mood-related behaviors, can assist child practitioners in differentiating normative patterns from less normative mood problems to evaluate which children may be at risk. Future work should identify the duration of depressive moods and behaviors in early childhood that predict clinically significant psychopathology over time.

Modulation of neural circuits by melatonin in neurodegenerative and neuropsychiatric disorders

Neurodegenerative and neuropsychiatric disorders are two broad categories of neurological disorders characterized by progressive impairments in movement and cognitive functions within the central and peripheral nervous systems, and have emerged as a significant cause of mortality. Oxidative stress, neuroinflammation, and neurotransmitter imbalances are recognized as prominent pathogenic factors contributing to cognitive deficits and neurobehavioral anomalies. Consequently, preventing neurodegenerative and neuropsychiatric diseases has surfaced as a pivotal challenge in contemporary public health. This review explores the investigation of neurodegenerative and neuropsychiatric disorders using both synthetic and natural bioactive compounds. A central focus lies on melatonin, a neuroregulatory hormone secreted by the pineal gland in response to light-dark cycles. Melatonin, an amphiphilic molecule, assumes multifaceted roles, including scavenging free radicals, modulating energy metabolism, and synchronizing circadian rhythms. Noteworthy for its robust antioxidant and antiapoptotic properties, melatonin exhibits diverse neuroprotective effects. The inherent attributes of melatonin position it as a potential key player in the pathophysiology of neurological disorders. Preclinical and clinical studies have demonstrated melatonin's efficacy in alleviating neuropathological symptoms across neurodegenerative and neuropsychiatric conditions (depression, schizophrenia, bipolar disorder, and autism spectrum disorder). The documented neuroprotective prowess of melatonin introduces novel therapeutic avenues for addressing neurodegenerative and psychiatric disorders. This comprehensive review encompasses many of melatonin's applications in treating diverse brain disorders. Despite the strides made, realizing melatonin's full neuroprotective potential necessitates further rigorous clinical investigations. By unravelling the extended neuroprotective benefits of melatonin, future studies promise to deepen our understanding and augment the therapeutic implications against neurological deficits.

Longitudinal effects of environmental noise and air pollution exposure on autism spectrum disorder and attention-deficit/hyperactivity disorder during adolescence and early adulthood: The TRAILS study

BACKGROUND

Exposure to ambient noise and air pollution may affect the manifestation and severity of Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD). However, evidence is limited, and most studies solely assessed environmental exposures during pregnancy and early childhood.

OBJECTIVE

To examine the longitudinal effects of ambient noise and air pollutants on ASD and ADHD symptom severity during adolescence and early adulthood.

METHODS

Using a longitudinal design, we included 2750 children between 10 and 12 years old from the TRacking Adolescents' Individual Lives Survey (TRAILS) in the Netherlands, who were assessed in 6 waves from 2001 to 2017. ASD was measured by the Children's Social Behavior Questionnaire and the Adult Social Behavior Questionnaire. ADHD was measured by Child Behavior Checklist and the Adult Behavior Checklist. Ambient noise and air pollution exposures, including Ozone (O₃), soot, sulfur dioxide (SO₂), nitrogen dioxide (NO₂), particulate matter 2.5 (PM_2.5), and PM₁₀ were modeled at the residential level according to standardized protocols. The longitudinal associations between exposures and symptom outcomes were examined using linear mixed models.

RESULTS

We found evidence that higher levels of exposure to PM were associated with more severe ASD and ADHD symptoms. This association decreased over time. We did not observe any other consistent associations of noise or other air pollutants with ASD and ADHD severity.

CONCLUSION

The current study provides evidence for the negative impact of PM on ASD and ADHD symptoms. We did not find evidence of the negative health impact of other air pollutants and noise exposures on ASD or ADHD symptoms. Our study adds more evidence on the presence of associations between PM air pollution and neurodevelopmental diseases among adolescents and young adults.

DRDs and Brain-Derived Neurotrophic Factor Share a Common Therapeutic Ground: A Novel Bioinformatic Approach Sheds New Light Toward Pharmacological Treatment of Cognitive and Behavioral Disorders

Cognitive and behavioral disorders are subgroups of mental health disorders. Both cognitive and behavioral disorders can occur in people of different ages, genders, and social backgrounds, and they can cause serious physical, mental, or social problems. The risk factors for these diseases are numerous, with a range from genetic and epigenetic factors to physical factors. In most cases, the appearance of such a disorder in an individual is a combination of his genetic profile and environmental stimuli. To date, researchers have not been able to identify the specific causes of these disorders, and as such, there is urgent need for innovative study approaches. The aim of the present study was to identify the genetic factors which seem to be more directly responsible for the occurrence of a cognitive and/or behavioral disorder. More specifically, through bioinformatics tools and software as well as analytical methods such as systemic data and text mining, semantic analysis, and scoring functions, we extracted the most relevant single nucleotide polymorphisms (SNPs) and genes connected to these disorders. All the extracted SNPs were filtered, annotated, classified, and evaluated in order to create the "genomic grammar" of these diseases. The identified SNPs guided the search for top suspected genetic factors, dopamine receptors D and neurotrophic factor BDNF, for which regulatory networks were built. The identification of the "genomic grammar" and underlying factors connected to cognitive and behavioral disorders can aid in the successful disease profiling and the establishment of novel pharmacological targets and provide the basis for personalized medicine, which takes into account the patient's genetic background as well as epigenetic factors.

Predictors of cognitive, behavioural and academic difficulties in NF1

The impact of the Neurofibromatosis type 1 (NF1) on cognition have been subject to much clinical investigation, but environmental modifiers of disease expression have not yet been systematically investigated. The aim of this paper is to determine the role of demographic and environmental factors such as age, sex, socioeconomic status, parental NF1 status and neurological complications on the cognitive, behavioural and academic outcomes in NF1. Participants included 206 children aged 4-18 years seen within the Manchester clinical research NF1 service. Multiple linear regression models were used to study the effect of the hypothesized predictor variables on cognitive, behavioural and academic outcomes. Relative to population norms, 80% of the NF1 sample demonstrated significantly lower scores in at least one cognitive, behavioural or academic domains. Family history of NF1 and lower SES were independently associated with poorer cognitive, behavioural and academic outcomes. Neurological problems such as epilepsy and hydrocephalus were associated with lower IQ and academic skills. Cognitive and behavioural phenotypes emerge commonly via a complex interplay between genes and environmental factors, and this is true also of a monogenic condition such as NF1. Early interventions and remedial education may be targeted to risk groups such those with familial NF1, families with lower SES and those with associated neurological comorbidities.

Look duration at the face as a developmental endophenotype: elucidating pathways to autism and ADHD

Identifying developmental endophenotypes on the pathway between genetics and behavior is critical to uncovering the mechanisms underlying neurodevelopmental conditions. In this proof-of-principle study, we explored whether early disruptions in visual attention are a unique or shared candidate endophenotype of autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). We calculated the duration of the longest look (i.e., peak look) to faces in an array-based eye-tracking task for 335 14-month-old infants with and without first-degree relatives with ASD and/or ADHD. We leveraged parent-report and genotype data available for a proportion of these infants to evaluate the relation of looking behavior to familial (n = 285) and genetic liability (using polygenic scores, n = 185) as well as ASD and ADHD-relevant temperament traits at 2 years of age (shyness and inhibitory control, respectively, n = 272) and ASD and ADHD clinical traits at 6 years of age (n = 94).

Results showed that longer peak looks at the face were associated with elevated polygenic scores for ADHD (β = 0.078, p = .023), but not ASD (β = 0.002, p = .944), and with elevated ADHD traits in mid-childhood (F(1,88) = 6.401, p = .013, $\eta _p^2$=0.068; ASD: F (1,88) = 3.218, p = .076), but not in toddlerhood (ps > 0.2). This pattern of results did not emerge when considering mean peak look duration across face and nonface stimuli. Thus, alterations in attention to faces during spontaneous visual exploration may be more consistent with a developmental endophenotype of ADHD than ASD. Our work shows that dissecting paths to neurodevelopmental conditions requires longitudinal data incorporating polygenic contribution, early neurocognitive function, and clinical phenotypic variation.

The building blocks of social competence: Contributions of the Consortium of Individual Development

Social competence refers to the ability to engage in meaningful interactions with others. It is a crucial skill potentially malleable to interventions. Nevertheless, it remains difficult to select which children, which periods in a child's life, and which underlying skills form optimal targets for interventions. Development of social competence is complex to characterize because (a) it is by nature context- dependent; (b) it is subserved by multiple relevant processes that develop at different times in a child's life; and (c) over the years multiple, possibly conflicting, ways have been coined to index a child's social competence. The current paper elaborates upon a theoretical model of social competence developed by Rose-Krasnor (Rose- Krasnor, 1997; Rose-Krasnor and Denham, 2009), and it makes concrete how underlying skills and the variety of contexts of social interaction are both relevant dimensions of social competence that might change over development. It then illustrates how the cohorts and work packages in the Consortium on Individual Development each provide empirical contributions necessary for testing this model on the development of social competence.

The building blocks of social competence: Contributions of the Consortium of Individual Development

Social competence refers to the ability to engage in meaningful interactions with others. It is a crucial skill potentially malleable to interventions. Nevertheless, it remains difficult to select which children, which periods in a child's life, and which underlying skills form optimal targets for interventions. Development of social competence is complex to characterize because (a) it is by nature context- dependent; (b) it is subserved by multiple relevant processes that develop at different times in a child's life; and (c) over the years multiple, possibly conflicting, ways have been coined to index a child's social competence. The current paper elaborates upon a theoretical model of social competence developed by Rose-Krasnor (Rose- Krasnor, 1997; Rose-Krasnor and Denham, 2009), and it makes concrete how underlying skills and the variety of contexts of social interaction are both relevant dimensions of social competence that might change over development. It then illustrates how the cohorts and work packages in the Consortium on Individual Development each provide empirical contributions necessary for testing this model on the development of social competence.

Computational modeling of interventions for developmental disorders

We evaluate the potential of connectionist models of developmental disorders to offer insights into the efficacy of interventions. Based on a range of computational simulation results, we assess factors that influence the effectiveness of interventions for reading, language, and other cognitive developmental disorders. The analysis provides a level of mechanistic detail that is generally lacking in behavioral approaches to intervention. We review an extended program of modeling work in four sections. In the first, we consider long-term outcomes and the possibility of compensated outcomes and resolution of early delays. In the second section, we address methods to remediate atypical development in a single network. In the third section, we address interventions to encourage compensation via alternative pathways. In the final section, we consider the key issue of individual differences in response to intervention. Together with advances in understanding the neural basis of developmental disorders and neural responses to training, formal computational approaches can spur theoretical progress to narrow the gap between the theory and practice of intervention.

Research domain criteria from neuroconstructivism: A developmental view on mental disorders

Neuroconstructivism can provide Research Domain Criteria (RDoC) with a developmental framework to understand mental disorders. Neuroconstructivism proposes that mental disorders are the outcome of a developmental trajectory. Based on this assumption, symptoms would reveal the system's adaptation to optimize functioning according to the system's experience of the physical and social contexts. RDoC adopts a translational research approach with the aim of detecting, curing, and preventing mental illness. More specifically this involves to: (a) identify early signs of mental disorders, (b) find the optimal patient-treatment fit, and (c) design efficient interventions to prevent the system's eventual pathological functioning. We propose that meeting RDoC's threefold objective necessarily involves predicting the system's developmental trajectory. Such endeavor requires counting with assessment tools that are sensitive to both the process of development and its different contexts; the measures provided by these tools will allow identifying the risk and protective factors that make the system vulnerable to depart from a typical developmental trajectory. Including vectors relative to time and contexts in a relevant part of the matrix will make of RDoC a truly integrative model, which considers the relationships between behavior and neural circuits throughout the developmental pathway. This article is categorized under: Psychology > Brain Function and Dysfunction Neuroscience > Clinical Neuroscience Neuroscience > Development.

Efficacy of early interventions for infants and young children with, and at risk for, autism spectrum disorders

With advances in the field's ability to identify autism spectrum disorders (ASD) at younger ages, the need for information about the evidence-base for early intervention continues to rise. This review of the ASD early intervention (EI) literature focuses on efficacy studies published within the past 15 years. The neurodevelopmental context for early intervention, timing of initiating intervention, primary intervention approaches, and predictors of treatment outcomes are discussed. The evidence indicates that young children with ASD benefit from EI, and their parents learn to implement child-responsive engagement strategies when a parent-coaching intervention is provided. Evidence supports combining parent-mediated and direct clinician-implemented intervention to maximize child developmental gains. Clinical practice recommendations are presented, based on the literature reviewed.

A Novel Way to Measure and Predict Development: A Heuristic Approach to Facilitate the Early Detection of Neurodevelopmental Disorders

PURPOSE OF REVIEW

Substantial research exists focusing on the various aspects and domains of early human development. However, there is a clear blind spot in early postnatal development when dealing with neurodevelopmental disorders, especially those that manifest themselves clinically only in late infancy or even in childhood.

RECENT FINDINGS

This early developmental period may represent an important timeframe to study these disorders but has historically received far less research attention. We believe that only a comprehensive interdisciplinary approach will enable us to detect and delineate specific parameters for specific neurodevelopmental disorders at a very early age to improve early detection/diagnosis, enable prospective studies and eventually facilitate randomised trials of early intervention. In this article, we propose a dynamic framework for characterising neurofunctional biomarkers associated with specific disorders in the development of infants and children. We have named this automated detection 'Fingerprint Model', suggesting one possible approach to accurately and early identify neurodevelopmental disorders.

A Novel Way to Measure and Predict Development: A Heuristic Approach to Facilitate the Early Detection of Neurodevelopmental Disorders

PURPOSE OF REVIEW

Substantial research exists focusing on the various aspects and domains of early human development. However, there is a clear blind spot in early postnatal development when dealing with neurodevelopmental disorders, especially those that manifest themselves clinically only in late infancy or even in childhood.

RECENT FINDINGS

This early developmental period may represent an important timeframe to study these disorders but has historically received far less research attention. We believe that only a comprehensive interdisciplinary approach will enable us to detect and delineate specific parameters for specific neurodevelopmental disorders at a very early age to improve early detection/diagnosis, enable prospective studies and eventually facilitate randomised trials of early intervention. In this article, we propose a dynamic framework for characterising neurofunctional biomarkers associated with specific disorders in the development of infants and children. We have named this automated detection 'Fingerprint Model', suggesting one possible approach to accurately and early identify neurodevelopmental disorders.

A hierarchical causal taxonomy of psychopathology across the life span

We propose a taxonomy of psychopathology based on patterns of shared causal influences identified in a review of multivariate behavior genetic studies that distinguish genetic and environmental influences that are either common to multiple dimensions of psychopathology or unique to each dimension. At the phenotypic level, first-order dimensions are defined by correlations among symptoms; correlations among first-order dimensions similarly define higher-order domains (e.g., internalizing or externalizing psychopathology). We hypothesize that the robust phenotypic correlations among first-order dimensions reflect a hierarchy of increasingly specific etiologic influences. Some nonspecific etiologic factors increase risk for all first-order dimensions of psychopathology to varying degrees through a general factor of psychopathology. Other nonspecific etiologic factors increase risk only for all first-order dimensions within a more specific higher-order domain. Furthermore, each first-order dimension has its own unique causal influences. Genetic and environmental influences common to family members tend to be nonspecific, whereas environmental influences unique to each individual are more dimension-specific. We posit that these causal influences on psychopathology are moderated by sex and developmental processes. This causal taxonomy also provides a novel framework for understanding the heterogeneity of each first-order dimension: Different persons exhibiting similar symptoms may be influenced by different combinations of etiologic influences from each of the 3 levels of the etiologic hierarchy. Furthermore, we relate the proposed causal taxonomy to transdimensional psychobiological processes, which also impact the heterogeneity of each psychopathology dimension. This causal taxonomy implies the need for changes in strategies for studying the etiology, psychobiology, prevention, and treatment of psychopathology. (PsycINFO Database Record

Brain adaptation and alternative developmental trajectories

Resilience and adaptation in the face of early genetic or environmental risk has become a major interest in child psychiatry over recent years. However, we still remain far from an understanding of how developing human brains as a whole adapt to the diffuse and widespread atypical synaptic function that may be characteristic of some common developmental disorders. The first part of this paper discusses four types of whole-brain adaptation in the face of early risk: redundancy, reorganization, niche construction, and adjustment of developmental rate. The second part of the paper applies these adaptation processes specifically to autism. We speculate that key features of autism may be the end result of processes of early brain adaptation, rather than the direct consequences of ongoing neural pathology.

Merging Policy Initiatives and Developmental Perspectives in Early Intervention

The provision of early intervention services for vulnerable children and their families is now both accepted and expected by the international community. This article considers the importance of a developmental perspective as an essential guide to early intervention service systems. Emphasized in this framework are three critical features: relationship formation, the continuity of interventions, and the comprehensiveness of interventions. Guidance to early intervention systems design with respect to structural and values principles is also discussed. Future advances in early intervention may well depend upon the merging of these perspectives to create policy initiatives to enhance early intervention systems.

Building an adaptive brain across development: targets for neurorehabilitation must begin in infancy

Much progress has been made toward behavioral and pharmacological intervention in intellectual disability, which was once thought too difficult to treat. Down syndrome (DS) research has shown rapid advances, and clinical trials are currently underway, with more on the horizon. Here, we review the literature on the emergent profile of cognitive development in DS, emphasizing that treatment approaches must consider how some "end state" impairments, such as language deficits, may develop from early alterations in neural systems beginning in infancy. Specifically, we highlight evidence suggesting that there are pre- and early postnatal alterations in brain structure and function in DS, resulting in disturbed network function across development. We stress that these early alterations are likely amplified by Alzheimer's disease (AD) progression and poor sleep. Focusing on three network hubs (prefrontal cortex, hippocampus, and cerebellum), we discuss how these regions may relate to evolving deficits in cognitive function in individuals with DS, and to their language profile in particular.

Novel paradigms to measure variability of behavior in early childhood: posture, gaze, and pupil dilation

A central challenge of investigating the underlying mechanisms of and the individual differences in young children's behavior is the measurement of the internal physiological mechanism and the involved expressive emotions. Here, we illustrate two paradigms that assess concurrent indicators of both children's social perception as well as their emotional expression. In one set of studies, children view situations while their eye movements are mapped onto a live scene. In these studies, children's internal arousal is measured via changes in their pupil dilation by using eye tracking technology. In another set of studies, we measured children's emotional expression via changes in their upper-body posture by using depth sensor imaging technology. Together, these paradigms can provide new insights into the internal mechanism and outward emotional expression involved in young children's behavior.

Idiosyncratic brain activation patterns are associated with poor social comprehension in autism

Autism spectrum disorder (ASD) features profound social deficits but neuroimaging studies have failed to find any consistent neural signature. Here we connect these two facts by showing that idiosyncratic patterns of brain activation are associated with social comprehension deficits. Human participants with ASD (N = 17) and controls (N = 20) freely watched a television situation comedy (sitcom) depicting seminaturalistic social interactions ("The Office", NBC Universal) in the scanner. Intersubject correlations in the pattern of evoked brain activation were reduced in the ASD group-but this effect was driven entirely by five ASD subjects whose idiosyncratic responses were also internally unreliable. The idiosyncrasy of these five ASD subjects was not explained by detailed neuropsychological profile, eye movements, or data quality; however, they were specifically impaired in understanding the social motivations of characters in the sitcom. Brain activation patterns in the remaining ASD subjects were indistinguishable from those of control subjects using multiple multivariate approaches. Our findings link neurofunctional abnormalities evoked by seminaturalistic stimuli with a specific impairment in social comprehension, and highlight the need to conceive of ASD as a heterogeneous classification.