The development of sentence-interpretation strategies in monolingual German-learning children with and without specific language impairment

Previous research on sentence comprehension conducted with German-learning children has concentrated on the role of case marking and word order in typically developing children. This paper compares, the performance of German-learning children with language impairment (age 4-6 years) and without language impairment (aged 2-6, 8-9 years) in two experiments that systematically vary the cues animacy, case marking; word-order, and subject-verb agreement. The two experiments differ with regard to the choice of case marking: in the first it is distinct but in the second it is neutralized. The theoretical framework is the competition model developed by Bates and Mac Whinney and their collaborators, a variant of the parallel distributed processing models. It is hypothesized that children of either population first appreciate the cue animacy that can be processed locally, that is, "on the spot," before they turn to more distributed cues leading ultimately up to subject-verb agreement, which presupposes the comparison of various constituents before an interpretation can be established. Thus agreement is more "costly" in processing than animacy or the (more) local cue initial NP. In experiment I with unambiguous case markers it is shown that the typically developing children proceed from animacy to the nominative (predominantly in coalition with the initial NP) to agreement, while in the second experiment with ambiguous case markers these children turn from animacy to the initial NP and then to agreement. The impaired children also progress from local to distributed cues. Yet, in contrast to the control group, they do not acknowledge the nominative in coalition with the initial NP in the first experiment but only in support of agreement. However, although they do not seem to appreciate distinct case markers to any large extent in the first experiment, they are irritated if such distinctions are lacking: in experiment II all impaired children turn to. animacy (some in coalition with the initial NP and/or particular word orders). In the discussion, the relationship between short-term memory and processing as well as the relationship between production and comprehension of case markers and agreement are addressed. Further research is needed to explore in more detail "cue costs" in sentence comprehension

Longitudinal associations of DNA methylation and sleep in children : a meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Sleep is important for healthy functioning in children. Numerous genetic and environmental factors, from conception onwards, may influence this phenotype. Epigenetic mechanisms such as DNA methylation have been proposed to underlie variation in sleep or may be an early-life marker of sleep disturbances. We examined if DNA methylation at birth or in school age is associated with parent-reported and actigraphy-estimated sleep outcomes in children. Methods: We meta-analysed epigenome-wide association study results. DNA methylation was measured from cord blood at birth in 11 cohorts and from peripheral blood in children (4–13 years) in 8 cohorts. Outcomes included parent-reported sleep duration, sleep initiation and fragmentation problems, and actigraphy-estimated sleep duration, sleep onset latency and wake-after-sleep-onset duration. Results: We found no associations between DNA methylation at birth and parent-reported sleep duration (n = 3658), initiation problems (n = 2504), or fragmentation (n = 1681) (p values above cut-off 4.0 × 10–8). Lower methylation at cg24815001 and cg02753354 at birth was associated with longer actigraphy-estimated sleep duration (p = 3.31 × 10–8, n = 577) and sleep onset latency (p = 8.8 × 10–9, n = 580), respectively. DNA methylation in childhood was not cross-sectionally associated with any sleep outcomes (n = 716–2539). Conclusion: DNA methylation, at birth or in childhood, was not associated with parent-reported sleep. Associations observed with objectively measured sleep outcomes could be studied further if additional data sets become available.Peer reviewe

The LifeCycle Project-EU Child Cohort Network : a federated analysis infrastructure and harmonized data of more than 250,000 children and parents

Early life is an important window of opportunity to improve health across the full lifecycle. An accumulating body of evidence suggests that exposure to adverse stressors during early life leads to developmental adaptations, which subsequently affect disease risk in later life. Also, geographical, socio-economic, and ethnic differences are related to health inequalities from early life onwards. To address these important public health challenges, many European pregnancy and childhood cohorts have been established over the last 30 years. The enormous wealth of data of these cohorts has led to important new biological insights and important impact for health from early life onwards. The impact of these cohorts and their data could be further increased by combining data from different cohorts. Combining data will lead to the possibility of identifying smaller effect estimates, and the opportunity to better identify risk groups and risk factors leading to disease across the lifecycle across countries. Also, it enables research on better causal understanding and modelling of life course health trajectories. The EU Child Cohort Network, established by the Horizon2020-funded LifeCycle Project, brings together nineteen pregnancy and childhood cohorts, together including more than 250,000 children and their parents. A large set of variables has been harmonised and standardized across these cohorts. The harmonized data are kept within each institution and can be accessed by external researchers through a shared federated data analysis platform using the R-based platform DataSHIELD, which takes relevant national and international data regulations into account. The EU Child Cohort Network has an open character. All protocols for data harmonization and setting up the data analysis platform are available online. The EU Child Cohort Network creates great opportunities for researchers to use data from different cohorts, during and beyond the LifeCycle Project duration. It also provides a novel model for collaborative research in large research infrastructures with individual-level data. The LifeCycle Project will translate results from research using the EU Child Cohort Network into recommendations for targeted prevention strategies to improve health trajectories for current and future generations by optimizing their earliest phases of life.Peer reviewe

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders