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Linking the developing brain with individual differences in clinical and demographic traits is challenging due to the substantial interindividual heterogeneity of brain anatomy and organization. Here we employ an integrative approach that parses individual differences in both cortical thickness and common genetic variants, and assess their effects on a wide set of childhood traits. The approach uses a linear mixed model framework to obtain the unique effects of each type of similarity, as well as their covariance. We employ this approach in a sample of 7760 unrelated children in the ABCD cohort baseline sample (mean age 9.9, 46.8% female). In general, associations between cortical thickness similarity and traits were limited to anthropometrics such as height, weight, and birth weight, as well as a marker of neighborhood socioeconomic conditions. Common genetic variants explained significant proportions of variance across nearly all included outcomes, although estimates were somewhat lower than previous reports. No significant covariance of the effects of genetic and cortical thickness similarity was found. The present findings highlight the connection between anthropometrics as well as neighborhood socioeconomic conditions and the developing brain, which appear to be independent from individual differences in common genetic variants in this population-based sample., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The temporal characteristics of adolescent neurodevelopment are shaped by a complex interplay of genetic, biological, and environmental factors. Using a large longitudinal dataset of children aged 9-13 from the Adolescent Brain Cognitive Development (ABCD) study we tested the associations between pubertal status and brain maturation. Brain maturation was assessed using brain age prediction based on convolutional neural networks and minimally processed T1-weighted structural MRI data. Brain age prediction provided highly accurate and reliable estimates of individual age, with an overall mean absolute error of 0.7 and 1.4 years at the two timepoints respectively, and an intraclass correlation of 0.65. Linear mixed effects (LME) models accounting for age and sex showed that on average, a one unit increase in pubertal maturational level was associated with a 2.22 months higher brain age across time points (β = 0.10, p < .001). Moreover, annualized change in pubertal development was weakly related to the rate of change in brain age (β = .047, p = 0.04). These results demonstrate a link between sexual development and brain maturation in early adolescence, and provides a basis for further investigations of the complex sociobiological impacts of puberty on life outcomes., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Zebrafish display widespread and pronounced adult neurogenesis, which is fundamental for their regeneration capability after central nervous system injury. However, the cellular identity and the biological properties of adult newborn neurons are elusive for most brain areas. Here, we have used short-term lineage tracing of radial glia progeny to prospectively isolate newborn neurons from the her4.1 + radial glia lineage in the homeostatic adult forebrain. Transcriptome analysis of radial glia, newborn neurons and mature neurons using single cell sequencing identified distinct transcriptional profiles, including novel markers for each population. Specifically, we detected two separate newborn neuron types, which showed diversity of cell fate commitment and location. Further analyses showed that these cell types are homologous to neurogenic cells in the mammalian brain, identified neurogenic commitment in proliferating radial glia and indicated that glutamatergic projection neurons are generated in the adult zebrafish telencephalon. Thus, we prospectively isolated adult newborn neurons from the adult zebrafish forebrain, identified markers for newborn and mature neurons in the adult brain, and revealed intrinsic heterogeneity among adult newborn neurons and their homology with mammalian adult neurogenic cell types., Competing Interests: Competing interestsThe authors declare no competing or financial interests., (© 2020. Published by The Company of Biologists Ltd.)

The neural stem cell (NSC) reservoir can be harnessed for stem cell-based regenerative therapies. Zebrafish remarkably regenerate their brain by inducing NSC plasticity in a Amyloid-β-42 (Aβ42)-induced experimental Alzheimer's disease (AD) model. Interleukin-4 (IL-4) is also critical for AD-induced NSC proliferation. However, the mechanisms of this response have remained unknown. Using single-cell transcriptomics in the adult zebrafish brain, we identify distinct subtypes of NSCs and neurons and differentially regulated pathways and their gene ontologies and investigate how cell-cell communication is altered through ligand-receptor pairs in AD conditions. Our results propose the existence of heterogeneous and spatially organized stem cell populations that react distinctly to amyloid toxicity. This resource article provides an extensive database for the molecular basis of NSC plasticity in the AD model of the adult zebrafish brain. Further analyses of stem cell heterogeneity and neuro-regenerative ability at single-cell resolution could yield drug targets for mobilizing NSCs for endogenous neuro-regeneration in humans., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Human brains are prone to neurodegeneration, given that endogenous neural stem/progenitor cells (NSPCs) fail to support neurogenesis. To investigate the molecular programs potentially mediating neurodegeneration-induced NSPC plasticity in regenerating organisms, we generated an Amyloid-β42 (Aβ42)-dependent neurotoxic model in adult zebrafish brain through cerebroventricular microinjection of cell-penetrating Aβ42 derivatives. Aβ42 deposits in neurons and causes phenotypes reminiscent of amyloid pathophysiology: apoptosis, microglial activation, synaptic degeneration, and learning deficits. Aβ42 also induces NSPC proliferation and enhanced neurogenesis. Interleukin-4 (IL4) is activated primarily in neurons and microglia/macrophages in response to Aβ42 and is sufficient to increase NSPC proliferation and neurogenesis via STAT6 phosphorylation through the IL4 receptor in NSPCs. Our results reveal a crosstalk between neurons and immune cells mediated by IL4/STAT6 signaling, which induces NSPC plasticity in zebrafish brains., (Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.)

Transcriptome analysis of somatic stem cells and their progeny is fundamental to identify new factors controlling proliferation versus differentiation during tissue formation. Here, we generated a combinatorial, fluorescent reporter mouse line to isolate proliferating neural stem cells, differentiating progenitors and newborn neurons that coexist as intermingled cell populations during brain development. Transcriptome sequencing revealed numerous novel long non-coding (lnc)RNAs and uncharacterized protein-coding transcripts identifying the signature of neurogenic commitment. Importantly, most lncRNAs overlapped neurogenic genes and shared with them a nearly identical expression pattern suggesting that lncRNAs control corticogenesis by tuning the expression of nearby cell fate determinants. We assessed the power of our approach by manipulating lncRNAs and protein-coding transcripts with no function in corticogenesis reported to date. This led to several evident phenotypes in neurogenic commitment and neuronal survival, indicating that our study provides a remarkably high number of uncharacterized transcripts with hitherto unsuspected roles in brain development. Finally, we focussed on one lncRNA, Miat, whose manipulation was found to trigger pleiotropic effects on brain development and aberrant splicing of Wnt7b. Hence, our study suggests that lncRNA-mediated alternative splicing of cell fate determinants controls stem-cell commitment during neurogenesis.

Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

The interplay between functional brain network maturation and psychopathology during development remains elusive. To establish the structure of psychopathology and its neurobiological mechanisms, mapping of both shared and unique functional connectivity patterns across developmental clinical populations is needed. We investigated shared associations between resting-state functional connectivity and psychopathology in children and adolescents aged 5–21 (n = 1689). Specifically, we used partial least squares (PLS) to identify latent variables (LV) between connectivity and both symptom scores and diagnostic information. We also investigated associations between connectivity and each diagnosis specifically, controlling for other diagnosis categories. PLS identified five significant LVs between connectivity and symptoms, mapping onto the psychopathology hierarchy. The first LV resembled a general psychopathology factor, followed by dimensions of internalising- externalising, neurodevelopment, somatic complaints, and thought problems. Another PLS with diagnostic data revealed one significant LV, resembling a cross-diagnostic case-control pattern. The diagnosis-specific PLS identified a unique connectivity pattern for autism spectrum disorder (ASD). All LVs were associated with distinct patterns of functional connectivity. These dimensions largely replicated in an independent sample (n = 420) from the same dataset, as well as to an independent cohort (n = 3504). This suggests that covariance in developmental functional brain networks supports transdiagnostic dimensions of psychopathology. • Patterns linking psychopathology and resting-state functional connectivity in youth. • First study testing both diagnoses and symptoms in a developmental clinical sample. • Symptom-based patterns resembled the psychopathology hierarchy. • Diagnosis-based patterns were cross-diagnostic and autism-specific. [ABSTRACT FROM AUTHOR]

Abnormalities in brain structure are shared across diagnostic categories. Given the high rate of comorbidity, the interplay of relevant behavioural factors may also cross these classic boundaries. We aimed to detect brain-based dimensions of behavioural factors using canonical correlation and independent component analysis in a clinical youth sample (n = 1732, 64 % male, age: 5–21 years). We identified two correlated patterns of brain structure and behavioural factors. The first mode reflected physical and cognitive maturation (r = 0.92, p =.005). The second mode reflected lower cognitive ability, poorer social skills, and psychological difficulties (r = 0.92, p =.006). Elevated scores on the second mode were a common feature across all diagnostic boundaries and linked to the number of comorbid diagnoses independently of age. Critically, this brain pattern predicted normative cognitive deviations in an independent population-based sample (n = 1253, 54 % female, age: 8–21 years), supporting the generalisability and external validity of the reported brain-behaviour relationships. These results reveal dimensions of brain-behaviour associations across diagnostic boundaries, highlighting potent disorder-general patterns as the most prominent. In addition to providing biologically informed patterns of relevant behavioural factors for mental illness, this contributes to a growing body of evidence in favour of transdiagnostic approaches to prevention and intervention. • Two modes of brain-behaviour associations identified in a clinical sample of youth. • First mode related to maturation, second mode to social and cognitive impairment. • Patterns were cross-diagnostic and scaling with number of comorbidities. • Patterns were generalisable to population-based sample. [ABSTRACT FROM AUTHOR]