A longitudinal resource for population neuroscience of school-age children and adolescents in China

During the past decade, cognitive neuroscience has been calling for population diversity to address the challenge of validity and generalizability, ushering in a new era of population neuroscience. The developing Chinese Color Nest Project (devCCNP, 2013–2022), the first ten-year stage of the lifespan CCNP (2013–2032), is a two-stages project focusing on brain-mind development. The project aims to create and share a large-scale, longitudinal and multimodal dataset of typically developing children and adolescents (ages 6.0–17.9 at enrolment) in the Chinese population. The devCCNP houses not only phenotypes measured by demographic, biophysical, psychological and behavioural, cognitive, affective, and ocular-tracking assessments but also neurotypes measured with magnetic resonance imaging (MRI) of brain morphometry, resting-state function, naturalistic viewing function and diffusion structure. This Data Descriptor introduces the first data release of devCCNP including a total of 864 visits from 479 participants. Herein, we provided details of the experimental design, sampling strategies, and technical validation of the devCCNP resource. We demonstrate and discuss the potential of a multicohort longitudinal design to depict normative brain growth curves from the perspective of developmental population neuroscience. The devCCNP resource is shared as part of the “Chinese Data-sharing Warehouse for In-vivo Imaging Brain” in the Chinese Color Nest Project (CCNP) – Lifespan Brain-Mind Development Data Community (https://ccnp.scidb.cn) at the Science Data Bank

A longitudinal resource for population neuroscience of school-age children and adolescents in China

During the past decade, cognitive neuroscience has been calling for population diversity to address the challenge of validity and generalizability, ushering in a new era of population neuroscience. The developing Chinese Color Nest Project (devCCNP, 2013–2022), the first ten-year stage of the lifespan CCNP (2013–2032), is a two-stages project focusing on brain-mind development. The project aims to create and share a large-scale, longitudinal and multimodal dataset of typically developing children and adolescents (ages 6.0–17.9 at enrolment) in the Chinese population. The devCCNP houses not only phenotypes measured by demographic, biophysical, psychological and behavioural, cognitive, affective, and ocular-tracking assessments but also neurotypes measured with magnetic resonance imaging (MRI) of brain morphometry, resting-state function, naturalistic viewing function and diffusion structure. This Data Descriptor introduces the first data release of devCCNP including a total of 864 visits from 479 participants. Herein, we provided details of the experimental design, sampling strategies, and technical validation of the devCCNP resource. We demonstrate and discuss the potential of a multicohort longitudinal design to depict normative brain growth curves from the perspective of developmental population neuroscience. The devCCNP resource is shared as part of the “Chinese Data-sharing Warehouse for In-vivo Imaging Brain” in the Chinese Color Nest Project (CCNP) – Lifespan Brain-Mind Development Data Community (https://ccnp.scidb.cn) at the Science Data Bank. © 2023, Springer Nature Limited

Six cornerstones for translational brain charts

It is of great scientific and translational promise to formulate a normative reference for the lifespan development of human brain to precisely quantify individual differences. By aggregating more than 120,000 brain imaging scans across the world, the Lifespan Brain Chart Consortium (LBCC) recently published brain charts for the human lifespan in Nature. These charts (two examples showed in Fig. 1a) have revealed previously undocumented neurodevelopmental milestones, marking a research model on team working for the neuroimaging community towards population neuroscience. The LBCC team demonstrated that after decades of advancement and accumulation in technologies, methods, and resources, we now have a tangible opportunity to achieve translational science for brain health. Accordingly, the World Health Organization has articulated the great clinical and public health relevance of lifespan brain charts in its recent position paper.</p

A longitudinal resource for population neuroscience of school-age children and adolescents in China [Elektronisk resurs]

During the past decade, cognitive neuroscience has been calling for population diversity to address the challenge of validity and generalizability, ushering in a new era of population neuroscience. The developing Chinese Color Nest Project (devCCNP, 2013–2022), the first ten-year stage of the lifespan CCNP (2013–2032), is a two-stages project focusing on brain-mind development. The project aims to create and share a large-scale, longitudinal and multimodal dataset of typically developing children and adolescents (ages 6.0–17.9 at enrolment) in the Chinese population. The devCCNP houses not only phenotypes measured by demographic, biophysical, psychological and behavioural, cognitive, affective, and ocular-tracking assessments but also neurotypes measured with magnetic resonance imaging (MRI) of brain morphometry, resting-state function, naturalistic viewing function and diffusion structure. This Data Descriptor introduces the first data release of devCCNP including a total of 864 visits from 479 participants.Herein, we provided details of the experimental design, sampling strategies, and technical validation of the devCCNP resource. We demonstrate and discuss the potential of a multicohort longitudinal design to depict normative brain growth curves from the perspective of developmental population neuroscience. The devCCNP resource is shared as part of the “Chinese Data-sharing Warehouse for In-vivo Imaging Brain” in the Chinese Color Nest Project (CCNP) – Lifespan Brain-Mind Development Data Community (https://ccnp.scidb.cn) at the Science Data Bank. © 2023, Springer Nature Limited

Cortical gene expression architecture links healthy neurodevelopment to the imaging, transcriptomics and genetics of autism and schizophrenia

Human brain organisation involves the coordinated expression of thousands of genes. For example, the first principal component (C1) of cortical transcription identifies a hierarchy from sensorimotor to association regions. Here, optimised processing of the Allen Human Brain Atlas revealed two new components of cortical gene expression architecture, C2 and C3, which are distinctively enriched for neuronal, metabolic and immune processes, specific cell-types and cytoarchitecture, and genetic variants associated with intelligence. Using additional datasets (PsychENCODE, Allen Cell Atlas, and BrainSpan), we found that C1-C3 represent generalisable transcriptional programmes that are coordinated within cells, and differentially phased during foetal and postnatal development. Autism spectrum disorder and schizophrenia were specifically associated with C1/C2 and C3, respectively, across neuroimaging, differential expression, and genome-wide association studies. Evidence converged especially in support of C3 as a normative transcriptional programme for adolescent brain development, which can lead to atypical supra-granular cortical connectivity in people at high genetic risk for schizophrenia.R.D. was supported by the Gates Cambridge Trust (OPP1144). J.S. was supported by NIMH T32MH019112-29 and K08MH120564. A.A. was funded by a grant from the Australian Research Council (ARC) under its Linkage Project scheme (LP160101592). R.A.I.B. was supported by the Autism Research Trust. K.S.W. was supported by the Wellcome Trust (215901/Z/19/Z). E.T.B. was supported by an NIHR Senior Investigator award and the Wellcome Trust collaborative award for the Neuroscience in Psychiatry Network (NSPN). A.R. was supported by the National Institute of Mental Health Intramural Research Program (NIH Annual Report Number, 1ZIAMH002949-04). P.E.V. is a Fellow of MQ: Transforming Mental Health (MQF17_24)

Cortical gene expression architecture links healthy neurodevelopment to the imaging, transcriptomics and genetics of autism and schizophrenia

Human brain organisation involves the coordinated expression of thousands of genes. For example, the first principal component (C1) of cortical transcription identifies a hierarchy from sensorimotor to association regions. Here, optimised processing of the Allen Human Brain Atlas revealed two new components of cortical gene expression architecture, C2 and C3, which are distinctively enriched for neuronal, metabolic and immune processes, specific cell-types and cytoarchitecture, and genetic variants associated with intelligence. Using additional datasets (PsychENCODE, Allen Cell Atlas, and BrainSpan), we found that C1-C3 represent generalisable transcriptional programmes that are coordinated within cells, and differentially phased during foetal and postnatal development. Autism spectrum disorder and schizophrenia were specifically associated with C1/C2 and C3, respectively, across neuroimaging, differential expression, and genome-wide association studies. Evidence converged especially in support of C3 as a normative transcriptional programme for adolescent brain development, which can lead to atypical supra-granular cortical connectivity in people at high genetic risk for schizophrenia.R.D. was supported by the Gates Cambridge Trust (OPP1144). J.S. was supported by NIMH T32MH019112-29 and K08MH120564. A.A. was funded by a grant from the Australian Research Council (ARC) under its Linkage Project scheme (LP160101592). R.A.I.B. was supported by the Autism Research Trust. K.S.W. was supported by the Wellcome Trust (215901/Z/19/Z). E.T.B. was supported by an NIHR Senior Investigator award and the Wellcome Trust collaborative award for the Neuroscience in Psychiatry Network (NSPN). A.R. was supported by the National Institute of Mental Health Intramural Research Program (NIH Annual Report Number, 1ZIAMH002949-04). P.E.V. is a Fellow of MQ: Transforming Mental Health (MQF17_24)

Atypical Brain Aging and Its Association With Working Memory Performance in Major Depressive Disorder

Background: Patients with major depressive disorder (MDD) can present with altered brain structure and deficits in cognitive function similar to those seen in aging. However, the interaction between age-related brain changes and brain development in MDD remains understudied. In a cohort of adolescents and adults with and without MDD, we assessed brain aging differences and associations through a newly developed tool that quantifies normative neurodevelopmental trajectories. Methods: A total of 304 participants with MDD and 236 control participants without depression were recruited and scanned from 3 studies under the Canadian Biomarker Integration Network for Depression. Volumetric data were used to generate brain centile scores, which were examined for 1) differences between participants with MDD and control participants; 2) differences between individuals with versus without severe childhood maltreatment; and 3) correlations with depressive symptom severity, neurocognitive assessment domains, and escitalopram treatment response. Results: Brain centiles were significantly lower in the MDD group than in the control group. Brain centile was also significantly correlated with working memory in the control group but not the MDD group. No significant associations were observed between depression severity or antidepressant treatment response and brain centiles. Likewise, childhood maltreatment history did not significantly affect brain centiles. Conclusions: Consistent with previous work on machine learning models that predict brain age, brain centile scores differed in people diagnosed with MDD, and MDD was associated with differential relationships between centile scores and working memory. The results support the notion of atypical development and aging in MDD, with implications for neurocognitive deficits associated with aging-related cognitive function

Study design features increase replicability in brain-wide association studies.

Brain-wide association studies (BWAS) are a fundamental tool in discovering brain-behaviour associations1,2. Several recent studies have shown that thousands of study participants are required for good replicability of BWAS1-3. Here we performed analyses and meta-analyses of a robust effect size index using 63 longitudinal and cross-sectional MRI studies from the Lifespan Brain Chart Consortium4 (77,695 total scans) to demonstrate that optimizing study design is critical for increasing standardized effect sizes and replicability in BWAS. A meta-analysis of brain volume associations with age indicates that BWAS with larger variability of the covariate and longitudinal studies have larger reported standardized effect size. Analysing age effects on global and regional brain measures from the UK Biobank and the Alzheimer's Disease Neuroimaging Initiative, we showed that modifying study design through sampling schemes improves standardized effect sizes and replicability. To ensure that our results are generalizable, we further evaluated the longitudinal sampling schemes on cognitive, psychopathology and demographic associations with structural and functional brain outcome measures in the Adolescent Brain and Cognitive Development dataset. We demonstrated that commonly used longitudinal models, which assume equal between-subject and within-subject changes can, counterintuitively, reduce standardized effect sizes and replicability. Explicitly modelling the between-subject and within-subject effects avoids conflating them and enables optimizing the standardized effect sizes for each separately. Together, these results provide guidance for study designs that improve the replicability of BWAS

Atypical Brain Aging and Its Association With Working Memory Performance in Major Depressive Disorder

BACKGROUND: Patients with major depressive disorder (MDD) can present with altered brain structure and deficits in cognitive function similar to aging. Yet, the interaction between age-related brain changes and brain development in MDD remains understudied. In a cohort of adolescents and adults with and without MDD, we assessed brain aging differences and associations through a newly developed tool quantifying normative neurodevelopmental trajectories. METHODS: 304 MDD participants and 236 non-depressed controls were recruited and scanned from three studies under the Canadian Biomarker Integration Network for Depression. Volumetric data were used to generate brain centile scores, which were examined for: a) differences in MDD relative to controls; b) differences in individuals with versus without severe childhood maltreatment; and c) correlations with depressive symptom severity, neurocognitive assessment domains, or escitalopram treatment response. RESULTS: Brain centiles were significantly lower in the MDD group compared to controls. It was also significantly correlated with working memory in controls, but not the MDD group. No significant associations were observed in depression severity or antidepressant treatment response with brain centiles. Likewise, childhood maltreatment history did not significantly affect brain centiles. CONCLUSIONS: Consistent with prior work on machine learning models that predict "brain age", brain centile scores differed in people diagnosed with MDD, and MDD was associated with differential relationships between centile scores and working memory. The results support the notion of atypical development and aging in MDD, with implications on neurocognitive deficits associated with aging-related cognitive function