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Kristine B Walhovd,
Anders M Fjell,
Timothy T Brown,
Joshua M Kuperman,
Yoonho Chung,
Donald J Hagler,
J Cooper Roddey,
Matthew Erhart,
Connor McCabe,
Natacha Akshoomoff, [......],
B J Casey,
Linda Chang,
Thomas M Ernst,
Jean Frazier, Jeffrey R Gruen,
Walter E Kaufmann,
Sarah S Murray,
Peter van Zijl,
Stewart Mostofsky,
Anders M Dale
[show abstract]
[hide abstract]
ABSTRACT: It is now recognized that a number of cognitive, behavioral, and mental health outcomes across the lifespan can be traced to fetal development. Although the direct mediation is unknown, the substantial variance in fetal growth, most commonly indexed by birth weight, may affect lifespan brain development. We investigated effects of normal variance in birth weight on MRI-derived measures of brain development in 628 healthy children, adolescents, and young adults in the large-scale multicenter Pediatric Imaging, Neurocognition, and Genetics study. This heterogeneous sample was recruited through geographically dispersed sites in the United States. The influence of birth weight on cortical thickness, surface area, and striatal and total brain volumes was investigated, controlling for variance in age, sex, household income, and genetic ancestry factors. Birth weight was found to exert robust positive effects on regional cortical surface area in multiple regions as well as total brain and caudate volumes. These effects were continuous across birth weight ranges and ages and were not confined to subsets of the sample. The findings show that (i) aspects of later child and adolescent brain development are influenced at birth and (ii) relatively small differences in birth weight across groups and conditions typically compared in neuropsychiatric research (e.g., Attention Deficit Hyperactivity Disorder, schizophrenia, and personality disorders) may influence group differences observed in brain parameters of interest at a later stage in life. These findings should serve to increase our attention to early influences.
Proceedings of the National Academy of Sciences 11/2012; · 9.68 Impact Factor
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Anders M Fjell,
Kristine Beate Walhovd,
Timothy T Brown,
Joshua M Kuperman,
Yoonho Chung,
Donald J Hagler,
Vijay Venkatraman,
J Cooper Roddey,
Matthew Erhart,
Connor McCabe, [......], Jeffrey R Gruen,
Walter E Kaufmann,
Tal Kenet,
Jean Frazier,
Sarah S Murray,
Elizabeth R Sowell,
Peter van Zijl,
Stewart Mostofsky,
Terry L Jernigan,
Anders M Dale
[show abstract]
[hide abstract]
ABSTRACT: Self-regulation refers to the ability to control behavior, cognition, and emotions, and self-regulation failure is related to a range of neuropsychiatric problems. It is poorly understood how structural maturation of the brain brings about the gradual improvement in self-regulation during childhood. In a large-scale multicenter effort, 735 children (4-21 y) underwent structural MRI for quantification of cortical thickness and surface area and diffusion tensor imaging for quantification of the quality of major fiber connections. Brain development was related to a standardized measure of cognitive control (the flanker task from the National Institutes of Health Toolbox), a critical component of self-regulation. Ability to inhibit responses and impose cognitive control increased rapidly during preteen years. Surface area of the anterior cingulate cortex accounted for a significant proportion of the variance in cognitive performance. This finding is intriguing, because characteristics of the anterior cingulum are shown to be related to impulse, attention, and executive problems in neurodevelopmental disorders, indicating a neural foundation for self-regulation abilities along a continuum from normality to pathology. The relationship was strongest in the younger children. Properties of large-fiber connections added to the picture by explaining additional variance in cognitive control. Although cognitive control was related to surface area of the anterior cingulate independently of basic processes of mental speed, the relationship between white matter quality and cognitive control could be fully accounted for by speed. The results underscore the need for integration of different aspects of brain maturation to understand the foundations of cognitive development.
Proceedings of the National Academy of Sciences 11/2012; · 9.68 Impact Factor
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Timothy T Brown,
Joshua M Kuperman,
Yoonho Chung,
Matthew Erhart,
Connor McCabe,
Donald J Hagler,
Vijay K Venkatraman,
Natacha Akshoomoff,
David G Amaral,
Cinnamon S Bloss, [......],
Thomas M Ernst,
Jean A Frazier, Jeffrey R Gruen,
Walter E Kaufmann,
Tal Kenet,
David N Kennedy,
Sarah S Murray,
Elizabeth R Sowell,
Terry L Jernigan,
Anders M Dale
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Timothy T Brown,
Joshua M Kuperman,
Yoonho Chung,
Matthew Erhart,
Connor McCabe,
Donald J Hagler,
Vijay K Venkatraman,
Natacha Akshoomoff,
David G Amaral,
Cinnamon S Bloss, [......],
Thomas M Ernst,
Jean A Frazier, Jeffrey R Gruen,
Walter E Kaufmann,
Tal Kenet,
David N Kennedy,
Sarah S Murray,
Elizabeth R Sowell,
Terry L Jernigan,
Anders M Dale
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Timothy T Brown,
Joshua M Kuperman,
Yoonho Chung,
Matthew Erhart,
Connor McCabe,
Donald J Hagler,
Vijay K Venkatraman,
Natacha Akshoomoff,
David G Amaral,
Cinnamon S Bloss, [......],
Thomas M Ernst,
Jean A Frazier, Jeffrey R Gruen,
Walter E Kaufmann,
Tal Kenet,
David N Kennedy,
Sarah S Murray,
Elizabeth R Sowell,
Terry L Jernigan,
Anders M Dale
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Timothy T Brown,
Joshua M Kuperman,
Yoonho Chung,
Matthew Erhart,
Connor McCabe,
Donald J Hagler,
Vijay K Venkatraman,
Natacha Akshoomoff,
David G Amaral,
Cinnamon S Bloss, [......],
Thomas M Ernst,
Jean A Frazier, Jeffrey R Gruen,
Walter E Kaufmann,
Tal Kenet,
David N Kennedy,
Sarah S Murray,
Elizabeth R Sowell,
Terry L Jernigan,
Anders M Dale
[show abstract]
[hide abstract]
ABSTRACT: Structural MRI allows unparalleled in vivo study of the anatomy of the developing human brain. For more than two decades [1], MRI research has revealed many new aspects of this multifaceted maturation process, significantly augmenting scientific knowledge gathered from postmortem studies. Postnatal brain development is notably protracted and involves considerable changes in cerebral cortical [2-4], subcortical [5], and cerebellar [6, 7] structures, as well as significant architectural changes in white matter fiber tracts [8-11] (see [12]). Although much work has described isolated features of neuroanatomical development, it remains a critical challenge to characterize the multidimensional nature of brain anatomy, capturing different phases of development among individuals. Capitalizing on key advances in multisite, multimodal MRI, and using cross-validated nonlinear modeling, we demonstrate that developmental brain phase can be assessed with much greater precision than has been possible using other biological measures, accounting for more than 92% of the variance in age. Further, our composite metric of morphology, diffusivity, and signal intensity shows that the average difference in phase among children of the same age is only about 1 year, revealing for the first time a latent phenotype in the human brain for which maturation timing is tightly controlled. VIDEO ABSTRACT:
Current biology: CB 08/2012; 22(18):1693-8. · 10.99 Impact Factor
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Trygve E Bakken,
J Cooper Roddey,
Srdjan Djurovic,
Natacha Akshoomoff,
David G Amaral,
Cinnamon S Bloss,
B J Casey,
Linda Chang,
Thomas M Ernst, Jeffrey R Gruen, [......],
Bruce Rosen,
Nitzah Gebhard,
Holly Manigan,
Jean Frazier,
David Kennedy,
Lauren Yakutis,
Michael Hill,
Jeffrey Gruen,
Joan Bosson-Heenan,
Heatherly Carlson
[show abstract]
[hide abstract]
ABSTRACT: Visual cortical surface area varies two- to threefold between human individuals, is highly heritable, and has been correlated with visual acuity and visual perception. However, it is still largely unknown what specific genetic and environmental factors contribute to normal variation in the area of visual cortex. To identify SNPs associated with the proportional surface area of visual cortex, we performed a genome-wide association study followed by replication in two independent cohorts. We identified one SNP (rs6116869) that replicated in both cohorts and had genome-wide significant association (P(combined) = 3.2 × 10(-8)). Furthermore, a metaanalysis of imputed SNPs in this genomic region identified a more significantly associated SNP (rs238295; P = 6.5 × 10(-9)) that was in strong linkage disequilibrium with rs6116869. These SNPs are located within 4 kb of the 5' UTR of GPCPD1, glycerophosphocholine phosphodiesterase GDE1 homolog (Saccharomyces cerevisiae), which in humans, is more highly expressed in occipital cortex compared with the remainder of cortex than 99.9% of genes genome-wide. Based on these findings, we conclude that this common genetic variation contributes to the proportional area of human visual cortex. We suggest that identifying genes that contribute to normal cortical architecture provides a first step to understanding genetic mechanisms that underlie visual perception.
Proceedings of the National Academy of Sciences 03/2012; 109(10):3985-90. · 9.68 Impact Factor
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Trygve E. Bakken,
J. Cooper Roddey,
Srdjan Djurovic,
Natacha Akshoomoff,
David G. Amaral,
Cinnamon S. Bloss,
B. J. Casey,
Linda Chang,
Thomas M. Ernst, Jeffrey R. Gruen, [......],
Elizabeth R. Sowell,
Lars M. Rimol,
Morten Mattingsdal,
Ingrid Melle,
Ingrid Agartz,
Ole A. Andreassen,
Nicholas J. Schork,
Anders M. Dale,
for the Alzheimer's Disease Neuroimaging Initiative,
Pediatric Imaging, Neurocognition, and Genetics Study
[show abstract]
[hide abstract]
ABSTRACT: Visual cortical surface area varies two- to threefold between human individuals, is highly heritable, and has been correlated
with visual acuity and visual perception. However, it is still largely unknown what specific genetic and environmental factors
contribute to normal variation in the area of visual cortex. To identify SNPs associated with the proportional surface area
of visual cortex, we performed a genome-wide association study followed by replication in two independent cohorts. We identified
one SNP (rs6116869) that replicated in both cohorts and had genome-wide significant association (Pcombined = 3.2 × 10−8). Furthermore, a metaanalysis of imputed SNPs in this genomic region identified a more significantly associated SNP (rs238295;
P = 6.5 × 10−9) that was in strong linkage disequilibrium with rs6116869. These SNPs are located within 4 kb of the 5′ UTR of GPCPD1, glycerophosphocholine phosphodiesterase GDE1 homolog (Saccharomyces cerevisiae), which in humans, is more highly expressed in occipital cortex compared with the remainder of cortex than 99.9% of genes
genome-wide. Based on these findings, we conclude that this common genetic variation contributes to the proportional area
of human visual cortex. We suggest that identifying genes that contribute to normal cortical architecture provides a first
step to understanding genetic mechanisms that underlie visual perception.
Proceedings of the National Academy of Sciences · 9.68 Impact Factor
