Biology subjects

Jernigan, T.

Publications and source records attributed to Jernigan, T..

4 recordsLinked to original sources

bioRxiv2025

Age associations with cortical and subcortical brain structure in adolescents age 9-17

IntroductionAdolescence is a pivotal period in brain structural development and maturation. However, investigation of cortical and subcortical brain changes during this time have been limited by small sample size and have generally examined the brain at the level of predetermined regions of interest. The recently developed Fast Efficient Mixed-Effects Algorithm (FEMA) allows for increased computational speed using mixed-effects models applied at the voxel or vertex level, as well as across multiple regions of interest. MethodsWe extended the existing FEMA framework to represent predictors using natural spline basis functions, enabling us to model nonlinear trajectories of brain structure as a function of age. We then applied this model to the The Adolescent Brain Cognitive DevelopmentSM Study (22,651 observations from 10,521 unique subjects aged 9.00-17.77) to study the age-related trajectories of tabulated cortical and subcortical volumes, vertexwise cortical thickness and surface area, and voxelwise volume assessed using the Jacobian. Models are reported separately in males and females. ResultsGlobal volume variables, including total subcortical gray matter volume, peaked near 13 years in females and 15 years in males. Vertexwise cortical surface area followed an inverted U-shaped curve, whereas vertexwise cortical thickness followed a monotonic decrease during the age range studied. Voxelwise imaging analysis revealed regional differences in age trajectories at the subregional level. DiscussionThe results of this work replicate and extend prior findings related to adolescent brain development, and illustrate distinct spatiotemporal patterns of structural changes in subcortical regions. The updated FEMA framework is publicly available for use in similar large datasets.

neuroscience↗

bioRxiv2021

A Comprehensive Overview of the Physical Health of the Adolescent Brain Cognitive Development Study (ABCD) Cohort at Baseline

Physical health in childhood is crucial for neurobiological as well as overall development, and can shape long-term outcomes into adulthood. The landmark, longitudinal Adolescent Brain Cognitive Development StudySM (ABCD study(R)), was designed to investigate brain development and health in almost 12,000 youth who were recruited when they were 9-10 years old and will be followed through adolescence and early adulthood. The overall goal of this paper is to provide descriptive analyses of physical health measures in the ABCD study at baseline, including but not limited to sleep, physical activity and sports involvement, and body mass index, and how these measures vary across demographic groups. This paper outlines how the physical health of the ABCD sample corresponds with that of the US population and highlights important avenues for health disparity research. This manuscript will provide important information for ABCD users and help guide analyses investigating physical health as it pertains to adolescent and young adult development.

developmental biology↗

bioRxiv2021

Generalization of Cortical Multivariate Genome-Wide Associations Within and Across Samples

Genome-Wide Association studies have typically been limited to single phenotypes, given that high dimensional phenotypes incur a large multiple comparisons burden: ~1 million tests across the genome times the number of phenotypes. Recent work demonstrates that a Multivariate Omnibus Statistic Test (MOSTest) is well powered to discover genomic effects distributed across multiple phenotypes. Applied to cortical brain MRI morphology measures, MOSTest has resulted in a drastic improvement in power to discover loci when compared to established approaches (min-P). One question that arises is how well these discovered loci replicate in independent data. Here we perform 10 times cross validation within 35,644 individuals from UK Biobank for imaging measures of cortical area, thickness and sulcal depth (>1,000 dimensionality for each). By deploying a replication method that aggregates discovered effects distributed across multiple phenotypes, termed PolyVertex Score (PVS), we demonstrate a higher replication yield and comparable replication rate of discovered loci for MOSTest (# replicated loci: 348-845, replication rate: 94-95%) in independent data when compared with the established min-P approach (# replicated loci: 31-68, replication rate: 65-80%). An out-of-sample replication of discovered loci was conducted with a sample of 8,336 individuals from the Adolescent Brain Cognitive Development(R) (ABCD) study, who are on average 50 years younger than UK Biobank individuals. We observe a higher replication yield and comparable replication rate of MOSTest compared to min-P. This finding underscores the importance of using well-powered multivariate techniques for both discovery and replication of high dimensional phenotypes in Genome-Wide Association studies.

genomics↗

bioRxiv2018

Genetics of brain age suggest an overlap with common brain disorders

Numerous genetic and environmental factors contribute to psychiatric disorders and other brain disorders. Common risk factors likely converge on biological pathways regulating the optimization of brain structure and function across the lifespan. Here, using structural magnetic resonance imaging and machine learning, we estimated the gap between brain age and chronological age in 36,891 individuals aged 3 to 96 years, including individuals with different brain disorders. We show that several disorders are associated with accentuated brain aging, with strongest effects in schizophrenia, multiple sclerosis and dementia, and document differential regional patterns of brain age gaps between disorders. In 16,269 healthy adult individuals, we show that brain age gap is heritable with a polygenic architecture overlapping those observed in common brain disorders. Our results identify brain age gap as a genetically modulated trait that offers a window into shared and distinct mechanisms in different brain disorders.

neuroscience↗