Biology subjects

Teeuw, J.

Publications and source records attributed to Teeuw, J..

3 recordsLinked to original sources

bioRxiv2025

White matter microstructure changes across the lifespan: a meta-analysis of longitudinal diffusion MRI studies

BackgroundWhite matter in the human brain is known to play a critical role in facilitating communication between different brain regions. White matter microstructure is often quantified using fractional anisotropy (FA) derived from diffusion-weighted MRI and is often considered a key measure of neural efficiency that is positively associated with motor and cognitive functioning. While lifespan trajectories of FA have been well studied in cross-sectional designs, it remains less clear how FA changes longitudinally with age across the lifespan, and whether the rates of change are influenced by genetic variation. MethodsWe systematically reviewed the evidence of white matter changes, as measured by fractional anisotropy (FA) with diffusion magnetic resonance imaging longitudinally across the lifespan, and the genetic influences on this change. Searches were conducted in Medline, PsycInfo, and EMBASE up to August 2023 with terms related to DTI/FA and longitudinal/change. Following this, genetic-related search terms were applied to the results, and the search was broadened to include other measures of white matter change. Our systematic search resulted in 29 studies that met our criteria. In addition, 14 studies investigated genetic influences on FA change rates across the lifespan. A meta-regression using a thin-plate spline model was conducted to examine annual whole-brain FA change as a function of age. ResultsAcross childhood and adolescence, FA increased, and the rate of increase slowed into early adulthood. Between ages 20 and 35, changes in FA were not statistically significant. This was followed by a significant decline in FA between ages 36 and 50. The decreases plateaued between ages 51 and 61 and then continued at a slightly slower rate towards the upper end of the age range assessed (77 years). Average FA change per year relative to baseline assessment reached a maximum of +1.1% during development, and-0.6% per year, during ageing. Significant heritability was found for change in local but not global FA during development. During ageing, common variants in genes that have been related to increased risk for neuropsychiatric disorders (APOE, HTT, MAPT) were associated in some studies with accelerated local FA decreases over time. ConclusionsIn conclusion, there are changes in white matter microstructure within individuals across the lifespan, with increases during childhood, adolescence and early adulthood, followed by a period of relative stability during early to mid-adulthood, and subsequent gradual declines from midlife onwards. Evidence is emerging for genetic influences on white matter changes over time, shaping individual trajectories.

neuroscience↗

bioRxiv2022

Automated segmentation of fetal intracranial volume in 3D ultrasound using deep learning: identifying sex differences in prenatal brain development

The human brain undergoes major developmental changes during pregnancy. Three-dimensional (3D) ultrasound images allow for the opportunity to investigate typical prenatal brain development on a large scale. Here, we developed a convolutional neural network (CNN) model for automated segmentation of fetal intracranial volume (ICV) from 3D ultrasound, and we applied the trained model in a large independent sample (N = 9795 ultrasounds; N=1763 participants) from the YOUth Baby and Child cohort measured at 20- and 30-week of gestational age to investigate sex differences in fetal ICV and ICV growth. 168 3D ultrasound images with ICV annotations were included to develop a 3D CNN model for automated fetal ICV segmentation. A data augmentation strategy provided physical variation and additional data to train the network. K-fold cross-validation and Bayesian optimization were used for network selection and the ensemble-based system combined multiple networks to form the final ensemble network. The final ensemble network produced consistent and high-quality segmentations of ICV. Our trained model successfully predicted ICV and ICV growth in a large independent longitudinal data set. Boys had significantly larger ICV at 20- (B=2.83; p=1.4e-13) and 30-weeks of pregnancy (B=12.01; p=2.0e-28), and more pronounced ICV growth than girls (t=-4.395; p=1.3e-5). Our approach provides us with the opportunity to investigate fetal brain development on a much larger scale and to answer fundamental questions related to prenatal brain development.

neuroscience↗

bioRxiv2020

Dynamics of Brain Structure and its Genetic Architecture over the Lifespan

Human brain structure changes throughout our lives. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental, and neurodegenerative diseases. Here, we identified common genetic variants that affect rates of brain growth or atrophy, in the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal MRI data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene-set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and ageing.

genetics↗