Ann‐Marie G. de Lange

The paper examines how different types of early-life adversity relate to brain age gaps in children, finding some types are linked to younger-looking brains and others to older-looking brains.

The paper evaluates age-related changes in brain asymmetry using MRI data from 48,040 UK Biobank participants and introduces hemispheric brain age as a marker of asymmetry.

The paper analyzes white matter aging using diffusion MRI data from UK Biobank, finding that fornix microstructure is central to brain age prediction.

The paper estimates brain age gap (BAG) using neural networks and identifies eight genomic regions associated with BAG, finding causal relationships with Alzheimer's and bipolar disorder but not Parkinson's, depression, or schizophrenia.

This study evaluates performance metrics in brain-age prediction across datasets, showing variability based on age range, sample size, and age-bias correction.

This study conducts a GWAS on MRI-derived body composition measures, identifying genetic loci and genes associated with body composition and cardiometabolic diseases, with liver fat showing strong genetic associations.

The paper introduces YTTRIUM, a QC method for diffusion MRI data, showing it improves brain age prediction accuracy in UK Biobank data.

The paper links the number of previous childbirths to white matter brain age in midlife and older women using UK Biobank data.

This study uses advanced diffusion models and brain-age prediction to analyze white matter microstructure changes across adult lifespan, finding that advanced models provide sensitive measures of age-related changes.

This study examines how sex-hormone exposure, pregnancies, and genetic risk for Alzheimer's disease influence brain aging in women using UK Biobank data.

The paper predicts brain age using multimodal MRI data from the Whitehall II cohort and links brain aging to cardiovascular risk factors.

This study uses diffusion tensor imaging and machine learning to predict brain age in schizophrenia and bipolar disorder patients, finding age overestimation in both groups compared to controls.

This study links a history of childbirths to region-specific brain aging patterns in middle and older-aged women using brain-age prediction methods.

The paper uses neuroimaging and machine learning to show that more childbirths are associated with a younger-looking brain in women, independent of genetics.

The paper examines the relationship between sleep problems and amyloid deposition in cortical regions with high HOMER1 expression in older adults, finding a stronger link in younger participants and regions with high HOMER1 expression.