Biology subjects

Baltramonaityte, V.

Publications and source records attributed to Baltramonaityte, V..

3 recordsLinked to original sources

bioRxiv2026

Epigenetic and brain age across development: Performance and associations in the MIND consortium

Understanding how biological age measures perform across development lays the groundwork for investigations into lifespan trajectories of healthy aging. We provide the most comprehensive assessment of epigenetic and brain age models across development (birth to 24 years; [≤]20,917 observations across 15 cohorts), evaluating how these models associate with chronological age and with each other, and how these associations change across development. Chronological age-prediction accuracy of epigenetic and brain age models was modest and varied substantially. Accuracy improved with age and stabilized by middle childhood. Few brain and fewer epigenetic clocks performed stably and well across all developmental stages. Performance was better when age range and tissue corresponded between training and testing data. Associations between epigenetic-brain age residuals were small, and changed little across development, tissues or clock generation. Given this developmentally dynamic system of epigenetic-brain age performances and associations, we give key recommendations to improve developmental research in this field.

neuroscience↗

bioRxiv2025

Altered Frontoparietal, Temporal and Sensorimotor Structure-Function Coupling and Its Genetic Underpinnings in Bipolar Disorder

BackgroundStructure-function coupling quantifies how strongly structural connectivity supports functional communication across brain regions. Investigating structure-function coupling in bipolar disorder, a condition marked by dysconnectivity, may elucidate underlying neural mechanisms. We examined regional structure-function coupling in bipolar disorder and its genetic underpinnings to characterize network-level disruptions. MethodsRegional structure-function coupling was estimated in UK Biobank participants using edge-wise regression between measures of structural connectivity and functional connectivity. Bipolar disorder (n=163) and controls (n=326) were age and sex-matched and compared using general linear models. To explore the genetic basis of these structure-function coupling alterations, genome-wide association studies (GWAS) were conducted in an independent UK Biobank sample (n=38,190) for regions showing significant group differences. ResultsStructure-function coupling demonstrated a unimodal-to-transmodal gradient with highest coupling evident in visual regions (R2=0.29) and lowest in the insula (R2=0.03). The Bipolar disorder group showed higher structure-function coupling in the temporal pole and superior frontal gyrus ({beta}=0.269; {beta}=0.211) and lower coupling in the supramarginal, precentral, and postcentral gyri and the frontal pole ({beta}=-0.206 to -0.275). GWAS identified seven significant loci, with mapped genes (e.g., KAT6B, INPP5A, PLCE1) involved in neuronal development and cellular signaling. ConclusionBipolar disorder showed altered structure-function coupling across regions implicating multiple networks. These alterations suggest stronger structure-function alignment in limbic and attention networks and weaker alignment in sensorimotor, executive, frontoparietal, and salience regions relative to controls, potentially disrupting flexible polysynaptic communication. Altered coupling may relate to genetic variation affecting neurodevelopment, neuronal signaling, and synaptic plasticity. Together, these findings offer novel insight into the architectural contributions to the pathophysiology underlying bipolar disorder.

neuroscience↗

bioRxiv2022

Associations between methylation age and brain age in late adolescence

Recent research suggests that biological age, based on DNA methylation or neuroimaging measures, may predict health traits in adulthood more accurately than chronological age. However, whether these findings apply to earlier stages in life is unknown. We therefore aimed to characterise the performance of and interdependence between measures of biological age during adolescence, leveraging longitudinal data from a subsample of young adolescents from the population-based ALSPAC cohort (n=386). We derived four methylation age measures in late adolescence (17-19 years) and a measure of brain age derived from structural neuroimaging data (18-24 years). We then examined associations between these measures of biological age, and their relationship with five measures of physical, cognitive and mental health (8-18 years). Brain age was largely independent of different measures of methylation age, after accounting for age, cell type composition, array and study (beta range: -0.60 to 0.60, all p>0.05). Smoking and BMI were associated with three measures of advanced methylation age (beta range: -0.35 to 0.52, all p<0.05), but not brain age. Depressive symptoms and cognitive ability were unrelated to all measures of biological age. Our findings emphasize the variability of and independence between these methylation- and brain-based measures of age in adolescents. They also highlight the importance of tracking the mosaic of ageing in younger populations.

neuroscience↗