del Cerro Leon, A. | Search bioRxiv

bioRxiv2025

Complementary MR measures of white matter and their relation to cardiovascular health and cognition

Magnetic Resonance Imaging (MRI) offers many ways to non-invasively estimate the properties of white matter (WM) in the brain. In addition to the various metrics derived from diffusion-weighted MRI, one can estimate total WM volume from T1-weighted MRI, WM hyper-intensities from T2-weighted MRI, myelination from the T1:T2 ratio, or from the magnetisation-transfer ratio (MTR). Here we utilise the presence of all of these MR contrasts in a population based life-span cohort of 650 healthy adults [CamCAN cohort] to identify the latent factors underlying the covariance of 11 commonly-used WM metrics. Four factors were needed to explain 89% of the variance, which we interpreted in terms of 1) fibre density / myelination, 2) free-water / tissue damage, 3) fibre-crossing complexity and 4) microstructural complexity. These factors showed distinct effects of age and sex. To test the validity of these factors, we related them to measures of cardiovascular health and cognitive performance. Specifically, we ran path analyses 1) linking cardio-vascular measures to the WM factors, given the idea that WM health is related to cardiovascular health, and 2) linking the WM factors to cognitive measure, given the idea that WM health is important for cognition. Even after adjusting for age, we found that a vascular factor related to pulse pressure predicted the WM factor capturing free-water / tissue damage, and that several WM factors made unique predictions for fluid intelligence and processing speed. Our results show that there is both complementary and redundant information across common MR measures of WM, and their underlying latent factors may be useful for pinpointing the differential causes and contributions of white matter health in healthy aging.

neuroscience↗

bioRxiv2024

From electrophysiology to drink: Adolescent alcohol consumption predicted by differences in functional connectivity and neuroanatomy

Alcohol consumption during adolescence has been associated with neuroanatomical abnormalities and the appearance of future disorders. However, the latest advances in this field point to the existence of risk profiles which may lead to some individuals into an early consumption. To date, some studies have established predictive models of consumption based on sociodemographic, behavioural, and anatomical-functional variables using MRI. However, the neuroimaging variables employed are usually restricted to local and hemodynamic phenomena. Given the potential of connectome approaches, and the high temporal dynamics of electrophysiology, we decided to explore the relationship between future alcohol consumption and electrophysiological connectivity measured by MEG in a cohort of 83 individuals aged 14 to 16. We calculated predictive models throughout multiple linear regressions based on behavioural, anatomical, and functional connectivity variables. As a result, we found a positive correlation between alcohol consumption and the functional connectivity in frontal, parietal, and frontoparietal connections. Also, we identified negative relationships of alcohol consumption with neuroanatomical variables. Finally, the linear regression analysis determined the importance of anatomical and functional variables in the prediction of alcohol consumption but failed to find associations with impulsivity, sensation-seeking, and executive function scales. As conclusion, the predictive traits obtained in these models were closely associated with changes occurring during neurodevelopment, suggesting the existence of different paths in neurodevelopment that have the potential to influence adolescents relationship with alcohol consumption. Significance statementTo understand the onset of heavy drinking habits and develop prevention strategies, we need to characterize predisposition profiles at early ages. This longitudinal work provides important evidence by showing how adolescents at risk for engaging in alcohol behaviors showed resting-state functional connectivity and grey matter differences years before. The combination of these metrics allows us to establish predictive models of future alcohol episodes. In addition, differences in functional connectivity showed a positive relationship with behavioral variables such as lower executive functions and higher on the sensation-seeking. These predisposition phenotypes may rely on divergent neurodevelopmental pathways and deeper neurobiological abnormalities, such as dysfunctions of inhibitory neurotransmission and/or a genetic background of vulnerability.

neuroscience↗