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In this paper, we attempt to answer two questions: 1) which regions of the human brain, in terms of morphometry, are most strongly related to individual differences in domain-general cognitive functioning ( )? and 2) what are the underlying neurobiological properties of those regions? We meta-analyse vertex-wise -cortical morphometry (volume, surface area, thickness, curvature and sulcal depth) associations using data from 3 cohorts: the UK Biobank (UKB), Generation Scotland (GenScot), and the Lothian Birth Cohort 1936 (LBC1936), with the meta-analytic = 38,379 (age range = 44 to 84 years old). These morphometry associations vary in magnitude and direction across the cortex (|β| range = -0.12 to 0.
View Article and Find Full Text PDFTOMM40 may mediate GFAP, neurofilament light Protein, pTau181, and brain morphometry in aging.
Aging Brain
December 2024
University of Kansas Alzheimer's Disease Research Center, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
A growing amount of data has implicated the gene in the risk for Alzheimer's disease (AD), neurodegeneration, and accelerated aging. No studies have investigated the relationship of rs2075650 ('650 on the structural complexity of the brain or plasma markers of neurodegeneration. We used a comprehensive approach to quantify the impact of '650 on brain morphology and multiple cortical attributes in cognitively unimpaired (CU) individuals.
View Article and Find Full Text PDFPredicting Antidepressant Treatment Response From Cortical Structure on MRI: A Mega-Analysis From the ENIGMA-MDD Working Group.
Hum Brain Mapp
January 2025
Amsterdam UMC, Department of Radiology and Nuclear Medicine, University of Amsterdam, Amsterdam, the Netherlands.
Accurately predicting individual antidepressant treatment response could expedite the lengthy trial-and-error process of finding an effective treatment for major depressive disorder (MDD). We tested and compared machine learning-based methods that predict individual-level pharmacotherapeutic treatment response using cortical morphometry from multisite longitudinal cohorts. We conducted an international analysis of pooled data from six sites of the ENIGMA-MDD consortium (n = 262 MDD patients; age = 36.
View Article and Find Full Text PDFDisentangling the effect of sex from brain size on brain organization and cognitive functioning.
Geroscience
January 2025
Cerebral Imaging Center, Douglas Mental Health University Institute, 6875 Boulevard LaSalle, Montréal, QC, H4H 1R3, Canada.
Neuroanatomical sex differences estimated in neuroimaging studies are confounded by total intracranial volume (TIV) as a major biological factor. Employing a matching approach widely used for causal modeling, we disentangled the effect of TIV from sex to study sex-differentiated brain aging trajectories, their relation to functional networks and cytoarchitectonic classes, brain allometry, and cognition. Using data from the UK Biobank, we created subsamples that removed, maintained, or exaggerated the TIV differences in the original sample.
View Article and Find Full Text PDFCorrelation between polygenic risk scores of depression and cortical morphology networks.
J Psychiatry Neurosci
January 2025
From the Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China (Gong, Wang, Nie, Ma, Zhou, Deng, Xie, Lyu, Chen, Kang, Liu); the Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan, China (Liu)
Background: Cortical morphometry is an intermediate phenotype that is closely related to the genetics and onset of major depressive disorder (MDD), and cortical morphometric networks are considered more relevant to disease mechanisms than brain regions. We sought to investigate changes in cortical morphometric networks in MDD and their relationship with genetic risk in healthy controls.
Methods: We recruited healthy controls and patients with MDD of Han Chinese descent.
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