Literature DB >> 26572143

Male brain ages faster: the age and gender dependence of subcortical volumes.

András Király1, Nikoletta Szabó1,2, Eszter Tóth1, Gergő Csete1, Péter Faragó1, Krisztián Kocsis1, Anita Must1, László Vécsei1,3, Zsigmond Tamás Kincses4,5.   

Abstract

Effects of gender on grey matter (GM) volume differences in subcortical structures of the human brain have consistently been reported. Recent research evidence suggests that both gender and brain size influences volume distribution in subcortical areas independently. The goal of this study was to determine the effects of the interplay between brain size, gender and age contributing to volume differences of subcortical GM in the human brain. High-resolution T1-weighted images were acquired from 53 healthy males and 50 age-matched healthy females. Total GM volume was determined using voxel-based morphometry. We used model-based subcortical segmentation analysis to measure the volume of subcortical nuclei. Main effects of gender, brain volume and aging on subcortical structures were examined using multivariate analysis of variance. No significant difference was found in total brain volume between the two genders after correcting for total intracranial volume. Our analysis revealed significantly larger hippocampus volume for females. Additionally, GM volumes of the caudate nucleus, putamen and thalamus displayed a significant age-related decrease in males as compared to females. In contrast to this only the thalamic volume loss proved significant for females. Strikingly, GM volume decreases faster in males than in females emphasizing the interplay between aging and gender on subcortical structures. These findings might have important implications for the interpretation of the effects of unalterable factors (i.e. gender and age) in cross-sectional structural MRI studies. Furthermore, the volume distribution and changes of subcortical structures have been consistently related to several neuropsychiatric disorders (e.g. Parkinson's disease, attention deficit hyperactivity disorder, etc.). Understanding these changes might yield further insight in the course and prognosis of these disorders.

Entities:  

Keywords:  Aging; Brain volume; Gender; MRI; Subcortical structures

Mesh:

Year:  2016        PMID: 26572143     DOI: 10.1007/s11682-015-9468-3

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.978


  14 in total

1.  The detection of age-, gender-, and region-specific changes in mouse brain tocopherol levels via the application of different validated HPLC methods.

Authors:  Nikolett Nánási; Gábor Veres; Edina K Cseh; Márton Szentirmai; Diána Martos; Evelin Sümegi; Levente Hadady; Péter Klivényi; László Vécsei; Dénes Zádori
Journal:  Neurochem Res       Date:  2018-09-07       Impact factor: 3.996

2.  Sex-Based Differences in Cortical and Subcortical Development in 436 Individuals Aged 4-54 Years.

Authors:  Emma G Duerden; M Mallar Chakravarty; Jason P Lerch; Margot J Taylor
Journal:  Cereb Cortex       Date:  2020-05-14       Impact factor: 5.357

3.  Smaller total brain volume but not subcortical structure volume related to common genetic risk for ADHD.

Authors:  Michael A Mooney; Priya Bhatt; Robert J M Hermosillo; Peter Ryabinin; Molly Nikolas; Stephen V Faraone; Damien A Fair; Beth Wilmot; Joel T Nigg
Journal:  Psychol Med       Date:  2020-01-24       Impact factor: 7.723

4.  Early Prediction of Alzheimer's Disease Using Null Longitudinal Model-Based Classifiers.

Authors:  Giovana Gavidia-Bovadilla; Samir Kanaan-Izquierdo; María Mataró-Serrat; Alexandre Perera-Lluna
Journal:  PLoS One       Date:  2017-01-03       Impact factor: 3.240

5.  Designing in vitro Blood-Brain Barrier Models Reproducing Alterations in Brain Aging.

Authors:  Elena D Osipova; Yulia K Komleva; Andrey V Morgun; Olga L Lopatina; Yulia A Panina; Raissa Ya Olovyannikova; Elizaveta F Vais; Vladimir V Salmin; Alla B Salmina
Journal:  Front Aging Neurosci       Date:  2018-08-06       Impact factor: 5.750

6.  Multi-study validation of data-driven disease progression models to characterize evolution of biomarkers in Alzheimer's disease.

Authors:  Damiano Archetti; Silvia Ingala; Vikram Venkatraghavan; Viktor Wottschel; Alexandra L Young; Maura Bellio; Esther E Bron; Stefan Klein; Frederik Barkhof; Daniel C Alexander; Neil P Oxtoby; Giovanni B Frisoni; Alberto Redolfi
Journal:  Neuroimage Clin       Date:  2019-07-23       Impact factor: 4.881

7.  Whole Brain and Cranial Size Adjustments in Volumetric Brain Analyses of Sex- and Age-Related Trends.

Authors:  Marek Kijonka; Damian Borys; Krzysztof Psiuk-Maksymowicz; Kamil Gorczewski; Piotr Wojcieszek; Bartosz Kossowski; Artur Marchewka; Andrzej Swierniak; Maria Sokol; Barbara Bobek-Billewicz
Journal:  Front Neurosci       Date:  2020-04-03       Impact factor: 4.677

8.  Inter-Cohort Validation of SuStaIn Model for Alzheimer's Disease.

Authors:  Damiano Archetti; Alexandra L Young; Neil P Oxtoby; Daniel Ferreira; Gustav Mårtensson; Eric Westman; Daniel C Alexander; Giovanni B Frisoni; Alberto Redolfi
Journal:  Front Big Data       Date:  2021-05-20

9.  Distinct Functional Connectivity Patterns Are Associated With Social and Cognitive Lifestyle Factors: Pathways to Cognitive Reserve.

Authors:  Jessica I Fleck; Molly Arnold; Benjamin Dykstra; Katharine Casario; Elizabeth Douglas; Otto Morris
Journal:  Front Aging Neurosci       Date:  2019-11-13       Impact factor: 5.750

Review 10.  MAGNIMS consensus recommendations on the use of brain and spinal cord atrophy measures in clinical practice.

Authors:  Jaume Sastre-Garriga; Deborah Pareto; Marco Battaglini; Maria A Rocca; Olga Ciccarelli; Christian Enzinger; Jens Wuerfel; Maria P Sormani; Frederik Barkhof; Tarek A Yousry; Nicola De Stefano; Mar Tintoré; Massimo Filippi; Claudio Gasperini; Ludwig Kappos; Jordi Río; Jette Frederiksen; Jackie Palace; Hugo Vrenken; Xavier Montalban; Àlex Rovira
Journal:  Nat Rev Neurol       Date:  2020-02-24       Impact factor: 42.937

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