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000151613 0247_ $$2doi$$a10.1016/j.mayocp.2019.05.030
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000151613 041__ $$aEnglish
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000151613 1001_ $$0P:(DE-2719)2810491$$aWittfeld, Katharina$$b0$$eFirst author$$udzne
000151613 245__ $$aCardiorespiratory Fitness and Gray Matter Volume in the Temporal, Frontal, and Cerebellar Regions in the General Population.
000151613 260__ $$a[S.l.]$$bElsevier$$c2020
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000151613 520__ $$aTo analyze the association between cardiorespiratory fitness (CRF) and global and local brain volumes.We studied 2103 adults (21-84 years old) from 2 independent population-based cohorts (Study of Health in Pomerania, examinations from June 25, 2008, through September 30, 2012). Cardiorespiratory fitness was measured using peak oxygen uptake (VO2peak), oxygen uptake at the anaerobic threshold (VO2@AT), and maximal power output from cardiopulmonary exercise testing on a bicycle ergometer. Magnetic resonance imaging brain data were analyzed by voxel-based morphometry using regression models with adjustment for age, sex, education, smoking, body weight, systolic blood pressure, glycated hemoglobin level, and intracranial volume.Volumetric analyses revealed associations of CRF with gray matter (GM) volume and total brain volume. After multivariable adjustment, a 1-standard deviation increase in VO2peak was related to a 5.31 cm³ (95% CI, 3.27 to 7.35 cm³) higher GM volume. Whole-brain voxel-based morphometry analyses revealed significant positive relations between CRF and local GM volumes. The VO2peak was strongly associated with GM volume of the left middle temporal gyrus (228 voxels), the right hippocampal gyrus (146 voxels), the left orbitofrontal cortex (348 voxels), and the bilateral cingulate cortex (68 and 43 voxels).Cardiorespiratory fitness was positively associated with GM volume, total brain volume, and specific GM and white matter clusters in brain areas not primarily involved in movement processing. These results, from a representative population sample, suggest that CRF might contribute to improved brain health and might, therefore, decelerate pathology-specific GM decrease.
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000151613 650_2 $$2MeSH$$aAdult
000151613 650_2 $$2MeSH$$aAged
000151613 650_2 $$2MeSH$$aAged, 80 and over
000151613 650_2 $$2MeSH$$aAnaerobic Threshold
000151613 650_2 $$2MeSH$$aBrain: diagnostic imaging
000151613 650_2 $$2MeSH$$aBrain: pathology
000151613 650_2 $$2MeSH$$aCardiorespiratory Fitness: physiology
000151613 650_2 $$2MeSH$$aCorrelation of Data
000151613 650_2 $$2MeSH$$aExercise Test: methods
000151613 650_2 $$2MeSH$$aExercise Test: statistics & numerical data
000151613 650_2 $$2MeSH$$aFemale
000151613 650_2 $$2MeSH$$aGray Matter: diagnostic imaging
000151613 650_2 $$2MeSH$$aGray Matter: pathology
000151613 650_2 $$2MeSH$$aHumans
000151613 650_2 $$2MeSH$$aMale
000151613 650_2 $$2MeSH$$aMiddle Aged
000151613 650_2 $$2MeSH$$aOrgan Size
000151613 7001_ $$aJochem, Carmen$$b1
000151613 7001_ $$aDörr, Marcus$$b2
000151613 7001_ $$aSchminke, Ulf$$b3
000151613 7001_ $$aGläser, Sven$$b4
000151613 7001_ $$aBahls, Martin$$b5
000151613 7001_ $$aMarkus, Marcello R P$$b6
000151613 7001_ $$aFelix, Stephan B$$b7
000151613 7001_ $$aLeitzmann, Michael F$$b8
000151613 7001_ $$aEwert, Ralf$$b9
000151613 7001_ $$aBülow, Robin$$b10
000151613 7001_ $$aVölzke, Henry$$b11
000151613 7001_ $$aJanowitz, Deborah$$b12
000151613 7001_ $$aBaumeister, Sebastian E$$b13
000151613 7001_ $$0P:(DE-2719)2811781$$aGrabe, Hans Jörgen$$b14$$eLast author$$udzne
000151613 773__ $$0PERI:(DE-600)2052617-9$$a10.1016/j.mayocp.2019.05.030$$gVol. 95, no. 1, p. 44 - 56$$n1$$p44 - 56$$tMayo Clinic proceedings$$v95$$x0025-6196$$y2020
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