A longitudinal study of age‐ and gender‐related annual rate of volume changes in regional gray matter in healthy adults

The aim of this study was to analyze correlations among the annual rate of gray matter volume change, age, gender, and cerebrovascular risk factors in 381 healthy community‐dwelling subjects with a large age range by applying a longitudinal design over 6 years using brain magnetic resonance images (MRIs). Brain MRI data were processed with voxel‐based morphometry using a custom template by applying diffeomorphic anatomical registration using the exponentiated lie algebra procedure. The annual rate of regional gray matter volume change showed significant positive correlations with age in several regions, including the bilateral temporal pole, caudate nucleus, ventral and dorsolateral prefrontal cortices, insula, hippocampus, and temporoparietal cortex, whereas significant negative correlations with age were observed in several regions including the bilateral cingulate gyri and anterior lobe of the cerebellum. Additionally, a significant age‐by‐gender interaction was found for the annual rate of regional gray matter volume change in the bilateral hippocampus. No significant correlations were observed between the annual rate of regional gray matter volume change and body mass index or systolic blood pressure. A significant positive correlation between the annual rate of gray matter volume change and age indicates that the region shows not linear but accelerated gray matter loss with age. Therefore, evaluating the annual rate of the gray matter volume change with age in healthy subjects is important in understanding how gray matter volume changes with aging in each brain region and in anticipating what cognitive functions are likely to show accelerated decline with aging. Hum Brain Mapp 34:2292–2301, 2013. © 2012 Wiley Periodicals, Inc.

[1]  Karl J. Friston,et al.  Unified segmentation , 2005, NeuroImage.

[2]  Kazunori Sato,et al.  Neuroanatomical database of normal Japanese brains , 2003, Neural Networks.

[3]  N. Schuff,et al.  Age effects on atrophy rates of entorhinal cortex and hippocampus , 2006, Neurobiology of Aging.

[4]  Michael W Weiner,et al.  Longitudinal MRI and cognitive change in healthy elderly. , 2007, Neuropsychology.

[5]  E. Tangalos,et al.  Memory function in normal aging , 1992, Neurology.

[6]  E. Gordon,et al.  Brain maturation in adolescence: Concurrent changes in neuroanatomy and neurophysiology , 2007, Human brain mapping.

[7]  A. Toga,et al.  Localizing Age-Related Changes in Brain Structure between Childhood and Adolescence Using Statistical Parametric Mapping , 1999, NeuroImage.

[8]  F. Schmitt,et al.  Age and gender effects on human brain anatomy: A voxel-based morphometric study in healthy elderly , 2007, Neurobiology of Aging.

[9]  Karl J. Friston,et al.  Computing average shaped tissue probability templates , 2009, NeuroImage.

[10]  Kewei Chen,et al.  Brain abnormalities in human obesity: A voxel-based morphometric study , 2006, NeuroImage.

[11]  Hiroshi Fukuda,et al.  Relationship Between Body Mass Index and Gray Matter Volume in 1,428 Healthy Individuals , 2008, Obesity.

[12]  S. Wheatcroft,et al.  Obesity, atherosclerosis and the vascular endothelium: mechanisms of reduced nitric oxide bioavailability in obese humans , 2002, International Journal of Obesity.

[13]  Nick C Fox,et al.  A longitudinal study of brain volume changes in normal aging using serial registered magnetic resonance imaging. , 2003, Archives of neurology.

[14]  Leanne M Williams,et al.  Preservation of limbic and paralimbic structures in aging , 2005, Human brain mapping.

[15]  John Ashburner,et al.  A fast diffeomorphic image registration algorithm , 2007, NeuroImage.

[16]  G. Busatto,et al.  Voxel-based morphometry in Alzheimer’s disease , 2008, Expert review of neurotherapeutics.

[17]  Cheryl L. Dahle,et al.  Regional brain changes in aging healthy adults: general trends, individual differences and modifiers. , 2005, Cerebral cortex.

[18]  E Gould,et al.  Hippocampal neurogenesis in adult Old World primates. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[19]  D. Head,et al.  Selective aging of the human cerebral cortex observed in vivo: differential vulnerability of the prefrontal gray matter. , 1997, Cerebral cortex.

[20]  P. Ridker,et al.  Usefulness of visceral obesity (waist/hip ratio) in predicting vascular endothelial function in healthy overweight adults. , 2001, The American journal of cardiology.

[21]  S. Resnick,et al.  Longitudinal Magnetic Resonance Imaging Studies of Older Adults: A Shrinking Brain , 2003, The Journal of Neuroscience.

[22]  A. Toga,et al.  Brain Structure and Obesity , 2009, NeuroImage.

[23]  C. Jack,et al.  Quantitative magnetic resonance techniques as surrogate markers of Alzheimer’s disease , 2004, NeuroRX.

[24]  C. Fennema-Notestine,et al.  Effects of age on tissues and regions of the cerebrum and cerebellum , 2001, Neurobiology of Aging.

[25]  C. Björkelund,et al.  A 24-year follow-up of body mass index and cerebral atrophy , 2004, Neurology.

[26]  Hiroshi Fukuda,et al.  A longitudinal study of gray matter volume decline with age and modifying factors , 2011, Neurobiology of Aging.

[27]  J. Haxby,et al.  Brain atrophy in hypertension. A volumetric magnetic resonance imaging study. , 1992, Hypertension.

[28]  S. Kinomura,et al.  Correlation between gray/white matter volume and cognition in healthy elderly people , 2011, Brain and Cognition.

[29]  Karl J. Friston,et al.  Voxel-Based Morphometry—The Methods , 2000, NeuroImage.

[30]  J. LERE BOULLET,et al.  [Brain atrophy]. , 1954, La Revue du praticien.

[31]  G. Pearlson,et al.  Elucidating the contributions of processing speed, executive ability, and frontal lobe volume to normal age-related differences in fluid intelligence , 2000, Journal of the International Neuropsychological Society.

[32]  Suzanne E. Welcome,et al.  Mapping cortical change across the human life span , 2003, Nature Neuroscience.

[33]  Arno Klein,et al.  Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration , 2009, NeuroImage.

[34]  K. Kayaba,et al.  Age at Menopause and Mortality in Japan: the Jichi Medical School Cohort Study , 2006, Journal of epidemiology.

[35]  A. Sorisky.  Molecular Links Between Obesity and Cardiovascular Disease , 2002, American journal of therapeutics.

[36]  R. Buckner,et al.  Normative estimates of cross-sectional and longitudinal brain volume decline in aging and AD , 2005, Neurology.

[37]  S. Folstein,et al.  "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. , 1975, Journal of psychiatric research.

[38]  L H Kuller,et al.  Age, Alzheimer disease, and brain structure , 2009, Neurology.

[39]  Robert H. Paul,et al.  The relationship between frontal gray matter volume and cognition varies across the healthy adult lifespan. , 2006, The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry.

[40]  Karen M Rodrigue,et al.  Hypertension and the brain: vulnerability of the prefrontal regions and executive functions. , 2003, Behavioral neuroscience.

[41]  S. Connelly,et al.  Age and reading: the impact of distraction. , 1991, Psychology and aging.

[42]  Thomas F. Nugent,et al.  Dynamic mapping of human cortical development during childhood through early adulthood. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[43]  M. Bond,et al.  Association of Obesity and Central Fat Distribution With Carotid Artery Wall Thickening in Middle-Aged Women , 2002, Stroke.

[44]  A. Dale,et al.  High consistency of regional cortical thinning in aging across multiple samples. , 2009, Cerebral cortex.

[45]  J. Westerbacka,et al.  Vascular actions of insulin in obesity , 2000, International Journal of Obesity.

[46]  Andrea Cherubini,et al.  Aging of subcortical nuclei: Microstructural, mineralization and atrophy modifications measured in vivo using MRI , 2009, NeuroImage.

[47]  Hiroshi Fukuda,et al.  Voxel-based morphometry of human brain with age and cerebrovascular risk factors , 2004, Neurobiology of Aging.

[48]  Aaron Carass,et al.  Longitudinal changes in cortical thickness associated with normal aging , 2010, NeuroImage.

[49]  L. Galea,et al.  Influence of different estrogens on neuroplasticity and cognition in the hippocampus. , 2010, Biochimica et biophysica acta.

[50]  David Clarys,et al.  Executive functioning and processing speed in age-related differences in memory: Contribution of a coding task , 2009, Brain and Cognition.

[51]  J. Haxby,et al.  A Volumetric Magnetic Resonance Imaging Study , 2005 .

[52]  Sterling C. Johnson,et al.  The effect of body mass index on global brain volume in middle-aged adults: a cross sectional study , 2005, BMC neurology.

[53]  S. Resnick,et al.  Longitudinal pattern of regional brain volume change differentiates normal aging from MCI , 2009, Neurology.

[54]  Faith M. Gunning-Dixon,et al.  Aging, sexual dimorphism, and hemispheric asymmetry of the cerebral cortex: replicability of regional differences in volume , 2004, Neurobiology of Aging.

[55]  Karl J. Friston,et al.  A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains , 2001, NeuroImage.

[56]  Marie Chupin,et al.  Can voxel based morphometry, manual segmentation and automated segmentation equally detect hippocampal volume differences in acute depression? , 2009, NeuroImage.

[57]  G. Alexander,et al.  Interactive effects of age and hypertension on volumes of brain structures. , 1997, Stroke.

[58]  J. Rapoport,et al.  Mapping adolescent brain change reveals dynamic wave of accelerated gray matter loss in very early-onset schizophrenia , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[59]  Karl J. Friston,et al.  Image registration using a symmetric prior—in three dimensions , 1999, Human brain mapping.