Consistent neuroanatomical age-related volume differences across multiple samples. Neurobiol Aging

Center for the Study of Human Cognition, Department of Psychology, University of Oslo, Norway.
Neurobiology of aging (Impact Factor: 4.85). 07/2009; 32(5):916-32. DOI: 10.1016/j.neurobiolaging.2009.05.013
Source: PubMed

ABSTRACT Magnetic resonance imaging (MRI) is the principal method for studying structural age-related brain changes in vivo. However, previous research has yielded inconsistent results, precluding understanding of structural changes of the aging brain. This inconsistency is due to methodological differences and/or different aging patterns across samples. To overcome these problems, we tested age effects on 17 different neuroanatomical structures and total brain volume across five samples, of which one was split to further investigate consistency (883 participants). Widespread age-related volume differences were seen consistently across samples. In four of the five samples, all structures, except the brainstem, showed age-related volume differences. The strongest and most consistent effects were found for cerebral cortex, pallidum, putamen and accumbens volume. Total brain volume, cerebral white matter, caudate, hippocampus and the ventricles consistently showed non-linear age functions. Healthy aging appears associated with more widespread and consistent age-related neuroanatomical volume differences than previously believed.

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Available from: Naftali Raz, Aug 28, 2015
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    • "Heterochronicity in growth and aging trajectories of regional brain volumes has been firmly established with quantitative neuroimaging (e.g., Abe et al., 2008; Giedd et al., 2010; Jernigan et al., 2001; Pfefferbaum et al., 1994; Raz and Rodrigue, 2006; Walhovd et al., 2011). Age-related effects across the adult span have shown areas especially vulnerable to aging, including prefrontal cortex and cerebellar hemispheres and those relatively resistant to aging, including motor, sensory, occipital cortices, corpus callosum, and ventral pons (e.g.,Good et al., 2001; Jernigan et al., 2001; Pfefferbaum et al., 2013; Raz and Rodrigue, 2006; Raz et al., 2005; Walhovd et al., 2011). These observations have been based largely on " crosssectional " studies, that is, data from healthy individuals of different ages examined once each, with the assumption that resulting age regressions reflect longitudinal change. "
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    ABSTRACT: The healthy adult brain undergoes tissue volume decline with age, but contradictory findings abound regarding rate of change. To identify a source of this discrepancy, we present contrasting statistical approaches to estimate hippocampal volume change with age based on 200 longitudinally-acquired magnetic resonance imaging in 70 healthy adults, age 20-70 years, who had 2-5 magnetic resonance imaging collected over 6 months to 8 years. Linear mixed-effects modeling using volume trajectories over age for each subject revealed significantly negative slopes with aging after a linear decline with a suggestion of acceleration in older individuals. By contrast, general linear modeling using either the first observation only of each subject or all observations treated independently (thereby disregarding trajectories) indicated no significant correlation between volume and age. Entering a quadratic term into the linear model yielded a biologically plausible function that was not supported by longitudinal analysis. The results underscore the importance of analyses that incorporate the trajectory of individuals in the study of brain aging. Copyright © 2015 Elsevier Inc. All rights reserved.
    Neurobiology of Aging 05/2015; DOI:10.1016/j.neurobiolaging.2015.05.005 · 4.85 Impact Factor
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    • "× ↓ ↓ ↓ ↓ [Walhovd et al., 2011] × ↓ [Well et al., 2007] × ↓ ↓ ↓ [Scahill et al., 2003] × ↓ [Svennerholm et al., 1997] × – [Johnson et al., 1984] × ↑ [Ho et al., 1980] × ↓ [Courchesne et al., 2000] × ↓ – [Kaye et al., 1997] × × ↓ ↓ ↓ ↓ ↓ ↓ ↓ [Sawabe et al., 2006] Mice B6C3F1 × ↑ ↑ ↑ ↑ ↑ ↑ – – [Marino, 2012] B6C3F1 × ↑ [Cameron et al., 1985] HLG × ↑ ↑ ↑ [Bergmann et al., 1995] FVB/NJ × ↑ ↑ ↑ ↑ [Carroll et al., 2011] White Swiss × ↑ ↑ ↑ ↑ ↑ [Webster et Liljegren, 1955] C57BL/Icrf a t × ↑ ↑ ↑ ↑ – ↑ ↓ ↓ [Rowlatt et al., 1976] C57BL/6J × ↑ [Cao et al., 2003; Fahlstrom et al., 2011; Fahlstrom et al., 2012; Glatt et al., 2007; Halloran et al., 2002] C57BL/6J × ↑ [Armstrong, 1990] C57BL/6J × – ↑ ↑ ↑ [Leto et al., 1971] C57BL/6, DBA/2 × ↑↓ [Ferguson et al., 2007] C57BL/6 × ↑ [Mirich et al., 2002] "
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    ABSTRACT: In order to further understand age-related physiological changes and to have in deph reference values for C57BL/6 mice, we undertook a study to assess the effects of aging on peripheral organ weights, and brain region weights in wild type C57BL/6 male mice. Peripheral organs, body and brain region weights were collected from young (3-4 months), mid (12months), old (23-28 months) and very old (>30months) mice. Significant increases are observed with aging in body, liver, heart, kidney and spleen organ weights. A decrease in organ weight is observed with aging in liver and kidney only in the very old mice. In contrast, testes weight decreases with age. Within the brain, hippocampi, striata and olfactory bulbs weight decreases with age. These data further our knowledge of the anatomical and biological changes that occur with aging and provide reference values for physiological-based pharmacokinetic studies in C57BL/6 mice. Copyright © 2015. Published by Elsevier Inc.
    Experimental Gerontology 01/2015; 63. DOI:10.1016/j.exger.2015.01.003 · 3.53 Impact Factor
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    • "Many of these cognitive and motor functions deteriorate with age (Mark and Rugg, 1998; Smith et al., 1999; Mattay et al., 2002), and co-occur with marked anatomical changes in the basal ganglia. Morphology studies consistently reveal declines in striatal/pallidal volume by 4–8% per decade, starting as early as age 20 (e.g., Brabec et al., 2003; Raz et al., 2003; Walhovd et al., 2011; Goodro et al., 2012). Postmortem studies have shown age-related neuronal loss and changes to basic cellular structure such as the myelin sheath in basal ganglia (for reviews, see Haug, 1985; Kemper, 1994; Peters, 2002). "
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    ABSTRACT: The basal ganglia nuclei are critical for a variety of cognitive and motor functions. Much work has shown age-related structural changes of the basal ganglia. Yet less is known about how the functional interactions of these regions with the cerebral cortex and the cerebellum change throughout the lifespan. Here, we took advantage of a convenient sample and examined resting state functional magnetic resonance imaging data from 250 adults 18 to 49years of age, focusing specifically on the caudate nucleus, pallidum, putamen, and ventral tegmental area/substantia nigra (VTA/SN). There are a few main findings to report. First, with age, caudate head connectivity increased with a large region of ventromedial prefrontal/medial orbitofrontal cortex. Second, across all subjects, pallidum and putamen showed negative connectivity with default mode network (DMN) regions such as the ventromedial prefrontal cortex and posterior cingulate cortex, in support of anticorrelation of the "task-positive" network (TPN) and DMN. This negative connectivity was reduced with age. Furthermore, pallidum, posterior putamen and VTA/SN connectivity to other TPN regions, such as somatomotor cortex, decreased with age. These results highlight a distinct effect of age on cerebral functional connectivity of the dorsal striatum and VTA/SN from young to middle adulthood and may help research investigating the etiologies or monitoring outcomes of neuropsychiatric conditions that implicate dopaminergic dysfunction. Copyright © 2014 Elsevier Inc. All rights reserved.
    NeuroImage 12/2014; 107. DOI:10.1016/j.neuroimage.2014.12.016 · 6.36 Impact Factor
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