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Regional age differences in gray matter diffusivity among healthy older adults

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Abstract

Aging is associated with microstructural changes in brain tissue that can be visualized using diffusion tensor imaging (DTI). While previous studies have established age-related changes in white matter (WM) diffusion using DTI, the impact of age on gray matter (GM) diffusion remains unclear. The present study utilized DTI metrics of mean diffusivity (MD) to identify age differences in GM/WM microstructure in a sample of healthy older adults (N = 60). A secondary aim was to determine the functional significance of whole-brain GM/WM MD on global cognitive function using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Participants were divided into three age brackets (ages 50–59, 60–69, and 70+) to examine differences in MD and cognition by decade. MD was examined bilaterally in the frontal, temporal, parietal, and occipital lobes for the primary analyses and an aggregate measure of whole-brain MD was used to test relationships with cognition. Significantly higher MD was observed in bilateral GM of the temporal and parietal lobes, and in right hemisphere WM of the frontal and temporal lobes of older individuals. The most robust differences in MD were between the 50–59 and 70+ age groups. Higher whole-brain GM MD was associated with poorer RBANS performance in the 60–69 age group. Results suggest that aging has a significant and differential impact on GM/WM diffusion in healthy older adults, which may explain a modest degree of cognitive variability at specific time points during older adulthood.

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References

  • Alexander, A. L., Lee, J. E., Lazar, M., & Field, A. S. (2007). Diffusion tensor imaging of the brain. Neurotherapeutics, 4(3), 316–329.

    Article  PubMed  PubMed Central  Google Scholar 

  • Barnes, J., Foster, J., & Fox, N. C. (2007). Structural magnetic resonance imaging-derived biomarkers for Alzheimer’s disease. Biomarkers in Medicine, 1, 79–92.

    Article  PubMed  Google Scholar 

  • Baron, J. C., Chetelat, G., Desgranges, B., Perchey, G., Landeau, B., de la Sayette, V., & Eustache, F. (2001). In vivo mapping of gray matter loss with voxel-based morphometry in mild Alzheimer’s disease. NeuroImage, 14(2), 298–309.

    Article  CAS  PubMed  Google Scholar 

  • Bartrés-Faz, D., & Arenaza-Urquijo, E. M. (2011). Structural and functional imaging correlates of cognitive and brain reserve hypotheses in healthy and pathological aging. Brain Topography, 24(3-4), 340–357.

    Article  PubMed  Google Scholar 

  • Bartzokis, G., Tishler, T. A., Lu, P. H., Villablanca, P., Altshuler, L. L., Carter, M., & Mintz, J. (2007). Brain ferritin iron may influence age-and gender-related risks of neurodegeneration. Neurobiology of Aging, 28(3), 414–423.

    Article  CAS  PubMed  Google Scholar 

  • Basser, P. J., & Pierpaoli, C. (1996). Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. Journal of Magnetic Resonance Series B, 111(3), 209–219.

    Article  CAS  PubMed  Google Scholar 

  • Bhagat, Y. A., & Beaulieu, C. (2004). Diffusion anisotropy in subcortical white matter and cortical gray matter: changes with aging and the role of CSF-suppression. Journal of Magnetic Resonance Imaging, 20(2), 216–227. doi:10.1002/jmri.20102.

    Article  PubMed  Google Scholar 

  • Bilgic, B., Pfefferbaum, A., Rohlfing, T., Sullivan, E. V., & Adalsteinsson, E. (2012). MRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping. NeuroImage, 59(3), 2625–2635.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Bosch, B., Bartrés-Faz, D., Arenaza-Urquijo, E. M., Rami, L., Sala-Llonch, R., Junqué, C., & Solé-Padullés, C. (2012). Multiple DTI index analysis in normal aging, amnestic MCI and AD. Relationship with neuropsychological performance. Neurobiology of Aging, 33(1), 61–74.

    Article  PubMed  Google Scholar 

  • Chetelat, G., Desgranges, B., de la Sayette, V., Viader, F., Eustache, F., & Baron, J. C. (2003). Mild cognitive impairment Can FDG-PET predict who is to rapidly convert to Alzheimer’s disease? Neurology, 60(8), 1374–1377.

    Article  CAS  PubMed  Google Scholar 

  • Conturo, T. E., McKinstry, R. C., Akbudak, E., & Robinson, B. H. (1996). Encoding of anisotropic diffusion with tetrahedral gradients: a general mathematical diffusion formalism and experimental results. Magnetic Resonance in Medicine, 35(3), 399–412.

    Article  CAS  PubMed  Google Scholar 

  • de Jong, G. I., Vos, R. D., Steur, E. J., & Luiten, P. G. M. (1997). Cerebrovascular hypoperfusion: a risk factor for Alzheimer’s disease? Annals of the New York Academy of Sciences, 826(1), 56–74.

    Article  PubMed  Google Scholar 

  • de Jong, G. I., Farkas, E., Stienstra, C. M., Plass, J. R. M., Keijser, J. C., de la Torre, J. C., & Luiten, P. G. M. (1999). Cerebral hypoperfusion yields capillary damage in the hippocampal CA1 area that correlates with spatial memory impairment. Neuroscience, 91(1), 203–210.

    Article  PubMed  Google Scholar 

  • de la Torre, J. C. (2000). Critically attained threshold of cerebral hypoperfusion: the CATCH hypothesis of Alzheimer’s pathogenesis. Neurobiology of Aging, 21(2), 331–342.

    Article  PubMed  Google Scholar 

  • de Toledo Ferraz Alves, T. C., Scazufca, M., Squarzoni, P., de Souza Duran, F. L., Tamashiro-Duran, J. H., Vallada, H. P., & Busatto, G. F. (2011). Subtle gray matter changes in temporo-parietal cortex associated with cardiovascular risk factors. Journal of Alzheimer’s Disease, 27(3), 575–589.

    PubMed  Google Scholar 

  • Dolcos, F., Rice, H. J., & Cabeza, R. (2002). Hemispheric asymmetry and aging: right hemisphere decline or asymmetry reduction. Neuroscience & Biobehavioral Reviews, 26(7), 819–825.

    Article  Google Scholar 

  • Duff, K., Patton, D. E., Schoenberg, M. R., Mold, J., Scott, J. G., & Adams, R. A. (2003). Age- and education-corrected independent normative data for the RBANS in a community dwelling elderly sample. The Clinical Neuropsychologist, 17, 351–366.

    Article  PubMed  Google Scholar 

  • Dukart, J., Mueller, K., Villringer, A., Kherif, F., Draganski, B., Frackowiak, R., & Schroeder, M. L. (2013). Relationship between imaging biomarkers, age, progression and symptom severity in Alzheimer’s disease. Neuroimage Clin, 3, 84–94.

    Article  PubMed  PubMed Central  Google Scholar 

  • Eriksson, S. H., Rugg-Gunn, F. J., Symms, M. R., Barker, G. J., & Duncan, J. S. (2001). Diffusion tensor imaging in patients with epilepsy and malformations of cortical development. Brain, 124, 617–626.

    Article  CAS  PubMed  Google Scholar 

  • Freeman, S. H., Kandel, R., Cruz, L., Rozkalne, A., Newell, K., Frosch, M. P., & Hedley-Whyte, E. T. (2008). Preservation of neuronal number despite age-related cortical brain atrophy in elderly subjects without Alzheimer disease. Journal of Neuropathology & Experimental Neurology, 67(12), 1205–1212.

    Article  Google Scholar 

  • Ge, Y., Grossman, R. I., Babb, J. S., Rabin, M. L., Mannon, L. J., & Kolson, D. L. (2002). Age-related total gray matter and white matter changes in normal adult brain. Part I: volumetric MR imaging analysis. American Journal of Neuroradiology, 23(8), 1327–1333.

    PubMed  Google Scholar 

  • Gontkovsky, S. T., Beatty, W. W., & Mold, J. W. (2004). Repeatable battery for the assessment of neuropsychological status in a normal, geriatric sample. Clinical Gerontologist, 27(3), 79–86. doi:10.1300/J018v27n03_07.

    Article  Google Scholar 

  • Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N., Fristen, K. J., & Frackowiak, R. S. (2001). A voxel-based morphometric study of ageing in 465 normal adult human brains. NeuroImage, 14, 21–26.

    Article  CAS  PubMed  Google Scholar 

  • Hajnal, J. V., Bryant, D. J., Kasuboski, L., Pattany, P. M., de Coene, B., Lewis, P. D., & Bydder, G. M. (1992). Use of fluid attenuated inversion recovery (FLAIR) pulse sequences in MRI of the brain. Journal of Computer Assisted Tomography, 16(6), 841–844.

    Article  CAS  PubMed  Google Scholar 

  • Jacobs, H. I., van Boxtel, M. P., Gronenschild, E. H., Uylings, H. B., Jolles, J., & Verhey, F. R. (2013). Decreased gray matter diffusivity: a potential early Alzheimer’s disease biomarker? Alzheimer’s & Dementia, 9(1), 93–97.

    Article  Google Scholar 

  • Jahng, G., Xu, S., Weiner, M. W., Meyerhoff, D. J., Park, S., & Schuff, N. (2011). DTI studies in patients with Alzheimer’s disease, mild cognitive impairment, or normal cognition with evaluation of the intrinsic background gradients. Neuroradiology, 53(10), 749–762. doi:10.1007/s00234-011-0845-3.

    Article  PubMed  PubMed Central  Google Scholar 

  • Jenkinson, M., & Smith, S. (2001). A global optimisation method for robust affine registration of brain images. Medical Image Analysis, 5(2), 143–156.

    Article  CAS  PubMed  Google Scholar 

  • Jespersen, S. N., Kroenke, C. D., Østergaard, L., Ackerman, J. J., & Yablonskiy, D. A. (2007). Modeling dendrite density from magnetic resonance diffusion measurements. NeuroImage, 34(4), 1473–1486.

    Article  PubMed  Google Scholar 

  • Kim, H. J., Kim, S. J., Kim, H. S., Choi, C. G., Kim, N., Han, S., & Lee, C. S. (2013). Alterations of mean diffusivity in brain white matter and deep gray matter in Parkinson’s disease. Neuroscience Letters, 550, 64–68.

    Article  CAS  PubMed  Google Scholar 

  • Koo, B. B., Hua, N., Choi, C. H., Ronen, I., Lee, J. M., & Kim, D. (2009). A framework to analyze partial volume effect on gray matter mean diffusivity measurements. NeuroImage, 44(1), 136–144.

    Article  PubMed  Google Scholar 

  • Lawton, M. P., & Brody, E. (1969). Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontology, 9, 179–186.

    Article  CAS  Google Scholar 

  • Li, Z., Moore, A. B., Tyner, C., & Hu, X. (2009). Asymmetric connectivity reduction and its relationship to “HAROLD” in aging brain. Brain Research, 1295, 149–158.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ma, X., Kadah, Y. M., LaConte, S. M., & Hu, X. (2004). Enhancing measured diffusion anisotropy in gray matter by eliminating CSF contamination with FLAIR. Magnetic Resonance in Medicine, 51(2), 423–427.

    Article  PubMed  Google Scholar 

  • Madden, D. J., Bennett, I. J., & Song, A. W. (2009). Cerebral white matter integrity and cognitive aging: contributions from diffusion tensor imaging. Neuropsychology Review, 19(4), 415–435. doi:10.1007/s11065-009-9113-2.

    Article  PubMed  PubMed Central  Google Scholar 

  • McNab, J. A., Polimeni, J. R., Wang, R., Augustinack, J. C., Fujimoto, K., Player, A., & Wald, L. L. (2013). Surface based analysis of diffusion orientation for identifying architectonic domains in the in vivo human cortex. NeuroImage, 69, 87–100.

    Article  PubMed  PubMed Central  Google Scholar 

  • Mielke, M. M., Kozauer, N. A., Chan, K. C. G., George, M., Toroney, J., Zerrate, M., & Albert, M. (2009). Regionally-specific diffusion tensor imaging in mild cognitive impairment and Alzheimer’s disease. NeuroImage, 46(1), 47–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Molko, N., Pappata, S., Mangin, J. F., Poupon, C., Vahedi, K., Jobert, A., & Chabriat, H. (2001). Diffusion tensor imaging study of subcortical gray matter in CADASIL. Stroke, 32(9), 2049–2054.

    Article  CAS  PubMed  Google Scholar 

  • Mortamet, B., Zeng, D., Gerig, G., Prastawa, M., & Bullitt, E. (2005). Effects of healthy aging measured by intracranial compartment volumes using a designed MR brain database. In Medical Image Computing and Computer-Assisted Intervention–MICCAI 2005 (pp. 383–391). Springer Berlin Heidelberg.

  • Mugler, J. P., & Brookeman, J. R. (1990). Three-dimensional magnetization-prepared rapid gradient-echo imaging (3D MP RAGE). Magnetic Resonance in Medicine, 15(1), 152–157.

    Article  PubMed  Google Scholar 

  • Mugler, J. P., & Brookeman, J. R. (1991). Rapid three‐dimensional T1‐weighted MR imaging with the MP-RAGE sequence. Journal of Magnetic Resonance Imaging, 1(5), 561–567.

  • Naganawa, S., Sato, K., Katagiri, T., Mimura, T., & Ishigaki, T. (2003). Regional ADC values of the normal brain: differences due to age, gender, and laterality. European Radiology, 13(1), 6–11.

    PubMed  Google Scholar 

  • Nasreddine, Z. S., Phillips, N. A., Bédirian, V., Charbonneau, S., Whitehead, V., Collin, I., & Chertkow, H. (2005). The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53(4), 695–699.

    Article  PubMed  Google Scholar 

  • Ni, J. M., Chen, S., Liu, J. J., Huang, G., Shen, T. Z., & Chen, X. R. (2010). Regional diffusion changes of cerebral grey matter during normal aging—A fluid-inversion prepared diffusion imaging study. European Journal of Radiology, 75(2), 134–138.

    Article  PubMed  Google Scholar 

  • Pal, D., Trivedi, R., Saksena, S., Yadav, A., Kumar, M., Pandey, C. M., & Gupta, R. K. (2011). Quantification of age- and gender-related changes in diffusion tensor imaging indices in deep grey matter of the normal human brain. Journal of Clinical Neuroscience, 18(2), 193–196. doi:10.1016/j.jocn.2010.05.033.

    Article  PubMed  Google Scholar 

  • Paul, R. H., Haque, O., Gunstad, J., Tate, D. F., Grieve, S. M., Hoth, K., & Gordon, E. (2005). Subcortical hyperintensities impact cognitive function among a select subset of healthy elderly. Archives of Clinical Neuropsychology, 20(6), 697–704.

    Article  PubMed  PubMed Central  Google Scholar 

  • Paul, R., Lane, E. M., Tate, D. F., Heaps, J., Romo, D. M., Akbudak, E., & Conturo, T. E. (2011). Neuroimaging signatures and cognitive correlates of the Montreal cognitive assessment screen in a nonclinical elderly sample. Archives of Clinical Neuropsychology, 26(5), 454–460.

    Article  PubMed  PubMed Central  Google Scholar 

  • Pfefferbaum, A., Adalsteinsson, E., Rohlfing, T., & Sullivan, E. V. (2009). MRI estimates of brain iron concentration in normal aging: comparison of field-dependent (FDRI) and phase (SWI) methods. NeuroImage, 47(2), 493–500.

    Article  PubMed  PubMed Central  Google Scholar 

  • Pfefferbaum, A., Adalsteinsson, E., Rohlfing, T., & Sullivan, E. V. (2010). Diffusion tensor imaging of deep gray matter brain structures: effects of age and iron concentration. Neurobiology of Aging, 31(3), 482–493.

    Article  PubMed  PubMed Central  Google Scholar 

  • Plumet, J., Gil, R., & Gaonac’h, D. (2005). Neuropsychological assessment of executive functions in women: effects of age and education. Neuropsychology, 19(5), 566–577.

    Article  PubMed  Google Scholar 

  • Randolph, C. C., Tireney, M. C., Mohr, E. E., & Chase, T. N. (1998). The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS): preliminary clinical validity. Journal of Clinical and Experimental Neuropsychology, 20(3), 310–320. doi:10.1076/jcen.20.3.310.823.

    Article  CAS  PubMed  Google Scholar 

  • Rathi, Y., Pasternak, O., Savadjiev, P., Michailovich, O., Bouix, S., Kubicki, M., & Shenton, M. E. (2013). Gray matter alterations in early aging: a diffusion magnetic resonance imaging study. Human Brain Mapping, 35(8), 3841–3856. doi:10.1002/hbm.22441.

    Article  PubMed  PubMed Central  Google Scholar 

  • Ray, K. M., Wang, H., Chu, Y., Chen, Y. F., Bert, A., Hasso, A. N., & Su, M. Y. (2006). Mild cognitive impairment: apparent diffusion coefficient in regional gray matter and white matter structures 1. Radiology, 241(1), 197–205.

    Article  PubMed  Google Scholar 

  • Resnick, S. M., Pham, D. L., Kraut, M. A., Zonderman, A. B., & Davatzikos, C. (2003). Longitudinal magnetic resonance imaging studies of older adults: a shrinking brain. The Journal of Neuroscience, 23, 3295–3301.

    CAS  PubMed  Google Scholar 

  • Rossini, P. M., Rossi, S., Babiloni, C., & Polich, J. (2007). Clinical neurophysiology of aging brain: from normal aging to neurodegeneration. Progress in Neurobiology, 83(6), 375–400.

    Article  CAS  PubMed  Google Scholar 

  • Salminen, L. E., Schofield, P. R., Pierce, K. D., Conturo, T. E., Tate, D. F., Lane, E. M., & Paul, R. H. (2014). Impact of the AGTR1 A1166C polymorphism on subcortical hyperintensities and cognition in healthy older adults. Age, 36(4), 1–8. doi:10.1007/s11357-014-9664-x.

    Article  CAS  Google Scholar 

  • Sexton, C. E., Kalu, U. G., Filippini, N., Mackay, C. E., & Ebmeier, K. P. (2011). A meta-analysis of diffusion tensor imaging in mild cognitive impairment and alzheimer’s disease. Neurobiology of Aging, 32(12), 2322.e5–2322.e18. doi:10.1016/j.neurobiolaging.2010.05.019.

    Article  Google Scholar 

  • Shaw, T. G., Mortel, K. F., Meyer, J. S., Rogers, R. L., Hardenberg, J., & Cutaia, M. M. (1984). Cerebral blood flow changes in benign aging and cerebrovascular disease. Neurology, 34(7), 855.

    Article  CAS  PubMed  Google Scholar 

  • Sullivan, E. V., & Pfefferbaum, A. (2006). Diffusion tensor imaging and aging. Neuroscience and Biobehavioral Reviews, 30(6), 749–761.

    Article  PubMed  Google Scholar 

  • Sundgren, P. C., Dong, Q., Gomez-Hassan, D., Mukherji, S. K., Maly, P., & Welsh, R. (2004). Diffusion tensor imaging of the brain: review of clinical applications. Neuroradiology, 46(5), 339–350.

    Article  CAS  PubMed  Google Scholar 

  • Tamnes, C. K., Walhovd, K. B., Dale, A. M., Østby, Y., Grydeland, H., Richardson, G., & Fjell, A. M. (2013). Brain development and aging: overlapping and unique patterns of change. NeuroImage, 68, 63–74.

    Article  PubMed  Google Scholar 

  • Trenkle, D. L., Shankle, W. R., & Azen, S. P. (2007). Detecting cognitive impairment in primary care: performance assessment of three screening instruments. Journal of Alzheimer’s Disease, 11(3), 323–335.

    PubMed  Google Scholar 

  • Wald, L. L. (2012). The future of acquisition speed, coverage, sensitivity, and resolution. NeuroImage, 62(2), 1221–1229.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wang, Y., Wang, Q., Haldar, J. P., Yeh, F. C., Xie, M., Sun, P., & Song, S. K. (2011). Quantification of increased cellularity during inflammatory demyelination. Brain, 134(12), 3590–3601.

    Article  PubMed  Google Scholar 

  • Westlye, L. T., Walhovd, K. B., Dale, A. M., Bjørnerud, A., Due-Tønnessen, P., Engvig, A., & Fjell, A. M. (2010). Life-span changes of the human brain white matter: diffusion tensor imaging (DTI) and volumetry. Cerebral Cortex, 20(9), 2055–2068.

  • Yoshiura, T., Noguchi, T., Hiwatashi, A., Togao, O., Yamashita, K., Nagao, E., & Honda, H. (2010). Intra- and interhemispheric variations of diffusivity in subcortical white matter in normal human brain. European Radiology, 20(1), 227–233. doi:10.1007/s00330-009-1534-z.

    Article  PubMed  Google Scholar 

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Acknowledgments

This work was supported by the National Institutes of Health/National Institute of Neurological Disorders and Stroke [grant numbers R01NS052470, R01NS039538]; the National Institutes of Health/National Institute of Mental Health [grant number R21MH090494]; and the Australian National Health and Medical Research Council [grant number 1037196]. Recruitment database searches were supported in part by the National Institutes of Health/National Center for Research Resources [grant number UL1 TR000448].

Conflict of interest

L. Salminen, T. Conturo, D. Laidlaw, R. Cabeen, E. Akbudak, E. Lane, J. Heaps, J. Bolzenius, L. Baker, S. Cooley, S. Scott, L. Cagle, S. Phillips, and R. Paul declare no conflicts of interest.

Informed Consent

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, and the applicable revisions at the time of the investigation. Informed consent was obtained from all patients for being included in the study.

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  1. Department of Psychology, University of Missouri- Saint Louis, 1 University Boulevard, Stadler Hall 442 A, Saint Louis, MO, 63121, USA

    Lauren E. Salminen, Jacob D. Bolzenius, Laurie M. Baker, Sarah Cooley, Staci Scott, Lee M. Cagle, Sarah Phillips & Robert H. Paul

  2. Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway, St. Louis, MO, 63110, USA

    Thomas E. Conturo & Erbil Akbudak

  3. Computer Science Department, Brown University, Providence, RI, 02912, USA

    David H. Laidlaw & Ryan P. Cabeen

  4. Vanderbilt University Medical Center, 1211 Medical Center Drive, Nashville, TN, 37232, USA

    Elizabeth M. Lane

  5. Missouri Institute of Mental Health, 4633 World Parkway Circle, Berkeley, MO, 63134-3115, USA

    Jodi M. Heaps & Robert H. Paul

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  1. Lauren E. Salminen
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Salminen, L.E., Conturo, T.E., Laidlaw, D.H. et al. Regional age differences in gray matter diffusivity among healthy older adults. Brain Imaging and Behavior 10, 203–211 (2016). https://doi.org/10.1007/s11682-015-9383-7

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