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Fractional anisotropy of water diffusion in cerebral white matter across the lifespan

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Kochunov, P., Williamson, D.E., Lancaster, J., Fox, P., Cornell, J., Blangero, J., Glahn, D.C.·2012·Neurobiology of Aging

Abstract

Determining the time of peak of cerebral maturation is vital for our understanding of when cerebral maturation ceases and the cerebral degeneration in healthy aging begins. We carefully mapped changes in fractional anisotropy (FA) of water diffusion for eleven major cerebral white matter tracts in a large group (831) of healthy human subjects aged 11–90. FA is a neuroimaging index of micro-structural white matter integrity, sensitive to age-related changes in cerebral myelin levels, measured using diffusion tensor imaging. The average FA values of cerebral white matter (WM) reached peak at the age 32±6 years. FA measurements for all but one major cortical white matter tract (cortico-spinal) reached peaks between 23 and 39 years of age. The maturation rates, prior to age-of-peak were significantly correlated (r=0.74; p=.01) with the rates of decline, past age-of-peak. Regional analysis of corpus callosum (CC) showed that thinly-myelinated, densely packed fibers in the genu, that connect pre-frontal areas, maturated later and showed higher decline in aging than the more thickly myelinated motor and sensory areas in the body and splenium of CC. Our findings can be summarized as: associative, cerebral WM tracts that reach their peak FA values later in life also show progressively higher age-related decline than earlier maturing motor and sensory tracts. These findings carry multiple and diverse implications for both theoretical studies of the neurobiology of maturation and aging and for the clinical studies of neuropsychiatric disorders.

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Research works printed but not linked: 59

  1. Abe, 2002, Normal aging in the central nervous system: quantitative MR diffusion-tensor analysis, Neurobiol. Aging, 23, 433, 10.1016/S0197-4580(01)00318-9 · DOI · Paper page
  2. Abe, 2008, Aging in the CNS: comparison of gray/white matter volume and diffusion tensor data, Neurobiol. Aging, 29, 102, 10.1016/j.neurobiolaging.2006.09.003 · DOI
  3. Aboitiz, 1992, Brain connections: interhemispheric fiber systems and anatomical brain asymmetries in humans, Biol. Res., 25, 51
  4. Aboitiz, 1992, Fiber composition of the human corpus callosum, Brain Res., 598, 143, 10.1016/0006-8993(92)90178-C · DOI · Paper page
  5. Ashe, 1994, Movement parameters and neural activity in motor cortex and area 5, Cereb. Cortex, 4, 590, 10.1093/cercor/4.6.590 · DOI · Paper page
  6. Bartzokis, 2004, Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer's disease, Neurobiol. Aging, 25, 5, 10.1016/j.neurobiolaging.2003.03.001 · DOI · Paper page
  7. Bartzokis, 2001, Age-related changes in frontal and temporal lobe volumes in men: a magnetic resonance imaging study, Arch. Gen. Psychiatry, 58, 461, 10.1001/archpsyc.58.5.461 · DOI · Paper page
  8. Bartzokis, 1999, MRI evaluation of brain iron in earlier- and later-onset Parkinson's disease and normal subjects, Magn. Reson. Imaging, 17, 213, 10.1016/S0730-725X(98)00155-6 · DOI
  9. Bartzokis, 2003, White matter structural integrity in healthy aging adults and patients with Alzheimer disease: a magnetic resonance imaging study, Arch. Neurol., 60, 393, 10.1001/archneur.60.3.393 · DOI · Paper page
  10. Bartzokis, 2008, Lifespan trajectory of myelin integrity and maximum motor speed, Neurobiol. Aging
  11. Basser, 1994, Focal magnetic stimulation of an axon, IEEE Trans. Biomed. Eng., 41, 601, 10.1109/10.293248 · DOI
  12. Bastos Leite, 2004, Pathological aging of the brain: an overview, Top. Magn. Reson. Imaging, 15, 369, 10.1097/01.rmr.0000168070.90113.dc · DOI
  13. Ben Bashat, 2005, Normal white matter development from infancy to adulthood: comparing diffusion tensor and high b value diffusion weighted MR images, J. Magn. Reson. Imaging, 21, 503, 10.1002/jmri.20281 · DOI
  14. Budde, 2007, Toward accurate diagnosis of white matter pathology using diffusion tensor imaging, Magn. Reson. Med., 57, 688, 10.1002/mrm.21200 · DOI · Paper page
  15. Charlton, 2009, Diffusion Tensor Imaging detects age-related white matter change over a two-year follow-up which is associated with working memory decline, J. Neurol. Neurosurg. Psychiatry
  16. Conturo, 1996, Encoding of anisotropic diffusion with tetrahedral gradients: a general mathematical diffusion formalism and experimental results, Magn. Reson. Med., 35, 399, 10.1002/mrm.1910350319 · DOI · Paper page
  17. De Bellis, 2003, Biologic findings of post-traumatic stress disorder and child maltreatment, Curr. Psychiatry Rep., 5, 108, 10.1007/s11920-003-0027-z · DOI
  18. den Heijer, 2003, Higher estrogen levels are not associated with larger hippocampi and better memory performance, Arch. Neurol., 60, 213, 10.1001/archneur.60.2.213 · DOI
  19. Eberling, 2004, Estrogen- and tamoxifen-associated effects on brain structure and function, Neuroimage, 21, 364, 10.1016/j.neuroimage.2003.08.037 · DOI
  20. Flechsig, 1901, Developmental (myelogenetic) localisation of the cerebral cortex in the human, Lancet, 158, 1027, 10.1016/S0140-6736(01)01429-5 · DOI
  21. Gao, 2009, Temporal and spatial development of axonal maturation and myelination of white matter in the developing brain, AJNR Am. J. Neuroradiol., 30, 290, 10.3174/ajnr.A1363 · DOI · Paper page
  22. Hasan, 2009, Development and aging of the healthy human brain uncinate fasciculus across the lifespan using diffusion tensor tractography, Brain Res., 1276, 67, 10.1016/j.brainres.2009.04.025 · DOI
  23. Hasan, 2009, Diffusion tensor tractography quantification of the human corpus callosum fiber pathways across the lifespan, Brain Res., 1249, 91, 10.1016/j.brainres.2008.10.026 · DOI
  24. Hermoye, 2006, Pediatric diffusion tensor imaging: normal database and observation of the white matter maturation in early childhood, Neuroimage, 29, 493, 10.1016/j.neuroimage.2005.08.017 · DOI · Paper page
  25. Hsu, 2009, Microstructural white matter changes in normal aging: a diffusion tensor imaging study with higher-order polynomial regression models, Neuroimage
  26. Jones, D.K., Horsfield, M.A., Simmons, A., 1999. Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn. Reson. Med. 42(3), 515–525. doi:10.1002/(SICI)1522-2594(199909)42:3<515::AID-MRM14>3.0.CO;2-Q.[pii]. · DOI
  27. Kochunov, 2010, Processing speed is correlated with cerebral health markers in the frontal lobes as quantified by neuro-imaging, Neuroimage, 49, 1190, 10.1016/j.neuroimage.2009.09.052 · DOI
  28. Kochunov, P., Glahn, D., Lancaster, J., Wincker, P., Smith, S., Thompson, P., Almasy, L., Duggirala, R., Fox, P., Blangero, J., 2010b. Genetics of microstructure of cerebral white matter using diffusion tensor imaging, Neuroimage, doi:10.1016/j.neuroimage.2010.01.078. · DOI
  29. Kochunov, 2005, Mapping structural differences of the corpus callosum in individuals with 18q deletions using targetless regional spatial normalization, Hum. Brain Mapp., 24, 325, 10.1002/hbm.20090 · DOI
  30. Kochunov, 2001, Regional spatial normalization: toward an optimal target, J. Comput. Assist. Tomogr., 25, 805, 10.1097/00004728-200109000-00023 · DOI
  31. Kochunov, 2005, Age-related morphology trends of cortical sulci, Hum. Brain Mapp., 26, 210, 10.1002/hbm.20198 · DOI
  32. Kochunov, 2009, Loss of cerebral white matter structural integrity tracks the gray matter metabolic decline in normal aging, Neuroimage, 45, 17, 10.1016/j.neuroimage.2008.11.010 · DOI
  33. Kochunov, 2009, Can structural MRI cerebral health markers track cognitive trends in executive control function during normal maturation and adulthood?, Hum. Brain Mapp., 30, 2581, 10.1002/hbm.20689 · DOI
  34. Konrad, 2009, Correlation of brain white matter diffusion anisotropy and mean diffusivity with reaction time in an oddball task, Neuropsychobiology, 60, 55, 10.1159/000236445 · DOI
  35. Lamantia, 1990, Cytological and quantitative characteristics of four cerebral commissures in the rhesus monkey, J. Comp. Neurol., 291, 520, 10.1002/cne.902910404 · DOI · Paper page
  36. Lehmbeck, 2006, Combining voxel-based morphometry and diffusion tensor imaging to detect age-related brain changes, Neuroreport, 17, 467, 10.1097/01.wnr.0000209012.24341.7f · DOI
  37. Lutz, 2005, Asymmetry of cortical activation during maximum and convenient tapping speed, Neurosci. Lett., 373, 61, 10.1016/j.neulet.2004.09.058 · DOI
  38. McLaughlin, 2007, Diffusion tensor imaging of the corpus callosum: a cross-sectional study across the lifespan, Int. J. Dev. Neurosci., 25, 215, 10.1016/j.ijdevneu.2007.03.008 · DOI
  39. Moseley, 2002, Diffusion tensor imaging and aging—a review, NMR Biomed., 15, 553, 10.1002/nbm.785 · DOI · Paper page
  40. Muetzel, R.L., Collins, P.F., Mueller, B.A., A, M.S., Lim, K.O., Luciana, M. 2008. The development of corpus callosum microstructure and associations with bimanual task performance in healthy adolescents. Neuroimage 39(4), 1918–1925. S1053-8119(07)00956-1 [pii]; doi:10.1016/j.neuroimage.2007.10.018. · DOI
  41. Peters, 2000, Effects of aging on myelinated nerve fibers in monkey primary visual cortex, J. Comp. Neurol., 419, 364, 10.1002/(SICI)1096-9861(20000410)419:3<364::AID-CNE8>3.0.CO;2-R · DOI
  42. Pfefferbaum, 2000, Age-related decline in brain white matter anisotropy measured with spatially corrected echo-planar diffusion tensor imaging, Magn. Reson. Med., 44, 259, 10.1002/1522-2594(200008)44:2<259::AID-MRM13>3.0.CO;2-6 · DOI
  43. Pierpaoli, 1996, Toward a quantitative assessment of diffusion anisotropy, Magn. Reson. Med., 36, 893, 10.1002/mrm.1910360612 · DOI · Paper page
  44. Prins, 2004, Cerebral white matter lesions and the risk of dementia, Arch. Neurol., 61, 1531, 10.1001/archneur.61.10.1531 · DOI · Paper page
  45. Raz, 1997, Selective aging of the human cerebral cortex observed in vivo: differential vulnerability of the prefrontal gray matter, Cereb. Cortex, 7, 268, 10.1093/cercor/7.3.268 · DOI · Paper page
  46. Salat, 2005, Age-related alterations in white matter microstructure measured by diffusion tensor imaging, Neurobiol. Aging, 26, 1215, 10.1016/j.neurobiolaging.2004.09.017 · DOI · Paper page
  47. Salthouse, 2009, When does age-related cognitive decline begin?, Neurobiol. Aging, 30, 507, 10.1016/j.neurobiolaging.2008.09.023 · DOI · Paper page
  48. Schiavone, 2009, Imaging age-related cognitive decline: a comparison of diffusion tensor and magnetization transfer MRI, J. Magn. Reson. Imaging, 29, 23, 10.1002/jmri.21572 · DOI
  49. Smith, 2002, Fast robust automated brain extraction, Hum. Brain Mapp., 17, 143, 10.1002/hbm.10062 · DOI · Paper page
  50. Smith, 2006, Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data, Neuroimage, 31, 1487, 10.1016/j.neuroimage.2006.02.024 · DOI · Paper page
  51. Smith, 2006, Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data, Neuroimage, 10.1016/j.neuroimage.2006.02.024 · DOI · Paper page
  52. Smith, 2007, Acquisition and voxelwise analysis of multi-subject diffusion data with tract-based spatial statistics, Nat. Protoc., 2, 499, 10.1038/nprot.2007.45 · DOI · Paper page
  53. Sullivan, 2001, Equivalent disruption of regional white matter microstructure in ageing healthy men and women, Neuroreport, 12, 99, 10.1097/00001756-200101220-00027 · DOI · Paper page
  54. Sullivan, 2003, Diffusion tensor imaging in normal aging and neuropsychiatric disorders, Eur. J. Radiol., 45, 244, 10.1016/S0720-048X(02)00313-3 · DOI
  55. Ulug, 1995, Correction of motional artifacts in diffusion-weighted images using a reference phase map, Magn. Reson. Med., 34, 476, 10.1002/mrm.1910340327 · DOI
  56. Vernooij, M.W., Ikram, M.A., Vrooman, H.A., Wielopolski, P.A., Krestin, G.P., Hofman, A., Niessen, W.J., Van der Lugt, A., Breteler, M.M., 2009. White matter microstructural integrity and cognitive function in a general elderly population. Arch. Gen. Psychiatry 66(5), 545–53. 66/5/545 [pii]; doi:10.1001/archgenpsychiatry.2009.5. · DOI · Paper page
  57. Wakana, 2004, Fiber tract-based atlas of human white matter anatomy, Radiology, 230, 77, 10.1148/radiol.2301021640 · DOI · Paper page
  58. Witelson, 1989, Hand and sex differences in the isthmus and genu of the human corpus callosum. A postmortem morphological study, Brain, 112, 799, 10.1093/brain/112.3.799 · DOI · Paper page
  59. Xu, 2000, Gender effects on age-related changes in brain structure, AJNR Am. J. Neuroradiol., 21, 112

Cited by

Metadata

Authors
Kochunov, P., Williamson, D. E., Lancaster, J., Fox, P., Cornell, J., Blangero, J., & Glahn, D. C.
Venue
Neurobiology of Aging
Publisher
Elsevier BV
Published
2012-01
Volume
33
Issue
1
Pages
9-20
ISSN
0197-4580 (ISSN-L)
OpenAlex
W2031157309
Cited by
365
References
13
FWCI
13.50
Type
journal article
Language
en
Open access
green
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Funders
  • National Institute of Biomedical Imaging and Bioengineering (K01 EB006395)
  • the National Institute on Alcohol Abuse and Alcoholism (R01AA016274)
  • the National Institute of Mental Health (MH078111, MH0708143 and MH083824)
  • NIMH and NIDA (P20 MH/DA52176)
  • General Clinical Research Core (HSC19940074H)

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