Advertisement

Brain Imaging and Behavior

, Volume 13, Issue 5, pp 1246–1254 | Cite as

Regional leukoaraiosis and cognition in non-demented older adults

  • Margaret E. Wiggins
  • Jared Tanner
  • Nadine Schwab
  • Samuel J. Crowley
  • Ilona Schmalfuss
  • Babette Brumback
  • David J. Libon
  • Kenneth Heilman
  • Catherine C. PriceEmail author
Original Research

Abstract

Frontal lobe-executive functions are heavily dependent on distal white matter connectivity. Even with healthy aging there is an increase in leukoaraiosis that might interrupt this connectivity. The goal of this study is to learn 1) the location, depth, and percentage of leukoaraiosis in white matter among a sample of non-demented older adults and 2) associations between these leukoarioasis metrics and composites of cognitive efficiency (processing speed, working memory, and inhibitory function), and episodic memory. Participants were 154 non-demented older adults (age range 60–85) who completed a brain MRI and neuropsychological testing on the same day. Brain MRIs were segmented via Freesurfer and white matter leukoaraiosis depth segmentations was based on published criteria. On average, leukoaraiosis occupied 1 % of total white matter. There was no difference in LA distribution in the frontal (1.12%), parietal (1.10%), and occipital (0.95%) lobes; there was less LA load within the temporal lobe (0.23%). For cortical depth, leukoaraiosis was predominantly in the periventricular region (3.39%; deep 1.46%, infracortical 0.15%). Only increasing frontal lobe and periventricular leukoaraiosis were associated with a reduction in processing speed, working memory, and inhibitory function. Despite the general presence of LA throughout the brain, only frontal and periventricular LA contributed to the speeded and mental manipulation of executive functioning. This study provides a normative description of LA for non-demented adults to use as a comparison to more disease samples.

Keywords

Brain aging Hyperintensities White matter alterations Frontal lobes Executive function Episodic memory 

Notes

Acknowledgements

Margaret E Wiggins, Jared Tanner, Nadine Schwab, Samuel J Crowley, Loren P Hizel, Ilona Schmalfuss, Babette Brumback, David J Libon, Kenneth Heilman, and Catherine C Price declare that they have no conflicts of interest.

We sincerely thank the research participants involved in this investigation. This work was supported by the National Institute of Neurological Disorders and Stroke (R01NS082386); and the National Institute of Nursing Research (R01NR01481).

Compliance with ethical standards

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.

Supplementary material

11682_2018_9938_MOESM1_ESM.docx (88 kb)
ESM 1 (DOCX 88 kb)

References

  1. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.CrossRefGoogle Scholar
  2. Amici, S., Ogar, J., Brambati, S. M., Miller, B. L., Neuhaus, J., Dronkers, N. L., & Gorno-Tempini, M. L. (2007). Performance in specific language tasks correlates with regional volume changes in progressive aphasia. Cognitive and Behavioral Neurology, 20(4), 203–211.  https://doi.org/10.1097/WNN.0b013e31815e6265.CrossRefGoogle Scholar
  3. Annweiler, C., Annweiler, T., Bartha, R., Hermann, F. R., Camicioli, R., & Beauchet, O. (2014). Vitamin d and white matter abnormalities in older adults: A cross-sectional neuroimaging study. Medical Biophysics Publications, 21, 1436–1442.  https://doi.org/10.1111/ene.12511.Google Scholar
  4. Brandt, J., & Benedict, R. H. B. (2001). Hopkins verbal learning test—Revised. Professional manual. Lutz, FL: Psychological Assessment Resources, Inc..Google Scholar
  5. Brandt, J., Spencer, M., & Folstein, M. (1988). The telephone interview for cognitive status. Neuropsychiatry, Neuropsychology, and Behavioral Neurology, 1(2), 111–117.Google Scholar
  6. Breteler, M. M., van Swieten, J. C., Bots, M. L., Grobbee, D. E., Claus, J. J., van den Hout, J. H., et al. (1994). Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study: The Rotterdam study. Neurology, 44(7), 1246–1252.CrossRefGoogle Scholar
  7. Brickman, A. M., Provenzano, F. A., Muraskin, J., Manly, J. J., Blum, S., Apa, Z., et al. (2012). Regional white matter hyperintensity volume, not hippocampal atrophy, predicts incident Alzheimer disease in the community. Archives of Neurology, 69(12), 1621–1627.  https://doi.org/10.1001/archneurol.2012.1527.CrossRefGoogle Scholar
  8. Charlson, M., Szatrowski, T. P., Peterson, J., & Gold, J. (1994). Validation of a combined comorbidity index. Journal of Clinical Epidemiology, 47(11), 1245–1251.CrossRefGoogle Scholar
  9. Corrigan, J. D., Agresti, A. A., & Hinkeldey, N. S. (1987). Psychometric characteristics of the category test: Replication and extension. Journal of Clinical Psychology, 43, 368–376.CrossRefGoogle Scholar
  10. Del Bene, A., Ciolli, L., Borgheresi, L., Poggesi, A., Inzitari, D., & Pantoni, L. (2015). Is type 2 diabetes related to leukoaraiosis? An updated review. Acta Neurologica Scandinavica, 132(3), 147–155.CrossRefGoogle Scholar
  11. Devanand, D. P., Pradhaban, G., Lui, X., Khandji, A., De Santi, S., Segal, S., et al. (2007). Hippocampal and entorhinal atrophy in mild cognitive impairment prediction of Alzheimer disease. Neurology, 68(11), 828–836.  https://doi.org/10.1212/01.wnl.0000256697.20968.d7.CrossRefGoogle Scholar
  12. Erkinjuntti, T., Inzitari, D., Pantoni, L., Wallin, A., Scheltens, P., Rockwood, K., Roman, G. C., Chui, H., & Desmond, D. W. (2000). Research criteria for subcortical vascular dementia in clinical trials. Journal of Neural Transmission, 59, 23–30.Google Scholar
  13. Fernández, G., Effern, A., Grunwald, T., Pezer, N., Lehnertz, K., Dümpelmann, M., et al. (1999). Real-time tracking of memory formation in the human rhinal cortex and hippocampus. Science, 285(5433), 1582–1585.CrossRefGoogle Scholar
  14. Fischl, B. (2012). Freesurfer. Neuroimage, 62, 774–781.CrossRefGoogle Scholar
  15. Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., & Haselgrove, C. (2002). Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron, 33(3), 341–355.CrossRefGoogle Scholar
  16. Fukui, T., Sugita, K., Sato, Y., Takeuchi, T., & Tsukagoshi, H. (1994). Cognitive functions in subjects with incidental cerebral hyperintensities. European Neurology, 34(5), 272–276.CrossRefGoogle Scholar
  17. Fuster, J. M. (1985). The prefrontal cortex, mediator of cross-temporal contingencies. Human Neurobiology, 4(3), 169–179.Google Scholar
  18. de Groot, J. C., de Leeuw, F. E., Oudkerk, M., van Gijn, J., Hofman, A., Jolles, J., & Breteler, M. M. (2000). Cerebral white matter lesions and cognitive function: The Rotterdam scan study. Annals of Neurology, 47, 145–151.CrossRefGoogle Scholar
  19. Hachinski, V. C., Potter, P., & Merskey, H. (1986). Leuko-araiosis: An ancient term for a new problem. Le Journal Canadien des Sciences Neurologiques, 13, 533–534.Google Scholar
  20. Hachinski, V. C., Potter, P., & Merskey, H. (1987). Leuko-araiosis. Archives of Neurology, 44, 21–23.CrossRefGoogle Scholar
  21. Heaton, R., Miller, W., Taylor, M., & Grant, I. (2004). Revised comprehensive norms for an expanded Halstead-Reitan battery: Demographically adjusted neuropsychological norms for African American and Caucasian adults. Lutz, FL: Psychological Assessment Resources, Inc..Google Scholar
  22. Hogervorst, E., Ribiero, H. M., Molyneux, A., Budge, M., & Smith, A. D. (2002). Plasma homocysteine levels, cerebrovascular risk factors, and cerebral white matter changes (leukoaraiosis) in patients with Alzheimer disease. Archives of Neurology, 59(5), 788–793.CrossRefGoogle Scholar
  23. Jak, A. J., Bondi, M. W., Delano-Wood, L., Wierenga, C., Corey-Bloom, J., Salmon, D. P., & Delis, D. C. (2009). Quantification of five neuropsychological approaches to defining mild cognitive impairment. The American Journal of Geriatric Psychiatry, 17(5), 368–375.CrossRefGoogle Scholar
  24. Jenkinson, M., Beckmann, C. F., Behrens, T. E., Woolrich, M. W., & Smith, S. M. (2012). FSL. Neuroimage, 62, 782–790.CrossRefGoogle Scholar
  25. Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002) Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage, 17, 825–841.Google Scholar
  26. Junqué, C., Jesús, P., Vandrell, P., Bruna, O., Jódar, M., Ribas, J., et al. (1990). Leuko-araiosis on magnetic resonance imaging and speed of mental processing. Archives of Neurology, 47(2), 151–156.  https://doi.org/10.1001/archneur.1990.00530020047013.CrossRefGoogle Scholar
  27. Lamar, M., Price, C. C., Giovannetti, T., Swenson, R., & Libon, D. J. (2009/2010). The dysexecutive syndrome associated with ischaemic vascular disease and related subcortical neuropathology: A Boston process approach. Behavioral Neurology, 22, 53–62.  https://doi.org/10.3233/BEN-2009-0237.CrossRefGoogle Scholar
  28. Lawton, M. P., & Brody, E. M. (1969). Assessment of older people: Self-maintaining and instrumental activities of daily living. The Gerontologist, 9(3), 179–186.CrossRefGoogle Scholar
  29. Leskelä, M., Hietanen, M., Kalska, H., Ylikoski, R., Pohjasvaara, T., Mäntylä, R., & Erkinjuntti, T. (1999). Executive functions and speed of mental processing in elderly patients with frontal or nonfrontal ischemic stroke. European Journal of Neurology, 6(6), 653–661.CrossRefGoogle Scholar
  30. Lezak, M. D., Howieson, D., Bigler, E., & Tranel, D. (2012). Neuropsychological Assessment (5th Ed.). New York: Oxford University press.Google Scholar
  31. Liao, D., Cooper, L., Cai, J., Toole, J. F., Bryan, N. R., Hutchinson, R. G., & Tyroler, H. A. (1996). Presence and severity of cerebral white matter lesions and hypertension, its treatment, and its control. The ARIC Study. Stroke, 27, 2262–2270.  https://doi.org/10.1161/01.STR.27.12.2262.CrossRefGoogle Scholar
  32. Libon, D. J., Price, C. C., Garrett, K. D., & Giovannetti, T. (2004). From Binswanger’s disease to leukoaraiosis: What we have learned about subcortical vascular dementia. The Clinical Neuropsychologist, 18, 83–100.  https://doi.org/10.1080/13854040490507181.CrossRefGoogle Scholar
  33. Libon, D., Price, C. C., Giovannetti, T., Swenson, R., Bettcher, B. M., Heilman, K., & Pennisi, A. (2008). Linking MRI hyperintensities with patterns of neuropsychological impairment: Evidence for a threshold effect. Stroke, 39, 806–813.  https://doi.org/10.1161/STROKEAHA.107.489997.CrossRefGoogle Scholar
  34. Lindemer, E. R., Greve, D. N., Fischl, B. R., Augustinack, J. C., & Salat, D. H. (2017). Regional staging of white matter signal abnormalities in aging and Alzheimer’s disease. Neuroimage: Clinical, 14, 156–165.  https://doi.org/10.1016/j.nicl.2017.01.022.CrossRefGoogle Scholar
  35. Lindgren, A., Roijer, A., Rudling, O., Norrving, B., Larson, E. M., Eskilsson, J., et al. (1994). Cerebral lesions on magnetic resonance imaging, heart disease, and vascular risk factors in subjects without stroke. A population-based study. Stroke, 25(5), 929–934.CrossRefGoogle Scholar
  36. Michielse, S., Coupland, N., Camicioli, R., Carter, R., Seres, P., Sabino, J., & Malykhin, N. (2010). Selective effects of aging on brain white matter microstructure: A diffusion tensor imaging tractography study. NeuroImage, 52(4), 1190–1201.CrossRefGoogle Scholar
  37. Price, C. C., Jefferson, A. L., Merino, J. G., Heilman, K. M., & Libon, D. J. (2005). Subcortical vascular dementia: Integrating neuropsychological and neuroradiologic data. Neurology, 65(3), 376–382.  https://doi.org/10.1212/01.wnl.0000168877.06011.15.CrossRefGoogle Scholar
  38. Price, C. C., Mitchell, S. M., Brumback, B., Tanner, J. J., Schmalfuss, I., Lamar, M., et al. (2012). MRI-leukoaraiosis thresholds and the phenotypic expression of dementia. Neurology, 79, 734–740.CrossRefGoogle Scholar
  39. Price, C. C., Tanner, J. J., Schmalfuss, I. M., Brumback, B., Heilman, K. M., & Libon, D. J. (2015). Dissociating statistically-determined Alzheimer’s disease/vascular dementia neuropsychological syndromes using white and gray Neuroradiological parameters. Journal of Alzheimer’s Disease, 48(3), 833–847.CrossRefGoogle Scholar
  40. Reitan, R. M. (1958). Validity of the trail making test as an indicator of organic brain damage. Perceptual and Motor Skills, 8, 271–276.CrossRefGoogle Scholar
  41. Schmidt, R., Fazekas, F., Offenbacher, H., Dusek, T., Zach, E., Reinhard, B., et al. (1993). Neuropsychologic correlates of MRI white matter hyperintensities: A study of 150 normal volunteers. Neurology, 43(12), 2490–2494.CrossRefGoogle Scholar
  42. Schmidt, R., Fazekas, F., Kapeller, P., Schmidt, H., & Hartung, H. P. (1999). MRI white matter hyperintensities: Three-year follow-up of the Austrian stroke prevention study. Neurology, 53(1), 132–139.CrossRefGoogle Scholar
  43. Spilt, A., Goekoop, R., Westendorp, R. G., Blauw, G. J., de Craen, A. J., & van Buchem, M. A. (2006). Not all age-related white matter hyperintensities are the same: A magnetization transfer imaging study. American Journal of Neuroradiology, 27(9), 1964–1968.Google Scholar
  44. Stout, J. C., Jernigan, T. L., Archibald, S. L., & Salmon, D. P. (1996). Association of dementia severity with cortical gray matter and abnormal white matter volumes in dementia of the Alzheimer type. Archives of Neurology, 53(8), 742–749.CrossRefGoogle Scholar
  45. Stuss, D. T. (2011). Functions of the frontal lobes: Relation to executive functions. Journal of the International Neuropsychological Society, 17(5), 759–765.CrossRefGoogle Scholar
  46. Tabert, M. H., Manly, J. J., Lui, X., Pelton, G. H., Rosenblum, S., Jacobs, M., et al. (2006). Neuropsychological prediction of conversion to Alzheimer disease in patients with mild cognitive impairment. Archives of General Psychiatry, 63(8), 916–924.  https://doi.org/10.1001/archpsyc.63.8.916.CrossRefGoogle Scholar
  47. Tomimoto, H., Ohtani, R., Wakita, H., Lin, J. X., Ihara, M., Miki, Y., et al. (2006). Small artery dementia in Japan: Radiological differences between CADASIL, leukoaraiosis and Binswanger's disease. Dementia and Geriatric Cognitive Disorders, 21(3), 169–169.  https://doi.org/10.1159/000090677.CrossRefGoogle Scholar
  48. Tosto, G., Zimmerman, M. E., Carmichael, O. T., & Brickman, A. M. (2014). Predicting aggressive decline in mild cognitive impairment: The importance of white matter hyperintensities. JAMA Neurology, 71(7), 872–877.  https://doi.org/10.1001/jamaneurol.2014.667.CrossRefGoogle Scholar
  49. Tosto, G., Zimmerman, M. E., Hamilton, J. L., Carmichael, O. T., & Brickman, A. M. (2015). The effect of white matter hyperintensities on neurodegeneration in mild cognitive impairment. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 11(12), 1510–1519.  https://doi.org/10.1016/j.jalz.2015.05.014.CrossRefGoogle Scholar
  50. Van der Werf, Y. D., Scheltens, P., Lindeboom, J., Witter, M. P., Uylings, H. B., & Jolles, J. (2003). Deficits of memory, executive functioning and attention following infarction in the thalamus; a study of 22 cases with localized lesions. Neuropsychologia, 41(10), 1330–1344.CrossRefGoogle Scholar
  51. Wang, L., Leonards, C. O., Sterzer, P., & Ebinger, M. (2014). White matter lesions and depression: A systematic review and meta-analysis. Journal of Psychiatric Research, 56, 56–64.CrossRefGoogle Scholar
  52. Wechsler, D. (1997). Wechsler memory scale (WMS-III) (Vol. 14). San Antonio, TX: Psychological corporation.Google Scholar
  53. Wolk, D. A., & Dickerson, B. C. (2011). Fractionating verbal episodic memory in Alzheimer’s disease. Neuroimage, 54, 1530–1539.CrossRefGoogle Scholar
  54. Yesavage, J. A., Brink, T. L., Rose, T. L., Lum, O., Huang, V., Adey, M., & Leirer, V. O. (1982). Development and validation of a geriatric depression screening scale: A preliminary report. Journal of Psychiatric Research, 17(1), 37–49.CrossRefGoogle Scholar
  55. Ylikoski, R., Ylikoski, A., Erkinjuntti, T., Sulkava, R., Raininko, R., & Tilvis, R. (1993). White matter changes in healthy elderly persons correlate with attention and speed of mental processing. Archives of Neurology, 50(8), 818–824.CrossRefGoogle Scholar
  56. Zimmerman, R. D., Fleming, C. A., & Lee, B. C. (1986). Periventricular hyperintensity as seen by magnetic resonance: Prevalence and significance. American Journal of Roentgenology, 146(3), 443–450.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Margaret E. Wiggins
    • 1
  • Jared Tanner
    • 1
  • Nadine Schwab
    • 1
  • Samuel J. Crowley
    • 1
  • Ilona Schmalfuss
    • 2
  • Babette Brumback
    • 3
  • David J. Libon
    • 4
  • Kenneth Heilman
    • 5
  • Catherine C. Price
    • 1
    Email author
  1. 1.Clinical and Health PsychologyUniversity of FloridaGainesvilleUSA
  2. 2.Radiology, University of Florida College of MedicineGainesvilleUSA
  3. 3.Biostatistics, University of FloridaGainesvilleUSA
  4. 4.Departments of Geriatric and Gerontology and Psychology, School of Osteopathic MedicineRowan UniversityStratfordUSA
  5. 5.Neurology, University of Florida College of MedicineGainesvilleUSA

Personalised recommendations