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Periventricular white matter hyperintensities and the risk of dementia: a CREDOS study

Published online by Cambridge University Press:  27 July 2015

Sangha Kim ,
Seong Hye Choi ,
Young Min Lee ,
Min Ji Kim ,
Young Don Kim ,
Jin Young Kim ,
Jin Hong Park ,
Woojae Myung ,
Hae Ri Na  and
Hyun Jeong Han
...Show all authors
Sangha Kim
Affiliation:
Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
Seong Hye Choi
Affiliation:
Department of Neurology, Inha University School of Medicine, Incheon, South Korea
Young Min Lee
Affiliation:
Department of Psychiatry, Busan National University Hospital, Busan, South Korea
Min Ji Kim
Affiliation:
Biostatistics Team, Samsung Biomedical Research Institute, Seoul, South Korea
Young Don Kim
Affiliation:
Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
Jin Young Kim
Affiliation:
Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
Jin Hong Park
Affiliation:
Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
Woojae Myung
Affiliation:
Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
Hae Ri Na
Affiliation:
Department of Neurology, Bobath Memorial Hospital, Seongnam, South Korea
Hyun Jeong Han
Affiliation:
Department of Neurology, Dementia and Neurocognitive center, Myongji Hospital, Goyang, South Korea
Yong S. Shim
Affiliation:
Department of Neurology, Bucheon St. Mary's Hospital, The Catholic Univerisy of Korea, School of Medicine, Bucheon, South Korea
Jong Hun Kim
Affiliation:
Department of Neurology, National Health Insurance Corporation Ilsan Hospital, Goyang, South Korea
Soo Jin Yoon
Affiliation:
Department of Neurology, Eulji University College of Medicine, Daejeon, South Korea
Sang Yun Kim
Affiliation:
Department of Neurology, Seoul National University Bundang Hospital, Seongnam, South Korea
Doh Kwan Kim*
Affiliation:
Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
*
Correspondence should be addressed to: Professor Doh Kwan Kim, MD, PhD., Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, 135-710, South Korea. Phone: +822-3410-3582; Fax: +822-3410-0941. Email: [email protected].
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Abstract

Background:

Cerebral white matter hyperintensities (WMH) are prevalent incident findings on brain MRI scans among elderly people and have been consistently implicated in cognitive dysfunction. However, differential roles of WMH by region in cognitive function are still unclear. The aim of this study was to ascertain the differential role of regional WMH in predicting progression from mild cognitive impairment (MCI) to different subtypes of dementia.

Methods:

Participants were recruited from the Clinical Research Center for Dementia of South Korea (CREDOS) study. A total of 622 participants with MCI diagnoses at baseline and follow-up evaluations were included for the analysis. Initial MRI scans were rated for WMH on a visual rating scale developed for the CREDOS. Differential effects of regional WMH in predicting incident dementia were evaluated using the Cox proportional hazards model.

Results:

Of the 622 participants with MCI at baseline, 139 patients (22.3%) converted to all-cause dementia over a median of 14.3 (range 6.0–36.5) months. Severe periventricular WMH (PWMH) predicted incident all-cause dementia (Hazard ratio (HR) 2.22; 95% confidence interval (CI) 1.43–3.43) and Alzheimer's disease (AD) (HR 1.86; 95% CI 1.12–3.07). Subcortical vascular dementia (SVD) was predicted by both PWMH (HR 16.14; 95% CI 1.97–132.06) and DWMH (HR 8.77; 95% CI 1.77–43.49) in more severe form (≥ 10 mm).

Conclusions:

WMH differentially predict dementia by region and severity. Our findings suggest that PWMH may play an independent role in the pathogenesis of dementia, especially in AD.

Keywords

mild cognitive impairmentdementiawhite matter hyperintensityAlzheimer’s diseasesubcortical vascular dementia
Type
Research Article
Information
International Psychogeriatrics , Volume 27 , Issue 12 , December 2015 , pp. 2069 - 2077
Copyright
Copyright © International Psychogeriatric Association 2015 

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References

Ahn, H. J. et al. (2010). Seoul neuropsychological screening battery-dementia version (SNSB-D): a useful tool for assessing and monitoring cognitive impairments in dementia patients. Journal of Korean Medical Science, 25, 1071–1076. doi:10.3346/jkms.2010.25.7.1071.CrossRefGoogle ScholarPubMed
American Psychiatric Association (1994). Diagnostic and Statistical Manual of Mental Disorders. Washington, DC: American Psychiatric Assocation.Google Scholar
Armstrong, R. J. and Barker, R. A. (2001). Neurodegeneration: a failure of neuroregeneration? Lancet, 358, 1174–1176. doi:10.1016/s0140-6736(01)06260-2.Google Scholar
Bae, J. N. and Cho, M. J. (2004). Development of the Korean version of the Geriatric Depression Scale and its short form among elderly psychiatric patients. Journal of Psychosomatic Research, 57, 297–305. doi:10.1016/j.jpsychores.2004.01.004.Google Scholar
Brickman, A. M. et al. (2012). Regional white matter hyperintensity volume, not hippocampal atrophy, predicts incident Alzheimer disease in the community. Archives of Neurology, 69, 1621–1627. doi:10.1001/archneurol.2012.1527.CrossRefGoogle Scholar
Busse, A., Hensel, A., Guhne, U., Angermeyer, M. C. and Riedel-Heller, S. G. (2006). Mild cognitive impairment: long-term course of four clinical subtypes. Neurology, 67, 2176–2185. doi:10.1212/01.wnl.0000249117.23318.e1.Google Scholar
Curtis, M. A., Faull, R. L. and Eriksson, P. S. (2007). The effect of neurodegenerative diseases on the subventricular zone. Nature Reviews: Neuroscience, 8, 712–723. doi:10.1038/nrn2216.Google Scholar
Desai, M. K., Sudol, K. L., Janelsins, M. C., Mastrangelo, M. A., Frazer, M. E. and Bowers, W. J. (2009). Triple-transgenic Alzheimer's disease mice exhibit region-specific abnormalities in brain myelination patterns prior to appearance of amyloid and tau pathology. Glia, 57, 54–65. doi:10.1002/glia.20734.Google Scholar
Erkinjuntti, T. (2002). Subcortical vascular dementia. Cerebrovascular Diseases, 13 (Suppl. 2), 58–60. doi:49152.Google Scholar
Gage, F. H. (2000). Mammalian neural stem cells. Science, 287, 1433–1438.Google Scholar
Hachinski, V. C. et al. (1975). Cerebral blood flow in dementia. Archives of Neurology, 32, 632–637.Google Scholar
Kang, Y., Na, D. L. and Hahn, S. (1997). A validity study on the Korean Mini-Mental State Examination (K-MMSE) in dementia patients. Journal of the Korean Neurological Association, 15, 300–308.Google Scholar
Kim, K. W., MacFall, J. R. and Payne, M. E. (2008). Classification of white matter lesions on magnetic resonance imaging in elderly persons. Biological Psychiatry, 64, 273–280. doi:10.1016/j.biopsych.2008.03.024.Google Scholar
Lee, H. K., Lee, Y. M., Park, J. M., Lee, B. D., Moon, E. S. and Chung, Y. I. (2014). Amnestic multiple cognitive domains impairment and periventricular white matter hyperintensities are independently predictive factors progression to dementia in mild cognitive impairment. International Journal of Geriatric Psychiatry, 29, 526–532. doi:10.1002/gps.4035.Google Scholar
Lin, D. Y., Wei, L. J. and Ying, Z. (1993). Checking the Cox model with cumulative sums of Martingale-based residuals. Biometrika, 80, 557–572.CrossRefGoogle Scholar
McKeith, I. G. et al. (1996). Consensus guidelines for the clinical and pathologic diagnosis of dementia with Lewy bodies (DLB): report of the consortium on DLB international workshop. Neurology, 47, 1113–1124.Google Scholar
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D. and Stadlan, E. M. (1984). Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA work group under the auspices of department of health and human services task force on Alzheimer's disease. Neurology, 34, 939–944.Google Scholar
Moon, S. Y. et al. (2011). Impact of white matter changes on activities of daily living in mild to moderate dementia. European Neurology, 65, 223–230. doi:10.1159/000318161.Google Scholar
Morris, J. C. (1993). The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology, 43, 2412–2414.Google Scholar
Noh, Y. et al. (2014). A new classification system for ischemia using a combination of deep and periventricular white matter hyperintensities. Journal of Stroke and Cerebrovascular Diseases, 23, 636–642. doi:10.1016/j.jstrokecerebrovasdis.2013.06.002.Google Scholar
Park, H. K. et al. (2011). Clinical characteristics of a nationwide hospital-based registry of mild-to-moderate Alzheimer's disease patients in Korea: a CREDOS (clinical research center for dementia of South Korea) study. Journal of Korean Medical Science, 26, 1219–1226. doi:10.3346/jkms.2011.26.9.1219.Google Scholar
Poggesi, A. et al. (2011). 2001–2011: a decade of the LADIS (leukoaraiosis and disability) study: what have we learned about white matter changes and small-vessel disease? Cerebrovascular Diseases, 32, 577–588. doi:10.1159/000334498.Google Scholar
Prins, N. D. et al. (2004). Cerebral white matter lesions and the risk of dementia. Archives of Neurology, 61, 1531–1534. doi:10.1001/archneur.61.10.1531.Google Scholar
Provenzano, F. A. et al. (2013). White matter hyperintensities and cerebral amyloidosis: necessary and sufficient for clinical expression of Alzheimer disease? JAMA Neurology, 70, 455–461. doi:10.1001/jamaneurol.2013.1321.Google Scholar
Roman, G. C. et al. (1993). Vascular dementia: diagnostic criteria for research studies. Report of the NINDS-AIREN International Workshop. Neurology, 43, 250–260.Google Scholar
Schmidt, R. et al. (2011). Heterogeneity in age-related white matter changes. Acta Neuropathologica, 122, 171–185. doi:10.1007/s00401-011-0851-x.CrossRefGoogle ScholarPubMed
Simpson, J. E. et al. (2007). White matter lesions in an unselected cohort of the elderly: astrocytic, microglial and oligodendrocyte precursor cell responses. Neuropathology and Applied Neurobiology, 33, 410–419. doi:10.1111/j.1365-2990.2007.00828.x.Google Scholar
The Lund and Manchester Groups (1994). Clinical and neuropathological criteria for frontotemporal dementia. Journal of Neurology, Neurosurgery and Psychiatry, 57, 416–418.Google Scholar
van Straaten, E. C. et al. (2008). Periventricular white matter hyperintensities increase the likelihood of progression from amnestic mild cognitive impairment to dementia. Journal of Neurology, 255, 1302–1308. doi:10.1007/s00415-008-0874-y.Google Scholar
Verdelho, A. et al. (2010). White matter changes and diabetes predict cognitive decline in the elderly: the LADIS study. Neurology, 75, 160–167. doi:10.1212/WNL.0b013e3181e7ca05.Google Scholar
Vernooij, M. W. et al. (2007). Incidental findings on brain MRI in the general population. New England Journal of Medicine, 357, 1821–1828. doi:10.1056/NEJMoa070972.Google Scholar
Vuorinen, M. et al. (2011). Changes in vascular risk factors from midlife to late life and white matter lesions: a 20-year follow-up study. Dementia and Geriatric Cognitive Disorders, 31, 119–125. doi:10.1159/000323810.CrossRefGoogle ScholarPubMed
Ye, B. S. et al. (2013). Effects of education on the progression of early-versus late-stage mild cognitive impairment. International Psychogeriatrics, 25, 597–606. doi:10.1017/s1041610212002001.Google Scholar
Yoshita, M. et al. (2006). Extent and distribution of white matter hyperintensities in normal aging, MCI, and AD. Neurology, 67, 2192–2198. doi:10.1212/01.wnl.0000249119.95747.1f.Google Scholar
Zhang, Y. et al. (2007). Diffusion tensor imaging of cingulum fibers in mild cognitive impairment and Alzheimer disease. Neurology, 68, 13–19. doi:10.1212/01.wnl.0000250326.77323.01.Google Scholar