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Metabolic Syndrome is Associated with White Matter Hyperintensity in Stroke Patients

Published online by Cambridge University Press:  07 June 2017

Zheng Zhang ,
Wan-Li Zhang ,
Jia Li  and
Mei-Juan Xiao
Zheng Zhang
Affiliation:
Department of Neurology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China
Wan-Li Zhang
Affiliation:
Department of Neurology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China
Jia Li
Affiliation:
Department of Neurology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China
Mei-Juan Xiao*
Affiliation:
Department of Neurology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China
*
Address for correspondence: Mei-Juan Xiao, Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China. E-mail: [email protected].
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Abstract

Some risk factors of stroke may play a role in white matter hyperintensity (WMH). Metabolic syndrome (MetS) is a recognised risk factor of stroke, but it is controversial whether MetS is also associated with WMH. We examined the association of MetS with the prevalence of WMH in acute stroke patients. We conducted a cross-sectional study in 246 acute ischemia stroke patients. The patients with acute stroke were clinically evaluated, including waistline circumference, blood pressure, glycaemia, serum triglyceride and high density lipoprotein cholesterol level. The degree of WMH was assessed by Fluid-attenuated inversion recovery (FLAIR) sequence of magnetic resonance imaging (MRI) scans. MetS was diagnosed using the criteria by the National Cholesterol Education Adult Treatment Panel III. MetS was the independent variable evaluated in Binary regression analyses. It is found that old age (>60 years old), MetS and smoking were significantly associated with WMH in univariate analysis (p < .05). Spearman rank correlation showed that old age and MetS are related to WMH (r = 0.18, p = .005 and r = 0.18, p = .004, respectively). Hypertension is weakly but not significantly associated with WMH in correlation analysis (r = 0.11, p = .08). In multiple regression analysis, age and MetS remained independently associated with WMH (OR = 7.6, 95% CI 0.2–0.7 and OR = 11.7, 95% CI 0.1–0.5). Hypertension and hyperglycaemia tend to be associated but not significantly with WMH (p = .07, p = .08). Other MetS components such as large waist circumference and dyslipidaemia showed no association with WMH. After adjustment for age, WMH is significantly associated with MetS in stroke patients. Hypertension and hyperglycaemia tend to associated but not significantly with WMH in stroke patients.

Keywords

LeukoaraiosisWMHMetSMRI
Type
Articles
Information
Brain Impairment , Volume 18 , Issue 3 , December 2017 , pp. 277 - 283
Copyright
Copyright © Australasian Society for the Study of Brain Impairment 2017 

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References

Au, R., Massaro, J.M., Wolf, P.A., Young, M.E., Beiser, A., Seshadri, S., . . . DeCarli, C. (2006). Association of white matter hyperintensity volume with decreased cognitive functioning: The framingham heart study. Archives of Neurology, 63 (2), 246–250.Google Scholar
Basile, A.M., Pantoni, L., Pracucci, G., Asplund, K., Chabriat, H., Erkinjuntti, T., . . . LADIS Study Group. (2006). Age, hypertension, and lacunar stroke are the major determinants of the severity of age-related white matter changes. The LADIS (Leukoaraiosis and Disability in the Elderly) study. Cerebrovascular Diseases, 21 (5), 315–322.Google Scholar
Bokura, H., Yamaguchi, S., Iijima, K., Nagai, A., & Oguro, H. (2008). Metabolic syndrome is associated with silent ischemic brain lesions. Stroke, 39 (5), 1607–1609.Google Scholar
Cho, H., Kim, C., Kim, H.J., Ye, B.S., Kim, Y.J., Jung, N.Y., . . . Seo, S.W. (2016). Impact of smoking on neurodegeneration and cerebrovascular disease markers in cognitively normal men. European Journal of Neurology, 23 (1), 110–119.Google Scholar
Choi, H.S., Cho, Y.M., Kang, J.H., Shin, C.S., Park, K.S., & Lee, H.K. (2009). Cerebral white matter hyperintensity is mainly associated with hypertension among the components of metabolic syndrome in Koreans. Clinical Endocrinology, 71 (2), 184–188.Google Scholar
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 (2), 145–151.Google Scholar
de Leeuw, F.E., de Groot, J.C., Achten, E., Oudkerk, M., Ramos, L.M., Heijboer, R., . . . Breteler, M. (2001). Prevalence of cerebral white matter lesions in elderly people: A population based magnetic resonance imaging study. The Rotterdam scan study. Journal of Neurology Neurosurgery and Psychiatry, 70 (1), 9–14.Google Scholar
Dearborn, J.L., Schneider, A.L., Sharrett, A.R., Mosley, T.H., Bezerra, D.C., Knopman, D.S., . . . Gottesman, R.F. (2015). Obesity, insulin resistance, and incident small vessel diseaseon magnetic resonance imaging: Atherosclerosis risk in communities study. Stroke, 46 (11), 3131–3136.Google Scholar
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 ScholarPubMed
Dufouil, C., de Kersaint-Gilly, A., Besançon, V., Levy, C., Auffray, E., Brunnereau, L., . . . Tzourio, C. (2001). Longitudinal study of blood pressure and white matter hyperintensities: The EVA MRI Cohort. Neurology, 56 (7), 921–926.Google Scholar
Furie, K.L., & Smith, E.E. (2007). Metabolic syndrome: A target for preventing leukoaraiosis and age-related dementia? Neurology, 69 (10), 951–952.Google Scholar
Godin, O., Tzourio, C., Maillard, P., Alpérovitch, A., Mazoyer, B., & Dufouil, C. (2009). Apolipoprotein E genotype is related to progression of white matter lesion load. Stroke, 40 (10), 3186–3190.Google Scholar
Hachinski, V.C., Potter, P., & Merskey, H. (1987). Leukoaraiosis. Archives of Neurology, 44 (1), 21–23.Google Scholar
Kapeller, P., Barber, R., Vermeulen, R.J., Adèr, H., Scheltens, P., Freidl, W., . . . European Task Force of Age Related White Matter Changes (2003). Visual rating of age related white matter changes on magnetic resonance imaging: scale comparison, interrater agreement, and correlations with quantitative measurements. Stroke, 34 (2), 441–445.Google Scholar
Knopman, D.S., Mosley, T.H., Catellier, D.J., & Sharrett, A.R. (2005). Atherosclerosis risk in communities (ARIC) study. Cardiovascular risk factors and cerebral atrophy in a middle-aged cohort. Neurology, 65 (6), 876–881.Google Scholar
Kuller, L.H., Longstreth, W.T. Jr, Arnold, A.M., Bernick, C., Bryan, R.N., . . . Beauchamp, N.J. Jr, for the Cardiovascular Health Study Collaborative Research Group (2004). Cardiovascular Health Study Collaborative Research Group. White matter hyperintensity on cranial magnetic resonance imaging: A predictor of stroke. Stroke, 35 (8), 1821–1825.Google Scholar
Kuller, L.H., Margolis, K.L., Gaussoin, S.A., Bryan, N.R., Kerwin, D., Limacher, M., . . . Women's Health Initiative Memory Study Research Group (2010). Relationship of hypertension, blood pressure, and blood pressure control with white matter abnormalities in the women's health initiative memory study (WHIMS)-MRI trial. Journal of Clinical Hypertension (Greenwich), 12 (3), 203–212.Google Scholar
Launer, L.J., Berger, K., Breteler, M.M., Dufouil, C., Fuhrer, R., Giampaoli, S., . . . Hofman, A. (2006). Regional variability in the prevalence of cerebral white matter lesions: An MRI study in 9 European countries (CASCADE). Neuroepidemiology, 26 (1), 23–29.Google Scholar
Liao, D., Cooper, L., Cai, J., Toole, J., Bryan, N., Burke, G., . . . Heiss, G. (1997). The prevalence and severity of white matter lesions, their relationship with age, ethnicity, gender, and cardiovascular disease risk factors: The ARIC study. Neuroepidemiology, 16 (3), 149–162.Google Scholar
Lin, Q., Huang, W.Q., & Tzeng, C.M. (2015). Genetic associations of leukoaraiosis indicate pathophysiological mechanisms in white matter lesions etiology. Reviews in the Neurosciences, 26 (3), 343–358.Google Scholar
Longstreth, W.T. Jr., Manolio, T.A., Arnold, A., Burke, G.L., Bryan, N., Jungreis, C.A., . . . Fried, L. (1996). Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly people. The cardiovascular health study. Stroke, 27 (8), 1274–1282.Google Scholar
Lucatelli, P., Montisci, R., Sanfilippo, R., Sacconi, B., Suri, J.S., Catalano, C., & Saba, L. (2016). Is there an association between leukoaraiosis volume and diabetes? Journal of Neuroradiology, 43 (4), 273–279.Google Scholar
Nandigam, R.N. (2008). Significant association between leukoaraiosis and metabolic syndrome in healthy subjects. Neurology, 71 (3), 227–228.Google Scholar
Nebes, R.D., Vora, I.J., Meltzer, C.C., Fukui, M.B., Williams, R.L., Kamboh, M.I., . . . Reynolds, C.F. 3rd (2001). Relationship of deep white matter hyperintensities and apolipoprotein E genotype to depressive symptoms in older adults without clinical depression. American Journal of Psychiatry, 158 (6), 878–884.Google Scholar
Park, J.H., Ryoo, S., Kim, S.J., Kim, G.M., Chung, C.S., Lee, K.H., & Bang, O.Y. (2012). Differential risk factors for lacunar stroke depending on the MRI (white and red) subtypes of microangiopathy. PLoS One, 7 (9), e44865.Google Scholar
Park, K., Yasuda, N., Toyonaga, S., Nakabayashi, H., Nakasato, M., Nakagomi, T., . . . Shimizu, K. (2007). Significant association between leukoaraiosis and metabolic syndrome in healthy subjects. Neurology, 69 (10), 974–978.Google Scholar
Roriz-Filho, J.S., Sá-Roriz, T.M., Rosset, I., Camozzato, A.L., Santos, A.C., Chaves, M.L., . . . Roriz-Cruz, M. (2009). (Pre)diabetes, brain aging, and cognition. Biochimica et Biophysica Acta, 1792 (5), 432–443.Google Scholar
Rozanski, M., Richter, T.B., Grittner, U., Endres, M., Fiebach, J.B., & Jungehulsing, G.J. (2014). Elevated levels of hemoglobin A1c are associated with cerebral white matter disease in patients with stroke. Stroke, 45 (4), 1007–1011.Google Scholar
Tiehuis, A.M., van der Graaf, Y., Mali, W.P., Vincken, K., Muller, M., & Geerlings, M.I. (2014). SMART Study Group. Metabolic syndrome, prediabetes, and brain abnormalities on MRI in patients with manifest arterial disease: The SMART-MR study. Diabetes Care, 37 (9), 2515–2521.Google Scholar
Turk, M., Zaletel, M., & Pretnar-Oblak, J. (2016). Ratio between carotid artery stiffness and blood flow – a new ultrasound index of ischemic leukoaraiosis. Clinical Interventions in Aging, 5, 65–71.CrossRefGoogle Scholar
Varghese, V., Chandra, S.R., Christopher, R., Rajeswaran, J., Prasad, C., Subasree, R., & Issac, T.G. (2016). Factors determining cognitive dysfunction in cerebral small vessel disease. Indian Journal of Psychological Medicine, 38 (1), 56–61.Google Scholar
Wen, W., & Sachdev, P. (2004). The topography of white matter hyperintensities on brain MRI in healthy 60- to 64-year-old individuals. Neuroimage, 22 (1), 144–154.Google Scholar
Willey, J.Z., Gardener, H., Moon, Y.P., Yoshita, M., DeCarli, C., Cheung, Y.K., . . . Wright, C.B. (2014). Lipid profile components and subclinical cerebrovascular disease in the northern Manhattan study. Cerebrovascular Diseases, 37 (6), 423–430.Google Scholar
Zhang, Z., Xiao, M., Ye, Z., Zhang, W., Han, B., & Li, Y. (2015). Noncardiogenic stroke patients with metabolic syndrome have more border-zone infarction and intracranial artery stenosis. Journal of Stroke & Cerebrovascular Diseases, 24 (3), 629–634.Google Scholar