Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-26T21:15:09.553Z Has data issue: false hasContentIssue false
  • English
  • Français

Brain Arterial Diameters and Cognitive Performance: The Northern Manhattan Study

Published online by Cambridge University Press:  23 November 2017

Jose Gutierrez Open the ORCID record for Jose Gutierrez [Opens in a new window] ,
Erin Kulick ,
Yeseon Park Moon ,
Chuanhui Dong ,
Ken Cheung ,
Bagci Ahmet ,
Yaakov Stern ,
Noam Alperin ,
Tatjana Rundek  and
Ralph L. Sacco
...Show all authors
Jose Gutierrez*
Affiliation:
Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York
Erin Kulick
Affiliation:
Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
Yeseon Park Moon
Affiliation:
Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York
Chuanhui Dong
Affiliation:
Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida
Ken Cheung
Affiliation:
Division of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York
Bagci Ahmet
Affiliation:
Department of Radiology, University of Miami Miller School of Medicine, Miami, Florida
Yaakov Stern
Affiliation:
Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York
Noam Alperin
Affiliation:
Department of Radiology, University of Miami Miller School of Medicine, Miami, Florida
Tatjana Rundek
Affiliation:
Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida Neuroscience Program, University of Miami Miller School of Medicine, Miami, Florida
Ralph L. Sacco
Affiliation:
Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida
Clinton B. Wright
Affiliation:
National Institutes of Health, Bethesda, Maryland
Mitchell S.V. Elkind
Affiliation:
Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
*
Correspondence and reprint requests to: Jose Gutierrez, 710 W 168th Street, 6th Floor, Suite 639, New York, NY, 10032. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Objectives: To test the hypothesis that brain arterial diameters are associated with cognitive performance, particularly in arteries supplying domain-specific territories. Methods: Stroke-free participants in the Northern Manhattan Study were invited to have a brain MRI from 2003–2008. The luminal diameters of 13 intracranial arterial segments were obtained using time-of-flight magnetic resonance angiogram (MRA), and then averaged and normalized into a global score and region-specific arterial diameters. Z-Scores for executive function, semantic memory, episodic memory and processing speed were obtained at MRI and during follow-up. Adjusted generalized additive models were used to assess for associations. Results: Among the 1034 participants with neurocognitive testing and brain MRI, there were non-linear relationships between left anterior (ACA) and middle cerebral artery (MCA) diameter and semantic memory Z-scores (χ2=10.00; DF=3; p=.019), and left posterior cerebral artery (PCA) and posterior communicating artery (Pcomm) mean diameter and episodic memory Z-scores (χ2=9.88; DF=3; p=.020). Among the 745 participants who returned for 2nd neuropsychological testing, on average 5.0±0.4 years after their MRI, semantic memory change was associated non-linearly with the left PCA/Pcomm mean diameter (χ2=13.09; DF=3; p=.004) and with the right MCA/ACA mean diameter (χ2=8.43; DF=3; p=.03). In both cross-sectional and longitudinal analyses, participants with the larger brain arterial diameters had more consistently lower Z-scores and greater decline than the rest of the participants. Conclusions: Brain arterial diameters may have downstream effects in brain function presenting as poorer cognition. Identifying the mechanisms and the directionality of such interactions may increase the understanding of the vascular contribution to cognitive impairment and dementia. (JINS, 2018, 24, 335–346)

Keywords

DolichoectasiaVascular remodelingCognitionVascular dementiaArterial dilatationAging
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 24 , Issue 4 , April 2018 , pp. 335 - 346
Copyright
Copyright © The International Neuropsychological Society 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Baldo, J.V., Arévalo, A., Patterson, J.P., & Dronkers, N.F. (2013). Grey and white matter correlates of picture naming: Evidence from a voxel-based lesion analysis of the Boston Naming Test. Cortex, 49(3), 658–667. doi: 10.1016/j.cortex.2012.03.001 Google Scholar
Bouissou, H., Emery, M., & Sorbara, R. (1975). Age related changes of the middle cerebral artery and a comparison with the radial and coronary artery. Angiology, 26(3), 257–268.Google Scholar
Brown, W.R., & Thore, C.R. (2011). Review: Cerebral microvascular pathology in ageing and neurodegeneration. Neuropathology and Applied Neurobiology, 37(1), 56–74. doi: 10.1111/j.1365-2990.2010.01139.x Google Scholar
Bryden, P., & Roy, E. (2005). A new method of administering the Grooved Pegboard Test: Performance as a function of handedness and sex. Brain and Cognition, 58(3), 258–268.Google Scholar
Chmayssani, M., Lazar, R.M., Hirsch, J., & Marshall, R.S. (2009). Reperfusion normalizes motor activation patterns in large-vessel disease. Annals of Neurology, 65(2), 203–208. doi: 10.1002/ana.21554 CrossRefGoogle ScholarPubMed
D’Elia, L., & Satz, P. (1996). Color trails test. Luyz, FL: Psychological Assessment Resources.Google Scholar
de Leeuw, F.E., Richard, F., de Groot, J.C., van Duijn, C.M., Hofman, A., Van Gijn, J., & Breteler, M.M. (2004). Interaction between hypertension, apoE, and cerebral white matter lesions. Stroke, 35(5), 1057–1060. doi: 10.1161/01.str.0000125859.71051.83 Google Scholar
DeCarli, C., Maisog, J., Murphy, D.G., Teichberg, D., Rapoport, S.I., & Horwitz, B. (1992). Method for quantification of brain, ventricular, and subarachnoid CSF volumes from MR images. Journal of Computer Assisted Tomography, 16(2), 274–284.Google Scholar
Duff, K., & Ramezani, A. (2015). Regression-based normative formulae for the repeatable battery for the assessment of neuropsychological status for older adults. Archives of Clinical Neuropsychology, 30(7), 600–604. doi: 10.1093/arclin/acv052 Google Scholar
Duff, K., Schoenberg, M.R., Mold, J.W., Scott, J.G., & Adams, R.L. (2011). Gender differences on the Repeatable Battery for the Assessment of Neuropsychological Status subtests in older adults: Baseline and retest data. Journal of Clinical and Experimental Neuropsychology, 33(4), 448–455. doi: 10.1080/13803395.2010.533156 CrossRefGoogle ScholarPubMed
Echt, D.S., Liebson, P.R., Mitchell, L.B., Peters, R.W., Obias-Manno, D., Barker, A.H., et al. (1991). Mortality and morbidity in patients receiving encainide, flecainide, or placebo. The Cardiac Arrhythmia Suppression Trial. New England Journal of Medicine, 324(12), 781–788. doi: 10.1056/nejm199103213241201 Google Scholar
Forteza, A., Echeverria, Y., Haussen, D.C., Gutierrez, J., Wiley, E., & De Gusmao, C. (2010). Cerebral vasomotor reactivity monitoring in posterior reversible encephalopathy syndrome. BMJ Case Reports, 2010. doi: 10.1136/bcr.10.2009.2345 Google Scholar
Frearson, W., & Eysenck, H.J. (1986). Intelligence, reaction time (RT) and a new ‘odd-man-out’ RT paradigm. Personality and Individual Differences, 7(6), 807–817. doi:http://dx.doi.org/ 10.1016/0191-8869(86)90079-6 Google Scholar
Gorelick, P.B., Scuteri, A., Black, S.E., Decarli, C., Greenberg, S.M., Iadecola, C., & Seshadri, S. (2011). Vascular contributions to cognitive impairment and dementia: A statement for healthcare professionals from the american heart association/american stroke association. Stroke, 42(9), 2672–2713. doi:STR.0b013e3182299496 [pii] 10.1161/STR.0b013e3182299496.CrossRefGoogle ScholarPubMed
Gosling, R.G., & Budge, M.M. (2003). Terminology for describing the elastic behavior of arteries. Hypertension, 41(6), 1180–1182. doi: 10.1161/01.hyp.0000072271.36866.2a Google Scholar
Gutierrez, J. (2014). Dolichoectasia and the risk of stroke and vascular disease: A critical appraisal. Current Cardiology Reports, 16(9), 525. doi: 10.1007/s11886-014-0525-0 Google Scholar
Gutierrez, J., Bagci, A., Gardener, H., Rundek, T., Ekind, M.S., Alperin, N., & Wright, C.B. (2014). Dolichoectasia diagnostic methods in a multi-ethnic, stroke-free cohort: Results from the northern Manhattan study. Journal of Neuroimaging, 24(3), 226–231. doi: 10.1111/j.1552-6569.2012.00781.x CrossRefGoogle Scholar
Gutierrez, J., Cheung, H.W., Bagci, A., Rundek, T., Alperin, N., Sacco, R., & Wright, C. (2016). Brain arterial diameters as biomarkers of cognitive performance: Results from the Northern Manhattan Study. Neurology, 86(16), P2.246.Google Scholar
Gutierrez, J., Cheung, K., Bagci, A., Rundek, T., Alperin, N., Sacco, R.L., & Elkind, M.S. (2015). Brain arterial diameters as a risk factor for vascular events. Journal of the American Heart Association, 4(8), e002289. doi: 10.1161/JAHA.115.002289 Google Scholar
Gutierrez, J., Elkind, M.S., Cheung, K., Rundek, T., Sacco, R.L., & Wright, C.B. (2015). Pulsatile and steady components of blood pressure and subclinical cerebrovascular disease: The Northern Manhattan Study. Journal of Hypertension, 33(10), 2115–2122. doi: 10.1097/HJH.0000000000000686 Google Scholar
Gutierrez, J., Honig, L., Elkind, M.S., Mohr, J.P., Goldman, J., Dwork, A.J., & Marshall, R.S. (2016). Brain arterial aging and its relationship to Alzheimer dementia. Neurology, 86(16), 1507–1515. doi: 10.1212/WNL.0000000000002590 Google Scholar
Gutierrez, J., Sultan, S., Bagci, A., Rundek, T., Alperin, N., Elkind, M.S., & Wright, C.B. (2013). Circle of Willis configuration as a determinant of intracranial dolichoectasia. Cerebrovascular Diseases, 36(5-6), 446–453. doi: 10.1159/000356347 Google Scholar
Hebert, L.E., Weuve, J., Scherr, P.A., & Evans, D.A. (2013). Alzheimer disease in the United States (2010-2050) estimated using the 2010 census. Neurology, 80(19), 1778–1783. doi: 10.1212/WNL.0b013e31828726f5 CrossRefGoogle ScholarPubMed
Hendrikse, J., van Raamt, A.F., van der Graaf, Y., Mali, W.P., & van der Grond, J. (2005). Distribution of cerebral blood flow in the circle of Willis. Radiology, 235(1), 184–189. doi:10.1148/radiol.2351031799 CrossRefGoogle ScholarPubMed
Hillis, A.E., Barker, P.B., Wityk, R.J., Aldrich, E.M., Restrepo, L., Breese, E.L., & Work, M. (2004). Variability in subcortical aphasia is due to variable sites of cortical hypoperfusion. Brain and Language, 89(3), 524–530. doi: 10.1016/j.bandl.2004.01.007 CrossRefGoogle ScholarPubMed
Honig, L.S., Kukull, W., & Mayeux, R. (2005). Atherosclerosis and AD: Analysis of data from the US National Alzheimer’s Coordinating Center. Neurology, 64(3), 494–500. doi:64/3/494 [pii] 10.1212/01.WNL.0000150886.50187.30.Google Scholar
Hughes, T.M., Kuller, L.H., Barinas-Mitchell, E.J., Mackey, R.H., McDade, E.M., Klunk, W.E., & Lopez, O.L. (2013). Pulse wave velocity is associated with beta-amyloid deposition in the brains of very elderly adults. Neurology, 81(19), 1711–1718. doi: 10.1212/01.wnl.0000435301.64776.37 Google Scholar
Kaplan, E., Goodglass, H., & Weintraub, S. (2001). Boston naming test. Austin, TX: Pro-ed.Google Scholar
Knecht, S., Dräger, B., Deppe, M., Bobe, L., Lohmann, H., Flöel, A., & Henningsen, H. (2000). Handedness and hemispheric language dominance in healthy humans. Brain, 123(12), 2512–2518. doi: 10.1093/brain/123.12.2512 Google Scholar
Kubis, N., Checoury, A., Tedgui, A., & Levy, B.I. (2001). Adaptive common carotid arteries remodeling after unilateral internal carotid artery occlusion in adult patients. Cardiovascular Research, 50(3), 597–602.Google Scholar
Ogasawara, K., Yukawa, H., Kobayashi, M., Mikami, C., Konno, H., Terasaki, T., & Ogawa, A. (2003). Prediction and monitoring of cerebral hyperperfusion after carotid endarterectomy by using single-photon emission computerized tomography scanning. Journal of Neurosurgery, 99(3), 504–510. doi: 10.3171/jns.2003.99.3.0504 Google Scholar
Li, Z., Yuan, A., Han, G., Gao, G., & Li, Q. (2014). Rank-based tests for identifying multiple genetic variants associated with quantitative traits. Annals of Human Genetics, 78(4), 306–310. doi: 10.1111/ahg.12067 Google Scholar
Marmarou, A., Takagi, H., & Shulman, K. (1980). Biomechanics of brain edema and effects on local cerebral blood flow. Advances in Neurology, 28, 345–358.Google ScholarPubMed
McSweeny, A.J., Naugle, R.I., Chelune, G.J., & Lüders, H. (1993). “T Scores for Change”: An illustration of a regression approach to depicting change in clinical neuropsychology. The Clinical Neuropsychologist, 7(3), 300–312.Google Scholar
Meinzer, M., Wilser, L., Flaisch, T., Eulitz, C., Rockstroh, B., Conway, T., & Crosson, B. (2009). Neural signatures of semantic and phonemic fluency in young and old adults. Journal of Cognitive Neuroscience, 21(10), 2007–2018. doi: 10.1162/jocn.2009.21219 Google Scholar
Mitchell, G.F., van Buchem, M.A., Sigurdsson, S., Gotal, J.D., Jonsdottir, M.K., Kjartansson, O., & Launer, L.J. (2011). Arterial stiffness, pressure and flow pulsatility and brain structure and function: The Age, Gene/Environment Susceptibility--Reykjavik study. Brain, 134(Pt 11), 3398–3407. doi: 10.1093/brain/awr253 Google Scholar
Ochi, N., Kohara, K., Tabara, Y., Nagai, T., Kido, T., Uetani, E., & Miki, T. (2010). Association of central systolic blood pressure with intracerebral small vessel disease in Japanese. American Journal of Hypertension, 23(8), 889–894. doi: 10.1038/ajh.2010.60 Google Scholar
Ott, C., Raff, U., Harazny, J.M., Michelson, G., & Schmieder, R.E. (2013). Central pulse pressure is an independent determinant of vascular remodeling in the retinal circulation. Hypertension, 61(6), 1340–1345. doi: 10.1161/hypertensionaha.111.00617 Google Scholar
Peters, R., Beckett, N., Fagard, R., Thijs, L., Wang, J.G., Forette, F., & Bulpitt, C. (2013). Increased pulse pressure linked to dementia: Further results from the Hypertension in the Very Elderly Trial - HYVET. Journal of Hypertension, 31(9), 1868–1875. doi: 10.1097/HJH.0b013e3283622cc6 CrossRefGoogle ScholarPubMed
Roher, A.E., Esh, C., Kokjohn, T.A., Kalback, W., Luehrs, D.C., Seward, J.D., & Beach, T.G. (2003). Circle of willis atherosclerosis is a risk factor for sporadic Alzheimer’s disease. Arteriosclerosis, Thrombosis, and Vascular Biology, 23(11), 2055–2062. doi: 10.1161/01.ATV.0000095973.42032.44 Google Scholar
Sacco, R.L., Boden-Albala, B., Gan, R., Chen, X., Kargman, D.E., Shea, S., & Hauser, W.A. (1998). Stroke Incidence among White, Black, and Hispanic Residents of an urban community: The Northern Manhattan Stroke Study. American Journal of Epidemiology, 147(3), 259–268.Google Scholar
Sacco, R.L., Kargman, D.E., Gu, Q., & Zamanillo, M.C. (1995). Race-ethnicity and determinants of intracranial atherosclerotic cerebral infarction. The Northern Manhattan Stroke Study. Stroke, 26(1), 14–20.Google Scholar
Schaefer, E.J., Lamon-Fava, S., Jenner, J.L., McNamara, J.R., Ordovas, J.M., Davis, C.E., & Levy, R.I. (1994). Lipoprotein(a) levels and risk of coronary heart disease in men. The lipid Research Clinics Coronary Primary Prevention Trial. JAMA, 271(13), 999–1003.Google Scholar
Sorbara, R. (1972). Étude comparative du vieillissement des artères du polygone de Willis. [Toulouse]: Université Paul-Sabatier.Google Scholar
Stuss, D.T., Alexander, M.P., Palumbo, C.L., Buckle, L., Sayer, L., & Pogue, J. (1994). Organizational strategies with unilateral or bilateral frontal lobe injury in word learning tasks. Neuropsychology, 8(3), 355.CrossRefGoogle Scholar
Szabo, K., Forster, A., Jager, T., Kern, R., Griebe, M., Hennerici, M.G., & Gass, A. (2009). Hippocampal lesion patterns in acute posterior cerebral artery stroke: Clinical and MRI findings. Stroke, 40(6), 2042–2045. doi: 10.1161/strokeaha.108.536144 Google Scholar
Tomaszewki Farias, S., Harrington, G., Broomand, C., & Seyal, M. (2005). Differences in functional MR imaging activation patterns associated with confrontation naming and responsive naming. AJNR American Journal of Neuroradiology, 26(10), 2492–2499.Google Scholar
Tombaugh, T.N., Kozak, J., & Rees, L. (1999). Normative data stratified by age and education for two measures of verbal fluency: FAS and animal naming. Archives of Clinical Neuropsychology, 14(2), 167–177.Google Scholar
Tsao, C.W., Seshadri, S., Beiser, A.S., Westwood, A.J., Decarli, C., Au, R., & Mitchell, G.F. (2013). Relations of arterial stiffness and endothelial function to brain aging in the community. Neurology, 81(11), 984–991. doi: 10.1212/WNL.0b013e3182a43e1c Google Scholar
van der Zwan, A., Hillen, B., Tulleken, C.A., & Dujovny, M. (1993). A quantitative investigation of the variability of the major cerebral arterial territories. Stroke, 24(12), 1951–1959.Google Scholar
Vermeer, S.E., Prins, N.D., den Heijer, T., Hofman, A., Koudstaal, P.J., & Breteler, M.M. (2003). Silent brain infarcts and the risk of dementia and cognitive decline. New England Journal of Medicine, 348(13), 1215–1222. doi: 10.1056/NEJMoa022066348/13/1215 [pii].Google Scholar
Zeeman, G.G., Hatab, M., & Twickler, D.M. (2003). Maternal cerebral blood flow changes in pregnancy. American Journal of Obstetrics and Gynecology, 189(4), 968–972. doi:http://dx.doi.org/ 10.1067/S0002-9378(03)00820-2 Google Scholar