Exploring the effects of coexisting amyloid in subcortical vascular cognitive impairment

Elizabeth Dao, Ging-Yuek Robin Hsiung, Vesna Sossi, Claudia Jacova, Roger Tam, Katie Dinelle, John R Best, Teresa Liu-Ambrose, Elizabeth Dao, Ging-Yuek Robin Hsiung, Vesna Sossi, Claudia Jacova, Roger Tam, Katie Dinelle, John R Best, Teresa Liu-Ambrose

Abstract

Background: Mixed pathology, particularly Alzheimer's disease with cerebrovascular lesions, is reported as the second most common cause of dementia. Research on mixed dementia typically includes people with a primary AD diagnosis and hence, little is known about the effects of co-existing amyloid pathology in people with vascular cognitive impairment (VCI). The purpose of this study was to understand whether individual differences in amyloid pathology might explain variations in cognitive impairment among individuals with clinical subcortical VCI (SVCI).

Methods: Twenty-two participants with SVCI completed an (11)C Pittsburgh compound B (PIB) position emission tomography (PET) scan to quantify global amyloid deposition. Cognitive function was measured using: 1) MOCA; 2) ADAS-Cog; 3) EXIT-25; and 4) specific executive processes including a) Digits Forward and Backwards Test, b) Stroop-Colour Word Test, and c) Trail Making Test. To assess the effect of amyloid deposition on cognitive function we conducted Pearson bivariate correlations to determine which cognitive measures to include in our regression models. Cognitive variables that were significantly correlated with PIB retention values were entered in a hierarchical multiple linear regression analysis to determine the unique effect of amyloid on cognitive function. We controlled for age, education, and ApoE ε4 status.

Results: Bivariate correlation results showed that PIB binding was significantly correlated with ADAS-Cog (p < 0.01) and MOCA (p < 0.01); increased PIB binding was associated with worse cognitive function on both cognitive measures. PIB binding was not significantly correlated with the EXIT-25 or with specific executive processes (p > 0.05). Regression analyses controlling for age, education, and ApoE ε4 status indicated an independent association between PIB retention and the ADAS-Cog (adjusted R-square change of 15.0%, Sig F Change = 0.03). PIB retention was also independently associated with MOCA scores (adjusted R-Square Change of 27.0%, Sig F Change = 0.02).

Conclusion: We found that increased global amyloid deposition was significantly associated with greater memory and executive dysfunctions as measured by the ADAS-Cog and MOCA. Our findings point to the important role of co-existing amyloid deposition for cognitive function in those with a primary SVCI diagnosis. As such, therapeutic approaches targeting SVCI must consider the potential role of amyloid for the optimal care of those with mixed dementia.

Trial registration: NCT01027858.

References

    1. Ferri CP, Prince M, Brayne C, Brodaty H, Fratiglioni L, Ganguli M, et al. Global prevalence of dementia: a Delphi consensus study. Lancet. 2005;366(9503):2112–2117. doi: 10.1016/S0140-6736(05)67889-0.
    1. Dementia: a public health priority . World Health Organization. 2012.
    1. Mattson MP. Pathways towards and away from Alzheimer’s disease. Nature. 2004;430(7000):631–639. doi: 10.1038/nature02621.
    1. Tulving E. Episodic memory: from mind to brain. Annu Rev Psychol. 2002;53:1–25. doi: 10.1146/annurev.psych.53.100901.135114.
    1. Moorhouse P, Rockwood K. Vascular cognitive impairment: current concepts and clinical developments. Lancet Neurol. 2008;7(3):246–255. doi: 10.1016/S1474-4422(08)70040-1.
    1. Erkinjuntti T. Subcortical ischemic vascular disease and dementia. Int Psychogeriatr. 2003;15(Suppl 1):23–26. doi: 10.1017/S1041610203008925.
    1. Gorelick PB, Scuteri A, Black SE, Decarli C, Greenberg SM, Iadecola C, et al. Vascular contributions to cognitive impairment and dementia: a statement for healthcare professionals from the american heart association/american stroke association. Stroke. 2011;42(9):2672–2713. doi: 10.1161/STR.0b013e3182299496.
    1. Breteler MM, van Swieten JC, Bots ML, Grobbee DE, Claus JJ, van den Hout JH, et al. Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study: the Rotterdam Study. Neurology. 1994;44(7):1246–1252. doi: 10.1212/WNL.44.7.1246.
    1. Jellinger KA, Attems J. Neuropathological evaluation of mixed dementia. J Neurol Sci. 2007;257(1–2):80–87. doi: 10.1016/j.jns.2007.01.045.
    1. Kalaria RN. The role of cerebral ischemia in Alzheimer’s disease. Neurobiol Aging. 2000;21(2):321–330. doi: 10.1016/S0197-4580(00)00125-1.
    1. Rockwood K, Macknight C, Wentzel C, Black S, Bouchard R, Gauthier S, et al. The diagnosis of “mixed” dementia in the Consortium for the Investigation of Vascular Impairment of Cognition (CIVIC) Ann N Y Acad Sci. 2000;903:522–528. doi: 10.1111/j.1749-6632.2000.tb06408.x.
    1. Schneider JA, Arvanitakis Z, Bang W, Bennett DA. Mixed brain pathologies account for most dementia cases in community-dwelling older persons. Neurology. 2007;69(24):2197–2204. doi: 10.1212/01.wnl.0000271090.28148.24.
    1. Zekry D, Hauw JJ, Gold G. Mixed dementia: epidemiology, diagnosis, and treatment. J Am Geriatr Soc. 2002;50(8):1431–1438. doi: 10.1046/j.1532-5415.2002.50367.x.
    1. Wang BW, Lu E, Mackenzie IR, Assaly M, Jacova C, Lee PE, et al. Multiple pathologies are common in Alzheimer patients in clinical trials. Can J Neurol Sci. 2012;39(5):592–599. doi: 10.1017/S0317167100015316.
    1. Jellinger KA, Attems J. Prevalence of dementia disorders in the oldest-old: an autopsy study. Acta Neuropathol. 2010;119(4):421–433. doi: 10.1007/s00401-010-0654-5.
    1. Dubois B, Feldman HH, Jacova C, Cummings JL, Dekosky ST, Barberger-Gateau P, et al. Revising the definition of Alzheimer’s disease: a new lexicon. Lancet Neurol. 2010;9(11):1118–1127. doi: 10.1016/S1474-4422(10)70223-4.
    1. Esiri MM, Nagy Z, Smith MZ, Barnetson L, Smith AD. Cerebrovascular disease and threshold for dementia in the early stages of Alzheimer’s disease. Lancet. 1999;354(9182):919–920. doi: 10.1016/S0140-6736(99)02355-7.
    1. Nagy Z, Esiri MM, Jobst KA, Morris JH, King EM, McDonald B, et al. The effects of additional pathology on the cognitive deficit in Alzheimer disease. J Neuropathol Exp Neurol. 1997;56(2):165–170. doi: 10.1097/00005072-199702000-00007.
    1. Rosen WG, Mohs RC, Davis KL. A new rating scale for Alzheimer’s disease. Am J Psychiatry. 1984;141(11):1356–1364. doi: 10.1176/ajp.141.11.1356.
    1. Royall DR, Mahurin RK, Gray KF. Bedside assessment of executive cognitive impairment: the executive interview. J Am Geriatr Soc. 1992;40(12):1221–1226. doi: 10.1111/j.1532-5415.1992.tb03646.x.
    1. Koski L. Validity and applications of the Montreal cognitive assessment for the assessment of vascular cognitive impairment. Cerebrovasc Dis. 2013;36(1):6–18. doi: 10.1159/000352051.
    1. O’Brien J, Lilienfeld S. Relevant clinical outcomes in probable vascular dementia and Alzheimer’s disease with cerebrovascular disease. J Neurol Sci. 2002;203–204:41–48. doi: 10.1016/S0022-510X(02)00259-9.
    1. Mohs RC, Kawas C, Carrillo MC. Optimal design of clinical trials for drugs designed to slow the course of Alzheimer’s disease. Alzheimers Dement. 2006;2(3):131–139. doi: 10.1016/j.jalz.2006.04.003.
    1. Hachinski V, Iadecola C, Petersen RC, Breteler MM, Nyenhuis DL, Black SE, et al. National Institute of Neurological Disorders and Stroke-Canadian Stroke Network vascular cognitive impairment harmonization standards. Stroke. 2006;37(9):2220–2241. doi: 10.1161/01.STR.0000237236.88823.47.
    1. Liu-Ambrose T, Eng JJ, Boyd LA, Jacova C, Davis JC, Bryan S, et al. Promotion of the mind through exercise (PROMoTE): a proof-of-concept randomized controlled trial of aerobic exercise training in older adults with vascular cognitive impairment. BMC Neurol. 2010;10:14. doi: 10.1186/1471-2377-10-14.
    1. Nasreddine ZS, Phillips NA, Bedirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–699. doi: 10.1111/j.1532-5415.2005.53221.x.
    1. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–198. doi: 10.1016/0022-3956(75)90026-6.
    1. Sled JG, Zijdenbos AP, Evans AC. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging. 1998;17(1):87–97. doi: 10.1109/42.668698.
    1. Smith SMB JM. SUSAN-a new approach to low level image processing. Int J Comput Vis. 1997;23:1.
    1. Smith SM. Fast robust automated brain extraction. Hum Brain Mapp. 2002;17(3):143–155. doi: 10.1002/hbm.10062.
    1. McAusland J, Tam R, Wong E, Riddehough A, Li D. Optimizing the Use of Radiologist Seed Points for Improved Multiple Sclerosis Lesion Segmentation. IEEE Trans Biomed Eng. 2010
    1. Parzen E. On estimation of a probability density function and mode. Ann Math Stat. 1962;33:1065–1076. doi: 10.1214/aoms/1177704472.
    1. Lam B, Middleton LE, Masellis M, Stuss DT, Harry RD, Kiss A, et al. Criterion and convergent validity of the Montreal cognitive assessment with screening and standardized neuropsychological testing. J Am Geriatr Soc. 2013;61(12):2181–2185. doi: 10.1111/jgs.12541.
    1. Dong Y, Sharma VK, Chan BP, Venketasubramanian N, Teoh HL, Seet RC, et al. The Montreal Cognitive Assessment (MoCA) is superior to the Mini-Mental State Examination (MMSE) for the detection of vascular cognitive impairment after acute stroke. J Neurol Sci. 2010;299(1–2):15–18. doi: 10.1016/j.jns.2010.08.051.
    1. Kirk A. Target symptoms and outcome measures: cognition. Can J Neurol Sci. 2007;34(Suppl 1):S42–S46. doi: 10.1017/S0317167100005552.
    1. Stokholm J, Vogel A, Gade A, Waldemar G. The executive interview as a screening test for executive dysfunction in patients with mild dementia. J Am Geriatr Soc. 2005;53(9):1577–1581. doi: 10.1111/j.1532-5415.2005.53470.x.
    1. Royall DR, Rauch R, Roman GC, Cordes JA, Polk MJ. Frontal MRI findings associated with impairment on the Executive Interview (EXIT25) Exp Aging Res. 2001;27(4):293–308. doi: 10.1080/03610730109342350.
    1. Roman GC, Royall DR. Executive control function: a rational basis for the diagnosis of vascular dementia. Alzheimer Dis Assoc Disord. 1999;13(Suppl 3):S69–S80. doi: 10.1097/00002093-199912001-00012.
    1. Royall DR, Chiodo LK, Polk MJ. Executive dyscontrol in normal aging: normative data, factor structure, and clinical correlates. Curr Neurol Neurosci Rep. 2003;3(6):487–493. doi: 10.1007/s11910-003-0052-7.
    1. Wechsler D. Wechsler adult intelligence scale. 4ed. New York: NCS Pearson; 2008.
    1. Trenerry M. Stroop neuropsychological screening test manual. Odessa, FL: Psychological Assessment Resources; 1989.
    1. Allen DN, Haderlie MM. Trail-making test. The Corsini Encyclopedia of Psychology: Wiley; 2010.
    1. Innis RB, Cunningham VJ, Delforge J, Fujita M, Gjedde A, Gunn RN, et al. Consensus nomenclature for in vivo imaging of reversibly binding radioligands. J Cereb Blood Flow Metab. 2007;27(9):1533–1539. doi: 10.1038/sj.jcbfm.9600493.
    1. Logan J, Fowler JS, Volkow ND, Wang GJ, Ding YS, Alexoff DL. Distribution volume ratios without blood sampling from graphical analysis of PET data. J Cereb Blood Flow Metab. 1996;16(5):834–840. doi: 10.1097/00004647-199609000-00008.
    1. Logan J, Fowler JS, Volkow ND, Wolf AP, Dewey SL, Schlyer DJ, et al. Graphical analysis of reversible radioligand binding from time-activity measurements applied to [N-11C-methyl]-(−)-cocaine PET studies in human subjects. J Cereb Blood Flow Metab. 1990;10(5):740–747. doi: 10.1038/jcbfm.1990.127.
    1. Lopresti BJ, Klunk WE, Mathis CA, Hoge JA, Ziolko SK, Lu X, et al. Simplified quantification of Pittsburgh Compound B amyloid imaging PET studies: a comparative analysis. J Nucl Med. 2005;46(12):1959–1972.
    1. Price JC, Klunk WE, Lopresti BJ, Lu X, Hoge JA, Ziolko SK, et al. Kinetic modeling of amyloid binding in humans using PET imaging and Pittsburgh Compound-B. J Cereb Blood Flow Metab. 2005;25(11):1528–1547. doi: 10.1038/sj.jcbfm.9600146.
    1. Collins DL, Neelin P, Peters TM, Evans AC. Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr. 1994;18(2):192–205. doi: 10.1097/00004728-199403000-00005.
    1. Park JH, Seo SW, Kim C, Kim SH, Kim GH, Kim ST, et al. Effects of cerebrovascular disease and amyloid beta burden on cognition in subjects with subcortical vascular cognitive impairment. Neurobiol Aging. 2014;35(1):254–260. doi: 10.1016/j.neurobiolaging.2013.06.026.
    1. Aizenstein HJ, Nebes RD, Saxton JA, Price JC, Mathis CA, Tsopelas ND, et al. Frequent amyloid deposition without significant cognitive impairment among the elderly. Arch Neurol. 2008;65(11):1509–1517. doi: 10.1001/archneur.65.11.1509.
    1. Jagust WJ, Bandy D, Chen K, Foster NL, Landau SM, Mathis CA, et al. The Alzheimer’s Disease Neuroimaging Initiative positron emission tomography core. Alzheimers Dement. 2010;6(3):221–229. doi: 10.1016/j.jalz.2010.03.003.
    1. Yaqub M, Tolboom N, Boellaard R, van Berckel BN, van Tilburg EW, Luurtsema G, et al. Simplified parametric methods for [11C] PIB studies. NeuroImage. 2008;42(1):76–86. doi: 10.1016/j.neuroimage.2008.04.251.
    1. Hsiung GY, Sadovnick AD, Feldman H. Apolipoprotein E epsilon4 genotype as a risk factor for cognitive decline and dementia: data from the Canadian Study of Health and Aging. CMAJ. 2004;171(8):863–867. doi: 10.1503/cmaj.1031789.
    1. Doraiswamy PM, Sperling RA, Johnson K, Reiman EM, Wong TZ, Sabbagh MN, et al. Florbetapir F 18 amyloid PET and 36-month cognitive decline: a prospective multicenter study. Mol Psychiatry. 2014;19(9):1044–1051. doi: 10.1038/mp.2014.9.
    1. Resnick SM, Sojkova J, Zhou Y, An Y, Ye W, Holt DP, et al. Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [11C] PiB. Neurology. 2010;74(10):807–815. doi: 10.1212/WNL.0b013e3181d3e3e9.
    1. Villemagne VL, Pike KE, Darby D, Maruff P, Savage G, Ng S, et al. Abeta deposits in older non-demented individuals with cognitive decline are indicative of preclinical Alzheimer’s disease. Neuropsychologia. 2008;46(6):1688–1697. doi: 10.1016/j.neuropsychologia.2008.02.008.
    1. Forsberg A, Engler H, Almkvist O, Blomquist G, Hagman G, Wall A, et al. PET imaging of amyloid deposition in patients with mild cognitive impairment. Neurobiol Aging. 2008;29(10):1456–1465. doi: 10.1016/j.neurobiolaging.2007.03.029.
    1. Pike KE, Savage G, Villemagne VL, Ng S, Moss SA, Maruff P, et al. Beta-amyloid imaging and memory in non-demented individuals: evidence for preclinical Alzheimer’s disease. Brain. 2007;130(Pt 11):2837–2844. doi: 10.1093/brain/awm238.
    1. Okello A, Koivunen J, Edison P, Archer HA, Turkheimer FE, Nagren K, et al. Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET study. Neurology. 2009;73(10):754–760. doi: 10.1212/WNL.0b013e3181b23564.
    1. Wolk DA, Price JC, Saxton JA, Snitz BE, James JA, Lopez OL, et al. Amyloid imaging in mild cognitive impairment subtypes. Ann Neurol. 2009;65(5):557–568. doi: 10.1002/ana.21598.
    1. Collette F, Van der Linden M, Salmon E. Executive dysfunction in Alzheimer’s disease. Cortex. 1999;35(1):57–72. doi: 10.1016/S0010-9452(08)70785-8.
    1. Sgaramella TM, Borgo F, Mondini S, Pasini M, Toso V, Semenza C. Executive deficits appearing in the initial stage of Alzheimer’s disease. Brain Cogn. 2001;46(1–2):264–268. doi: 10.1016/S0278-2626(01)80080-4.
    1. Gibbons LE, Carle AC, Mackin RS, Harvey D, Mukherjee S, Insel P, et al. A composite score for executive functioning, validated in Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants with baseline mild cognitive impairment. Brain Imaging Behav. 2012;6(4):517–527. doi: 10.1007/s11682-012-9176-1.
    1. Lee MJ, Seo SW, Na DL, Kim C, Park JH, Kim GH, et al. Synergistic effects of ischemia and beta-amyloid burden on cognitive decline in patients with subcortical vascular mild cognitive impairment. JAME Psychiatry. 2014;71(4):412–422. doi: 10.1001/jamapsychiatry.2013.4506.
    1. Nordlund A, Rolstad S, Klang O, Edman A, Hansen S, Wallin A. Two-year outcome of MCI subtypes and aetiologies in the Goteborg MCI study. J Neurol Neurosurg Psychiatry. 2010;81(5):541–546. doi: 10.1136/jnnp.2008.171066.
    1. Bennett DA, Schneider JA, Wilson RS, Bienias JL, Arnold SE. Neurofibrillary tangles mediate the association of amyloid load with clinical Alzheimer disease and level of cognitive function. Arch Neurol. 2004;61(3):378–384. doi: 10.1001/archneur.61.3.378.
    1. Carmichael O, Schwarz C, Drucker D, Fletcher E, Harvey D, Beckett L, et al. Longitudinal changes in white matter disease and cognition in the first year of the Alzheimer disease neuroimaging initiative. Arch Neurol. 2010;67(11):1370–1378. doi: 10.1001/archneurol.2010.284.
    1. Pasi M, Salvadori E, Poggesi A, Ciolli L, Del Bene A, Marini S, et al. White matter microstructural damage in small vessel disease is associated with Montreal Cognitive Assessment but not with mini mental state examination performances: Vascular Mild Cognitive Impairment Tuscany study. Stroke. 2015;46(1):262–264. doi: 10.1161/STROKEAHA.114.007553.
    1. Van Petten C, Plante E, Davidson PS, Kuo TY, Bajuscak L, Glisky EL. Memory and executive function in older adults: relationships with temporal and prefrontal gray matter volumes and white matter hyperintensities. Neuropsychologia. 2004;42(10):1313–1335. doi: 10.1016/j.neuropsychologia.2004.02.009.
    1. Rolstad S, Berg AI, Eckerstrom C, Johansson B, Wallin A. Differential Impact of Neurofilament Light Subunit on Cognition and Functional Outcome in Memory Clinic Patients with and without Vascular Burden. J Alzheimers Dis. 2015;45(3):873–881.
    1. Lee JH, Kim SH, Kim GH, Seo SW, Park HK, Oh SJ, et al. Identification of pure subcortical vascular dementia using 11C-Pittsburgh compound B. Neurology. 2011;77(1):18–25. doi: 10.1212/WNL.0b013e318221acee.

Source: PubMed

스폰서 및 공동 작업자

건강 상태

약물 개입

3
구독하다