Hostname: page-component-8448b6f56d-xtgtn Total loading time: 0 Render date: 2024-04-23T19:45:03.441Z Has data issue: false hasContentIssue false
  • English
  • Français

Vascular risk factors and the relationships between cognitive impairment and hypoperfusion in late-onset Alzheimer’s disease

Published online by Cambridge University Press:  22 August 2018

Michio Takahashi ,
Yasunori Oda ,
Koichi Sato  and
Yukihiko Shirayama
Michio Takahashi
Affiliation:
Department of Psychiatry, Teikyo University Chiba Medical Center, Ichihara, Japan
Yasunori Oda
Affiliation:
Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan
Koichi Sato
Affiliation:
Department of Psychiatry, Teikyo University Chiba Medical Center, Ichihara, Japan
Yukihiko Shirayama*
Affiliation:
Department of Psychiatry, Teikyo University Chiba Medical Center, Ichihara, Japan
*
*Author for correspondence: Yukihiko Shirayama, Department of Psychiatry, Teikyo University Chiba Medical Center, 3426-3 Anesaki, Ichihara 299-0111, Japan. Tel: +81 436 62 1211; Fax: +81 436 62 1511; E-mail: shirayama@rapid.ocn.ne.jp
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective

Our recent single-photon emission computed tomography (SPECT) study of patients with late-onset Alzheimer’s disease (AD) revealed that regional cerebral blood flow (rCBF) was reduced in the frontal, temporal, and limbic lobes, and to a lesser degree in the parietal and occipital lobes. Moreover, these patients’ scores on the Alzheimer’s Disease Assessment Scale-cognitive subscale (ADAS-cog) were significantly correlated with rCBF in some gyri of the frontal, parietal, and limbic lobes. Our present study aimed to understand how vascular factors and metabolic disease influenced the relationship between rCBF and ADAS-cog scores.

Methods

We divided late-onset AD patients into two groups according to their Hachinski Ischemic Score (HIS), low vascular risk patients had values of ≤4 (n=25) and high vascular risk patients had scores ≥5 (n=15). We examined rCBF using brain perfusion SPECT data.

Results

The degrees and patterns of reduced rCBF were largely similar between late-onset AD patients in both groups, regardless of HIS values. Cognitive function was significantly associated with rCBF among late-onset AD patients with low vascular risk (HIS≤4), but not among those with high vascular risk (HIS≥5). Furthermore, metabolic diseases, such as hypertension and diabetes mellitus, disrupted the relationships between hypoperfusion and cognitive impairments in late-onset AD patients.

Conclusion

Factors other than hypoperfusion, such as hypertension and diabetes mellitus, could be involved in the cognitive dysfunction of late-onset AD patients with high vascular risk.

Keywords

cognitive functiondementiametabolic diseaseSPECT
Type
Original Article
Information
Acta Neuropsychiatrica , Volume 30 , Issue 6 , December 2018 , pp. 350 - 358
Copyright
© Scandinavian College of Neuropsychopharmacology 2018 

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

1. Dubois B, Feldman HH, Jacova C, Cummings JL, DeKosky ST, Barberger-Gateau P, Delacourte A, Frisoni G, Fox NC, Galasko D, Gauthier S, Hampel H, Jicha GA, Meguro K, O'Brien J, Pasquier F, Robert P, Rossor M, Salloway S, Sarazin M, de Souza LC, Stern Y, Visser PJ and Scheltens P (2010) Revising the definition of Alzheimer’s disease: a new lexicon. Lancet Neurol 9, 1118–1127.Google Scholar
2. McKhann, G, Drachman, D, Folstein, M, Katzman, R, Price, D Stadlan, EM (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
3. Lampl, Y, Sadeh, M, Laker, O Lorberboym, M (2003) Correlation of neuropsychological evaluation and SPECT imaging in patients with Alzheimer’s disease. Int J Geriatr Psychiatry 18, 288–291.Google Scholar
4. Nebu A, Ikeda M, Fukuhara R, Shigenobu K, Maki N, Hokoishi K, Komori K, Yasuoka T and Tanabe H (2001) Relationship between blood flow kinetics and severity of Alzheimer’s disease: assessment of severity using a questionnaire-type examination, Alzheimer’s disease assessment scale, cognitive sub-scale (ADAS(cog)). Dement Geriatr Cogn Disord 12, 318–325.Google Scholar
5. Ones T, Midi I, Dede F, Tuncer N, Erdil, TY, Onultan O, Ceylan S, Inanir S and Turoglu HT (2012) Initial mini-mental state and cerebral perfusion in Alzheimer’s disease. Clin Neuroradiol 22, 219–226.Google Scholar
6. Cavedo E, Pievani M, Boccardi M, Galluzzi S, Bocchetta M, Bonetti M, Thompson PM and Frisoni GB (2014) Medial temporal atrophy in early and late-onset Alzheimer’s disease. Neurobiol Aging 35, 2004–2012.Google Scholar
7. Frisoni GB, Pievani M, Testa C, Sabattoli F, Bresciani L, Bonetti M, Beltramello A, Hayashi KM, Toga AW and Thompson PM (2007) The topography of grey matter involvement in early and late onset Alzheimer’s disease. Brain 130, 720–730.Google Scholar
8. Ishii K, Kawachi T, Sasaki H, Kono AK, Fukuda T, Kojima Y and Mori E (2005) Voxel-based morphometric comparison between early- and late-onset mild Alzheimer’s disease and assessment of diagnostic performance of z score images. Am J Neuroradiol 26, 333–340.Google Scholar
9. Möller C, Vrenken H, Jiskoot L, Versteeg A, Barkhof F, Scheltens P and van der Flier WM (2013) Different patterns of gray matter atrophy in early- and late-onset Alzheimer’s disease. Neurobiol Aging 34, 2014–2022.Google Scholar
10. Takahashi, M, Oda, Y, Okubo, T Shirayama, Y (2017) Relationships between cognitive impairment on ADAS-cog and regional cerebral blood flow using SPECT in late-onset Alzheimer’s disease. J Neural Trans 124, 1109–1121.Google Scholar
11. Reitz, C Mayeux, R (2014) Genetics of Alzheimer’s disease in Caribbean Hispanic and African American populations. Biol Psychiatry 75, 534–541.Google Scholar
12. Xiao E, Chen Q, Goldman AL, Tan HY, Healy K, Zoltick B, Das S, Kolachana B, Callicott JH, Dickinson D, Berman KF, Weinberger DR and Mattay VS (2017) Late-onset Alzheimer’s disease polygenic risk profile score predicts hippocampal function. Biol Psychiatry Cogn Neurosci Neuroimaging 2, 673–679.Google Scholar
13. Panegyres, PK Chen, HY (2014) Early-onset Alzheimer’s disease: a global cross-sectional analysis. Eur J Neurol 2, 1149–1154.Google Scholar
14. Kume K, Hanyu H, Sato T, Hirao K, Shimizu S, Kanetaka H, Sakurai H and Iwamoto T (2011) Vascular risk factors are associated with faster decline of Alzheimer disease: a longitudinal SPECT study. J Neurol 258, 1295–1303.Google Scholar
15. Kisler, K, Nelson, AR, Montagne, A Zlokovic, BV (2017) Cerebral blood flow regulation and neurovascular dysfunction in Alzheimer disease. Nat Rev Neurosci 18, 419–434.Google Scholar
16. Richard, F Pasquier, F (2012) Can the treatment of vascular risk factors slow cognitive decline in Alzheimer’s disease patients? J Alzheimers Dis 32, 765–772.Google Scholar
17. Bellew, KM, Pigeon, JG, Stang, PE, Fleischman, W, Gardner, RM Baker, WW (2004) Hypertension and the rate of cognitive decline in patients with dementia of the Alzheimer type. Alzheimer Dis Assoc Disord 18, 208–213.Google Scholar
18. Mielke MM, Rosenberg PB, Tschanz J, Cook L, Corcoran C, Hayden KM, Norton M, Rabins PV, Green RC, Welsh-Bohmer KA, Breitner JC, Munger R and Lyketsos CG (2007) Vascular factors predict rate of progression in Alzheimer disease. Neurology 69, 1850–1858.Google Scholar
19. Razay, G, Williams, J, King, E, Smith, AD Wilcock, G (2009) Blood pressure, dementia and Alzheimer’s disease: the OPTIMA longitudinal study. Dement Geriatr Cogn Disord 28, 70–74.Google Scholar
20. Hajjar, I, Schumpert, J, Hirth, V, Wieland, D Eleazer, GP (2002) The impact of the use of statins on the prevalence of dementia and the progression of cognitive impairment. J Gerontol A Biol Sci Med Sci 57, M414–M418.Google Scholar
21. Helzner EP, Luchsinger JA, Scarmeas N, Cosentino S, Brickman AM, Glymour MM and Stern Y (2009) Contribution of vascular risk factors to the progression in Alzheimer disease. Arch Neurol 66, 343–348.Google Scholar
22. Masse I, Bordet R, Deplanque D, Al Khedr A, Richard F, Libersa C and Pasquier F (2005) Lipid lowering agents are associated with a slower cognitive decline in Alzheimer’s disease. J Neurol Neurosurg Psychiatry 76, 1624–1629.Google Scholar
23. Sato, T, Hanyu, H, Hirao, K, Kanetaka, H, Sakurai, H Iwamoto, T (2011) Efficacy of PPAR-γ agonist pioglitazone in mild Alzheimer disease. Neurobiol Aging 32, 1626–1633.Google Scholar
24. Bangen KJ, Nation DA, Clark LR, Harmell AL, Wierenga CE, Dev SI, Delano-Wood L, Zlatar ZZ, Salmon DP, Liu TT and Bondi MW (2014) Interactive effects of vascular risk burden and advanced age on cerebral blood flow. Front Aging Neurosci 6, 159.Google Scholar
25. Lourenço, CF, Ledo, A, Dias, C, Barbosa, RM Laranjinha, J (2015) Neurovascular and neurometabolic derailment in aging and Alzheimer’s disease. Front Aging Neurosci 7, 103.Google Scholar
26. Sato, N Morishita, R (2013) Roles of vascular and metabolic components in cognitive dysfunction of Alzheimer disease: short- and long-term modification by non-genetic risk factors. Front Aging Neurosci 5, 64.Google Scholar
27. Deschaintre, Y, Richard, F, Leys, D Pasquier, F (2009) Treatment of vascular risk factors is associated with slower decline in Alzheimer disease. Neurology 73, 674–680.Google Scholar
28. Minoshima, S, Frey, KA, Koeppe, RA, Foster, NL Kuhl, DE (1995) A diagnostic approach in Alzheimer’s disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. J Nucl Med 36, 1238–1248.Google Scholar
29. Ishii K, Willoch F, Minoshima S, Drzezga A, Ficaro EP, Cross DJ, Kuhl DE and Schwaiger M (2001) Statistical brain mapping of 18F-FDG PET in Alzheimer’s disease: validation of anatomic standardization for atrophied brains. J Nucl Med 42, 548–557.Google Scholar
30. Mizumura S, Kumita S, Cho K, Ishihara M, Nakajo H, Toba M and Kumazaki T (2003) Development of quantitative analysis method for stereotactic brain image: assessment of reduced accumulation in extent and severity using anatomical segmentation. Ann Nucl Med 17, 289–295.Google Scholar
31. American Psychiatric Association (2000) Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR), 4th edn. Washington, DC: American Psychiatric Press.Google Scholar
32. Folstein, MF, Folstein, SE McHugh, PR (1975) “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12, 189–198.Google Scholar
33. Kukull, WA, Larson, EB, Teri, L, Bowen, J, McCormick, W Pfanschmidt, ML (1994) The mini-mental state examination score and the clinical diagnosis of dementia. J Clin Epidemiol 47, 1061–1067.Google Scholar
34. Li W, Antuono PG, Xie C, Chen G, Jones JL, Ward BD, Franczak MB, Goveas JS and Li SJ (2012) Changes in regional cerebral blood flow and functional connectivity in the cholinergic pathway associated with cognitive performance in subjects with mild Alzheimer’s disease after 12-week donepezil treatment. Neuroimage 60, 1083–1091.Google Scholar
35. Reisberg B, Ferris SH, Anand R, de Leon MJ, Schneck MK, Buttinger C and Borenstein J (1984) Functional staging of dementia of the Alzheimer type. Ann N Y Acad Sci 435, 481–483.Google Scholar
36. Rosen, WG, Mohs, RC Davis, KL (1984) A new rating scale for Alzheimer’s disease. Am J Psychiatry 141, 1356–1364.Google Scholar
37. Hachinski VC, Iliff LD, Zilhka E, Du Boulay GH, McAllister VL, Marshall J, Russell RW and Symon L (1975) Cerebral blood flow in dementia. Arch Neurol 32, 632–637.Google Scholar
38. Moroney JT, Bagiella E, Desmond DW, Hachinski VC, Molsa PK, Gustafson L, Brun A, Fischer P, Erkinjuntti T, Rosen W, Paik MC and Tatemichi TK (1997) Meta-analysis of the Hachinski Ischemic Score in pathologically verified dementias. Neurology 49, 1096–1105.Google Scholar
39. Shirayama Y, Takahashi M, Oda Y, Yoshino K, Sato K and Okubo T (2018) rCBF and cognitive impairment changes by SPECT and ADAS-cog in late-onset Alzheimer’s disease after 18 months of treatment with the cholinesterase inhibitors donepezil or galantamine. Brain Imaging Behav doi: 10.1007/s11682-017-9803-y.Google Scholar
40. Skoog, I, Kakaria, RN Breteler, MB (1999) Vascular factors and Alzheimer’s disease. Alzheimer Dis Assoc Disord 13(Suppl. 3), S106–S114.Google Scholar
41. Luchsinger, JA, Reitz, C, Honig, LS, Tang, MX, Shea, S Mayeux, R (2005) Aggregation of vascular risk factors and risk of incident Alzheimer disease. Neurology 65, 545–551.Google Scholar
42. Shih YH, Tsai SF, Huang SH, Chiang YT, Hughes MW, Wu SY, Yang TT and Kuo YM (2016) Hypertension impairs hippocampus-related adult neurogenesis, CA1 neuron dendritic arborization and long-term memory. Neuroscience 322, 346–357.Google Scholar
43. Roberts RO, Knopman DS, Geda YE, Cha RH, Pankratz VS, Baertlein L, Boeve BF, Tangalos EG, Ivnik RJ, Mielke MM and Petersen RC (2014) Association of diabetes with amnestic and nonamnestic mild cognitive impairment. Alzheimer’s Dement 10, 18–26.Google Scholar
44. Debette S, Seshadri S, Beiser A, Au R, Himali JJ, Palumbo C, Wolf PA and DeCarli C (2011) Midlife vascular risk factor exposure accelerates structural brain aging and cognitive decline. Neurology 77, 461–468.Google Scholar
45. Fotuhi, M, Do, D Jack, C (2012) Modifiable factors that alter the size of the hippocampus with ageing. Nat Rev Neurol 8, 189–202.Google Scholar