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Predicting Cognitive Decline across Four Decades in Mutation Carriers and Non-carriers in Autosomal-Dominant Alzheimer’s Disease

Published online by Cambridge University Press:  12 January 2017

Ove Almkvist ,
Elena Rodriguez-Vieitez ,
Steinunn Thordardottir ,
Kaarina Amberla ,
Karin Axelman ,
Hans Basun ,
Anne Kinhult-Ståhlbom ,
Lena Lilius ,
Anne Remes  and
Lars-Olof Wahlund
...Show all authors
Ove Almkvist*
Affiliation:
Karolinska Institutet, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Division of Translational Alzheimer Neurobiology, Stockholm, Sweden Department of Geriatric Medicine, Karolinska University Hospital at Huddinge, Stockholm, Sweden Department of Psychology, Stockholm University, Stockholm, Sweden
Elena Rodriguez-Vieitez
Affiliation:
Karolinska Institutet, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Division of Translational Alzheimer Neurobiology, Stockholm, Sweden
Steinunn Thordardottir
Affiliation:
Department of Geriatric Medicine, Karolinska University Hospital at Huddinge, Stockholm, Sweden Karolinska Institutet, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Division of Neurogeriatrics, Stockholm, Sweden
Kaarina Amberla
Affiliation:
Department of Geriatric Medicine, Karolinska University Hospital at Huddinge, Stockholm, Sweden
Karin Axelman
Affiliation:
Department of Geriatric Medicine, Karolinska University Hospital at Huddinge, Stockholm, Sweden
Hans Basun
Affiliation:
Department of Public Health and Caring Sciences/Geriatrics, Uppsala University, Uppsala, Sweden
Anne Kinhult-Ståhlbom
Affiliation:
Department of Geriatric Medicine, Karolinska University Hospital at Huddinge, Stockholm, Sweden Karolinska Institutet, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Division of Neurogeriatrics, Stockholm, Sweden
Lena Lilius
Affiliation:
Department of Geriatric Medicine, Karolinska University Hospital at Huddinge, Stockholm, Sweden
Anne Remes
Affiliation:
Department of Neurology, Institute of Clinical Medicine Neurology, University of Eastern Finland, Kuopio, Finland
Lars-Olof Wahlund
Affiliation:
Department of Geriatric Medicine, Karolinska University Hospital at Huddinge, Stockholm, Sweden Karolinska Institutet, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Division of Clinical Geriatrics, Stockholm, Sweden
Matti Viitanen
Affiliation:
Department of Geriatric Medicine, Karolinska University Hospital at Huddinge, Stockholm, Sweden Karolinska Institutet, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Division of Clinical Geriatrics, Stockholm, Sweden Department of Geriatrics, Turku City Hospital, Turku, Finland University of Turku, Turku, Finland
Lars Lannfelt
Affiliation:
Department of Public Health and Caring Sciences/Geriatrics, Uppsala University, Uppsala, Sweden
Caroline Graff
Affiliation:
Department of Geriatric Medicine, Karolinska University Hospital at Huddinge, Stockholm, Sweden Karolinska Institutet, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Division of Neurogeriatrics, Stockholm, Sweden
*
Correspondence and reprint requests to: Ove Almkvist, Karolinska Institutet, Center for Alzheimer Research; Department of Neurobiology Care Sciences and Society, Division of Translational Alzheimer Neurobiology, SE-14157 Huddinge, Sweden. E-mail: ove.almkvist@ki.se
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Abstract

Objectives: The aim of this study was to investigate cognitive performance including preclinical and clinical disease course in carriers and non-carriers of autosomal-dominant Alzheimer’s disease (adAD) in relation to multiple predictors, that is, linear and non-linear estimates of years to expected clinical onset of disease, years of education and age. Methods: Participants from five families with early-onset autosomal-dominant mutations (Swedish and Arctic APP, PSEN1 M146V, H163Y, and I143T) included 35 carriers (28 without dementia and 7 with) and 44 non-carriers. All participants underwent a comprehensive clinical evaluation, including neuropsychological assessment at the Memory Clinic, Karolinska University Hospital at Huddinge, Stockholm, Sweden. The time span of disease course covered four decades of the preclinical and clinical stages of dementia. Neuropsychological tests were used to assess premorbid and current global cognition, verbal and visuospatial functions, short-term and episodic memory, attention, and executive function. Results: In carriers, the time-related curvilinear trajectory of cognitive function across disease stages was best fitted to a formulae with three predictors: years to expected clinical onset (linear and curvilinear components), and years of education. In non-carriers, the change was minimal and best predicted by two predictors: education and age. The trajectories for carriers and non-carriers began to diverge approximately 10 years before the expected clinical onset in episodic memory, executive function, and visuospatial function. Conclusions: The curvilinear trajectory of cognitive functions across disease stages was mimicked by three predictors in carriers. In episodic memory, executive and visuospatial functions, the point of diverging trajectories occurred approximately 10 years ahead of the clinical onset compared to non-carriers. (JINS, 2017, 23, 195–203)

Keywords

Autosomal-dominantAlzheimer’s diseaseMutation carrierCognitionPredictorsAge of onset
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 23 , Issue 3 , March 2017 , pp. 195 - 203
Copyright
Copyright © The International Neuropsychological Society 2017 

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References

REFERENCES

Aguirre-Acevedo, D.C., Lopera, F., Henao, E., Tirado, V., Munoz, C., Giraldo, M., & Jaimes, F. (2016). Cognitive decline in a Colombian kindred with autosomal-dominant Alzheimer Disease: A retrospective cohort study. JAMA Neurology, 73, 431–438.Google Scholar
Almkvist, O., Adveen, M., Henning, L., & Tallberg, I.M. (2007). Estimation of premorbid cognitive function based on word knowledge: The Swedish Lexical Decision Test (SLDT). Scandinavian Journal of Psychology, 48, 271–279.CrossRefGoogle ScholarPubMed
Almkvist, O., Axelman, K., Basun, H., Wahlund, L.O., & Lannfelt, L. (2002). Conversion from preclinical to clinical stage of Alzheimer’s disease as shown by decline of cognitive functions in carriers of the Swedish APP-mutation. Journal of Neural Transmission, (Suppl). 62, 117–125.CrossRefGoogle Scholar
Almkvist, O., & Bäckman, L. (1993). Progression in Alzheimer’s disease: Sequencing of neuropsychological decline. International Journal of Geriatric Psychiatry, 8, 755–763.Google Scholar
Almkvist, O., & Tallberg, I.M. (2009). Cognitive decline from estimated premorbid status predicts neurodegeneration in Alzheimer’s disease. Neuropsychology, 23, 117–124.CrossRefGoogle ScholarPubMed
American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: American Psychiatric Association.Google Scholar
Ardila, A., Lopera, F., Rosselli, M., Moreno, S., Madrigal, L., Arango-Lasprilla, J.C., & Kosik, K.S. (2000). Neuropsychological profile of a large kindred with familial Alzheimer’s disease caused by the E280A single presenilin-1 mutation. Archives of Clinical Neuropsychology, 15, 515–528.CrossRefGoogle ScholarPubMed
Axelman, K., Basun, H., & Lannfelt, L. (1998). Wide range of disease onset in a family with Alzheimer disease and a His163Tyr mutation in the presenilin-1 gene. Archives of Neurology, 55, 698–702.Google Scholar
Axelman, K., Basun, H., Winblad, B., & Lannfelt, L. (1994). A large Swedish family with Alzheimer’s disease with a codon 670/671 amyloid precursor protein mutation. A clinical and genealogical investigation. Archives of Neurology, 51, 1193–1197.Google Scholar
Bartfai, A., Nyman, H., & Stegman, B. (1994). Wechsler Adult Intelligence Scale revised: WAIS-R Manual. Stockholm, Sweden: Psykologiförlaget.Google Scholar
Basun, H., Bogdanovic, N., Ingelsson, M., Almkvist, O., Näslund, J., Axelman, K., & Lannfelt, L. (2008). Clinical and neuropathological features of the arctic APP gene mutation causing early-onset Alzheimer disease. Archives of Neurology, 65, 499–505.Google Scholar
Bateman, R.J., Xiong, C., Benzinger, T.L.S., Fagan, A.M., Goate, A., Fox, N.C., & Morris, J.C. (2012). Clinical and biomarker changes in dominantly inherited Alzheimer’s disease. New England Journal of Medicine, 367, 795–804.Google Scholar
Bergman, I., Blomberg, M., & Almkvist, O. (2007). The importance of impaired physical health and age in normal cognitive aging. Scandinavian Journal of Psychology, 48, 115–125.CrossRefGoogle ScholarPubMed
Braak, H., & Braak, E. (1991). Neuropathological stageing of Alzheimer-related changes. Acta Neuropathologica (Berlin), 82, 239–259.Google Scholar
Díaz-Olavarrieta, C., Ostrosky-Solis, F., Garcia de la Cadena, C., Rodriguez, Y., & Alonso, E. (1997). Neuropsychological changes in subjects at risk of inheriting Alzheimer’s disease. Neuroreport, 28, 2449–2453.CrossRefGoogle Scholar
Duara, R., Lopez-Alberola, R.F., Barker, W.W., Loewenstein, D.A., Zatinsky, M., Eisdorfer, C.E., & Weinberg, G.B. (1993). A comparison of familial and sporadic Alzheimer’s disease. Neurology, 43, 1377–1384.CrossRefGoogle ScholarPubMed
Dubois, B., Feldman, H.H., Jacova, C., Dekosky, S.T., Barberger-Gateau, P., Cummings, J., & Scheltens, P. (2007). Research criteria for the diagnosis of Alzheimer’s disease: Revising the NINCDS-ADRDA criteria. Lancet Neurology, 6, 734–746.Google Scholar
Fleisher, A.S., Chen, K., Quiroz, Y.T., Jakimovich, L.J., Gutierrez Gomez, M., Langois, C.M., & Reiman, E.M. (2015). Associations between biomarkers and age in the presenilin 1 E280A autosomal dominant Alzheimer disease kindred: A cross-sectional study. JAMA Neurology, 72, 316–324.CrossRefGoogle ScholarPubMed
Fox, N.C., Warrington, E.K., Seiffer, A.L., Agnew, S.K., & Rossor, M.N. (1998). Presymptomatic cognitive deficits in individuals at risk of familial Alzheimer’s disease. A longitudinal prospective study. Brain, 121, 1631–1639.Google Scholar
Godbolt, A.K., Cipolotti, L., Anderson, V.M., Archer, H., Janssen, J.C., Price, S., & Fox, N.C. (2005). A decade of pre-diagnostic assessment in a case of familial Alzheimer’s disease: Tracking progression from asymptomatic to MCI and dementia. Neurocase, 11, 56–64.CrossRefGoogle Scholar
Haltia, M., Viitanen, M., Sulkava, R., Ala-Hurula, V., Poyhonen, M., Goldfarb, L., & Hardy, J. (1994). Chromosome 14-encoded Alzheimer’s disease: Genetic and clinicopathological description. Annals of Neurology, 36, 362–367.Google Scholar
Jack, C.R., & Holtzman, D.M. (2013). Biomarker modeling of Alzheimer’s disease. Neuron, 80, 1347–1358.Google Scholar
Keller, L., Welander, H., Chiang, H.H., Tjernberg, L.O., Nennesmo, I., Wallin, A.K., & Graff, C. (2010). The PSEN1 I143T mutation in a Swedish family with Alzheimer’s disease: Clinical report and quantification of Aβ in different brain regions. European Journal of Human Genetics, 18, 1202–1208.CrossRefGoogle Scholar
Lezak, M.D., Howieson, D.B., & Loring, D.W. (2004). Neuropsychological Assessment (4th ed.). New York: Oxford University Press.Google Scholar
Lippa, C.F., Saunders, A.M., Smith, T.W., Swearer, J.M., Drachman, D.A., Ghetti, B., & Pollen, D.A. (1996). Familial and sporadic Alzheimer’s disease: Neuropathology cannot exclude a final common pathway. Neurology, 46, 406–412.Google Scholar
McKhann, G., Drachmann, D., Folstein, M., Katzman, R., Price, D., & 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
Mullan, M., Crawford, F., Axelman, K., Houlden, H., Lilius, L., Winblad, B., & Lannfelt, L. (1992). A pathogenic mutation for probable Alzheimer’s disease in the APP gene at the N-terminus of beta-amyloid. Nature Genetics, 1, 345–347.Google Scholar
Nestor, P.J., Scheltens, P., & Hodges, J.R. (2004). Advances in the early detection of Alzheimer’s disease. Nature Medicine, 10(Suppl.). S34–S41.Google Scholar
Newman, S.K., Warrington, E.K., Kennedy, A.M., & Rossor, M.N. (1994). The earliest cognitive change in a person with familial Alzheimer’s disease: Presymptomatic neuropsychological features in a pedigree with familial Alzheimer’s disease confirmed at necropsy. Journal of Neurology, Neurosurgery, and Psychiatry, 57, 967–972.Google Scholar
Nilsberth, C., Westlind-Danielsson, A., Eckman, C.B., Condron, M.M., Axelman, K., Forsell, C., & Lannfelt, L. (2001). The Arctic APP mutation (E693G) causes Alzheimer’s disease by enhanced Aβ protofibril formation. Nature Neuroscience, 4, 887–893.CrossRefGoogle ScholarPubMed
Ringman, J.M. (2005). What the study of persons at risk for familial Alzheimer’s disease can tell us about the earliest stages of the disorder: A review. Journal of Geriatrics Psychiatry and Neurology, 18, 228–233.CrossRefGoogle Scholar
Ryman, D.C., Acosta-Baena, N., Aisen, P.S., Bird, T., Danek, A., Fox, N.C., & Bateman, R.J. (2014). Symptom onset in autosomal dominant Alzheimer disease: A systematic review and meta-analysis. Neurology, 83, 253–260.Google Scholar
Salthouse, T.A. (2010). Selective review of cognitive aging. Journal of the International Neuropsychological Society, 16, 754–760.Google Scholar
Selkoe, D.J., & Hardy, J. (2016). The amyloid hypothesis of Alzheimer’s disease at 25 years. EMBO Molecular Medicine, 8, 595–608.Google Scholar
Sliwinski, M., Lipton, R.B., Buschke, H., & Stewart, W. (1996). The effects of preclinical dementia on estimates of normal cognitive functioning in aging. Journal of Gerontology B Psycholological Science and Social Science, 51, P217–P225.Google Scholar
Sperling, R.A., Aisen, P.S., Beckett, L.A., Bennett, D.A., Craft, S., Fagan, A.M., & Phelps, C.H. (2011). Towards defining the preclinical stage of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s Dementia, 7, 280–292.CrossRefGoogle Scholar
Stern, Y. (2009). Cognitive Reserve. Neuropsychologia, 47, 2015–2028.Google Scholar
Storandt, M., Balota, D.A., Aschenbrenner, A.J., & Morris, J.C. (2014). Clinical and psychological characteristics of the initial cohort of the dominantly inherited Alzheimer network (DIAN). Neuropsychology, 28, 19–29.Google Scholar
Thordardottir, S., Kinhult-Ståhlbom, A., Ferreira, D., Almkvist, O., Westman, E., Zetterberg, H., & Graff, C. (2015). Preclinical cerebrospinal fluid and volumetric magnetic resonance imaging biomarkers in Swedish familial Alzheimer’s disease. Journal of Alzheimer’s Disease, 43, 1393–1402.Google Scholar
Wahlund, L.O., Basun, H., Almkvist, O., Julin, P., Axelman, K., Shigeta, M., & Lannfelt, L. (1999). A follow-up study of the family with the Swedish APP 670/671 Alzheimer’s disease mutation. Dementia and Geriatric Cognitive Disorders, 10, 526–533.Google Scholar
Wechsler, D. (1981). Wechsler Adult Intelligence Scale revised: WAIS-R Manual. New York: Psychological Corporation.Google Scholar
Winblad, B., Amouyel, P., Andrieu, S., Ballard, C., Brayne, C., Brodaty, H., & Zetterberg, H. (2016). Defeating Alzheimer’s disease and other dementias: A priority for European science and society. Lancet Neurology, 15, 455–532.Google Scholar
Winblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L.O., & Petersen, R.C. (2004). Mild cognitive impairment: Beyond controversies, towards a consensus. Journal of Internal Medicine, 256, 240–246.Google Scholar
Yau, W.Y., Tudorascu, D.L., McDade, E.M., Ikonomovic, S., James, J.A., Minhas, D., & Klunk, W.E. (2015). Longitudinal assessment of neuroimaging and clinical markers in autosomal dominant Alzheimer’s disease: A prospective cohort study. Lancet Neurology, 14, 804–813.Google Scholar
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