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Journal of Neurology

, Volume 266, Issue 6, pp 1310–1322 | Cite as

Mapping the neuroanatomy of functional decline in Alzheimer’s disease from basic to advanced activities of daily living

  • Andrea SlachevskyEmail author
  • Gonzalo Forno
  • Paulo Barraza
  • Eneida Mioshi
  • Carolina Delgado
  • Patricia Lillo
  • Fernando Henriquez
  • Eduardo Bravo
  • Mauricio Farias
  • Carlos Muñoz-Neira
  • Agustin Ibañez
  • Mario A. Parra
  • Michael Hornberger
Original Communication

Abstract

Background

Impairments in activities of daily living (ADL) are a criterion for Alzheimer’s disease (AD) dementia. However, ADL gradually decline in AD, impacting on advanced (a-ADL, complex interpersonal or social functioning), instrumental (IADL, maintaining life in community), and finally basic functions (BADL, activities related to physiological and self-maintenance needs). Information and communication technologies (ICT) have become an increasingly important aspect of daily functioning. Yet, the links of ADL, ICT, and neuropathology of AD dementia are poorly understood. Such knowledge is critical as it can provide biomarker evidence of functional decline in AD.

Methods

ADL were evaluated with the Technology–Activities of Daily Living Questionnaire (T-ADLQ) in 33 patients with AD and 30 controls. ADL were divided in BADL, IADL, and a-ADL. The three domain subscores were covaried against gray matter atrophy via voxel-based morphometry.

Results

Our results showed that three domain subscores of ADL correlate with several brain structures, with a varying degree of overlap between them. BADL score correlated mostly with frontal atrophy, IADL with more widespread frontal, temporal and occipital atrophy and a-ADL with occipital and temporal atrophy. Finally, ICT subscale was associated with atrophy in the precuneus.

Conclusions

The association between ADL domains and neurodegeneration in AD follows a traceable neuropathological pathway which involves different neural networks. This the first evidence of ADL phenotypes in AD characterised by specific patterns of functional decline and well-defined neuropathological changes. The identification of such phenotypes can yield functional biomarkers for dementias such as AD.

Keywords

Alzheimer’s disease Functional impairment Activities of daily living Technology–activities of daily living questionnaire 

Notes

Acknowledgements

Funding from CONICYT/FONDECYT/11404223 (to A.S, C.D, E.B, F.H, C.M., and P.B); FONDAP Program Grant 15150012 (to AS, PL, GF and AI); CONICYT/FONDECYT (Regular 1170010), CONICYT/FONDECYT regular 1160940 (to AS and PL), the INECO Foundation (to AI), the Global Brain Health Institute (GBHI-UCSF) (to AI),  the Inter-American Development Bank (IADB) (to AI and AS), PIA-CONICYT Basal Funds for Centers of Excellence Project FB0003 (to A.S; PB and FH) and the Alzheimer’s Society (Grant AS-SF-14-008) (to MAP).

Compliance with ethical standards

Conflicts of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Ethical approval

All the procedures conducted with the participants of this study were carried out according to the Declaration of Helsinki. Ethical approvals were provided by the Ethical and Scientific Committees of the East Metropolitan Health Service and Hospital Clínico Universidad de Chile from Santiago, Chile.

Supplementary material

415_2019_9260_MOESM1_ESM.docx (172 kb)
Supplementary material 1 (DOCX 172 KB)

References

  1. 1.
    Ferri CP, Prince M, Brayne C, Brodaty H, Fratiglioni L, Ganguli M, Hall K, Hasegawa K, Hendrie H, Huang Y, Jorm A, Mathers C, Menezes PR, Rimmer E, Scazufca M (2005) Global prevalence of dementia: a Delphi consensus study. Lancet 366:2112–2117Google Scholar
  2. 2.
    Qiu C, Kivipelto M, von Strauss E (2009) Epidemiology of Alzheimer’s disease: occurrence, determinants, and strategies toward intervention. Dialogues Clin Neurosci 11:111–128Google Scholar
  3. 3.
    McKhanna GM, Knopman DS, Chertkow H, Hyman BT, Jack CRJ, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, Mohs RC, Morris JC, Rossor MN, Scheltens P, Carrillo MC, Thies B, Weintraub S, Phelps CH (2011) The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7:263–269Google Scholar
  4. 4.
    De Vriendt P, Gorus E, Cornelis E, Bautmans I, Petrovic M, Mets T (2013) The Advanced activities of daily living: a tool allowing the evaluation of subtle functional decline in mild cognitive impairment. J Nutr Health Aging 17:64–71Google Scholar
  5. 5.
    De Vriendt P, Gorus E, Cornelis E, Velghe A, Petrovic M, Mets T (2012) The process of decline in advanced activities of daily living: a qualitative explorative study in mild cognitive impairment. Int Psychogeriatr 24:974–986Google Scholar
  6. 6.
    Dias EG, de Andrade FB, de Oliveira Duarte YA, Ferreira Santos JL, Lúcia Lebrão M (2015) Advanced activities of daily living and incidence of cognitive decline in the elderly: the SABE Study. Cad Saúde Pública 8:1–13Google Scholar
  7. 7.
    Reuben DB, Laliberte L, Hiris J, Mor V (1990) A hierarchical exercise scale to measure function at the advanced activities of daily living (AADL) level. J Am Geriatr Soc 38:855–861Google Scholar
  8. 8.
    De Vriendt P, Mets T, Petrovic M, Gorus E (2015) Discriminative power of the advanced activities of daily living (a-ADL) tool in the diagnosis of mild cognitive impairment in an older population. Int Psychogeriatr 27:1419–1427Google Scholar
  9. 9.
    Femia EE, Zarit SH, Johansson B (1997) Predicting change in activities of daily living: a longitudinal study of the oldest old in Sweden. J Gerontol Psychol Sci 52B:294–302Google Scholar
  10. 10.
    Goldberg TE, Koppel J, Keehlisen L, Christen E, Dreses-Werringloer U, Conejero-Goldberg C, Gordon ML, Davies P (2010) Performance-based measures of everyday function in mild cognitive impairment. Am J Psychiatry 167:845–853Google Scholar
  11. 11.
    Reisberg B, Finkel S, Overall J, Schmidt-Gollas N, Kanowski S, Lehfeld H, Hulla F, Sclan S, Wilms H, Heininger I, Stemmler M, Poon L, Kluger A, Cooler C, Bergener M, Hugonot-Diener L, Robert P, Antipolis S, Erzigkeit H (2001) The Alzheimer’s disease activities of daily living international scale (ADL-IS). Int Psychogeriatr 13:163–181Google Scholar
  12. 12.
    Kalisch T, Richter J, Lenz M, Kattenstroth J-C, Kolankowska I, Tegenthoff M, Dinse HR (2011) Questionnaire-based evaluation of everyday competence in older adults. Clin Interv Aging 6:37–46Google Scholar
  13. 13.
    Rosenberg L, Kottorp A, Winblad B, Nygard L (2009) Perceived difficulty in everyday technology use among older adults with or without cognitive deficits. Scand J Occup Ther 16:216–226Google Scholar
  14. 14.
    Luborsky MR (1993) Sociocultural factors shaping technology usage: fulfilling the promise. Technol Disabil 2:71–78Google Scholar
  15. 15.
    Mioshi E, Hodges JR, Hornberger M (2013) Neural correlates of activities of daily living in frontotemporal dementia. J Geriatr Psychiatry Neurol 26:51–57Google Scholar
  16. 16.
    Cahn-Weiner D, Farias S, Julian L, Harvey DJ, Kramer JH, Reed BR, Mungas D, Wetzel M, Chui H (2007) Cognitive and neuroimaging predictors of instrumental activities of daily living. J Int Neuropsychol Soc 13:747–757Google Scholar
  17. 17.
    Marshall GA, Lorius N, Locascio JJ, Hyman BT, Rentz DM, Johnson KA, Sperling RA (2014) Regional cortical thinning and cerebrospinal biomarkers predict worsening daily functioning across the Alzheimer’s disease spectrum. J Alzheimers Dis 41:719–728Google Scholar
  18. 18.
    Roy K, Pepin LC, Philiossaint M, Lorius N, Becker JA, Locascio JJ, Rentz DM, Sperling RA, Johnson KA, Marshall GA (2014) Regional fluorodeoxyglucose metabolism and instrumental activities of daily living across the Alzheimer’s disease spectrum. J Alzheimers Dis 42:291–300Google Scholar
  19. 19.
    Muñoz-Neira C, Henriquez F, Ihnen J, Sánchez-Cea M, Flores P, Slachevsky A (2012) Propiedades Psicométricas y Utilidad Diagnóstica del Addenbrooke’s Cognitive Examination—Revised (ACE-R) en una muestra de ancianos chilenos. Rev Med Chil 140:1006–1013Google Scholar
  20. 20.
    Muñoz-Neira C, López L, Riveros O, Núñez-Huasaf R, Flores J, Slachevsky P A (2012) The technology—activities of daily living questionnaire: a version with a technology-related subscale. Dement Geriatr Cogn Disord 33:361–371Google Scholar
  21. 21.
    Folstein MF, Folstein SE, McHugh PR (1975) Mini-mental state: a practical method for grading the cognitive state of patients for clinician. J Psychiatr Res 12:189–198Google Scholar
  22. 22.
    Rey A (1959) Test de copie d’une figure complexe. Centre de Psychologie Appliquée, ParisGoogle Scholar
  23. 23.
    Dubois B, Slachevsky A, Litvan I, Pillon B (2000) The FAB: a frontal assessment battery at bedside. Neurology 55:1621–1626Google Scholar
  24. 24.
    Nelson HE (1976) A modified card sorting test sensitive to frontal lobe defects. Cortex 12:313–324Google Scholar
  25. 25.
    Reitan R (1958) Validity of the trail making test as an indication of organic brain damage. Percept Mot Skills 8:271–276Google Scholar
  26. 26.
    Arango-Lasprilla JC, Rivera D, Aguayo A, Rodriguez W, Garza M, Saracho C, Rodriguez-Agudelo Y, Aliaga A, Weiler G, Luna M, Longoni M, Ocampo-Barba N, Galarza-del-Angel J, Panyavin I, Guerra A, Esenarro L, Garcia de la Cadena P, Martinez C, Perrin P (2015) Trail making test: normative data for the Latin American Spanish speaking adult population. NeuroRehabilitation 37:639–661Google Scholar
  27. 27.
    Johnson N, Barion A, Rademaker A, Rehkemper G, Weintraub S (2004) The activities of daily living questionnaire: a validation study in patients with dementia. Alzheimer Dis Assoc Disord 18:223–230Google Scholar
  28. 28.
    Cohen J (1988) Statistical power analysis for the behavioral sciences. L. Erlbaum Associates, HillsdaleGoogle Scholar
  29. 29.
    Ashburner J, Friston KJ (2000) Voxel-based morphometry—the methods. Neuroimage 11:805–821Google Scholar
  30. 30.
    Good CD, Johnsrude IS, Ashburner J, Henson RN, Friston KJ, Frackowiak RS (2001) A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage 14:21–36Google Scholar
  31. 31.
    Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TE, Johansen-Berg H, Bannister PR, De Luca M, Drobnjak I, Flitney DE, Niazy RK, Saunders J, Vickers J, Zhang Y, De Stefano N, Brady JM, Matthews PM (2004) Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23(Suppl 1):S208–S219Google Scholar
  32. 32.
    Zhang Y, Brady M, Smith S (2001) Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging 20:45–57Google Scholar
  33. 33.
    Andersson JLR, Jenkinson M, Smith S (2007) Non-linear optimisation. FMRIB technical report. In: FMRIB Analysis Group technical reports. FMRIB technical reportGoogle Scholar
  34. 34.
    Rueckert D, Sonoda LI, Hayes C, Hill DLG, Leach MO, Hawkes DJ (1999) Non-rigid registration using free-form deformations: application to breast MR images. IEEE Trans Med Imaging 18:712–721Google Scholar
  35. 35.
    Nichols TE, Holmes AP (2002) Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp 15:1–25Google Scholar
  36. 36.
    Irish M, Piguet O, Hodges JR, Hornberger M (2014) Common and unique gray matter correlates of episodic memory dysfunction in frontotemporal dementia and Alzheimer’s disease. Hum Brain Mapp 35:1422–1435Google Scholar
  37. 37.
    Henon H, Pasquier F, Durieu I, Pruvo JP, Leys D (1998) Medial temporal lobe atrophy in stroke patients: relation to pre-existing dementia. J Neurol Neurosurg Psychiatry 65:641–647Google Scholar
  38. 38.
    Yoshida D, Shimada H, Makizako H, Doi T, Ito K, Kato T, Shimokata H, Washimi Y, Endo H, Suzuki T (2012) The relationship between atrophy of the medial temporal area and daily activities in older adults with mild cognitive impairment. Aging Clin Exp Res 24:423–429Google Scholar
  39. 39.
    Aminoff EM, Kveraga K, Bar M (2013) The role of the parahippocampal cortex in cognition. Trends Cogn Sci 17:379–390Google Scholar
  40. 40.
    Echavarri C, Aalten P, Uylings HB, Jacobs HI, Visser PJ, Gronenschild EH, Verhey FR, Burgmans S (2011) Atrophy in the parahippocampal gyrus as an early biomarker of Alzheimer’s disease. Brain Struct Funct 215:265–271Google Scholar
  41. 41.
    Nijboer T, van de Port I, Schepers V, Post M, Visser-Meily A (2013) Predicting functional outcome after stroke: the influence of neglect on basic activities in daily living. Front Hum Neurosci 7:182Google Scholar
  42. 42.
    Mercier L, Audet T, Hébert R, Rochette A, Dubois MF (2001) Impact of motor, cognitive, and perceptual disorders on ability to perform activities of daily living after stroke. Stroke 32:2602–2608Google Scholar
  43. 43.
    Gialanella B, Santoro R, Ferlucci C (2013) Predicting outcome after stroke: the role of basic activities of daily living predicting outcome after stroke. Eur J Phys Rehabil Med 49:629–637Google Scholar
  44. 44.
    Scarmeas N, Hadjigeorgoioi GM, Papadimitriou A, Dubois B, Sarazin M, Brandt J, Albert M, Marder K, Bell K, Honig LS, Wegesin D, Stern Y (2004) Motor signs during the course of Alzheimer disease. Neurology 63:975–982Google Scholar
  45. 45.
    Vidoni ED, Honea RA, Burns JM (2010) Neural correlates of impaired functional independence in early Alzheimer’s disease. J Alzheimers Dis 19:517–527Google Scholar
  46. 46.
    Baune BT, Schmidt WP, Roesler A, Berger K (2009) Functional consequences of subcortical white matter lesions and MRI-defined brain infarct in an elderly general population. J Geriatr Psychiatry Neurol 22:266–273Google Scholar
  47. 47.
    Golby A, Silverberg G, Race E, Gabrieli S, O’Shea J, Knierim K, Stebbins G, Gabrieli J (2005) Memory encoding in Alzheimer’s disease: an fMRI study of explicit and implicit memory. Brain 128:773–787Google Scholar
  48. 48.
    Braak H, Braak E (1997) Diagnostic criteria for neuropathologic assessment of Alzheimer’s disease. Neurobiol Aging 18: S85–S88Google Scholar
  49. 49.
    Almkvist O (1996) Neuropsychological features of early Alzheimer’s disease: preclinical and clinical stages. Acta Neurol Scand 94:63–71Google Scholar
  50. 50.
    Crosson B, Sadek JR, Bobholz JA, Gokcay D, Mohr CM, Leonard CM, Maron L, Auerbach EJ, Browd SR, Freeman AJ, Briggs RW (1999) Activity in the paracingulate and cingulate sulci during word generation: an fMRI study of functional anatomy. Cereb Cortex 9:307–316Google Scholar
  51. 51.
    Desai AK, Grossberg GT, Sheth DN (2004) Activities of daily living in patients with dementia: clinical relevance, methods of assessment and effects of treatment. CNS Drugs 18:853–875Google Scholar
  52. 52.
    Maguire EA, Burgess N, Donnett JG, Frackowiak RS, Frith CD, O’Keefe J (1998) Knowing where and getting there: a human navigation network. Science 280:921–924Google Scholar
  53. 53.
    Aguirre GK, Detre JA, Alsop DC, D’Esposito M (1996) The parahippocampus subserves topographical learning in man. Cereb Cortex 6:823–829Google Scholar
  54. 54.
    Mellet E, Briscogne S, Tzourio-Mazoyer N, Ghaem O, Petit L, Zago L, Etard O, Berthoz A, Mazoyer B, Denis M (2000) Neural correlates of topographic mental exploration: the impact of route versus survey perspective learning. NeuroImage 12:588–600Google Scholar
  55. 55.
    Wenderoth N, Debaere F, Sunaert S, Swinnen SP (2005) The role of anterior cingulate cortex and precuneus in the coordination of motor behaviour. Eur J Neurosci 22:235–246Google Scholar
  56. 56.
    Karas G, Scheltens P, Rombouts S, van Schijndel R, Klein M, Jones B, van der Flier W, Vrenken H, Barkhof F (2007) Precuneus atrophy in early-onset Alzheimer’s disease: a morphometric structural MRI study. Neuroradiology 49:967–976Google Scholar
  57. 57.
    Cavanna AE, Trimble MR (2006) The precuneus: a review of its functional anatomy and behavioural correlates. Brain 129:564–583Google Scholar
  58. 58.
    Small GW, Moody TD, Siddarth P, Bookheimer SY (2009) Your brain on Google: patterns of cerebral activation during internet searching. Am J Geriatr Psychiatry 17:116–126Google Scholar
  59. 59.
    Sagari A, Iso N, Moriuchi T, Ogahara K, Kitajima E, Tanaka K, Tabira T, Higashi T (2015) Changes in cerebral hemodynamics during complex motor learning by character entry into touch-screen terminals. PLoS One 10(10):e0140552Google Scholar
  60. 60.
    Counts SE, Ikonomovic MD, Mercado N, Vega IE, Mufson EJ (2017) Biomarkers for the early detection and progression of Alzheimer’s disease. Neurotherapeutics 14:35–53Google Scholar
  61. 61.
    Subsecretaría de Telecomunicaciones del Gobierno de Chile (2017) Estudio Octava Encuesta sobre Acceso, Usos y Usuarios de Internet en Chile. In: Subsecretaria de Telecomunicaciones (Subtel). Santiago, ChileGoogle Scholar
  62. 62.
    Subsecretaría de Telecomunicaciones de Chile (2018) IX Encuesta de Acceso y Usos de Internet—Informe Final. In: Subsecretaría de Telecomunicaciones, Subtel, Samtiago, ChileGoogle Scholar
  63. 63.
    Neves BB, Amaro F (2012) Too old for technology? How the elderly of Lisbon use and perceive ICT. J Commu Inform 8(1):1–12Google Scholar
  64. 64.
    Delgado C, Vergara RC, Martinez M, Musa G, Henriquez F, Slachevsky A (2019) Neuropsychiatric symptoms in Alzheimer’s disease are the main determinants of functional impairment in advanced everyday activities. J Alzheimers Dis 67:381–392Google Scholar
  65. 65.
    Fillenbaum GG, Chandra V, Ganguli M, Pandav R, Gilby JE, Seaberg EC, Belle S, Baker C, Echement DA, Nath LM (1999) Development of an activities of daily living scale to screen for dementia in an illiterate rural older population in India. Age Ageing 28:161–168Google Scholar
  66. 66.
    Forman SD, Cohen JD, Fitzgerald M, Eddy WF, Mintun MA, Noll DC (1995) Improved assessment of significant activation in functional magnetic resonance imaging (fMRI): use of a cluster-size threshold. Magn Reson Med 33:636–647Google Scholar
  67. 67.
    Jack CR Jr, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, Holtzman DM, Jagust W, Jessen F, Karlawish J, Liu E, Molinuevo JL, Montine T, Phelps C, Rankin KP, Rowe CC, Scheltens P, Siemers E, Snyder HM, Sperling R, Contributors (2018) NIA-AA research framework: toward a biological definition of Alzheimer’s disease. Alzheimers Dement 14:535–562Google Scholar
  68. 68.
    Farias ST, Mungas D, Reed B, Haan MN, Jagust WJ (2004) Everyday functioning in relation to cognitive functioning and neuroimaging in community-dwelling Hispanic and non-Hispanic older adults. J Int Neuropsychol Soc 10:342–354Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Andrea Slachevsky
    • 1
    • 2
    • 3
    • 5
    • 17
    Email author
  • Gonzalo Forno
    • 1
    • 2
    • 3
  • Paulo Barraza
    • 4
  • Eneida Mioshi
    • 6
  • Carolina Delgado
    • 7
    • 17
  • Patricia Lillo
    • 1
    • 16
    • 17
  • Fernando Henriquez
    • 1
    • 2
    • 3
    • 4
  • Eduardo Bravo
    • 8
  • Mauricio Farias
    • 8
  • Carlos Muñoz-Neira
    • 3
  • Agustin Ibañez
    • 10
    • 11
    • 12
    • 13
    • 14
  • Mario A. Parra
    • 9
    • 10
  • Michael Hornberger
    • 6
    • 15
  1. 1.Geroscience Center for Brain Health and Metabolism (GERO), Faculty of MedicineUniversity of ChileSantiagoChile
  2. 2.Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department - ICBM, Neurocience and East Neuroscience Departments, Faculty of MedicineUniversity of ChileSantiagoChile
  3. 3.Memory and Neuropsychiatric Clinic (CMYN) Neurology DepartmentHospital del Salvador and Faculty of Medicine, University of ChileSantiagoChile
  4. 4.Center for Advanced Research in Education (CIAE)University of ChileSantiagoChile
  5. 5.Servicio de Neurología, Departamento de MedicinaClínica Alemana-Universidad del DesarrolloSantiagoChile
  6. 6.School of Health SciencesUniversity of East AngliaNorwichUK
  7. 7.Neurology and Neurosurgery Department, Clinical HospitalUniversity of ChileSantiagoChile
  8. 8.Neuroradiologic DepartmentInstitute of Neurosurgery AsenjoSantiagoChile
  9. 9.Psychology Department, School of Psychological Sciences & HealthUniversity of StrathclydeGlasgowUK
  10. 10.Universidad Autonoma del CaribeBarranquillaColombia
  11. 11.Institute of Cognitive and Translational Neuroscience (INCYT), INECO FoundationFavaloro UniversityBuenos AiresArgentina
  12. 12.National Scientific and Technical Research Council (CONICET)Buenos AiresArgentina
  13. 13.Center for Social and Cognitive Neuroscience (CSCN), School of PsychologyUniversidad Adolfo IbañezSantiagoChile
  14. 14.Centre of Excellence in Cognition and its DisordersAustralian Research Council (ACR)SydneyAustralia
  15. 15.Norfolk and Suffolk Foundation TrustNorwichUK
  16. 16.Departamento de Neurociencia y Neurología Sur, Facultad de MedicinaUniversidad de ChileSantiagoChile
  17. 17.Departamento de Neurociencia, Facultad de MedicinaUniversidad de ChileSantiagoChile

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