Cognitive Reserve Relates to Functional Network Efficiency in Alzheimer's Disease

Carregando...
Imagem de Miniatura
Citações na Scopus
26
Tipo de produção
article
Data de publicação
2018
Título da Revista
ISSN da Revista
Título do Volume
Editora
FRONTIERS MEDIA SA
Autores
WEILER, Marina
CASSEB, Raphael Fernandes
CAMPOS, Brunno Machado de
TEIXEIRA, Camila Vieira de Ligo
CARLETTI-CASSANI, Ana Flavia Mac Knight
VICENTINI, Jessica Elias
MAGALHAES, Thamires Naela Cardoso
ALMEIRA, Debora Queiroz de
Citação
FRONTIERS IN AGING NEUROSCIENCE, v.10, article ID 255, 14p, 2018
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Alzheimer's disease (AD) is the most common form of dementia, with no means of cure or prevention. The presence of abnormal disease-related proteins in the population is, in turn, much more common than the incidence of dementia. In this context, the cognitive reserve (CR) hypothesis has been proposed to explain the discontinuity between pathophysiological and clinical expression of AD, suggesting that CR mitigates the effects of pathology on clinical expression and cognition. fMRI studies of the human connectome have recently reported that AD patients present diminished functional efficiency in resting-state networks, leading to a loss in information flow and cognitive processing. No study has investigated, however, whether CR modifies the effects of the pathology in functional network efficiency in AD patients. We analyzed the relationship between CR, pathophysiology and network efficiency, and whether CR modifies the relationship between them. Fourteen mild AD, 28 amnestic mild cognitive impairment (aMCI) due to AD, and 28 controls were enrolled. We used education to measure CR, cerebrospinal fluid (CSF) biomarkers to evaluate pathophysiology, and graph metrics to measure network efficiency. We found no relationship between CR and CSF biomarkers; CR was related to higher network efficiency in all groups; and abnormal levels of CSF protein biomarkers were related to more efficient networks in the AD group. Education modified the effects of tau-related pathology in the aMCI and mild AD groups. Although higher CR might not protect individuals from developing AD pathophysiology, AD patients with higher CR are better able to cope with the effects of pathology-presenting more efficient networks despite pathology burden. The present study highlights that interventions focusing on cognitive stimulation might be useful to slow age-related cognitive decline or dementia and lengthen healthy aging.
Palavras-chave
fMRI, graph theory, mild cognitive impairment, neuropathology, educational measurement, network efficiency
Referências
  1. Albert MS, 2011, ALZHEIMERS DEMENT, V7, P270, DOI 10.1016/j.jalz.2011.03.008
  2. Almeida RP, 2015, JAMA NEUROL, V72, P699, DOI 10.1001/jamaneurol.2015.0098
  3. Amieva H, 2014, BRAIN, V137, P1167, DOI 10.1093/brain/awu035
  4. Arenaza-Urquijo EM, 2013, NEUROIMAGE, V83, P450, DOI 10.1016/j.neuroimage.2013.06.053
  5. Arenaza-Urquijo EM, 2013, J ALZHEIMERS DIS, V35, P715, DOI 10.3233/JAD-121906
  6. Beauquis J, 2013, EXP NEUROL, V239, P28, DOI 10.1016/j.expneurol.2012.09.009
  7. Bennett DA, 2003, NEUROLOGY, V60, P1909, DOI 10.1212/01.WNL.0000069923.64550.9F
  8. Bennett DA, 2006, NEUROLOGY, V66, P1837, DOI 10.1212/01.wnl.0000219668.47116.e6
  9. Binnewijzend MAA, 2014, HUM BRAIN MAPP, V35, P2383, DOI 10.1002/hbm.22335
  10. Blennow K, 2009, J ALZHEIMERS DIS, V18, P413, DOI 10.3233/JAD-2009-1177
  11. Boots EA, 2015, ARCH CLIN NEUROPSYCH, V30, P634, DOI 10.1093/arclin/acv041
  12. Bosch B, 2010, CORTEX, V46, P451, DOI 10.1016/j.cortex.2009.05.006
  13. Bozzali M, 2015, J ALZHEIMERS DIS, V44, P243, DOI 10.3233/JAD-141824
  14. Brayne C, 2010, BRAIN, V133, P2210, DOI 10.1093/brain/awq185
  15. Brier MR, 2014, NEUROBIOL AGING, V35, P757, DOI 10.1016/j.neurobiolaging.2013.10.081
  16. Bruandet A, 2008, DEMENT GERIATR COGN, V25, P74, DOI 10.1159/000111693
  17. Brucki SMD, 2003, ARQ NEURO-PSIQUIAT, V61, P777, DOI 10.1590/S0004-282X2003000500014
  18. Bullmore ET, 2009, NAT REV NEUROSCI, V10, P186, DOI 10.1038/nrn2575
  19. Canuet L, 2015, J NEUROSCI, V35, P10325, DOI 10.1523/JNEUROSCI.0704-15.2015
  20. Celebi O, 2016, ARCH GERONTOL GERIAT, V62, P125, DOI 10.1016/j.archger.2015.09.010
  21. Colangeli S, 2016, AM J ALZHEIMERS DIS, V31, P443, DOI 10.1177/1533317516653826
  22. Daianu M, 2015, I S BIOMED IMAGING, P458, DOI 10.1109/ISBI.2015.7163910
  23. de Campos BM, 2016, HUM BRAIN MAPP, V37, P3137, DOI 10.1002/hbm.23231
  24. Del Ser T, 1999, BRAIN, V122, P2309, DOI 10.1093/brain/122.12.2309
  25. FAZEKAS F, 1987, AM J ROENTGENOL, V149, P351, DOI 10.2214/ajr.149.2.351
  26. Fischer FU, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0086258
  27. Forlenza Orestes V, 2015, Alzheimers Dement (Amst), V1, P455, DOI 10.1016/j.dadm.2015.09.003
  28. Franzmeier N, 2017, BRAIN IMAGING BEHAV, V11, P368, DOI 10.1007/s11682-016-9599-1
  29. Guo LH, 2013, ALZHEIMERS DEMENT, V9, P580, DOI 10.1016/j.jalz.2012.10.002
  30. HACHINSKI VC, 1975, ARCH NEUROL-CHICAGO, V32, P632, DOI 10.1001/archneur.1975.00490510088009
  31. Harris P, 2015, NEUROPSYCH DIS TREAT, V11, P2599, DOI 10.2147/NDT.S84292
  32. Ihunwo AO, 2016, NEURAL REGEN RES, V11, P1869, DOI 10.4103/1673-5374.195278
  33. Jack CR, 2010, LANCET NEUROL, V9, P119, DOI 10.1016/S1474-4422(09)70299-6
  34. Jagust WJ, 2011, TRENDS COGN SCI, V15, P520, DOI 10.1016/j.tics.2011.09.004
  35. Jiang Y, 2016, FRONT AGING NEUROSCI, V8, DOI 10.3389/fnagi.2016.00015
  36. Johansson CB, 1999, EXP CELL RES, V253, P733, DOI 10.1006/excr.1999.4678
  37. Khazaee A, 2017, BEHAV BRAIN RES, V322, P339, DOI 10.1016/j.bbr.2016.06.043
  38. Kruschwitz JD, 2015, J NEUROSCI METH, V245, P107, DOI 10.1016/j.jneumeth.2015.02.021
  39. Landau SM, 2012, ARCH NEUROL-CHICAGO, V69, P623, DOI 10.1001/archneurol.2011.2748
  40. Lazarov O, 2005, CELL, V120, P701, DOI 10.1016/j.cell.2005.01.015
  41. Li XZ, 2013, SCI REP-UK, V3, DOI 10.1038/srep01339
  42. Liu YW, 2012, NEURORADIOLOGY, V54, P929, DOI 10.1007/s00234-012-1005-0
  43. Lu YH, 2016, FRONT BEHAV NEUROSCI, V10, DOI 10.3389/fnbeh.2016.00229
  44. Marques P, 2015, SCI REP-UK, V5, DOI 10.1038/srep12812
  45. McKhann GM, 2011, JAMA-J AM MED ASSOC, V305, P2458, DOI 10.1001/jama.2011.810
  46. MORRIS JC, 1993, NEUROLOGY, V43, P2412, DOI 10.1212/WNL.43.11.2412-a
  47. Morris JC, 2010, ANN NEUROL, V67, P122, DOI 10.1002/ana.21843
  48. Nilsson M, 1999, J NEUROBIOL, V39, P569, DOI 10.1002/(SICI)1097-4695(19990615)39:4<569::AID-NEU10>3.0.CO;2-F
  49. Osone A, 2015, GERIATR GERONTOL INT, V15, P428, DOI 10.1111/ggi.12292
  50. Perneczky R, 2006, J NEUROL NEUROSUR PS, V77, P1060, DOI 10.1136/jnnp.2006.094714
  51. PFEFFER RI, 1982, J GERONTOL, V37, P323, DOI 10.1093/geronj/37.3.323
  52. Qiu TT, 2016, J ALZHEIMERS DIS, V54, P1483, DOI 10.3233/JAD-160403
  53. Rentz DM, 2010, ANN NEUROL, V67, P353, DOI 10.1002/ana.21904
  54. Robertson IH, 2013, NEUROBIOL AGING, V34, P298, DOI 10.1016/j.neurobiolaging.2012.05.019
  55. Roe CM, 2008, ARCH NEUROL-CHICAGO, V65, P1467, DOI 10.1001/archneur.65.11.1467
  56. Rubinov M, 2011, NEUROIMAGE, V56, P2068, DOI 10.1016/j.neuroimage.2011.03.069
  57. Rzezak P, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0140945
  58. Santarnecchi E, 2015, CORTEX, V64, P293, DOI 10.1016/j.cortex.2014.11.005
  59. Sanz-Arigita EJ, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0013788
  60. Scarmeas N, 2003, J CLIN EXP NEUROPSYC, V25, P625, DOI 10.1076/jcen.25.5.625.14576
  61. Scarmeas N, 2006, J NEUROL NEUROSUR PS, V77, P308, DOI 10.1136/jnnp.2005.072306
  62. Scarmeas N, 2003, ARCH NEUROL-CHICAGO, V60, P359, DOI 10.1001/archneur.60.3.359
  63. Scarmeas N, 2001, NEUROLOGY, V57, P2236, DOI 10.1212/WNL.57.12.2236
  64. Serra L, 2017, J ALZHEIMERS DIS, V55, P421, DOI 10.3233/JAD-160735
  65. Serra L, 2011, REJUV RES, V14, P143, DOI 10.1089/rej.2010.1103
  66. Shirer WR, 2012, CEREB CORTEX, V22, P158, DOI 10.1093/cercor/bhr099
  67. Soldan A, 2013, NEUROBIOL AGING, V34, P2827, DOI 10.1016/j.neurobiolaging.2013.06.017
  68. Sole-Padulles C, 2009, NEUROBIOL AGING, V30, P1114, DOI 10.1016/j.neurobiolaging.2007.10.008
  69. Song M, 2008, NEUROIMAGE, V41, P1168, DOI 10.1016/j.neuroimage.2008.02.036
  70. Stam CJ, 2007, CEREB CORTEX, V17, P92, DOI 10.1093/cercor/bhj127
  71. Stern Y, 2005, CEREB CORTEX, V15, P394, DOI 10.1093/cercor/bhh142
  72. Stern Y, 2002, J INT NEUROPSYCH SOC, V8, P448, DOI 10.1017/S1355617702813248
  73. Stern Y, 2012, LANCET NEUROL, V11, P1006, DOI 10.1016/S1474-4422(12)70191-6
  74. Supekar K, 2008, PLOS COMPUT BIOL, V4, DOI 10.1371/journal.pcbi.1000100
  75. Tapiola T, 2009, ARCH NEUROL-CHICAGO, V66, P382, DOI 10.1001/archneurol.2008.596
  76. van den Heuvel MP, 2009, J NEUROSCI, V29, P7619, DOI 10.1523/JNEUROSCI.1443-09.2009
  77. van Praag H, 2000, NAT REV NEUROSCI, V1, P191, DOI 10.1038/35044558
  78. Wang JH, 2015, HUM BRAIN MAPP, V36, P1828, DOI 10.1002/hbm.22740
  79. Wang JH, 2013, BIOL PSYCHIAT, V73, P472, DOI 10.1016/j.biopsych.2012.03.026
  80. Wang L, 2013, JAMA NEUROL, V70, P1242, DOI 10.1001/jamaneurol.2013.3253
  81. Yaffe K, 2011, JAMA-J AM MED ASSOC, V305, P261, DOI 10.1001/jama.2010.1995
  82. Zalesky A, 2010, NEUROIMAGE, V53, P1197, DOI 10.1016/j.neuroimage.2010.06.041
  83. Zalesky A, 2010, NEUROIMAGE, V50, P970, DOI 10.1016/j.neuroimage.2009.12.027