Biomarker clusters are differentially associated with longitudinal cognitive decline in late midlife

Brain

Volumn 139, Issue 8, 2016, Pages 2261-2274

  Racine, Annie M ^a,b   Koscik, Rebecca L ^a   Berman, Sara E ^a   Nicholas, Christopher R ^a,c   Clark, Lindsay R ^a,c   Okonkwo, Ozioma C ^a   Rowley, Howard A ^a   Asthana, Sanjay ^a,c   Bendlin, Barbara B ^a   Blennow, Kaj ^d,e   Zetterberg, Henrik ^d,e,f   Gleason, Carey E ^a,c   Carlsson, Cynthia M ^a,c   Johnson, Sterling C ^a,c,g  

^a UNIVERSITY OF WISCONSIN SCHOOL OF MEDICINE AND PUBLIC HEALTH   (United States)

^b UNIVERSITY OF WISCONSIN MADISON   (United States)

^c WILLIAM S MIDDLETON MEMORIAL VETERANS HOSPITAL   (United States)

^d UNIVERSITY OF GOTHENBURG   (Sweden)

^e SAHLGRENSKA UNIVERSITY HOSPITAL   (Sweden)

^f UNIVERSITY COLLEGE LONDON   (United Kingdom)

^g UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

cerebrospinal fluid; cluster analysis; longitudinal; neuroimaging; preclinical Alzheimer's disease

Indexed keywords

AMYLOID BETA PROTEIN[1-40]; AMYLOID BETA PROTEIN[1-42]; BIOLOGICAL MARKER; TAU PROTEIN; AMYLOID BETA PROTEIN; AMYLOID BETA-PROTEIN (1-42); PEPTIDE FRAGMENT;

ADULT; AGE DISTRIBUTION; ALZHEIMER DISEASE; ARTICLE; BRAIN ATROPHY; BRAIN SIZE; CEREBROSPINAL FLUID ANALYSIS; CLUSTER ANALYSIS; COGNITION; COGNITIVE DEFECT; COHORT ANALYSIS; EPISODIC MEMORY; EXECUTIVE FUNCTION; FEMALE; HIPPOCAMPUS; HUMAN; LONGITUDINAL STUDY; LUMBAR PUNCTURE; MAJOR CLINICAL STUDY; MALE; MEMORY TEST; MIDDLE AGED; NERVE DEGENERATION; NEUROFIBRILLARY TANGLE; NEUROPATHOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; PROTEIN CEREBROSPINAL FLUID LEVEL; PROTEIN PHOSPHORYLATION; RISK ASSESSMENT; SEMANTIC MEMORY; WHITE MATTER LESION; AGED; AGING; ATROPHY; CEREBROSPINAL FLUID; DIAGNOSTIC IMAGING; PATHOLOGY; PATHOPHYSIOLOGY; WHITE MATTER;

AGED; AGING; ALZHEIMER DISEASE; AMYLOID BETA-PEPTIDES; ATROPHY; BIOMARKERS; CLUSTER ANALYSIS; COGNITIVE DYSFUNCTION; FEMALE; HIPPOCAMPUS; HUMANS; LONGITUDINAL STUDIES; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; PEPTIDE FRAGMENTS; WHITE MATTER;

EID: 84982952687     PISSN: 00068950     EISSN: 14602156     Source Type: Journal    
DOI: 10.1093/brain/aww142     Document Type: Article

References (64)

1. Albert MS, Moss MB, Tanzi R, Jones K. Preclinical prediction of AD using neuropsychological tests. J Int Neuropsychol Soc 2001; 7: 631-9.
2. Alexander DM, Williams LM, Gatt JM, Dobson-Stone C, Kuan SA, Todd EG, et al. The contribution of apolipoprotein E alleles on cognitive performance and dynamic neural activity over six decades. Biol Psychol 2007; 75: 229-38.
3. Almeida RP, Schultz SA, Austin BP, Boots EA, Dowling NM, Gleason CE, et al. Effect of cognitive reserve on age-related changes in cerebrospnal fluid biomarkers of Alzheimer disease. JAMA Neurol 2015; 72: 699-706.
4. Alosco ML, Brickman AM, Spitznagel MB, Griffith EY, Narkhede A, Raz N, et al. Independent and interactive effects of blood pressure and cardiac function on brain volume and white matter hyperintensities in heart failure. J Am Soc Hypertens 2013; 7: 336-43.
5. Backman L, Jones S, Berger AK, Laukka EJ, Small BJ. Cognitive impairment in preclinical Alzheimer's disease: a meta-analysis. Neuropsychology 2005; 19: 520-31.
6. Backman L, Small BJ, Fratiglioni L. Stability of the preclinical episodic memory deficit in Alzheimer's disease. Brain 2001; 124 (Pt 1): 96-102.
7. Berman S, Rivera L, Clark L, Racine A, Carlsson C, Bendlin B, et al. Intracranial arterial 4D-Flow is associated with metrics of brain health and Alzheimer's disease. Alzheimer's Dementia 2015; 1: 420-8.
8. Birdsill AC, Koscik RL, Jonaitis EM, Johnson SC, Okonkwo OC, Hermann BP, et al. Regional white matter hyperintensities: aging, Alzheimer's disease risk, and cognitive function. Neurobiol Aging 2014; 35: 769-76.
9. Brun A, Englund E. A white matter disorder in dementia of the Alzheimer type: a pathoanatomical study. Ann Neurol 1986; 19: 253-62.
10. Casado Naranjo I, Portilla Cuenca JC, Duque de San Juan B, Garcia AF, Sevilla RR, Serrano Cabrera A, et al. Association of vascular factors and amnestic mild cognitive impairment: a comprehensive approach. J Alzheimers Dis 2015; 44: 695-704.
11. Clatworthy J, Buick D, Hankins M, Weinman J, Horne R. The use and reporting of cluster analysis in health psychology: a review. Br J Health Psychol 2005; 10 (Pt 3): 329-58.
12. Collie A, Maruff P. The neuropsychology of preclinical Alzheimer's disease and mild cognitive impairment. Neurosci Biobehav Rev 2000; 24: 365-74.
13. Corey-Bloom J, Galasko D, Hofstetter CR, Jackson JE, Thal LJ. Clinical features distinguishing large cohorts with possible AD, probable AD, and mixed dementia. J Am Geriatr Soc 1993; 41: 31-7.
14. Dormann CF, Elith J, Bacher S, Buchmann C, Carl G, Carre G, et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 2013; 36: 27-46.
15. Dubois B, Hampel H, Feldman HH, Scheltens P, Aisen P, Andrieu S, et al. Preclinical Alzheimer's disease: definition, natural history, and diagnostic criteria. Alzheimers Dement 2016; 12: 292-323.
16. Escudero J, Zajicek JP, Ifeachor E. Early detection and characterization of Alzheimer's disease in clinical scenarios using Bioprofile concepts and K-means. In: Proceedings of the 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA, 2011: 6470-3.
17. Goff DC Jr, Lloyd-Jones DM, Bennett G, Coady S, D'Agostino RB, Sr, Gibbons R, et al. 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/ American heart association task force on practice guidelines. J Am College of Cardiology 2014; 63 (25 Pt B): 2935-59.
18. Grober E, Hall CB, Lipton RB, Zonderman AB, Resnick SM, Kawas C. Memory impairment, executive dysfunction, and intellectual decline in preclinical Alzheimer's disease. J Int Neuropsychol Soc 2008; 14: 266-78.
19. Hair JF, Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate data analysis. Pearson Education Limited; Upper Saddle River, NJ, 2013.
20. Howieson DB, Carlson NE, Moore MM, Wasserman D, Abendroth CD, Payne-Murphy J, et al. Trajectory of mild cognitive impairment onset. J Int Neuropsychol Soc 2008; 14: 192-8.
21. Iqbal K, Flory M, Khatoon S, Soininen H, Pirttila T, Lehtovirta M, et al. Subgroups of Alzheimer's disease based on cerebrospinal fluid molecular markers. Ann Neurol 2005; 58: 748-57.
22. Jack CR Jr, Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS, et al. Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol 2013; 12: 207-16.
23. Jack CR Jr, Knopman DS, Weigand SD, Wiste HJ, Vemuri P, Lowe V, et al. An operational approach to National Institute on Aging-Alzheimer's Association criteria for preclinical Alzheimer disease. Ann Neurol 2012; 71: 765-75.
24. Jansen WJ, Ossenkoppele R, Knol DL, Tijms BM, Scheltens P, Verhey FR, et al. Prevalence of cerebral amyloid pathology in persons without dementia: a meta-analysis. JAMA 2015; 313: 1924-38.
25. Jellinger KA. The enigma of mixed dementia. Alzheimers Dement 2007; 3: 40-53.
26. Johnson SC, Christian BT, Okonkwo OC, Oh JM, Harding S, Xu G, et al. Amyloid burden and neural function in people at risk for Alzheimer's disease. Neurobiol Aging 2014; 35: 576-84.
27. Jonaitis E, La Rue A, Mueller KD, Koscik RL, Hermann B, Sager MA. Cognitive activities and cognitive performance in middle-aged adults at risk for Alzheimer's disease. Psychol Aging 2013; 28: 1004-14.
28. Koscik RL, La Rue A, Jonaitis EM, Okonkwo OC, Johnson SC, Bendlin BB, et al. Emergence of mild cognitive impairment in late middle-aged adults in the wisconsin registry for Alzheimer's prevention. Dement Geriatr Cogn Disord 2014; 38: 16-30.
29. Kramer JH, Reed BR, Mungas D, Weiner MW, Chui HC. Executive dysfunction in subcortical ischaemic vascular disease. J Neurol Neurosurg Psychiatry 2002; 72: 217-20.
30. Mattsson N, Insel PS, Donohue M, Landau S, Jagust WJ, Shaw LM, et al. Independent information from cerebrospinal fluid amyloid-beta and florbetapir imaging in Alzheimer's disease. Brain 2015; 138 (Pt 3): 772-83.
31. Mondadori CR, de Quervain DJ, Buchmann A, Mustovic H, Wollmer MA, Schmidt CF, et al. Better memory and neural efficiency in young apolipoprotein E epsilon4 carriers. Cereb Cortex 2007; 17: 1934-47.
32. Morris JC. Early-stage and preclinical Alzheimer disease. Alzheimer Dis Assoc Disord 2005; 19: 163-5.
33. Moser DJ, Cohen RA, Paul RH, Paulsen JS, Ott BR, Gordon NM, et al. Executive function and magnetic resonance imaging subcortical hyperintensities in vascular dementia. Neuropsychiatry Neuropsychol Behav Neurol 2001; 14: 89-92.
34. Murray ME, Graff-Radford NR, Ross OA, Petersen RC, Duara R, Dickson DW. Neuropathologically defined subtypes of Alzheimer's disease with distinct clinical characteristics: a retrospective study. Lancet Neurol 2011; 10: 785-96.
35. Murtagh F, Legendre P. Ward's hierarchical agglomerative clustering method: which algorithms implement ward's criterion? J Classif 2014; 31: 274-95.
36. Nettiksimmons J, Beckett L, Schwarz C, Carmichael O, Fletcher E, Decarli C. Subgroup of ADNI normal controls characterized by atrophy and cognitive decline associated with vascular damage. Psychol Aging 2013; 28: 191-201.
37. Nettiksimmons J, DeCarli C, Landau S, : Beckett L, Alzheimer's Disease Neuroimaging I. Biological heterogeneity in ADNI amnestic mild cognitive impairment. Alzheimers Dement 2014; 10: 511-21. e1.
38. Nettiksimmons J, Harvey D, Brewer J, Carmichael O, DeCarli C, Jack CR Jr, et al. Subtypes based on cerebrospinal fluid and magnetic resonance imaging markers in normal elderly predict cognitive decline. Neurobiol Aging 2010; 31: 1419-28.
39. Noh Y, Jeon S, Lee JM, Seo SW, Kim GH, Cho H, et al. Anatomical heterogeneity of Alzheimer disease: based on cortical thickness on MRIs. Neurology 2014; 83: 1936-44.
40. Patenaude B, Smith SM, Kennedy DN, Jenkinson M. A Bayesian model of shape and appearance for subcortical brain segmentation. Neuroimage 2011; 56: 907-22.
41. Pike KE, Ellis KA, Villemagne VL, Good N, Chetelat G, Ames D, et al. Cognition and beta-amyloid in preclinical Alzheimer's disease: data from the AIBL study. Neuropsychologia 2011; 49: 2384-90.
42. Provenzano FA, Muraskin J, Tosto G, Narkhede A, Wasserman BT, Griffith EY, et al. White matter hyperintensities and cerebral amyloidosis: necessary and sufficient for clinical expression of Alzheimer disease? JAMA Neurol 2013; 70: 455-61.
43. Querfurth HW, LaFerla FM. Alzheimer's disease. N Engl J Med 2010; 362: 329-44.
44. Racine AM, Adluru N, Alexander AL, Christian BT, Okonkwo OC, Oh J, et al. Associations between white matter microstructure and amyloid burden in preclinical Alzheimer's disease: a multimodal imaging investigation. NeuroImage Clin 2014; 4: 604-14
45. Rajan KB, Wilson RS, Weuve J, Barnes LL, Evans DA. Cognitive impairment 18 years before clinical diagnosis of Alzheimer disease dementia. Neurology 2015; 85: 898-904.
46. Ryan NS, Biessels GJ, Kim L, Nicholas JM, Barber PA, Walsh P, et al. Genetic determinants of white matter hyperintensities and amyloid angiopathy in familial Alzheimer's disease. Neurobiol Aging 2015; 36: 3140-51.
47. Sager MA, Hermann B, La Rue A. Middle-aged children of persons with Alzheimer's disease: APOE genotypes and cognitive function in the Wisconsin Registry for Alzheimer's Prevention. J Geriatr Psychiatry Neurol 2005; 18: 245-9.
48. Scheltens P, Barkhof F, Leys D, Wolters EC, Ravid R, Kamphorst W. Histopathologic correlates of white matter changes on MRI in Alzheimer's disease and normal aging. Neurology 1995; 45: 883-8.
49. Schmidt P, Gaser C, Arsic M, Buck D, Forschler A, Berthele A, et al. An automated tool for detection of FLAIR-hyperintense whitematter lesions in Multiple Sclerosis. Neuroimage 2012; 59: 3774-83.
50. Schneider JA, Arvanitakis Z, Bang W, Bennett DA. Mixed brain pathologies account for most dementia cases in community-dwelling older persons. Neurology 2007; 69: 2197-204.
51. Schneider JA, Bennett DA. Where vascular meets neurodegenerative disease. Stroke 2010; 41 (Suppl 10): S144-6.
52. Skillback T, Zetterberg H, Blennow K, Mattsson N. Cerebrospinal fluid biomarkers for Alzheimer disease and subcortical axonal damage in 5, 542 clinical samples. Alzheimers Res Ther 2013; 5: 47.
53. Starks EJ, Patrick O'Grady J, Hoscheidt SM, Racine AM, Carlsson CM, Zetterberg H, et al. Insulin resistance is associated with higher cerebrospinal fluid tau levels in asymptomatic APOEvarepsilon4 carriers. J Alzheimers Dis 2015; 46: 525-33.
54. Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, et al. Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement 2011; 7: 280-92.
55. Sperling RA, Karlawish J, Johnson KA. Preclinical Alzheimer diseasethe challenges ahead. Nat Rev Neurol 2013; 9: 54-8.
56. Storandt M, Head D, Fagan AM, Holtzman DM, Morris JC. Toward a multifactorial model of Alzheimer disease. Neurobiol Aging 2012; 33: 2262-71.
57. van der Vlies AE, Verwey NA, Bouwman FH, Blankenstein MA, Klein M, Scheltens P, et al. CSF biomarkers in relationship to cognitive profiles in Alzheimer disease. Neurology 2009; 72: 1056-61.
58. Vemuri P, Simon G, Kantarci K, Whitwell JL, Senjem ML, Przybelski SA, et al. Antemortem differential diagnosis of dementia pathology using structural MRI: differential-STAND. Neuroimage 2011; 55: 522-31.
59. Villemagne VL, Burnham S, Bourgeat P, Brown B, Ellis KA, Salvado O, et al. Amyloid b deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study. Lancet Neurol 2013; 12: 357-67.
60. Wallin AK, Blennow K, Zetterberg H, Londos E, Minthon L, Hansson O. CSF biomarkers predict a more malignant outcome in Alzheimer disease. Neurology 2010; 74: 1531-7.
61. Ward JH. Hierarchical grouping to optimize an objective function. J Am Stat Assoc 1963; 58: 236-44.
62. Wen W, Sachdev PS, Li JJ, Chen X, Anstey KJ. White matter hyperintensities in the forties: their prevalence and topography in an epidemiological sample aged 44-48. Hum Brain Mapp 2009; 30: 1155-67.
63. Wright RO, Hu H, Silverman EK, Tsaih SW, Schwartz J, Bellinger D, et al. Apolipoprotein E genotype predicts 24-month bayley scales infant development score. Pediatr Res 2003; 54: 819-25.
64. Young VG, Halliday GM, Kril JJ. Neuropathologic correlates of white matter hyperintensities. Neurology 2008; 71: 804-11.