Associations between Alzheimer disease biomarkers, neurodegeneration, and cognition in cognitively normal older people.

IMPORTANCE Criteria for preclinical Alzheimer disease (AD) propose β-amyloid (Aβ) plaques to initiate neurodegeneration within AD-affected regions. However, some cognitively normal older individuals harbor neural injury similar to patients with AD, without concurrent Aβ burden. Such findings challenge the proposed sequence and suggest that Aβ-independent precursors underlie AD-typical neurodegenerative patterns. OBJECTIVE To examine relationships between Aβ and non-Aβ factors as well as neurodegeneration within AD regions in cognitively normal older adults. The study quantified neurodegenerative abnormalities using imaging biomarkers and examined cross-sectional relationships with Aβ deposition; white matter lesions (WMLs), a marker of cerebrovascular disease; and cognitive functions. DESIGN, SETTING, AND PARTICIPANTS Cross-sectional study in a community-based convenience sample of 72 cognitively normal older individuals (mean [SD] age, 74.9 [5.7] years; 48 women; mean [SD] 17.0 [1.9] years of education) of the Berkeley Aging Cohort. INTERVENTION Each individual underwent a standardized neuropsychological test session, magnetic resonance imaging, and positron emission tomography scanning. MAIN OUTCOMES AND MEASURES For each individual, 3 AD-sensitive neurodegeneration biomarkers were measured: hippocampal volume, glucose metabolism, and gray matter thickness, the latter 2 sampled from cortical AD-affected regions. To quantify neurodegenerative abnormalities, each biomarker was age adjusted, dichotomized into a normal or abnormal status (using cutoff thresholds derived from an independent AD sample), and summarized into 0, 1, or more than 1 abnormal neurodegenerative biomarker. Degree and topographic patterns of neurodegenerative abnormalities were assessed and their relationships with cognitive functions, WML volume, and Aβ deposition (quantified using carbon 11-labeled Pittsburgh compound B positron emission tomography). RESULTS Of our cognitively normal elderly individuals, 40% (n = 29) displayed at least 1 abnormal neurodegenerative biomarker, 26% (n = 19) of whom had no evidence of elevated Pittsburgh compound B retention. In those people who were classified as having abnormal cortical thickness, degree and topographic specificity of neurodegenerative abnormalities were similar to patients with AD. Accumulation of neurodegenerative abnormalities was related to poor memory and executive functions as well as larger WML volumes but not elevated Pittsburgh compound B retention. CONCLUSIONS AND RELEVANCE Our study confirms that a substantial proportion of cognitively normal older adults harbor neurodegeneration, without Aβ burden. Associations of neurodegenerative abnormalities with cerebrovascular disease and cognitive performance indicate that neurodegenerative pathology can emerge through non-Aβ pathways within regions most affected by AD.

[1]  Hwamee Oh,et al.  Association of gray matter atrophy with age, β-amyloid, and cognition in aging. , 2014, Cerebral cortex.

[2]  W. Jagust,et al.  The effect of amyloid β on cognitive decline is modulated by neural integrity in cognitively normal elderly , 2013, Alzheimer's & Dementia.

[3]  L. Kuller,et al.  Cognitive trajectories associated with β-amyloid deposition in the oldest-old without dementia , 2013, Neurology.

[4]  C. Jack,et al.  Brain injury biomarkers are not dependent on β‐amyloid in normal elderly , 2013, Annals of neurology.

[5]  Miranka Wirth,et al.  Alzheimer's Disease Neurodegenerative Biomarkers Are Associated with Decreased Cognitive Function but Not β-Amyloid in Cognitively Normal Older Individuals , 2013, The Journal of Neuroscience.

[6]  A. Dale,et al.  Amyloid-β--associated clinical decline occurs only in the presence of elevated P-tau. , 2012, Archives of neurology.

[7]  C. Jack,et al.  An operational approach to National Institute on Aging–Alzheimer's Association criteria for preclinical Alzheimer disease , 2012, Annals of neurology.

[8]  Cindee M. Madison,et al.  Cerebrovascular disease, beta-amyloid, and cognition in aging , 2012, Neurobiology of Aging.

[9]  Owen Carmichael,et al.  White matter lesions and brain gray matter volume in cognitively normal elders , 2012, Neurobiology of Aging.

[10]  Elizabeth C Mormino,et al.  Not quite PIB-positive, not quite PIB-negative: Slight PIB elevations in elderly normal control subjects are biologically relevant , 2012, NeuroImage.

[11]  L. McEvoy,et al.  Predicting MCI outcome with clinically available MRI and CSF biomarkers , 2011, Neurology.

[12]  Reisa A. Sperling,et al.  Failure to Modulate Attentional Control in Advanced Aging Linked to White Matter Pathology , 2011, Cerebral cortex.

[13]  Denise C. Park,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 , 2011, Alzheimer's & Dementia.

[14]  B Fischl,et al.  Correlations between MRI white matter lesion location and executive function and episodic memory , 2011, Neurology.

[15]  R. Killiany,et al.  Alzheimer-signature MRI biomarker predicts AD dementia in cognitively normal adults , 2011, Neurology.

[16]  Keith A. Johnson,et al.  Amyloid-β Associated Cortical Thinning in Clinically Normal Elderly , 2011, Annals of neurology.

[17]  Hwamee Oh,et al.  β-Amyloid affects frontal and posterior brain networks in normal aging , 2011, NeuroImage.

[18]  L. Ferrucci,et al.  Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [11C]PiB , 2010, Neurology.

[19]  Mark A Mintun,et al.  Cognitive decline and brain volume loss as signatures of cerebral amyloid-beta peptide deposition identified with Pittsburgh compound B: cognitive decline associated with Abeta deposition. , 2009, Archives of neurology.

[20]  A. Fagan,et al.  Multimodal techniques for diagnosis and prognosis of Alzheimer's disease , 2009, Nature.

[21]  Jeffrey A. Fessler,et al.  Reducing between scanner differences in multi-center PET studies , 2009, NeuroImage.

[22]  Cindee M. Madison,et al.  Episodic memory loss is related to hippocampal-mediated beta-amyloid deposition in elderly subjects. , 2009, Brain : a journal of neurology.

[23]  Nick C Fox,et al.  The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods , 2008, Journal of magnetic resonance imaging : JMRI.

[24]  Hae-Jeong Park,et al.  Cortical surface-based analysis of 18F-FDG PET: Measured metabolic abnormalities in schizophrenia are affected by cortical structural abnormalities , 2006, NeuroImage.

[25]  Anders M. Dale,et al.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.

[26]  Felice Sun,et al.  Brain imaging evidence of preclinical Alzheimer's disease in normal aging , 2006, Annals of neurology.

[27]  A. Dale,et al.  Whole Brain Segmentation Automated Labeling of Neuroanatomical Structures in the Human Brain , 2002, Neuron.

[28]  A M Dale,et al.  Measuring the thickness of the human cerebral cortex from magnetic resonance images. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[29]  J F Toole,et al.  Presence and severity of cerebral white matter lesions and hypertension, its treatment, and its control. The ARIC Study. Atherosclerosis Risk in Communities Study. , 1996, Stroke.

[30]  N. Volkow,et al.  Distribution Volume Ratios without Blood Sampling from Graphical Analysis of PET Data , 1996, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[31]  A. Hofman,et al.  Cerebral white matter lesions, vascular risk factors, and cognitive function in a population‐based study , 1994, Neurology.

[32]  S. Folstein,et al.  "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. , 1975, Journal of psychiatric research.

[33]  A. Hofman,et al.  Use of hippocampal and amygdalar volumes on magnetic resonance imaging to predict dementia in cognitively intact elderly people. , 2006, Archives of general psychiatry.

[34]  V. Leirer,et al.  Development and validation of a geriatric depression screening scale: a preliminary report. , 1982, Journal of psychiatric research.