Abstract

We studied whether gray matter network parameters are associated with rate of clinical progression in nondemented subjects who have abnormal amyloid markers in the cerebrospinal fluid (CSF), that is, predementia Alzheimer's disease. Nondemented subjects (62 with subjective cognitive decline; 160 with mild cognitive impairment (MCI); age = 68 ± 8 years; Mini-Mental State Examination (MMSE) = 28 ± 2.4) were selected from the Amsterdam Dementia Cohort when they had abnormal amyloid in CSF (<640 pg/mL). Networks were extracted from gray matter structural magnetic resonance imaging (MRI), and 9 parameters were calculated. Cox proportional hazards models were used to test associations between each connectivity predictor and rate of progression to MCI or dementia. After a median time of 2.2 years, 122 (55%) subjects showed clinical progression. Lower network parameter values were associated with increased risk for progression, with the strongest hazard ratio of 0.29 for clustering (95% confidence interval = 0.12-0.70; p < 0.01). Results remained after correcting for tau, hippocampal volume, and MMSE scores. Our results suggest that at predementia stages, gray matter network parameters may have use to identify subjects who will show fast clinical progression.

Original languageEnglish
Pages (from-to)75-81
Number of pages7
JournalNeurobiology of Aging
Volume61
DOIs
Publication statusPublished - Jan 2018

Cite this

@article{2afb08b1bce546c6b57b6570cb430c4c,
title = "Gray matter networks and clinical progression in subjects with predementia Alzheimer's disease",
abstract = "We studied whether gray matter network parameters are associated with rate of clinical progression in nondemented subjects who have abnormal amyloid markers in the cerebrospinal fluid (CSF), that is, predementia Alzheimer's disease. Nondemented subjects (62 with subjective cognitive decline; 160 with mild cognitive impairment (MCI); age = 68 ± 8 years; Mini-Mental State Examination (MMSE) = 28 ± 2.4) were selected from the Amsterdam Dementia Cohort when they had abnormal amyloid in CSF (<640 pg/mL). Networks were extracted from gray matter structural magnetic resonance imaging (MRI), and 9 parameters were calculated. Cox proportional hazards models were used to test associations between each connectivity predictor and rate of progression to MCI or dementia. After a median time of 2.2 years, 122 (55{\%}) subjects showed clinical progression. Lower network parameter values were associated with increased risk for progression, with the strongest hazard ratio of 0.29 for clustering (95{\%} confidence interval = 0.12-0.70; p < 0.01). Results remained after correcting for tau, hippocampal volume, and MMSE scores. Our results suggest that at predementia stages, gray matter network parameters may have use to identify subjects who will show fast clinical progression.",
keywords = "Aged, Alzheimer Disease/diagnosis, Amyloid/cerebrospinal fluid, Biomarkers, Cognitive Dysfunction/diagnosis, Disease Progression, Female, Gray Matter/diagnostic imaging, Humans, Magnetic Resonance Imaging, Male, Mental Status and Dementia Tests, Middle Aged, Organ Size, Proportional Hazards Models, Risk, Time Factors",
author = "Tijms, {Betty M.} and {ten Kate}, Mara and Gouw, {Alida A.} and Andreas Borta and Sander Verfaillie and Teunissen, {Charlotte E.} and Philip Scheltens and Frederik Barkhof and {van der Flier}, {Wiesje M.}",
note = "Copyright {\circledC} 2017 Elsevier Inc. All rights reserved.",
year = "2018",
month = "1",
doi = "10.1016/j.neurobiolaging.2017.09.011",
language = "English",
volume = "61",
pages = "75--81",
journal = "Neurobiology of Aging",
issn = "0197-4580",
publisher = "Elsevier Inc.",

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TY - JOUR

T1 - Gray matter networks and clinical progression in subjects with predementia Alzheimer's disease

AU - Tijms, Betty M.

AU - ten Kate, Mara

AU - Gouw, Alida A.

AU - Borta, Andreas

AU - Verfaillie, Sander

AU - Teunissen, Charlotte E.

AU - Scheltens, Philip

AU - Barkhof, Frederik

AU - van der Flier, Wiesje M.

N1 - Copyright © 2017 Elsevier Inc. All rights reserved.

PY - 2018/1

Y1 - 2018/1

N2 - We studied whether gray matter network parameters are associated with rate of clinical progression in nondemented subjects who have abnormal amyloid markers in the cerebrospinal fluid (CSF), that is, predementia Alzheimer's disease. Nondemented subjects (62 with subjective cognitive decline; 160 with mild cognitive impairment (MCI); age = 68 ± 8 years; Mini-Mental State Examination (MMSE) = 28 ± 2.4) were selected from the Amsterdam Dementia Cohort when they had abnormal amyloid in CSF (<640 pg/mL). Networks were extracted from gray matter structural magnetic resonance imaging (MRI), and 9 parameters were calculated. Cox proportional hazards models were used to test associations between each connectivity predictor and rate of progression to MCI or dementia. After a median time of 2.2 years, 122 (55%) subjects showed clinical progression. Lower network parameter values were associated with increased risk for progression, with the strongest hazard ratio of 0.29 for clustering (95% confidence interval = 0.12-0.70; p < 0.01). Results remained after correcting for tau, hippocampal volume, and MMSE scores. Our results suggest that at predementia stages, gray matter network parameters may have use to identify subjects who will show fast clinical progression.

AB - We studied whether gray matter network parameters are associated with rate of clinical progression in nondemented subjects who have abnormal amyloid markers in the cerebrospinal fluid (CSF), that is, predementia Alzheimer's disease. Nondemented subjects (62 with subjective cognitive decline; 160 with mild cognitive impairment (MCI); age = 68 ± 8 years; Mini-Mental State Examination (MMSE) = 28 ± 2.4) were selected from the Amsterdam Dementia Cohort when they had abnormal amyloid in CSF (<640 pg/mL). Networks were extracted from gray matter structural magnetic resonance imaging (MRI), and 9 parameters were calculated. Cox proportional hazards models were used to test associations between each connectivity predictor and rate of progression to MCI or dementia. After a median time of 2.2 years, 122 (55%) subjects showed clinical progression. Lower network parameter values were associated with increased risk for progression, with the strongest hazard ratio of 0.29 for clustering (95% confidence interval = 0.12-0.70; p < 0.01). Results remained after correcting for tau, hippocampal volume, and MMSE scores. Our results suggest that at predementia stages, gray matter network parameters may have use to identify subjects who will show fast clinical progression.

KW - Aged

KW - Alzheimer Disease/diagnosis

KW - Amyloid/cerebrospinal fluid

KW - Biomarkers

KW - Cognitive Dysfunction/diagnosis

KW - Disease Progression

KW - Female

KW - Gray Matter/diagnostic imaging

KW - Humans

KW - Magnetic Resonance Imaging

KW - Male

KW - Mental Status and Dementia Tests

KW - Middle Aged

KW - Organ Size

KW - Proportional Hazards Models

KW - Risk

KW - Time Factors

U2 - 10.1016/j.neurobiolaging.2017.09.011

DO - 10.1016/j.neurobiolaging.2017.09.011

M3 - Article

VL - 61

SP - 75

EP - 81

JO - Neurobiology of Aging

JF - Neurobiology of Aging

SN - 0197-4580

ER -