Tijms, BM;
Ten Kate, M;
Gouw, AA;
Borta, A;
Verfaillie, S;
Teunissen, CE;
Scheltens, P;
... Van der Flier, WM; + view all
(2018)
Gray matter networks and clinical progression in subjects with predementia Alzheimer's disease.
Neurobiology of Aging
, 61
pp. 75-81.
10.1016/j.neurobiolaging.2017.09.011.
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Barkhof_Tijms Segment_Grey matter networks and clinical progression in subjects with pre-dementia Alzheimer's disease.pdf - Accepted Version Download (1MB) | Preview |
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.
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