» Articles » PMID: 24130528

Biomarker-based Prediction of Progression in MCI: Comparison of AD Signature and Hippocampal Volume with Spinal Fluid Amyloid-β and Tau

Overview
Specialty Geriatrics
Date 2013 Oct 17
PMID 24130528
Citations 78
Authors
Affiliations
Soon will be listed here.
Abstract

Objective: New diagnostic criteria for mild cognitive impairment (MCI) due to Alzheimer's disease (AD) have been developed using biomarkers aiming to establish whether the clinical syndrome is likely due to underlying AD. We investigated the utility of magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) biomarkers in predicting progression from amnesic MCI to dementia, testing the hypotheses that (1) markers of amyloid and neurodegeneration provide distinct and complementary prognostic information over different time intervals, and that (2) evidence of neurodegeneration in amyloid-negative MCI individuals would be useful prognostically.

Methods: Data were obtained from the ADNI-1 (Alzheimer's Disease Neuroimaging Initiative Phase 1) database on all individuals with a baseline diagnosis of MCI, baseline MRI and CSF data, and at least one follow-up visit. MRI data were processed using a published set of a priori regions of interest to derive a measure known as the ``AD signature,'' as well as hippocampal volume. The CSF biomarkers amyloid-β, total tau, and phospho tau were also examined. We performed logistic regression analyses to identify the best baseline biomarker predictors of progression to dementia over 1 or 3 years, and Cox regression models to test the utility of these markers for predicting time-to-dementia.

Results: For prediction of dementia in MCI, the AD signature cortical thickness biomarker performed better than hippocampal volume. Although CSF tau measures were better than CSF amyloid-β at predicting dementia within 1 year, the AD signature was better than all CSF measures at prediction over this relatively short-term interval. CSF amyloid-β was superior to tau and AD signature at predicting dementia over 3 years. When CSF amyloid-β was dichotomized using previously published cutoff values and treated as a categorical variable, a multivariate stepwise Cox regression model indicated that both the AD signature MRI marker and the categorical CSF amyloid-β marker were useful in predicting time-to-event diagnosis of AD dementia.

Conclusion: In amnesic MCI, short-term (1 year) prognosis of progression to dementia relates strongly to baseline markers of neurodegeneration, with the AD signature MRI biomarker of cortical thickness performing the best among MRI and CSF markers studied here. Longer-term (3 year) prognosis in these individuals was better predicted by a marker indicative of brain amyloid. Prediction of time-to-event in a survival model was predicted by the combination of these biomarkers. These results provide further support for emerging models of the temporal relationship of pathophysiologic events in AD and demonstrate the utility of these biomarkers at the prodromal stage of the illness.

Citing Articles

Dissociable spatial topography of cortical atrophy in early-onset and late-onset Alzheimer's disease: A head-to-head comparison of the LEADS and ADNI cohorts.

Katsumi Y, Touroutoglou A, Brickhouse M, Eloyan A, Eckbo R, Zaitsev A Alzheimers Dement. 2025; 21(2):e14489.

PMID: 39968692 PMC: 11851163. DOI: 10.1002/alz.14489.


Connectome-based biophysical models of pathological protein spreading in neurodegenerative diseases.

Ren P, Cui X, Liang X PLoS Comput Biol. 2025; 21(1):e1012743.

PMID: 39836660 PMC: 11750110. DOI: 10.1371/journal.pcbi.1012743.


Alzheimer's disease: a comprehensive review of epidemiology, risk factors, symptoms diagnosis, management, caregiving, advanced treatments and associated challenges.

Safiri S, Ghaffari Jolfayi A, Fazlollahi A, Morsali S, Sarkesh A, Daei Sorkhabi A Front Med (Lausanne). 2024; 11:1474043.

PMID: 39736972 PMC: 11682909. DOI: 10.3389/fmed.2024.1474043.


Greater baseline cortical atrophy in the dorsal attention network predicts faster clinical decline in Posterior Cortical Atrophy.

Katsumi Y, Eckbo R, Chapleau M, Wong B, McGinnis S, Touroutoglou A Alzheimers Res Ther. 2024; 16(1):262.

PMID: 39696378 PMC: 11653806. DOI: 10.1186/s13195-024-01636-z.


Greater baseline cortical atrophy in the dorsal attention network predicts faster clinical decline in Posterior Cortical Atrophy.

Katsumi Y, Eckbo R, Chapleau M, Wong B, McGinnis S, Touroutoglou A medRxiv. 2024; .

PMID: 39484250 PMC: 11527058. DOI: 10.1101/2024.10.15.24315270.


References
1.
Visser P, Verhey F, Knol D, Scheltens P, Wahlund L, Freund-Levi Y . Prevalence and prognostic value of CSF markers of Alzheimer's disease pathology in patients with subjective cognitive impairment or mild cognitive impairment in the DESCRIPA study: a prospective cohort study. Lancet Neurol. 2009; 8(7):619-27. DOI: 10.1016/S1474-4422(09)70139-5. View

2.
Hansson O, Zetterberg H, Buchhave P, Londos E, Blennow K, Minthon L . Association between CSF biomarkers and incipient Alzheimer's disease in patients with mild cognitive impairment: a follow-up study. Lancet Neurol. 2006; 5(3):228-34. DOI: 10.1016/S1474-4422(06)70355-6. View

3.
Bakkour A, Morris J, Wolk D, Dickerson B . The effects of aging and Alzheimer's disease on cerebral cortical anatomy: specificity and differential relationships with cognition. Neuroimage. 2013; 76:332-44. PMC: 4098706. DOI: 10.1016/j.neuroimage.2013.02.059. View

4.
Landau S, Mintun M, Joshi A, Koeppe R, Petersen R, Aisen P . Amyloid deposition, hypometabolism, and longitudinal cognitive decline. Ann Neurol. 2012; 72(4):578-86. PMC: 3786871. DOI: 10.1002/ana.23650. View

5.
Shaw L, Vanderstichele H, Knapik-Czajka M, Clark C, Aisen P, Petersen R . Cerebrospinal fluid biomarker signature in Alzheimer's disease neuroimaging initiative subjects. Ann Neurol. 2009; 65(4):403-13. PMC: 2696350. DOI: 10.1002/ana.21610. View