MRI and CSF biomarkers in normal, MCI, and AD subjects: Predicting future clinical change

Prashanthi D Vemuri, H. J. Wiste, S. D. Weigand, L. M. Shaw, J. Q. Trojanowski, M. W. Weiner, David S Knopman, Ronald Carl Petersen, Clifford R Jr. Jack

Research output: Contribution to journalArticle

261 Citations (Scopus)

Abstract

OBJECTIVE: To investigate the relationship between baseline MRI and CSF biomarkers and subsequent change in continuous measures of cognitive and functional abilities in cognitively normal (CN) subjects and patients with amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD) and to examine the ability of these biomarkers to predict time to conversion from aMCI to AD. METHODS: Data from the Alzheimer's Disease Neuroimaging Initiative, which consists of CN, aMCI, and AD cohorts with both CSF and MRI, were used. Baseline CSF (t-tau, Aβ1-42, and p-tau181P) and MRI scans were obtained in 399 subjects (109 CN, 192 aMCI, 98 AD). Structural Abnormality Index (STAND) scores, which reflect the degree of AD-like features in MRI, were computed for each subject. RESULTS: Change on continuous measures of cognitive and functional performance was modeled as average Clinical Dementia Rating-sum of boxes and Mini-Mental State Examination scores over a 2-year period. STAND was a better predictor of subsequent cognitive/functional change than CSF biomarkers. Single-predictor Cox proportional hazard models for time to conversion from aMCI to AD showed that STAND and log (t-tau/Aβ1-42) were both predictive of future conversion. The age-adjusted hazard ratio for an interquartile change (95% confidence interval) of STAND was 2.6 (1.7, 4.2) and log (t-tau/Aβ1-42) was 2.0 (1.1, 3.4). Both MRI and CSF provided information about future cognitive change even after adjusting for baseline cognitive performance. CONCLUSIONS: MRI and CSF provide complimentary predictive information about time to conversion from amnestic mild cognitive impairment to Alzheimer disease and combination of the 2 provides better prediction than either source alone. However, we found that MRI was a slightly better predictor of future clinical/functional decline than the CSF biomarkers tested.

Original languageEnglish (US)
Pages (from-to)294-301
Number of pages8
JournalNeurology
Volume73
Issue number4
DOIs
StatePublished - Jul 2009

Fingerprint

Alzheimer Disease
Biomarkers
Aptitude
Proportional Hazards Models
Neuroimaging
Dementia
Cognitive Dysfunction
Magnetic Resonance Imaging
Confidence Intervals

ASJC Scopus subject areas

  • Clinical Neurology

Cite this

MRI and CSF biomarkers in normal, MCI, and AD subjects : Predicting future clinical change. / Vemuri, Prashanthi D; Wiste, H. J.; Weigand, S. D.; Shaw, L. M.; Trojanowski, J. Q.; Weiner, M. W.; Knopman, David S; Petersen, Ronald Carl; Jack, Clifford R Jr.

In: Neurology, Vol. 73, No. 4, 07.2009, p. 294-301.

Research output: Contribution to journalArticle

Vemuri, Prashanthi D ; Wiste, H. J. ; Weigand, S. D. ; Shaw, L. M. ; Trojanowski, J. Q. ; Weiner, M. W. ; Knopman, David S ; Petersen, Ronald Carl ; Jack, Clifford R Jr. / MRI and CSF biomarkers in normal, MCI, and AD subjects : Predicting future clinical change. In: Neurology. 2009 ; Vol. 73, No. 4. pp. 294-301.
@article{b441e03b7c104092affe456904cb147d,
title = "MRI and CSF biomarkers in normal, MCI, and AD subjects: Predicting future clinical change",
abstract = "OBJECTIVE: To investigate the relationship between baseline MRI and CSF biomarkers and subsequent change in continuous measures of cognitive and functional abilities in cognitively normal (CN) subjects and patients with amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD) and to examine the ability of these biomarkers to predict time to conversion from aMCI to AD. METHODS: Data from the Alzheimer's Disease Neuroimaging Initiative, which consists of CN, aMCI, and AD cohorts with both CSF and MRI, were used. Baseline CSF (t-tau, Aβ1-42, and p-tau181P) and MRI scans were obtained in 399 subjects (109 CN, 192 aMCI, 98 AD). Structural Abnormality Index (STAND) scores, which reflect the degree of AD-like features in MRI, were computed for each subject. RESULTS: Change on continuous measures of cognitive and functional performance was modeled as average Clinical Dementia Rating-sum of boxes and Mini-Mental State Examination scores over a 2-year period. STAND was a better predictor of subsequent cognitive/functional change than CSF biomarkers. Single-predictor Cox proportional hazard models for time to conversion from aMCI to AD showed that STAND and log (t-tau/Aβ1-42) were both predictive of future conversion. The age-adjusted hazard ratio for an interquartile change (95{\%} confidence interval) of STAND was 2.6 (1.7, 4.2) and log (t-tau/Aβ1-42) was 2.0 (1.1, 3.4). Both MRI and CSF provided information about future cognitive change even after adjusting for baseline cognitive performance. CONCLUSIONS: MRI and CSF provide complimentary predictive information about time to conversion from amnestic mild cognitive impairment to Alzheimer disease and combination of the 2 provides better prediction than either source alone. However, we found that MRI was a slightly better predictor of future clinical/functional decline than the CSF biomarkers tested.",
author = "Vemuri, {Prashanthi D} and Wiste, {H. J.} and Weigand, {S. D.} and Shaw, {L. M.} and Trojanowski, {J. Q.} and Weiner, {M. W.} and Knopman, {David S} and Petersen, {Ronald Carl} and Jack, {Clifford R Jr.}",
year = "2009",
month = "7",
doi = "10.1212/WNL.0b013e3181af79fb",
language = "English (US)",
volume = "73",
pages = "294--301",
journal = "Neurology",
issn = "0028-3878",
publisher = "Lippincott Williams and Wilkins",
number = "4",

}

TY - JOUR

T1 - MRI and CSF biomarkers in normal, MCI, and AD subjects

T2 - Predicting future clinical change

AU - Vemuri, Prashanthi D

AU - Wiste, H. J.

AU - Weigand, S. D.

AU - Shaw, L. M.

AU - Trojanowski, J. Q.

AU - Weiner, M. W.

AU - Knopman, David S

AU - Petersen, Ronald Carl

AU - Jack, Clifford R Jr.

PY - 2009/7

Y1 - 2009/7

N2 - OBJECTIVE: To investigate the relationship between baseline MRI and CSF biomarkers and subsequent change in continuous measures of cognitive and functional abilities in cognitively normal (CN) subjects and patients with amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD) and to examine the ability of these biomarkers to predict time to conversion from aMCI to AD. METHODS: Data from the Alzheimer's Disease Neuroimaging Initiative, which consists of CN, aMCI, and AD cohorts with both CSF and MRI, were used. Baseline CSF (t-tau, Aβ1-42, and p-tau181P) and MRI scans were obtained in 399 subjects (109 CN, 192 aMCI, 98 AD). Structural Abnormality Index (STAND) scores, which reflect the degree of AD-like features in MRI, were computed for each subject. RESULTS: Change on continuous measures of cognitive and functional performance was modeled as average Clinical Dementia Rating-sum of boxes and Mini-Mental State Examination scores over a 2-year period. STAND was a better predictor of subsequent cognitive/functional change than CSF biomarkers. Single-predictor Cox proportional hazard models for time to conversion from aMCI to AD showed that STAND and log (t-tau/Aβ1-42) were both predictive of future conversion. The age-adjusted hazard ratio for an interquartile change (95% confidence interval) of STAND was 2.6 (1.7, 4.2) and log (t-tau/Aβ1-42) was 2.0 (1.1, 3.4). Both MRI and CSF provided information about future cognitive change even after adjusting for baseline cognitive performance. CONCLUSIONS: MRI and CSF provide complimentary predictive information about time to conversion from amnestic mild cognitive impairment to Alzheimer disease and combination of the 2 provides better prediction than either source alone. However, we found that MRI was a slightly better predictor of future clinical/functional decline than the CSF biomarkers tested.

AB - OBJECTIVE: To investigate the relationship between baseline MRI and CSF biomarkers and subsequent change in continuous measures of cognitive and functional abilities in cognitively normal (CN) subjects and patients with amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD) and to examine the ability of these biomarkers to predict time to conversion from aMCI to AD. METHODS: Data from the Alzheimer's Disease Neuroimaging Initiative, which consists of CN, aMCI, and AD cohorts with both CSF and MRI, were used. Baseline CSF (t-tau, Aβ1-42, and p-tau181P) and MRI scans were obtained in 399 subjects (109 CN, 192 aMCI, 98 AD). Structural Abnormality Index (STAND) scores, which reflect the degree of AD-like features in MRI, were computed for each subject. RESULTS: Change on continuous measures of cognitive and functional performance was modeled as average Clinical Dementia Rating-sum of boxes and Mini-Mental State Examination scores over a 2-year period. STAND was a better predictor of subsequent cognitive/functional change than CSF biomarkers. Single-predictor Cox proportional hazard models for time to conversion from aMCI to AD showed that STAND and log (t-tau/Aβ1-42) were both predictive of future conversion. The age-adjusted hazard ratio for an interquartile change (95% confidence interval) of STAND was 2.6 (1.7, 4.2) and log (t-tau/Aβ1-42) was 2.0 (1.1, 3.4). Both MRI and CSF provided information about future cognitive change even after adjusting for baseline cognitive performance. CONCLUSIONS: MRI and CSF provide complimentary predictive information about time to conversion from amnestic mild cognitive impairment to Alzheimer disease and combination of the 2 provides better prediction than either source alone. However, we found that MRI was a slightly better predictor of future clinical/functional decline than the CSF biomarkers tested.

UR - http://www.scopus.com/inward/record.url?scp=68249111164&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=68249111164&partnerID=8YFLogxK

U2 - 10.1212/WNL.0b013e3181af79fb

DO - 10.1212/WNL.0b013e3181af79fb

M3 - Article

C2 - 19636049

AN - SCOPUS:68249111164

VL - 73

SP - 294

EP - 301

JO - Neurology

JF - Neurology

SN - 0028-3878

IS - 4

ER -