Neuroimaging measures and chemical biomarkers may be important indices of clinical progression in normal aging and mild cognitive impairment (MCI) and need to be evaluated longitudinally.
To ...characterize cross-sectionally and longitudinally clinical measures in normal controls, subjects with MCI, and subjects with mild Alzheimer disease (AD) to enable the assessment of the utility of neuroimaging and chemical biomarker measures.
A total of 819 subjects (229 cognitively normal, 398 with MCI, and 192 with AD) were enrolled at baseline and followed for 12 months using standard cognitive and functional measures typical of clinical trials.
The subjects with MCI were more memory impaired than the cognitively normal subjects but not as impaired as the subjects with AD. Nonmemory cognitive measures were only minimally impaired in the subjects with MCI. The subjects with MCI progressed to dementia in 12 months at a rate of 16.5% per year. Approximately 50% of the subjects with MCI were on antidementia therapies. There was minimal movement on the Alzheimer's Disease Assessment Scale-Cognitive Subscale for the normal control subjects, slight movement for the subjects with MCI of 1.1, and a modest change for the subjects with AD of 4.3. Baseline CSF measures of Abeta-42 separated the 3 groups as expected and successfully predicted the 12-month change in cognitive measures.
The Alzheimer's Disease Neuroimaging Initiative has successfully recruited cohorts of cognitively normal subjects, subjects with mild cognitive impairment (MCI), and subjects with Alzheimer disease with anticipated baseline characteristics. The 12-month progression rate of MCI was as predicted, and the CSF measures heralded progression of clinical measures over 12 months.
PET imaging using (18)Ffluorodeoxyglucose (FDG) and (11)CPittsburgh compound B (PIB) have been proposed as biomarkers of Alzheimer disease (AD), as have CSF measures of the 42 amino acid beta-amyloid ...protein (Abeta(1-42)) and total and phosphorylated tau (t-tau and p-tau). Relationships between biomarkers and with disease severity are incompletely understood.
Ten subjects with AD, 11 control subjects, and 34 subjects with mild cognitive impairment from the Alzheimer's Disease Neuroimaging Initiative underwent clinical evaluation; CSF measurement of Abeta(1-42), t-tau, and p-tau; and PIB-PET and FDG-PET scanning. Data were analyzed using continuous regression and dichotomous outcomes with subjects classified as "positive" or "negative" for AD based on cutoffs established in patients with AD and controls from other cohorts.
Dichotomous categorization showed substantial agreement between PIB-PET and CSF Abeta(1-42) measures (91% agreement, kappa = 0.74), modest agreement between PIB-PET and p-tau (76% agreement, kappa = 0.50), and minimal agreement for other comparisons (kappa <0.3). Mini-Mental State Examination score was significantly correlated with FDG-PET but not with PIB-PET or CSF Abeta(1-42). Regression models adjusted for diagnosis showed that PIB-PET was significantly correlated with Abeta(1-42), t-tau, and p-tau(181p), whereas FDG-PET was correlated only with Abeta(1-42).
PET and CSF biomarkers of Abeta agree with one another but are not related to cognitive impairment. (18)Ffluorodeoxyglucose-PET is modestly related to other biomarkers but is better related to cognition. Different biomarkers for Alzheimer disease provide different information from one another that is likely to be complementary.
A variety of measurements have been individually linked to decline in mild cognitive impairment (MCI), but the identification of optimal markers for predicting disease progression remains unresolved. ...The goal of this study was to evaluate the prognostic ability of genetic, CSF, neuroimaging, and cognitive measurements obtained in the same participants.
APOE epsilon4 allele frequency, CSF proteins (Abeta(1-42), total tau, hyperphosphorylated tau p-tau(181p)), glucose metabolism (FDG-PET), hippocampal volume, and episodic memory performance were evaluated at baseline in patients with amnestic MCI (n = 85), using data from a large multisite study (Alzheimer's Disease Neuroimaging Initiative). Patients were classified as normal or abnormal on each predictor variable based on externally derived cutoffs, and then variables were evaluated as predictors of subsequent conversion to Alzheimer disease (AD) and cognitive decline (Alzheimer's Disease Assessment Scale-Cognitive Subscale) during a variable follow-up period (1.9 +/- 0.4 years).
Patients with MCI converted to AD at an annual rate of 17.2%. Subjects with MCI who had abnormal results on both FDG-PET and episodic memory were 11.7 times more likely to convert to AD than subjects who had normal results on both measures (p <or= 0.02). In addition, the CSF ratio p-tau(181p)/Abeta(1-42) (beta = 1.10 +/- 0.53; p = 0.04) and, marginally, FDG-PET predicted cognitive decline.
Baseline FDG-PET and episodic memory predict conversion to AD, whereas p-tau(181p)/Abeta(1-42) and, marginally, FDG-PET predict longitudinal cognitive decline. Complementary information provided by these biomarkers may aid in future selection of patients for clinical trials or identification of patients likely to benefit from a therapeutic intervention.
Hippocampal volume change over time, measured with MRI, has huge potential as a marker for Alzheimer's disease. The objectives of this study were: (i) to test if constant and accelerated hippocampal ...loss can be detected in Alzheimer's disease, mild cognitive impairment and normal ageing over short periods, e.g. 6–12 months, with MRI in the large multicentre setting of the Alzheimer's Disease Neuroimaging Initiative (ADNI); (ii) to determine the extent to which the polymorphism of the apolipoprotein E (ApoE) gene modulates hippocampal change; and (iii) to determine if rates of hippocampal loss correlate with cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease, such as the β-amyloid (Aβ1–42) and tau proteins (tau). The MRI multicentre study included 112 cognitive normal elderly individuals, 226 mild cognitive impairment and 96 Alzheimer's disease patients who all had at least three successive MRI scans, involving 47 different imaging centres. The mild cognitive impairment and Alzheimer's disease groups showed hippocampal volume loss over 6 months and accelerated loss over 1 year. Moreover, increased rates of hippocampal loss were associated with presence of the ApoE allele ɛ4 gene in Alzheimer's disease and lower CSF Aβ1–42 in mild cognitive impairment, irrespective of ApoE genotype, whereas relations with tau were only trends. The power to measure hippocampal change was improved by exploiting correlations statistically between successive MRI observations. The demonstration of considerable hippocampal loss in mild cognitive impairment and Alzheimer's disease patients over only 6 months and accelerated loss over 12 months illustrates the power of MRI to track morphological brain changes over time in a large multisite setting. Furthermore, the relations between faster hippocampal loss in the presence of ApoE allele ɛ4 and decreased CSF Aβ1–42 supports the concept that increased hippocampal loss is an indicator of Alzheimer's disease pathology and a potential marker for the efficacy of therapeutic interventions in Alzheimer's disease.
Neuroimaging in mild cognitive impairment (MCI) and Alzheimer disease (AD) generally shows medial temporal lobe atrophy and diminished glucose metabolism and cerebral blood flow in the posterior ...cingulate gyrus. However, it is unclear whether these abnormalities also impact the cingulum fibers, which connect the medial temporal lobe and the posterior cingulate regions.
To use diffusion tensor imaging (DTI), by measuring fractional anisotropy (FA), to test 1) if MCI and AD are associated with DTI abnormalities in the parahippocampal and posterior cingulate regions of the cingulum fibers; 2) if white matter abnormalities extend to the neocortical fiber connections in the corpus callosum (CC); 3) if DTI improves accuracy to separate AD and MCI from healthy aging vs structural MRI.
DTI and structural MRI were preformed on 17 patients with AD, 17 with MCI, and 18 cognitively normal (CN) subjects.
FA of the cingulum fibers was significantly reduced in MCI, and even more in AD. FA was also significantly reduced in the splenium of the CC in AD, but not in MCI. Adding DTI to hippocampal volume significantly improved the accuracy to separate MCI and AD from CN.
Assessment of the cingulum fibers using diffusion tensor imaging may aid early diagnosis of Alzheimer disease.
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.
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, Abeta(1-42), and p-tau(181P)) 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.
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/Abeta(1-42)) 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/Abeta(1-42)) was 2.0 (1.1, 3.4). Both MRI and CSF provided information about future cognitive change even after adjusting for baseline cognitive performance.
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.
Although β-amyloid (Aβ) plaques are a primary diagnostic criterion for Alzheimer's disease, this pathology is commonly observed in the brains of non-demented older individuals. To explore the ...importance of this pathology in the absence of dementia, we compared levels of amyloid deposition (via ‘Pittsburgh Compound-B’ (PIB) positron emission tomography (PET) imaging) to hippocampus volume (HV) and episodic memory (EM) in three groups: (i) normal controls (NC) from the Berkeley Aging Cohort (BAC NC, n = 20); (ii) normal controls (NC) from the Alzheimer's disease neuroimaging initiative (ADNI NC, n = 17); and (iii) PIB+ mild cognitive impairment subjects from the ADNI (ADNI PIB+ MCI, n = 39). Age, gender and education were controlled for in each statistical model, and HV was adjusted for intracranial volume (aHV). In BAC NC, elevated PIB uptake was significantly associated with smaller aHV (P = 0.0016) and worse EM (P = 0.0086). Within ADNI NC, elevated PIB uptake was significantly associated with smaller aHV (P = 0.047) but not EM (P = 0.60); within ADNI PIB+ MCI, elevated PIB uptake was significantly associated with both smaller aHV (P = 0.00070) and worse EM (P = 0.046). To further understand these relationships, a recursive regression procedure was conducted within all ADNI NC and PIB+ MCI subjects (n = 56) to test the hypothesis that HV mediates the relationship between Aβ and EM. Significant correlations were found between PIB index and EM (P = 0.0044), PIB index and aHV (P < 0.0001), as well as between aHV and EM (P < 0.0001). When both aHV and PIB were included in the same model to predict EM, aHV remained significant (P = 0.0015) whereas PIB index was no longer significantly associated with EM (P = 0.50). These results are consistent with a model in which Aβ deposition, hippocampal atrophy, and EM occur sequentially in elderly subjects, with Aβ deposition as the primary event in this cascade. This pattern suggests that declining EM in older individuals may be caused by Aβ-induced hippocampus atrophy.
Abstract The overall goal was to identify patterns of brain atrophy associated with cognitive impairment and future cognitive decline in non-demented elders. Seventy-one participants were studied ...with structural MRI and neuropsychological testing at baseline and 1-year follow-up. Deformation-based morphometry was used to examine the relationship between regional baseline brain tissue volume with baseline and longitudinal measures of delayed verbal memory, semantic memory, and executive function. Smaller right hippocampal and entorhinal cortex (ERC) volumes at baseline were associated with worse delayed verbal memory performance at baseline while smaller left ERC volume was associated with greater longitudinal decline. Smaller left superior temporal cortex at baseline was associated with worse semantic memory at baseline, while smaller left temporal white and gray matter volumes were associated with greater semantic memory decline. Increased CSF and smaller frontal lobe volumes were associated with impaired executive function at baseline and greater longitudinal executive decline. These findings suggest that baseline volumes of prefrontal and temporal regions may underlie continuing cognitive decline due to aging, pathology, or both in non-demented elderly individuals.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Although β-amyloid (Aβ) plaques are a primary diagnostic criterion for Alzheimer's disease, this pathology is commonly observed in the brains of non-demented older individuals. To explore the ...importance of this pathology in the absence of dementia, we compared levels of amyloid deposition (via 'Pittsburgh Compound-B' (PIB) positron emission tomography (PET) imaging) to hippocampus volume (HV) and episodic memory (EM) in three groups: (i) normal controls (NC) from the Berkeley Aging Cohort (BAC NC, n = 20); (ii) normal controls (NC) from the Alzheimer's disease neuroimaging initiative (ADNI NC, n = 17); and (iii) PIB+ mild cognitive impairment subjects from the ADNI (ADNI PIB+ MCI, n = 39). Age, gender and education were controlled for in each statistical model, and HV was adjusted for intracranial volume (aHV). In BAC NC, elevated PIB uptake was significantly associated with smaller aHV (P = 0.0016) and worse EM (P = 0.0086). Within ADNI NC, elevated PIB uptake was significantly associated with smaller aHV (P = 0.047) but not EM (P = 0.60); within ADNI PIB+ MCI, elevated PIB uptake was significantly associated with both smaller aHV (P = 0.00070) and worse EM (P = 0.046). To further understand these relationships, a recursive regression procedure was conducted within all ADNI NC and PIB+ MCI subjects (n = 56) to test the hypothesis that HV mediates the relationship between Aβ and EM. Significant correlations were found between PIB index and EM (P = 0.0044), PIB index and aHV (P < 0.0001), as well as between aHV and EM (P < 0.0001). When both aHV and PIB were included in the same model to predict EM, aHV remained significant (P = 0.0015) whereas PIB index was no longer significantly associated with EM (P = 0.50). These results are consistent with a model in which Aβ deposition, hippocampal atrophy, and EM occur sequentially in elderly subjects, with Aβ deposition as the primary event in this cascade. This pattern suggests that declining EM in older individuals may be caused by Aβ-induced hippocampus atrophy.
To assess the correlations of both MRI and CSF biomarkers with clinical diagnosis and with cognitive performance in cognitively normal (CN) subjects and patients with amnestic mild cognitive ...impairment (aMCI) and Alzheimer disease (AD).
This is a cross-sectional study with data from the Alzheimer's Disease Neuroimaging Initiative, which consists of CN subjects, subjects with aMCI, and subjects with AD with both CSF and MRI. Baseline CSF (t-tau, Abeta(1-42), and p-tau(181P)) 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 anatomic features on MRI, were computed for each subject.
We found no significant correlation between CSF biomarkers and cognitive scores in any of the 3 clinical groups individually. Conversely, STAND scores correlated with both Clinical Dementia Rating-sum of boxes and Mini-Mental State Examination in aMCI and AD (p < or = 0.01). While STAND and all CSF biomarkers were predictors of clinical group membership (CN, aMCI, or AD) univariately (p < 0.001), STAND was more predictive than CSF both univariately and in combined models.
CSF and MRI biomarkers independently contribute to intergroup diagnostic discrimination and the combination of CSF and MRI provides better prediction than either source of data alone. However, MRI provides greater power to effect cross-sectional groupwise discrimination and better correlation with general cognition and functional status cross-sectionally. We therefore conclude that although MRI and CSF provide complementary information, MRI reflects clinically defined disease stage better than the CSF biomarkers tested.
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