Longitudinal MRI atrophy biomarkers: relationship to conversion in the ADNI cohort.
ABSTRACT: Atrophic changes in early Alzheimer's disease (AD) and amnestic mild cognitive impairment (MCI) have been proposed as biomarkers for detection and monitoring. We analyzed magnetic resonance imaging (MRI) atrophy rate from baseline to 1 year in 4 groups of participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI): AD (n = 152), converters from MCI to probable AD (MCI-C, n = 60), stable MCI (MCI-S, n = 261), and healthy controls (HC, n = 200). Scans were analyzed using multiple methods, including voxel-based morphometry (VBM), regions of interest (ROIs), and automated parcellation, permitting comparison of annual percent change (APC) in neurodegeneration markers. Effect sizes and the sample required to detect 25% reduction in atrophy rates were calculated. The influence of APOE genotype on APC was also evaluated. AD patients and converters from MCI to probable AD demonstrated high atrophy APCs across regions compared with minimal change in healthy controls. Stable MCI subjects showed intermediate atrophy rates. APOE genotype was associated with APC in key regions. In sum, APC rates are influenced by APOE genotype, imminent MCI to AD conversion, and AD-related neurodegeneration.
Project description:The goal was to elucidate the time course of regional brain atrophy rates relative to age in cognitively normal (CN) aging, mild cognitively impairment (MCI), and Alzheimer's disease (AD), without a priori models for atrophy progression. Regional brain volumes from 147 cognitively normal subjects, 164 stable MCI, 93 MCI-to-AD converters and 111 ad patients, between 51 and 91 years old and who had repeated 1.5 T magnetic resonance imaging (MRI) scans over 30 months, were analyzed. Relations between regional brain volume change and age were determined using generalized additive models, an established nonparametric concept for approximating nonlinear relations. Brain atrophy rates varied nonlinearly with age, predominantly in regions of the temporal lobe. Moreover, the atrophy rates of some regions leveled off with increasing age in control and stable MCI subjects whereas those rates progressed further in MCI-to-AD converters and AD patients. The approach has potential uses for early detection of AD and differentiation between stable and progressing MCI.
Project description:Patients with amnestic mild cognitive impairment (MCI) represent an important clinical group as they are at increased risk of developing Alzheimer disease (AD). (11)C-PIB PET is an in vivo marker of brain amyloid load.To assess the rates of conversion of MCI to AD during a 3-year follow-up period and to compare levels of amyloid deposition between MCI converters and nonconverters.Thirty-one subjects with MCI with baseline (11)C-PIB PET, MRI, and neuropsychometry have been clinically followed up for 1 to 3 years (2.68 +/- 0.6 years). Raised cortical (11)C-PIB binding in subjects with MCI was detected with region of interest analysis and statistical parametric mapping.Seventeen of 31 (55%) subjects with MCI had increased (11)C-PIB retention at baseline and 14 of these 17 (82%) clinically converted to AD during follow-up. Only one of the 14 PIB-negative MCI cases converted to AD. Of the PIB-positive subjects with MCI, half (47%) converted to AD within 1 year of baseline PIB PET, these faster converters having higher tracer-retention values than slower converters in the anterior cingulate (p = 0.027) and frontal cortex (p = 0.031). Seven of 17 (41%) subjects with MCI with known APOE status were epsilon4 allele carriers, this genotype being associated with faster conversion rates in PIB-positive subjects with MCI (p = 0.035).PIB-positive subjects with mild cognitive impairment (MCI) are significantly more likely to convert to AD than PIB-negative patients, faster converters having higher PIB retention levels at baseline than slower converters. In vivo detection of amyloid deposition in MCI with PIB PET provides useful prognostic information.
Project description:<h4>Background</h4>Mild cognitive impairment (MCI) of an amnestic type is a common condition in older people and highly predictive of Alzheimer's disease (AD). To date, there is no clear consensus regarding the best antecedent biomarker to predict early conversion to AD.<h4>Objective</h4>The aim of the study is to demonstrate that (1)H magnetic resonance spectroscopy (MRS) of the brain in MCI patients may predict early conversion to dementia within the 2-year period after baseline assessment.<h4>Methods</h4>A cohort of patients fulfilling the criteria of amnestic MCI were enrolled consecutively. At baseline the patients underwent neuropsychological examination, standard blood tests and APOE genotype. (1)H-MRS (1.5 T) of the brain was carried out by exploring two areas: the posteromedial bilateral parietal lobe and left medial occipital lobe. The patients were followed up to detect conversion to probable AD according to the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association group criteria.<h4>Results</h4>After a 2-year follow-up, 27 (38%) patients converted to AD. The mean N-acetyl-aspartate/creatine (NAA/Cr) ratio in the posteromedial bilateral parietal cortex was 1.38 in converters versus 1.49 in non-converters (p<0.0001). An NAA/Cr ratio equal to or lower than 1.43 in this area predicted conversion to probable AD at 74.1% sensitivity and 83.7% specificity (area under the curve: 0.84; 95% CI 0.73 to 0.92). The cross-validated accuracy of classification was 82%, which reaches 85% when the APOE4 genotype and memory test are included in the analysis. In the left medial occipital lobe, the predictive value was somewhat lower with 85.2% sensitivity and 61.4% specificity (area under the curve: 0.8; 95% CI 0.69 to 0.89). Neither the APOE4 genotype nor leuco-araiosis was predictive of conversion to dementia.<h4>Conclusion</h4>MRS is a valuable biomarker to predict early conversion to dementia in patients with amnestic MCI.
Project description:Patients with amnestic mild cognitive impairment (MCI) demonstrate decline in everyday function. In this study, we investigated whether whole brain atrophy and apolipoprotein E (APOE) genotype are associated with the rate of functional decline in MCI.Participants were 164 healthy controls, 258 MCI patients, and 103 patients with mild Alzheimer's disease (AD), enrolled in the Alzheimer's Disease Neuroimaging Initiative. They underwent brain MRI scans, APOE genotyping, and completed up to six biannual Functional Activities Questionnaire (FAQ) assessments. Random effects regressions were used to examine trajectories of decline in FAQ across diagnostic groups, and to test the effects of ventricle-to-brain ratio (VBR) and APOE genotype on FAQ decline among MCI patients.Rate of decline in FAQ among MCI patients was intermediate between that of controls and mild AD patients. Patients with MCI who converted to mild AD declined faster than those who remained stable. Among MCI patients, increased VBR and possession of any APOE varepsilon4 allele were associated with faster rate of decline in FAQ. In addition, there was a significant VBR by APOE varepsilon4 interaction such that patients who were APOE varepsilon4 positive and had increased atrophy experienced the fastest decline in FAQ.Functional decline occurs in MCI, particularly among patients who progress to mild AD. Brain atrophy and APOE varepsilon4 positivity are associated with such declines, and patients who have elevated brain atrophy and are APOE varepsilon4 positive are at greatest risk of functional degradation. These findings highlight the value of genetic and volumetric MRI information as predictors of functional decline, and thus disease progression, in MCI.
Project description:To investigate whether APOE ?4 carriers have higher hippocampal atrophy rates than non-carriers in Alzheimer's disease (AD), mild cognitive impairment (MCI) and controls, and if so, whether higher hippocampal atrophy rates are still observed after adjusting for concurrent whole-brain atrophy rates.MRI scans from all available visits in ADNI (148 AD, 307 MCI, 167 controls) were used. MCI subjects were divided into "progressors" (MCI-P) if diagnosed with AD within 36 months or "stable" (MCI-S) if a diagnosis of MCI was maintained. A joint multi-level mixed-effect linear regression model was used to analyse the effect of ?4 carrier-status on hippocampal and whole-brain atrophy rates, adjusting for age, gender, MMSE and brain-to-intracranial volume ratio. The difference in hippocampal rates between ?4 carriers and non-carriers after adjustment for concurrent whole-brain atrophy rate was then calculated.Mean adjusted hippocampal atrophy rates in ?4 carriers were significantly higher in AD, MCI-P and MCI-S (p?0.011, all tests) compared with ?4 non-carriers. After adjustment for whole-brain atrophy rate, the difference in mean adjusted hippocampal atrophy rate between ?4 carriers and non-carriers was reduced but remained statistically significant in AD and MCI-P.These results suggest that the APOE ?4 allele drives atrophy to the medial-temporal lobe region in AD.
Project description:To realize an individual-level risk evaluation of progression of early Alzheimer's disease (AD), we applied an AD resemblance atrophy index (AD-RAI) to differentiate the subjects at risk of progression from normal subjects (NC) to mild cognitive impairment (MCI) and from MCI to AD. We included 183 subjects with a two-year follow-up: 50 NC stable (NCs), 23 NC-to-MCI converters (NCc), 50 MCI stable (MCIs), 35 MCI-to-AD converters (MCIc), 25 AD stable (ADs). ANCOVA analyses were used to identify baseline brain atrophy in converters compared with non-converters. To explore the relative merits of AD-RAI over individual regional volumetric measures in prediction of disease progression, we searched for the optimal cutoff for each measure in logistic regressions and plotted the longitudinal trajectories of these brain volumetric measures in converters and non-converters. Baseline AD-RAI performed the best in differentiating NCc from NCs (odds ratio 26.35, AUC 0.740) and MCIc from MCIs (odds ratio 8.91, AUC 0.771). The AD-RAI presented greater increase in the second year for NCc vs. NCs but not for MCIc vs. MCIs. Baseline AD-RAIs were also associated with CSF-based and PET-based AD biomarkers. These results showed the potential of AD-RAI in early risk estimation before progression to MCI/AD at an individual-level.
Project description:The study characterized the status of retrograde amnesia (RA) in amnestic mild cognitive impairment (MCI).We measured RA, anterograde amnesia (AA), brain measures, apolipoprotein-E status (ApoE), and conversion to probable Alzheimer's disease (AD) across 3 years in 15 individuals with MCI. We compared the severity of amnesia and brain atrophy in MCI to a group of patients with limited damage to the hippocampus (H) or more extensive damage to the medial temporal lobe (MTL).The MCI group exhibited modest AA, together with severe RA, covering nearly 4 decades before their diagnosis. Compared with H-MTL patients, the temporal extent of RA was disproportionate to the severity of AA. The MCI group exhibited more modest AA and MTL atrophy than H-MTL patients, together with more severe RA and neocortical atrophy than H-MTL patients. The severity of AA corresponded to the integrity of MTL structures, whereas the severity of RA corresponded to the integrity of both MTL and neocortical structures. RA (but not AA, nor measures of cognitive status) was related to ApoE status and subsequent diagnosis of probable AD. RA was predicted by heritable risk for AD, in addition to the integrity of MTL and neocortical structures.Compared with H-MTL patients, the MCI group exhibited RA that was disproportionate to their AA and that was more severe than would be expected if their atrophy were limited primarily to the MTL. Heritable risk for AD, as well as the integrity of brain regions within and beyond the MTL, are important for understanding RA in MCI.
Project description:Introduction:Currently, there are no tools that can accurately predict which patients with mild cognitive impairment (MCI) will progress to Alzheimer's disease (AD). Texture analysis uses image processing and statistical methods to identify patterns in voxel intensities that cannot be appreciated by visual inspection. Our main objective was to determine whether MRI texture could be used to predict conversion of MCI to AD. Methods:A method of 3-dimensional, whole-brain texture analysis was used to compute texture features from T1-weighted MR images. To assess predictive value, texture changes were compared between MCI converters and nonconverters over a 3-year observation period. A predictive model using texture and clinical factors was used to predict conversion of patients with MCI to AD. This model was then tested on ten randomly selected test groups from the data set. Results:Texture features were found to be significantly different between normal controls (n = 225), patients with MCI (n = 382), and patients with AD (n = 183). A subset of the patients with MCI were used to compare between MCI converters (n = 98) and nonconverters (n = 106). A composite model including texture features, APOE-?4 genotype, Mini-Mental Status Examination score, sex, and hippocampal occupancy resulted in an area under curve of 0.905. Application of the composite model to ten randomly selected test groups (nonconverters = 26, converters = 24) predicted MCI conversion with a mean accuracy of 76.2%. Discussion:Early texture changes are detected in patients with MCI who eventually progress to AD dementia. Therefore, whole-brain 3D texture analysis has the potential to predict progression of patients with MCI to AD.
Project description:Patients with Mild Cognitive Impairment (MCI) are at high risk of progression to Alzheimer's dementia. Identifying MCI individuals with high likelihood of conversion to dementia and the associated biosignatures has recently received increasing attention in AD research. Different biosignatures for AD (neuroimaging, demographic, genetic and cognitive measures) may contain complementary information for diagnosis and prognosis of AD.We have conducted a comprehensive study using a large number of samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to test the power of integrating various baseline data for predicting the conversion from MCI to probable AD and identifying a small subset of biosignatures for the prediction and assess the relative importance of different modalities in predicting MCI to AD conversion. We have employed sparse logistic regression with stability selection for the integration and selection of potential predictors. Our study differs from many of the other ones in three important respects: (1) we use a large cohort of MCI samples that are unbiased with respect to age or education status between case and controls (2) we integrate and test various types of baseline data available in ADNI including MRI, demographic, genetic and cognitive measures and (3) we apply sparse logistic regression with stability selection to ADNI data for robust feature selection.We have used 319 MCI subjects from ADNI that had MRI measurements at the baseline and passed quality control, including 177 MCI Non-converters and 142 MCI Converters. Conversion was considered over the course of a 4-year follow-up period. A combination of 15 features (predictors) including those from MRI scans, APOE genotyping, and cognitive measures achieves the best prediction with an AUC score of 0.8587.Our results demonstrate the power of integrating various baseline data for prediction of the conversion from MCI to probable AD. Our results also demonstrate the effectiveness of stability selection for feature selection in the context of sparse logistic regression.
Project description:There is a range of factors that predict the development of Alzheimer's disease (AD) dementia among patients with amnestic mild cognitive impairment (MCI).To identify the neuropsychological, genetic, and functional brain imaging data that best predict conversion to AD dementia in patients with amnestic MCI.From an initial group of 42 amnestic MCI patients assessed with neurological, neuropsychological, and brain SPECT, 39 (25 converters, 14 non-converters) were followed for 4 years, and 36 had APOE ?4 genotyping. Baseline neuropsychological data and brain SPECT data were used to predict which of the MCI patients would develop dementia by the end of the 4 years of observation.The MCI patients who had converted to AD dementia had poorer performance on long-term visual memory and Semantic Fluency tests. The MCI subjects who developed dementia were more likely to carry at least one copy of the APOE ?4 allele (Hazard Risk = 4.22). There was lower brain perfusion in converters than non-converters, mainly in postcentral gyrus. An additional analysis of the SPECT data found differences between the MCI subjects and controls in the posterior cingulate gyrus and the basal forebrain. When the brain imaging and neuropsychological test data were combined in the same Cox regression model, only the neuropsychological test data were significantly associated with time to dementia.Although the presence of reduced brain perfusion in postcentral gyrus and basal forebrain indicated an at-risk condition, it was the extent of memory impairment that was linked to the speed of decline from MCI to AD.