Dataset Information

Mild cognitive impairment: baseline and longitudinal structural MR imaging measures improve predictive prognosis.

ABSTRACT: To assess whether single-time-point and longitudinal volumetric magnetic resonance (MR) imaging measures provide predictive prognostic information in patients with amnestic mild cognitive impairment (MCI).This study was conducted with institutional review board approval and in compliance with HIPAA regulations. Written informed consent was obtained from all participants or the participants' legal guardians. Cross-validated discriminant analyses of MR imaging measures were performed to differentiate 164 Alzheimer disease (AD) cases from 203 healthy control cases. Separate analyses were performed by using data from MR images obtained at one time point or by combining single-time-point measures with 1-year change measures. Resulting discriminant functions were applied to 317 MCI cases to derive individual patient risk scores. Risk of conversion to AD was estimated as a continuous function of risk score percentile. Kaplan-Meier survival curves were computed for risk score quartiles. Odds ratios (ORs) for the conversion to AD were computed between the highest and lowest quartile scores.Individualized risk estimates from baseline MR examinations indicated that the 1-year risk of conversion to AD ranged from 3% to 40% (average group risk, 17%; OR, 7.2 for highest vs lowest score quartiles). Including measures of 1-year change in global and regional volumes significantly improved risk estimates (P = 001), with the risk of conversion to AD in the subsequent year ranging from 3% to 69% (average group risk, 27%; OR, 12.0 for highest vs lowest score quartiles).Relative to the risk of conversion to AD conferred by the clinical diagnosis of MCI alone, MR imaging measures yield substantially more informative patient-specific risk estimates. Such predictive prognostic information will be critical if disease-modifying therapies become available.http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11101975/-/DC1.

SUBMITTER: McEvoy LK

PROVIDER: S-EPMC3099042 | biostudies-other | 2011 Jun

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:Although subtle discourse declines in people with mild cognitive impairment (MCI) have been reported, heterogeneous measures and tasks among the MCI discourse studies have yielded widely varying outcomes. The present study aimed to first, identify discourse measures that aid the differentiation among people with amnestic MCI (aMCI), people with non-amnestic MCI (naMCI), and cognitively healthy control (HC) participants, and second, delineate the cognitive functions related to such discourse measures. Three discourse tasks (an episodic narrative, a planning task, and a picture description) were performed by 30 aMCI, 22 naMCI, and 21 HC participants. Samples were analyzed using six categories of 15 measures, namely coherence, cohesion, proposition, grammaticality, lexicality, and fluency. The statistical analyses included (1) a multivariate analysis of variance for group comparison; (2) binary simple logistic regression and receiver operating characteristic curve analysis for differentiation between two groups; (3) binary multiple logistic regression for being diagnosed with naMCI or aMCI with the minimum number of predictors; and (4) Pearson correlation analysis for identifying the cognitive functions associated with the discourse measures. The proportion of cohesive words and propositional density in aMCI participants were worse than those in naMCI participants. Global coherence, the proportion of cohesive words, and the proportion of dysfluencies and pauses in naMCI participants were lower than those in the HC participants. Global and local coherence and the proportion of cohesive words, cohesive ties per utterances, propositional density, and dysfluencies and pauses in aMCI participants were worse than those in the HC participants. The aforementioned measures were demonstrated to be effective predictors for classifying groups by receiver operating characteristic curve analysis. In addition, the proportions of cohesive words and pauses were common discourse measures for differentiation between naMCI and HC participants or between aMCI and HC participants using binary multiple logistic regression. According to the correlation analysis, memory and executive functions are needed for coherent, cohesive, and efficient discourse productions in MCI. The detailed description of discourse performances in this study will aid the characterization of the declined language abilities of MCI participants and also the understanding of the cognitive functions involved in discourse performance in MCI.

Project description:Plasma-based biomarkers present a promising approach in the research and clinical practice of Alzheimer's disease as they are inexpensive, accessible and minimally invasive. In particular, prognostic biomarkers of cognitive decline may aid in planning and management of clinical care. Although recent studies have demonstrated the prognostic utility of plasma biomarkers of Alzheimer pathology or neurodegeneration, such as pTau-181 and NF-L, whether other plasma biomarkers can further improve prediction of cognitive decline is undetermined. We conducted an observational cohort study to determine the prognostic utility of plasma biomarkers in predicting progression to dementia for individuals presenting with mild cognitive impairment due to probable Alzheimer's disease. We used the Olink™ Proximity Extension Assay technology to measure the level of 460 circulating proteins in banked plasma samples of all participants. We used a discovery data set comprised 60 individuals with mild cognitive impairment (30 progressors and 30 stable) and a validation data set consisting of 21 stable and 21 progressors. We developed a machine learning model to distinguish progressors from stable and used 44 proteins with significantly different plasma levels in progressors versus stable along with age, sex, education and baseline cognition as candidate features. A model with age, education, APOE genotype, baseline cognition, plasma pTau-181 and 12 plasma Olink protein biomarker levels was able to distinguish progressors from stable with 86.7% accuracy (mean area under the curve = 0.88). In the validation data set, the model accuracy was 78.6%. The Olink proteins selected by the model included those associated with vascular injury and neuroinflammation (e.g. IL-8, IL-17A, TIMP-4, MMP7). In addition, to compare these prognostic biomarkers to those that are altered in Alzheimer's disease or other types of dementia relative to controls, we analyzed samples from 20 individuals with Alzheimer, 30 with non-Alzheimer dementias and 34 with normal cognition. The proteins NF-L and PTP-1B were significantly higher in both Alzheimer and non-Alzheimer dementias compared with cognitively normal individuals. Interestingly, the prognostic markers of decline at the mild cognitive impairment stage did not overlap with those that differed between dementia and control cases. In summary, our findings suggest that plasma biomarkers of inflammation and vascular injury are associated with cognitive decline. Developing a plasma biomarker profile could aid in prognostic deliberations and identify individuals at higher risk of dementia in clinical practice.

Dataset Information

Mild cognitive impairment: baseline and longitudinal structural MR imaging measures improve predictive prognosis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets