Dataset Information

Practical algorithms for amyloid ? probability in subjective or mild cognitive impairment.

ABSTRACT: Introduction:Practical algorithms predicting the probability of amyloid pathology among patients with subjective cognitive decline or mild cognitive impairment may help clinical decisions regarding confirmatory biomarker testing for Alzheimer's disease. Methods:Algorithm feature selection was conducted with Alzheimer's Disease Neuroimaging Initiative and Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing data. Probability algorithms were developed in Alzheimer's Disease Neuroimaging Initiative using nested cross-validation accompanied by stratified subsampling to obtain 1000 internally validated decision trees. Semi-independent validation was conducted using Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing. Independent external validation was conducted in the population-based Mayo Clinic Study of Aging. Results:Two algorithms were developed using age and normalized immediate recall z-scores, with or without apolipoprotein E ?4 carrier status. Both algorithms had robust performance across data sets and when substituting different recall memory tests. Discussion:The statistical framework resulted in robust probability estimation. Application of these algorithms may assist in clinical decision-making for further testing to diagnose amyloid pathology.

SUBMITTER: Maserejian N

PROVIDER: S-EPMC6827360 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Practical algorithms for amyloid β probability in subjective or mild cognitive impairment.

Maserejian Nancy N Bian Shijia S Wang Wenting W Jaeger Judith J Syrjanen Jeremy A JA Aakre Jeremiah J Jack Clifford R CR Mielke Michelle M MM Gao Feng F

Alzheimer's & dementia (Amsterdam, Netherlands) 20191022

<h4>Introduction</h4>Practical algorithms predicting the probability of amyloid pathology among patients with subjective cognitive decline or mild cognitive impairment may help clinical decisions regarding confirmatory biomarker testing for Alzheimer's disease.<h4>Methods</h4>Algorithm feature selection was conducted with Alzheimer's Disease Neuroimaging Initiative and Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing data. Probability algorithms were developed in Alzheimer's ...[more]

PMID: 31700988

Similar Datasets

Project description:Subjective cognitive decline (SCD) as an indicator of preclinical Alzheimer's disease (AD) may precede mild cognitive impairment (MCI) over several decades. Self-reported cognitive decline as a typical clinical manifestation is critical in preclinical AD. Metacognition represents a person's ability to accurately assess cognition. Our study aimed to examine (1) the alternations of metamemory in a cohort across the Alzheimer's continuum, (2) the association between metamemory and cognition, and (3) the relationship of cortical thickness in four regions of interest (ROI) with metamemory scores. Six hundred ninety-seven participants were classified as 79 AD dementia, 161 aMCI, 261 SCD, and 196 cognitively unimpaired (CU) individuals, in which 418 participants aged above 65, 131 participants with Aβ+ after receiving positron emission tomography, and 602 participants received sMRI. The degree of confidence (DOC) was measured by calculating discrepancies between judgments and memory performance. We assessed the relationships between DOC tertiles and cognition and analyzed the screening power, then investigated the partial correlation between DOC and ROIs, controlled by age, sex, and cognition. In the Aβ+ subgroup, SCD showed significantly higher DOC scores than the CU group. There was an increasing trend of overconfidence with the decline of cognition across the AD spectrum (P for trend < 0.001). After adjusting for age, sex, and education, the lower degree of confidence-long-term delay recall (DOC-LD) tertiles were associated with lower odds ratio in SCD, aMCI, and AD in the Aβ+ subgroup (all P for trend < 0.05). The area under the curves of DOC scores for screening SCD from CU in the Aβ+ subgroup was better than that in all participants and the age ≥65 subgroup. Partial correlation showed that in the Aβ+ subgroup, DOC-SD (degree of confidence-short-term delay recall) was negatively correlated with the anterior cingulate cortex; DOC-LD was negatively correlated with the cortices of parahippocampal, anterior cingulate, posterior cingulate, and medial orbitofrontal. In individuals with Aβ+, SCD exhibited a detectable metamemory alternation before objective cognitive impairment could be tested, indicated by the overestimation in the memory performance. The pattern of an increasing trend of overconfidence across SCD, aMCI, and AD dementia supports the view of a continuum in Alzheimer's disease.

Project description:Background: The spectrum of early Alzheimer's disease (AD) is thought to include subjective cognitive impairment, early mild cognitive impairment (eMCI), and late mild cognitive impairment (lMCI). Choline dysfunction affects the early progression of AD, in which the basal nucleus of Meynert (BNM) is primarily responsible for cortical cholinergic innervation. The aims of this study were to determine the abnormal patterns of BNM-functional connectivity (BNM-FC) in the preclinical AD spectrum (SCD, eMCI, and lMCI) and further explore the relationships between these alterations and neuropsychological measures. Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) was used to investigate FC based on a seed mask (BNM mask) in 28 healthy controls (HC), 30 SCD, 24 eMCI, and 25 lMCI patients. Furthermore, the relationship between altered FC and neurocognitive performance was examined by a correlation analysis. The receiver operating characteristic (ROC) curve of abnormal BNM-FC was used to specifically determine the classification ability to differentiate the early AD disease spectrum relative to HC (SCD and HC, eMCI and HC, lMCI and HC) and pairs of groups in the AD disease spectrum (eMCI and SCD, lMCI and SCD, eMCI and lMCI). Results: Compared with HC, SCD patients showed increased FC in the bilateral SMA and decreased FC in the bilateral cerebellum and middle frontal gyrus (MFG), eMCI patients showed significantly decreased FC in the bilateral precuneus, and lMCI individuals showed decreased FC in the right lingual gyrus. Compared with the SCD group, the eMCI group showed decreased FC in the right superior frontal gyrus (SFG), while the lMCI group showed decreased FC in the left middle temporal gyrus (MTG). Compared with the eMCI group, the lMCI group showed decreased FC in the right hippocampus. Interestingly, abnormal FC was associated with certain cognitive domains and functions including episodic memory, executive function, information processing speed, and visuospatial function in the disease groups. BNM-FC of SFG in distinguishing eMCI from SCD; BNM-FC of MTG in distinguishing lMCI from SCD; BNM-FC of the MTG, hippocampus, and cerebellum in distinguishing SCD from HC; and BNM-FC of the hippocampus and MFG in distinguishing eMCI from lMCI have high sensitivity and specificity. Conclusions: The abnormal BNM-FC patterns can characterize the early disease spectrum of AD (SCD, eMCI, and lMCI) and are closely related to the cognitive domains. These new and reliable findings will provide a new perspective in identifying the early disease spectrum of AD and further strengthen the role of cholinergic theory in AD.

Project description:BACKGROUND:Determination of β-amyloid (Aβ) positivity and likelihood of underlying Alzheimer's disease (AD) relies on dichotomous biomarker cut-off values. Individuals with mild cognitive impairment (MCI) and Aβ within the normal range may still have a substantial risk of developing dementia, primarily of Alzheimer type. Their prognosis, as well as predictors of clinical progression, are not fully understood. The aim of this study was to explore the associations of cerebrospinal fluid (CSF) biomarkers (Aβ42, total tau, phosphorylated tau) and other characteristics, including modifiable vascular factors, with the risk of progression to dementia among patients with MCI and normal CSF Aβ42. METHODS:Three hundred eighteen memory clinic patients with CSF and clinical data, and at least 1-year follow-up, were included. Patients had normal CSF Aβ42 levels based on clinical cut-offs. Cox proportional hazard models with age as time scale and adjusted for sex, education, and cognition (Mini-Mental State Examination) were used to investigate predictors of progression to dementia and Alzheimer-type dementia. Potential predictors included CSF biomarkers, cognitive performance (verbal learning and memory), apolipoprotein E (APOE) ε4 genotype, medial temporal lobe atrophy, family history of dementia, depressive symptoms, and vascular factors, including the Cardiovascular Risk Factors, Aging and Dementia (CAIDE) risk score. Predictive performance of patient characteristics was further explored with Harrell C statistic. RESULTS:Lower normal Aβ42 and higher total tau and phosphorylated tau were associated with higher dementia risk, and the association was not driven by Aβ42 values close to cut-off. Additional predictors included poorer cognition, APOE ε4 genotype, higher systolic blood pressure, and lower body mass index, but not the CAIDE dementia risk score. Aβ42 individually and in combination with other CSF biomarkers improved the risk prediction compared to age and cognition alone. Medial temporal lobe atrophy or vascular factors did not increase the predictive performance. CONCLUSIONS:Possibility of underlying AD pathology and increased dementia risk should not be ruled out among MCI patients with CSF Aβ42 within the normal range. While cut-offs may be useful in clinical practice to identify high-risk individuals, personalized risk prediction tools incorporating continuous biomarkers may be preferable among individuals with intermediate risk. The role of modifiable vascular factors could be explored in this context.

Dataset Information

Practical algorithms for amyloid ? probability in subjective or mild cognitive impairment.

Publications

Practical algorithms for amyloid β probability in subjective or mild cognitive impairment.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets