Brain amyloid load, subjective memory complaints, and cognitive trajectories in older individuals at risk for dementia.

Background And Purpose: This study evaluated associations of brain amyloid with 2-year objective and subjective cognitive measures in a trial-ready older general population at risk for dementia.

Methods: Forty-eight participants in the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability underwent C-Pittsburgh compound B (PiB) positron emission tomography (PET) scans and assessment of cognition (modified Neuropsychological Test Battery [NTB]) and subjective memory complaints (Prospective and Retrospective Memory Questionnaire).

Results: Mean age was 71.

Machine learning prediction of future amyloid beta positivity in amyloid-negative individuals.

Background: The pathophysiology of Alzheimer's disease (AD) involves -amyloid (A ) accumulation. Early identification of individuals with abnormal -amyloid levels is crucial, but A quantification with positron emission tomography (PET) and cerebrospinal fluid (CSF) is invasive and expensive.

Methods: We propose a machine learning framework using standard non-invasive (MRI, demographics, APOE, neuropsychology) measures to predict future A -positivity in A -negative individuals.

The Australian National University Alzheimer's Disease Risk Index (ANU-ADRI) score as a predictor for cognitive decline and potential surrogate outcome in the FINGER lifestyle randomized controlled trial.

Background And Purpose: The complex aetiology of Alzheimer's disease suggests prevention potential. Risk scores have potential as risk stratification tools and surrogate outcomes in multimodal interventions targeting specific at-risk populations. The Australian National University Alzheimer's Disease Risk Index (ANU-ADRI) was tested in relation to cognition and its suitability as a surrogate outcome in a multidomain lifestyle randomized controlled trial, in older adults at risk of dementia.

β-Amyloid, Tau, Neurodegeneration Classification and Eligibility for Anti-amyloid Treatment in a Memory Clinic Population.

Background And Objectives: ATN (β-amyloid [Aβ], tau, neurodegeneration) system categorizes individuals based on their core Alzheimer disease (AD) biomarkers. An important potential future use for ATN is therapeutic decision-making in clinical practice once disease-modifying treatments (e.g.

cCOG: A web-based cognitive test tool for detecting neurodegenerative disorders.

Introduction: Web-based cognitive tests have potential for standardized screening in neurodegenerative disorders. We examined accuracy and consistency of cCOG, a computerized cognitive tool, in detecting mild cognitive impairment (MCI) and dementia.

Methods: Clinical data of 306 cognitively normal, 120 mild cognitive impairment (MCI), and 69 dementia subjects from three European cohorts were analyzed.

Detecting Amyloid Positivity in Elderly With Increased Risk of Cognitive Decline.

The importance of early interventions in Alzheimer's disease (AD) emphasizes the need to accurately and efficiently identify at-risk individuals. Although many dementia prediction models have been developed, there are fewer studies focusing on detection of brain pathology. We developed a model for identification of amyloid-PET positivity using data on demographics, vascular factors, cognition, genotype, and structural MRI, including regional brain volumes, cortical thickness and a visual medial temporal lobe atrophy (MTA) rating.

Association of Peripheral Insulin Resistance and Other Markers of Type 2 Diabetes Mellitus with Brain Amyloid Deposition in Healthy Individuals at Risk of Dementia.

We explored the association of type 2 diabetes related blood markers with brain amyloid accumulation on PiB-PET scans in 41 participants from the FINGER PET sub-study. We built logistic regression models for brain amyloid status with12 plasma markers of glucose and lipid metabolism, controlled for diabetes and APOEɛ4 carrier status. Lower levels of insulin, insulin resistance index (HOMA-IR), C-peptide, and plasminogen activator (PAI-1) were associated with amyloid positive status, although the results were not significant after adjusting for multiple testing.

Late-life personality traits, cognitive impairment, and mortality in a population-based cohort.

Objectives: We examined longitudinal associations between late-life personality traits and cognitive impairment, dementia, and mortality in the population-based Cardiovascular Risk Factors, Aging and Dementia (CAIDE) Study.

Methods: Anger expression and trait anger (State-Trait Anger Expression Inventory), anxiety (State-Trait Anxiety Inventory), and sense of coherence (Sense of Coherence Scale) were assessed at the 1998 CAIDE visit (1266 cognitively normal individuals, mean age 71.0 years).

Metabolic Profiles Help Discriminate Mild Cognitive Impairment from Dementia Stage in Alzheimer's Disease.

Accurate differentiation between neurodegenerative diseases is developing quickly and has reached an effective level in disease recognition. However, there has been less focus on effectively distinguishing the prodromal state from later dementia stages due to a lack of suitable biomarkers. We utilized the Disease State Index (DSI) machine learning classifier to see how well quantified metabolomics data compares to clinically used cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD).

The Association Between Distinct Frontal Brain Volumes and Behavioral Symptoms in Mild Cognitive Impairment, Alzheimer's Disease, and Frontotemporal Dementia.

Our aim was to investigate the association between behavioral symptoms of agitation, disinhibition, irritability, elation, and aberrant motor behavior to frontal brain volumes in a cohort with various neurodegenerative diseases. A total of 121 patients with mild cognitive impairment (MCI, = 58), Alzheimer's disease (AD, = 45) and behavioral variant frontotemporal dementia (bvFTD, = 18) were evaluated with a Neuropsychiatric Inventory (NPI). A T1-weighted MRI scan was acquired for each participant and quantified with a multi-atlas segmentation method.

Low Serum High-Density Lipoprotein Cholesterol Levels Associate with the C9orf72 Repeat Expansion in Frontotemporal Lobar Degeneration Patients.

Decreased levels of serum high-density lipoprotein (HDL) cholesterol have previously been linked to systemic inflammation and neurodegenerative diseases, such as Alzheimer's disease. Here, we aimed to analyze the lipoprotein profile and inflammatory indicators, the high-sensitivity C-reactive peptide (hs-CRP) and glycoprotein acetyls (GlycA), in sporadic and C9orf72 repeat expansion-associated frontotemporal lobar degeneration (FTLD) patients. The C9orf72 hexanucleotide repeat expansion is the most frequent genetic etiology underlying FTLD.

Predicting Development of Alzheimer's Disease in Patients with Shunted Idiopathic Normal Pressure Hydrocephalus.

Background: Idiopathic normal pressure hydrocephalus (iNPH) patients often develop Alzheimer's disease (AD) related brain pathology. Disease State Index (DSI) is a method to combine data from various sources for differential diagnosis and progression of neurodegenerative disorders.

Objective: To apply DSI to predict clinical AD in shunted iNPH-patients in a defined population.

Understanding the effect of cognitive/brain reserve and depression on regional atrophy in early Alzheimer's disease.

: Depression in patients with mild cognitive impairment (MCI) and dementia of the Alzheimer's type (AD) is associated with worse prognosis. Indeed, depressed MCI patients have worse cognitive performance and greater loss of gray-matter volume in several brain areas. To date, knowledge of the factors that can mitigate this detrimental effect is still limited.

Association Between Later Life Lifestyle Factors and Alzheimer's Disease Biomarkers in Non-Demented Individuals: A Longitudinal Descriptive Cohort Study.

Background: Lifestyle factors have been associated with the risk of dementia, but the association with Alzheimer's disease (AD) remains unclear.

Objective: To examine the association between later life lifestyle factors and AD biomarkers (i.e.

The Modified Frontal Behavioral Inventory (FBI-mod) for Patients with Frontotemporal Lobar Degeneration, Alzheimer's Disease, and Mild Cognitive Impairment.

While behavioral symptoms are both early and prevalent features of behavioral variant frontotemporal dementia (bvFTD), they can be present in other types of dementia as well, including Alzheimer's disease (AD) and even mild cognitive impairment (MCI). The Frontal Behavioral Inventory (FBI) was specifically developed to capture the behavioral and personality changes in bvFTD; it has also been modified into a self-administered caregiver questionnaire (FBI-mod). We examined the utility of the FBI-mod in differentiating bvFTD (n = 26), primary progressive aphasia (PPA) (n = 7), AD (n = 53), and MCI (n = 50) patients, and investigated how the FBI-mod may be associated with neuropsychological measures.

Development of a Late-Life Dementia Prediction Index with Supervised Machine Learning in the Population-Based CAIDE Study.

Background And Objective: This study aimed to develop a late-life dementia prediction model using a novel validated supervised machine learning method, the Disease State Index (DSI), in the Finnish population-based CAIDE study.

Methods: The CAIDE study was based on previous population-based midlife surveys. CAIDE participants were re-examined twice in late-life, and the first late-life re-examination was used as baseline for the present study.

Multimodal analysis to predict shunt surgery outcome of 284 patients with suspected idiopathic normal pressure hydrocephalus.

Objectives: Optimal selection of idiopathic normal pressure hydrocephalus (iNPH) patients for shunt surgery is challenging. Disease State Index (DSI) is a statistical method that merges multimodal data to assist clinical decision-making. It has previously been shown to be useful in predicting progression in mild cognitive impairment and differentiating Alzheimer's disease (AD) and frontotemporal dementia.

The effect of TOMM40 poly-T repeat lengths on age of onset and cerebrospinal fluid biomarkers in Finnish Alzheimer's disease patients.

Background: Poly-T repeat lengths of rs10524523 in TOMM40 together with APOE polymorphism have been reported to affect the risk of late-onset Alzheimer's disease (LOAD) and the age of onset (AOO).

Objective: To explore whether the AOO and cerebrospinal fluid biomarkers Aβ42, total tau and phosphorylated tau are associated with different repeat lengths.

Methods: We conducted both the fragment and sequencing analysis of rs10524523 in 336 LOAD patients with a known APOE genotype.

Generalizability of the disease state index prediction model for identifying patients progressing from mild cognitive impairment to Alzheimer's disease.

Background: The Disease State Index (DSI) prediction model measures the similarity of patient data to diagnosed stable and progressive mild cognitive impairment (MCI) cases to identify patients who are progressing to Alzheimer's disease.

Objectives: We evaluated how well the DSI generalizes across four different cohorts: DESCRIPA, ADNI, AddNeuroMed, and the Kuopio MCI study.

Methods: The accuracy of the DSI in predicting progression was examined for each cohort separately using 10 × 10-fold cross-validation and for inter-cohort validation using each cohort as a test set for the model built from the other independent cohorts using bootstrapping with 10 repetitions.

Effects of Alzheimer's disease-associated risk loci on cerebrospinal fluid biomarkers and disease progression: a polygenic risk score approach.

Background: Several risk loci for Alzheimer's disease (AD) have been identified during recent years in large-scale genome-wide association studies. However, little is known about the mechanisms by which these loci influence AD pathogenesis.

Objective: To investigate the individual and combined risk effects of the newly identified AD loci.