Dementia and Cognitive Impairment Research

This paper defines transdiagnostic disease categories using histopathological data and predicts cluster membership from CSF and genotype data with high accuracy.

The paper investigates if story recall of proper names is linked to beta-amyloid levels in cognitively unimpaired adults at risk for Alzheimer's disease, finding an association with delayed recall.

The paper identifies reduced grey matter density in the left entorhinal cortex as a biomarker for predicting mild cognitive impairment in cognitively healthy elderly individuals.

This study finds that higher cardiometabolic burden in older adults is associated with reduced P3b ERP amplitude during working memory tasks.

This study uses Mendelian randomization to assess if physical activity reduces Alzheimer's disease risk, finding no significant protective effect.

The paper identifies four latent atrophy factors in posterior cortical atrophy using Bayesian modeling, finding that most patients exhibit mixed profiles rather than distinct variants.

The paper investigates associations between APOE genotypes and blood biomarkers in UK Biobank, finding both expected and unexpected links to AD risk factors.

The paper develops a Bayesian longitudinal clustering framework to identify distinct AD brain atrophy patterns and their progression, revealing heterogeneity in disease progression.

This study compares functional connectivity in temporal lobe regions between Alzheimer's disease, semantic dementia, and healthy controls, identifying shared and distinct patterns of dysconnectivity.

The paper introduces longitudinal ComBat to harmonize multi-scanner imaging data, showing it improves detection of longitudinal changes and controls type I error better than existing methods.

The paper shows that poor episodic memory and semantic verbal fluency in middle-aged men predict progression to mild cognitive impairment within six years.

The paper uses blood RNA levels and machine learning to predict Clinical Dementia Rating (CDR) groups, finding that combining nonsignificant probes improves classification accuracy.

This study uses gene expression imputation to identify candidate genes and tissue-specific associations linked to frontotemporal dementia risk loci.

The paper identifies a SHARPIN variant associated with limbic system atrophy and family history of Alzheimer’s disease using MRI and genome-wide data.

This study investigates whether prior knowledge enhances memory encoding in early Alzheimer's Disease using fMRI, finding that patients do not benefit from pre-experimental knowledge while controls do.

This study identifies genetic variants and pathways associated with cognitive resilience to Alzheimer's disease, finding a novel locus linked to bile acid metabolism and methylation changes.

The paper predicts future cognitive decline using non-brain and multimodal brain imaging data in healthy and pathological aging, finding that non-brain data and structural MRI improve predictions.

This study identifies FDG hyper-metabolism in cerebellar and olfactory regions in Alzheimer's disease, suggesting disrupted inhibitory networks.

The paper predicts brain age from MRI scans and provides prediction intervals to quantify uncertainty in age estimation for different cognitive states.

The paper identifies key neuropsychological tests that predict dementia conversion in Parkinson's disease patients using logistic regression and elastic net methods.

The paper analyzes fMRI data from asymptomatic older adults to investigate how APOE4 genetic status affects memory-related brain activity during a spatial source recollection task.

This study examines how amyloid-beta biomarkers and clinical profiles change in sporadic Alzheimer's disease, finding that amyloid changes are inconsistent with clinical and imaging markers during progression.

This paper evaluates the ATN framework's accuracy in diagnosing Alzheimer's disease subtypes and frontotemporal lobar degeneration using cerebrospinal fluid biomarkers, finding that non-amnestic Alzheimer's patients have lower tau levels and the framework is less sensitive to frontotemporal lobar degeneration.

The paper identifies a 7-miRNA biosignature in platelets that distinguishes dementia with Lewy bodies from Alzheimer disease.

This study examines the association between multiple self-reported health behaviors and cognitive decline in a cohort of non-demented middle-aged individuals, finding limited significant associations.

This study finds that severe hyposmia (reduced sense of smell) is a distinguishing feature between dementia with Lewy bodies and Alzheimer’s disease dementia, based on neuropathological confirmation.

This study investigates path integration impairments in vascular cognitive impairment and Alzheimer's disease, finding egocentric deficits specific to VCI and similar allocentric deficits in both groups.

This study examines the relationship between mid-life and late life leisure activities and MRI measures of brain structure and functional connectivity in older adults from the UK Biobank.

This paper develops a deep learning framework that classifies Alzheimer's disease using MRI, age, gender, and MMSE scores, achieving high accuracy across multiple datasets.

This study compares resting state EEG and structural MRI for classifying Alzheimer’s disease and mild cognitive impairment, finding MRI outperforms EEG in most cases.