Alzheimer's Disease

Genetic risk in Alzheimer's disease.

Alzheimer's disease (AD) has a strong genetic predisposition. Genome-wide association studies have identified multiple risk loci, yet many non-coding variants remain uncharacterized. Machine learning-based polygenic risk scores (PRS) enhance prediction by modeling genetic epistasis and sex-specific risks. This review summarizes AD genetic risk factors, PRS methodologies, and ML-based AD risk predi...

Plasma ATN biomarkers across the alzheimer's disease continuum in a Chilean community- and clinic-based cohort.

BACKGROUND: Plasma biomarkers have emerged as robust indicators of Alzheimer's disease (AD) pathology, offering accessible tools for staging and stratification. However, their expression across globally diverse populations remains poorly characterized. The aim of this study was to evaluate whether the combination of plasma biomarkers could distinguish different stages along the AD continuum and as...

Predicting disease-specific histone modifications and functional effects of non-coding variants by leveraging DNA language models.

BACKGROUND: Epigenetic modifications play a vital role in the pathogenesis of human diseases, particularly neurodegenerative disorders such as Alzheim...

TropMol: a cloud-based web tool for virtual screening and early-stage prediction of acetylcholinesterase inhibitors using machine learning.

Alzheimer's disease (AD) is the most common type of dementia, accounting for at least two-thirds of dementia cases in people aged 65 and older. Numero...

Capturing silent oxidative stress in early Alzheimer's disease: prediction of CSF biomarkers from sleep qEEG data.

Oxidative stress is a central pathogenic process in the earliest stages of Alzheimer's disease (AD), promoting non-enzymatic protein modifications tha...

Accelerated brain aging in prolonged grief disorder of later life: Influence of comorbid depression.

BACKGROUND: Prolonged Grief Disorder (PGD) in later life may involve volumetric patterns indicative of accelerated brain aging. This study examined wh...

Empowering Alzheimer's and Related Dementia Prevention Through Primary Care Using Responsible AI: A Pilot Walk-in Memory Sync Booth.

Alzheimer's disease and related dementias (ADRD) remain underdiagnosed early due to reliance on costly, invasive, and time-intensive assessments, prom...

AI-enhanced culturally tailored intervention for Latino family caregivers of persons living with dementia: a feasibility study.

BACKGROUND AND OBJECTIVES: CONFIDENCE is a culturally tailored intervention to reduce caregiver financial strain, which disproportionately impacts Lat...

Evaluating an AI-Enabled Mobile Mental Health Monitoring Tool Among Family Caregivers of Adults Living With Cancer: Single-Arm Feasibility and Acceptability Trial Protocol.

BACKGROUND: Psychological distress, particularly symptoms of depression and anxiety (D&A), is highly prevalent among family caregivers of individuals ...

A new graph-transformer framework for EEG-based differentiation of Alzheimer's disease and frontotemporal dementia.

Differentiating between Alzheimer's disease (AD), frontotemporal dementia (FTD), and cognitively normal (CN) subjects remains a significant challenge ...

Silencer variants are key drivers of gene up-regulation in Alzheimer's disease.

The genetic mechanisms of ~90% of Alzheimer's disease (AD)-associated variants residing in noncoding DNA remain poorly understood. To address this, we...

Association between leukocyte telomere length and neurodegenerative diseases: a prospective cohort in the UK Biobank.

BACKGROUND: This study aims to investigate the association between leukocyte telomere length (LTL) and the risk of incident NDDs using a large-scale c...

Shortening the MacArthur-Bates Communicative Developmental Inventory Using Machine Learning Based Computerized Adaptive Testing (ML-CAT).

Early identification of infants and toddlers at risk for developmental disorders can improve the efficiency of early intervention programs and can red...

A physics-informed graph neural network to approximate docking-based binding affinity for DYRK2 in Alzheimer's drug repurposing.

Alzheimer's disease (AD) requires the discovery of new therapeutic targets, but traditional molecular docking methods for virtual screening are often ...

Long-Term Caregivers' Perceptions and Expectations Toward the Use of Nursing Robots: A Meta-Synthesis of Qualitative Research.

This study aims to synthesize the perceptions and expectations of long-term caregivers regarding the use of nursing robots to inform strategies for en...

Unsupervised Disentanglement of Brain Heterogeneity for Identifying Subtypes of Alzheimer's Disease.

Neuroanatomical heterogeneity in Alzheimer's disease (AD) hinders precision diagnosis and treatment, as distinct brain phenotypes may correspond to di...

A Multiobjective Evolutionary Algorithm Based on Bipopulation With Uniform Sampling for Neural Architecture Search.

Neural architecture search (NAS) automates neural network design, improving efficiency over manual approaches. However, efficiently discovering high-p...

Alzheimer's disease prediction using deep learning and XAI based interpretable feature selection from blood gene expression data.

Alzheimer's disease (AD), a type of neurodegenerative disorder, has seen an increase in cases over the past decade, necessitating the construction of ...

Health-oriented sleep states: making sleep states reflect health conditions.

STUDY OBJECTIVES: The rich information in sleep offers insights into brain function and overall health. The current guidelines for sleep staging by th...

Elucidating the toxicological impact and mechanism of plasticizers exposure on Alzheimer's disease through network toxicology and molecular docking.

This study aimed to explore the underlying mechanisms and key targets of widely used plasticizers, including dimethyl phthalate (DMP), diethyl phthala...