Dementia

Disease-specific tau polymorphs define unique protein interaction networks across proteinopathies

Tau protein aggregates exhibit distinct conformations across tauopathies, but their disease-specific protein interactions remain poorly understood. Here, we demonstrate that disease-specific tau conformations determine unique protein interaction landscapes across Alzheimer’s disease (AD), progressive supranuclear palsy (PSP), and dementia with Lewy bodies (DLB). Through comprehensive interactome p...

Frequency-Aware Interpretable Deep Learning Framework for Alzheimer’s Disease Classification Using rs-fMRI

Gaining insight into the spectral and temporal alterations in brain connectivity associated with Alzheimer’s disease (AD) may offer pathways toward more informative biomarkers and a deeper understanding of disease mechanisms. We propose FINE (Frequency-aware Interpretable Neural Encoder), a novel deep learning model designed to capture multi-scale temporal and frequency-specific patterns in dynami...

Evaluation of Deep Learning Algorithms to Predict Multiple Dementia-Related Neuropathologies from Brain MRI, Clinical and Genetic Data

Alzheimer’s disease and related dementias (ADRD) involve overlapping neurodegenerative and vascular pathologies—such as amyloid-β (Aβ), tau, cerebral ...

Hippocampal grey matter changes across scales in Alzheimer’s Disease

Alzheimer’s disease (AD) is a progressive and debilitating neurodegenerative disease of the central nervous system, characterized by deterioration in ...

Integrative Chemical Genetics Platform Identifies Condensate Modulators Linked to Neurological Disorders

Aberrant biomolecular condensates are implicated in multiple incurable neurological disorders, including Amyotrophic Lateral Sclerosis, Frontotemporal...

Cross-species connectome comparisons reveal the network attributes of memory capacity and time series prediction

The brain’s connectome provides a powerful blueprint for designing efficient neural networks, yet the impact of incorporating its intricate, non-rando...

A Systematic Fairness Evaluation of Racial Bias in Alzheimer’s Disease Diagnosis Using Machine Learning Models

Alzheimer’s disease (AD) is a major global health concern, expected to affect 12.7 million Americans by 2050. Machine learning (ML) algorithms have be...

Cooperative multi-view integration with Scalable and Interpretable Model Explainer

Single-omics approaches often provide a limited perspective on complex biological systems, whereas multi-omics integration enables a more comprehensiv...

HypoAD: volumetric and single-cell analysis reveals changes in the human hypothalamus in aging and Alzheimer’s disease

Alterations in metabolism, stress response, sleep, circadian rhythms, and neuroendocrine processes are key features of aging and neurodegeneration. Th...

MRI-based classifier to identify close-to-onset cases in C9orf72 genetic frontotemporal dementia

Predicting symptom onset in genetic frontotemporal dementia (FTD) is crucial for advancing targeted interventions and clinical trial design. Brain cha...

Neural Underpinnings of Olfactory Dysfunction across Parkinson’s and Alzheimer’s Spectra

Olfactory dysfunction is a frequent yet understudied feature of neurodegenerative spectrum disorders, including Alzheimer’s disease (AD) and Parkinson...

Leveraging Multimodal Large Language Models to Extract Mechanistic Insights from Biomedical Visuals: A Case Study on COVID-19 and Neurodegenerative Diseases

The COVID-19 pandemic has intensified concerns about its long-term neurological impact, with growing evidence linking SARS-CoV-2 infection to neurodeg...

Uncovering the dark transcriptome in polarized neuronal compartments with mcDETECT

Spatial transcriptomics (ST) is a powerful tool for studying the molecular basis of brain diseases. However, most current analyses focus only on nucle...

Bridging Language Markers and Pathology: Correlations Between Digital Speech Measures and Surrogate CSF Biomarkers in Alzheimer’s Disease

Digital language markers show promise in detecting early cognitive impairment related to Alzheimer’s disease (AD), yet their relationship with cerebro...

Increased levels of HAPLN2, which anchors dense extracellular matrix, in the hippocampus of APOE4 targeted replacement mice

Hyaluronan and proteoglycan link protein 2 (HAPLN2) / Brain link protein-1 (Bral1) is important for the binding of chondroitin sulfate proteoglycans (...

Deep Mediation Analysis for Multimodal Genotype-Imaging Associations with Disease Phenotypes

Both genotype and imaging data carry entangled information about the phenotypes. Associations between genotypes and phenotypes can be manifested or ab...

Protein Compositional Ratio Representation (PCRR) Systematically Improves Human Disease Prediction

Plasma proteomics captures a functional snapshot of human physiology; yet, most machine learning models treat protein abundances as independent variab...

BrainBridge Characterizes Key Factors affecting Alzheimer’s Disease and Associated Phenotypes

Single-cell RNA sequencing (scRNA-seq) has significantly advanced our understanding of Alzheimer’s disease and aging by revealing cellular heterogenei...

Integrative Genomic and Functional Analyses Reveal NINL as a Modulator of Tau Aggregation

Proteostasis dysfunction is a hallmark of frontotemporal dementia (FTD) and Alzheimer’s disease (AD), yet the genetic and molecular pathways that disr...

Temporal Dynamics of High-Frequency Oscillations in Alzheimer’s Disease: A Longitudinal Study in hAPP-J20 Mice

Alzheimer’s disease (AD) is characterized by progressive cognitive decline and increased seizure susceptibility; yet both the mechanistic and temporal...