Comprehensive characterization of the transcriptional landscape in Alzheimer's disease (AD) brains.

Alzheimer's disease (AD) is the leading dementia among the elderly with complex origins. Despite extensive investigation into the AD-associated protein-coding genes, the involvement of noncoding RNAs (ncRNAs) and posttranscriptional modification (PTM) in AD pathogenesis remains unclear. Here, we comprehensively characterized the landscape of ncRNAs and PTM events in 1460 samples across six brain regions sourced from the Mount Sinai/JJ Peters VA Medical Center Brain Bank Study and Mayo cohorts, encompassing 33,321 long ncRNAs, 92,897 enhancer RNAs, 53,763 alternative polyadenylation events, and 900,221 A-to-I RNA editing events.

Overview of Alzheimer's Disease Neuroimaging Initiative and future clinical trials.

The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to optimize and validate biomarkers for clinical trials while sharing all data and biofluid samples with the global scientific community. ADNI has been instrumental in standardizing and validating amyloid beta (Aβ) and tau positron emission tomography (PET) imaging. ADNI data were used for the US Food and Drug Administration (FDA) approval of the Fujirebio and Roche Elecsys cerebrospinal fluid diagnostic tests.

Cell Type Differentiation Using Network Clustering Algorithms.

Single cell RNA-seq (scRNA-seq) technologies provide unprecedented resolution representing transcriptomics at the level of single cell. One of the biggest challenges in scRNA-seq data analysis is the cell type annotation, which is usually inferred by cell separation approaches. In-silico algorithms that accurately identify individual cell types in ongoing single-cell sequencing studies are crucial for unlocking cellular heterogeneity and understanding the biological basis of diseases.

Tau pathway-based gene analysis on PET identifies CLU and FYN in a Korean cohort.

Introduction: The influence of genetic variation on tau protein aggregation, a key factor in Alzheimer's disease (AD), remains not fully understood. We aimed to identify novel genes associated with brain tau deposition using pathway-based candidate gene association analysis in a Korean cohort.

Methods: We analyzed data for 146 older adults from the well-established Korean AD continuum cohort (Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's Disease; KBASE).