This paper presents homogeneous clusters of patients, identified in the Alzheimer's Disease Neuroimaging Initiative (ADNI) data population of 317 females and 342 males, described by a total of 243 biological and clinical descriptors. Clustering was performed with a novel methodology, which supports identification of patient subpopulations that are homogeneous regarding both clinical and biological descriptors. Properties of the constructed clusters clearly demonstrate the differences between female and male Alzheimer's disease patient groups. The major difference is the existence of two male subpopulations with unexpected values of intracerebral and whole brain volumes.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4963443 | PMC |
http://dx.doi.org/10.1007/s40708-016-0035-5 | DOI Listing |
Expert Rev Proteomics
January 2025
Skolkovo Institute of Science and Technology, Moscow, Russian Federation.
Introduction: Identifying early risks of developing Alzheimer's disease (AD) is a major challenge as the number of patients with AD steadily increases and requires innovative solutions. Current molecular diagnostic modalities, such as cerebrospinal fluid (CSF) testing and positron emission tomography (PET) imaging, exhibit limitations in their applicability for large-scale screening. In recent years, there has been a marked shift toward the development of blood plasma-based diagnostic tests, which offer a more accessible and clinically viable alternative for widespread use.
View Article and Find Full Text PDFWorld J Clin Cases
January 2025
Department of Neurology, Guizhou Medical University, Guiyang 550004, Guizhou Province, China.
Dementia is a group of diseases, including Alzheimer's disease (AD), vascular dementia, Lewy body dementia, frontotemporal dementia, Parkinson's disease dementia, metabolic dementia and toxic dementia. The treatment of dementia mainly includes symptomatic treatment by controlling the primary disease and accompanying symptoms, nutritional support therapy for repairing nerve cells, psychological auxiliary treatment, and treatment that improves cognitive function through drugs. Among them, drug therapy to improve cognitive function is important.
View Article and Find Full Text PDFFront Pharmacol
December 2024
Department of Orthodontics, State Key Laboratory of Oral Diseases, West China School of Stomatology, Sichuan University, Chengdu, Sichuan, China.
Neprilysin (NEP), a zinc-dependent membrane-bound metallopeptidase, regulates various bioactive peptides, particularly in kidneys, vascular endothelium, and the central nervous system. NEP's involvement in metabolizing natriuretic peptides, insulin, and enkephalins makes it a promising target for treating cardiovascular and Alzheimer's diseases. Several NEP inhibitors, such as sacubitril and omapatrilat, have been approved for clinical use, which inhibit NEP activity to prolong the bioactivity of beneficial peptides, thereby exerting therapeutic effects.
View Article and Find Full Text PDFFront Neurosci
December 2024
Institute of Reconstructive Neurobiology, Medical Faculty and University Hospital of Bonn, University of Bonn, Bonn, Germany.
Brain aging is a chronic process linked to inflammation, microglial activation, and oxidative damage, which can ultimately lead to neuronal loss. Sialic acid-binding immunoglobulin-like lectin-11 (SIGLEC-11) is a human lineage-specific microglial cell surface receptor that recognizes -2-8-linked oligo-/polysialylated glycomolecules with inhibitory effects on the microglial inflammatory pathways. Recently, the gene locus was prioritized as a top tier microglial gene with potential causality to Alzheimer's disease, although its role in inflammation and neurodegeneration remains poorly understood.
View Article and Find Full Text PDFEClinicalMedicine
August 2024
Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, United Kingdom.
Background: Predicting dementia early has major implications for clinical management and patient outcomes. Yet, we still lack sensitive tools for stratifying patients early, resulting in patients being undiagnosed or wrongly diagnosed. Despite rapid expansion in machine learning models for dementia prediction, limited model interpretability and generalizability impede translation to the clinic.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!