ArticleFrontiers in aging neuroscience2021
Machine Learning Profiling of Alzheimer's Disease Patients Based on Current Cerebrospinal Fluid Markers and Iron Content in Biofluids.
Article in Frontiers in aging neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Systematic review: fluid biomarkers and machine learning methods to improve the diagnosis from mild cognitive impairment to Alzheimer's disease.Alzheimer's research & therapy · 2023Pooled it
- Evaluating the correspondence of neuropsychological profiles with clinical diagnostic criteria for frontotemporal lobar degeneration and Alzheimer's disease: insights fromFrontiers in dementia · 2026Article
- Development of Plasma Protein Classification Models for Alzheimer's Disease Using Multiple Machine Learning Approaches.International journal of molecular sciences · 2025Article
- From Molecules to Medicines: The Role of AI-Driven Drug Discovery Against Alzheimer's Disease and Other Neurological Disorders.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Examining the Cognitive Underpinnings of Functional Decline in Prodromal Alzheimer's Disease: Insights From the Details of Functions of Everyday Life (DoFEL) Scale.Journal of aging research · 2025Article
- The Underestimated Role of Iron in Frontotemporal Dementia: A Narrative Review.International journal of molecular sciences · 2024Review
- Identifying clusters of objective functional impairment in patients with degenerative lumbar spinal disease using unsupervised learning.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2024Article
- Iron Overload in Brain: Transport Mismatches, Microbleeding Events, and How Nanochelating Therapies May Counteract Their Effects.International journal of molecular sciences · 2024Review
- Association between Alzheimer's disease pathologic products and age and a pathologic product-based diagnostic model for Alzheimer's disease.Frontiers in aging neuroscience · 2024Article
- Article
- Advancements in Portable Voltammetry: A Promising Approach for Iron Speciation Analysis.Molecules (Basel, Switzerland) · 2023Article
- Metals in Alzheimer's Disease.Biomedicines · 2023Review
- The Use of Artificial Intelligence in the Management of Neurodegenerative Disorders; Focus on Alzheimer's Disease.Galen medical journal · 2023Article
- Heavy Metals and Essential Metals Are Associated with Cerebrospinal Fluid Biomarkers of Alzheimer's Disease.International journal of molecular sciences · 2022Article
- Searching for optimal machine learning model to classify mild cognitive impairment (MCI) subtypes using multimodal MRI data.Scientific reports · 2022Article
- Exposure of metal toxicity in Alzheimer's disease: An extensive review.Frontiers in pharmacology · 2022Review
- Alteration of Iron Concentration in Alzheimer's Disease as a Possible Diagnostic Biomarker Unveiling Ferroptosis.International journal of molecular sciences · 2021Review
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Alzheimer's disease (AD) is the most common form of dementia, characterized by a complex etiology that makes therapeutic strategies still not effective. A true understanding of key pathological mechanisms and new biomarkers are needed, to identify alternative disease-modifying therapies counteracting the disease progression. Iron is an essential element for brain metabolism and its imbalance is implicated in neurodegeneration, due to its potential neurotoxic effect. However, the role of iron in different stages of dementia is not clearly established. This study aimed to investigate the potential impact of iron both in cerebrospinal fluid (CSF) and in serum to improve early diagnosis and the related therapeutic possibility. In addition to standard clinical method to detect iron in serum, a precise quantification of total iron in CSF was performed using graphite-furnace atomic absorption spectrometry in patients affected by AD, mild cognitive impairment, frontotemporal dementia, and non-demented neurological controls. The application of machine learning techniques, such as clustering analysis and multiclassification algorithms, showed a new potential stratification of patients exploiting iron-related data. The results support the involvement of iron dysregulation and its potential interaction with biomarkers (Tau protein and Amyloid-beta) in the pathophysiology and progression of dementia.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.