Abstract
New concepts about Alzheimer's disease (AD), considered as a clinical-biological entity, make essential the definition of biomarkers that could be used for the in vivo diagnosis of the disorder before dementia develops. Different types of genetic, biochemical and neuroimaging markers have been described, highlighting some of the changes that occur in the brain during the course of the disease, yet there is little proof of their pathognomonic and diagnostic value. Furthermore, many of the assays used are difficult to perform, the equipment/reagents are expensive or potentially hazardous (e.g.; use of radioactive compounds, CSF extraction). Thus, there is a need to define more suitable and convenient approaches, such as the determination of blood parameters that are easy to obtain and that can be repeated as necessary without contraindications. These data can be used by algorithms that combine specific and non-specific changes to classify patients at different stages of AD and/or distinguish AD from other related diseases with a greater specificity and reliability (> 80%). The blood parameters considered in this review are varied, including: β-amyloid, tau, apolipoproteins and proteins, as well as the metabolic behavior of blood cells, etc. Among the proteins, cytokines/chemokines and other cell factors related to both neuro-inflammatory and peripheral-inflammatory processes in AD are of prime importance. New technologies to detect and quantify these substances, reasonably priced such as the vibrational spectroscopy, panels of parameters and algorithms to assess the results, would be fundamental for the early AD diagnosis and to define new potential therapies.
Keywords: Alzheimer’s Disease, amyloid, biomarkers, blood, blood cells, cytokines, chemokines, plasma, mild cognitive impairment, serum, blood proteins, vibrational spectroscopy.
Current Alzheimer Research
Title:Blood-Based Biomarkers of Alzheimer´s Disease: Diagnostic Algorithms and New Technologies
Volume: 13 Issue: 4
Author(s): Pedro Carmona, Marina Molina and Adolfo Toledano
Affiliation:
Keywords: Alzheimer’s Disease, amyloid, biomarkers, blood, blood cells, cytokines, chemokines, plasma, mild cognitive impairment, serum, blood proteins, vibrational spectroscopy.
Abstract: New concepts about Alzheimer's disease (AD), considered as a clinical-biological entity, make essential the definition of biomarkers that could be used for the in vivo diagnosis of the disorder before dementia develops. Different types of genetic, biochemical and neuroimaging markers have been described, highlighting some of the changes that occur in the brain during the course of the disease, yet there is little proof of their pathognomonic and diagnostic value. Furthermore, many of the assays used are difficult to perform, the equipment/reagents are expensive or potentially hazardous (e.g.; use of radioactive compounds, CSF extraction). Thus, there is a need to define more suitable and convenient approaches, such as the determination of blood parameters that are easy to obtain and that can be repeated as necessary without contraindications. These data can be used by algorithms that combine specific and non-specific changes to classify patients at different stages of AD and/or distinguish AD from other related diseases with a greater specificity and reliability (> 80%). The blood parameters considered in this review are varied, including: β-amyloid, tau, apolipoproteins and proteins, as well as the metabolic behavior of blood cells, etc. Among the proteins, cytokines/chemokines and other cell factors related to both neuro-inflammatory and peripheral-inflammatory processes in AD are of prime importance. New technologies to detect and quantify these substances, reasonably priced such as the vibrational spectroscopy, panels of parameters and algorithms to assess the results, would be fundamental for the early AD diagnosis and to define new potential therapies.
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Cite this article as:
Carmona Pedro, Molina Marina and Toledano Adolfo, Blood-Based Biomarkers of Alzheimer´s Disease: Diagnostic Algorithms and New Technologies, Current Alzheimer Research 2016; 13 (4) . https://dx.doi.org/10.2174/1567205013666151116130301
DOI https://dx.doi.org/10.2174/1567205013666151116130301 |
Print ISSN 1567-2050 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5828 |
Call for Papers in Thematic Issues
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Aims and Scope: Introduction: Alzheimer's disease (AD) poses a significant global health challenge, with an increasing prevalence that demands concerted efforts to advance our understanding and strategies for prevention, diagnosis, treatment, and rehabilitation. This thematic issue aims to bring together cutting-edge research and innovative approaches from multidisciplinary perspectives to address ...read more
Diagnostic and therapeutic biomarkers of dementia
Dementia affects 18 million people worldwide. Dementia is a syndrome of symptoms caused by brain disease, usually chronic or progressive, clinically characterized by multiple impairments of higher cortical functions such as memory, thinking, orientation, and learning. In addition, in the course of dementia, cognitive deficits are observed, which often hinder ...read more
Early nutritional intervention and physical activity in the prevention of Alzheimer's disease and other dementias
The aim is to broaden the knowledge about the impact of the consumption of food ingredients, diet ingredients, methods of processing of food raw materials as well as the impact of composing of diets on the possibility of preventing Alzheimer's disease and other types of dementia at each stage of ...read more
Enhancing Alzheimer's Disease Diagnosis and Treatment Efficacy Prediction with Explainable AI, Radiomics, Biomarkers, and Multimodal Neuroimaging
The thematic issue, Enhancing Alzheimer's Disease Diagnosis and Treatment Efficacy Prediction with Explainable AI, Radiomics, Biomarkers, and Multimodal Neuroimaging, aims to bridge the gap between advanced computational techniques and clinical practice in Alzheimer’s disease research. Alzheimer’s disease poses significant challenges in early diagnosis, disease progression monitoring, and predicting treatment efficacy. ...read more
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