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Phenotypic Heterogeneity in Dementia: A Challenge for Epidemiology and Biomarker Studies

Dementia can result from a number of distinct diseases with differing etiology and pathophysiology. Even within the same disease, there is considerable phenotypic heterogeneity with varying symptoms and disease trajectories. Dementia diagnosis is thus very complex, time-consuming, and expensive and...

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Autores principales: Ryan, Joanne, Fransquet, Peter, Wrigglesworth, Jo, Lacaze, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6018385/
https://www.ncbi.nlm.nih.gov/pubmed/29971228
http://dx.doi.org/10.3389/fpubh.2018.00181
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author Ryan, Joanne
Fransquet, Peter
Wrigglesworth, Jo
Lacaze, Paul
author_facet Ryan, Joanne
Fransquet, Peter
Wrigglesworth, Jo
Lacaze, Paul
author_sort Ryan, Joanne
collection PubMed
description Dementia can result from a number of distinct diseases with differing etiology and pathophysiology. Even within the same disease, there is considerable phenotypic heterogeneity with varying symptoms and disease trajectories. Dementia diagnosis is thus very complex, time-consuming, and expensive and can only be made definitively post-mortem with histopathological confirmation. These inherent difficulties combined with the overlap of some symptoms and even neuropathological features, present a challenging problem for research in the field. This has likely hampered progress in epidemiological studies of risk factors and preventative interventions, as well as genetic and biomarker research. Resource limitations in large epidemiologically studies mean that limited diagnostic criteria are often used, which can result in phenotypically heterogeneous disease states being grouped together, potentially resulting in misclassification bias. When biomarkers are identified for etiologically heterogeneous diseases, they will have low specificity for any utility in clinical practice, even if their sensitivity is high. We highlight several challenges in in the field which must be addressed for the success of future genetic and biomarker studies, and may be key to the development of the most effective treatments. As a step toward achieving this goal, defining the dementia as a biological construct based on the presence of specific pathological features, rather than clinical symptoms, will enable more precise predictive models. It has the potential to lead to the discovery of novel genetic variants, as well as the identification of individuals at heightened risk of the disease, even prior to the appearance of clinical symptoms.
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spelling pubmed-60183852018-07-03 Phenotypic Heterogeneity in Dementia: A Challenge for Epidemiology and Biomarker Studies Ryan, Joanne Fransquet, Peter Wrigglesworth, Jo Lacaze, Paul Front Public Health Public Health Dementia can result from a number of distinct diseases with differing etiology and pathophysiology. Even within the same disease, there is considerable phenotypic heterogeneity with varying symptoms and disease trajectories. Dementia diagnosis is thus very complex, time-consuming, and expensive and can only be made definitively post-mortem with histopathological confirmation. These inherent difficulties combined with the overlap of some symptoms and even neuropathological features, present a challenging problem for research in the field. This has likely hampered progress in epidemiological studies of risk factors and preventative interventions, as well as genetic and biomarker research. Resource limitations in large epidemiologically studies mean that limited diagnostic criteria are often used, which can result in phenotypically heterogeneous disease states being grouped together, potentially resulting in misclassification bias. When biomarkers are identified for etiologically heterogeneous diseases, they will have low specificity for any utility in clinical practice, even if their sensitivity is high. We highlight several challenges in in the field which must be addressed for the success of future genetic and biomarker studies, and may be key to the development of the most effective treatments. As a step toward achieving this goal, defining the dementia as a biological construct based on the presence of specific pathological features, rather than clinical symptoms, will enable more precise predictive models. It has the potential to lead to the discovery of novel genetic variants, as well as the identification of individuals at heightened risk of the disease, even prior to the appearance of clinical symptoms. Frontiers Media S.A. 2018-06-19 /pmc/articles/PMC6018385/ /pubmed/29971228 http://dx.doi.org/10.3389/fpubh.2018.00181 Text en Copyright © 2018 Ryan, Fransquet, Wrigglesworth and Lacaze. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Ryan, Joanne
Fransquet, Peter
Wrigglesworth, Jo
Lacaze, Paul
Phenotypic Heterogeneity in Dementia: A Challenge for Epidemiology and Biomarker Studies
title Phenotypic Heterogeneity in Dementia: A Challenge for Epidemiology and Biomarker Studies
title_full Phenotypic Heterogeneity in Dementia: A Challenge for Epidemiology and Biomarker Studies
title_fullStr Phenotypic Heterogeneity in Dementia: A Challenge for Epidemiology and Biomarker Studies
title_full_unstemmed Phenotypic Heterogeneity in Dementia: A Challenge for Epidemiology and Biomarker Studies
title_short Phenotypic Heterogeneity in Dementia: A Challenge for Epidemiology and Biomarker Studies
title_sort phenotypic heterogeneity in dementia: a challenge for epidemiology and biomarker studies
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6018385/
https://www.ncbi.nlm.nih.gov/pubmed/29971228
http://dx.doi.org/10.3389/fpubh.2018.00181
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