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Proposing a minimal set of metrics and methods to predict probabilities of amyloidosis disease and onset age in individuals
Many amyloid-driven pathologies have both genetic and stochastic components where assessing risk of disease development requires a multifactorial assessment where many of the variables are poorly understood. Risk of transthyretin-mediated amyloidosis is enhanced by age and mutation of the transthyre...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746394/ https://www.ncbi.nlm.nih.gov/pubmed/33203794 http://dx.doi.org/10.18632/aging.202208 |
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author | Criddle, Richard S. Lin, Hsien-Jung L. James, Isabella Park, Ji Sun Hansen, Lee D. Price, John C. |
author_facet | Criddle, Richard S. Lin, Hsien-Jung L. James, Isabella Park, Ji Sun Hansen, Lee D. Price, John C. |
author_sort | Criddle, Richard S. |
collection | PubMed |
description | Many amyloid-driven pathologies have both genetic and stochastic components where assessing risk of disease development requires a multifactorial assessment where many of the variables are poorly understood. Risk of transthyretin-mediated amyloidosis is enhanced by age and mutation of the transthyretin (TTR) gene, but amyloidosis is not directly initiated by mutated TTR proteins. Nearly all of the 150+ known mutations increase dissociation of the homotetrameric protein structure and increase the probability of an individual developing a TTR amyloid disease late in life. TTR amyloidosis is caused by dissociated monomers that are destabilized and refold into an amyloidogenic form. Therefore, monomer concentration, monomer proteolysis rate, and structural stability are key variables that may determine the rate of development of amyloidosis. Here we develop a unifying biophysical model that quantifies the relationships among these variables in plasma and suggest the probability of an individual developing a TTR amyloid disease can be estimated. This may allow quantification of risk for amyloidosis and provide the information necessary for development of methods for early diagnosis and prevention. Given the similar observation of genetic and sporadic amyloidoses for other diseases, this model and the measurements to assess risk may be applicable to more proteins than just TTR. |
format | Online Article Text |
id | pubmed-7746394 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-77463942021-01-04 Proposing a minimal set of metrics and methods to predict probabilities of amyloidosis disease and onset age in individuals Criddle, Richard S. Lin, Hsien-Jung L. James, Isabella Park, Ji Sun Hansen, Lee D. Price, John C. Aging (Albany NY) Theory Article Many amyloid-driven pathologies have both genetic and stochastic components where assessing risk of disease development requires a multifactorial assessment where many of the variables are poorly understood. Risk of transthyretin-mediated amyloidosis is enhanced by age and mutation of the transthyretin (TTR) gene, but amyloidosis is not directly initiated by mutated TTR proteins. Nearly all of the 150+ known mutations increase dissociation of the homotetrameric protein structure and increase the probability of an individual developing a TTR amyloid disease late in life. TTR amyloidosis is caused by dissociated monomers that are destabilized and refold into an amyloidogenic form. Therefore, monomer concentration, monomer proteolysis rate, and structural stability are key variables that may determine the rate of development of amyloidosis. Here we develop a unifying biophysical model that quantifies the relationships among these variables in plasma and suggest the probability of an individual developing a TTR amyloid disease can be estimated. This may allow quantification of risk for amyloidosis and provide the information necessary for development of methods for early diagnosis and prevention. Given the similar observation of genetic and sporadic amyloidoses for other diseases, this model and the measurements to assess risk may be applicable to more proteins than just TTR. Impact Journals 2020-11-18 /pmc/articles/PMC7746394/ /pubmed/33203794 http://dx.doi.org/10.18632/aging.202208 Text en Copyright: © 2020 Criddle et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Theory Article Criddle, Richard S. Lin, Hsien-Jung L. James, Isabella Park, Ji Sun Hansen, Lee D. Price, John C. Proposing a minimal set of metrics and methods to predict probabilities of amyloidosis disease and onset age in individuals |
title | Proposing a minimal set of metrics and methods to predict probabilities of amyloidosis disease and onset age in individuals |
title_full | Proposing a minimal set of metrics and methods to predict probabilities of amyloidosis disease and onset age in individuals |
title_fullStr | Proposing a minimal set of metrics and methods to predict probabilities of amyloidosis disease and onset age in individuals |
title_full_unstemmed | Proposing a minimal set of metrics and methods to predict probabilities of amyloidosis disease and onset age in individuals |
title_short | Proposing a minimal set of metrics and methods to predict probabilities of amyloidosis disease and onset age in individuals |
title_sort | proposing a minimal set of metrics and methods to predict probabilities of amyloidosis disease and onset age in individuals |
topic | Theory Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746394/ https://www.ncbi.nlm.nih.gov/pubmed/33203794 http://dx.doi.org/10.18632/aging.202208 |
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