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Selection for depression-specific dementia cases with replication in two cohorts

The latent variable “δ” (for “dementia”) provides an etiologically “agnostic” omnibus dementia severity metric capable of recognizing the dementing potential of any condition. Depressive symptoms are independent predictors of δ and are thereby implicated as “dementing”. Serum resistin levels partial...

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Detalles Bibliográficos
Autores principales: Royall, Donald R., Palmer, Raymond F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6544211/
https://www.ncbi.nlm.nih.gov/pubmed/31150419
http://dx.doi.org/10.1371/journal.pone.0216413
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author Royall, Donald R.
Palmer, Raymond F.
author_facet Royall, Donald R.
Palmer, Raymond F.
author_sort Royall, Donald R.
collection PubMed
description The latent variable “δ” (for “dementia”) provides an etiologically “agnostic” omnibus dementia severity metric capable of recognizing the dementing potential of any condition. Depressive symptoms are independent predictors of δ and are thereby implicated as “dementing”. Serum resistin levels partially mediate the association between depressive symptoms and δ. We use a novel “off-diagonal” CHI SQ algorithm to demonstrate our ability to select individuals demented solely by depression’s effect in both the Texas Alzheimer’s Research and Care Consortium (TARCC) (N ≌ 3,500), and the Alzheimer’s Disease Neuroimaging Initiative (ADNI (N ≌ 1,750), and demonstrate the higher resistin levels of such cases in TARCC. This approach can be adapted to any δ-related dementia risk factor or biomarker and used identify individuals who might revert back to non-demented states after its successful treatment.
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spelling pubmed-65442112019-06-17 Selection for depression-specific dementia cases with replication in two cohorts Royall, Donald R. Palmer, Raymond F. PLoS One Research Article The latent variable “δ” (for “dementia”) provides an etiologically “agnostic” omnibus dementia severity metric capable of recognizing the dementing potential of any condition. Depressive symptoms are independent predictors of δ and are thereby implicated as “dementing”. Serum resistin levels partially mediate the association between depressive symptoms and δ. We use a novel “off-diagonal” CHI SQ algorithm to demonstrate our ability to select individuals demented solely by depression’s effect in both the Texas Alzheimer’s Research and Care Consortium (TARCC) (N ≌ 3,500), and the Alzheimer’s Disease Neuroimaging Initiative (ADNI (N ≌ 1,750), and demonstrate the higher resistin levels of such cases in TARCC. This approach can be adapted to any δ-related dementia risk factor or biomarker and used identify individuals who might revert back to non-demented states after its successful treatment. Public Library of Science 2019-05-31 /pmc/articles/PMC6544211/ /pubmed/31150419 http://dx.doi.org/10.1371/journal.pone.0216413 Text en © 2019 Royall et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Royall, Donald R.
Palmer, Raymond F.
Selection for depression-specific dementia cases with replication in two cohorts
title Selection for depression-specific dementia cases with replication in two cohorts
title_full Selection for depression-specific dementia cases with replication in two cohorts
title_fullStr Selection for depression-specific dementia cases with replication in two cohorts
title_full_unstemmed Selection for depression-specific dementia cases with replication in two cohorts
title_short Selection for depression-specific dementia cases with replication in two cohorts
title_sort selection for depression-specific dementia cases with replication in two cohorts
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6544211/
https://www.ncbi.nlm.nih.gov/pubmed/31150419
http://dx.doi.org/10.1371/journal.pone.0216413
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