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Predicting future rates of tau accumulation on PET

Clinical trials with anti-tau drugs will need to target individuals at risk of accumulating tau. Our objective was to identify variables available in a research setting that predict future rates of tau PET accumulation separately among individuals who were either cognitively unimpaired or cognitivel...

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Autores principales: Jack, Clifford R, Wiste, Heather J, Weigand, Stephen D, Therneau, Terry M, Lowe, Val J, Knopman, David S, Botha, Hugo, Graff-Radford, Jonathan, Jones, David T, Ferman, Tanis J, Boeve, Bradley F, Kantarci, Kejal, Vemuri, Prashanthi, Mielke, Michelle M, Whitwell, Jennifer, Josephs, Keith, Schwarz, Christopher G, Senjem, Matthew L, Gunter, Jeffrey L, Petersen, Ronald C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7586089/
https://www.ncbi.nlm.nih.gov/pubmed/33094327
http://dx.doi.org/10.1093/brain/awaa248
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author Jack, Clifford R
Wiste, Heather J
Weigand, Stephen D
Therneau, Terry M
Lowe, Val J
Knopman, David S
Botha, Hugo
Graff-Radford, Jonathan
Jones, David T
Ferman, Tanis J
Boeve, Bradley F
Kantarci, Kejal
Vemuri, Prashanthi
Mielke, Michelle M
Whitwell, Jennifer
Josephs, Keith
Schwarz, Christopher G
Senjem, Matthew L
Gunter, Jeffrey L
Petersen, Ronald C
author_facet Jack, Clifford R
Wiste, Heather J
Weigand, Stephen D
Therneau, Terry M
Lowe, Val J
Knopman, David S
Botha, Hugo
Graff-Radford, Jonathan
Jones, David T
Ferman, Tanis J
Boeve, Bradley F
Kantarci, Kejal
Vemuri, Prashanthi
Mielke, Michelle M
Whitwell, Jennifer
Josephs, Keith
Schwarz, Christopher G
Senjem, Matthew L
Gunter, Jeffrey L
Petersen, Ronald C
author_sort Jack, Clifford R
collection PubMed
description Clinical trials with anti-tau drugs will need to target individuals at risk of accumulating tau. Our objective was to identify variables available in a research setting that predict future rates of tau PET accumulation separately among individuals who were either cognitively unimpaired or cognitively impaired. All 337 participants had: a baseline study visit with MRI, amyloid PET, and tau PET exams, at least one follow-up tau PET exam; and met clinical criteria for membership in one of two clinical diagnostic groups: cognitively unimpaired (n = 203); or cognitively impaired (n = 134, a combined group of participants with either mild cognitive impairment or dementia with Alzheimer’s clinical syndrome). Our primary analyses were in these two clinical groups; however, we also evaluated subgroups dividing the unimpaired group by normal/abnormal amyloid PET and the impaired group by clinical phenotype (mild cognitive impairment, amnestic dementia, and non-amnestic dementia). Linear mixed effects models were used to estimate associations between age, sex, education, APOE genotype, amyloid and tau PET standardized uptake value ratio (SUVR), cognitive performance, cortical thickness, and white matter hyperintensity volume at baseline, and the rate of subsequent tau PET accumulation. Log-transformed tau PET SUVR was used as the response and rates were summarized as annual per cent change. A temporal lobe tau PET meta-region of interest was used. In the cognitively unimpaired group, only higher baseline amyloid PET was a significant independent predictor of higher tau accumulation rates (P < 0.001). Higher rates of tau accumulation were associated with faster rates of cognitive decline in the cognitively unimpaired subgroup with abnormal amyloid PET (P = 0.03), but among the subgroup with normal amyloid PET. In the cognitively impaired group, younger age (P = 0.02), higher baseline amyloid PET (P = 0.05), APOE ε4 (P = 0.05), and better cognitive performance (P = 0.05) were significant independent predictors of higher tau accumulation rates. Among impaired individuals, faster cognitive decline was associated with faster rates of tau accumulation (P = 0.01). While we examined many possible predictor variables, our results indicate that screening of unimpaired individuals for potential inclusion in anti-tau trials may be straightforward because the only independent predictor of high tau rates was amyloidosis. In cognitively impaired individuals, imaging and clinical variables consistent with early onset Alzheimer’s disease phenotype were associated with higher rates of tau PET accumulation suggesting this may be a highly advantageous group in which to conduct proof-of-concept clinical trials that target tau-related mechanisms. The nature of the dementia phenotype (amnestic versus non-amnestic) did not affect this conclusion.
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spelling pubmed-75860892020-10-30 Predicting future rates of tau accumulation on PET Jack, Clifford R Wiste, Heather J Weigand, Stephen D Therneau, Terry M Lowe, Val J Knopman, David S Botha, Hugo Graff-Radford, Jonathan Jones, David T Ferman, Tanis J Boeve, Bradley F Kantarci, Kejal Vemuri, Prashanthi Mielke, Michelle M Whitwell, Jennifer Josephs, Keith Schwarz, Christopher G Senjem, Matthew L Gunter, Jeffrey L Petersen, Ronald C Brain Original Articles Clinical trials with anti-tau drugs will need to target individuals at risk of accumulating tau. Our objective was to identify variables available in a research setting that predict future rates of tau PET accumulation separately among individuals who were either cognitively unimpaired or cognitively impaired. All 337 participants had: a baseline study visit with MRI, amyloid PET, and tau PET exams, at least one follow-up tau PET exam; and met clinical criteria for membership in one of two clinical diagnostic groups: cognitively unimpaired (n = 203); or cognitively impaired (n = 134, a combined group of participants with either mild cognitive impairment or dementia with Alzheimer’s clinical syndrome). Our primary analyses were in these two clinical groups; however, we also evaluated subgroups dividing the unimpaired group by normal/abnormal amyloid PET and the impaired group by clinical phenotype (mild cognitive impairment, amnestic dementia, and non-amnestic dementia). Linear mixed effects models were used to estimate associations between age, sex, education, APOE genotype, amyloid and tau PET standardized uptake value ratio (SUVR), cognitive performance, cortical thickness, and white matter hyperintensity volume at baseline, and the rate of subsequent tau PET accumulation. Log-transformed tau PET SUVR was used as the response and rates were summarized as annual per cent change. A temporal lobe tau PET meta-region of interest was used. In the cognitively unimpaired group, only higher baseline amyloid PET was a significant independent predictor of higher tau accumulation rates (P < 0.001). Higher rates of tau accumulation were associated with faster rates of cognitive decline in the cognitively unimpaired subgroup with abnormal amyloid PET (P = 0.03), but among the subgroup with normal amyloid PET. In the cognitively impaired group, younger age (P = 0.02), higher baseline amyloid PET (P = 0.05), APOE ε4 (P = 0.05), and better cognitive performance (P = 0.05) were significant independent predictors of higher tau accumulation rates. Among impaired individuals, faster cognitive decline was associated with faster rates of tau accumulation (P = 0.01). While we examined many possible predictor variables, our results indicate that screening of unimpaired individuals for potential inclusion in anti-tau trials may be straightforward because the only independent predictor of high tau rates was amyloidosis. In cognitively impaired individuals, imaging and clinical variables consistent with early onset Alzheimer’s disease phenotype were associated with higher rates of tau PET accumulation suggesting this may be a highly advantageous group in which to conduct proof-of-concept clinical trials that target tau-related mechanisms. The nature of the dementia phenotype (amnestic versus non-amnestic) did not affect this conclusion. Oxford University Press 2020-06-24 /pmc/articles/PMC7586089/ /pubmed/33094327 http://dx.doi.org/10.1093/brain/awaa248 Text en © The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Articles
Jack, Clifford R
Wiste, Heather J
Weigand, Stephen D
Therneau, Terry M
Lowe, Val J
Knopman, David S
Botha, Hugo
Graff-Radford, Jonathan
Jones, David T
Ferman, Tanis J
Boeve, Bradley F
Kantarci, Kejal
Vemuri, Prashanthi
Mielke, Michelle M
Whitwell, Jennifer
Josephs, Keith
Schwarz, Christopher G
Senjem, Matthew L
Gunter, Jeffrey L
Petersen, Ronald C
Predicting future rates of tau accumulation on PET
title Predicting future rates of tau accumulation on PET
title_full Predicting future rates of tau accumulation on PET
title_fullStr Predicting future rates of tau accumulation on PET
title_full_unstemmed Predicting future rates of tau accumulation on PET
title_short Predicting future rates of tau accumulation on PET
title_sort predicting future rates of tau accumulation on pet
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7586089/
https://www.ncbi.nlm.nih.gov/pubmed/33094327
http://dx.doi.org/10.1093/brain/awaa248
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