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Personalising Alzheimer’s Disease progression using brain atrophy markers
INTRODUCTION: Neuroanatomical normative modelling can capture individual variability in Alzheimer’s Disease (AD). We used neuroanatomical normative modelling to track individuals’ disease progression in people with mild cognitive impairment (MCI) and patients with AD. METHODS: Cortical thickness and...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312850/ https://www.ncbi.nlm.nih.gov/pubmed/37398392 http://dx.doi.org/10.1101/2023.06.15.23291418 |
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author | Verdi, Serena Rutherford, Saige Fraza, Charlotte Tosun, Duygu Altmann, Andre Raket, Lars Lau Schott, Jonathan M. Marquand, Andre F. Cole, James H. |
author_facet | Verdi, Serena Rutherford, Saige Fraza, Charlotte Tosun, Duygu Altmann, Andre Raket, Lars Lau Schott, Jonathan M. Marquand, Andre F. Cole, James H. |
author_sort | Verdi, Serena |
collection | PubMed |
description | INTRODUCTION: Neuroanatomical normative modelling can capture individual variability in Alzheimer’s Disease (AD). We used neuroanatomical normative modelling to track individuals’ disease progression in people with mild cognitive impairment (MCI) and patients with AD. METHODS: Cortical thickness and subcortical volume neuroanatomical normative models were generated using healthy controls (n~58k). These models were used to calculate regional Z-scores in 4361 T1-weighted MRI time-series scans. Regions with Z-scores <−1.96 were classified as outliers and mapped on the brain, and also summarised by total outlier count (tOC). RESULTS: Rate of change in tOC increased in AD and in people with MCI who converted to AD and correlated with multiple non-imaging markers. Moreover, a higher annual rate of change in tOC increased the risk of MCI progression to AD. Brain Z-score maps showed that the hippocampus had the highest rate of atrophy change. CONCLUSIONS: Individual-level atrophy rates can be tracked by using regional outlier maps and tOC. |
format | Online Article Text |
id | pubmed-10312850 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-103128502023-07-01 Personalising Alzheimer’s Disease progression using brain atrophy markers Verdi, Serena Rutherford, Saige Fraza, Charlotte Tosun, Duygu Altmann, Andre Raket, Lars Lau Schott, Jonathan M. Marquand, Andre F. Cole, James H. medRxiv Article INTRODUCTION: Neuroanatomical normative modelling can capture individual variability in Alzheimer’s Disease (AD). We used neuroanatomical normative modelling to track individuals’ disease progression in people with mild cognitive impairment (MCI) and patients with AD. METHODS: Cortical thickness and subcortical volume neuroanatomical normative models were generated using healthy controls (n~58k). These models were used to calculate regional Z-scores in 4361 T1-weighted MRI time-series scans. Regions with Z-scores <−1.96 were classified as outliers and mapped on the brain, and also summarised by total outlier count (tOC). RESULTS: Rate of change in tOC increased in AD and in people with MCI who converted to AD and correlated with multiple non-imaging markers. Moreover, a higher annual rate of change in tOC increased the risk of MCI progression to AD. Brain Z-score maps showed that the hippocampus had the highest rate of atrophy change. CONCLUSIONS: Individual-level atrophy rates can be tracked by using regional outlier maps and tOC. Cold Spring Harbor Laboratory 2023-06-16 /pmc/articles/PMC10312850/ /pubmed/37398392 http://dx.doi.org/10.1101/2023.06.15.23291418 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Verdi, Serena Rutherford, Saige Fraza, Charlotte Tosun, Duygu Altmann, Andre Raket, Lars Lau Schott, Jonathan M. Marquand, Andre F. Cole, James H. Personalising Alzheimer’s Disease progression using brain atrophy markers |
title | Personalising Alzheimer’s Disease progression using brain atrophy markers |
title_full | Personalising Alzheimer’s Disease progression using brain atrophy markers |
title_fullStr | Personalising Alzheimer’s Disease progression using brain atrophy markers |
title_full_unstemmed | Personalising Alzheimer’s Disease progression using brain atrophy markers |
title_short | Personalising Alzheimer’s Disease progression using brain atrophy markers |
title_sort | personalising alzheimer’s disease progression using brain atrophy markers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312850/ https://www.ncbi.nlm.nih.gov/pubmed/37398392 http://dx.doi.org/10.1101/2023.06.15.23291418 |
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