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Parsing heterogeneity within dementia with Lewy bodies using clustering of biological, clinical, and demographic data
BACKGROUND: Dementia with Lewy bodies (DLB) includes various core clinical features that result in different phenotypes. In addition, Alzheimer’s disease (AD) and cerebrovascular pathologies are common in DLB. All this increases the heterogeneity within DLB and hampers clinical diagnosis. We address...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8783432/ https://www.ncbi.nlm.nih.gov/pubmed/35063023 http://dx.doi.org/10.1186/s13195-021-00946-w |
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author | Abdelnour, Carla Ferreira, Daniel van de Beek, Marleen Cedres, Nira Oppedal, Ketil Cavallin, Lena Blanc, Frédéric Bousiges, Olivier Wahlund, Lars-Olof Pilotto, Andrea Padovani, Alessandro Boada, Mercè Pagonabarraga, Javier Kulisevsky, Jaime Aarsland, Dag Lemstra, Afina W. Westman, Eric |
author_facet | Abdelnour, Carla Ferreira, Daniel van de Beek, Marleen Cedres, Nira Oppedal, Ketil Cavallin, Lena Blanc, Frédéric Bousiges, Olivier Wahlund, Lars-Olof Pilotto, Andrea Padovani, Alessandro Boada, Mercè Pagonabarraga, Javier Kulisevsky, Jaime Aarsland, Dag Lemstra, Afina W. Westman, Eric |
author_sort | Abdelnour, Carla |
collection | PubMed |
description | BACKGROUND: Dementia with Lewy bodies (DLB) includes various core clinical features that result in different phenotypes. In addition, Alzheimer’s disease (AD) and cerebrovascular pathologies are common in DLB. All this increases the heterogeneity within DLB and hampers clinical diagnosis. We addressed this heterogeneity by investigating subgroups of patients with similar biological, clinical, and demographic features. METHODS: We studied 107 extensively phenotyped DLB patients from the European DLB consortium. Factorial analysis of mixed data (FAMD) was used to identify dimensions in the data, based on sex, age, years of education, disease duration, Mini-Mental State Examination (MMSE), cerebrospinal fluid (CSF) levels of AD biomarkers, core features of DLB, and regional brain atrophy. Subsequently, hierarchical clustering analysis was used to subgroup individuals based on the FAMD dimensions. RESULTS: We identified 3 dimensions using FAMD that explained 38% of the variance. Subsequent hierarchical clustering identified 4 clusters. Cluster 1 was characterized by amyloid-β and cerebrovascular pathologies, medial temporal atrophy, and cognitive fluctuations. Cluster 2 had posterior atrophy and showed the lowest frequency of visual hallucinations and cognitive fluctuations and the worst cognitive performance. Cluster 3 had the highest frequency of tau pathology, showed posterior atrophy, and had a low frequency of parkinsonism. Cluster 4 had virtually normal AD biomarkers, the least regional brain atrophy and cerebrovascular pathology, and the highest MMSE scores. CONCLUSIONS: This study demonstrates that there are subgroups of DLB patients with different biological, clinical, and demographic characteristics. These findings may have implications in the diagnosis and prognosis of DLB, as well as in the treatment response in clinical trials. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13195-021-00946-w. |
format | Online Article Text |
id | pubmed-8783432 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-87834322022-01-24 Parsing heterogeneity within dementia with Lewy bodies using clustering of biological, clinical, and demographic data Abdelnour, Carla Ferreira, Daniel van de Beek, Marleen Cedres, Nira Oppedal, Ketil Cavallin, Lena Blanc, Frédéric Bousiges, Olivier Wahlund, Lars-Olof Pilotto, Andrea Padovani, Alessandro Boada, Mercè Pagonabarraga, Javier Kulisevsky, Jaime Aarsland, Dag Lemstra, Afina W. Westman, Eric Alzheimers Res Ther Research BACKGROUND: Dementia with Lewy bodies (DLB) includes various core clinical features that result in different phenotypes. In addition, Alzheimer’s disease (AD) and cerebrovascular pathologies are common in DLB. All this increases the heterogeneity within DLB and hampers clinical diagnosis. We addressed this heterogeneity by investigating subgroups of patients with similar biological, clinical, and demographic features. METHODS: We studied 107 extensively phenotyped DLB patients from the European DLB consortium. Factorial analysis of mixed data (FAMD) was used to identify dimensions in the data, based on sex, age, years of education, disease duration, Mini-Mental State Examination (MMSE), cerebrospinal fluid (CSF) levels of AD biomarkers, core features of DLB, and regional brain atrophy. Subsequently, hierarchical clustering analysis was used to subgroup individuals based on the FAMD dimensions. RESULTS: We identified 3 dimensions using FAMD that explained 38% of the variance. Subsequent hierarchical clustering identified 4 clusters. Cluster 1 was characterized by amyloid-β and cerebrovascular pathologies, medial temporal atrophy, and cognitive fluctuations. Cluster 2 had posterior atrophy and showed the lowest frequency of visual hallucinations and cognitive fluctuations and the worst cognitive performance. Cluster 3 had the highest frequency of tau pathology, showed posterior atrophy, and had a low frequency of parkinsonism. Cluster 4 had virtually normal AD biomarkers, the least regional brain atrophy and cerebrovascular pathology, and the highest MMSE scores. CONCLUSIONS: This study demonstrates that there are subgroups of DLB patients with different biological, clinical, and demographic characteristics. These findings may have implications in the diagnosis and prognosis of DLB, as well as in the treatment response in clinical trials. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13195-021-00946-w. BioMed Central 2022-01-21 /pmc/articles/PMC8783432/ /pubmed/35063023 http://dx.doi.org/10.1186/s13195-021-00946-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Abdelnour, Carla Ferreira, Daniel van de Beek, Marleen Cedres, Nira Oppedal, Ketil Cavallin, Lena Blanc, Frédéric Bousiges, Olivier Wahlund, Lars-Olof Pilotto, Andrea Padovani, Alessandro Boada, Mercè Pagonabarraga, Javier Kulisevsky, Jaime Aarsland, Dag Lemstra, Afina W. Westman, Eric Parsing heterogeneity within dementia with Lewy bodies using clustering of biological, clinical, and demographic data |
title | Parsing heterogeneity within dementia with Lewy bodies using clustering of biological, clinical, and demographic data |
title_full | Parsing heterogeneity within dementia with Lewy bodies using clustering of biological, clinical, and demographic data |
title_fullStr | Parsing heterogeneity within dementia with Lewy bodies using clustering of biological, clinical, and demographic data |
title_full_unstemmed | Parsing heterogeneity within dementia with Lewy bodies using clustering of biological, clinical, and demographic data |
title_short | Parsing heterogeneity within dementia with Lewy bodies using clustering of biological, clinical, and demographic data |
title_sort | parsing heterogeneity within dementia with lewy bodies using clustering of biological, clinical, and demographic data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8783432/ https://www.ncbi.nlm.nih.gov/pubmed/35063023 http://dx.doi.org/10.1186/s13195-021-00946-w |
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