129 Distinct brain MRI phenotypes and their association with long-term dementia risk 6 subgroups. Another limitation could be that the model is dependent on the selection of brain MRI markers that were included in the model. We therefore chose to include etiologically and prognostically relevant and validated brain MRI markers of which many can be quantified automatically. Moreover, the hierarchical clustering results could also be influenced by the choice of linkage method (e.g., Ward’s, centroid), which is used to delineate the subgroups. We have chosen to use Ward’s criteria as a linkage method because it generates subgroups with minimal within subgroup variance and to maximize the between-subgroup variance, which we deemed as most suitable for this data set and type of analysis. Another general limitation of the clustering method could be that in our sensitivity analyses, we showed that there is some dependency of the clustering results based on the number and selection of participants. For future research the Subtype and Stage Inference (SuStaIn) method, an unsupervised machine learning technique that identifies population subgroups with common patterns of disease progression could be an interesting approach.37 SuStaIn could provide additional insights since it combines traditional clustering with disease progression modeling, but the effect of this approach on reproducibility is also of interest. Another limitation of this study could be that most neuroimaging research 1.5T MRI scanners are nowadays replaced with a 3T MRI system, which was not yet the case at the time of the data collection for our study. Nevertheless, we did successfully identify distinct brain MRI phenotypes based on our data set. In conclusion, distinct brain MRI phenotypes are related to varying long-term risks of developing dementia. Brain MRI phenotypes may assist in an improved understanding of the structural correlates of dementia predisposition. These findings may aid in the future to determine patient prognosis and for patient selection for future treatment studies. 6.6 ACKNOWLEDGEMENTS The Age, Gene/Environment Susceptibility Reykjavik Study was supported by NIH contracts N01-AG-1-2100 and HHSN27120120022C, the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament). This work was supported by an Alzheimer Nederland grant (WE.03-201908) to Jeroen de Bresser.
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