Figure 1 NMF in ADD patients and classification of prodromal Alzheimer’s disease participants. Grey matter ... Figure 1 NMF in ADD patients and classification.

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Figure 1 NMF in ADD patients and classification of prodromal Alzheimer’s disease participants. Grey matter ... Figure 1 NMF in ADD patients and classification of prodromal Alzheimer’s disease participants. Grey matter segmentations were extracted from structural MRI and parcellated into 1024 equally-sized regions of interest, from which regional grey matter volumes were derived (for illustrative purposes only eight regions of interest are shown). In ADD patients, NMF, a dual-clustering approach, was used to identify clusters of features (in this case atrophy patterns) and participants at the same time. Top right: The regions of interest are clustered into distinct atrophy patterns. Each row represents a region of interest and each column an atrophy cluster. The warmer the colour, the more that region of interest contributes to the atrophy cluster. Middle: Subjects are grouped into subtypes based on the best fit of their region of interest volumes to each of the atrophy clusters. Each row represents one participant and the warmer the colour, the better the fit of that participants’ region of interest volumes to the region of interest volumes of that atrophy cluster. For each of the atrophy clusters, we made a cluster signature by computing the average volume in each of the top cluster-defining regions of interest across all ADD patients classified as that atrophy subtype. We classified prodromal Alzheimer’s disease participants based on the lowest absolute minimal distance between their own region of interest volumes and that of the cluster-signatures. AD = Alzheimer’s disease; CL = cluster; ROI = region of interest. Unless provided in the caption above, the following copyright applies to the content of this slide: © The Author(s) (2018). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.comThis article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) Brain, Volume 141, Issue 12, 22 October 2018, Pages 3443–3456, https://doi.org/10.1093/brain/awy264 The content of this slide may be subject to copyright: please see the slide notes for details.

Figure 2 Cluster features across datasets Figure 2 Cluster features across datasets. (A) In each dataset we visualized the top 100 most important ... Figure 2 Cluster features across datasets. (A) In each dataset we visualized the top 100 most important cluster-defining features. The bottom row represents the combined important cluster features across datasets: colour bars indicate whether the top 100 cluster-defining features were observed in 1/3, 2/3 or 3/3 datasets. Right hemisphere is displayed on the left side and vice versa. (B) Subtype-specific biomarker profiles: mean ± standard error (SE) of normalized values (z-scores) of CSF levels of amyloid-β<sub>1-42</sub> (abeta42), t-tau and p-tau and WMH. (C) Subtype-specific cognitive profiles: mean ± SE of normalized values (z-scores) of neuropsychological composite scores for memory, language, visuospatial and executive/attention domains. Unless provided in the caption above, the following copyright applies to the content of this slide: © The Author(s) (2018). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.comThis article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) Brain, Volume 141, Issue 12, 22 October 2018, Pages 3443–3456, https://doi.org/10.1093/brain/awy264 The content of this slide may be subject to copyright: please see the slide notes for details.

Figure 3 Atrophy patterns in each subtype Figure 3 Atrophy patterns in each subtype. (A) Voxel-based morphometry comparison between atrophy subtypes and control ... Figure 3 Atrophy patterns in each subtype. (A) Voxel-based morphometry comparison between atrophy subtypes and control (cognitively normal, amyloid negative) participants. (B) Voxel-based morphometry comparison between atrophy subtypes. Top row: In yellow-red regions where each subtype has most atrophy compared to all other clusters. Rows 2–5: In yellow-red pairwise comparisons between subtypes. Bottom row: In blue regions where each subtype has least atrophy (most grey matter) compared to all other subtypes. Colour bar represents t-statistic. Data are presented at voxel-level P<sub>FWE</sub> < 0.05. Right hemisphere is displayed on the left side and vice versa. ST1 = subtype 1 (medial-temporal dominant atrophy); ST2 = subtype 2 (parieto-occipital atrophy); ST3 = subtype 3 (mild atrophy); ST4 = subtype 4 (diffuse atrophy). Unless provided in the caption above, the following copyright applies to the content of this slide: © The Author(s) (2018). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.comThis article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) Brain, Volume 141, Issue 12, 22 October 2018, Pages 3443–3456, https://doi.org/10.1093/brain/awy264 The content of this slide may be subject to copyright: please see the slide notes for details.

Figure 4 Biomarker and cognitive profile comparisons between subtypes Figure 4 Biomarker and cognitive profile comparisons between subtypes. Data are presented as mean ± SE normalized ... Figure 4 Biomarker and cognitive profile comparisons between subtypes. Data are presented as mean ± SE normalized values (z-scores). P-values are based on ANOVA tests. For neuropsychology, composite scores are presented. Abeta42 = amyloid-β<sub>1-42</sub>. (A) Biomarker profile comparisons between subtypes in ADD. (B) Cognitive profile comparisons between subtypes in ADD. (C) Biomarker profile comparisons between subtypes in prodromal Alzheimer’s disease. (D) Cognitive profile comparisons between subtypes in prodromal Alzheimer’s disease. Subtype 1 = medial-temporal atrophy; subtype 2 = parieto-occipital atrophy; subtype 3 = mild atrophy; subtype 4 = diffuse cortical atrophy. Unless provided in the caption above, the following copyright applies to the content of this slide: © The Author(s) (2018). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.comThis article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) Brain, Volume 141, Issue 12, 22 October 2018, Pages 3443–3456, https://doi.org/10.1093/brain/awy264 The content of this slide may be subject to copyright: please see the slide notes for details.

Figure 5 Disease progression in prodromal Alzheimer’s disease for each of the four atrophy subtypes. (A) Progression ... Figure 5 Disease progression in prodromal Alzheimer’s disease for each of the four atrophy subtypes. (A) Progression curves for time to dementia onset within 3 years. (B) Decline over time in cognitive functioning in memory, language, visuospatial functioning and executive/attention plotted per subtype. Subtype 1 = medial-temporal atrophy; subtype 2 = parieto-occipital atrophy; subtype 3 = mild atrophy; subtype 4 = diffuse cortical atrophy. Unless provided in the caption above, the following copyright applies to the content of this slide: © The Author(s) (2018). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.comThis article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) Brain, Volume 141, Issue 12, 22 October 2018, Pages 3443–3456, https://doi.org/10.1093/brain/awy264 The content of this slide may be subject to copyright: please see the slide notes for details.