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. 2025 Jan 9;17:16. doi: 10.1186/s13195-024-01633-2

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© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. 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-nc-nd/4.0/.

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Fig. 4 — Results from modelling LPA WMH volumes as a function of combined pathology. (A) Results from the generalized linear model including 6 pathological variables of interest. T-statistics and p values for each independent variable of interest are provided, with p values below the significance threshold (< 0.05) highlighted in bold. (B) Boxplot showing the distribution of WMH volumes as a function of Deramecourt vascular score, which shows the strongest contribution in the combined model. (C) Boxplot of WMH volume as a function of Braak tau stage, with a significant effect in the combined model. HS = hippocampal sclerosis of aging; LATE = Limbic Predominant Age-Related TDP-43 Encephalopathy; LB = Lewy body pathology; LPA = Lesion Prediction Algorithm; WMH = white matter hyperintensity