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. 2018 Sep 5;8:13236. doi: 10.1038/s41598-018-31653-6

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© The Author(s) 2018

Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Effects of age. (A) In NL, age was significantly correlated with subject scores determined by GLM method (r = 0.350, p < 0.001). In AD, no correlation was observed (r = 0.113, p = 0.279). Similar level of correlations were also observed only in NL when SSM/PCA1 (r = 0.370, p < 0.001) and SSM/PCA2 (r = 0.367, p < 0.001) were used. (B) Likewise, similar level of correlations between subject scores and age were observed only in stable MCI (GLM: r = 0.387, p < 0.001; SSM/PCA1: r = 0.329, p < 0.001; SSM/PCA2: r = 0.401, p < 0.001) but not in prodromal AD (r < 0.28). (C) In stable MCI, patients who were designated as “AD” (n = 45 out of 141) by SVM-ISDA were significantly older than patients who were designated as “non-AD” (^*t(184) = 2.762, p = 0.006). Similar trend was observed when SVM-SMO was used (t(184) = 1.767, p = 0.079). This age difference associated with “AD”-designation was not observed in prodromal AD patients in both SVM methods (p > 0.48).