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. 2021 May 28;13:679688. doi: 10.3389/fnagi.2021.679688

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Copyright © 2021 Yin, Ibrahim, Petersen and Yu.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Prediction of aging and age-related diseases using autoantibodies. (A) Strategy for modeling and autoantibody selection for the prediction of aging and neurodegenerative diseases. The mean classifications accuracy rate, sensitivity, and specificity were calculated across the 500 resampled test data sets. (B) Path plot of sensitivity and specificity for models includes the 2 to 20 top selected autoantibodies for aging and neurodegenerative diseases. The numbers of autoantibodies are indicated by the numbers in the lines within the plot. Gray quadrant indicates the area of the figure in which sensitivity and specificity are higher than 0.7. (C) Path plot of the accuracy rate of classification and its SD across 500 permutations for models includes the top 2 to 20 selected autoantibodies for aging and neurodegenerative diseases. A small SD across permutations (close to 0) demonstrates a high stability of the model. (D) Heatmap of importance index of top 5 selected autoantibodies in aging and neurodegenerative diseases.