Prediction of serum anti-HSP27 antibody titers changes using a light gradient boosting machine (LightGBM) technique

Previous studies have proposed that heat shock proteins 27 (HSP27) and its anti-HSP27 antibody titers may play a crucial role in several diseases including cardiovascular disease. However, available studies has been used simple analytical methods. This study aimed to determine the factors that associate serum anti-HSP27 antibody titers using ensemble machine learning methods and to demonstrate the magnitude and direction of the predictors using PFI and SHAP methods. The study employed Python 3 to apply various machine learning models, including LightGBM, CatBoost, XGBoost, AdaBoost, SVR, MLP, and MLR. The best models were selected using model evaluation metrics during the K-Fold cross-validation strategy. The LightGBM model (with RMSE: 0.1900 & PLUSMN; 0.0124; MAE: 0.1471 & PLUSMN; 0.0044; MAPE: 0.8027 & PLUSMN; 0.064 as the mean & PLUSMN; sd) and the SHAP method revealed that several factors, including pro-oxidant-antioxidant balance (PAB), physical activity level (PAL), platelet distribution width, mid-upper arm circumference, systolic blood pressure, age, red cell distribution width, waist-to-hip ratio, neutrophils to lymphocytes ratio, platelet count, serum glucose, serum cholesterol, red blood cells were associated with anti-HSP27, respectively. The study found that PAB and PAL were strongly associated with serum anti-HSP27 antibody titers, indicating a direct and indirect relationship, respectively. These findings can help improve our understanding of the factors that determine anti-HSP27 antibody titers and their potential role in disease development.

Automated summary

This study used ensemble machine learning methods to determine the factors associated with serum anti-HSP27 antibody titers and demonstrated the magnitude and direction of the predictors using PFI and SHAP methods. The LightGBM model revealed several factors associated with anti-HSP27, including pro-oxidant-antioxidant balance, physical activity level, and various other factors. These findings improve our understanding of factors influencing anti-HSP27 antibody titers and their potential role in disease development.