An application of CART algorithms for detection of an association between VDR polymorphisms and reduced bone density in individuals with type 2 diabetes: a population-based cross-sectional study

Maryam Ghodsi; Bagher Larijani; Shahin Roshani; Mahsa Mohammad Amoli; Farideh Razi; Abbas Ali Keshtkar; Patricia Khashayar; Fariba Zarrabi; Mohamad Reza  Mohajeri-Tehrani

doi:10.18502/jbe.v8i1.10406

Maryam Ghodsi Diabetes Research Center (DRC), Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Bagher Larijani Endocrinology and Metabolism Research Center (EMRC), Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences (TUMS), Tehran, Iran.
Shahin Roshani Non-Communicable Diseases Research Center (NCDRC), Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences (TUMS), Tehran, Iran
Mahsa Mohammad Amoli Metabolic Disorders Research Center (MDRC), Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences (TUMS), Tehran, Iran.
Farideh Razi Diabetes Research Center (DRC), Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Abbas Ali Keshtkar Department of Health Sciences Education Development, School of Public Health (SPH), Tehran University of Medical Sciences (TUMS), Tehran, Iran.
Patricia Khashayar Center for microsystem technology, Imec and Ghent University, Zwijnaarde, Ghent, Belgium.
Fariba Zarrabi Thrombosis Hemostasis Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Mohamad Reza Mohajeri-Tehrani Endocrinology and Metabolism Research Center (EMRC), Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences (TUMS), Tehran, Iran.

DOI: https://doi.org/10.18502/jbe.v8i1.10406

Keywords: Data mining; Osteoporosis; Bone density; Type 2; Diabetes; Vitamin D receptor

Abstract

Introduction: An important part of preventing major common diseases is identifying genetic factors that contribute to their occurrence. For the first time in our knowledge, we investigated the association between five polymorphisms of vitamin D receptor (VDR) gene (ApaI, BsmI, FokI, EcoRV, and TaqI) and low bone density/osteopenia/osteoporosis in individuals with type 2 diabetes using classification and regression tree (CART) algorithms.

Methods: Data from 158 participants with T2D were used to develop the CART analysis. The binary output variable was "bone state" with low or normal values. Age and BMI (continuous variables), vitamin D deficiency (yes/no), and gender (binary variables), as well as the studied polymorphism of the VDR gene (categorical variables) all played a role in the explanatory model. A 5-fold cross-validation process was used for model validation.

Results: Participants were divided into three groups: men, women, and both sexes. In all groups, age was the major factor predicting the low state in the final obtained tree model. The second most significant predictor in each model was BMI in both sexes (accuracy:75.30% ± 2.80%, AUC: 0.740 ± 0.064), EcoRV polymorphism in women (accuracy: 80.79% ± 6.58%, AUC:0.785 ± 0.063), and TaqI polymorphism in men (accuracy: 76.36% ± 3.05%, AUC:0.706 ± 0.125).

Conclusion: Model validation of the final tree models demonstrated that the use of CART algorithms could be an acceptable technique for risk factors of osteoporosis among individuals with T2D. Our recommendation is to conduct more population-based studies. We hope this study will serve as a basis for future research.