Prediction of dyslipidemia using gene mutations, family history of diseases and anthropometric indicators in children and adolescents: the CASPIAN-III study

Publication date: Available online 2 March 2018 Source:Computational and Structural Biotechnology Journal Author(s): Hamid R. Marateb, Roya Kelishadi, Mohammad Reza Mohebian, Shaghayegh Haghjooy Javanmard, Amir Ali Tavallaei, Mohammad Hasan Tajadini, Motahar Heidari-Beni, Miguel Angel Mañanas, Mohammad Esmaeil Motlagh, Ramin Heshmat, Marjan Mansourian Dyslipidemia, the disorder of lipoprotein metabolism resulting in high lipid profile, is an important modifiable risk factor for coronary heart diseases (CHDs). It is associated with more than four million worldwide deaths per year. Half of the children with dyslipidemia have hyperlipidemia during adulthood, and its prediction and screening are thus critical. We designed a new dyslipidemia diagnosis system. The sample size of 725 subjects (age 14.66 ± 2.61 years; 48% male; dyslipidemia prevalence of 42%) was selected by multistage random cluster sampling in Iran. Single nucleotide polymorphisms (rs1801177, rs708272, rs320, rs328, rs2066718, rs2230808, rs5880, rs5128, rs2893157, rs662799, and Apolipoprotein-E2/E3/E4), and anthropometric, life-style attributes, and family history of diseases were analyzed. A framework for classifying mixed-type data in imbalanced datasets was proposed. It included internal feature mapping and selection, re-sampling, optimized group method of data handling using convex and stochastic optimizations, a new cost function for imbalanced data and an internal validation. Its performance wa...
Source: Computational and Structural Biotechnology Journal - Category: Biotechnology Source Type: research