Metabolomics and partial least square discriminant analysis to predict history of myocardial infarction of self-claimed healthy subjects: validity and feasibility for clinical practice

Journal of Clinical Bioinformatics

Mohd Zaki Salleh²  Lay Kek Teh²  AdzroolIdzwan Ismail³  Kamarudzaman Md.Isa³  ThuhairahHasrah Abdul Rahman⁴  FadzilahMohd Nor⁴  Aminuddin Ahmad⁴  Manikandan Selvaraj³  Thomas Hennessy¹  Zakaria Bannur³  MohdSalleh Rofiee³  Rose Iszati Ismet³  Nornazliya Mohamad³ 

[1] Life Sciences & Diagnostics Group, Translational Research Institute, Brisbane, Australia;Faculty of Pharmacy, Universiti Teknologi MARA (UiTM), Bandar Puncak Alam 42300, Selangor, Malaysia;Integrative Pharmacogenomics Institute (iPROMISE), Universiti Teknologi MARA (UiTM), Bandar Puncak Alam, Puncak Alam Malaysia 42300, Selangor, Malaysia;Faculty of Medicine, Universiti Teknologi MARA (UiTM), Sungai Buloh, Selangor, Malaysia

关键词: Phenotype;    Predictive model;    Myocardial infarction;    Metabolomics;    Orang Asli;   

Others  :  1145420
DOI  :  10.1186/s13336-015-0018-4

 received in 2014-12-26, accepted in 2015-02-27,  发布年份 2015

【 摘 要 】

Background

The dynamics of metabolomics in establishing a prediction model using partial least square discriminant analysis have enabled better disease diagnosis; with emphasis on early detection of diseases. We attempted to translate the metabolomics model to predict the health status of the Orang Asli community whom we have little information. The metabolite expressions of the healthy vs. diseased patients (cardiovascular) were compared. A metabotype model was developed and validated using partial least square discriminant analysis (PLSDA). Cardiovascular risks of the Orang Asli were predicted and confirmed by biochemistry profiles conducted concurrently.

Results

Fourteen (14) metabolites were determined as potential biomarkers for cardiovascular risks with receiver operating characteristic of more than 0.7. They include 15S-HETE (AUC = 0.997) and phosphorylcholine (AUC = 0.995). Seven Orang Asli were clustered with the patients’ group and may have ongoing cardiovascular risks and problems. This is supported by biochemistry tests results that showed abnormalities in cholesterol, triglyceride, HDL and LDL levels.

Conclusions

The disease prediction model based on metabolites is a useful diagnostic alternative as compared to the current single biomarker assays. The former is believed to be more cost effective since a single sample run is able to provide a more comprehensive disease profile, whilst the latter require different types of sampling tubes and blood volumes.

【 授权许可】

   
2015 Mohamad et al.; licensee BioMed Central.

【 图 表 】

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