Diabetes is a leading health problem inthe developed world. The recent surge of wealth inQatar has made it one of the most vulnerable nationsto diabetes and related diseases. Recent technologicaladvances in 1H nuclear magnetic resonance (NMR) spectroscopy techniques for metabolomics profilingoffer a great opportunity for biomarkers discovery tobetter understand the disease. Using this technology, we present in this study, an integrative approach witha newly proposed algorithm named Kernel SpectralClustering (KSC) to discover new metabolites andpossibly new biomarkers. We performed an integrativeanalysis of 1H NMR spectras measured in urine, from348 participants of the Qatar Metabolomics Study onDiabetes (QMDiab). Our analyses revealed groupedmetabolites that correlate with diabetes and identifiedspecific metabolites affected by antidiabetes medication, which constraints differentiation between diabetic andcontrol patients.
['Raghvendra Mall', 'Laure Berti-Equille', 'Halima Bensmail']
Metabolomic Data Profiling for Diabetes Research in Qatar