Metabolomic Data Profiling for Diabetes Research in Qatar

RaghvenPhDa Mall, Laure Berti-Equille, Halima Bensmail

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 27th International Workshop on Database and Expert Systems Applications, DEXA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages39-43
Number of pages5
ISBN (Electronic)9781509036356
DOIs
Publication statusPublished - 12 Jan 2017
Event27th International Workshop on Database and Expert Systems Applications, DEXA 2016 - Porto, Portugal
Duration: 5 Sep 20168 Sep 2016

Other

Other27th International Workshop on Database and Expert Systems Applications, DEXA 2016
CountryPortugal
CityPorto
Period5/9/168/9/16

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Keywords

  • Biomarkers
  • Diabetes
  • H-NMR
  • Kernel Spectral Clustering 1
  • Kernel Spectral Clustering H-NMR
  • Metabolomics

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Mall, R., Berti-Equille, L., & Bensmail, H. (2017). Metabolomic Data Profiling for Diabetes Research in Qatar. In Proceedings - 27th International Workshop on Database and Expert Systems Applications, DEXA 2016 (pp. 39-43). [7816621] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DEXA.2016.023