Untargeted metabolomic profiling reveals molecular signatures associated with type 2 diabetes in Nigerians.
Ayo P DoumateyDaniel ShrinerJie ZhouLin LeiGuanjie ChenOmolara Oluwasola-TaiwoSusan NkemAdela OgundejiSally N AdebamowoAmy R BentleyMateus H GouveiaKarlijn A C MeeksClement A AdebamowoAdebowale A AdeyemoCharles N RotimiPublished in: Genome medicine (2024)
We demonstrate that metabolomic dysregulation associated with T2D in Nigerians affects multiple processes, including glycolysis, free fatty acid and bile metabolism, and branched chain amino acid catabolism. Our study replicated previous findings in other populations and identified a metabolic signature that could be used as a biomarker panel of T2D risk and glycemic control thus enhancing our knowledge of molecular pathophysiologic changes in T2D. The metabolomics dataset generated in this study represents an invaluable addition to publicly available multi-omics data on understudied African ancestry populations.
Keyphrases
- type diabetes
- glycemic control
- fatty acid
- mass spectrometry
- amino acid
- healthcare
- single cell
- cardiovascular disease
- weight loss
- blood glucose
- insulin resistance
- metabolic syndrome
- machine learning
- gene expression
- skeletal muscle
- dna methylation
- deep learning
- high resolution
- genetic diversity
- simultaneous determination