Metabolomics facilitates differential diagnosis in common inherited retinal degenerations by exploring their profiles of serum metabolites.

Journal: Nature communications
PMID: 38670966

Abstract

The diagnosis of inherited retinal degeneration (IRD) is challenging owing to its phenotypic and genotypic complexity. Clinical information is important before a genetic diagnosis is made. Metabolomics studies the entire picture of bioproducts, which are determined using genetic codes and biological reactions. We demonstrated that the common diagnoses of IRD, including retinitis pigmentosa (RP), cone-rod dystrophy (CRD), Stargardt disease (STGD), and Bietti's crystalline dystrophy (BCD), could be differentiated based on their metabolite heatmaps. Hundreds of metabolites were identified in the volcano plot compared with that of the control group in every IRD except BCD, considered as potential diagnosing markers. The phenotypes of CRD and STGD overlapped but could be differentiated by their metabolomic features with the assistance of a machine learning model with 100% accuracy. Moreover, EYS-, USH2A-associated, and other RP, sharing considerable similar characteristics in clinical findings, could also be diagnosed using the machine learning model with 85.7% accuracy. Further study would be needed to validate the results in an external dataset. By incorporating mass spectrometry and machine learning, a metabolomics-based diagnostic workflow for the clinical and molecular diagnoses of IRD was proposed in our study.

Authors

  • Wei-Chieh Wang
    Department of Chemistry, National Taiwan University, Taipei, Taiwan.
  • Chu-Hsuan Huang
    Department of Ophthalmology, Cathay General Hospital, Taipei, Taiwan.
  • Hsin-Hsiang Chung
    Department of Chemistry , National Taiwan University , Taipei 10617 , Taiwan.
  • Pei-Lung Chen
    Graduate Institute of Medical Genomics and Proteomics, College of Medicine, National Taiwan University, Taipei, Taiwan.
  • Fung-Rong Hu
    Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan.
  • Chang-Hao Yang
    Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan; College of Medicine, National Taiwan University, Taipei, Taiwan.
  • Chung-May Yang
    Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan; College of Medicine, National Taiwan University, Taipei, Taiwan.
  • Chao-Wen Lin
    Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan.
  • Cheng-Chih Hsu
    Department of Chemistry, National Taiwan University, 10617, Taipei, Taiwan.
  • Ta-Ching Chen
    Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan.

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