ENOrphanet Journal of Rare Diseases | Applications of Metabolomics in Screening and Diagnosis of Inherited Metabolic Disorders
Date: February 17, 2026
Classification: Frontiers
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This article systematically reviews the clinical applications of metabolomics in inherited metabolic disorders, emphasizing its critical role in early screening, precise diagnosis, and personalized treatment, while also discussing technical challenges and future research directions.
Literature Overview
The article titled 'Decoding rare inherited metabolic disorders: advancing precision in screening and diagnosis,' published in the Orphanet Journal of Rare Diseases, reviews and summarizes recent advances in the application of metabolomics for screening and diagnosing inherited metabolic disorders (IMDs). The paper systematically outlines the clinical features and diagnostic challenges of IMDs, focusing on the advantages of metabolomics in improving diagnostic efficiency, discovering novel biomarkers, and enabling personalized management. It also discusses current bottlenecks such as technical standardization, data interpretation, and multi-omics integration, while highlighting the potential of artificial intelligence and multi-center collaborations to advance the field.Background Knowledge
Inherited metabolic disorders (IMDs) are a group of genetic diseases caused by mutations in genes encoding metabolic enzymes or transporters, leading to abnormal synthesis, breakdown, or transport of molecules such as carbohydrates, lipids, amino acids, organic acids, and nucleotides. These diseases exhibit highly heterogeneous clinical manifestations, affecting multiple organ systems, with common symptoms including developmental delay, intellectual disability, seizures, and metabolic crises. Without timely intervention, they may lead to severe disability or death. Current newborn screening primarily relies on tandem mass spectrometry (MS/MS) to detect approximately 50–60 metabolites, covering only a limited number of conditions. However, many IMDs remain undiagnosed using conventional methods. Metabolomics, an omics technology that studies all small-molecule metabolites in biological systems, comprehensively captures dynamic changes in metabolic networks using techniques such as mass spectrometry (MS) or nuclear magnetic resonance (NMR). Targeted and untargeted metabolomics are suitable for analyzing known pathways and discovering unknown metabolites, respectively. In recent years, its application in IMDs has significantly improved diagnostic rates, particularly in patients with unexplained neurodevelopmental disorders. Nevertheless, challenges related to technical standardization, database development, data complexity, and cost continue to limit its widespread clinical translation. Therefore, optimizing analytical workflows, integrating multi-omics data, and facilitating clinical implementation have become key research priorities.
Research Methods and Experiments
This study employed a systematic literature review approach, searching peer-reviewed English research articles, reviews, and case reports related to 'inherited metabolic disorders' and 'metabolomics' in PubMed, Web of Science, and Google Scholar from January 2002 to June 2025. Studies were screened and quality-assessed based on scientific rigor, clarity, and clinical relevance. The literature analysis covered clinical features of IMDs, the importance of early diagnosis, technical principles of metabolomics, and its applications in screening, diagnosis, and monitoring, while summarizing current challenges and future directions.Key Conclusions and Insights
Research Significance and Outlook
This study underscores the central role of metabolomics in the management of IMDs, providing strong technical support for early diagnosis and offering new perspectives for understanding disease mechanisms and developing targeted therapies. By integrating AI and multi-omics data, more precise diagnostic models may be developed in the future, enabling a shift from 'reactive care' to 'predictive and preventive medicine.'
In addition, the article calls for strengthened international collaboration to establish standardized analytical workflows and shared databases, promoting the transition of metabolomics from a research tool to routine clinical testing. It also emphasizes the need for cost-effectiveness analyses to improve accessibility across healthcare systems. With ongoing advancements in high-resolution mass spectrometry, NMR technologies, and computational methods, metabolomics is poised to become a cornerstone technology in newborn screening and rare disease diagnosis.
Conclusion
This article provides a comprehensive summary of the value and challenges of metabolomics in the screening and diagnosis of inherited metabolic disorders (IMDs). Metabolomics has significantly improved diagnostic rates for IMDs due to its high throughput, high sensitivity, and non-invasive sampling advantages, demonstrating strong potential in complex cases that remain undiagnosed by traditional methods. Through comprehensive metabolic profiling, the technology not only enables early detection and precise subtyping but also provides critical insights into disease mechanisms, biomarker discovery, and personalized treatment guidance. Integration with artificial intelligence and multi-omics strategies further enhances diagnostic accuracy and efficiency. However, issues related to technical standardization, complex data interpretation, and high costs remain major barriers to clinical translation. Future efforts should focus on large-scale multi-center studies, workflow optimization, and database development to advance metabolomics into routine clinical practice. Overall, metabolomics is becoming an indispensable tool in the management of IMDs, with the potential to significantly improve patient outcomes and reduce healthcare burdens.
