# Decoding rare inherited metabolic disorders: advancing precision in screening and diagnosis

**Authors:** Muhammad Wasim, Haq Nawaz Khan, Yajun Wang, Guoda Ma

PMC · DOI: 10.1186/s13023-026-04208-6 · 2026-01-19

## TL;DR

Metabolomics is a powerful tool for detecting and managing inherited metabolic disorders by analyzing small molecules in biological samples.

## Contribution

The paper highlights metabolomics' role in improving early detection and personalized treatment of inherited metabolic disorders.

## Key findings

- Metabolomics can detect metabolic signatures specific to inherited metabolic disorders.
- Advancements in metabolomics technology are enhancing early diagnosis and disease monitoring.
- Challenges remain in standardizing and interpreting metabolomic data.

## Abstract

Inherited Metabolic Disorders (IMDs) constitute a varied group of genetic disorders marked by disruptions in essential molecule metabolism, resulting in diverse clinical manifestations. Early diagnosis and prompt intervention are critical for optimal disease management and the prevention of long-term complications. Metabolomics, an impactful analytical approach, has surfaced as a valuable tool in the screening, diagnosis, and monitoring of IMDs. This review offers an insight into the role of metabolomics in IMD screening, emphasizing its applications, challenges, and future potential. Metabolomics interrogates the complete spectrum of small-molecule metabolites in biological samples, allowing precise detection of metabolic perturbations that serve as signatures of specific disease states. Despite challenges in data interpretation and standardization, the ongoing evolution of technology positions metabolomics as a promising avenue for early detection and personalized management of IMDs, contributing to advancements in both research and clinical practice.

## Full-text entities

- **Diseases:** inherited metabolic disorders (MESH:D020739)

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12896334/full.md

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Source: https://tomesphere.com/paper/PMC12896334