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Updated: Aug 6, 2026
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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
Published on: April 4, 2018
From Variant Interpretation to Biomarker Translation: Multi-omics Integration in Inherited Neuromuscular Diseases
Suming Zhang1, Xiaoling Lang2, Lunxin Liu3
1Department of Radiology, Key Laboratory of Obstetric & Gynecologic and Pediatric Disease and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China, scu.edu.cn.
Human Mutation
|July 22, 2026
Summary
Multi-omics biomarkers show promise for genetic neuromuscular diseases, but clinical translation faces significant hurdles. Addressing these challenges is crucial for developing effective diagnostic and therapeutic tools.
Area of Science:
- Biomarker Discovery
- Genetics
- Neuromuscular Diseases
Background:
- Genetic neuromuscular diseases present diagnostic and therapeutic challenges, necessitating precise biomarkers.
- Multi-omics technologies (genomics, transcriptomics, proteomics, metabolomics) offer advanced biomarker discovery.
- Translational gaps hinder the clinical application of multi-omics discoveries.
Purpose of the Study:
- To systematically review multi-omics biomarker applications in genetic neuromuscular diseases.
- To analyze barriers in translating multi-omics discoveries into clinical practice.
- To explore solutions for efficient and responsible multi-omics translation.
Main Methods:
- Systematic review of current multi-omics biomarker applications.
- In-depth analysis of technical, clinical, data interpretation, and health system barriers.
- Exploration of emerging solutions like AI and policy preparedness.
Main Results:
- Multi-omics integration enhances disease diagnosis, subtyping, prognosis, and monitoring.
- Significant barriers impede the clinical translation of multi-omics biomarkers.
- Artificial intelligence, ethical governance, and policy are key to overcoming these barriers.
Conclusions:
- A framework is proposed for responsible and efficient multi-omics translation in neuromuscular disease research.
- Overcoming translational gaps requires a multidisciplinary approach.
- Future efforts should focus on integrating multi-omics data for improved patient outcomes.
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