Multi-Omics Integration in Clinical Practice for the Identification of Genetic Variants in Rare Diseases.

Abstract

One of the main challenges in the field of rare diseases (RDs) remains the persistent lack of timely and accurate diagnoses. Currently, it is estimated that over half of patients remain undiagnosed. The recent development of high-throughput omics technologies, such as genomics, transcriptomics, epigenomics, proteomics, and metabolomics, is transforming the diagnosis and research of rare genetic diseases. These technologies allow for a deeper understanding of the underlying molecular mechanisms and greatly improve diagnostic accuracy. This review outlines a comprehensive clinical workflow that integrates deep phenotyping, genomic variant identification, and functional validation with multi-omics approaches to enhance diagnostic accuracy in RDs. We detail the key methodologies, bioinformatics tools, and developmental processes used in omics, focusing on their roles in identifying and prioritizing candidate variants, interpreting variants of uncertain significance, and generating clinically relevant information. Furthermore, we highlight the importance of both targeted and non-targeted functional validation strategies, which provide essential evidence of pathogenicity. The integration of multi-omics approaches will improve our understanding of RDs, enhance diagnostic accuracy in clinical settings, and lay the foundation for future therapeutic development within the framework of precision medicine.