Journal
JOURNAL OF INHERITED METABOLIC DISEASE
Volume 43, Issue 1, Pages 25-35Publisher
WILEY
DOI: 10.1002/jimd.12130
Keywords
multi-omics; genomics; transcriptomics; proteomics; diagnostics
Funding
- GENOMIT European Network for Mitochondrial Disease [01GM1207]
- mitoNet German Network for Mitochondrial Diseases [01GM1113C]
- SOUND EU Horizon2020 Collaborative Research Project [633974]
- PhD Program Medical Life Science and Technology scholarship - TUM School of Medicine
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Given the rapidly decreasing cost and increasing speed and accessibility of massively parallel technologies, the integration of comprehensive genomic, transcriptomic, and proteomic data into a multi-omics diagnostic pipeline is within reach. Even though genomic analysis has the capability to reveal all possible perturbations in our genetic code, analysis typically reaches a diagnosis in just 35% of cases, with a diagnostic gap arising due to limitations in prioritization and interpretation of detected variants. Here we review the utility of complementing genetic data with transcriptomic data and give a perspective for the introduction of proteomics into the diagnostic pipeline. Together these methodologies enable comprehensive capture of the functional consequence of variants, unobtainable by the analysis of each methodology in isolation. This facilitates functional annotation and reprioritization of candidate genes and variants-a promising approach to shed light on the underlying molecular cause of a patient's disease, increasing diagnostic rate, and allowing actionability in clinical practice.
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