Integrative omics approaches to advance rare disease diagnostics

Area of Science:

• Genomics
• Biochemistry
• Bioinformatics

Background:

• High-throughput DNA sequencing (whole exome and whole genome) is standard for Mendelian disease diagnostics.
• Current diagnostic rates range from 30% to 50%, leaving many patients undiagnosed.
• Advances in omics and computational analysis offer potential to increase diagnostic yield.

Purpose of the Study:

• To review the application of omics technologies for rare genetic disease diagnostics.
• To focus on inborn errors of metabolism as a specific application area.

Main Methods:

• Review of current literature on omics technologies in genetic diagnostics.
• Focus on RNA-sequencing, proteomics, metabolomics, and DNA-methylation profiling.

Main Results:

• Omics technologies provide complementary data for variant validation and prioritization.
• These methods can uncover disease mechanisms not apparent from DNA sequencing alone.
• Integration of multi-omics data enhances diagnostic accuracy.

Conclusions:

• Omics technologies are crucial for improving diagnostic rates in rare genetic diseases.
• RNA-sequencing, proteomics, metabolomics, and DNA-methylation profiling offer valuable insights.
• Further integration of these technologies is essential for comprehensive rare disease diagnostics.