2023 ACMG Annual Clinical Genetics Meeting Digital Edition: Poster Gallery-Diagnostic yield of multi-omics approach in Undiagnosed Diseases Network Miami Clinical Site

Pdf Summary

The study conducted at the Miami Clinical Site of the Undiagnosed Diseases Network aimed to diagnose patients with rare and undiagnosed disorders using a multi-omics approach. The research involved 42 probands from both multiplex and simplex families who had remained undiagnosed despite previous genetic investigations. The multi-omics approach included genomics, transcriptomics, and metabolomics, combined with deep phenotyping. Genome and transcriptome sequencing were performed on blood and/or fibroblast samples, and targeted and untargeted metabolomics studies were conducted on serum, plasma, and urine samples.<br /><br />The study successfully identified genetic causes in 10 probands (24% of cases). The identified genetic variants included a deep intronic variant in the PLA2G6 gene in one participant, which was discovered through a combined genome and transcriptome sequencing approach. For other participants, rare variants were detected via genome sequencing, helping to explain their observed phenotypes.<br /><br />Some interesting findings were made in specific cases. MUDN21 presented with severe progressive peripheral neuropathy and was found to have a rare missense variant in the KIF21A gene. This expands the known phenotype associated with KIF21A variants beyond the typical isolated congenital fibrosis of extraocular muscles. MUDN41 had autism and distinct craniofacial anomalies, which did not match the previously reported phenotype associated with ATP1A1 variants. Through collaboration, another patient with the same phenotype and the same ATP1A1 variant was identified, thus broadening the phenotype caused by ATP1A1 variants.<br /><br />Overall, genome sequencing was found to be the most helpful modality in identifying causative variants in the participants. RNA sequencing also assisted in confirming the splice-disrupting effect of non-coding variants in 10% of diagnosed individuals.<br /><br />This research demonstrates the diagnostic potential of a multi-omics approach in solving undiagnosed rare diseases and expanding our understanding of genotype-phenotype correlations. The findings contribute to ongoing efforts to improve the diagnosis and management of patients with rare and undiagnosed disorders.

Asset Subtitle

Presenting Author - Guney Bademci, MD, FACMG; Co-Author - Stephanie A. Bivona, MS; Co-Author - LeShon A. Peart, MD; Co-Author - Brittney Johnson, BS; Co-Author - Joanna Gonzalez, MS; Co-Author - Nicholas Borja, MD; Co-Author - Paulo Borjas-Mendoza, MD; Co-Author - Irman Forghani, MD; Co-Author - Deborah S. Barbouth; Co-Author - Kumarie Latchman, DO; Co-Author - Willa Thorson, MD; Co-Author - Shengru Guo, MS; Co-Author - Carson Smith; Co-Author - Stephan Zuchner, PhD, MD; Co-Author - Mustafa Tekin;

Meta Tag

Genome sequencing

Methodology

NextGen Sequencing

Phenotype

Variant Detection

Co-Author Stephanie A. Bivona, MS

Co-Author LeShon A. Peart, MD

Co-Author Brittney Johnson, BS

Co-Author Joanna Gonzalez, MS

Co-Author Nicholas Borja, MD

Co-Author Paulo Borjas-Mendoza, MD

Co-Author Irman Forghani, MD

Co-Author Deborah S. Barbouth

Co-Author Kumarie Latchman, DO

Co-Author Willa Thorson, MD

Co-Author Shengru Guo, MS

Co-Author Carson Smith

Co-Author Stephan Zuchner, PhD, MD

Co-Author Mustafa Tekin

Presenting Author Guney Bademci, MD, FACMG

Keywords

multi-omics approach

genomics

transcriptomics

metabolomics

deep phenotyping

genetic causes

genome sequencing

transcriptome sequencing

genetic variants

diagnostic potential