ClinicalTrials.Veeva

Menu

Identification and Characterization of Novel Non-Coding Variants That Contribute to Genetic Disorders

Duke University logo

Duke University

Status

Suspended

Conditions

Inborn Errors of Metabolism
Glycogen Storage Disease
Lysosomal Storage Diseases
Genetic Disease
Storage Disease

Study type

Observational

Funder types

Other

Identifiers

NCT04399694
Pro00090878

Details and patient eligibility

About

The goal of this study is to identify and characterize novel non-coding and splicing variants that may contribute to genetic disorders. We will particularly focus on patients with a diagnosed genetic disorder that has inconclusive genetic findings.

Full description

To perform this study, we will use patient DNA and RNA that is isolated from blood samples. DNA will be sequenced (targeted capture and/or whole genome DNA sequencing (WGS)) to identify any non-coding single nucleotide variants (SNVs), smaller insertions/deletions (indels), or larger structural variants (SVs). RNA will be sequenced (RNA-seq) to identify genes that are expressed in a differential and/or allele-specific manner, which may indicate a functional non-coding or splicing variant. We will test the function of non-coding variants using high-throughput reporter assays and CRISPR based methodologies.

Enrollment

200 estimated patients

Sex

All

Volunteers

No Healthy Volunteers

Inclusion and exclusion criteria

Inclusion criteria:

Subjects will have one or more of the following:

  • Patients (probands) diagnosed with a genetic disease
  • Patients (probands) with inconclusive genetic results
  • Patients (probands) that have identical coding and/or splicing variants, but display highly diverse phenotypes
  • Unaffected family members of probands

Exclusion Criteria: There are no exclusion criteria for this study.

Trial contacts and locations

1

Loading...

Central trial contact

Erica Nading, MS, CGC

Data sourced from clinicaltrials.gov

Clinical trials

Find clinical trialsTrials by location
© Copyright 2024 Veeva Systems