The Rare and Atypical Diabetes Network (RADIANT) Study: Design and Early Results
Authors' conclusion
The analyses will lead to improved means of atypical diabetes identification. Genetic sequencing can identify new variants, and metabolomics and transcriptomics analysis can identify novel mechanisms and biomarkers for atypical disease.
Study context
- Population
- Individuals with uncharacterized (rare and atypical) forms of diabetes and, if informative, their family members122 with WGS results
- Participants
- 878 individuals
- Outcome
- Likely pathogenic variant in a known diabetes monogenic gene
Methodological detailsdesign and early results, network study, genomic, phenotypic, metabolomic and metabolic assessments
- Design and early results
- Network study
- Genomic, phenotypic, metabolomic and metabolic assessments
Main finding
As reported in the abstract
Likely pathogenic variant in known monogenic diabetes gene, among 122 with WGS results
3
2.5%
New monogenic variants identified (SMAD5, PTPMT1, INS, NFKB1, IGF1R, PAX6)
6
Observational data: associations, not effects.
Further findings
Phenotypic clusters
- Frequent clusters: lean T2D, autoantibody-negative and insulin-deficient diabetes, lipodystrophic diabetes, and new forms of possible monogenic or oligogenic diabetes
Original publication
The Rare and Atypical Diabetes Network (RADIANT) Study: Design and Early Results. Diabetes Care. Published 27 April 2023. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →