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Identification Of Pathogenic Mutations And Application Of Polygenic Risk Scores To Differentiate MODY Patients From Other Diabetes Types
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Abstract
Maturity-onset Diabetes of the Young (MODY) presents a diagnostic challenge, with a large proportion of cases lacking identifiable genetic mutations. This study investigates the genetic basis of MODY in a Latvian cohort comprising 66 suspected MODY families, contrasted with 177 non-diabetic controls. Employing panel-based and whole-genome sequencing (WGS), we identified 22 pathogenic mutations in three MODY genes (GCK, HNF1A, and HNF4A), eight of them being novel. We selected and tested the best-performing population specific type 1 diabetes (T1D) and type 2 diabetes (T2D) polygenic risk score (PRS) models on the established MODY cohort and controls. Patients without genetically confirmed MODY had a significantly higher risk for T1D compared to controls. A 75% centile of T1D-PRS included only 8.7% of the genetically confirmed MODY patients, compared to 34% of patients without mutations, providing good specificity for the identification of indicative T1D at this PRS range. While T2D-PRS was increased in the MODY cohort, it did not demonstrate an ability to discriminate between both MODY subgroups. In summary, our study demonstrates that the application of WGS improves diagnostic accuracy and highlights the potential of T1D-PRS as a critical tool for stratification of MODY suspected patients.
Springer Science and Business Media LLC
Title: Identification Of Pathogenic Mutations And Application Of Polygenic Risk Scores To Differentiate MODY Patients From Other Diabetes Types
Description:
Abstract
Maturity-onset Diabetes of the Young (MODY) presents a diagnostic challenge, with a large proportion of cases lacking identifiable genetic mutations.
This study investigates the genetic basis of MODY in a Latvian cohort comprising 66 suspected MODY families, contrasted with 177 non-diabetic controls.
Employing panel-based and whole-genome sequencing (WGS), we identified 22 pathogenic mutations in three MODY genes (GCK, HNF1A, and HNF4A), eight of them being novel.
We selected and tested the best-performing population specific type 1 diabetes (T1D) and type 2 diabetes (T2D) polygenic risk score (PRS) models on the established MODY cohort and controls.
Patients without genetically confirmed MODY had a significantly higher risk for T1D compared to controls.
A 75% centile of T1D-PRS included only 8.
7% of the genetically confirmed MODY patients, compared to 34% of patients without mutations, providing good specificity for the identification of indicative T1D at this PRS range.
While T2D-PRS was increased in the MODY cohort, it did not demonstrate an ability to discriminate between both MODY subgroups.
In summary, our study demonstrates that the application of WGS improves diagnostic accuracy and highlights the potential of T1D-PRS as a critical tool for stratification of MODY suspected patients.
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