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Updated: Jan 6, 2026

In Vivo Modeling of the Morbid Human Genome using Danio rerio
Published on: August 24, 2013
Population Prevalence, Penetrance, and Mortality for Genetically Confirmed MODY
Luke N Sharp1, Kevin Colclough1,2, Jacques Murray Leech1
1Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter EX4 4QJ, UK.
Context:
Diagnosing maturity-onset diabetes of the young (MODY) is clinically important for treatment and prognosis. However, phenotype-based studies of MODY are prone to ascertainment bias, limiting accurate estimates of its population prevalence and phenotypic spectrum.
Objective:
To apply a genotype-first approach to determine the population prevalence, penetrance, and all-cause mortality associated with MODY.
Methods:
We analyzed exome sequencing and clinical data from 454 275 UK Biobank participants to identify pathogenic variants in 10 established MODY genes. We assessed variant prevalence, age-dependent diabetes penetrance, and all-cause mortality by genetic etiology over a mean follow-up of 13.4 years.
Results:
Pathogenic MODY variants were present in 1 in 1052 individuals and accounted for 1.48% of diabetes cases diagnosed before age 40. GCK variants were the most frequent (1 in 2787), demonstrating high penetrance (mean HbA1c 8.8 mmol/mol higher; 94.5% with prediabetes or diabetes) but no significant association with all-cause mortality (P = .09). Variants in other MODY genes showed lower penetrance, with 12% of carriers developing diabetes by age 40 and 31.6% by age 60 and showed no increase in all-cause mortality (P = .89). Penetrance varied by genetic etiology, with HNF1A showing the highest penetrance and PDX1, NEUROD1, and RFX6 the lowest. Parental history of diabetes and polygenic risk for type 2 diabetes were important modifiers of penetrance (hazard ratios 2.54 and 1.52, respectively; P < 3.9 × 10-3).
Conclusion:
This large-scale genotype-first study provides novel insights into MODY in the population. These findings have broad implications for genetic counseling, personalized treatment strategies, and healthcare resource allocation.
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