| Title: | Analysis of rare coding variants in 470,000 exome-sequenced subjects characterises contributions to risk of type 2 diabetes |
| Journal: | PLOS ONE |
| Published: | 12 Dec 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39666780/ |
| DOI: | https://doi.org/10.1371/journal.pone.0311827 |
Publication 13998
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Abstract
AIMS: To follow up results from an earlier study using an extended sample of 470,000 exome-sequenced subjects to identify genes associated with type 2 diabetes (T2D) and to characterise the distribution of rare variants in these genes.</p>
MATERIALS AND METHODS: Exome sequence data for 470,000 UK Biobank participants was analysed using a combined phenotype for T2D obtained from diagnostic and prescription data. Gene-wise weighted burden analysis of rare coding variants in the new cohort of 270,000 samples was carried out for the 32 genes previously significant with uncorrected p < 0.001 along with 7 other genes previously implicated in T2D. Follow-up studies of GCK, GIGYF1, HNF1A and HNF4A used the full sample of 470,000 to investigate the effects of different categories of variant.</p>
RESULTS: No novel genes were identified as exome wide significant. Rare loss of function (LOF) variants in GCK exerted a very large effect on T2D risk but more common (though still very rare) nonsynonymous variants classified as probably damaging by PolyPhen on average approximately doubled risk. Rare variants in the other three genes also had large effects on risk.</p>
CONCLUSIONS: In spite of the very large sample size, no novel genes are implicated. Coding variants with an identifiable effect are collectively too rare be generally useful for guiding treatment choices for most patients. The finding that some nonsynonymous variants in GCK affect T2D risk is novel but not unexpected and does not have obvious practical implications. This research has been conducted using the UK Biobank Resource.</p>
10 Keywords
- Diabetes Mellitus, Type 2
- Exome
- Exome Sequencing
- Female
- Genetic Predisposition to Disease
- Genetic Variation
- Humans
- Male
- Middle Aged
- Risk Factors
1 Author
- David Curtis
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