| Title: | Utility of Polygenic Scores for Differentiating Diabetes Diagnosis Among Patients With Atypical Phenotypes of Diabetes |
| Journal: | The Journal of Clinical Endocrinology & Metabolism |
| Published: | 10 Aug 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37560999/ |
| DOI: | https://doi.org/10.1210/clinem/dgad456 |
| Citations: | 3 (3 in last 2 years) as of 8 Aug 2024 |
Publication 9766
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Abstract
CONTEXT: Misclassification of diabetes type occurs in people with atypical presentations of type 1 diabetes (T1D) or type 2 diabetes (T2D). Although current clinical guidelines suggest clinical variables and treatment response as ways to help differentiate diabetes type, they remain insufficient for people with atypical presentations.</p>
OBJECTIVE: This work aimed to assess the clinical utility of 2 polygenic scores (PGSs) in differentiating between T1D and T2D.</p>
METHODS: Patients diagnosed with diabetes in the UK Biobank were studied (N = 41 787), including 464 (1%) and 15 923 (38%) who met the criteria for classic T1D and T2D, respectively, and 25 400 (61%) atypical diabetes. The validity of 2 published PGSs for T1D (PGST1D) and T2D (PGST2D) in differentiating classic T1D or T2D was assessed using C statistic. The utility of genetic probability for T1D based on PGSs (GenProb-T1D) was evaluated in atypical diabetes patients.</p>
RESULTS: The joint performance of PGST1D and PGST2D for differentiating classic T1D or T2D was outstanding (C statistic = 0.91), significantly higher than that of PGST1D alone (0.88) and PGST2D alone (0.70), both P less than .001. Using an optimal cutoff of GenProb-T1D, 23% of patients with atypical diabetes had a higher probability of T1D and its validity was independently supported by clinical presentations that are characteristic of T1D.</p>
CONCLUSION: PGST1D and PGST2D can be used to discriminate classic T1D and T2D and have potential clinical utility for differentiating these 2 types of diseases among patients with atypical diabetes.</p>
11 Authors
- Liana K Billings
- Zhuqing Shi
- Jun Wei
- Andrew S Rifkin
- S Lilly Zheng
- Brian T Helfand
- Nadim Ilbawi
- Henry M Dunnenberger
- Peter J Hulick
- Arman Qamar
- Jianfeng Xu
1 Application
| Application ID | Title |
|---|---|
| 50295 | Validity and performance of inherited risk assessment for common diseases using polygenic risk score, family history, and high-penetrance genes |
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