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Type 1 Diabetes Polygenic Scores Improve Diagnostic Accuracy in Pediatric Diabetes Care
Raymond J Kreienkamp1,2,3,4, Aaron J Deutsch2,3,4, Alicia Huerta-Chagoya2,3,4
1Division of Endocrinology, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA.
Insights
Type 1 diabetes (T1D) polygenic scores can accurately classify pediatric diabetes, improving diagnostic accuracy. These genetic risk scores show clinical utility in distinguishing T1D from other forms of diabetes in children.
Area of Science:
- Genetics
- Pediatrics
- Endocrinology
Background:
- Pediatric diabetes classification is challenging, risking suboptimal care.
- Type 1 diabetes (T1D) polygenic scores assess genetic risk for T1D.
- These scores show potential to enhance diagnostic accuracy in clinical settings.
Purpose of the Study:
- To evaluate the clinical utility of T1D polygenic scores in a pediatric cohort.
- To assess the diagnostic accuracy of T1D polygenic scores in differentiating T1D from other diabetes types.
Main Methods:
- Applied T1D polygenic scores to 1846 pediatric patients from Boston Children's Hospital PrecisionLink Biobank.
- Included 96 individuals with a T1D diagnosis and genetic data.
Main Results:
- Patients with T1D had significantly higher T1D polygenic scores than controls (P<0.0001).
- T1D polygenic scores correctly identified T1D in 69 out of 74 cases exceeding a validated cutoff.
- Scores demonstrated utility in identifying T1D in ambiguous cases, including PAA-negative and atypical diabetes presentations.
Conclusions:
- T1D polygenic scores possess clinical utility for aiding accurate pediatric diabetes diagnosis.
- Further efforts are required to integrate these genetic tools into routine clinical practice.
Background:
Accurately classifying pediatric diabetes can be challenging for providers, and misclassification can result in suboptimal care. In recent years, type 1 diabetes (T1D) polygenic scores, which quantify one's genetic risk for T1D based on T1D risk allele burden, have been developed with good discriminating capacity between T1D and not-T1D. These tools have the potential to improve significantly diagnostic provider accuracy if used in clinic.
Methods:
We applied T1D polygenic scores to a group of pediatric patients (n=1846) with genetic data available in the Boston Children's Hospital PrecisionLink Biobank, including 96 individuals diagnosed with T1D.
Results:
Patients with a clinical diagnosis of T1D had higher T1D polygenic scores compared to controls (Wilcoxon rank-sum P<0.0001). Sixty-nine of the 74 individuals with diabetes and a T1D polygenic score exceeding an externally validated cutoff for distinguishing T1D from not-T1D were confirmed to have T1D. There were multiple cases where T1D polygenic scores would have clinical utility. An elevated T1D polygenic score suggested T1D in a pancreatic autoantibody (PAA)- negative individual with negative MODY genetic testing and a phenotype matching T1D. A low T1D polygenic score accurately indicated atypical diabetes in an individual found to have HNF1B-MODY. One individual had positive PAA, but the provider noted that the patient may not have classic T1D, as later suggested by a low T1D polygenic score.
Conclusion:
T1D polygenic scores already have clinical utility to aid in the accurate diagnosis of pediatric diabetes. Efforts are now needed to advance their use in clinical practice.
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