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Screening pathway could aid in diagnosis of monogenic diabetes
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A biomarker-based screening method assessing levels of C-peptide and islet autoantibodies in patients with diabetes is an effective, inexpensive approach to identify patients with monogenic forms of the disease, including maturity-onset diabetes of the young, according to findings from a population-based assessment conducted in Britain.
“Identifying patients with monogenic diabetes, particularly [maturity-onset diabetes of the young], can be challenging,” Beverley M. Shields, PhD, senior lecturer in medical statistics with the Institute of Biomedical and Clinical Science at the University of Exeter Medical School, United Kingdom, and colleagues wrote. “Monogenic diabetes is confirmed by molecular genetic testing, but this is expensive, so testing all patients is not feasible. An approach that could be used to enrich for monogenic diabetes, increasing the proportion identified in those who undergo genetic testing, would be helpful.”
Shields and colleagues tested a screening pathway using both C-peptide (via urinary C-peptide to creatinine ratio) and glutamic acid decarboxylase (GAD) and insulinoma-associated-2 autoantibodies (IA-2A) to exclude type 1 diabetes in two populations with previously high pickup rates of maturity-onset diabetes of the young (MODY) — patients diagnosed before age 30 years and currently younger than 50 years from the areas surrounding Royal Devon and Exeter NHS Foundation Trust (n = 716) and Ninewells Hospital (n = 702), both in the United Kingdom. For all patients negative for antibodies with significant endogenous insulin, DNA sequencing was performed for known MODY-related mutations.
Within the cohort, 1,365 had no known genetic cause for their diabetes, 34 had confirmed monogenic diabetes at baseline and eight had cystic fibrosis-related diabetes. After urinary C-peptide to creatinine testing, 979 (76%) had minimal endogenous insulin secretion, indicating type 1 diabetes, and received no further testing. Of the 386 patients then tested for GAD or IA-2A autoantibodies, 170 (44%) tested positive, also indicating type 1 diabetes, and received no further testing.
The remaining 216 patients underwent sequencing for the three most common MODY-related genes; eight tested positive, according to researchers. Of the 208 who tested negative for common MODY genes, additional testing by targeted, next-generation sequencing identified mutations in genes associated with monogenic diabetes in eight more patients. One additional patient had a MODY-related mutation identified through exome sequencing. The results suggested a prevalence of 3.6% (95% CI, 2.7-4.7) among the 1,407 recruited participants.
“A total of 199 out of 1,348 (15%) patients were put forward for genetic testing who were not found to have monogenic diabetes (ie, 15% false-positive rate, so 85% specificity),” the researchers wrote. “Assuming a 98% sensitivity and 85% specificity, the [positive predictive value] for the pathway is 20%, suggesting a 1-in-5 pickup rate for monogenic diabetes, a 5.6-fold increase in probability over the background prevalence alone.”
The strength of the pathway, the researchers wrote, is in the integration of both C-peptide and islet autoantibodies, rather than relying on clinical features.
“This offers a simple approach that does not require specific clinician interpretation or complex algorithms of different combinations of features,” the researchers wrote. “By combining the two biomarkers, we increase the discriminatory ability and allow the clinician to pick up even atypical cases and rarer forms of monogenic diabetes, which traditional criteria may miss. The use of clinical features, however, results in fewer cases being sent for genetic testing that are negative, which clearly has cost implications.”
The most cost-effective approach will likely involve a combination of both biomarkers and clinical features, they noted, and further research is needed to determine whether the pickup rate could be improved by integrating the pathway with clinical features, such as the MODY calculator. – by Regina Schaffer
Disclosures: The authors report no relevant financial disclosures.
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