Abstract
Single gene mutations that primarily affect pancreatic β-cell function account for approximately 1-2% of all cases of diabetes. Overlapping clinical features with common forms of diabetes makes diagnosis of monogenic diabetes challenging. A genetic diagnosis often leads to significant alterations in treatment, allows better prediction of disease prognosis and progression, and has implications for family members. Currently, genetic testing for monogenic diabetes relies on selection of appropriate individual genes for analysis based on the availability of often-limited phenotypic information, decreasing the likelihood of making a genetic diagnosis. We thus developed a targeted next-generation sequencing (NGS) assay for the detection of mutations in 36 genes known to cause monogenic forms of diabetes, including transient or permanent neonatal diabetes mellitus (TNDM or PNDM), maturity-onset diabetes of the young (MODY) and rare syndromic forms of diabetes. A total of 95 patient samples were analyzed: 19 with known causal mutations and 76 with a clinically suggestive phenotype but lacking a genetic diagnosis. All previously identified mutations were detected, validating our assay. Pathogenic sequence changes were identified in 19 out of 76 (25%) patients: 7 of 32 (22%) NDM cases, and 12 of 44 (27%) MODY cases. In 2 NDM patients the causal mutation was not expected as consanguinity was not reported and there were no clinical features aside from diabetes. A 3 year old patient with NDM diagnosed at 3 months of age, who previously tested negative for INS, KCNJ11 and ABCC8 mutations, was found to carry a novel homozygous mutation in EIF2AK3 (associated with Wolcott-Rallison syndrome), a gene not previously suspected because consanguinity, delayed growth, abnormal bone development and hepatic complications had not been reported. Similarly, another infant without a history of consanguinity was found to have a homozygous GCK mutation causing PNDM at birth. This study demonstrates the effectiveness of multi-gene panel analysis in uncovering molecular diagnoses in patients with monogenic forms of diabetes.