Aims: To evaluate (a) the diagnostic yield of genetic testing for monogenic diabetes when using single gene and gene panel-based testing approaches in the New Zealand (NZ) population, (b) whether the MODY (Maturity Onset Diabetes of the Young) pre-test probability calculator can be used to guide referrals for testing in NZ, (c) the number of referrals for testing for Māori/Pacific ethnicities compared to NZ European, and (d) the volume of proband vs cascade tests being requested.

Methods: A retrospective audit of 495 referrals, from NZ, for testing of monogenic diabetes genes was performed. Referrals sent to LabPlus (Auckland) laboratory for single gene testing or small multi-gene panel testing, or to the Exeter Genomics Laboratory, UK, for a large gene panel, received from January 2014 - December 2021 were included. Detection rates of single gene, small multi-gene and large gene panels (neonatal and non-neonatal), and cascade testing were analysed. Pre-test probability was calculated using the Exeter MODY probability calculator and ethnicity data was also collected.

Results: The diagnostic detection rate varied across genes, from 32% in GCK, to 2% in , with single gene or small gene panel testing averaging a 12% detection rate. Detection rate by type of panel was 9% for small gene panel, 23% for non-neonatal monogenic diabetes large gene panel and 40% for neonatal monogenic diabetes large gene panel. 45% (67/147) of patients aged 1-35 years at diabetes diagnosis scored <20% on MODY pre-test probability, of whom 3 had class 4/5 variants in , or . Ethnicity data of those selected for genetic testing correlated with population diabetes prevalence for Māori (15% vs 16%), but Pacific People appeared under-represented (8% vs 14%). Only 1 in 6 probands generated a cascade test.

Conclusions: A new monogenic diabetes testing algorithm for NZ is proposed, which directs clinicians to choose a large gene panel in patients without syndromic features who score a pre-test MODY probability of above 20%.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10080040PMC
http://dx.doi.org/10.3389/fendo.2023.1116880DOI Listing

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