{"title":"Optimizing pre-genetic diagnosis of monogenic diabetes: clinical thresholds for targeted testing","authors":"Pichakacheri Sureshkumar , Sidharth S. Kumar","doi":"10.1016/j.endmts.2025.100243","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Monogenic Diabetes Mellitus (MDM) represents a minority of Diabetes Mellitus (DM) cases but poses diagnostic complexities owing to its clinical overlap with other forms of DM. Preliminary clinical screening is crucial for diagnosis due to the paucity of genetic testing facilities.</div></div><div><h3>Aim</h3><div>We aimed to identify clinical thresholds that could enhance the likelihood of obtaining positive genetic test results while excluding young-onset T2DM in suspected cases of MDM.</div></div><div><h3>Methodology</h3><div>We analyzed the demographic, anthropometric, and biochemical details of genetically confirmed MDM participants (<em>n</em> = 10) from our center and compared them with those of clinically suspected patients who tested negative for MDM (<em>n</em> = 67), excluding two neonatal DM (NDM) cases. Using Receiver Operating Characteristic curves, we determined the thresholds for various parameters, prioritizing a sensitivity of ≥75 %.</div></div><div><h3>Results</h3><div>The upper cut-off values obtained for identifying individuals with a potential for genetic positivity were age of onset of DM 25.5 years, BMI 23.5 kg/m<sup>2</sup>, visceral fat 7 %, waist circumference (irrespective of gender) 86 cm, random C-peptide 1.41 ng/mL, AST 31 units/dL, ALT 41 units/dL, triglyceride 150 mg/dL, and for HDL, the lower cut-off point was 48.5 mg/dL.</div></div><div><h3>Conclusion</h3><div>These defined thresholds offer a potential to enhance the efficient use of genetic testing by ensuring more targeted utilization, thus optimizing resource allocation and improving diagnostic accuracy in the assessment of MDM.</div></div>","PeriodicalId":34427,"journal":{"name":"Endocrine and Metabolic Science","volume":"18 ","pages":"Article 100243"},"PeriodicalIF":0.0000,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Endocrine and Metabolic Science","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666396125000299","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Monogenic Diabetes Mellitus (MDM) represents a minority of Diabetes Mellitus (DM) cases but poses diagnostic complexities owing to its clinical overlap with other forms of DM. Preliminary clinical screening is crucial for diagnosis due to the paucity of genetic testing facilities.
Aim
We aimed to identify clinical thresholds that could enhance the likelihood of obtaining positive genetic test results while excluding young-onset T2DM in suspected cases of MDM.
Methodology
We analyzed the demographic, anthropometric, and biochemical details of genetically confirmed MDM participants (n = 10) from our center and compared them with those of clinically suspected patients who tested negative for MDM (n = 67), excluding two neonatal DM (NDM) cases. Using Receiver Operating Characteristic curves, we determined the thresholds for various parameters, prioritizing a sensitivity of ≥75 %.
Results
The upper cut-off values obtained for identifying individuals with a potential for genetic positivity were age of onset of DM 25.5 years, BMI 23.5 kg/m2, visceral fat 7 %, waist circumference (irrespective of gender) 86 cm, random C-peptide 1.41 ng/mL, AST 31 units/dL, ALT 41 units/dL, triglyceride 150 mg/dL, and for HDL, the lower cut-off point was 48.5 mg/dL.
Conclusion
These defined thresholds offer a potential to enhance the efficient use of genetic testing by ensuring more targeted utilization, thus optimizing resource allocation and improving diagnostic accuracy in the assessment of MDM.