MODY Probability Calculator Is Suitable for MODY Screening in China: A Population-based Study

Distinct Roles of Common Genetic Variants and Their Contributions to Diabetes: MODY and Uncontrolled T2DM

Type 2 diabetes mellitus (T2DM) encompasses a range of clinical manifestations, with uncontrolled diabetes leading to progressive or irreversible damage to various organs. Numerous genes associated with monogenic diabetes, exhibiting classical patterns of inheritance (autosomal dominant or recessive), have been identified. Additionally, genes involved in complex diabetes, which interact with environmental factors to trigger the disease, have also been discovered. These genetic findings have raised hopes that genetic testing could enhance diagnostics, disease surveillance, treatment selection, and family counseling. However, the accurate interpretation of genetic data remains a significant challenge, as variants may not always be definitively classified as either benign or pathogenic. Research to date, however, indicates that periodic reevaluation of genetic variants in diabetes has led to more consistent findings, with biases being steadily eliminated. This has improved the interpretation of variants across diverse ethnicities. Clinical studies suggest that genetic risk information may motivate patients to adopt behaviors that promote the prevention or management of T2DM. Given that the clinical features of certain monogenic diabetes types overlap with T2DM, and considering the significant role of genetic variants in diabetes, healthcare providers caring for prediabetic patients should consider genetic testing as part of the diagnostic process. This review summarizes current knowledge of the most common genetic variants associated with T2DM, explores novel therapeutic targets, and discusses recent advancements in the pharmaceutical management of uncontrolled T2DM.

Evaluation of the MDM-score system for screening mitochondrial diabetes mellitus in newly diagnosed diabetes patients: a multi-center cohort study in China

Objective

To evaluate the performance of MDM-score system in screening for mitochondrial diabetes mellitus (MDM) with m.3243A>G mutation in newly diagnosed diabetes.

Methods

From 2015 to 2017, we recruited 5130 newly diagnosed diabetes patients distributed in 46 hospitals in China. Their DNA samples were subjected to targeted sequencing of 37 genes, including the mitochondrial m.3243A>G mutation. Based on this cohort, we analyzed the clinical characteristics of MDM and type 2 diabetes (T2DM), and evaluated the overall efficacy of the MDM-score through ROC curve analysis.

Results

MDM patients were diagnosed at a younger age (P =0.002) than T2DM patients. They also had a higher proportion of females, lower body mass index, lower height, lower weight, lower systolic blood pressure, and lower fasting C-peptide (P < 0.05). Among 48 MDM patients, the m.3243A>G heteroplasmy level was higher in MDM score ≥ 3 than in MDM score < 3 (P = 0.0281). There were 23 cases with MDM-score ≥ 3 in clinical T2DM, with an AUC of 0.612 (95% CI: 0.540-0.683, P <0.001) on ROC curve analysis, yielding sensitivity of 47.9%, specificity of 74.4%, positive predictive value of 1.9%, and negative predictive value of 99.3%. This suggests that almost half of MDM patients can be identified by the MDM score system.

Conclusions

The MDM-score is effective for screening MDM in newly diagnosed clinical T2DM, and some metrics may help to improve its performance in the future, thereby assisting clinicians in identifying suitable patients for genetic testing, and preventing misdiagnosis and mismanagement of MDM patients.

The Maturity-Onset Diabetes of the Young (MODY) Calculator Overestimates MODY Probability in Hispanic Youth

CONTEXT

The applicability of the MODY risk calculator (Shields et al) to non- White European populations remains unknown.

OBJECTIVE

We aimed to test its real-world application in Hispanic youth.

METHODS

We conducted a retrospective chart review of Hispanic youth (<23 years) with diabetes (n=2033) in a large pediatric tertiary care center in the U.S. We calculated MODY probability for all subjects, splitting them into two cohorts based on the original model: Individuals who were started on insulin within 6 months of diabetes diagnosis (Cohort 1) and those who were not (Cohort 2).

RESULTS

Cohort 1 consisted of 1566 individuals (median age [25p, 75p]: 16 [13, 19] years, 49% female), while Cohort 2 comprised 467 youth (median age [25p, 75p]: 17 [15, 20] years, 62% female). The mean MODY probability was 5.9% and 61.9% in Cohort 1 and Cohort 2, respectively. The mean probability for both cohorts combined was 18.8% suggesting an expected 382 individuals with MODY, which is much higher than previous estimations (1-5%; i.e. 20-102 individuals in this cohort). A total of 18 individuals tested positive for MODY among the limited number of individuals tested based on clinical suspicion and genetic testing availability (n=44 out of 2033 tested, [2.2% of overall cohort]).

CONCLUSIONS

The MODY risk calculator likely overestimates the probability of MODY in Hispanic youth, largely driven by an overestimation in those not early-insulin treated (predominantly young-onset type 2 diabetes). The calculator needs updating to improve its applicability in this population. In addition, further research to help better identify MODY in Hispanic youth.

MODY Probability Calculator Is Suitable for MODY Screening in China: A Population-based Study

Context

Selecting appropriate individuals for genetic testing is essential due to the optimal treatment for maturity-onset diabetes of the young (MODY). However, how to effectively screen for MODY in China remains unclear.

Objective

To validate the performance of current screening strategies in selecting patients with MODY based on a nationwide type 2 diabetes cohort.

Methods

A panel of 14 MODY genes was analyzed from 1911 type 2 diabetes patients who were ages 15 to 35 years. Variants were evaluated according to the American College of Medical Genetics and Genomics guidelines. Based on this cohort, we simulated the 2 most frequently used screening strategies, including the traditional MODY criteria and the MODY probability calculator (MPC), to assess their ability to select patients with MODY.

Results

From a total of 1911 participants, 42 participants harbored pathogenic/likely pathogenic variants. The performance of the traditional criteria was sensitivity: 19.0%, specificity: 72.9%, positive predictive value (PPV): 1.6%, and missing rate: 81.0%. The optimal cut-off for MPC was 40.7%. Based on this cut-off value, the performance was sensitivity: 54.8%, specificity: 81.0%, PPV: 6.1%, and missing rate: 45.2%. Moreover, hemoglobin A1c, insulin treatment, and family history of diabetes have poor discrimination between MODY and young-onset type 2 diabetes.

Conclusion

The MPC is better than traditional criteria in terms of both sensitivity and PPV. To ensure more MODY patients benefit from optimal treatment, we therefore suggest that routine genetic testing be performed on all type 2 diabetes patients who are between the ages of 15 and35 years and have MPC probability value over 40.7%.