In an ancestrally diverse pediatric cohort with clinician-diagnosed type 2 diabetes (ProDiGY; 82% non-White; autoantibody-negative), investigators evaluated whether the adult-derived maturity-onset diabetes of the young (MODY) probability calculator could distinguish monogenic diabetes (MODY) from youth-onset type 2 diabetes. Exome sequencing across 10 ClinGen-endorsed MODY genes identified 100 MODY cases (3%) among 3,379 participants, most commonly in HNF1A (41%), GCK (27%), HNF4A (26%), with smaller contributions from PDX1 (4%) and INS (2%). Performance was assessed at the earliest post-diagnosis time point per calculator specifications, using participants from SEARCH, TODAY, and TODAY Genetics.

Among those with complete data (44 MODY; 694 type 2 diabetes), the MODY calculator failed to add clinical utility over simple anthropometrics: its variables achieved an area under the curve (AUC) of 0.82—no better than body mass index (BMI) alone (AUC 0.82). The adult trigger threshold (>25% probability) captured 98% of MODY but also 92% of type 2 cases, yielding only a 6.3% positive rate; even >75% probability had a 7% yield. BMI was the strongest single predictor, while age at diagnosis had modest discrimination (AUC 0.63) and HbA1c or “on any medication” had none (AUC ~0.51). Parental diabetes did not differentiate groups (≈74% in both), though having two affected parents was more common in type 2 diabetes. Lower BMI enriched for MODY (eg, ≤25 kg/m²), but this strategy would miss approximately 45% of cases, and most youth with MODY were still overweight/obese by pediatric percentiles. Other helpful markers included fasting insulin and waist circumference (both AUC 0.81), C-peptide (0.80), and fibrinogen (0.77). Overall, the adult-validated calculator underperforms in youth; BMI-based screening thresholds may be a pragmatic stopgap that should vary by ancestry, but new (ideally gene-specific) biomarkers are needed to reliably distinguish MODY from youth-onset type 2 diabetes.

Reference: Kreienkamp RJ, Shields BM, Pollin TI, et al. MODY Calculator and Clinical Features Routinely Used to Distinguish MODY From Type 2 Diabetes in Adults Perform Poorly for Youth Clinically Diagnosed With Type 2 Diabetes. Diabetes Care. 2025 Jan 1;48(1):e3-e5. doi: 10.2337/dc24-1565.

Diabetes increases fracture risk through mechanisms beyond bone mineral density (BMD), making standard tools prone to underestimation—especially in type 2 diabetes (T2DM). While osteoporosis is densitometrically evident in type 1 diabetes (T1DM), both T1DM and T2DM have higher rates of low-energy fractures (hip, vertebrae, humerus; plus forearm/foot in T2DM). Contributing factors include impaired bone microarchitecture, accumulation of AGEs, low osteocalcin/P1NP with higher sclerostin, microvascular disease, hypercalciuria, vitamin D deficiency, and fall risks (neuropathy, vision loss, hypoglycemia, sarcopenia). FRAX can underestimate risk in T2DM. Trabecular bone score (TBS) adds microarchitectural insight and improves risk prediction when combined with BMD. Screening guidance suggests earlier and repeated dual-energy X-ray absorptiometry in T1DM (starting ~5 years after diagnosis) and careful interpretation of “normal” or “high” BMD in T2DM, where fracture risk may still be elevated.

Management centers on optimal glycemic control, fall prevention, vitamin D/calcium repletion, weight-bearing/strength exercise, and addressing modifiable risks (smoking, alcohol). For diabetes therapies, metformin, DPP-4 inhibitors, sulfonylureas, and GLP-1 receptor agonists are neutral/beneficial for bone. Thiazolidinediones and canagliflozin are associated with higher fracture risk and should be avoided when possible. Clinicians should incorporate TBS (and consider FRAX-with-TBS adjustment), recognize that patients with T2DM fracture at higher BMD, and maintain high suspicion for “diabetic bone disease.”

Reference: Tomasiuk JM, Nowakowska-Płaza A, Wisłowska M, Głuszko P. Osteoporosis and diabetes - possible links and diagnostic difficulties. Reumatologia. 2023;61(4):294-304. doi: 10.5114/reum/170048.

The dawn phenomenon (DP) refers to early morning hyperglycemia in individuals with diabetes or prediabetes, typically occurring between 3:00 and 8:00 AM, without prior nocturnal hypoglycemia. It impacts up to 55% of those with type 2 diabetes and is linked to poorer outcomes, including higher A1c levels and increased risks of heart and kidney disease. DP arises from an increase in hormones like cortisol and growth hormone, which trigger liver glucose production. In individuals with insulin resistance or diabetes, this process may lead to an uncontrollable blood glucose surge. Research suggests that disrupted circadian rhythms and poor sleep quality contribute to DP, offering potential areas for new treatments.

Management of DP involves both pharmacologic and nonpharmacologic approaches. While increasing medication doses can be risky due to the potential for nocturnal hypoglycemia, insulin therapy—especially continuous infusion or basal insulin—can help control the early morning glucose spike. Dietary interventions, such as higher protein meals in the evening and avoiding large, late-night meals, can reduce the severity of DP. Regular exercise, particularly before breakfast, enhances insulin sensitivity and helps manage glucose levels. A multidisciplinary approach, involving clinicians, diabetes educators, and dietitians, is essential for effective management of DP, with a focus on lifestyle adjustments and careful medication monitoring.

Reference: Yasgur B. Awakening to the Dawn Phenomenon in Diabetes. Medscape. Published November 07, 2024. Accessed January 20, 2025. https://www.medscape.com/viewarticle/awakening-dawn-phenomenon-diabetes-2024a1000kcb

The American Diabetes Association provides clinical recommendations for managing diabetes with a focus on personalized, interprofessional care. This approach considers individual preferences, cultural factors, and barriers to care. A coordinated team of specialists works with the patient with diabetes to create a comprehensive care plan, emphasizing lifestyle management, regular assessments, and evidence-based strategies to address complications like neuropathy, retinopathy, and foot care.

The comprehensive evaluation of diabetes includes regular assessments of health status, complications, and psychosocial well-being. Early identification of complications and comorbidities, such as cardiovascular disease and kidney issues, is vital for effective treatment. This includes evaluating risk factors, reviewing medications, and setting personalized goals. Annual evaluations should address complications like retinopathy and neuropathy while ensuring preventive care, including vaccinations and screenings. The guidelines also recommend screening for metabolic dysfunction–associated steatotic liver disease in individuals with type 2 diabetes or prediabetes and managing related comorbidities like obesity and cardiovascular disease.

Reference: American Diabetes Association Professional Practice Committee. 4. Comprehensive Medical Evaluation and Assessment of Comorbidities: Standards of Care in Diabetes-2024. Diabetes Care. 2024;47(Suppl 1):S52-S76. doi: 10.2337/dc24-S004. 

In healthy individuals, glucose is filtered at the glomerulus, with most reabsorbed by sodium-glucose cotransporters (SGLT2 and SGLT1) in the proximal tubule. Kidney disease can impair this process, reducing the ability to filter and reabsorb glucose, potentially causing hyperglycemia or hypoglycemia. Additionally, the kidneys consume glucose for metabolic functions and gluconeogenesis, creating a complex relationship between glucose metabolism and medication clearance, which can lead to variable glycemic outcomes in patients with kidney disease.

Indirect glycemic markers, like hemoglobin A1C, fructosamine, glycated albumin, and 1,5-anhydroglucitol (1,5-AG), are used to assess long-term glucose control. While A1C has been the gold standard, its accuracy is reduced in patients with chronic kidney disease (CKD) due to factors like anemia and medications. Alternative markers such as glycated proteins and 1,5-AG are less affected by these issues but still have limitations in CKD. Continuous glucose monitoring (CGM) offers real-time data, helping to identify glycemic excursions, especially in advanced CKD. However, more studies are needed to validate CGM’s efficacy in managing glycemia in patients with CKD.

Reference: Hassanein M, Shafi T. Assessment of glycemia in chronic kidney disease. BMC Med. 2022;20(1):117. doi: 10.1186/s12916-022-02316-1. 

Current equations used to estimate glomerular filtration rate (eGFR) incorporate age, sex, and race—despite race in these equations being used as a social, not biological, construct. To address this, researchers developed new eGFR equations that exclude race, using large development and validation data sets. When validated, existing creatinine-based equations overestimated kidney function in Black individuals and slightly in non-Black individuals. Removing the race adjustment led to underestimation in Black participants. A new equation using age and sex alone still showed racial discrepancies. However, a combined creatinine–cystatin C equation without race demonstrated improved accuracy and reduced disparities between racial groups.

These race-free creatinine–cystatin C equations were more precise than creatinine-only formulas and produced smaller differences in estimated kidney function between Black and non-Black individuals. While switching to new creatinine-only equations raised the projected prevalence of chronic kidney disease (CKD) among Black adults, the creatinine–cystatin C models offered more balanced prevalence estimates across groups. These findings support adopting race-neutral equations using both biomarkers to improve equity and clinical accuracy in CKD diagnosis and care.

Reference: Inker LA, Eneanya ND, Coresh J, et al. New Creatinine- and Cystatin C-Based Equations to Estimate GFR without Race. N Engl J Med. 2021;385(19):1737-1749. doi: 10.1056/NEJMoa2102953.

Researchers of a recent study explored the relationship between iron deficiency anemia (IDA) and diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus. A retrospective analysis of 1,398 patients found that lower hemoglobin levels were associated with an increased risk of DKD. Logistic regression confirmed IDA as an independent risk factor for DKD. Mendelian randomization analyses supported a causal link between IDA and DKD but found no significant evidence that iron supplementation contributed to DKD risk. These findings suggest that IDA itself, rather than iron therapy, may play a direct role in DKD development.

Further investigation using gene expression data from an iron-deficient diet model identified 580 differentially expressed genes associated with kidney function. These genes were enriched in biological pathways related to cytokine signaling, oxidative stress, and small molecule transport. Protein-protein interaction analysis revealed several hub genes potentially involved in this mechanism, including Cyp2d26 and Fgf4. Overall, the study concludes that IDA may contribute to DKD pathogenesis through biological stress and transport disruption, while iron supplementation appears to be safe in this population.

Reference: Huang B, Wen W, Ye S. Iron-Deficiency Anemia Elevates Risk of Diabetic Kidney Disease in Type 2 Diabetes Mellitus. J Diabetes. 2025;17(2):e70060. doi: 10.1111/1753-0407.70060. 

Chronic kidney disease (CKD) is a major health concern, increasing risks for mortality, cardiovascular issues, and kidney failure. Early identification and management are key to reducing these risks. A 5-step plan for CKD evaluation includes recognizing criteria such as abnormal kidney structure or function lasting more than three months, screening with tests like albumin-to-creatinine ratio (ACR) and glomerular filtration rate (GFR) and implementing an action plan based on CKD classification. Referrals to a nephrologist are recommended when GFR drops below 30 mL/min/1.73m2 or ACR exceeds 300 mg/g.

GFR is the most accurate method for assessing kidney function, but it's usually estimated using equations involving serum creatinine, age, race, and gender. A reduced GFR, particularly below 60 mL/min/1.73m2, increases the risk of complications, including cardiovascular disease. Albuminuria, detected via spot urine ACR, is a key marker for kidney damage. Persistent elevated albumin levels over three months signal kidney dysfunction. Monitoring GFR and ACR over time is crucial for managing CKD and preventing progression to more severe stages such as end-stage renal disease.

Reference: Quick Reference Guide on Kidney Disease Screening. National Kidney Foundation. Accessed February 26, 2025. https://www.kidney.org/quick-reference-guide-kidney-disease-screening