ABSTRACT
Aims
Evidence regarding the efficacy and safety of sodium–glucose cotransporter 2 inhibitors (SGLT2i) in monogenic diabetes is limited. We evaluated real‐world metabolic, renal, and safety outcomes of SGLT2i therapy in adults with monogenic diabetes.
Materials and Methods
This multicenter retrospective study included adults with genetically confirmed monogenic diabetes treated with SGLT2i. Clinical and biological data were collected at baseline and after approximately 1 and 2 years. Longitudinal changes were analysed using linear mixed‐effects models adjusted for baseline value, age, and sex and treatment intensification.
Results
Forty patients (mean age 48.6 ± 15.2 years) with MIDD (n = 16), HNF1B‐MODY (n = 9), HNF1A/HNF4A‐MODY (n = 11), or other MODY subtypes (ABCC8, INS, RFX6; n = 4) were followed for 23.9 ± 5.9 months. HbA1c remained stable overall but decreased significantly in patients with baseline HbA1c ≥ 8% (9.6% ± 1.3% to 7.6% ± 0.7%; p = 0.001). UACR declined significantly (−35.6% at 1 year and −43.5% at 2 years; p = 0.004), particularly in those with baseline CKD (trend). Genotype‐specific trends suggested greater glycemic improvement in HNF1A/HNF4A‐MODY and greater UACR reduction in MIDD. eGFR declined modestly over time. Non‐serious adverse events occurred in 15% of patients, 7.5% discontinued treatment, and no ketoacidosis, acute kidney injury, or deaths were reported.
Conclusions
In this nationwide cohort of patients with monogenic diabetes—the largest reported to date—SGLT2i therapy was associated with improved glycemic control in individuals with baseline HbA1c ≥ 8%, reduced albuminuria, and showed a favourable safety profile. These findings support SGLT2i as a potential therapeutic option that warrants confirmation in larger controlled studies.
Keywords: diabetic nephropathy, insulin secretion, observational study, SGLT2 inhibitor
1. Introduction
Sodium–glucose cotransporter 2 inhibitors (SGLT2i) are now central to type 2 diabetes (T2D) management [1]. By promoting glycosuria, they modestly lower HbA1c (0.5%–0.8%/6–9 mmol/mol) and confer cardio‐renal protection, potentially via reduced oxidative stress, enhanced mitochondrial efficiency, and decreased inflammation [2, 3]. Common adverse effects such as urogenital infections are mild, while rare but serious events include euglycaemic diabetic ketoacidosis (DKA), especially in the setting of insulin deficiency. For instance, in the Empagliflozin as Adjunctive to Insulin Therapy (EASE) program, ketosis occurred in 25% of patients with type 1 diabetes on empagliflozin and DKA in 4% [4].
Monogenic diabetes is a rare form of diabetes (2%–5% of cases) caused by single‐gene variants mainly affecting insulin secretion. Main subtypes include maturity‐onset diabetes of the young (MODY), maternally inherited diabetes and deafness (MIDD), and neonatal diabetes (ND) typically characterized by early onset, absence of autoimmunity, and autosomal dominant inheritance. Despite shared β‐cell dysfunction, each subtype has distinct pathophysiology requiring tailored treatment, making genetic diagnosis essential [5, 6]. GCK‐MODY usually causes mild hyperglycaemia without treatment. HNF1A‐ and HNF4A‐MODY present with progressive insulin deficiency, are predisposed to complications similar to T2D [7, 8] and are mainly treated with sulfonylureas [9]. Glycosuria in HNF1A‐MODY may relate to reduced SGLT2 expression due to HNF1A regulation of the SLC5A2 gene [10]. HNF1B‐MODY and MIDD are syndromic forms often requiring insulin therapy and cardio‐renal protection [9, 11]. HNF1B‐MODY is frequently associated with congenital kidney anomalies, renal dysfunction, or electrolyte disturbances [12]. MIDD, accounting for ~1% of diabetes, is maternally inherited. Mitochondrial DNA variants impair the respiratory chain, increasing oxidative stress and energy deficiency, resulting in insulin resistance and progressive β‐cell failure [13, 14]. Multisystem involvement is common, including sensorineural deafness, cardiomyopathy, nephropathy, and macular dystrophy.
Recent EASD/ADA Precision Medicine in Diabetes Initiative (PMDI) recommendations highlight the potential cardio‐renal benefits of SGLT2i in monogenic diabetes but caution regarding euglycaemic DKA in insulin‐deficient patients [9]. Evidence remains limited to case report or small studies [11, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25]. Recently, short‐term use in HNF1A‐MODY, has nevertheless shown good efficacy and safety over 4 weeks [26]. Long‐term duration use remains unexplored and routine use is not currently recommended. However, SGLT2i may be particularly beneficial in HNF1B‐MODY and MIDD given their cardio‐renal effects and potential ability to decrease mitochondrial oxidative stress [2, 3]. Here, we report a nationwide French study assessing the real‐world outcomes of SGLT2i therapy in 39 adults with MODY (due to pathogenic variants in HNF1A, HNF4A, HNF1B, ABCC8, INS or RFX6) or MIDD recruited through a national rare disease network, representing to our knowledge, the largest reported cohort to date.
2. Research Design and Methods
2.1. Study Population
This retrospective multicenter cohort was conducted within the PRISIS (National Reference Center for Rare Diseases of Insulin Secretion and Insulin Sensitivity) network.
Patients were consecutively included within 2021 to 2025 if they had received SGLT2i therapy and met the following inclusion criteria: age ≥ 18 years and a genetic diagnosis of monogenic diabetes, defined by the presence of a pathogenic or likely pathogenic variant in a gene involved in insulin secretion. Exclusion criteria were: non‐pathogenic genetic variant or variant of uncertain significance or genetic variant not known to induce diabetes, and patients with GCK‐MODY. It should be noted that in France, reimbursement for SGLT2i was introduced in April 2020 for dapagliflozin and in March 2021 for empagliflozin. As a result, dapagliflozin initially held a monopoly and was more frequently prescribed in 2021.
Data were collected from Hospitals of Angers, Lille, Marseille, Montpellier, Nice, and Paris (Cochin‐Port Royal, Lariboisière‐Fernand‐Widal, Pitié‐Salpêtrière, and Saint‐Antoine Hospitals), France.
Data were collected retrospectively within 2 years prior to SGLT2 initiation (baseline data) and during follow‐up at 1 year (1Y: 6 to 18 months after SGLT2i initiation) and 2 years (2Y: 18 months to 30 months). Anthropometric, clinical including systolic and diastolic blood pressure (SBP and DBP), and biological data (HbA1c, creatinine, estimated glomerular filtration rate (eGFR) according to CKD epi estimation, urinary albumin‐to‐creatinine ratio (UACR)) were recorded along with diabetes duration, complications and treatments. Nephropathy and chronic kidney disease (CKD) were defined according to KDIGO criteria based on eGFR (G categories) and albuminuria (A categories). Nephropathy was defined as an eGFR < 60 mL/min/1.73 m2 (G ≥ 3) and/or albuminuria ≥ 3 mg/mmol (A ≥ 2) and CKD was defined as an eGFR < 60 mL/min/1.73 m2 (G ≥ 3) and/or severely increased albuminuria ≥ 30 mg/mmol (A ≥ 3).
The primary objective of this study was to assess the outcomes of glycemic parameters under treatment with SGLT2i in adults with MODY or MIDD.
Secondary objectives included assessing renal function (eGFR, UACR) and metabolic parameters (weight, blood pressure), and quantifying adverse and serious adverse events during SGLT2i therapy, as this population could be exposed to a high risk of euglycemic diabetic ketoacidosis and kidney failure.
2.2. Ethical Considerations
The patients were included in the French National Rare Disease Registry (French data protection agency CNIL # 2211418). The study followed the Helsinki Declaration and CIOMS guidelines. The use of this cohort has received ethical approval from the CPP (P050318 Comités de protection des personnes: 24 November 2006) from the CNIL (Commission nationale de l'informatique et des libertés, N°1222666).
2.3. Statistical Analysis
Longitudinal analyses were performed using complete‐case data for the variables included in each model. Repeated measurements were analysed using linear mixed‐effects models with a random intercept for participants to account for within‐subject correlation. Changes in antidiabetic treatments over time were primarily described as the proportion of treated patients at each time point. Antidiabetic treatment intensification was defined as an increase compared to baseline in the number of antidiabetic drugs and/or a ≥ 25% increase in insulin dosage.
For the main longitudinal analyses, adjusted mean changes from baseline (least‐square means, LS‐means) and their 95% confidence intervals (CIs) were estimated at each time point (Baseline, 1Y and 2Y) from models including time as a fixed effect and adjusted for the corresponding baseline value of the outcome, age at baseline, and sex. For HbA1c, UACR, and eGFR changes, additional adjustment for antidiabetic treatment intensification was performed. For UACR and eGFR changes, additional adjustment for diuretics and CE inhibitors/angiotensin II receptor blockers (ACEi/ARB) usage was performed. The overall effect of SGLT2i initiation (pre vs. post) was assessed using a binary pre/post indicator in mixed‐effects models, with p values derived from the pre/post term.
Subgroup analyses according to baseline HbA1c (< 8% vs. ≥ 8%) and baseline chronic kidney disease were conducted by adding a pre/post‐by‐subgroup interaction term to the mixed‐effects models.
Because the UACR is typically right‐skewed, UACR was analysed on the natural log scale. Changes in UACR were expressed as relative percentage changes corresponding to the geometric mean change, calculated as 100 × [exp(mean log‐change) − 1]. Confidence intervals were obtained by exponentiating the corresponding limits on the log scale.
The differences obtained with p‐values < 0.05 were considered significant.
All analyses and the formatting of the results in the form of graphs were carried out using R Studio software (version 1.2.1335).
3. Results
3.1. Baseline Characteristics
A total of 40 individuals with genetically confirmed monogenic diabetes were included. All variants were classified as pathogenic or probably pathogenic (Table S1). Baseline clinical characteristics are summarized in Table 1.
TABLE 1.
Clinical characteristics of patients at baseline.
| Variables | All (N = 40) | MIDD (N = 16) | HNF1B‐MODY (N = 9) | HNF1A‐ and HNF4A‐MODY (N = 11) | ABCC8‐, INS‐ and RFX6‐MODY (N = 4) |
|---|---|---|---|---|---|
| Age (years) | 48.6 (15.2) | 47.6 (11.3) | 55.2 (16.3) | 42.4 (17.9) | 54.4 (16.1) |
| Sex (F/M) | |||||
| F | 23 (57.5%) | 9 (56.2%) | 5 (55.6%) | 7 (63.6%) | 2 (50.0%) |
| HbA1c (%) | 7.7 (1.4) | 7.5 (0.9) | 7.9 (1.9) | 8.0 (1.5) | 7.5 (1.6) |
| Weight (kg) | 66.8 (13.6) | 60.9 (10.2) | 70.4 (17.3) | 68.5 (14.3) | 78.0 (3.3) |
| BMI (kg/m2) | 24.2 (4.2) | 22.6 (2.9) | 26.0 (6.2) | 24.3 (3.4) | 26.7 (3.6) |
| Numbers of antidiabetic drugs | |||||
| 1 | 12 (30.0%) | 7 (43.8%) | 2 (22.2%) | 3 (27.3%) | 0 (0.0%) |
| 2 | 19 (47.5%) | 5 (31.2%) | 4 (44.4%) | 7 (63.6%) | 3 (75.0%) |
| 3 | 6 (15.0%) | 3 (18.8%) | 2 (22.2%) | 0 (0.0%) | 1 (25.0%) |
| 4 | 2 (5.0%) | 1 (6.2%) | 0 (0.0%) | 1 (9.1%) | 0 (0.0%) |
| Biguanides | 19 (47.5%) | 6 (37.5%) | 5 (55.6%) | 6 (54.5%) | 2 (50.0%) |
| Sulfonylureas | 14 (35.0%) | 3 (18.8%) | 3 (33.3%) | 8 (63.6%) | 1 (25.0%) |
| Glinides | 5 (12.5%) | 2 (12.5%) | 0 (0.0%) | 2 (18.2%) | 1 (25.0%) |
| GLP‐1 receptor agonist | 6 (15.0%) | 3 (18.8%) | 1 (11.1%) | 1 (9.1%) | 1 (25.0%) |
| DPP4‐inhibitor | 10 (25.0%) | 6 (37.5%) | 2 (22.2%) | 2 (18.2%) | 0 (0.0%) |
| Alpha glucosidase inhibitor | 1 (2.5%) | 1 (6.2%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) |
| Basal insulin | 21 (52.5%) | 9 (56.2%) | 5 (55.6%) | 3 (27.3%) | 4 (100.0%) |
| Rapid insulin | 11 (27.5%) | 4 (25.0%) | 4 (44.4%) | 2 (18.2%) | 1 (25.0%) |
| Statin therapy | 19 (47.5%) | 6 (37.5%) | 6 (66.7%) | 5 (45.5%) | 2 (50.0%) |
| ACE inhibitor or ARB therapy | 17 (45.9%) | 7 (46.7%) | 4 (44.4%) | 4 (44.4%) | 2 (50.0%) |
| Diuretic therapy | 8 (20.0%) | 3 (18.8%) | 3 (33.3%) | 1 (9.1%) | 1 (25.0%) |
| Retinopathy | 4 (10.5%) | 1 (6.2%) | 0 (0.0%) | 2 (22.2%) | 1 (25.0%) |
| Peripheral neuropathy | 9 (23.1%) | 3 (18.8%) | 1 (11.1%) | 3 (30.0%) | 2 (50.0%) |
| Nephropathy (KDIGO A ≥ 2 or G ≥ 3) | 22 (55.0%) | 10 (62.5%) | 7 (77.8%) | 3 (27.3%) | 2 (50.0%) |
| Chronic kidney disease (KDIGO A ≥ 3 or G ≥ 3) | 16 (40.0%) | 8 (50.0%) | 5 (55.6%) | 2 (18.2%) | 1 (25.0%) |
| eGFR (ml/min/1.73 m2) | 83.6 (28.9) | 81.6 (26.8) | 61.7 (22.6) | 105.9 (26.2) | 92.6 (17.4) |
| UACR (mg/mmol) | 31.4 (52.4) | 51.3 (70.9) | 9.4 (11.0) | 26.0 (39.2) | 14.3 (18.4) |
| Hypertension | 21 (53.8%) | 8 (50.0%) | 6 (75.0%) | 4 (36.4%) | 3 (75.0%) |
| SBP (mmHg) | 126.8 (17.0) | 127.7 (16.1) | 129.4 (22.9) | 121.3 (14.5) | 132.5 (13.7) |
| DBP (mmHg) | 74.3 (10.8) | 80.7 (10.7) | 73.1 (4.7) | 71.5 (9.6) | 60.5 (9.3) |
| Cardiovascular disease | 5 (12.5%) | 2 (12.5%) | 2 (22.2%) | 1 (10.0%) | 0 (0.0%) |
| Heart failure | 4 (10.3%) | 2 (12.5%) | 2 (22.2%) | 0 (0.0%) | 0 (0.0%) |
| HFpEF | 1 (2.5%) | 1 (6.2%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) |
| HFrEF | 3 (7.5%) | 1 (6.2%) | 2 (22.2%) | 0 (0.0%) | 0 (0.0%) |
Note: Data are means ± SD for the quantitative variables and effective (%) for qualitative variables.
Abbreviations: A, albuminuria; ACE, angiotensin‐converting enzyme; ARB, angiotensin receptor blocker; BMI, body mass index; DBP, diastolic blood pressure; DPP4, dipeptidyl peptidase 4; eGFR, estimated glomerular filtration rate; F, female; G, GFR; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; KDIGO, kidney disease improving global outcome; M, male; SBP, systolic blood pressure; UACR, urinary albumin‐to‐creatinine ratio.
The mean age of patients was 48.6 ± 15.2 years, and 57.5% were women. The distribution of diabetes subtypes was as follows: MIDD, 40.0% of patients (n = 16); HNF1B‐MODY, 22.5% (n = 9); HNF1A‐ or HNF4A‐MODY, 27.5% (n = 11; respectively n = 7 and 4); and ABCC8‐, RFX6‐ or INS‐MODY, 10.0% (n = 4, respectively n = 2; 1 and 1). Mean HbA1c at baseline was 7.7% ± 1.4% (61 ± 15 mmol/mol). Before SGLT2i initiation, most patients were receiving insulin therapy (52.5%), approximately half of them were treated with sulfonylureas or glinides (47.5%), as well as metformin (47.5%), and 25.0% with DPP‐4 inhibitors. Finally, 15.0% were receiving GLP‐1 receptor agonists (Table 1). Mean BMI was 24.2 ± 4.2 kg/m2.
With respect to microvascular diabetes‐related complications at baseline, 10.5% of patients had diabetic retinopathy, none had maculopathy, 55.0% had nephropathy (KDIGO A ≥ 2 or G ≥ 3), and 23.1% had peripheral neuropathy.
Mean eGFR was 83.6 ± 28.9 mL/min/1.73 m2 and mean UACR was 31.4 ± 52.4 mg/mmol. Overall, 40.0% had CKD (KDIGO A ≥ 3 or G ≥ 3). Hypertension was present in 53.8% of patients, 12.5% had a history of cardiovascular disease, and 10.3% (n = 4) had heart failure with preserved or mildly reduced left ventricular ejection fraction (LVEF > 40%) in 2.5% (n = 1), and reduced LVEF (< 40%) in 7.5% (n = 3).
The nature and daily dose of SGLT2i therapy were Dapagliflozin 10 mg in 32 patients, Empagliflozin 10 mg in 7 patients and Empagliflozin 25 mg in 1 patient. The last follow‐up visit was at 23.9 ± 5.9 months after SGLT2i initiation. Mean delay since treatment initiation was—6.0 ± 7.8 months at baseline, 10.4 ± 3.1 months at 1 year (1Y), and 24.7 ± 4 months at 2 years (2Y) (Table 2).
TABLE 2.
Clinical characteristics at baseline and follow‐up for all patients.
| Variables | Baseline | n | 1Y | n | 2Y | n | p |
|---|---|---|---|---|---|---|---|
| Delay to SGLT2i introduction (months) | −6.0 (7.7) | 40 | 10.4 (3.1) | 38 | 24.7 (4.0) | 37 | — |
| Weight (kg) | 66.8 (13.6) | 35 | 65.4 (14.1) | 34 | 65.8 (13.1) | 35 | 0.008 |
| HbA1c (%) | 7.7 (1.4) | 39 | 7.6 (1.6) | 35 | 7.5 (1.1) | 33 | 0.72 |
| eGFR (ml/min/1.73 m2) | 83.6 (28.9) | 37 | 78.8 (31.1) | 33 | 71.4 (29.7) | 32 | < 0.001 |
| UACR (mg/mmol) | 31.4 (52.4) | 28 | 20.2 (36.6) | 28 | 12.8 (27.2) | 32 | 0.004 |
| SBP (mmHg) | 126.8 (17.0) | 38 | 123.2 (16.9) | 32 | 124.8 (14.0) | 32 | 0.205 |
| DBP (mmHg) | 74.3 (10.8) | 38 | 69.9 (9.3) | 32 | 72.4 (12.3) | 32 | 0.087 |
Note: Data are means ± (SD). Linear mixed‐effects models adjusted for baseline value, age and sex for all variables. For HbA1c, additional adjustment for antidiabetic treatment intensification was performed. For UACR and eGFR changes, additional adjustment for antidiabetic treatment intensification, diuretics and ACE inhibitors/angiotensin II receptor blockers (ACEi/ARB) usage was performed.
Abbreviations: BMI, body mass index; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; SBP, systolic blood pressure; UACR, urinary albumin‐to‐creatinine ratio.
3.2. Metabolic and Renal Effects of SGLT2 Inhibitor Therapy
Clinical and biological variables over time are summarized in Table 2. Considering all patients treated with SGLT2i, mean body weight significantly decreased from 66.8 ± 13.6 kg at baseline to 65.8 ± 13.1 kg at 2 years (p = 0.008) (Figure 1A and Table 2).
FIGURE 1.
Changes in metabolic and renal parameters after initiation of SGLT2 inhibitors. Adjusted mean changes from baseline (least‐square means, LS‐means) and 95% confidence intervals estimated at Baseline, 1 year (1Y), and 2 years (2Y) after initiation of SGLT2 inhibitors for body weight (A), HbA1c (B), estimated glomerular filtration rate eGFR (C), urinary albumin‐to‐creatinine ratio (UACR) (D), systolic blood pressure (SBP) (E), and diastolic blood pressure (DBP) (F). Estimates were derived from linear mixed‐effects models including time as a fixed effect and adjusted for the corresponding baseline value of the outcome, age at baseline, and sex, antidiabetic treatment intensification, with a random intercept for participant. For UACR and eGFR changes, additional adjustment for diuretics and CE inhibitors/angiotensin II receptor blockers (ACEi/ARB) usage. UACR was analysed on the natural log scale. Asterisks indicate the significance of the overall pre/post treatment effect derived from mixed‐effects models (*p < 0.05, **p < 0.01, ***p < 0.001).
Following initiation of SGLT2i therapy, HbA1c remained stable in the overall cohort, with no significant change from baseline throughout follow‐up (Figure 1B and Table 2). In contrast, patients with a baseline HbA1c ≥ 8% (64 mmol/mol) experienced a marked reduction in HbA1c, reaching 7.6% ± 0.7% at 2 years compared with 9.6% ± 1.3% at baseline (p = 0.0001 after adjustment for intensification of glucose‐lowering therapy) (Figure 2A). Glycemic responses also appeared to differ according to genotype. In patients with HNF1B‐MODY, HbA1c initially increased during the first year (+0.7% ± 2.5%) before returning to values comparable to baseline at 2 years (7.9% ± 1.7% vs. 7.9% ± 1.9% at baseline; Table S2). By contrast, patients with HNF1A‐ or HNF4A‐MODY, despite having a similar baseline HbA1c (8.0% ± 1.5%) as HNF1B‐MODY, showed a substantial improvement after 1 year (−0.7% ± 1.3%; Table S2).
FIGURE 2.
Changes in HbA1c according to baseline HbA1c and evolution of antidiabetic treatments after initiation of SGLT2 inhibitors. (A) Adjusted mean changes from baseline in HbA1c (least‐square means, LS‐means) and 95% confidence intervals estimated at baseline, 1 year (1Y), and 2 years (2Y) according to baseline HbA1c (< 8% vs. ≥ 8%). Estimates were derived from linear mixed‐effects models including time, baseline HbA1c group, and their interaction, and adjusted for age at baseline, sex, antidiabetic treatment intensification, with a random intercept for participant. The p value corresponds to the time‐by‐baseline HbA1c interaction. (B) Proportion of patients treated with antidiabetic medications at baseline, 1 year (1Y), and 2 years (2Y) after initiation of SGLT2 inhibitors. Mean time since treatment initiation was −6.0 ± 7.7 months at baseline, 10.4 ± 3.1 months at 1 year (1Y), and 24.7 ± 4.0 months at 2 years (2Y). SU, sulfonylureas; DPP‐4i, dipeptidyl peptidase‐4 inhibitors; GLP‐1RA, glucagon‐like peptide‐1 receptor agonists; a‐Gl, alpha‐glucosidase inhibitors.
The proportion of patients receiving insulin, sulfonylureas, biguanides and incretin‐based therapies over time is shown in Figure 2B. Overall treatment patterns remained relatively stable over 1 year. At 2 years, insulin and GLP1‐RA treatment slightly increased (n = 21/37 (57%) patients vs. n = 21/40 (52%) at baseline and n = 7/37 (19%) patients vs. n = 6/40 (15%) at baseline respectively) whereas biguanide and sulfonylureas use decreased (n = 13/37 (35%) patients vs. n = 19/40 (47.5%) at baseline; n = 9/37 (24.3%) patients vs. n = 14/40 (35%) at baseline respectively) (Figure 2B).
Mean eGFR declined significantly during follow‐up (Table 2), the means change was −6.3 ± 9.2 mL/min/1.73 m2 from baseline to 1 year and −4.4 ± 9.5 mL/min/1.73 m2 from baseline to 2 years (Figure 1C and Table 2). Decline of eGFR was not significantly different at 2 years for patients with a history of CKD at baseline (−5.9 ± 2.1 mL/min/1.73 m2 vs. −2.8 ± 2.0 mL/min/1.73 m2 without history of CKD, p = 0.41) (Figure 3A).
FIGURE 3.
Changes in kidney outcomes according to baseline chronic kidney disease after initiation of SGLT2 inhibitors. Adjusted mean changes from baseline (least‐square means, LS‐means) and 95% confidence intervals estimated at baseline, 1 year (1Y), and 2 years (2Y) after initiation of SGLT2 inhibitors for estimated glomerular filtration rate (eGFR) (A) and urinary albumin‐to‐creatinine ratio (UACR) (B), according to the presence of chronic kidney disease at baseline. Estimates were derived from linear mixed‐effects models including time, baseline CKD status (KDIGO A ≥ 3 or G ≥ 3) and their interaction, and adjusted for age at baseline and sex, antidiabetic treatment intensification and diuretics and CE inhibitors/angiotensin II receptor blockers (ACEi/ARB) usage with a random intercept for participant. UACR was analysed on the natural log scale. Interaction p‐values correspond to the time‐by‐baseline chronic kidney disease interaction term.
Mean UACR decreased significantly in the overall cohort (Figure 1D, Table 2). Compared with baseline, the geometric mean ratio of UACR decreased by −35.6% (95% CI, −53.6 to −10.0) at 1 year and by −43.5% (95% CI, −64.8 to −9.3) at 2 years (overall p = 0.004) (Figure 1D). Patients with CKD at baseline tended to experience greater reductions in UACR than those without CKD, with decreases of −41.7% (95% CI, −62.1 to −10.4) and −57.8% (95% CI, −73.0 to −34.1) at 1 and 2 years, respectively, compared with −31.1% (95% CI, −55.8 to 7.4) and −28.8% (95% CI, −52.9 to 7.6) in patients without CKD; however, the interaction did not reach significance (p = 0.23) (Figure 3B).
When patients with genotypes commonly associated with renal disease (MIDD and HNF1B‐MODY) were pooled (Table S3), baseline eGFR was lower than in the remaining genotypes (74.5 ± 26.8 vs. 102.6 ± 24.3 mL/min/1.73 m2), whereas the decline in eGFR over 2 years was comparable between groups (−4.65 ± 10.08 vs. −3.70 ± 8.24 mL/min/1.73 m2; interaction p = 0.80). Baseline UACR was also higher in the MIDD/HNF1B group (35.3 ± 59.1 vs. 22.1 ± 32.8 mg/mmol), with a non‐significant trend toward a greater reduction after 2 years (−50.2% [95% CI, −75.4 to 1.0] vs. −27.3% [95% CI, −51.8 to 9.8]; interaction p = 0.34). Among individual genotypes, patients with MIDD had the highest baseline UACR (51.3 ± 70.9 mg/mmol; Table 1) and showed the largest apparent reduction over follow‐up (−63.5% [95% CI, −88.9 to 19.9] at 2 years) compared with the other genotypes. Because of the limited number of patients in each genotype subgroup, no formal statistical comparisons were performed, and these findings should be considered exploratory.
Systolic and diastolic blood pressure remained overall stable over time, without significant mean changes from baseline vs. at 1 and 2 years (Figure 1E,F and Table 2).
Regarding ophthalmological outcomes, no incident case of diabetic retinopathy was observed. One case of maculopathy was reported in a patient with MIDD 18 months after initiation of SGLT2i therapy, occurring in the absence of significant change in HbA1c (−0.1%).
No episode of acute heart failure or ischemic events occurred during follow‐up. Two patients with HNF1B‐MODY and heart failure with reduced ejection fraction showed improvement in left ventricular ejection fraction to > 40% after initiation of SGLT2i therapy.
Detailed subgroup analyses are provided in Table S2.
3.3. Adverse Events
Adverse events are summarized in Table S4. Overall, 6 patients (15%) experienced at least one non‐serious adverse event. These included two genital infections, one urinary tract infection, one ketosis, and two other minor events (polyuria). No serious adverse events were reported; notably, there were no cases of diabetic ketoacidosis, acute kidney injury, or death.
Treatment discontinuation occurred in 3 patients (7.5%): one due to nausea with ketosis (0.6 mmol/L) after 3 months of SGLT2i therapy, one due to impaired kidney function with a 27 μmol/L increase of creatinine (from 159 μmol/L to 186 μmol/L) and reduced eGFR (from 40.40 mL/min/1.73 m2 at baseline to 32.7 mL/min/1.73 m2) after 11 months of SGLT2i therapy, and one due to genital infection.
4. Discussion
This real‐world retrospective multicenter study provides novel insights into the use of SGLT2i in monogenic diabetes. Taking advantage of our national rare disease network PRISIS, we report longitudinal metabolic and renal outcomes of SGLT2i therapy in 40 patients with monogenic diabetes over a 2‐year follow‐up. Overall HbA1c remained stable after SGLT2i initiation but decreased significantly in patients with baseline HbA1c ≥ 8% (64 mmol/mol). Antidiabetic treatments remained stable over 1 year, while insulin, GLP1‐RA treatment use slightly increased and biguanide, sulfonylureas use decreased at 2 years. Renal benefits were observed with a significant reduction in UACR, with a trend to be more pronounced in patients with CKD at baseline. Overall, eGFR declined significantly over time. Treatment was generally well tolerated, with no serious adverse events reported, including ketoacidosis or death. However, one episode of ketosis and one case of progressive increased serum creatinine (+27 μmol/L, eGFR at baseline 40.4 mL/min/1.73 m2) resulted in treatment discontinuation. This represents, to our knowledge, the largest series evaluating SGLT2i use and safety in patients with monogenic diabetes.
In the entire cohort, HbA1c remained stable over 2 years, with a modest mean reduction (−0.1% ± 1.6% at 1 year and −0.2% ± 1.7% at 2 years) lower than that observed in individuals with type 2 diabetes, in whom mean HbA1c reductions range from −0.5% to −0.9% [27, 28, 29]. Importantly, individuals with HbA1c ≥ 8% (64 mmol/mol) experienced greater improvement than those already below this threshold. This pattern is consistent with data from other forms of diabetes, in which baseline glycemic control is a major determinant of treatment response magnitude [30]. Individuals with HNF1A‐ or HNF4A‐MODY exhibited consistent glycemic improvement at 1 year (−0.7% ± 1.3%), which was sustained at 2 years (initial HbA1c was 7.9% ± 1.9% (63 ± 16 mmol/mol)). These findings are consistent with the MOD3ST trial [26] a randomized cross‐over study including 18 individuals with HNF1A‐MODY. In this study, 4 weeks of SGLT2 inhibition as an adjunct glucose‐lowering therapy significantly improved glycemic control compared with placebo, without increasing the risk of adverse events. Together, these data suggest that reduced SLC5A2 expression in HNF1A‐MODY does not compromise the glycemic efficacy of SGLT2 inhibition. Notably, the same team showed that the renal glucose threshold in HNF1A‐MODY, assessed with and without 25 mg empagliflozin, was comparable to that observed in T2D under hyperglycemic clamp conditions [31]. Overall, our findings suggest that SGLT2i therapy induces a sustained glycemic efficacy over the long term (up to 2 years) in individuals with HNF1A‐MODY.
Regarding concomitant therapies, while treatment remained unchanged at 1 year, there was a decrease in sulfonylurea and biguanide use and a slight increase in insulin and GLP‐1 RA therapy at 2 years, concomitantly with a decline in renal function (71.4 ± 29.7 mL/min/1.73 m2 vs. 83.6 ± 28.9 mL/min/1.73 m2 at baseline). Treatment modifications were primarily driven by declining kidney function or worsening glycemic control (HbA1c ≥ 8%), leading to the replacement of biguanides and sulfonylureas with insulin therapy (data not shown). It should be noted that gliquidone, the short acting sulfonylurea approved for use in advanced renal failure, is not available in France. Consequently, sulfonylurea therapy could not be continued as kidney function deteriorated. The escalation in insulin use over the 2‐year period may have attenuated the apparent effects of SGLT2 inhibitors on HbA1c.
Renal outcomes are of particular interest, as more than 40% of participants met KDIGO criteria for CKD at baseline. UACR decreased significantly over time in the overall cohort, with a 43.5% reduction in the geometric mean ratio from baseline at 2 years (95% CI, −64.8 to −9.3). Exploratory subgroup analyses suggested a trend to larger reduction in patients with CKD at baseline (−57.8%; 95% CI, −73.0 to −34.1; interaction p = 0.23) and in those with genotypes commonly associated with kidney disease (MIDD or HNF1B‐MODY) (−50.2%; 95% CI, −75.4 to 1.0; interaction p = 0.34), although these interactions were not statistically significant. In individuals with T2D, treatment with SGLT2i is associated with an approximately 25 to 30% reduction in geometric mean ratio of UACR change from baseline after short term treatment, greater in case of macroalbuminuria [32, 33]. A potential explanation for the more pronounced renal benefit observed in individuals with MIDD might be because they presented the highest mean UACR (51.3 ± 70.9 mg/mmol) at baseline. Part of the beneficial effect could also involve direct mitochondrial effects of SGLT2i. Indeed, beyond its established renal effects, SGLT2 inhibition has been shown in preclinical models to enhance mitochondrial function, activate AMPK, promote fatty acid oxidation and reduce reactive oxygen species production [2, 3, 34]. MIDD is characterized by impaired oxidative phosphorylation and increased oxidative stress, particularly deleterious in energy‐demanding organs such as the kidney [14]. SGLT2i may mitigate mitochondrial stress and provide additional renoprotection in MIDD, even if their effect has to be balanced with the energy loss related to glycosuria. These mechanistic hypotheses warrant further experimental and clinical investigation.
In contrast, eGFR declined during follow‐up mostly the first year (−6.3 ± 9.2 mL/min/1.73 m2 at 1 year and −4.4 ± 9.5 mL/min/1.73 m2 at 2 years), with a magnitude exceeding that generally reported in individuals with T2D. In the DAPA‐CKD trial, the annual rate of eGFR decline in individuals with T2D and chronic kidney disease receiving dapagliflozin was −2.86 ± 0.11 mL/min/1.73 m2 per year over 30 months [35]. In Empakidney, the total decline of eGFR was −2.16 ± 0.08 mL/min/1.73 m2 including the substantial attenuation of the annual eGFR decline from 2 months to the time of the final follow‐up visit (−1.37 mL/min per year) [36]. In our study, the decline was consistent across renal risk strata (CKD at baseline or not). Importantly, no acute deterioration signal was observed, and no case of acute kidney injury was reported. However, treatment was stopped in one case because of impaired eGFR from 40.40 mL/min/1.73 m2 at baseline to 32.7 mL/min/1.73 m2 at 1 year.
The reduction in eGFR may reflect progression of the underlying genetic disease, particularly in MIDD and HNF1B‐MODY, both associated with intrinsic renal involvement. Indeed, HNF1B‐MODY typically shows progressive renal decline due to tubulointerstitial damage. In a cohort of 17 individuals with HNF1B‐MODY without end‐stage kidney disease, the annual eGFR decline was −2.45 mL/min per year, with marked interindividual variability ranging from stable renal function to −19 mL/min/1.73 m2 [37]. Similarly, MIDD can lead to glomerular or tubulointerstitial disease independent of glycemic control. The annual rate of eGFR decline has been estimated at approximately 5.4 mL/min/1.73 m2 in previous reports [38, 39]. Thus, the decline in renal function observed at 1 year in individuals with MIDD (−7.3 ± 10.6 mL/min/1.73 m2) and HNF1B‐MODY (−6.0 ± 10.5 mL/min/1.73 m2) is consistent with the expected natural history of these conditions. However, at 2 years, the rate of eGFR decline appeared attenuated compared with the first year, suggesting a potential renoprotective effect of SGLT2i in line with the concomitant significant reduction in UACR.
SGLT2i therapy was generally well tolerated, with only 15% of participants experiencing non‐serious adverse events however leading to treatment discontinuation in 7.5% of participants. Overall, the safety profile appears acceptable in this genetically heterogeneous and partially CKD‐affected population.
We anticipated a risk of euglycemic ketoacidosis with SGLT2i in monogenic diabetes due to impaired insulin secretion, as reported in type 1 diabetes [4]. Residual insulin secretion was not systematically assessed, and long diabetes duration (15.2 ± 11.4 years) with 27.5% on basal–bolus insulin suggests possible insulin deficiency. To date, only one case of ketosis decompensation without acidosis has been reported under SGLT2i therapy in HNF1A‐MODY, occurring in the context of a strict ketogenic diet [19]. Although no serious adverse events were observed here, one patient experienced treatment discontinuation for ketosis, suggesting caution and ketosis surveillance in this population. Larger studies with longer follow‐up are needed to confirm safety in this specific population with monogenic diabetes.
We chose to exclude patients with GCK‐MODY because they typically present with mild, stable hyperglycemia (usually HbA1c < 7.6%), for which glucose‐lowering therapies have little effect on glycemic control. However, a recent retrospective study combining published data and the Peking University cohort (total of 912 patients) reported that approximately 12% of patients had an HbA1c > 7%, and these patients were generally older and had a higher BMI [40]. Whether SGLT2i could provide glycemic or cardiorenal benefits in this subgroup remains unknown and warrants further investigation.
The strengths of this study include the large number of individuals with monogenic diabetes treated with SGLT2i, its nationwide design, the genetically‐confirmed diagnoses, and the follow‐up over 2 years.
Several limitations warrant consideration. First, although the overall sample size—and particularly the size of each genetic subgroup—represents the largest series reported in the literature to date, it remained modest, limiting statistical power and precluding definitive inter‐genotype comparisons. Second, attrition reduced the number of evaluable participants at 2 years. Third, the absence of a control group and the retrospective design limit causal inference regarding observed changes. Also, renal trajectories may reflect the natural history of the underlying genetic condition rather than treatment effects alone. Fourth, patients were likely selected by prescribing physicians, probably based on profiles considered to have potential benefit from cardio‐renal protection; therefore, the findings may not be generalizable to other populations. Finally, safety interpretation is constrained by the absence of C‐peptide data. Despite these limitations, these findings provide valuable real‐world insights.
In conclusion, SGLT2i improved glycemic control when HbA1c ≥ 8% (64 mmol/mol) at initiation, and reduced UACR in monogenic diabetes, with a modest eGFR decline likely reflecting underlying renal disease. Our findings also raise the possibility of genotype‐specific responses, with a potentially greater glycemic effect in HNF1A/HNF4A‐MODY and a greater reduction in UACR in MIDD. However, these observations are exploratory and should be interpreted cautiously, as the small sample size and baseline clinical heterogeneity precluded adequately powered subgroup analyses. Prospective studies specifically designed to compare genotypes are required to confirm these findings. Adverse events were rare and non‐severe under close monitoring. However, due to the non‐randomized design and the lack of assessment of insulin secretion in our study, close monitoring of ketone and ketogenic diet avoiding should be recommended following the prescription of SGLT2i in patients with monogenic diabetes. These results suggest SGLT2i as a valuable add‐on therapy, under strict surveillance, potentially expanding treatment options in individuals with monogenic diabetes (with the exception of GCK‐MODY), which lies outside standard algorithms but carries similar long‐term complication risks as type 1 or type 2 diabetes. Our findings in the largest real‐world dataset to date suggest that SGLT2i therapy should be considered in patients with monogenic diabetes. These preliminary findings need to be confirmed by larger prospective controlled genotype‐stratified studies.
Author Contributions
E.A., M.C.V., H.D., T.V.‐T., N.C., D.D.‐L., S.L., C.V., O.V., R.V., C.B., O.V., C.B.‐C., C.C. and C.A. collected the data in an electronic record and wrote the results. C.A., C.C. and C.Vi. designed the study, C.A. and P.B.L. analysed the data, E.A., C.C. and C.A. contributed to the writing of the results, reviewed and edited the manuscript. All authors approved the final version of the manuscript. C.C. and C.A. are the guarantors of this work; as such, they have full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Funding
The authors have nothing to report.
Conflicts of Interest
C.A. did expert advisory for Sanofi, Dexcom and received lecture fees from Eli Lilly, Abbott and Sanofi. C.Vi. served as a speaker to Amryt Pharmaceuticals, Sanofi, Ipsen and Lilly. M.C.V. served as a speaker for Chiesi and Ascendis. The other authors declare no conflicts of interest.
Supporting information
Table S1: Nomenclature and pathogenicity of variants.
Table S2: Summary descriptives table by subgroups of monogenic diabetes.
Table S3: Summary descriptives table of patients with MIDD or HNF1B‐MODY and the patients with HNF1A‐HNF4A‐ABCC8‐RFX6‐INS‐MODY.
Table S4: Side effects.
Acknowledgements
We are grateful to our patients who participate in our PRISIS cohort and give permission to use their data in research studies. Open access publication funding provided by COUPERIN CY26.
Audrain E., Bel Lassen P., Bellanné‐Chantelot C., et al., “Glycemic and Renal Effects of SGLT2 Inhibitors in Monogenic Diabetes: A Real‐World National Study,” Diabetes, Obesity and Metabolism 28, no. 10 (2026): 9633–9643, 10.1111/dom.71169.
Handling Editor: Richard Donnelly
Data Availability Statement
The datasets analysed in the current study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S1: Nomenclature and pathogenicity of variants.
Table S2: Summary descriptives table by subgroups of monogenic diabetes.
Table S3: Summary descriptives table of patients with MIDD or HNF1B‐MODY and the patients with HNF1A‐HNF4A‐ABCC8‐RFX6‐INS‐MODY.
Table S4: Side effects.
Data Availability Statement
The datasets analysed in the current study are available from the corresponding author upon reasonable request.