Associations between diabetes-related genetic risk scores and residual beta cell function in type 1 diabetes: the GUTDM1 study.

AIMS/HYPOTHESIS: Use of genetic risk scores (GRS) may help to distinguish between type 1 diabetes and type 2 diabetes, but less is known about whether GRS are associated with disease severity or progression after diagnosis. Therefore, we tested whether GRS are associated with residual beta cell function and glycaemic control in individuals with type 1 diabetes. METHODS: Immunochip arrays and TOPMed were used to genotype a cross-sectional cohort (n=479, age 41.7 ± 14.9 years, duration of diabetes 16.0 years [IQR 6.0-29.0], HbA1c 55.6 ± 12.2 mmol/mol). Several GRS, which were originally developed to assess genetic risk of type 1 diabetes (GRS-1, GRS-2) and type 2 diabetes (GRS-T2D), were calculated. GRS-C1 and GRS-C2 were based on SNPs that have previously been shown to be associated with residual beta cell function. Regression models were used to investigate the association between GRS and residual beta cell function, assessed using the urinary C-peptide/creatinine ratio, and the association between GRS and continuous glucose monitor metrics. RESULTS: Higher GRS-1 and higher GRS-2 both showed a significant association with undetectable UCPCR (OR 0.78; 95% CI 0.69, 0.89 and OR 0.84: 95% CI 0.75, 0.93, respectively), which were attenuated after correction for sex and age of onset (GRS-2) and disease duration (GRS-1). Higher GRS-C2 was associated with detectable urinary C-peptide/creatinine ratio (≥0.01 nmol/mmol) after correction for sex and age of onset (OR 6.95; 95% CI 1.19, 40.75). A higher GRS-T2D was associated with less time below range (TBR) (OR for TBR<4% 1.41; 95% CI 1.01 to 1.96) and lower glucose coefficient of variance (ß -1.53; 95% CI -2.76, -0.29). CONCLUSIONS/INTERPRETATION: Diabetes-related GRS are associated with residual beta cell function in individuals with type 1 diabetes. These findings suggest some genetic contribution to preservation of beta cell function.

Prevalence and predictive features of metabolic dysfunction-associated steatotic liver disease in type 1 diabetes.

AIMS/HYPOTHESIS: The prevalence and severity of metabolic dysfunction-associated steatotic liver disease (MASLD) in type 1 diabetes remain unclear. Therefore, we investigated the prevalence and severity of MASLD in type 1 diabetes and assessed which clinical features are most important in predicting MASLD severity. METHODS: A total of 453 individuals with type 1 diabetes (41.6 ± 15.0 years, 64% female, body mass index [BMI] 25.4 ± 4.2 kg/m2, and HbA1c 55.6 ± 12 mmol/mol) underwent vibration-controlled transient elastography (VCTE), with a controlled attenuation parameter (CAP) score for steatosis (≥280.0 dB/m) and a liver stiffness measurement (LMS) for fibrosis (≥8.0 kPa). A machine learning Extra-Trees classification model was performed to assess the predictive power of the clinical features associated with type 1 diabetes with respect to steatosis and fibrosis. RESULTS: The prevalence of hepatic steatosis and fibrosis was 9.5% (95% CI, 6.8-12.2) and 3.5% (95% CI, 1.8-5.2). Higher LMS was associated with a longer duration of type 1 diabetes (median 30.5 [IQR 18.0-39.3] years vs 15.0 [IQR 6.0-27.0] years), and individuals were older, had a higher BMI (mean 27.8 ± 5.2 vs 25.3 ± 4.1 kg/m2), and a higher CAP score (mean 211.4 ± 51.7 dB/m vs 241.4 ± 75.6 dB/m). The most important predictive features of fibrosis were duration of type 1 diabetes, age, and systolic blood pressure, with a mean ± SD area under the curve of 0.73 ± 0.03. CONCLUSION: Individuals with type 1 diabetes and high blood pressure, older age, higher BMI, and longer duration of disease could be considered at high-risk for developing MASLD.

Residual ß-Cell Function Is Associated With Longer Time in Range in Individuals With Type 1 Diabetes.

OBJECTIVE: Little is known about the influence of residual islet function on glycemic control in type 1 diabetes (T1D). We investigated the associations between residual ß-cell function and metrics of continuous glucose monitoring (CGM) in individuals with T1D. RESEARCH DESIGN AND METHODS: In this cross-sectional cohort comprising 489 individuals (64% female, age 41.0 ± 14.0 years), T1D duration was 15.0 (interquartile range [IQR] 6.0-29.0) years. Individuals had a time in range (TIR) of 66% (IQR 52-80%) and a urinary C-peptide-to-creatinine ratio (UCPCR) of 0.01 (IQR 0.00-0.41) nmol/mmol. To assess ß-cell function, we measured UCPCR (detectable >0.01 nmol/mmol), and to assess α-cell function, fasting plasma glucagon/glucose ratios were measured. CGM was used to record TIR (3.9-10 mmol/L), time below range (TBR) (<3.9 mmol/L), time above range (TAR) (>10 mmol/L), and glucose coefficient of variance (CV). For CGM, 74.7% used FreeStyle Libre 2, 13.8% Medtronic Guardian, and 11.5% Dexcom G6 as their device. RESULTS: The percentage of patients with T1D who had a detectable UCPCR was 49.4%. A higher UCPCR correlated with higher TIR (r = 0.330, P < 0.05), lower TBR (r = -0.237, P < 0.05), lower TAR (r = -0.302, P < 0.05), and lower glucose CV (r = -0.356, P < 0.05). A higher UCPCR correlated negatively with HbA1c levels (r = -0.183, P < 0.05) and total daily insulin dose (r = -0.183, P < 0.05). Glucagon/glucose ratios correlated with longer TIR (r = 0.234, P < 0.05). CONCLUSIONS: Significantly longer TIR, shorter TBR and TAR, and lower CV were observed in individuals with greater UCPCR-assessed ß-cell function. Therefore, better CGM-derived metrics in individuals with preserved ß-cell function may be a contributor to a lower risk of developing long-term complications.