Diabetes related genetics and outcomes after total pancreatectomy with islet autotransplantation.

CONTEXT: Approximately 20% of patients with chronic pancreatitis achieve insulin independence one year after total pancreatectomy with islet autotransplantation (TPIAT), an outcome associated with younger age and lower pre-transplant HbA1c. The contribution of diabetes-related genetics to TPIAT outcomes is unknown. Genetic risk scores (GRS) are associated with C-peptide levels in type 1 (T1D) and type 2 (T2D) diabetes.

OBJECTIVE

To evaluate whether T1D and T2D GRS and partitioned metabolic polygenic scores (PGS) are associated with diabetes before TPIAT and metabolic outcomes one year after transplant.

METHODS

We genotyped 318 patients with chronic pancreatitis undergoing TPIAT in the multicenter "Advancing Treatment for Pancreatitis: A Prospective Observational Study of TPIAT" using a global screening array. Regression models assessed associations of T1D- and T2D-GRS and metabolic PGS with diabetes outcomes one year after TPIAT.

RESULTS

Participants were 29±17 years old, 61% female, 84% non-Hispanic White, and 13% had diabetes prior to transplant. T2D-GRS was higher among those with pre-TPIAT diabetes (-0.6±0.3 versus -0.8±0.2, p=0.003) and was associated with higher pre-transplant HbA1c (β=0.19 % per 1-SD [95% CI:0.04, 0.33], p = 0.011). Adjusted for genotype-derived ancestry and islet equivalents/kg, the beta-cell PGS was associated with higher insulin dose (β=0.05 units/kg/day per 1-SD, [95%CI:0.01, 0.09], p=0.016) and higher insulin dose adjusted A1c (IDAA1c) (β=0.34[95%CI:0.03, 0.67], p=0.029) 1-year post-transplant. The lipodystrophy PGS was associated with higher IDAA1c (β=0.38 [95%CI:0.06, 0.69], p=0.019) and lower fasting C-peptide (β=-0.09 [95%CI:-0.18, 0], p=0.041) at 1 year.

CONCLUSIONS

T2D genetic risk is associated with diabetes prior to TPIAT, and beta cell and lipodystrophy PGS are associated with post-TPIAT diabetes outcomes. Diabetes-related genetics may influence transplantation outcomes and inform metabolic heterogeneity.