ABSTRACT Background First‐degree relatives (FDRs) of individuals with type 1 diabetes (T1D) carry a significantly elevated risk of developing autoimmune diseases, including celiac disease (CD) and autoimmune thyroid disease (AITD). The DiaUnion 1.0 study aimed to characterize one‐time autoantibodies, genetic risk profiles and long‐term progression to T1D, CD or AITD in siblings of children newly diagnosed with T1D. Methods Between 1997 and 2010, 1427 Danish siblings provided plasma and DNA samples to the DanDiabKids biobank. Autoantibodies associated with T1D (GADA, IAA, IA2A, ZnT8A), CD (tTGA) and AITD (TPOA) were measured using ADAP technology and confirmed by radiobinding assays. Genotyping was performed to compute a T1D Genetic Risk Score (GRS). National registry data were used to track disease incidence up to year 2024. Results Out of 1417 screened samples, 7.8% were positive for islet autoantibodies (IAab), and 4.6% had multiple IAab. Disease incidence rate increased substantially with IAab positivity: 0.11 per 100 person‐years in IAab‐negative siblings, 2.46 in single‐IAab positive and 8.10 in those with multiple IAab. Similarly, 1.97 per 100 person‐years of tTGA‐positive siblings developed CD, and 0.69 per 100 person‐years of TPOA‐positive individuals developed AITD. Higher GRS and HLA DR3/DR4 haplotypes were associated with autoantibody positivity (p < 0.0001). Conclusions A single screening for T1D, CD and AITD autoantibodies combined with genetic risk scoring stratified long‐term risk of clinically diagnosed autoimmune disease. These findings support further evaluation of targeted screening and follow‐up strategies in FDRs to enable surveillance and potential early intervention before clinical onset.
J. Christensen, G. Petersen, Simranjeet Kaur et al.· Diabetes, obesity and metabo...· 0 citations
BACKGROUND
Distal symmetrical polyneuropathy (DSPN) is a common complication of type 1 diabetes (T1D), yet validated biomarkers for early detection or prognosis are lacking. Metabolic disturbances driven by chronic hyperglycemia and dyslipidemia contribute to DSPN development and progression.
METHODS
We used untargeted serum liquid chromatography-mass spectrometry lipidomics to identify DSPN biomarkers. The discovery cohort included 153 individuals with T1D (109 with and 44 without DSPN) and 50 non-diabetic controls. The independent validation cohort included 99 individuals with T1D with established DSPN status. Key lipids were identified using multivariate modelling, followed by ANCOVA and adjusted post hoc tests.
RESULTS
A total of 543 lipid species were identified in the discovery cohort. Among these, 14 lipids were associated with DSPN. Of which, 6 lipids, namely Cer(d42:1), PC(36:4), LPC(16:0), LPE(18:1), PE(36:2), and PE(O-40:5) or PE(P-40:4), showed a clear pattern among non-diabetic individuals, people affected by T1D with and without DSPN. In the validation cohort, 3 of the 6 initially identified lipids showed the same directional changes as in the discovery cohort. A logistic regression model combining the six lipid biomarkers with HbA1c, diastolic blood pressure, and age achieved AUCs of 0.83 (95% CI, 0.76-0.91) in the discovery cohort and 0.81 (95% CI, 0.73-0.90) in the validation cohort for detecting DSPN in T1D. AUC improvement was not significant by DeLong's test in either cohort (p = 0.086 and 0.089) but was significant when combined using Fisher's method (χ2 = 9.7, p = 0.045). Additionally, 22 lipid species differed significantly between painful and painless DSPN.
CONCLUSIONS
We identified a reproducible lipidomic signature discriminating DSPN in type 1 diabetes. Painful DSPN was characterized by reduced unsaturated PC/PE and increased sphingolipids, offering new insight into disease pathophysiology.
T. Muk, T. Okdahl, M. Kokla et al.· Diabetes, obesity and metabo...· 0 citations
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