Evaluation of type 1 diabetes mellitus as a risk factor of Parkinson's disease in a Drosophila model

Tear Proteomics in Children and Adolescents with Type 1 Diabetes: A Promising Approach to Biomarker Identification of Diabetes Pathogenesis and Complications

The aim of the current study was to investigate the tear proteome in children and adolescents with type 1 diabetes (T1D) compared to healthy controls, and to identify differences in the tear proteome of children with T1D depending on different characteristics of the disease. Fifty-six children with T1D at least one year after diagnosis, aged 6-17 years old, and fifty-six healthy age- and sex-matched controls were enrolled in this cross-sectional study. The proteomic analysis was based on liquid chromatography tandem mass spectrometry (LC-MS/MS) enabling the identification and quantification of the protein content via Data-Independent Acquisition by Neural Networks (DIA-NN). Data are available via ProteomeXchange with the identifier PXD052994. In total, 3302 proteins were identified from tear samples. Two hundred thirty-nine tear proteins were differentially expressed in children with T1D compared to healthy controls. Most of them were involved in the immune response, tissue homeostasis and inflammation. The presence of diabetic ketoacidosis at diagnosis and the level of glycemic control of children with T1D influenced the tear proteome. Tear proteomics analysis revealed a different proteome pattern in children with T1D compared to healthy controls offering insights on deregulated biological processes underlying the pathogenesis of T1D. Differences within the T1D group could unravel biomarkers for early detection of long-term complications of T1D.

Increased incidence of neurodegenerative diseases in Finnish individuals with type 1 diabetes

INTRODUCTION

Diabetes is linked to neurodegenerative diseases (NDs), but data in type 1 diabetes are scarce. Our aim was to assess the standardized incidence ratios (SIRs) of different NDs in type 1 diabetes, and to evaluate the impact of diabetic vascular complications and age at diabetes onset.

RESEARCH DESIGN AND METHODS

In this observational cohort study, we included 4261 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy study, and 11 653 matched population-based controls without diabetes. NDs were identified from registers until the end of 2017. Diabetic complications were assessed at the baseline study visit. SIRs were calculated from diabetes onset, except for impact of complications that was calculated from baseline study visit.

RESULTS

The SIRs for NDs were increased in type 1 diabetes: any dementia 2.24 (95% CI 1.79 to 2.77), Alzheimer's disease 2.13 (95% CI 1.55 to 2.87), vascular dementia 3.40 (95% CI 2.08 to 5.6), other dementias 1.70 (95% CI 1.22 to 2.31), and Parkinson's disease 1.61 (95% CI 1.04 to 2.37). SIR showed a twofold increased incidence already in those without albuminuria (1.99 (1.44-2.68)), but further increased in presence of diabetic complications: kidney disease increased SIR for Alzheimer's disease, while cardiovascular disease increased SIR for both Alzheimer's disease and other dementias. Diabetes onset <15 years, compared with ≥15 years, increased SIR of Alzheimer's disease, 3.89 (2.21-6.35) vs 1.73 (1.16-2.48), p<0.05, but not the other dementias.

CONCLUSIONS

ND incidence is increased 1.7-3.4-fold in type 1 diabetes. The presence of diabetic kidney disease and cardiovascular disease further increased the incidence of dementia.

Association between Type 1 Diabetes Mellitus and Parkinson's Disease: A Mendelian Randomization Study

While much evidence suggests that type 2 diabetes mellitus increases the risk of Parkinson's disease (PD), the relationship between type 1 diabetes mellitus (T1DM) and PD is unclear. To study their association, we performed a two-sample Mendelian randomization (MR) using the following statistical methods: inverse variance weighting (IVW), MR-Egger, weight median, and weighted mode. Independent datasets with no sample overlap were retrieved from the IEU GWAS platform. All the MR methods found a lower risk of PD in T1DM (IVW-OR 0.93, 95% CI 0.91-0.96, p = 3.12 × 10-5; MR-Egger-OR 0.93, 95% CI 0.88-0.98, p = 1.45 × 10-2; weighted median-OR 0.93, 95% CI 0.89-0.98, p = 2.76 × 10-3; and weighted mode-OR 0.94, 95% CI 0.9-0.98, p = 1.58 × 10-2). The findings were then replicated with another independent GWAS dataset on T1DM (IVW-OR 0.97, 95% CI 0.95-0.99, p = 3.10 × 10-3; MR-Egger-OR 0.96, 95% CI 0.93-0.99, p = 1.08 × 10-2; weighted median-OR 0.97, 95% CI 0.94-0.99, p = 1.88 × 10-2; weighted mode-OR 0.97, 95% CI 0.94-0.99, p = 1.43 × 10-2). Thus, our study provides evidence that T1DM may have a protective effect on PD risk, though further studies are needed to clarify the underlying mechanisms.

Causal relationships between type 1 diabetes mellitus and Alzheimer's disease and Parkinson's disease: a bidirectional two-sample Mendelian randomization study

BACKGROUND

Previous compelling evidence suggests an association between Type 2 diabetes (T2D) and neurodegenerative diseases. However, it remains uncertain whether Type 1 diabetes mellitus (T1DM) exerts a causal influence on the risk of Alzheimer's disease (AD) and Parkinson's disease (PD). Consequently, this study employed a bidirectional two-sample Mendelian Randomization (MR) approach to investigate the causal relationship between T1DM and the genetic susceptibility to AD and PD.

METHODS

We utilized large-scale cohorts derived from publicly available genome-wide association study datasets involving European populations to perform MR analyses. The primary analytical method employed was the inverse-variance weighted (IVW) approach. Furthermore, sensitivity analyses, including assessments of heterogeneity and horizontal pleiotropy, were carried out using Cochran's Q, MR-Egger intercept, and MR-PRESSO tests to enhance the robustness of our conclusions.

RESULTS

Using the IVW-based method, the MR analysis indicated no significant association between genetically determined T1DM and AD (OR = 0.984, 95% CI: 0.958-1.011, p = 0.247). Conversely, T1DM appeared to be associated with a reduced risk of genetic susceptibility to PD (IVW: OR = 0.958, 95% CI: 0.928-0.989, p = 0.001). In the reverse direction, no evidence of reverse causality was observed between AD (OR = 1.010, 95% CI: 0.911-1.116, p = 0.881) or PD (OR = 1.164, 95% CI: 0.686-2.025, p = 0.5202) and T1DM. Additionally, our analysis found no indications of the results being influenced by horizontal pleiotropy.

CONCLUSION

This MR study reveals that T1DM is associated with a reduced genetic susceptibility to PD, whereas no significant genetic susceptibility is observed between T1DM and AD. These findings suggest that T1DM may have a distinct role in the development of neurodegenerative diseases compared to T2D. Further investigations are warranted to elucidate the underlying mechanisms and provide a more comprehensive understanding of this relationship.