Type 2 diabetes and glycemic traits are not causal factors of delirium: A two-sample mendelian randomization analysis

A Mendelian randomization-based study of the causal relationship between leisure sedentary behavior and delirium

BACKGROUND

Delirium is an acute or subacute change in mental status caused by various factors. We evaluated the causal relationship between leisure sedentary behaviors (LSBs) and delirium.

METHODS

A two-sample Mendelian randomization (MR) study was performed to evaluate the causal relationship between sedentary behaviors (time spent watching television, time spent using computer, and time spent driving) and delirium. Statistical information for the associations between single nucleotide polymorphisms (SNPs) and the traits of interest was obtained from independent consortia that focused on European populations. The dataset for LSBs was acquired from genome-wide association studies (GWAS) comprising a substantial sample size: 437887 samples for time spent watching television, 360,895 for time spent using computer, and 310,555 for time spent driving. A GWAS with 1269 delirium cases and 209,487 controls was used to identify genetic variation underlying the time of LSBs. We used five complementary MR methods, including inverse variance weighted method (IVW), MR-Egger, weighted median, weighted mode, and simple mode.

RESULTS

Genetically predicted time spent watching television (odds ratio [OR]: 2.921, 95 % confidence interval [CI]: 1.381-6.179) demonstrated significant association with delirium (P = 0.005), whereas no significant associations were observed between time spent using computer (OR: 0.556, 95 % CI: 0.246-1.257, P = 0.158) and time spent driving (OR: 1.747, 95 % CI: 0.09-3. 40, P = 0.713) and delirium. Sensitivity analyses supported a causal interpretation, with limited evidence of significant bias from genetic pleiotropy. Moreover, our MR assumptions appeared to be upheld, enhancing the credibility of our conclusions.

LIMITATIONS

Larger sample sizes are needed to validate the findings of our study.

CONCLUSION

Time spent watching television is a significant risk factor for delirium. Reducing television time may be an important intervention for those at higher risk of delirium.

Mendelian Randomization Reveals: Triglycerides and Sensorineural Hearing Loss

BACKGROUND

Sensorineural hearing loss (SNHL) is a multifactorial disorder with potential links to various physiological systems, including the cardiovascular system via blood lipid levels such as triglycerides (TG). This study investigates the causal relationship between TG levels and SNHL using Mendelian randomization (MR), which offers a method to reduce confounding and reverse causality by using genetic variants as instrumental variables.

METHODS

Utilizing publicly available genome-wide association study (GWAS) data, we performed a two-sample MR analysis. The initial analysis unveiled a causal relationship between TG (GWAS ID: ebi-a-GCST90018975) and SNHL (GWAS ID: finn b-H8_HL_SEN-NAS). Subsequent analysis validated this through MR with a larger sample size for TG (GWAS ID: ieu-b-111) and SNHL. To conduct the MR analysis, we utilized several methods including inverse-variance weighted (IVW), MR Egger, weighted median, and weighted mode. We also employed Cochrane's Q test to identify any heterogeneity in the MR results. To detect horizontal pleiotropy, we conducted the MR-Egger intercept test and MR pleiotropy residual sum and outliers (MR-PRESSO) test. We performed a leave-one-out analysis to assess the sensitivity of this association. Finally, a meta-analysis of the MR results was undertaken.

RESULTS

Our study found a significant positive correlation between TG and SNHL, with OR values of 1.14 (95% CI: 1.07-1.23, p < 0.001) in the IVW analysis and 1.09 (95% CI: 1.03-1.16, p < 0.006) in the replicate analysis. We also found no evidence of horizontal pleiotropy or heterogeneity between the genetic variants (p > 0.05), and a leave-one-out test confirmed the stability and robustness of this association. The meta-analysis combining the initial and replicate analyses showed a significant causal effect with OR values of 1.11 (95% CI: 1.06-1.16, p = 0.01).

CONCLUSION

These findings indicate TG as a risk factor for SNHL, suggesting potential pathways for prevention and intervention in populations at risk. This conclusion underscores the importance of managing TG levels as a strategy to mitigate the risk of developing SNHL.

Unveiling Atherosclerotic Plaque Heterogeneity and SPP1+/VCAN+ Macrophage Subtype Prognostic Significance Through Integrative Single-Cell and Bulk-Seq Analysis

Background

Dysregulated macrophages are important causes of Atherosclerosis (AS) formation and increased plaque instability, but the heterogeneity of these plaques and the role of macrophage subtypes in plaque instability have yet to be clarified.

Methods

This study integrates single-cell and bulk-seq data to analyze atherosclerotic plaques. Unsupervised clustering was used to reveal distinct plaque subtypes, while survival analysis and gene set variation analysis (GSVA) methods helped in understanding their clinical outcomes. Enrichment of differential expression of macrophage genes (DEMGs) score and pseudo-trajectory analysis were utilized to explore the biological functions and differentiation stages of macrophage subtypes in AS progression. Additionally, CellChat and the BayesPrism deconvolution method were used to elucidate macrophage subtype interaction and their prognostic significance at single-cell resolution. Finally, the expression of biomarkers was validated in mouse experiments.

Results

Three distinct AS plaque subtypes were identified, with cluster 3 plaque subtype being particularly associated with higher immune infiltration and poorer prognosis. The DEMGs score exhibited a significant elevation in three macrophage subtypes (SPP1+/VCAN+ macrophages, IL1B+ macrophages, and FLT3LG+ macrophages), associated with cluster 3 plaque subtype and highlighted the prognostic significance of these subtypes. Activation trajectory of the macrophage subtypes is divided into three states (Pre-branch, Cell fate 1, and Cell fate 2), and Cell fate 2 (SPP1+/VCAN+ macrophages, IL1B+ macrophages, and FLT3LG+ macrophages dominant) exhibiting the highest DEMGs score, distinct interactions with other cell components, and relating to poorer prognosis of ischemic events. This study also uncovered a unique SPP1+/VCAN+ macrophage subtype, rare in quantity but significant in influencing AS progression. Machine learning algorithms identified 10 biomarkers crucial for AS diagnosis. The validation of these biomarkers was performed using Mendelian Randomization analysis and in vitro methods, supporting their relevance in AS pathology.

Conclusion

Our study provides a comprehensive view of AS plaque heterogeneity and the prognostic significance of macrophage subtypes in plaque instability.

Association Between Antidiabetic Drugs and Delirium: A Study Based on the Adverse Drug Event Reporting Database in Japan

BACKGROUND AND OBJECTIVE

Several associations between diabetes mellitus and delirium have been reported; however, they have been inconsistent, and evidence on the effects of antidiabetic medications on delirium is also limited. This study aimed to investigate whether the use of antidiabetic drugs is a risk factor for delirium development.

METHODS

Using the Japanese Adverse Event Reporting Database, we analyzed 662,899 reports between 2004 and 2022. Reporting odds ratios (RORs) and 95% confidence intervals (CIs) for delirium associated with diabetes and using each antidiabetic medication were calculated after adjusting for potential confounders.

RESULTS

Overall, 8892 of the reports analyzed were associated with delirium. A comparison of the incidence of delirium between patients with and without diabetes showed no significant difference, with 1.34% in patients without diabetes and 1.37% in those with diabetes. In each antidiabetic medication, signals for delirium were detected for sulfonylurea (crude ROR, 1.35; 95% CI 1.21-1.51) and insulin (crude ROR, 1.28; 95% CI 1.13-1.44). These results were maintained even after adjusting for factors with potential confounders (sulfonylurea: adjusted ROR, 1.75; 95% CI 1.54-2.00, insulin: adjusted ROR, 1.35; 95% CI 1.20-1.54).

CONCLUSIONS

Our results suggest no association between diabetes and delirium; however, using sulfonylurea and insulin may be associated with delirium development. Nonetheless, these findings should be validated in future studies.

Association between human blood metabolome and the risk of delirium: a Mendelian Randomization study

Background

Delirium significantly contributes to both mortality and morbidity among hospitalized older adults. Furthermore, delirium leads to escalated healthcare expenditures, extended hospital stays, and enduring cognitive deterioration, all of which are acknowledged detrimental outcomes. Nonetheless, the current strategies for predicting and managing delirium remain constrained. Our aim was to employ Mendelian randomization (MR) to investigate the potential causal relationship between metabolites and delirium, as well as to identify potential therapeutic targets.

Methods

We identified 129 distinct blood metabolites from three genome-wide association studies (GWASs) conducted on the metabolome, involving a total of 147,827 participants of European descent. Genetic information pertaining to delirium was sourced from the ninth iteration of the Finngen Biobank, encompassing 359,699 individuals of Finnish ancestry. We conducted MR analyses to evaluate the connections between blood metabolites and delirium. Additionally, we extended our analysis to encompass the entire phenome using MR, aiming to uncover potential on-target consequences resulting from metabolite interventions.

Results

In our investigation, we discovered three metabolites serving as causal mediators in the context of delirium: clinical low density lipoprotein cholesterol (LDL-C) (odds ratio [OR]: 1.47, 95% confidence interval [CI]: 1.25-1.73, p = 3.92 x 10-6), sphingomyelin (OR: 1.47, 95% CI: 1.25-1.74, p = 5.97 x 10-6), and X-11593-O-methylascorbate (OR: 0.21, 95% CI: 0.10-0.43, p = 1.86 x 10-5). Furthermore, utilizing phenome-wide MR analysis, we discerned that clinical LDL-C, sphingomyelin, and O-methylascorbate not only mediate delirium susceptibility but also impact the risk of diverse ailments.

Limitations

(1) Limited representation of the complete blood metabolome, (2) reliance on the PheCode system based on hospital diagnoses may underrepresent conditions with infrequent hospital admissions, and (3) limited to European ancestry.

Conclusion

The genetic prediction of heightened O-methylascorbate levels seems to correspond to a diminished risk of delirium, in contrast to the association of elevated clinical LDL-C and sphingomyelin levels with an amplified risk. A comprehensive analysis of side-effect profiles has been undertaken to facilitate the prioritization of drug targets. Notably, O-methylascorbate emerges as a potentially auspicious target for mitigating and treating delirium, offering the advantage of lacking predicted adverse side effects.