Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes

Peptidylglycine alpha-amidating monooxygenase is important in mice for beta-cell cilia formation and insulin secretion but promotes diabetes risk through beta-cell independent mechanisms

OBJECTIVES

Carriers of PAM (peptidylglycine alpha-amidating monooxygenase) coding variant alleles have reduced insulinogenic index, higher risk of developing type 2 diabetes (T2D), and islets from heterozygous carriers of the PAM p.Asp563Gly variant display reduced insulin secretion. Exactly how global PAM deficiency contributes to hyperglycemia remains unclear. PAM is the only enzyme capable of converting glycine-extended peptide hormones into amidated products. Like neuropeptide Y (NPY), α-melanocyte stimulating hormone (αMSH), and glucagon-like peptide 1 (GLP-1), islet amyloid polypeptide (IAPP), a beta cell peptide that forms islet amyloid in type 2 diabetes, is a PAM substrate. We hypothesized that Pam deficiency limited to beta cells would lead to reduced insulin secretion, prevent the production of amidated IAPP, and reveal the extent to which loss of Pam in β-cells could accelerate the onset of hyperglycemia in mice.

METHODS

PAM activity was assessed in human islets from donors based on their PAM genotype. We generated beta cell-specific Pam knockout (Ins1Cre/+, Pamfl/fl; βPamKO) mice and performed islet culture, histological, and metabolic assays to evaluate the physiological roles of Pam in beta cells. We analyzed human IAPP (hIAPP) amyloid fibril forming kinetics using synthetic amidated and non-amidated hIAPP peptides, and generated hIAPP knock-in beta cell-specific Pam knockout (hIAPPw/w βPamKO) mice to determine the impact of hIAPP amidation on islet amyloid burden, islet graft survival, and glucose tolerance.

RESULTS

PAM enzyme activity was significantly reduced in islets from donors with the PAM p. Asp563Gly T2D-risk allele. Islets from βPamKO mice had impaired second-phase glucose- and KCl-induced insulin secretion. Beta cells from βPamKO mice had larger dense-core granules and fewer and shorter cilia. Interestingly, non-amidated hIAPP was less fibrillogenic in vitro, and high glucose-treated hIAPPw/w βPamKO islets had reduced amyloid burden. Despite these changes in beta cell function, βPamKO mice were not more susceptible to diet-induced hyperglycemia. In vitro beta cell death and in vivo islet graft survival remained comparable between hIAPPw/w βPamKO and hIAPPw/w islets. Surprisingly, aged hIAPPw/w βPamKO mice had improved insulin secretion and glucose tolerance.

CONCLUSIONS

Eliminating Pam expression only in beta cells leads to morphological changes in insulin granules, reduced insulin secretion, reduced hIAPP amyloid burden and altered ciliogenesis. However, in mice beta-cell Pam deficiency has no impact on the development of diet- or hIAPP-induced hyperglycemia. Our data are consistent with current studies revealing ancient, highly conserved roles for peptidergic signaling in the coordination of the diverse signals needed to regulate fundamental processes such as glucose homeostasis.

Causal relationship between metabolic dysfunction-associated fatty liver disease and endotoxin biomarkers: A Mendelian randomization study

Although the relationship among lipopolysaccharides (LPS), LPS-binding proteins, and metabolic dysfunction-associated fatty liver disease (MAFLD) is widely studied, no conclusive evidence is available. In this study, we used mendelian randomization (MR) to study the causal relationship of LPS, LPS-binding proteins, and MAFLD. Using bidirectional two-sample MR method, we evaluated data from the genome wide association study; for this analysis, nonalcoholic fatty liver disease (NAFLD), liver fat percentage, and other metabolic syndromes were employed as outcomes. Furthermore, MR analysis mainly involved the inverse variance weighted method. Heterogeneity and pleiotropy tests were also conducted. LPS was found to have a causal relationship with NAFLD, obesity, high density lipoprotein cholesterol, and TG levels. Furthermore, TG levels and LBP had significant causal relationships. This study mainly concluded that LPS is a risk factor for NAFLD, obesity, high density lipoprotein cholesterol, and TG, corroborating it's the LPS role in MAFLD pathogenesis. Hence, optimizing the gut microbiota using proper diet, probiotics, or fecal microbiota transplantation may help to reduce inflammation and (IR), thereby improving lipid and glucose metabolism disorders. Although a causal relationship between TG and LBP was observed, further studies are required to determine a specific mechanism.

Bacterial genome-wide association studies: exploring the genetic variation underlying bacterial phenotypes

With the continuous advancements in high-throughput genome sequencing technologies and the development of innovative bioinformatics tools, bacterial genome-wide association studies (BGWAS) have emerged as a transformative approach for investigating the genetic variations underlying diverse bacterial phenotypes at the population genome level. This review provides a comprehensive overview of the application of BGWAS in elucidating genetic determinants of bacterial drug resistance, pathogenicity, host specificity, biofilm formation, and probiotic fermentation characteristics. We systematically summarize the BGWAS workflow, including study design, data analysis pipelines, and the bioinformatics software employed at various stages. Furthermore, we highlight specialized tools tailored for BGWAS and discuss their unique features and applications. We also discuss confounding factors that can influence the accuracy and reliability of BGWAS results, including population structure, linkage disequilibrium, and multiple testing. By incorporating recent advancements, this review serves as a comprehensive reference for researchers utilizing BGWAS to uncover the genetic basis of bacterial phenotypes.

Circulating mediators linking cardiometabolic diseases to HFpEF: a mediation Mendelian randomization analysis

BACKGROUND

Heart failure with preserved ejection fraction (HFpEF) is an increasingly prevalent clinical syndrome with high morbidity and mortality. Although HFpEF frequently coexists with cardiometabolic diseases, the causal mechanisms and potential mediators remain poorly understood.

OBJECTIVES

This study aimed to identify cardiometabolic risk factors specifically driving HFpEF and to determine their underlying circulating mediators.

METHODS

We used two-sample Mendelian Randomization (MR) to analyze the effects of obesity, Type 2 diabetes, hypertension, chronic kidney disease (CKD), and dyslipidemia on HFpEF and heart failure with reduced ejection fraction (HFrEF) in large European-ancestry GWAS datasets. We then performed mediation MR to identify plasma proteins and metabolites that mediate the transition from each cardiometabolic disease to HFpEF, respectively. We applied multivariable MR to assess the impact of risk confounding on the results. Bioinformatic analyses were conducted to delineate mechanisms.

RESULTS

Cardiometabolic diseases had heterogeneous effects on HFpEF and HFrEF. Obesity and type 2 diabetes showed adjusted causal effects with HFpEF, hypertension showed potential relevance to HFpEF, whereas dyslipidemia and CKD did not. MR analysis identified 5 proteins that mediate obesity to HFpEF; 5 proteins that mediate type 2 diabetes to HFpEF. Further mediation MR analysis of obesity and T2D on HFrEF revealed heterogeneity in circulating mediators between metabolic HFpEF and HFrEF. Comprehensive bioinformatics analyses showed that IL1R1, together with other proteins such as TP53 and FGF19, orchestrates the inflammatory and fibrotic processes underlying HFpEF.

CONCLUSIONS

These findings suggest that metabolic HFpEF has distinct etiological features compared with HFrEF and is driven by complex, condition-specific mediators. IL1R1 mediates HFpEF in multiple metabolic risk states, suggesting a potential therapeutic target. Further translational studies are warranted to evaluate anti-inflammatory strategies targeting IL1R1 in HFpEF.

Causal Associations Between Pre-Pregnancy Diabetes Mellitus and Pre-Eclampsia Risk: Insights from a Mendelian Randomization Study

BACKGROUND AND OBJECTIVES

Pre-eclampsia (PE) is a serious pregnancy complication defined by the onset of hypertension and multi-organ dysfunction occurring after 20 weeks of gestation. Studies have indicated the correlation between diabetes mellitus (DM) and PE, but the causal relationship remains unclear.

MATERIALS AND METHODS

The two-sample Mendelian randomization (MR) approach, including the inverse variance weighted random effects (IVW-RE) model and the traditional sensitivity model, was employed to assess the causal effects of pre-pregnancy type 1 diabetes (T1D) and type 2 diabetes (T2D) on PE using summary-level data obtained from genome-wide association studies. Additionally, diabetes-related factors, such as glycated hemoglobin (HbA1c) levels, fasting insulin levels, and body mass index (BMI), were evaluated for their potential causal effects on the risk of PE. Pleiotropy-robust and multivariable Mendelian randomization (MVMR) methods were further used because of the intricate associations among the traits. Insulin and metformin use was also assessed for their causal role in PE risk.

RESULTS

Our findings show that genetically predicted T1D (OR = 1.06, 95% CI: 1.03-1.09, p < 0.001), T2D (OR = 1.09, 95% CI: 1.04-1.14, p < 0.001), and BMI (OR = 1.64, 95% CI 1.49 to 1.80, p < 0.001) had causal effects on the incidence of PE, while the effects of HbA1c (OR = 0.77, 95% CI 0.59 to 1.02, p = 0.064) and fasting insulin levels (OR = 1.35, 95% CI 0.89 to 2.05, p = 0.153) on the occurrence of PE were not significant. The results were verified by MVMR analysis. Additionally, insulin use increased the risk of pre-eclampsia (OR = 1.11, 95% CI 1.05-1.17, p < 0.001).

CONCLUSIONS

Our findings demonstrate a causal relationship between pre-pregnancy diabetes (DM) and obesity and the risk of PE from a genetic epidemiological perspective. Adverse maternal factors, including DM and obesity prior to pregnancy, should be considered in mechanistic studies of PE. In addition, comprehensive interventions for risk factors such as pre-pregnancy DM and obesity should be emphasized in clinical practice.

Placental weight as a predictor of future health: Insights from a large-scale genome-wide association study

INTRODUCTION

Placental weight has been associated with various adult-onset diseases, but the causal relationships and underlying mechanisms remain unclear.

METHODS

This two-sample Mendelian randomization (MR) study utilized genome-wide association study (GWAS) data from multiple independent cohorts, primarily of European ancestry. The analysis included over 1.8 million individuals for type 2 diabetes mellitus (T2DM) outcomes. Data from four independent cohorts were used for validation. The inverse variance-weighted method was used for primary analysis, with weighted median, weighted mode, and MR-Egger regression for sensitivity analyses.

RESULTS

Each standard deviation increase in genetically predicted placental weight was associated with T2DM (β = -0.109, 95 % CI: -0.184 to -0.034), basal cell carcinoma (β = 0.130, 95 % CI: 0.016 to 0.245), acute upper respiratory infections (β = -0.062, 95 % CI: -0.113 to -0.011), neurological diseases (β = -0.009, 95 % CI: -0.014 to -0.003), and endometrial cancer (β = -0.561, 95 % CI: -0.961 to -0.161). Placental weight also showed significant negative associations with blood glucose levels (β = -0.102, 95 % CI: -0.200 to -0.004). Mediation analyses revealed that dried fruit intake mediated 14.68 % of the total effect on T2DM risk, while immune cell phenotype analysis identified HLA DR on CD33dim HLA DR + CD11b + as a potential mediator in the causal pathway.

CONCLUSION

This study provides genetic evidence for a causal relationship between placental weight and T2DM risk, mediated partly through dietary habits and immune pathways. These findings suggest that early-life placental development may influence long-term metabolic health, highlighting the importance of prenatal care in preventing adult-onset diseases.

Insights into modifiable risk factors of retinal vascular occlusion: A Mendelian randomization study

Understanding the etiological risk factors for retinal vascular occlusion (RVO) is critical for prevention and treatment. While the effects of cardiovascular events, hypertension, glaucoma, obesity and glycemic risk factors on RVO are still controversial. This study employed two-sample Mendelian randomization (MR) analysis to investigate these causal risk factors. Single-nucleotide polymorphisms (SNPs) were used as instrumental variables (IVs). Genetic instruments for hypertension, glaucoma, obesity, cardiovascular events and glycemic risk factors were obtained from published genome-wide association studies (GWASs). Summary-level data for RVO and hypertension were obtained from the FinnGen consortium. MR analysis primarily utilized the inverse variance weighted (IVW) method, with MR-Egger and weighted median as supplementary approaches. Multivariable MR (MVMR) adjusting for hypertension or glaucoma of RVO were conducted. Heterogeneity was assessed using Cochrane's Q test and I2, while MR-Egger intercept and MR-PRESSO tested horizontal pleiotropy. All MR analyses were performed within R software (4.1.3) using the R packages "TwoSampleMR" and "MR-PRESSO." Genetic instruments for hypertension and glaucoma were significantly associated with RVO risk. A one-standard deviation (SD) increase in hypertension was associated with a higher risk of RVO [OR = 1.577, 95% CI = (1.342, 1.854), P < .001], while a one-SD increase in the log odds of genetically predicted glaucoma was associated with a higher risk of RVO [OR = 1.24, 95% CI = (1.115, 1.379), P < .001]. Meanwhile, hypertension and glaucoma were still significant in multivariable MR. There was not sufficient evidence to suggest cardiovascular events and obesity were associated with RVO risk. This MR study provided genetic evidence supporting that hypertension and glaucoma were causally associated with the risk of RVO. It may help guide clinical decisions in the management of RVO patients with hypertension and glaucoma.

Association Between T2DM, TyG Index, Multiple Sclerosis, and Rheumatoid Arthritis: Insights into Potential Mechanisms

Abundant research indicates that type 2 diabetes mellitus (T2DM) and insulin resistance (IR) have a certain association with autoimmune-related diseases (ARDs). However, the conclusions remain elusive. Therefore, this study aimed to explore whether there are causal associations between T2DM and IR indicator, triglyceride-glucose (TyG) index with ARDs, and evaluate the impact of immune cells. Comprehensive Mendelian randomization (MR) analysis combined with Bayesian colocalization was employed to investigate the relationship between T2DM, TyG index, ARDs, and specific-marker immune cells by extracting summary-level data from various genome-wide association studies (GWASs). Further investigations utilizing single-cell RNA sequencing (scRNA-seq) analysis were performed to explore the potential molecular mechanisms underlying the MR analysis results. Causal associations of T2DM with multiple sclerosis (MS) and rheumatoid arthritis (RA) were detected. Additionally, the TyG index was genetically predicted to be associated with MS. Furthermore, immune cells were found to be related to T2DM and TyG index, of which CD3 on naive CD8 + T cell mediate the effect on the association between TyG index and multiple sclerosis (MS). Additionally, genetic variation of TCF7L2 and TNFSF13B were assessed to play a crucial role in the aforementioned associations supported by colocalization analysis. This study identified T2DM and IR related to increased risk of MS and RA. The analysis of relevant immune cells and shared genetic loci provides a novel direction for exploring comorbidity mechanisms.

Identification and validation of five novel protein targets for type 2 diabetes mellitus

Despite advances in type 2 diabetes mellitus (T2DM) therapy, challenges remain due to the lack of novel therapeutic targets. We used Mendelian randomization to integrate cis-expression quantitative trait loci data for circulating proteins from the eQTLGen Consortium (31,684 individuals) with T2DM summary statistics from the Integrative Epidemiology Unit Open Genome-Wide Association Studies Project (61,714 cases, 593,952 controls). 42 genes were significantly associated with T2DM. Colocalization analysis revealed that six genes (CLSTN1, KCNJ11, MLX, DLD, RELA, and ULK1) shared common causal variants with T2DM. Among them, CLSTN1 (OR = 0.80, 95% CI: 0.70-0.90), KCNJ11 (OR = 0.66, 95% CI: 0.60-0.73), and MLX (OR = 0.73, 95% CI: 0.65-0.82) were negatively associated with T2DM, while DLD (OR = 1.38, 95% CI: 1.15-1.65), RELA (OR = 1.90, 95% CI: 1.41-2.55), and ULK1 (OR = 1.42, 95% CI: 1.17-1.71) were positively associated with T2DM. A matched case-control study further validated these associations, except for DLD, showing significant downregulation of CLSTN1, KCNJ11, and MLX (P < 0.05) alongside upregulation of RELA and ULK1 (P < 0.05) in T2DM patients. These findings underscore the potential of these proteins as drug targets, warranting further clinical investigation to confirm their therapeutic relevance.

Glucosamine supplementation contributes to reducing the risk of type 2 diabetes: Evidence from Mendelian randomization combined with a meta-analysis

ObjectiveObservational studies on glucosamine supplementation and type 2 diabetes risk have shown inconsistent results, necessitating the use of Mendelian randomization to clarify the true causal relationship.MethodsThe glucosamine supplementation-related genome-wide association study dataset was obtained from the MRC Integrative Epidemiology Unit consortium, whereas type 2 diabetes-related genome-wide association study datasets were obtained from the FinnGen consortium (discovery) and Xue et al.'s meta-analysis (validation). Two-sample Mendelian randomization analyses were performed separately in the discovery and validation datasets, followed by meta-analysis and multivariable Mendelian randomization analyses to verify the robustness of the results of two-sample Mendelian randomization. The estimation of the causal relationship was conducted through the inverse variance weighted method.ResultsGlucosamine supplementation exhibited a significant protective effect against type 2 diabetes, as identified by two-sample Mendelian randomization analysis in the FinnGen consortium (odds ratio: 0.13, 95% confidence interval: 0.02-0.89) and validated in Xue et al.'s meta-analysis (odds ratio: 0.06, 95%; confidence interval: 0.01-0.29). A combined meta-analysis (odds ratio: 0.08, 95%; confidence interval: 0.02-0.27) of the results of two-sample Mendelian randomization confirmed the robustness of these findings. Additionally, multivariable Mendelian randomization analysis (odds ratio: 0.12, 95%; confidence interval: 0.02-0.94), after adjusting for confounding factors, supported the results of two-sample Mendelian randomization. No evidence of heterogeneity or pleiotropy was observed.ConclusionOverall, our results revealed that genetically predicted glucosamine supplementation was inversely associated with the risk of type 2 diabetes, highlighting the potential importance of glucosamine supplementation in preventing type 2 diabetes.

THE CAUSAL ASSOCIATION OF CARDIOMETABOLIC DISEASES AND SEPSIS-RELATED OUTCOMES: A MENDELIAN RANDOMIZATION AND POPULATION STUDY

ABSTRACT

Objective: The causality between cardiometabolic disease (CMD) and sepsis has remained largely unknown. To elucidate this, we conducted a Mendelian randomization (MR) and population study. Methods: First, we used univariable and multivariable MR analyses to investigate causal associations between CMD and sepsis-related outcomes. We obtained genome-wide association study summary from both the MRC Integrative Epidemiology Unit and the FinnGen consortium. Subsequently, a two-step mediation MR analysis was performed to explore mediators. Afterward, we conducted an observational study using the Medical Information Mart for Intensive Care IV database, in which multivariable logistic regression models were utilized to examine the relationship between CMD and sepsis-related outcomes. Results: In the MR study, type 2 diabetes mellitus (OR = 1.058, 95% CI = 1.017-1.100, P = 0.005), obesity (OR = 1.113, 95% CI = 1.057-1.172, P < 0.001), and heart failure (HF) (OR = 1.178, 95% CI = 1.063-1.305, P = 0.002) were independently causally related to sepsis. Obesity (OR = 1.215, 95% CI = 1.027-1.437, P = 0.023) and HF (OR = 1.494, 95% CI = 1.080-2.065, P = 0.015) also showed independent causal associations with sepsis critical care admission. Mediation MR analysis identified 23 blood metabolites potentially causally linked to sepsis ( P < 0.05), yet none mediated the relationship between CMD and sepsis. In the observational study, we found associations between sepsis and several conditions including type 2 diabetes mellitus, obesity, hypertension, stroke, HF, and hyperlipidemia after adjusting for confounding factors. Moreover, hypertension, stroke, HF, coronary artery disease, and hyperlipidemia were linked to sepsis critical care admission. Conclusion: This study has, for the first time, revealed indicative evidence of a causal relationship between CMD and sepsis through observational and genetic evidence. Taken together, clinical attention to sepsis may be warranted among patients with CMD.

Inhibition of Putative Ibrutinib Targets Promotes Atrial Fibrillation, Conduction Blocks, and Proarrhythmic Electrocardiogram Indices: A Mendelian Randomization Analysis

Background

The mechanism by which ibrutinib, a Bruton's tyrosine kinase inhibitor, can elevate the risk of arrhythmias is not fully elucidated. In this study, we explored how inhibition of off-target kinases can contribute to this phenomenon.

Methods

We performed a Mendelian randomization analysis to examine the causal associations between genetically proxied inhibition of six putative ibrutinib drug targets (ErbB2/HER2, CSK, JAK3, TEC, BLK, and PLCG2) and the atrial fibrillation (AF) risk, proarrhythmic ECG indices, and cardiometabolic traits and diseases. Inverse-variance weighted random-effects models and Wald ratio were used to examine the associations between genetically proxied inhibition of these drug targets and the risk of outcomes. Colocalization analyses were employed to examine the robustness of the causally significant findings. ELISAs were used to measure ErbB2 levels in intracardiac plasma samples.

Results

Genetically proxied ErbB2 inhibition was associated with an increased AF risk, higher P wave terminal force, and prolonged QTc interval. Patients with AF had significantly higher intracardiac ErbB2 levels compared with patients with paroxysmal supraventricular tachycardia. CSK inhibition prolonged the QRS duration, decreased the QTc interval, and was potentially linked to conduction blocks. PLCG2 inhibition led to decreased P wave terminal force, shorter QTc interval, and increased risk of left bundle branch block. BLK inhibition shortened the QTc interval and was also associated with atrioventricular block.

Conclusion

The off-target effects and downstream targets of ibrutinib, including CSK, PLCG2, ERBB2, TEC, and BLK, may lead to cardiac electrical homeostasis imbalances and lethal cardiovascular diseases. Using drugs that inhibit these targets should be given extra caution.

Monocyte CCL2 signaling possibly contributes to increased asthma susceptibility in type 2 diabetes

In recent years, the respiratory system has been increasingly recognized as a key target organ in diabetes. Although observational studies have established significant clinical associations between type 2 diabetes (T2D), antidiabetic medication use, and asthma, the causal relationships and underlying molecular mechanisms remain unclear. This study employed a bidirectional two-sample Mendelian randomization (MR) approach combined with bioinformatics analysis to explore the causal relationships between T2D and asthma subtypes and complications, with a focus on immune-regulatory mechanisms. The MR analysis utilized inverse-variance weighted (IVW) and meta-analysis methods to evaluate overall effects, with sensitivity analyses confirming the robustness of the findings. Bioinformatics analysis focused on differential gene expression and pathway enrichment to identify potential molecular networks. The MR analysis showed that T2D has a significant positive causal effect on asthma (P < 0.05), with severe autoimmune T2D showing strong associations with specific asthma subtypes (eosinophilic and mixed asthma) and complications (e.g., acute respiratory infections and pneumonia) (P < 0.05). Bioinformatics analysis identified the monocyte-CCL2 signaling axis as a key mechanism linking T2D and asthma, where hyperglycemia-induced monocyte activation may promote asthma development. These findings reveal shared inflammatory pathways and deepen our understanding of the molecular mechanisms linking these two chronic diseases.

A case of familial partial lipodystrophy type 2 masquerading as Cushing syndrome: Explaining an atypical phenotype by whole-exome sequencing

Familial partial lipodystrophy type 2 is a rare disease, particularly when it is caused by nonclassical gene variants. A high index of suspicion is essential for a timely diagnosis. We present the case of a 32-year-old woman, referred to evaluation of a possible Cushing syndrome, which was clinically and biochemically ruled out. Yet, due to the finding of a rather abnormal fat distribution during physical examination, the diagnosis of lipodystrophy was cogitated. Whole-exome sequencing revealed a missense variant of exon 11 R582H of the gene encoding Laminin A (rs57830985,c.1745G>A, p.Arg582His). The patient presented some clinical and biochemical characteristics discordant with those previously reported in patients harboring other classical variants of this gene.

Causal associations between gut microbiota and type 2 diabetes mellitus subtypes: a mendelian randomization analysis

PURPOSE

To investigate the causal relationships between gut microbiota and novel adult-onset type 2 diabetes mellitus(T2DM) subtypes.

METHODS

We conducted Mendelian randomization (MR) analyses using genome-wide association data from European populations. Initial MR analyses examined associations between gut microbiota and four T2DM subtypes, followed by validation analyses using type 1 diabetes mellitus(T1DM) and T2DM GWAS data. We also performed bidirectional MR analyses and tested for heterogeneity and pleiotropy across all analyses.

RESULTS

Our MR analyses revealed distinctive associations between gut microbiota and T2DM subtypes: six bacterial taxa with severe insulin-deficient diabetes (SIDD), four with severe insulin-resistant diabetes (SIRD), eight with mild obesity-related diabetes (MOD), and eight with mild age-related diabetes (MARD). These associations were distinct from T1DM findings. Six bacterial taxa were validated in T2DM analyses, with four showing directionally consistent effects: Class Clostridia (OR = 0.57, P = 0.045) and Order Clostridiales (OR = 0.57, P = 0.045) were associated with reduced MOD risk, while species Catus (OR = 1.80, P = 0.007) was associated with increased MOD risk, and genus Holdemania (OR = 2.51, P = 0.004) was associated with increased SIRD risk. No significant heterogeneity or pleiotropy was observed across analyses.

CONCLUSIONS

Our MR analyses reveal novel causal relationships between gut microbiota and adult-onset T2DM subtypes, though further validation studies are warranted.

The dual role of diabetes on oral potentially malignant disorders

BACKGROUND

Observational studies suggest a link between diabetes and oral potentially malignant disorders (OPMDs), such as oral lichen planus (OLP) and oral leukoplakia (OLK). The causal relationship, as well as the type of diabetes that promotes OPMDs development, remains unclear. This Mendelian randomization (MR) study estimated the causal effects of diabetes-related traits on OPMDs.

METHODS

Large-scale genome-wide association study data on type 1 diabetes (T1D), type 2 diabetes (T2D), fasting glucose (FG), fasting insulin (FI), glycated hemoglobin (HbA1c), OLP, OLK, and actinic cheilitis (AC) were used. Causal effects were assessed using inverse-variance weighted (IVW), weighted median, and MR-Egger methods. Multivariable MR analyses evaluated the independent roles of these traits, with extensive sensitivity analyses.

RESULTS

Genetic susceptibility to T1D (IVW OR = 1.09, 95% CI 1.02-1.17, P = 0.007) and T2D (IVW OR = 0.91, 95% CI 0.86-0.97, P = 0.002) showed protective effects against AC. T1D was associated with an increased risk of OLP (IVW OR = 1.09, 95% CI 1.02-1.17, P = 0.007). The effect of T1D on AC and OLP remained robust after adjusting for FI, FG, and HbA1c, while T2D's effect on AC was not significant when considering these glycemic traits. No potential pleiotropy was detected (P > 0.05).

CONCLUSIONS

T1D may have a causal role in the development of OLP independent of glycemic traits, emphasizing the need for routine oral examinations in T1D patients. Conversely, genetically predicted T1D and T2D are significantly associated with a reduced risk of AC, challenging previous assumptions and offering new insights into the relationship between diabetes and OPMDs. Further extensive investigations are required to address the limitations of this study and to clarify these associations.

Exploring the Link Between Diabetes, Herpes Zoster, and Post-Herpetic Neuralgia: Insights From Mendelian Randomization

Background

Diabetes mellitus (DM), herpes zoster (HZ) and its sequelae, post-herpetic neuralgia (PHN), are common in elderly individuals. Previous observational studies have shown that the prevalence of HZ and PHN in conjunction with DM is increasing. Nonetheless, few studies have investigated the causal relationships between DM and the risk of HZ and PHN.

Methods

A two-sample Mendelian randomization (TSMR) analysis was conducted on genome-wide association study (GWAS) data. We obtained four separate datasets for DM: type 1 diabetes (T1D), type 2 diabetes (T2D), mother diabetes mellitus (mother-DM) and father diabetes mellitus (father-DM), and two independent datasets for HZ and anti-varicella-zoster virus IgG (VZV-IgG), a single GWAS for PHN. The inverse variance weighted (IVW), MR‒Egger, weighted median and weighted mode analyses were used to estimate the causality.

Results

Genetically predicted T1D increased the level of VZV-IgG (IVW: OR=1.011, 95% CI 1.006-1.016, P -FDR=8.44×10-6). T2D (IVW: OR=1.313; 95% CI 1.043-1.655, P -FDR=0.041), mother-DM (IVW: OR=7.909; 95% CI 1.232-50.777, P -FDR=0.039), and father-DM (IVW: OR=11.798; 95% CI 2.051-67.874, P -FDR=0.023) increased the risk of PHN. No reverse causality was found between HZ, PHN, and DM.

Conclusion

Our research reveals a causal link between genetically determined T1D and increased VZV-IgG levels. Additionally, genetically predicted T2D and a family history of DM increase the risk of PHN. These discoveries deepen our comprehension of the underlying causes of HZ and PHN.

Myokines as potential mediators of changes in glucose homeostasis and muscle mass after bariatric surgery

Myokines are bioactive peptides released by skeletal muscle. Myokines exert auto-, para-, or endocrine effects, enabling them to regulate many aspects of metabolism in various tissues. However, the contribution of myokines to the dramatic changes in glucose homeostasis and muscle mass induced by bariatric surgery has not been established. Our review highlights that myokines such as brain-derived neurotrophic factor (BDNF), meteorin-like protein (Metrnl), secreted protein acidic and rich in cysteine (SPARC), apelin (APLN) and myostatin (MSTN) may mediate changes in glucose homeostasis and muscle mass after bariatric surgery. Our review also identifies myonectin as an interesting candidate for future studies, as this myokine may regulate lipid metabolism and muscle mass after bariatric surgery. These myokines may provide novel therapeutic targets and biomarkers for obesity, type 2 diabetes and sarcopenia.

Exploring the Potential Effect of GLP1R Agonism on Common Aging-Related Diseases via Glucose Reduction: A Mendelian Randomization Study

BACKGROUND

Glucagon-like peptide-1 receptor agonists (GLP1RAs) are widely used in managing type 2 diabetes mellitus and weight control. Their potential in treating aging-related diseases has been gaining attention in recent years. However, the long-term effects of GLP1RAs on these diseases have yet to be fully revealed.

METHODS

Using a genetic variant in the GLP1R gene to model the long-term effects of GLP1RAs, this Mendelian randomization (MR) study systematically explored potential causal associations between GLP1R agonism and 12 aging-related diseases and indicators. Genetic summary data sets used in this study were obtained from previous genome-wide association studies.

RESULTS

The primary MR analysis results suggested that GLP1R agonism was potentially positively causally associated with appendicular lean mass (Beta = 0.246, 95% confidence interval [CI] = 0.096-0.396), whole-body fat-free mass (Beta = 0.202, 95% CI = 0.048-0.355), and lung function (forced vital capacity [FVC]; Beta = 0.179, 95% CI = 0.152-0.205; p < .05). Additionally, a potential negative causal association was observed with myocardial infarction (odds ratio = 0.430, 95% CI = 0.249-0.745; p < .05).

CONCLUSIONS

The present MR study provides exploratory evidence suggesting potential causal associations between GLP1R agonism and appendicular lean mass, whole-body fat-free mass, lung function (FVC), and myocardial infarction. Given the exploratory nature of these findings and the limitations of the MR methodology, further research is needed to validate these results and investigate the underlying biological mechanisms.

Genetic association studies using disease liabilities from deep neural networks

The case-control study is a widely used method for investigating the genetic underpinnings of binary traits. However, long-term, prospective cohort studies often grapple with absent or evolving health-related outcomes. Here, we propose two methods, liability and meta, for conducting genome-wide association studies (GWASs) that leverage disease liabilities calculated from deep patient phenotyping. Analyzing 38 common traits in ∼300,000 UK Biobank participants, we identified an increased number of loci in comparison to the number identified by the conventional case-control approach, and there were high replication rates in larger external GWASs. Further analyses confirmed the disease specificity of the genetic architecture; the meta method demonstrated higher robustness when phenotypes were imputed with low accuracy. Additionally, polygenic risk scores based on disease liabilities more effectively predicted newly diagnosed cases in the 2022 dataset, which were controls in the earlier 2019 dataset. Our findings demonstrate that integrating high-dimensional phenotypic data into deep neural networks enhances genetic association studies while capturing disease-relevant genetic architecture.

Body Fat Distribution and Ectopic Fat Accumulation as Mediator of Diabetogenic Action of Lipid-Modifying Drugs: A Mediation Mendelian Randomization Study

OBJECTIVE

To investigate the causal relationship between various lipid-modifying drugs and new-onset diabetes, as well as the mediators contributing to this relationship.

METHODS

Mediation Mendelian randomization was performed to investigate the causal effect of lipid-modifying drug targets on type 2 diabetes (T2D) outcomes and the proportion of this association that is mediated through ectopic fat accumulation traits. Specific sets of variants in or near genes that encode 11 lipid-modifying drug targets (LDLR, HMGCR, NPC1L1, PCSK9, APOB, ABCG5/ABCG8, LPL, PPARA, ANGPTL3, APOC3, and CETP; for expansion of gene symbols, use search tool at www.genenames.org) were extracted. Random effects inverse variance weighted were performed to evaluate the causal effects among outcomes. Mediation analyses were performed to identify the mediators of the association between lipid-modifying drugs and T2D. The study was conducted from November 10, 2023, to April 2, 2024 RESULTS: The genetic mimicry of HMGCR and APOB inhibition was associated with an increased T2D risk, whereas the genetic mimicry of LPL enhancement was linked to a lower T2D risk. Gluteofemoral adipose tissue volume was a mediator for explaining 9.52% (P=.002), 16.90% (P=.03), and 10.50% (P=.003) of the total effect of HMGCR, APOB, and LPL on T2D susceptibility, respectively. Liver fat was a mediator for explaining 21.12% (P=.005), 12.28% (P=.03), and 9.84% (P=.005) of the total effect of HMGCR, APOB, and LPL on T2D susceptibility, respectively.

CONCLUSION

Our findings support the hypothesis that liver fat and gluteofemoral adipose tissue play a mediating role in the prodiabetic effects of HMGCR and APOB inhibition, as well as in the antidiabetic effects of LPL enhancement.

Mediating factors in the association between educational attainment and stroke: A mendelian randomization study

Background

Stroke is a common cardiovascular and cerebrovascular disease with high disability and mortality. Lower educational attainment has been reported to be associated with an increased risk of stroke, but it is unclear which pathways mediate this association.

Methods

Using genome-wide association studies (GWAS) based on European ancestry, we performed two-sample Mendelian randomization (MR) analyses to investigate the causal association of genetically estimated educational attainment with stroke and its subtypes. Then, we used mediation analyses to assess the extent to which seven cardiometabolic risk factors alone and in combination explain their effects.

Results

Genetically estimated educational attainment was negatively associated with the risk of any stroke (AS), any ischemic stroke (AIS), ischemic stroke subtypes (large artery stroke [LAS], cardioembolic stroke [CES], and small vessel stroke [SVS]), and hemorrhagic stroke subtypes (cerebral hemorrhage [ICH] and subarachnoid hemorrhage [SAH]). For individual mediating effects, type 2 diabetes, hypertension, hyperlipidemia, and smoking mediated the impact of education on AS, AIS, and ischemic stroke subtypes, while obesity, NAFLD, and alcohol consumption played no role. For combined mediation, the proportion of the association that cardiometabolic mediators explained ranged from 4% (95% CI: 2.72%-5.27%) for SVS to 38.73% (95% CI: 37.42%-40.05%) for LAS. Nevertheless, they did not account for any of the estimates for hemorrhagic stroke subtypes.

Conclusion

Higher educational attainment would have a protective effect on stroke and its subtypes, and cardiometabolic risk factors mediated part proportion of this association. Hence, patients with low education should pay more attention to managing cardiometabolic diseases to prevent stroke.

Beyond guilty by association at scale: searching for causal variants on the basis of genome-wide summary statistics

Understanding the causal genetic architecture of complex phenotypes will fuel future research into disease mechanisms and potential therapies. Here, we illustrate the power of a novel framework: it detects, starting from summary statistics, and across the entire genome, sets of variants that carry non-redundant information on the phenotypes and are therefore more likely to be causal in a biological sense. The approach, implemented in open-source software, is also computationally efficient, requiring less than 15 minutes on a single CPU to perform genome-wide analysis. Through extensive genome-wide simulation studies, we show that the method can substantially outperform existing methods in false discovery rate control, statistical power and various fine-mapping criteria. In applications to a meta-analysis of ten large-scale genetic studies of Alzheimer's disease (AD), we identified 82 loci associated with AD, including 37 additional loci missed by conventional GWAS pipeline. Massively parallel reporter assays and CRISPR-Cas9 experiments have confirmed the functionality of the putative causal variants our method points to. Finally, we retrospectively analyzed summary statistics from 67 large-scale GWAS for a variety of phenotypes. Results reveal the method's capacity to robustly discover additional loci for polygenic traits and pinpoint potential causal variants underpinning each locus beyond conventional GWAS pipeline, contributing to a deeper understanding of complex genetic architectures in post-GWAS analyses.

Assessing causal relationships between diabetes mellitus and idiopathic pulmonary fibrosis: a Mendelian randomisation study

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a disease of progressive lung scarring. There is a known association between diabetes mellitus (DM) and IPF, but it is unclear whether a causal relationship exists between these traits.

OBJECTIVES

The objectives of this study are to examine causal relationships among DM, diabetes-associated traits and IPF using a Mendelian randomisation approach.

METHODS

Two-sample MR approaches, including bidirectional inverse-variance weighted random effects and routine sensitivity models, used genetic variants identified from genome-wide association studies for type 1 diabetes (T1D), type 2 diabetes (T2D), glycated haemoglobin level (HbA1c), fasting insulin level and body mass index (BMI) to assess for causal effects of these traits on IPF. Further analyses using pleiotropy-robust and multivariable MR (MVMR) methods were additionally performed to account for trait complexity.

RESULTS

Results did not suggest that either T1D (OR=1.00, 95% CI 0.93 to 1.07, p=0.90) or T2D (1.02, 0.93 to 1.11, p=0.69) are in the causal pathway of IPF. No effects were suggested of HbA1c (1.19, 0.63 to 2.22, p=0.59) or fasting insulin level (0.60, 0.31 to 1.15, p=0.12) on IPF, but potential effects of BMI on IPF were indicated (1.44, 1.12 to 1.85, p=4.00×10-3). Results were consistent in MVMR, although no independent effects of T2D (0.91, 0.68 to 1.21, p=0.51) or BMI (1.01, 0.94 to 1.09, p=0.82) on IPF were observed when modelled together.

CONCLUSIONS

This study suggests that DM and IPF are unlikely to be causally linked. This comorbid relationship may instead be driven by shared risk factors or treatment effects.

Insights Into Causal Effects of Genetically Proxied Lipids and Lipid-Modifying Drug Targets on Cardiometabolic Diseases

BACKGROUND

The differential impact of serum lipids and their targets for lipid modification on cardiometabolic disease risk is debated. This study used Mendelian randomization to investigate the causal relationships and underlying mechanisms.

METHODS

Genetic variants related to lipid profiles and targets for lipid modification were sourced from the Global Lipids Genetics Consortium. Summary data for 10 cardiometabolic diseases were compiled from both discovery and replication data sets. Expression quantitative trait loci data from relevant tissues were employed to evaluate significant lipid-modifying drug targets. Comprehensive analyses including colocalization, mediation, and bioinformatics were conducted to validate the results and investigate potential mediators and mechanisms.

RESULTS

Significant causal associations were identified between lipids, lipid-modifying drug targets, and various cardiometabolic diseases. Notably, genetic enhancement of LPL (lipoprotein lipase) was linked to reduced risks of myocardial infarction (odds ratio [OR]1, 0.65 [95% CI, 0.57-0.75], P1=2.60×10-9; OR2, 0.59 [95% CI, 0.49-0.72], P2=1.52×10-7), ischemic heart disease (OR1, 0.968 [95% CI, 0.962-0.975], P1=5.50×10-23; OR2, 0.64 [95% CI, 0.55-0.73], P2=1.72×10-10), and coronary heart disease (OR1, 0.980 [95% CI, 0.975-0.985], P1=3.63×10-14; OR2, 0.64 [95% CI, 0.54-0.75], P2=6.62×10-8) across 2 data sets. Moreover, significant Mendelian randomization and strong colocalization associations for the expression of LPL in blood and subcutaneous adipose tissue were linked with myocardial infarction (OR, 0.918 [95% CI, 0.872-0.967], P=1.24×10-3; PP.H4, 0.99) and coronary heart disease (OR, 0.991 [95% CI, 0.983-0.999], P=0.041; PP.H4=0.92). Glucose levels and blood pressure were identified as mediators in the total effect of LPL on cardiometabolic outcomes.

CONCLUSIONS

The study substantiates the causal role of lipids in specific cardiometabolic diseases, highlighting LPL as a potent drug target. The effects of LPL are suggested to be influenced by changes in glucose and blood pressure, providing insights into its mechanism of action.

Linking Genome-Wide Association Studies to Pharmacological Treatments for Psychiatric Disorders

Importance

Large-scale genome-wide association studies (GWAS) should ideally inform the development of pharmacological treatments, but whether GWAS-identified mechanisms of disease liability correspond to the pathophysiological processes targeted by current pharmacological treatments is unclear.

Objective

To investigate whether functional information from a range of open bioinformatics datasets can elucidate the relationship between GWAS-identified genetic variation and the genes targeted by current treatments for psychiatric disorders.

Design, Setting, and Participants

Associations between GWAS-identified genetic variation and pharmacological treatment targets were investigated across 4 psychiatric disorders-attention-deficit/hyperactivity disorder, bipolar disorder, schizophrenia, and major depressive disorder. Using a candidate set of 2232 genes listed as targets for all approved treatments in the DrugBank database, each gene was independently assigned 2 scores for each disorder-one based on its involvement as a treatment target and the other based on the mapping between GWAS-implicated single-nucleotide variants (SNVs) and genes according to 1 of 4 bioinformatic data modalities: SNV position, gene distance on the protein-protein interaction (PPI) network, brain expression quantitative trail locus (eQTL), and gene expression patterns across the brain. Study data were analyzed from November 2023 to September 2024.

Main Outcomes and Measures

Gene scores for pharmacological treatments and GWAS-implicated genes were compared using a measure of weighted similarity applying a stringent null hypothesis-testing framework that quantified the specificity of the match by comparing identified associations for a particular disorder with a randomly selected set of treatments.

Results

Incorporating information derived from functional bioinformatics data in the form of a PPI network revealed links for bipolar disorder (P permutation [P-perm] = 7 × 10-4; weighted similarity score, empirical [ρ-emp] = 0.1347; mean [SD] weighted similarity score, random [ρ-rand] = 0.0704 [0.0163]); however, the overall correspondence between treatment targets and GWAS-implicated genes in psychiatric disorders rarely exceeded null expectations. Exploratory analysis assessing the overlap between the GWAS-identified genetic architecture and treatment targets across disorders identified that most disorder pairs and mapping methods did not show a significant correspondence.

Conclusions and Relevance

In this bioinformatic study, the relatively low degree of correspondence across modalities suggests that the genetic architecture driving the risk for psychiatric disorders may be distinct from the pathophysiological mechanisms currently used for targeting symptom manifestations through pharmacological treatments. Novel approaches incorporating insights derived from GWAS based on refined phenotypes including treatment response may assist in mapping disorder risk genes to pharmacological treatments in the long term.

Systematic Mendelian Randomization Exploring Druggable Genes for Hemorrhagic Strokes

Patients with hemorrhagic stroke have high rates of morbidity and mortality, and drugs for prevention are very limited. Mendelian randomization (MR) analysis can increase the success rate of drug development by providing genetic evidence. Previous MR analyses only analyzed the role of individual drug target genes in hemorrhagic stroke; therefore, we used MR analysis to systematically explore the druggable genes for hemorrhagic stroke. We sequentially performed summary-data-based MR analysis and two-sample MR analysis to assess the associations of all genes within the database with intracranial aneurysm, intracerebral hemorrhage, and their subtypes. Validated genes were further analyzed by colocalization. Only genes that were positive in all three analyses and were druggable were considered desirable genes. We also explored the mediators of genes affecting hemorrhagic stroke incidence. Finally, the associations of druggable genes with other cardiovascular diseases were analyzed to assess potential side effects. We identified 56 genes that significantly affected hemorrhagic stroke incidence. Moreover, TNFSF12, SLC22A4, SPARC, KL, RELT, and ADORA3 were found to be druggable. The inhibition of TNFSF12, SLC22A4, and SPARC can reduce the risk of intracranial aneurysm, subarachnoid hemorrhage, and intracerebral hemorrhage. Gene-induced hypertension may be a potential mechanism by which these genes cause hemorrhagic stroke. We also found that blocking these genes may cause side effects, such as ischemic stroke and its subtypes. Our study revealed that six druggable genes were associated with hemorrhagic stroke, and the inhibition of TNFSF12, SLC22A4, and SPARC had preventive effects against hemorrhagic strokes.

Clinical research progress on β-cell dysfunction in T2DM development in the Chinese population

The prevalence of type-2 diabetes mellitus (T2DM) has increased over 10-fold in the past 40 years in China, which now has the largest T2DM population in the world. Insulin resistance and β-cell dysfunction are the typical features of T2DM. Although both factors play a role, decreased β-cell function and β-cell mass are the predominant factors for progression to T2DM. Considering the differences between Chinese T2DM patients and those of other ethnicities, it is important to characterize β-cell dysfunction in Chinese patients during T2DM progression. Herein, we reviewed the studies on the relationships between β-cell function and T2DM progression in the Chinese population and discussed the differences among individuals of varying ethnicities. Meanwhile, we summarized the risk factors and current treatments of T2DM in Chinese individuals and discussed their impacts on β-cell function with the hope of identifying a better T2DM therapy.

Additive Value of Polygenic Risk Score to Family History for Type 2 Diabetes Prediction: Results From the All of Us Research Database

OBJECTIVE

The goal of this study was to assess the additive value of considering type 2 diabetes (T2D) polygenic risk score (PRS) in addition to family history for T2D prediction.

RESEARCH DESIGN AND METHODS

Data were obtained from the All of Us (AoU) research database. First-degree T2D family history was self-reported on the personal family history health questionnaire. A PRS was constructed from 1,289 variants identified from a large multiancestry genome-wide association study meta-analysis for T2D. Logistic regression models were run to generate odds ratios (ORs) and 95% CIs for T2D. All models were adjusted for age, sex, and BMI.

RESULTS

A total of 109,958 AoU research participants were included in the analysis. The odds of T2D increased with 1 SD PRS (OR 1.75; 95% CI 1.71-1.79) and positive T2D family history (OR 2.32; 95% CI 2.20-2.43). In the joint model, both 1 SD PRS (OR 1.69; 95% CI 1.65-1.72) and family history (OR 2.06; 95% CI 1.98-2.15) were significantly associated with T2D, although the ORs were slightly attenuated. Predictive models that included both the PRS and family history (area under the curve [AUC] 0.794) performed better than models including only family history (AUC 0.763) or the PRS (AUC 0.785).

CONCLUSIONS

In predicting T2D, inclusion of a T2D PRS in addition to family history of T2D (first-degree relatives) added statistical value. Further study is needed to determine whether consideration of both family history and a PRS would be useful for clinical T2D prediction.

The Investigation of the Distribution of ABO/Rh Blood Group in Hospitalized COVID-19 Patients and Its Association With Disease Severity, Clinical Outcomes, Lab Tests, and Radiologic Findings

Background and Aims

it is important to identify patients at higher risk for severity and poor outcomes of COVID-19 infection, to have better disease management and pandemic control. In this study, we aimed to assess the distribution of ABO and Rh blood groups in hospitalized COVID-19 infected patients and demonstrate its association with severity and outcomes of the disease.

Methods

This is a cross-sectional study at Ziaeian Specialist Hospital, in Tehran, Iran. Of all confirmed COVID-19 infected patients who were admitted to this hospital, 273 patients were enrolled in this study and categorized based on their disease severity or clinical outcomes including intensive care unit (ICU) admission, need for mechanical ventilation and mortality. The distribution of ABO and Rh blood groups was assessed and compared between different groups, to investigate the association of blood group types with disease severity or outcomes. Also, the study population was categorized based on their blood group types to demonstrate the association of laboratory parameters, radiologic findings, and length of hospitalization with blood groups. Sex, age and underlying disease were adjusted in the final model by multivariate regression analysis.

Results

This study showed that Blood group A (35.9%) was the most prevalent among hospitalized COVID-19 patients followed by O (34.8%), B (21.6%), and AB (7.7%) (A > O > B > AB). ABO and Rh blood group was not associated with disease severity, need for mechanical ventilation, or ICU admission, while blood group B was associated with an increased risk of death in comparison with type O, in hospitalized COVID-19 patients (p = 0.02). The number of patients with severe levels of C-reactive protein (CRP) test results was lower in O blood group patients in comparison with non-O blood groups (p = 0.01).

Conclusion

No significant association was found between blood groups and other lab tests, radiologic findings, and length of hospitalization.

Association between subtypes of diabetes and special sensations: A 2-sample Mendelian randomization study

Diabetes, a chronic condition affecting millions of individuals, is divided into type 1 diabetes (T1D) and type 2 diabetes (T2D), each with unique pathophysiological characteristics. While the impact of diabetes on vision is established, its relationship with other special senses, balance, hearing, and olfaction, remains uncertain. This study utilized a 2-sample Mendelian randomization (MR) approach to investigate the associations between diabetes subtypes and specific sensory disorders. We performed MR analysis using various methods (inverse variance weighting [IVW], MR-Egger, simple mode, weighted mode, weighted median, MR-PRESSO) to assess the causal relationships between diabetes subtypes and sensory disorders (vestibular dysfunction, sensorineural hearing loss, conductive hearing loss, and olfactory dysfunction). Different diabetes genome-wide association studies datasets were utilized for validation. MR analysis revealed no significant correlations between T1D or T2D and the sensory disorders studied. Interestingly, an initial signal suggested that T1D might increase the risk of conductive hearing loss (IVW: odds ratio = 1.120, 95% CI: 1.035-1.211, P = .005), but this finding was not supported by validation studies. No evidence of horizontal pleiotropy or heterogeneity was found (P > .05). Our MR analysis and subsequent validation revealed no significant associations between diabetes subtypes and special senses. The initial suggestion of an increased risk of conductive hearing loss in T1D patients was not confirmed. Future research should further explore the intricate relationships among diabetes, sensory functions, and other factors, as well as the potential effects of diabetes management on sensory health.

The link between the ANPEP gene and type 2 diabetes mellitus may be mediated by the disruption of glutathione metabolism and redox homeostasis

Aminopeptidase N (ANPEP), a membrane-associated ectoenzyme, has been identified as a susceptibility gene for type 2 diabetes (T2D) by genome-wide association and transcriptome studies; however, the mechanisms by which this gene contributes to disease pathogenesis remain unclear. The aim of this study was to determine the comprehensive contribution of ANPEP polymorphisms to T2D risk and annotate the underlying mechanisms. A total of 3206 unrelated individuals including 1579 T2D patients and 1627 controls were recruited for the study. Twenty-three common functional single nucleotide polymorphisms (SNP) of ANPEP were genotyped by the MassArray-4 system. Six polymorphisms, rs11073891, rs12898828, rs12148357, rs9920421, rs7111, and rs25653, were found to be associated with type 2 diabetes (Pperm ≤ 0.05). Common haplotype rs9920421G-rs4932143G-rs7111T was strongly associated with increased risk of T2D (Pperm = 5.9 × 10-12), whereas two rare haplotypes such as rs9920421G-rs4932143C-rs7111T (Pperm = 6.5 × 10-40) and rs12442778A-rs12898828A-rs6496608T-rs11073891C (Pperm = 1.0 × 10-7) possessed strong protection against disease. We identified 38 and 109 diplotypes associated with T2D risk in males and females, respectively (FDR ≤ 0.05). ANPEP polymorphisms showed associations with plasma levels of fasting blood glucose, aspartate aminotransferase, total protein and glutathione (P < 0.05), and several haplotypes were strongly associated with the levels of reactive oxygen species and uric acid (P < 0.0001). A deep literature analysis has facilitated the formulation of a hypothesis proposing that increased plasma levels of ANPEP as well as liver enzymes such as aspartate aminotransferase, alanine aminotransferase and gammaglutamyltransferase serve as an adaptive response directed towards the restoration of glutathione deficiency in diabetics by stimulating the production of amino acid precursors for glutathione biosynthesis.

Genetic insights into the risk of hip osteoarthritis on stroke: A single-variable and multivariable Mendelian randomization

BACKGROUND

Hip osteoarthritis has been identified as a potential risk factor for stroke, with previous studies have demonstrated an association between hip osteoarthritis and stroke. This study aims to further elucidate the causal relationship between the two, employing Two-Sample and Multivariable Mendelian randomization methods.

METHODS

SNPs, derived from two extensive GWAS, served as instruments in exploring the association between genetically predicted hip osteoarthritis and stroke risk, utilizing two-sample Mendelian randomization. In Multivariable Mendelian randomization, factors such as cigarettes per day, alcoholic drinks per week, hypertension, body mass index, type 2 diabetes, C-reactive protein, rheumatoid arthritis were incorporated to further account for the independent causal effects of multiple correlated exposures.

RESULTS

Two-sample Mendelian randomization analysis revealed that hip osteoarthritis exerts a potential causal effect on any stroke, any ischemic stroke, and cardioembolic stroke, while it did not influence large artery stroke and small vessel stroke. Multivariable MR analysis indicated that the causal effect of hip osteoarthritis on any ischemic stroke and cardioembolic stroke was no longer evident after adjusting for C-reactive protein, and similarly, the effect on any ischemic stroke was not observed after adjusting for type 2 diabetes. However, the effects on any stroke, any ischemic stroke, and cardioembolic stroke remained significant after adjustments for hypertension, alcoholic drinks per week, cigarettes per day, body mass index, and rheumatoid arthritis.

CONCLUSION

The study demonstrated that elevated hip osteoarthritis, as predicted by genetic factors, was potential associated with an increased risk of any stroke, any ischemic stroke, and cardioembolic stroke, but showed no correlation with hypertension, alcoholic drinks per week, cigarettes per day, type 2 diabetes, C-reactive protein, body mass index levels, and rheumatoid arthritis.

GWAS highlights the neuronal contribution to multiple sclerosis susceptibility

Multiple Sclerosis (MS) is a chronic inflammatory and neurodegenerative disease affecting the brain and spinal cord. Genetic studies have identified many risk loci, that were thought to primarily impact immune cells and microglia. Here, we performed a multi-ancestry genome-wide association study with 20,831 MS and 729,220 control participants, identifying 236 susceptibility variants outside the Major Histocompatibility Complex, including four novel loci. We derived a polygenic score for MS and, optimized for European ancestry, it is informative for African-American and Latino participants. Integrating single-cell data from blood and brain tissue, we identified 76 genes affected by MS risk variants. Notably, while T cells showed the strongest enrichment, inhibitory neurons emerged as a key cell type. The expression of IL7 and STAT3 are affected only in inhibitory neurons, highlighting the importance of neuronal and glial dysfunction in MS susceptibility.

Rheumatoid Arthritis, Circulating Inflammatory Proteins, and Hypertension: A Mendelian Randomization Study

Observational studies have indicated that there is an association between rheumatoid arthritis (RA) and an elevated risk of hypertension. However, a definitive causal relationship between the two conditions has not been established. The objective of this study was to investigate the causal link between RA and hypertension, as well as the potential mediating role of circulating inflammatory proteins in this relationship. We utilized Mendelian randomization (MR) to examine the causal relationship between RA and hypertension. The study data were obtained from publicly accessible genome-wide association study (GWAS) databases and meta-aggregates of large GWAS studies. The primary statistical method for determining causal effects was the inverse variance weighted (IVW) method, which was supplemented by a variety of sensitivity analyses. The results of the IVW method suggest a causal relationship between RA and an increased risk of hypertension (OR = 1.03, 95% CI = 1.01-1.04, p = 3.32 × 10-5). This association remained statistically significant even after adjusting for multiple confounding factors. Furthermore, MR analyses also revealed causal links between 10 circulating inflammatory proteins and the risk of hypertension, with TNF-related activation-induced cytokine partially mediating RA-induced hypertension at a mediator ratio of 11.17% (0.27%-22.08%). Our study identifies causal relationships between several genetically determined inflammatory proteins and hypertension, establishing that RA increases hypertension risk, with inflammation partially mediating this effect. These findings provide new evidence supporting the inflammatory hypothesis in the mechanism of hypertension. Inflammatory factors may serve as potential targets for antihypertensive therapy.

Gender-specific genetic influence of rs1111875 on diabetes risk: Insights from the Taiwan biobank study

BACKGROUND

This study investigates the gender-specific genetic influence of the single nucleotide polymorphism (SNP) rs1111875 on diabetes risk within the Taiwanese population using data from the Taiwan Biobank. Diabetes mellitus, particularly type 2 diabetes (T2D), is influenced by genetic factors, and the rs1111875 SNP near the hematopoietically expressed homeobox (HHEX) gene has been linked to T2D susceptibility.

METHODS

The study included 69,272 participants after excluding those from arsenic-polluted areas and those with incomplete data. Logistic regression models were used for analyses.

RESULTS

The analyses revealed that the CT genotype of rs1111875 was associated with an increased risk of diabetes (OR = 1.092, 95% CI = 1.030-1.157, P = 0.003), as was the TT genotype (OR = 1.280, 95% CI = 1.165-1.407, P < 0.001). The effect was more pronounced in women (CT: OR = 1.118, 95% CI = 1.036-1.207, P = 0.004; TT: OR = 1.404, 95% CI = 1.243-1.585, P < 0.001). Men exhibited a higher overall risk of diabetes (OR = 1.565, 95% CI = 1.445-1.694, P < 0.001) and had a higher prevalence (12.71% vs 7.80%, P < 0.001) compared to women.

CONCLUSIONS

The findings underscore the importance of considering gender differences in genetic studies of diabetes and suggest that personalized diabetes management strategies should account for both genetic and gender-specific risk factors. This research contributes to the broader understanding of genetic determinants of diabetes and their interaction with gender, aiming to enhance personalized healthcare strategies for diabetes prevention and treatment.

Balanced diets are associated with a lower risk of type 2 diabetes than plant-based diets

BACKGROUND & AIMS

Plant-based diets benefit human health, while the deficient in some nutrients limits its application. We aimed to examine whether balanced diets could be better in reducing diabetes risk than plant-based diets.

METHODS

In cross-sectional analysis of Environment-Inflammation-Metabolic-Diseases Study (EIMDS), we used a questionnaire to investigate the habit of balanced and plant-based diets. In the prospective analysis of UK Biobank, we used the plant-based diet index of health (hPDI) and unhealth (uPDI) to evaluate the plant-based diets, and defined the balanced diet as a daily intake of 5 categories and at least 12 types of food. After analyzing proteomic data in UK Biobank, we explored the causal relationship between signature proteins of balanced diets and incident diabetes based on summary-data-based Mendelian randomization (SMR).

RESULTS

Compared to participants who had plant-based diets, those who had balanced diets showed a lower risk of diabetes in EIMDS (Odd Ratio 0.65, 95%CI 0.44-0.95). In UK Biobank, after excluding participants with unhealthy plant-based diets, participants with balanced diets still showed a lower diabetes risk than participants with plant-based diets (Hazard Ratio 0.86, 95%CI 0.77-0.95). Proteomic analysis identified 107 downregulated and 2 upregulated proteins that were associated with higher and lower risk of diabetes, respectively. In SMR analyses, the downregulated signature proteins of balanced diets (AGR2, DBI, IL17RA and SERPINH1) were causally associated with diabetes incidence.

CONCLUSION

Adhered to a balanced diet is associated with a lower risk of diabetes compared to plant-based diet, which might be attributed to signature proteins such as AGR2, DBI, IL17RA and SERPINH1.

Relationships between orofacial pain and sleep: Analysis of UK biobank and genome-wide association studies data

Background/purpose

Orofacial pain is common in dental practices. This study aimed to explore relationships between orofacial pain and sleep using the UK Biobank dataset and, based on epidemiological associations, to investigate the causal association using genome-wide association studies data.

Materials and methods

First, a cross-sectional study was conducted with 196,490 participants from UK Biobank. Information on pain conditions and sleep traits was collected. Multivariable models were used to explore the relationships with odds ratio (OR). Second, Mendelian randomization analyses were conducted using data for orofacial pain, including temporomandibular joint disorders-related pain (n = 377,277) and atypical facial pain (n = 331,749), and sleep traits, including sleep duration (n = 446,118), short sleep (n = 411,934), long sleep (n = 339,926), snoring (n = 359,916), ease of getting up (n = 385,949), insomnia (n = 453,379), daytime dozing (n = 452,071), daytime napping (n = 452,633), and chronotype (n = 403,195).

Results

The cross-sectional study confirmed the bidirectionality between pain and sleep. Participants experiencing pain all over the body showed a significant association with an unhealthy sleep pattern (OR = 1.18, P < 0.001) and other sleep traits (P < 0.05). Risks of chronic orofacial pain were associated with sleep duration in a non-linear relationship (P = 0.032). The Mendelian randomization analyses indicated that long sleep was causally associated with temporomandibular joint disorders-related pain (OR = 6.77, P = 0.006).

Conclusion

The relationship between pain and sleep is bidirectional. Long sleep is found to be causally associated with chronic orofacial pain.

GWAS highlights the neuronal contribution to multiple sclerosis susceptibility

Multiple Sclerosis (MS) is a chronic inflammatory and neurodegenerative disease affecting the brain and spinal cord. Genetic studies have identified many risk loci, that were thought to primarily impact immune cells and microglia. Here, we performed a multi-ancestry genome-wide association study with 20,831 MS and 729,220 control participants, identifying 236 susceptibility variants outside the Major Histocompatibility Complex, including four novel loci. We derived a polygenic score for MS and, optimized for European ancestry, it is informative for African-American and Latino participants. Integrating single-cell data from blood and brain tissue, we identified 76 genes affected by MS risk variants. Notably, while T cells showed the strongest enrichment, inhibitory neurons emerged as a key cell type, highlighting the importance of neuronal and glial dysfunction in MS susceptibility.

Causal Association Between Sedentary Behaviors and Health Outcomes: A Systematic Review and Meta-Analysis of Mendelian Randomization Studies

BACKGROUND

Different types of sedentary behavior are associated with several health outcomes, but the causality of these associations remains unclear.

OBJECTIVES

To conduct a systematic review and meta-analysis of Mendelian randomization (MR) studies investigating the associations between sedentary behaviors and health outcomes.

METHODS

A systematic search on PubMed, Embase, Web of Science, Scopus, and PsycINFO up to August 2023 was conducted to identify eligible MR studies. We selected studies that assessed associations of genetically determined sedentary behaviors and health outcomes. A meta-analysis was conducted to examine the causal associations when two or more MR studies were available. We graded the evidence level of each MR association based on the results of the main method and sensitivity analyses in MR studies.

RESULTS

A total of 31 studies with 168 MR associations between six types of sedentary behavior and 47 health outcomes were included. Results from meta-analyses suggested a total of 47 significant causal associations between sedentary behaviors and health outcomes. Notably, more leisure TV watching is robustly correlated with increased risks of myocardial infarction, coronary artery disease, all-cause ischemic stroke, and type 2 diabetes. Conversely, robust inverse associations were observed between leisure computer use and risks of rheumatoid arthritis, Alzheimer's disease, and gastroesophageal reflux disease.

CONCLUSION

These findings suggest that different types of sedentary behavior have distinct causal effects on health outcomes. Therefore, interventions should focus not only on reducing sedentary time but also on promoting healthier types of sedentary behavior.

PROSPERO REGISTRATION

CRD42023453828.

Role of human plasma metabolites in prediabetes and type 2 diabetes from the IMI-DIRECT study

AIMS/HYPOTHESIS

Type 2 diabetes is a chronic condition that is caused by hyperglycaemia. Our aim was to characterise the metabolomics to find their association with the glycaemic spectrum and find a causal relationship between metabolites and type 2 diabetes.

METHODS

As part of the Innovative Medicines Initiative - Diabetes Research on Patient Stratification (IMI-DIRECT) consortium, 3000 plasma samples were measured with the Biocrates AbsoluteIDQ p150 Kit and Metabolon analytics. A total of 911 metabolites (132 targeted metabolomics, 779 untargeted metabolomics) passed the quality control. Multivariable linear and logistic regression analysis estimates were calculated from the concentration/peak areas of each metabolite as an explanatory variable and the glycaemic status as a dependent variable. This analysis was adjusted for age, sex, BMI, study centre in the basic model, and additionally for alcohol, smoking, BP, fasting HDL-cholesterol and fasting triacylglycerol in the full model. Statistical significance was Bonferroni corrected throughout. Beyond associations, we investigated the mediation effect and causal effects for which causal mediation test and two-sample Mendelian randomisation (2SMR) methods were used, respectively.

RESULTS

In the targeted metabolomics, we observed four (15), 34 (99) and 50 (108) metabolites (number of metabolites observed in untargeted metabolomics appear in parentheses) that were significantly different when comparing normal glucose regulation vs impaired glucose regulation/prediabetes, normal glucose regulation vs type 2 diabetes, and impaired glucose regulation vs type 2 diabetes, respectively. Significant metabolites were mainly branched-chain amino acids (BCAAs), with some derivatised BCAAs, lipids, xenobiotics and a few unknowns. Metabolites such as lysophosphatidylcholine a C17:0, sum of hexoses, amino acids from BCAA metabolism (including leucine, isoleucine, valine, N-lactoylvaline, N-lactoylleucine and formiminoglutamate) and lactate, as well as an unknown metabolite (X-24295), were associated with HbA1c progression rate and were significant mediators of type 2 diabetes from baseline to 18 and 48 months of follow-up. 2SMR was used to estimate the causal effect of an exposure on an outcome using summary statistics from UK Biobank genome-wide association studies. We found that type 2 diabetes had a causal effect on the levels of three metabolites (hexose, glutamate and caproate [fatty acid (FA) 6:0]), whereas lipids such as specific phosphatidylcholines (PCs) (namely PC aa C36:2, PC aa C36:5, PC ae C36:3 and PC ae C34:3) as well as the two n-3 fatty acids stearidonate (18:4n3) and docosapentaenoate (22:5n3) potentially had a causal role in the development of type 2 diabetes.

CONCLUSIONS/INTERPRETATION

Our findings identify known BCAAs and lipids, along with novel N-lactoyl-amino acid metabolites, significantly associated with prediabetes and diabetes, that mediate the effect of diabetes from baseline to follow-up (18 and 48 months). Causal inference using genetic variants shows the role of lipid metabolism and n-3 fatty acids as being causal for metabolite-to-type 2 diabetes whereas the sum of hexoses is causal for type 2 diabetes-to-metabolite. Identified metabolite markers are useful for stratifying individuals based on their risk progression and should enable targeted interventions.

Bivariate genome-wide association study of circulating fibrinogen and C-reactive protein levels

BACKGROUND

Fibrinogen and C-reactive protein (CRP) play an important role in inflammatory pathways and share multiple genetic loci reported in previously published genome-wide association studies (GWAS), highlighting their common genetic background. Leveraging the shared biology may identify further loci pleiotropically associated with both fibrinogen and CRP.

OBJECTIVES

To identify novel genetic variants that are pleiotropic and associated with both fibrinogen and CRP, by integrating both phenotypes in a bivariate GWAS by using a multitrait GWAS.

METHODS

We performed a bivariate GWAS to identify further pleiotropic genetic loci, using summary statistics of previously published GWAS on fibrinogen (n = 120 246) from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium, consisting of European ancestry samples and CRP (n = 363 228) from UK Biobank, including 5 different population groups. The main analysis was performed using metaUSAT and N-GWAMA. We conducted replication for novel CRP associations to test the robustness of the findings using an independent GWAS for CRP (n = 148 164). We also performed colocalization analysis to compare the associations in identified loci for the 2 traits and Genotype-Tissue Expression data.

RESULTS

We identified 87 pleiotropic loci that overlapped between metaUSAT and N-GWAMA, including 23 previously known for either fibrinogen or CRP, 58 novel loci for fibrinogen, and 6 novel loci for both fibrinogen and CRP. Overall, there were 30 pleiotropic and novel loci for both traits, and 7 of these showed evidence of colocalization, located in or near ZZZ3, NR1I2, RP11-72L22.1, MICU1, ARL14EP, SOCS2, and PGM5. Among these 30 loci, 13 replicated for CRP in an independent CRP GWAS.

CONCLUSION

Bivariate GWAS identified additional associated loci for fibrinogen and CRP. This analysis suggests fibrinogen and CRP share a common genetic architecture with many pleiotropic loci.

Association between walking pace and heart failure: A Mendelian randomization analysis

BACKGROUND AND AIM

The relationship between walking pace and heart failure (HF) has been recognized, yet the directionality and underlying mediating risk factors remain unclear.

METHODS AND RESULTS

This study utilized bidirectional two-sample Mendelian randomization (MR) with genome-wide association studies (GWAS) summary statistics to assess the causal relationships between walking pace and HF. Additionally, we employed a two-step Multivariable Mendelian Randomization (MVMR) to explore potential mediating factors. We further validated our findings by conducting two-sample MR with another available GWAS summary data on heart failure. Results indicated that genetically predicted increases in walking pace were associated with a reduced risk of HF (odds ratio (OR), 0.589, 95% confidence interval (CI): 0.417-0.832). Among the considered mediators, the waist-to-hip ratio (WHR) accounts for the largest proportion of the effect (45.7%, 95% CI: 13.2%, 78.2%). This is followed by type 2 diabetes at 24.4% (95% CI: 6.7%, 42.0%) and triglycerides at 18.6% (95% CI: 4.5%, 32.7%). Furthermore, our findings reveal that genetically predicted HF risk (OR, 0.975, 95% CI: 0.960-0.991) is associated with a slower walking pace. Validated findings were consistent with the main results.

CONCLUSIONS

In conclusion, MR analysis demonstrates that a slow walking pace is a reliable indicator of an elevated risk of HF, and the causal relationship is bidirectional. Interventions focusing on waist-to-hip ratio, type 2 diabetes, and triglycerides may provide valuable strategies for HF prevention in individuals with a slow walking pace.

Associations between polygenic risk scores for cardiometabolic phenotypes and adolescent depression and body dissatisfaction

BACKGROUND

Adolescents with elevated body mass index (BMI) are at an increased risk for depression and body dissatisfaction. Type 2 diabetes (T2D) is an established risk factor for depression. However, shared genetic risk between cardiometabolic conditions and mental health outcomes remains understudied in youth.

METHODS

The current study examined associations between polygenic risk scores (PRS) for BMI and T2D, and symptoms of depression and body dissatisfaction, in a sample of 827 community adolescents (Mage = 13.63, SDage = 1.01; 76% girls). BMI, depressive symptoms, and body dissatisfaction were assessed using validated self-report questionnaires.

RESULTS

BMI-PRS was associated with phenotypic BMI (β = 0.24, p < 0.001) and body dissatisfaction (β = 0.17, p < 0.001), but not with depressive symptoms. The association between BMI-PRS and body dissatisfaction was significantly mediated by BMI (indirect effect = 0.10, CI [0.07-0.13]). T2D-PRS was not associated with depression or body dissatisfaction.

CONCLUSIONS

The results suggest phenotypic BMI may largely explain the association between genetic risk for elevated BMI and body dissatisfaction in adolescents. Further research on age-specific genetic effects is needed, as summary statistics from adult discovery samples may have limited utility in youth.

IMPACT

The association between genetic risk for elevated BMI and body dissatisfaction in adolescents may be largely explained by phenotypic BMI, indicating a potential pathway through which genetic predisposition influences body image perception. Furthermore, age-specific genetic research is needed to understand the unique influences on health outcomes during adolescence. By identifying BMI as a potential mediator in the association between genetic risk for elevated BMI and body dissatisfaction, the current findings offer insights that could inform interventions targeting body image concerns and mental health in this population.

Serum liver enzymes and risk of stroke: Systematic review with meta-analyses and Mendelian randomization studies

BACKGROUND AND PURPOSE

Previous observational studies have identified correlations between liver enzyme levels and stroke risk. However, the strength and consistency of these associations vary. To comprehensively evaluate the relationship between liver enzymes and stroke risk, we conducted meta-analyses complemented by Mendelian randomization (MR) analyses.

METHODS

Following the PRISMA guidelines, we performed meta-analyses of prospective studies and conducted subgroup analyses stratified by sex and stroke subtype. Subsequently, adhering to the STROBE-MR guidelines, we performed two-sample bidirectional univariable MR (UVMR) and multivariable MR (MVMR) analyses using the largest genome-wide association studies summary data. Finally, the single-nucleotide polymorphisms associated with liver enzymes on sex differences underwent gene annotation, gene set enrichment, and tissue enrichment analyses.

RESULTS

In the meta-analyses of 17 prospective studies, we found the relative risks for serum γ-glutamyl transferase (GGT) and alkaline phosphatase (ALP) were 1.23 (95% CI: 1.16-1.31) and 1.3 (95% CI: 1.19-1.43), respectively. Subgroup analyses revealed sex and stroke subtype differences in liver enzyme-related stroke risk. Bidirectional UVMR analyses confirmed that elevated GGT, alanine aminotransferase, and aspartate aminotransferase levels were associated with increased stroke occurrence. The primary results from the MVMR analyses revealed that higher ALP levels significantly increased the risk of stroke and ischemic stroke. Gene set and tissue enrichment analyses supported genetic differences in liver enzymes across sexes.

CONCLUSIONS

Our study provides evidence linking liver enzyme levels to stroke risk, suggesting liver enzymes as potential biomarkers for early identification of high-risk individuals. Personalized, sex-specific interventions targeting liver enzymes could offer new strategies for stroke prevention.

Styrene and ethylbenzene exposure and type 2 diabetes mellitus: A longitudinal gene-environment interaction study

Styrene and ethylbenzene (S/EB) are identified as hazardous air contaminants that raise significant concerns. The association between S/EB exposure and the incidence of type 2 diabetes mellitus (T2DM), and the interaction between genes and environment, remains poorly understood. Our study consisted of 2219 Chinese adults who were part of the Wuhan-Zhuhai cohort. A follow-up assessment was conducted after six years. Exposure to S/EB was quantified by determining the concentrations of urinary biomarkers of exposure to S/EB (UBE-S/EB; urinary phenylglyoxylic acid level plus urinary mandelic acid level). Logistic regression models were constructed to investigate the relations of UBE-S/EB and genetic risk score (GRS) with T2DM prevalence and incidence. The interaction effects of UBE-S/EB and GRS on T2DM were investigated on multiplicative and additive scales. UBE-S/EB was dose-dependently and positively related to T2DM prevalence and incidence. Participants with high levels of UBE-S/EB [relative risk (RR) = 1.930, 95% confidence interval (CI): 1.157-3.309] or GRS (1.943, 1.110-3.462) demonstrated the highest risk of incident T2DM, in comparison to those with low levels of UBE-S/EB or GRS. Significant additive interaction between UBE-S/EB and GRS on T2DM incidence was discovered with relative excess risk due to interaction (95% CI) of 0.178 (0.065-0.292). The RR (95% CI) of T2DM incidence was 2.602 (1.238-6.140) for individuals with high UBE-S/EB and high GRS, compared to those with low UBE-S/EB and low GRS. This study presented the initial evidence that S/EB exposure was significantly related to increased risk of T2DM incidence, and the relationship was interactively aggravated by genetic predisposition.

Relationship between socioeconomic status and stroke: An observational and network Mendelian randomization study

BACKGROUND

The relationship between socioeconomic status (SES) and stroke remains controversial, and the underlying mediator is unclear. This study aimed to assess the causal relationship of SES with stroke and its subtypes and to identify potential modifiable risk factors responsible for this relationship.

METHODS

The study included 372,437 participants from the UK Biobank. Over an average period of 12.13 years, 6,457 individuals (2.7 %) were recorded as having experienced a stroke. Cox proportional hazards model was used to determine the relationship between SES (average annual household income before tax and age at the end of full-time education) and stroke, ischemic stroke, and hemorrhagic stroke. Two-sample Mendelian randomization (MR) was employed to assess the causal relationship between SES and stroke and its subtypes. Furthermore, network MR was utilized to evaluate the potential mediating role of modifiable risk factors for stroke in this causal relationship.

RESULTS

After adjusting for factors such as sociodemographic characteristics, health behaviors, health status, and past medical history, participants in the second highest income group showed the lowest risk of stroke, with a hazard ratio (HR) of 0.780 (95 % confidence interval [CI]: 0.702-0.866), and for ischemic stroke, the HR was 0.701 (95 % CI: 0.618-0.795). Those who completed full-time education at the latest age group(>18 years) had the lowest risk of stroke (HR: 0.906, 95 % CI: 0.830-0.988) and ischemic stroke (HR: 0.897, 95% CI: 0.811-0.992). MR analysis showed that higher income and education were both associated with a lower risk of stroke (income: inverse-variance-weighted odds ratio [ORIVW] =0.796, 95 % CI: 0.675-0.940, education: ORIVW = 0.631, 95 % CI: 0.557-0.716) and ischemic stroke (income: ORIVW = 0.813, 95 % CI: 0.684-0.966, education: ORIVW = 0.641, 95 % CI: 0.559-0.735). Additionally, hypertension had the highest mediating effect on this relationship. It accounted for 57.12 % of the effect of income on stroke, 51.24 % on ischemic stroke, and 27 % and 24 % for education.

CONCLUSION

Higher SES was associated with a lower risk of stroke and ischemic stroke, and hypertension had the highest mediating effect on this causal relationship. The results have significant public health implications, emphasizing the importance of early intervention to reduce the risk of stroke in low SES populations.

The causal relationship between type 2 diabetes mellitus and isolated REM sleep behavior disorder: results from multivariable and network Mendelian randomization analysis

Objectives

To investigate the causal relationship between type 2 diabetes mellitus (T2DM, exposure) and isolated REM sleep behavior disorder (iRBD, outcome).

Methods

Genome-wide association study (GWAS) data for iRBD comprised 9,447 samples, including 1,061 iRBD cases from the International RBD Study Group. Initially, we performed linkage disequilibrium score regression (LDSC) to explore the genetic correlation between T2DM and iRBD. Then the two-sample univariate MR (UVMR) analysis was conducted to examine the effects of T2DM and blood sugar metabolism-related factors on iRBD. Subsequently, we applied multivariable MR (MVMR) methods to further adjust for confounders. Lastly, we executed a network MR analysis, with cytokines and immune cell characteristics as potential mediators, aiming to investigate indirect effect of T2DM on iRBD.

Results

Results from LDSC suggest a genetic correlation between T2DM and iRBD (rg=0.306, P=0.029). UVMR analysis indicates that both T2DM (Odds Ratio [95% Confidence Interval] = 1.19 [1.03, 1.37], P = 0.017) and high blood glucose levels (1.55 [1.04, 2.30], P = 0.032) are risk factors for iRBD. Even after adjusting for confounders in MVMR, the association between T2DM and iRBD remains robust. Finally, results from network MR analysis suggest that T2DM may indirectly promote the development of iRBD by reducing levels of Stromal Cell-Derived Factor 2 in circulation and by increasing BAFF-receptor expression in IgD- CD38- B cells.

Conclusions

T2DM may promote the onset of iRBD by influencing immune-inflammatory responses. Our findings provide valuable insights and directions for understanding the pathogenesis of iRBD, identifying high-risk groups, and discovering new therapeutic targets.

Impact of diabetes mellitus on the risk of Alzheimer's disease: a mendelian randomization study

BACKGROUND

The impact of diabetes on the risk of Alzheimer's disease remains uncertain. This study aimed to explore this issue from multiple perspectives by using the Mendelian randomization (MR) approach.

METHODS

Instrumental variables for predicting six diabetic traits (including insulin and blood glucose), eight metabolic risk factors for diabetes (including total cholesterol and blood pressure), and seven diabetic genes were extracted from their summary data. These data were derived from multiple European cohorts and included 31,684 to 810,865 subjects respectively. The two-sample MR, multivariate MR, and summary-data-based Mendelian randomization (SMR) methods were employed to determine the associations of these traits or genes with the risk of Alzheimer's disease.

RESULTS

The two-sample MR showed that elevated fasting insulin and total cholesterol levels were associated with an increased risk of dementia in Alzheimer's disease (P = 0.022, P = 0.041). Elevated systolic and diastolic blood pressure levels were associated with a decreased risk of dementia in Alzheimer's disease (P = 0.036, P = 0.025). The multivariate MR reported that adjusting for telomere length (a well-established biomarker of aging) did not change these findings (P < 0.05). Additionally, the two-sample MR showed that type 1 and type 2 diabetes did not affect the risk of Alzheimer's disease. The SMR also indicated that the diabetic genes did not affect the risk of this disease.

CONCLUSION

Multiple MR approaches concluded that fasting insulin, total cholesterol, and blood pressure, rather than diabetes, were potential metabolic variables that had an impact on the risk of Alzheimer's disease. However, aging might not be involved in these correlations.