Associations of polymorphisms in the candidate genes for Alzheimer's disease BIN1, CLU, CR1 and PICALM with gestational diabetes and impaired glucose tolerance

Gestational diabetes mellitus is associated with greater incidence of dementia during long-term post-partum follow-up

BACKGROUND

The impact of gestational diabetes mellitus (GDM) on incident dementia is unknown. Our aim was to evaluate the relationship between GDM and all-cause dementia and the mediating effects of chronic diseases on this relationship.

METHODS

This prospective cohort study included women from the UK Biobank who were grouped based on GDM history. Multivariate Cox proportional hazard models were used to explore the associations between GDM and dementia. We further analysed the mediating effects of chronic diseases on this relationship and the interactions of covariates.

RESULTS

A total of 1292 women with and 204,171 women without a history of GDM were included. During a median follow-up period of 45 years after first birth, 2921 women were diagnosed with dementia. Women with a GDM history had a 67% increased risk of incident dementia (hazard ratio 1.67, 95% confidence interval: 1.03-2.69) compared with those without a GDM history. According to mediation analyses, type 2 diabetes, coronary heart disease, chronic kidney disease and comorbidities (diagnosed with any two of the three diseases) explained 34.5%, 8.4%, 5.2% and 18.8% of the mediating effect on the relationship. Subgroup analyses revealed that physical activity modified the association between GDM history and dementia (p for interaction = 0.030). Among physically inactive women, GDM was significantly associated with incident dementia; however, this association was not observed among physically active women.

CONCLUSIONS

A history of GDM was associated with a greater risk of incident dementia. Type 2 diabetes partially mediated this relationship. Strategies for dementia prevention might be considered for women with a history of GDM.

Beyond sex differences: short- and long-term effects of pregnancy on the brain

Growing attention has been directed to the inclusion of females in neuroscience studies, and to the importance of studying sex as a biological variable. However, how female-specific factors such as menopause and pregnancy, affect the brain remains understudied. In this review, we use pregnancy as a case in point of a female-unique experience that can alter neuroplasticity, neuroinflammation, and cognition. We examine studies in both humans and rodents indicating that pregnancy can modify neural function in the short term, as well as alter the trajectory of brain aging. Furthermore, we discuss the influence of maternal age, fetal sex, number of pregnancies, and presence of pregnancy complications on brain health outcomes. We conclude by encouraging the scientific community to prioritize researching female health by recognizing and including factors such as pregnancy history in research.

Associations between parenthood and dementia in men and women: biology or confounding?

BACKGROUND

High parity and extremes of age at first birth have been linked with increased dementia risk in women, with exposure to pregnancy-associated physiological changes proposed as an explanation. However, confounding by socioeconomic and lifestyle factors could also produce such associations, whereby men would share similar patterns of association. We investigated whether these associations hold for both sexes.

METHODS

In a cohort study including all women (N = 2,222,638) and men (N = 2,141,002) ≥ 40 years of age in 1994-2017 in Denmark, we used Cox regression to evaluate associations between number of children, age at first birth, and dementia risk separately for women and men.

RESULTS

During follow-up, 81,413 women and 53,568 men (median age at diagnosis, 83.3 and 80.3 years, respectively) developed dementia. Compared with having one child, having two or more children was associated with modest decreases in overall dementia risk in both sexes (hazard ratio [HR] range 0.82-0.91, P_{difference men vs. women} = 0.07). Although the associations between childlessness and overall dementia risk differed statistically for men and women, the association magnitudes differed only slightly (HR_men 1.04, 95% confidence interval [CI] 1.01-1.06; HR_women 0.99, 95% CI 0.97-1.01; P = 0.002). Associations between age at becoming a parent and overall dementia were also similar for women and men, with the exception of older (≥ 40 years) first-time parents (HR_men 1.00, 95% CI 0.96-1.05; HR_women 0.92, 95% CI 0.86-0.98; P = 0.01). With few exceptions, sub-analyses by dementia subtype and timing of onset also revealed similar patterns and effect magnitudes for women and men.

CONCLUSIONS

Associations between number of children, age at becoming a parent, and dementia risk were similar for both sexes. Lifestyle and socioeconomic factors are more likely to explain the observed associations than normal pregnancy-related physiological changes.

Evaluating the Causal Effects of Gestational Diabetes Mellitus, Heart Disease, and High Body Mass Index on Maternal Alzheimer’s Disease and Dementia: Multivariable Mendelian Randomization

Introduction: Gestational diabetes mellitus (GDM), heart disease (HD) and high body mass index (BMI) are strongly related to Alzheimer’s disease (AD) dementia in pregnant women. Therefore, we aimed to determine the total effects of GDM, heart disease, and high BMI on maternal AD dementia.

Methods: We used data from the genome-wide association studies of European populations including more than 30,000 participants. We performed two-sample Mendelian randomization (MR) and multivariable MR (MVMR) to systematically estimate the direct effects of GDM, HD, and high BMI on maternal AD and dementia. Multiple sensitivity analyses involving classical MR approaches and expanded MR-pleiotropy residual sum and outlier analysis.

Results: In two-sample MR analysis, the inverse-variance weighted method in our study demonstrated no significant causality between GDM and maternal dementia (β = −0.006 ± 0.0026, p = 0.82). This method also revealed no significant causality between high BMI and maternal dementia (β = 0.0024 ± 0.0043, p = 0.57), and it was supported by the MR-Egger regression results, which showed no causal effect of high BMI on maternal Alzheimer’s disease and dementia (β = 0.0027 ± 0.0096, p = 0.78). The IVW method showed no significant causal relationship between maternal HD and maternal Alzheimer’s disease and dementia (β = −0.05 ± 0.0042, p = 0.117) and MR-Egger regression analysis gave a similar result (β = −0.12 ± 0.0060, p = 0.079). In MVMR analysis, we found no significant causal relationship between GDM, high BMI, or HD and maternal Alzheimer’s disease and dementia (p = 0.94, 0.82, and 0.13, respectively). Thus, the MVMR estimates were consistent with our results from the two-sample MR analysis. We confirmed that these results showed no horizontal pleiotropy and enhanced the robustness of our results through multiple sensitivity analyses.

Conclusion: In two-sample MR analysis, we found no significant causal relationship between GDM, HD, high BMI and maternal AD and dementia. These results differed from previous observational studies showing HD is a significant predictor of dementia. MVMR analysis supported no significant causal relationship between GDM, HD, high BMI and maternal AD and dementia. Sensitivity analysis broadly increased the robustness of two-sample MR and MVMR analysis results.

Study on plasma exosome biomarkers of pregnant women with intrahepatic cholestasis of pregnancy

OBJECTIVE AND AIMS

Serum total bile acid (TBA) level as the main index for the diagnosis of intrahepatic cholestasis of pregnancy (ICP) has some limitations. The early diagnosis and new treatment of ICP still need to be further strengthened.

MATERIALS AND METHODS

Plasma samples were collected, and exosomes were isolated. Key differential proteins were screened by bioinformatics methods. ELISA method was used to detect the concentration of the key differential protein in plasma samples, and the receiver operating characteristic curve (ROC) curve was drawn to find out the best critical value.

RESULTS

There were 138 differentially expressed proteins between the ICP and the normal groups by quantitative analysis. Cluster protein (CLU) was screened as a clinical validation index. The CLU concentration of plasma exosomes in the ICP group was significantly higher than that in the normal group (p < .0001). ROC curve analysis showed that the best critical point for diagnosing ICP according to the plasma exosomes CLU concentration of pregnant women was 255.28 ng/ml. In the ICP group, the best crucial point for predicting ICP with premature delivery is 286.72 ng/ml.

CONCLUSIONS

The plasma exosomes CLU in pregnant women with ICP is an important biomarker for clinical diagnosis and prediction of premature delivery of ICP.

Examining the effects of the CLU and APOE polymorphisms' combination on coronary artery disease complexed with type 2 diabetes mellitus

AIMS

Coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM) are important and increasing public health problems. This study aimed to identify the impact of APOE and CLU gene polymorphisms on the prevalence of both diseases, along with the effect of these polymorphisms on lipid profile and glucose metabolism.

METHODS

736 CAD patients (≥50 stenosis) and 549 non-CAD subjects (≤30 stenosis) were genotyped for APOE (rs429358 and rs7412) and CLU (rs11136000) gene polymorphisms using hydrolysis probes in real-time PCR. Blood samples of the individuals were drawn before coronary angiography and biochemical analyses were done. The associations between the polymorphisms and the selected parameters were assessed using statistical analysis.

RESULTS

In this study, the ε2 and ε4 isoforms of apoE were associated with serum lipid levels and TC/HDL-C and LDL-C/HDL-C ratios in analysis adjusted for several confounders and in crude analysis. It was observed that CLU T allele carrier non-CAD subjects had lower glycosylated hemoglobin levels. Furthermore, the effects of APOE and CLU polymorphisms were assessed on CAD and T2DM presence. In crude and multiple logistic regression analyses, the ε2 isoform carriers had a lower risk for CAD complexed with T2DM. When the combinational effects of APOE and CLU polymorphisms were examined, the ε2 and T allele carriers had decreased risk for CAD complexed with T2DM compared to non-carriers.

CONCLUSIONS

In conclusion, the combination of APOE and CLU polymorphisms is associated with CAD-DM status along with the APOE ε2 isoform by itself, and the apoE isoforms are strongly associated with serum lipid levels.

Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is the metabolic disorder that appears during pregnancy. The current investigation aimed to identify central differentially expressed genes (DEGs) in GDM. The transcription profiling by array data (E-MTAB-6418) was obtained from the ArrayExpress database. The DEGs between GDM samples and non-GDM samples were analyzed. Functional enrichment analysis were performed using ToppGene. Then we constructed the protein–protein interaction (PPI) network of DEGs by the Search Tool for the Retrieval of Interacting Genes database (STRING) and module analysis was performed. Subsequently, we constructed the miRNA–hub gene network and TF–hub gene regulatory network. The validation of hub genes was performed through receiver operating characteristic curve (ROC). Finally, the candidate small molecules as potential drugs to treat GDM were predicted by using molecular docking. Through transcription profiling by array data, a total of 869 DEGs were detected including 439 up-regulated and 430 down-regulated genes. Functional enrichment analysis showed these DEGs were mainly enriched in reproduction, cell adhesion, cell surface interactions at the vascular wall and extracellular matrix organization. Ten genes, HSP90AA1, EGFR, RPS13, RBX1, PAK1, FYN, ABL1, SMAD3, STAT3 and PRKCA were associated with GDM, according to ROC analysis. Finally, the most significant small molecules were predicted based on molecular docking. This investigation identified hub genes, signal pathways and therapeutic agents, which might help us, enhance our understanding of the mechanisms of GDM and find some novel therapeutic agents for GDM.

Clusterin as a Potential Biomarker of Obesity-Related Alzheimer's Disease Risk

Over 35% of the adult US population is obese. In turn, excess adiposity increases the risk of multiple complications including type 2 diabetes (T2D), insulin resistance, and cardiovascular disease; yet, obesity also independently heightens risk of Alzheimer's Disease (AD), even after adjusting for other important confounding risk factors including blood pressure, sociodemographics, cholesterol levels, smoking status, and Apolipoprotein E (ApoE) genotype. Among patients over the age of 65 with dementia, 37% have coexisting diabetes, and an estimated 7.3% of cases of AD are directly attributable to midlife obesity. Clusterin, also known as apolipoprotein J (ApoJ), is a multifunctional glycoprotein that acts as a molecular chaperone, assisting folding of secreted proteins. Clusterin has been implicated in several physiological and pathological states, including AD, metabolic disease, and cardiovascular disease. Despite long-standing interest in elucidating clusterin's relationship with amyloid beta (Aβ) aggregation/clearance and toxicity, significant knowledge gaps still exist. Altered clusterin expression and protein levels have been linked with cognitive and memory function, disrupted central nervous system lipid flux, as well as pathogenic brain structure; and its role in cardiometabolic disease suggests that it may be a link between insulin resistance, dyslipidemia, and AD. Here, we briefly highlight clusterin's relevance to AD by presenting existing evidence linking clusterin to AD and cardiometabolic disease, and discussing its potential utility as a biomarker for AD in the presence of obesity-related metabolic disease.

High glucose-mediated PICALM and mTORC1 modulate processing of amyloid precursor protein via endosomal abnormalities

BACKGROUND AND PURPOSE

Although diabetes mellitus (DM) is an important risk factor for Alzheimer's disease (AD), the detailed mechanism(s) by which DM regulates amyloid β (Aβ) processing is still unclear. The longer residence time of amyloid precursor protein (APP) in endosomes is critical for Aβ production and DM is known to cause endosomal dysregulation. Here we have examined the effects of high glucose on APP-producing endosomes and related signaling pathways.

EXPERIMENTAL APPROACH

To identify the underlying mechanisms, we investigated the effects of high glucose on abnormalities in early endosomes and related signalling pathways in human neuroblastoma cells. In vivo, diabetic mice treated with pharmacological inhibitors were used to examine endosomal dysfunction.

KEY RESULTS

The hippocampus of diabetic animals presented endosomal abnormalities and Aβ up-regulation. High glucose increased Aβ production through early endosomal enlargement achieved by increased lipid raft-mediated APP endocytosis. High glucose induced ROS-stimulated Sp1 activation, up-regulating phosphatidylinositol binding clathrin assembly protein (PICALM), clathrin heavy chain, and adaptor-related protein complex 2 alpha 1. PICALM facilitated clathrin-mediated APP endocytosis resulting in early endosomal enlargement. Meanwhile, AMPK/mTORC1-mediated autophagy defect and ROS- and mTORC1-mediated lysosomal dysfunction aggravated early endosomal enlargement under high glucose. Moreover, the increased Aβ production and cognitive deficits in diabetic mice were reversed by inhibition of early endosomal enlargement.

CONCLUSION AND IMPLICATIONS

High glucose induces early endosomal abnormalities through PICALM-induced APP endocytosis and mTORC1-inhibited endosomal clearance, up-regulating Aβ production. Thus, targeting PICALM and mTORC1 to prevent endosomal disorders is a promising strategy for managing diabetes-induced AD.