Altered blood gene expression in the obesity-related type 2 diabetes cluster may be causally involved in lipid metabolism: a Mendelian randomisation study

Harnessing the power of proteomics in precision diabetes medicine

Precision diabetes medicine (PDM) aims to reduce errors in prevention programmes, diagnosis thresholds, prognosis prediction and treatment strategies. However, its advancement and implementation are difficult due to the heterogeneity of complex molecular processes and environmental exposures that influence an individual's disease trajectory. To address this challenge, it is imperative to develop robust screening methods for all areas of PDM. Innovative proteomic technologies, alongside genomics, have proven effective in precision cancer medicine and are showing promise in diabetes research for potential translation. This narrative review highlights how proteomics is well-positioned to help improve PDM. Specifically, a critical assessment of widely adopted affinity-based proteomic technologies in large-scale clinical studies and evidence of the benefits and feasibility of using MS-based plasma proteomics is presented. We also present a case for the use of proteomics to identify predictive protein panels for type 2 diabetes subtyping and the development of clinical prediction models for prevention, diagnosis, prognosis and treatment strategies. Lastly, we discuss the importance of plasma and tissue proteomics and its integration with genomics (proteogenomics) for identifying unique type 2 diabetes intra- and inter-subtype aetiology. We conclude with a call for action formed on advancing proteomics technologies, benchmarking their performance and standardisation across sites, with an emphasis on data sharing and the inclusion of diverse ancestries in large cohort studies. These efforts should foster collaboration with key stakeholders and align with ongoing academic programmes such as the Precision Medicine in Diabetes Initiative consortium.

Autoimmune diseases and the risk of bladder cancer: A Mendelian randomization analysis

OBJECTIVE

To investigate the association between autoimmune diseases (AIDs) and bladder cancer (BC) at the genetic level using Mendelian randomization (MR).

METHODS

Single nucleotide polymorphisms (SNPs) associated with the seven AIDs were extracted from the IEU GWAS database, and the SNPs were quality-controlled using strict screening criteria. The association between AIDs and BC risk was assessed by inverse-variance weighted (IVW), MR-Egger regression and Weighted median method. The heterogeneity of SNPs was evaluated by Cochran Q test. MR-Egger intercept test and MR-PRESSO global test were used to test the horizontal pleiotropy of SNPs. Both sides with potential causal associations were validated using the validation set.

RESULTS

Our result showed that genetically predicted RA was significantly associated with an increased risk of BC (IVW OR = 1.214, 95 % CI = 1.062-1.388, P = 0.005). MS nominally increased the risk of BC (IVW OR = 1.095, 95 % CI = 1.005-1.193, P = 0.037), consistent with the results of the MR analysis of the BC validation cohort. However SLE, T1D, UC, CD, and MG were not causally associated with BC risk (P > 0.05). The sensitivity analyses showed that there was no heterogeneity or horizontal pleiotropy in our findings.

CONCLUSION

This study provides evidence of a causal relationship between AIDs and BC risk at the genetic level, confirming a causal relationship between RA and MS in increasing the risk of BC.

HDL levels modulate the impact of type 2 diabetes susceptibility alleles in older adults

BACKGROUND

Type 2 Diabetes (T2D) is influenced by genetic, environmental, and ageing factors. Ageing pathways exacerbate metabolic diseases. This study aimed to examine both clinical and genetic factors of T2D in older adults.

METHODS

A total of 2,909 genotyped patients were enrolled in this study. Genome Wide Association Study was conducted, comparing T2D patients to non-diabetic older adults aged ≥ 60, ≥ 65, or ≥ 70 years, respectively. Binomial logistic regressions were applied to examine the association between T2D and various risk factors. Stepwise logistic regression was conducted to explore the impact of low HDL (HDL < 40 mg/dl) on the relationship between the genetic variants and T2D. A further validation step using data from the UK Biobank with 53,779 subjects was performed.

RESULTS

The association of T2D with both low HDL and family history of T2D increased with the age of control groups. T2D susceptibility variants (rs7756992, rs4712523 and rs10946403) were associated with T2D, more significantly with increased age of the control group. These variants had stronger effects on T2D risk when combined with low HDL cholesterol levels, especially in older control groups.

CONCLUSIONS

The findings highlight a critical role of age, genetic predisposition, and HDL levels in T2D risk. The findings suggest that individuals over 70 years who have high HDL levels without the T2D susceptibility alleles may be at the lowest risk of developing T2D. These insights can inform tailored preventive strategies for older adults, enhancing personalized T2D risk assessments and interventions.

Mendelian Randomization Validates the Immune Landscape Mediated by Aggrephagy in Esophageal Squamous Cell Carcinoma Patients from the Perspectives of Multi-omics

Objective: To delineate the immune landscape of ESCC patients mediated by aggrephagy through bioinformatics and identify prognostic cell cluster genes with causal attributes to esophageal cancer through Mendelian randomization. Methods: Quality control, dimension reduction, and annotation were performed on the ESCC single-cell dataset. NMF clustering of various cell subgroups was carried out based on the expression of AGG-related genes, and AGG-related genes in each cluster were identified. Pseudo-temporal analysis was used to observe changes in the expression of AGG-related genes in each cluster. Cell communication analysis was employed to observe interactions between cell subgroups. Changes in classification, metabolism, or KEGG pathways in related subgroups were observed based on different cell characteristics. The AGG cluster attributes of TCGA and GEO samples were assessed based on GSVA, and the prognosis of each cluster was observed. The immune treatment situation and the relationship between mutation level and prognosis of AGG cluster-related samples were observed through the TIDE database and microsatellite instability. Finally, the eQTL of genes in each prognostic AGG cluster was used as an instrumental variable, with esophageal cancer as the outcome factor. Through Mendelian randomization analysis, AGG cluster-related genes with a causal relationship to esophageal cancer were established. Results: Dimension reduction clustering of single-cell transcriptome data identified 19 different cell subgroups. After re-annotation of the 19 cell subgroups, it was found that the CAF cells, B cells, T cells, NK cells, etc., of ESCA patients were all elevated compared to the control group. CAF cells had a high degree of communication with most cells. There were significant differences in macrophage metabolism and B-cell-mediated signal transduction pathways in different AGG clusters. The TUBA1B+Mac-C0 cluster, along with other clusters, exhibits predictive prognostic and immunotherapeutic potential at the transcriptional level. Mendelian randomization analysis revealed a causal relationship between genes such as CTSZ, CTSC, DAD, COLEC12, ATOX1, within the AGG cluster, and the onset of esophageal cancer. Conclusion: Aggrephagy mediates and influences the alterations and interactions of various immune cells in patients with ESCC. We elucidate the roles of AGG-related clusters, such as TUBA1B+Mac-C0, VIM+CD8+T_cells-C0, UBB+Mac-C2, in mediating prognosis and immune therapy in ESCC patients. Genes causally associated with the occurrence of esophageal cancer are identified within the AGG cluster, including CTSZ, CTSC, DAD, COLEC12, ATOX1, etc., offering new evidence for clinical immune therapy. These findings underscore the significance of these gene clusters in influencing both prognosis and immune responses in the context of esophageal cancer, shedding light on potential therapeutic targets and prognostic markers.

Epigenetic modifications in obesity-associated diseases

The global prevalence of obesity has reached epidemic levels, significantly elevating the susceptibility to various cardiometabolic conditions and certain types of cancer. In addition to causing metabolic abnormalities such as insulin resistance (IR), elevated blood glucose and lipids, and ectopic fat deposition, obesity can also damage pancreatic islet cells, endothelial cells, and cardiomyocytes through chronic inflammation, and even promote the development of a microenvironment conducive to cancer initiation. Improper dietary habits and lack of physical exercise are important behavioral factors that increase the risk of obesity, which can affect gene expression through epigenetic modifications. Epigenetic alterations can occur in early stage of obesity, some of which are reversible, while others persist over time and lead to obesity-related complications. Therefore, the dynamic adjustability of epigenetic modifications can be leveraged to reverse the development of obesity-associated diseases through behavioral interventions, drugs, and bariatric surgery. This review provides a comprehensive summary of the impact of epigenetic regulation on the initiation and development of obesity-associated cancers, type 2 diabetes, and cardiovascular diseases, establishing a theoretical basis for prevention, diagnosis, and treatment of these conditions.

Microbiome and its implications in oncogenesis: a Mendelian randomization perspective

The human microbiome, an intricate ecological network, has garnered significant attention due to its potential implications in oncogenesis. This paper delves into the multifaceted relationships between the microbiome, its metabolites, and cancer development, emphasizing the human intestinal tract as the primary microbial habitat. Highlighting the potential causative associations between microbial disturbances and cancer progression, we underscore the role of specific bacterial strains in various cancers, such as stomach and colorectal cancer. Traditional causality assessment methods, like randomized controlled trials (RCTs), have limitations. Therefore, we advocate using Mendelian Randomization (MR) as a powerful alternative to study causal relationships, leveraging genetic variants as instrumental variables. With the proliferation of genome-wide association studies, MR harnesses genetic variations to infer causality, which is especially beneficial when addressing confounders like diet and lifestyle that can skew microbial research. We systematically review MR's application in understanding the microbiome-cancer nexus, emphasizing its strengths and challenges. While MR offers a unique perspective on causality, it faces hurdles like horizontal pleiotropy and weak instrumental variable bias. Integrating MR with multi-omics data, encompassing genomics, transcriptomics, proteomics, and metabolomics, holds promise for future research, potentially heralding groundbreaking discoveries in microbiology and genetics. This comprehensive review underscores the critical role of the human microbiome in oncogenesis and champions MR as an indispensable tool for advancing our understanding in this domain.

Association between testosterone and cancers risk in women: a two-sample Mendelian randomization study

OBJECTIVE

Previous observational studies have explored the correlation between testosterone and cancer risk. However, the causal association between testosterone and various cancer types in women remains inconclusive. The objective of this Mendelian randomization study is to evaluate the causal links between total testosterone (TT) and bioavailable testosterone (BT) with cancer risk in females.

METHODS

Initially, a rigorous quality control process was employed to identify suitable instrumental single nucleotide polymorphisms (SNPs) associated with the exposure under investigation that exhibited a significant association. The genetic causal relationship between female testosterone levels and the risk of developing cancers was examined through a two-sample Mendelian randomization. Various analytical methods, including inverse-variance weighted (IVW), MR-Egger, weighted median, simple mode, and weighted mode, were applied in the investigation. Key findings were primarily based on the results obtained via IVW (random effects), and sensitivity analyses were conducted to assess the reliability of the obtained results. Furthermore, maximum likelihood, penalized weighted median, and IVW (fixed effects) methods were utilized to further validate the robustness of the results.

RESULTS

Based on the results of IVW analysis, our study indicated a positive causal relationship between BT and breast cancer (OR = 1.1407, 95%CI: 1.0627-1.2244, P = 0.0015) and endometrial cancer (OR = 1.4610, 95%CI: 1.2695-1.6813, P = 1.22E-06). Moreover, our findings also showed a positive causal association between TT and breast cancer (OR = 1.1764, 95%CI: 1.0846-1.2761, P = 0.0005), cervical cancer(OR = 1.0020, 95%CI: 1.0007-1.0032, P = 0.0077), and endometrial cancer(OR = 1.4124, 95%CI: 1.2083-1.6511, P = 0.0001). Additionally, our results demonstrated a negative causal relationship between BT and ovarian cancer (OR = 0.8649, 95%CI: 0.7750-0.9653, P = 0.0320). However, no causal relationship was found between BT, TT and other types of cancer (corrected P > 0.05).

CONCLUSIONS

This study elucidates the role of testosterone on the development of breast cancer, endometrial cancer, ovarian cancer, and cervical cancer. It also hints at a potential but fragile link between testosterone and bladder cancer, as well as thyroid cancer. Nonetheless, it's worth noting that no statistically significant relationship between testosterone and various other types of cancer in females was identified.

Two-sample mendelian randomization reveals a causal association between membranous nephropathy and lung cancer

A risk association between membranous nephropathy (MN) and lung cancer is reported, but traditional observational studies cannot provide strong evidence of its causality. This study aimed to assess genome-wide association studies data for a causal relationship between MN and lung cancer using a two-sample Mendelian randomization (MR) approach. Inverse-variance weighted, and MR Egger regression techniques were used to determine the association of genetic variants from cohorts of MN and lung cancer patients. Independent genetic variants with genome-wide significance (P < 5×10-8) were used to determine the direction of chance. Sensitivity analyses confirmed the accuracy of the results. The results suggest that MN is an exposure factor for lung cancer, validated using a second cohort of lung cancer patients (P < 0.001). There is insufficient evidence to suggest a causal relationship between lung cancer and MN; however, cigarette smoking may be a confounding factor for lung cancer due to MN. The findings provide causal evidence for the effect of MN on lung cancer risk and may be useful for patient management, especially in older patients with MN who should be systematically screened regularly.

Celastrol functions as an emerging manager of lipid metabolism: Mechanism and therapeutic potential

Lipid metabolism disorders are pivotal in the development of various lipid-related diseases, such as obesity, atherosclerosis, non-alcoholic fatty liver disease, type 2 diabetes, and cancer. Celastrol, a bioactive compound extracted from the Chinese herb Tripterygium wilfordii Hook F, has recently demonstrated potent lipid-regulating abilities and promising therapeutic effects for lipid-related diseases. There is substantial evidence indicating that celastrol can ameliorate lipid metabolism disorders by regulating lipid profiles and related metabolic processes, including lipid synthesis, catabolism, absorption, transport, and peroxidation. Even wild-type mice show augmented lipid metabolism after treatment with celastrol. This review aims to provide an overview of recent advancements in the lipid-regulating properties of celastrol, as well as to elucidate its underlying molecular mechanisms. Besides, potential strategies for targeted drug delivery and combination therapy are proposed to enhance the lipid-regulating effects of celastrol and avoid the limitations of its clinical application.