Association of LRP5, TCF7L2, and GCG variants and type 2 diabetes mellitus as well as fasting plasma glucose and lipid metabolism indexes

Mendelian Randomization Analysis Identifies Inverse Causal Relationship between External Eating and Metabolic Phenotypes

Disordered eating contributes to weight gain, obesity, and type 2 diabetes (T2D), but the precise mechanisms underlying the development of different eating patterns and connecting them to specific metabolic phenotypes remain unclear. We aimed to identify genetic variants linked to eating behaviour and investigate its causal relationships with metabolic traits using Mendelian randomization (MR). We tested associations between 30 genetic variants and eating patterns in individuals with T2D from the Volga-Ural region and investigated causal relationships between variants associated with eating patterns and various metabolic and anthropometric traits using data from the Volga-Ural population and large international consortia. We detected associations between HTR1D and CDKAL1 and external eating; between HTR2A and emotional eating; between HTR2A, NPY2R, HTR1F, HTR3A, HTR2C, CXCR2, and T2D. Further analyses in a separate group revealed significant associations between metabolic syndrome (MetS) and the loci in CRP, ADCY3, GHRL, CDKAL1, BDNF, CHRM4, CHRM1, HTR3A, and AKT1 genes. MR results demonstrated an inverse causal relationship between external eating and glycated haemoglobin levels in the Volga-Ural sample. External eating influenced anthropometric traits such as body mass index, height, hip circumference, waist circumference, and weight in GWAS cohorts. Our findings suggest that eating patterns impact both anthropometric and metabolic traits.

Integrating Common Risk Factors with Polygenic Scores Improves the Prediction of Type 2 Diabetes

We tested associations between 13 established genetic variants and type 2 diabetes (T2D) in 1371 study participants from the Volga-Ural region of the Eurasian continent, and evaluated the predictive ability of the model containing polygenic scores for the variants associated with T2D in our dataset, alone and in combination with other risk factors such as age and sex. Using logistic regression analysis, we found associations with T2D for the CCL20 rs6749704 (OR = 1.68, P_FDR = 3.40 × 10^-5), CCR5 rs333 (OR = 1.99, P_FDR = 0.033), ADIPOQ rs17366743 (OR = 3.17, P_FDR = 2.64 × 10^-4), TCF7L2 rs114758349 (OR = 1.77, P_FDR = 9.37 × 10^-5), and CCL2 rs1024611 (OR = 1.38, P_FDR = 0.033) polymorphisms. We showed that the most informative prognostic model included weighted polygenic scores for these five loci, and non-genetic factors such as age and sex (AUC 85.8%, 95%CI 83.7-87.8%). Compared to the model containing only non-genetic parameters, adding the polygenic score for the five T2D-associated loci showed improved net reclassification (NRI = 37.62%, 1.39 × 10^-6). Inclusion of all 13 tested SNPs to the model with age and sex did not improve the predictive ability compared to the model containing five T2D-associated variants (NRI = -17.86, p = 0.093). The five variants associated with T2D in people from the Volga-Ural region are linked to inflammation (CCR5, CCL2, CCL20) and glucose metabolism regulation (TCF7L, ADIPOQ2). Further studies in independent groups of T2D patients should validate the prognostic value of the model and elucidate the molecular mechanisms of the disease development.

Bulk and single-cell transcriptome analyses of islet tissue unravel gene signatures associated with pyroptosis and immune infiltration in type 2 diabetes

INTRODUCTION

Type 2 diabetes (T2D) is a common chronic heterogeneous metabolic disorder. However, the roles of pyroptosis and infiltrating immune cells in islet dysfunction of patients with T2D have yet to be explored. In this study, we aimed to explore potential crucial genes and pathways associated with pyroptosis and immune infiltration in T2D.

METHODS

To achieve this, we performed a conjoint analysis of three bulk RNA-seq datasets of islets to identify T2D-related differentially expressed genes (DEGs). After grouping the islet samples according to their ESTIMATE immune scores, we identified immune- and T2D-related DEGs. A clinical prediction model based on pyroptosis-related genes for T2D was constructed. Weighted gene co-expression network analysis was performed to identify genes positively correlated with pyroptosis-related pathways. A protein-protein interaction network was established to identify pyroptosis-related hub genes. We constructed miRNA and transcriptional networks based on the pyroptosis-related hub genes and performed functional analyses. Single-cell RNA-seq (scRNA-seq) was conducted using the GSE153885 dataset. Dimensionality was reduced using principal component analysis and t-distributed statistical neighbor embedding, and cells were clustered using Seurat. Different cell types were subjected to differential gene expression analysis and gene set enrichment analysis (GSEA). Cell-cell communication and pseudotime trajectory analyses were conducted using the samples from patients with T2D.

RESULTS

We identified 17 pyroptosis-related hub genes. We determined the abundance of 13 immune cell types in the merged matrix and found that these cell types were correlated with the 17 pyroptosis-related hub genes. Analysis of the scRNA-seq dataset of 1892 islet samples from patients with T2D and controls revealed 11 clusters. INS and IAPP were determined to be pyroptosis-related and candidate hub genes among the 11 clusters. GSEA of the 11 clusters demonstrated that the myc, G2M checkpoint, and E2F pathways were significantly upregulated in clusters with several differentially enriched pathways.

DISCUSSION

This study elucidates the gene signatures associated with pyroptosis and immune infiltration in T2D and provides a critical resource for understanding of islet dysfunction and T2D pathogenesis.

Association of TCF7L2 gene polymorphisms, methylation, and gene-environment interaction with type 2 diabetes mellitus risk: A nested case-control study in the Rural Chinese Cohort Study

BACKGROUND

To assess the associations of single-nucleotide polymorphisms (SNPs) and methylation of transcription factor 7-like 2 (TCF7L2) gene with type 2 diabetes mellitus (T2DM) risk and further explore the interactions among SNPs, methylation, and environmental factors involved in T2DM risk.

METHODS

We conducted a nested case-control study with 290 pairs of T2DM cases and matched controls. We genotyped 3 SNPs of TCF7L2 in all included participants and tested 14 CpG loci of TCF7L2 in 76 pairs of cases and controls. Conditional logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) for T2DM risk according to SNPs and methylation of TCF7L2. Multifactor dimensionality reduction (MDR) analysis was used to explore the potential TCF7L2 gene-environment interactions in T2DM risk.

RESULTS

We found no statistically significant association between the TCF7L2 polymorphisms and T2DM risk. We observed significant positive associations of methylation at CpG5 and CpG7_8 with T2DM risk. For each 1% increase in DNA methylation at CpG5 and CpG7_8, T2DM risk increased 12% (OR 1.12, 95% CI 1.01-1.25) and 32% (OR 1.32, 95% CI 1.07-1.63), respectively. Additionally, MDR analyses identified significant SNP-environment interactions among rs290487, alcohol drinking, and hypertension and methylation-environment interactions among CpG5, CpG7_8 and hypertension (P <0.05).

CONCLUSIONS

TCF7L2 polymorphisms were not independently associated with T2DM risk. However, TCF7L2 methylation were positively associated with T2DM risk in rural Chinese adults. Interactions among TCF7L2 polymorphisms, TCF7L2 methylation and environmental factors also suggest a possible etiologic pattern for T2DM.

Analysis of potential genes and pathways associated with the colorectal normal mucosa-adenoma-carcinoma sequence

This study aimed to identify differentially expressed genes (DEGs) related to the colorectal normal mucosa-adenoma-carcinoma sequence using bioinformatics analysis. Raw data files were downloaded from Gene Expression Omnibus (GEO) and underwent quality assessment and preprocessing. DEGs were analyzed by the limma package in R software (R version 3.3.2). Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed with the DAVID online tool. In a comparison of colorectal adenoma (n = 20) and colorectal cancer (CRC) stage I (n = 31), II (n = 38), III (n = 45), and IV (n = 62) with normal colorectal mucosa (n = 19), we identified 336 common DEGs. Among them, seven DEGs were associated with patient prognosis. Five (HEPACAM2, ITLN1, LGALS2, MUC12, and NXPE1) of the seven genes presented a sequentially descending trend in expression with tumor progression. In contrast, TIMP1 showed a sequentially ascending trend. GCG was constantly downregulated compared with the gene expression level in normal mucosa. The significantly enriched GO terms included extracellular region, extracellular space, protein binding, and carbohydrate binding. The KEGG categories included HIF-1 signaling pathway, insulin secretion, and glucagon signaling pathway. We discovered seven DEGs in the normal colorectal mucosa-adenoma-carcinoma sequence that was associated with CRC patient prognosis. Monitoring changes in these gene expression levels may be a strategy to assess disease progression, evaluate treatment efficacy, and predict prognosis.

Association of type 2 diabetes mellitus with the interaction between low-density lipoprotein receptor-related protein 5 (LRP5) polymorphisms and overweight and obesity in rural Chinese adults

BACKGROUND

Low-density lipoprotein receptor-related protein 5 (LRP5) plays an important role in glucose and cholesterol metabolism. The present cohort study evaluated associations of LRP5 variants with the incidence of type 2 diabetes mellitus (T2DM) in a rural adult Chinese population.

METHODS

In all, 7751 subjects aged ≥18 years without T2DM underwent genotyping at baseline; 6326 subjects (81.62%) were followed-up, and 5511 with a clear disease outcome were eligible for analysis. The same questionnaire was administered and the same anthropometric and blood biochemical examinations were performed at baseline and follow-up. Association analysis was performed for five single nucleotide polymorphisms and haplotypes of LRP5.

RESULTS

Cox proportional hazards testing of three different genetic models found no significant association between T2DM and LRP5 after adjusting for potential risk factors (P > 0.05). However, the incidence of T2DM in subjects with LRP5 mutational genotypes was higher in the overweight/obese than normal weight population. Under the dominant model, the risk of T2DM was increased with an interaction between rs11228303 and the waist-to-height ratio adjusted for baseline age, sex, and family history of T2DM (synergy index [SI] = 4.172; 95% confidence interval [CI] 1.014-17.166)], and body mass index (SI = 3.237; 95% CI 1.102-9.509). Furthermore, the A allele of rs3758644 was related to decreased fasting plasma insulin and homeostatic model assessment of β-cell function levels, whereas the T allele of rs12363572 was related to increased high-density lipoprotein cholesterol levels in new-onset diabetes patients (P < 0.05).

CONCLUSIONS

The risk of T2DM may be associated with interactions between the LRP5 gene and overweight and obesity. Polymorphisms of LRP5 are related to β-cell function and lipid metabolism.

New role of LRP5, associated with nonsyndromic autosomal-recessive hereditary hearing loss

Human hearing loss is a common neurosensory disorder about which many basic research and clinically relevant questions are unresolved. At least 50% of hearing loss are due to a genetic etiology. Although hundreds of genes have been reported, there are still hundreds of related deafness genes to be found. Clinical, genetic, and functional investigations were performed to identify the causative mutation in a distinctive Chinese family with postlingual nonsyndromic sensorineural hearing loss. Whole-exome sequencing (WES) identified lipoprotein receptor-related protein 5 (LRP5), a member of the low-density lipoprotein receptor family, as the causative gene in this family. In the zebrafish model, lrp5 downregulation using morpholinos led to significant abnormalities in zebrafish inner ear and lateral line neuromasts and contributed, to some extent, to disabilities in hearing and balance. Rescue experiments showed that LRP5 mutation is associated with hearing loss. Knocking down lrp5 in zebrafish results in reduced expression of several genes linked to Wnt signaling pathway and decreased cell proliferation when compared with those in wild-type zebrafish. In conclusion, the LRP5 mutation influences cell proliferation through the Wnt signaling pathway, thereby reducing the number of supporting cells and hair cells and leading to nonsyndromic hearing loss in this Chinese family.