HNF1A：From Monogenic Diabetes to Type 2 Diabetes and Gestational Diabetes Mellitus

Investigation of shared genetic features and related mechanisms between diabetes and tuberculosis

OBJECTIVE

This study aimed to integrate bioinformatics technology to explore shared hub genes and related mechanisms between diabetes and tuberculosis and to provide a theoretical basis for revealing the disease mechanisms in patients with both diabetes and tuberculosis.

METHODS

Differentially expressed genes and Venn analysis were used to identify shared genes between diabetes and tuberculosis. PPI network analysis was used to screen key hub genes. GO and KEGG analyses were used to analyze the potential biological functions of these key hub genes. Immune infiltration analysis was performed using the ssGSEA algorithm. EnrichR online analysis website was used to explore potential therapeutic drugs.

RESULTS

The dataset analysis showed that PSMB9, ISG15, RTP4, CXCL10, GBP2, and GBP3 were six hub genes shared by diabetes and tuberculosis, which not only could distinguish between the two disease samples but also had a high diagnostic rate. GO and KEGG analyses showed that these six genes mainly mediate immune-related biological processes such as interferon, interleukin, and chemokine receptor binding, as well as signaling pathways such as RIG-I-like receptor, NOD-like receptor, and proteasome. Immune infiltration analysis showed that high expression of TIL may mediate the development of both diabetes and tuberculosis. In addition, suloctidil HL60 UP, thioridazine HL60 UP, mefloquine HL60 UP, 1-NITROPYRENE CTD 00001569, and chlorophyllin CTD 00000324 were the candidate drugs predicted by this study that were most likely to target hub genes.

CONCLUSION

Six differentially expressed genes shared by both diseases (PSMB9, ISG15, RTP4, CXCL10, GBP2, and GBP3) may play a key role in the disease progression of patients with both diabetes and tuberculosis. Candidate drugs targeting these hub genes have therapeutic potential and are worthy of further research. In summary, this study reveals potential shared pathogenic mechanisms between tuberculosis and diabetes.

Pleiotropic influence of DNA methylation QTLs on physiological and ageing traits

DNA methylation is influenced by genetic and non-genetic factors. Here, we chart quantitative trait loci (QTLs) that modulate levels of methylation at highly conserved CpGs using liver methylome data from mouse strains belonging to the BXD family. A regulatory hotspot on chromosome 5 had the highest density of trans-acting methylation QTLs (trans-meQTLs) associated with multiple distant CpGs. We refer to this locus as meQTL.5a. Trans-modulated CpGs showed age-dependent changes and were enriched in developmental genes, including several members of the MODY pathway (maturity onset diabetes of the young). The joint modulation by genotype and ageing resulted in a more 'aged methylome' for BXD strains that inherited the DBA/2J parental allele at meQTL.5a. Further, several gene expression traits, body weight, and lipid levels mapped to meQTL.5a, and there was a modest linkage with lifespan. DNA binding motif and protein-protein interaction enrichment analyses identified the hepatic nuclear factor, Hnf1a (MODY3 gene in humans), as a strong candidate. The pleiotropic effects of meQTL.5a could contribute to variations in body size and metabolic traits, and influence CpG methylation and epigenetic ageing that could have an impact on lifespan.

Dominant-negative HNF1α mutant promotes liver steatosis and inflammation by regulating hepatic complement factor D

Patients with HNF1A variants may develop liver steatosis, while the underlying mechanism is still unclear. Here, we established a mouse model carrying the dominant-negative HNF1α P291fsinsC mutation (hHNF1Amut/-) and found that the mutant mice developed liver steatosis spontaneously under the normal chow diet. Transcriptome analysis showed significant upregulation of Cfd and other genes related to innate immune response in the liver of hHNF1Amut/- mice. The changes in lipid metabolism and complement pathways were also confirmed by proteomics. We demonstrated that HNF1α inhibited CFD expression in hepatocytes, and the P291fsinsC mutant could reverse this inhibitory effect. Furthermore, the suppression of CFD with specific inhibitor or siRNAs reduced triglyceride levels in hepatocytes, suggesting that CFD regulated hepatocyte lipid deposition. Our results demonstrate that the HNF1α P291fsinsC mutant promotes hepatic steatosis and inflammation by upregulating CFD expression, and targeting CFD may delay the progression of nonalcoholic fatty liver disease.

To identify biomarkers associated with the transfer of diabetes combined with cancer in human genes using bioinformatics analysis

Currently, the incidence of diabetes mellitus is increasing rapidly, particularly in China, and its pathogenesis is still unclear. The goal of this study was to find meaningful biomarkers of metastasis in patients with diabetes and cancer using bioinformatic analysis in order to predict gene expression and prognostic importance for survival. We used the Differentially Expressed Gene, Database for Annotation Visualization and Integrated Discovery, and Gene Set Enrichment Analyses databases, as well as several bioinformatics tools, to explore the key genes in diabetes. Based on the above database, we ended up with 10 hub genes (FOS, ATF3, JUN, EGR1, FOSB, JUNB, BTG2, EGR2, ZFP36, and NR4A2). A discussion of the 10 critical genes, with extensive literature mentioned to validate the association between the 10 key genes and patients with diabetes and cancer, to demonstrate the importance of gene expression and survival prognosis. This study identifies several biomarkers associated with diabetes and cancer development and metastasis that may provide novel therapeutic targets for diabetes combined with cancer patients.

Comprehensive Molecular Evaluation of HNF-1 Alpha, miR-27a, and miR-146 Gene Variants and Their Link with Predisposition and Progression in Type 2 Diabetes Patients

BACKGROUND

Type 2 diabetes (T2D) is a metabolic condition induced by insulin resistance and pancreatic beta cell dysfunction. MicroRNAs (miRNAs) have biological significance because they regulate processes such as the molecular signaling pathways involved in the pathophysiology of diabetes mellitus. The hepatocyte nuclear factor-1 alpha (HNF-1 alpha) is a transcription factor found in hepatocytes and the pancreas. Mutations in the HNF-1 alpha gene were reportedly associated with maturity-onset diabetes of the young (MODY). The objective of the present study was to examine the associations between MiR-27a, MiR-146, and HNF-1 alpha single-nucleotide variations (SNVs) with T2D risk in the Saudi population.

METHODOLOGY

We evaluated the association of SNVs of miR-27a rs895819 A>G, 146a-rs2910164 C>G, and HNF-1 alpha rs1169288 G>T (I27L) with the risk of T2D in Saudi patients with the Amplification Refractory Mutation System PCR (ARMS-PCR). For the miR-27a SNVs, we used 115 cases (82 males, 33 females) and 117 matched healthy controls (HCs); for the Mir-146 SNVs, we used 103 cases (70 males, 33 females) and 108 matched HCs; and for the HNF-1 alpha, we employed 110 patients (80 males, 30 females) and 110 HCs. The blood biochemistry of the participants was essayed using commercial kits, and the methods of statistical analysis used were the Chi-square test, the Fisher exact test, and a multivariate analysis based on logistic regression, like the odds ratio (OD) and risk ratio (RR), with 95% confidence intervals (CIs).

RESULTS

The MiR-27a rs895819 AG genotype was linked to increased T2D susceptibility, with OR = 2.01 and p-value = 0.011, and the miR-146 rs2910164 CG genotype and C allele were linked to an elevated risk of T2D, with OR = 2.75, p-value < 0.0016, OR = 1.77, and p-value = 0.004. The results also showed that the GT genotype and T allele of the HNF-1 alpha (rs1169288) G>T is linked to T2D, with OR = 2.18, p-value = 0.0061, and 1.77, p-value = 0.0059.

CONCLUSIONS

The SNVs in miR-27a, miR-146, and HNF-1 alpha can be potential loci for T2D risk. The limitations of this study include the relatively small sample size and the fact that it was a cross-sectional study. To our knowledge, this is the first study to highlight the association between miR-27a, miR-146, and HNF-1 alpha SNVs and the risk of T2D in the Saudi population. Future large-scale case-control studies, as well as studies on the functions of the proteins and protein interaction studies for HNF-1 alpha, are required to verify our findings. Furthermore, these findings can be used for the identification and stratification of at-risk populations via genetic testing for T2D-prevention strategies.

Role of HNFA1 Gene Variants in Pancreatic Beta Cells Function and Glycaemic Control in Young Individuals with Type 1 Diabetes

The HNF1A transcription factor, implicated in the regulation of pancreatic beta cells, as well as in glucose and lipid metabolism, is responsible for type 3 maturity-onset diabetes of the young (MODY3). HNF1A is also involved in increased susceptibility to polygenic forms of diabetes, such as type 2 diabetes (T2D) and gestational diabetes (GD), while its possible role in type 1 diabetes (T1D) is not known. In this study, 277 children and adolescents with T1D and 140 healthy controls were recruited. The following SNPs in HNF1A gene were selected: rs1169286, rs1169288, rs7979478, and rs2259816. Through linear or logistic regression analysis, we analyzed their association with T1D susceptibility and related clinical traits, such as insulin dose-adjusted glycated hemoglobin A1c (IDAA1c) and glycated hemoglobin (HbA1c). We found that rs1169286 was associated with IDAA1c and HbA1c values (p-value = 0.0027 and p-value = 0.0075, respectively), while rs1169288 was associated with IDAA1c (p-value = 0.0081). No association between HNF1A SNPs and T1D development emerged. In conclusion, our findings suggest for the first time that HNF1A variants may be a risk factor for beta cell function and glycaemic control in T1D individuals.

HNF1α upregulation and promoter hypermethylation as a cause of glucose dysregulation: a case-control study of Kashmiri MODY population

AIM

HNF1α transcription factor regulates a network of genes involved in the development of β-cells and also serves as a model for transcription defects in pancreatic β-cells; mutations in this gene cause MODY. The goal of this study was to assess the promoter methylation and expression profile of the most common MODY causing gene, HNF1α, in Kashmiri MODY patients, as factors responsible for glucose dysregulation, as no such study had been performed on MODY patients in Kashmir previously.

METHODS

The study included 85 Kashmiri subjects. Samples were extracted for DNA and RNA using standard protocols. The HNF1α promoter methylation profile was assessed by bisulfite conversion of the DNA followed by MSP, whereas qPCR was used for expression analysis.

RESULTS

The expression of HNF1α was found to be upregulated (p value 0.0349*) in majority of MODY (60%) and T1D (72%) cases (p value 0.0349*). HNF1α expression was 1.33-fold higher in MODY cases with hypermethylated HNF1α promoters (p value 0.0360*). HNF1α expression was upregulated by 2.3-fold in MODY patients with HbA1c levels > 7% (p value 0.0025**). MODY cases with FBS levels > 7.7 mmol/l were upregulated by 0.646-fold than those with FBS levels ≤ 7.7 mmol/l (p value 0.0161*).

CONCLUSION

In this study, we found that as glucose dysregulation progresses, blood FBS, RBS, and HbA1c levels rise, and that at higher levels, HNF1α expression rises as well. From the results obtained, we may conclude that HNF1α is strongly upregulated in MODY, thus indicating the deleterious effect of over expression of HNF1α gene on glucose regulation.

Monogenic diabetes

Monogenic diabetes includes several clinical conditions generally characterized by early-onset diabetes, such as neonatal diabetes, maturity-onset diabetes of the young (MODY) and various diabetes-associated syndromes. However, patients with apparent type 2 diabetes mellitus may actually have monogenic diabetes. Indeed, the same monogenic diabetes gene can contribute to different forms of diabetes with early or late onset, depending on the functional impact of the variant, and the same pathogenic variant can produce variable diabetes phenotypes, even in the same family. Monogenic diabetes is mostly caused by impaired function or development of pancreatic islets, with defective insulin secretion in the absence of obesity. The most prevalent form of monogenic diabetes is MODY, which may account for 0.5-5% of patients diagnosed with non-autoimmune diabetes but is probably underdiagnosed owing to insufficient genetic testing. Most patients with neonatal diabetes or MODY have autosomal dominant diabetes. More than 40 subtypes of monogenic diabetes have been identified to date, the most prevalent being deficiencies of GCK and HNF1A. Precision medicine approaches (including specific treatments for hyperglycaemia, monitoring associated extra-pancreatic phenotypes and/or following up clinical trajectories, especially during pregnancy) are available for some forms of monogenic diabetes (including GCK- and HNF1A-diabetes) and increase patients' quality of life. Next-generation sequencing has made genetic diagnosis affordable, enabling effective genomic medicine in monogenic diabetes.

Leveraging the strengths of mice, human stem cells, and organoids to model pancreas development and diabetes

Diabetes is an epidemic with increasing incidence across the world. Most individuals who are afflicted by this disease have type 2 diabetes, but there are many who suffer from type 1, an autoimmune disorder. Both types of diabetes have complex genetic underpinnings that are further complicated by epigenetic and environmental factors. A less prevalent and often under diagnosed subset of diabetes cases are characterized by single genetic mutations and include Maturity Onset Diabetes of the Young (MODY) and Neonatal Diabetes Mellitus (NDM). While the mode of action and courses of treatment for all forms of diabetes are distinct, the diseases all eventually result in the dysfunction and/or death of the pancreatic β cell - the body's source of insulin. With loss of β cell function, blood glucose homeostasis is disrupted, and life-threatening complications arise. In this review, we focus on how model systems provide substantial insights into understanding β cell biology to inform our understanding of all forms of diabetes. The strengths and weaknesses of animal, hPSC derived β-like cell, and organoid models are considered along with discussion of GATA6, a critical transcription factor frequently implicated in pancreatic dysfunction with developmental origins; experimental studies of GATA6 have highlighted the advantages and disadvantages of how each of these model systems can be used to inform our understanding of β cell specification and function in health and disease.