BACKGROUND: Gluconeogenesis is a critical metabolic pathway for maintaining glucose homeostasis, and its dysregulation can lead to glycometabolic disorders. This study aimed to identify hub biomarkers of these disorders to provide a theoretical foundation for enhancing diagnosis and treatment. METHODS: Gene expression profiles from liver tissues of three well-characterized gluconeogenesis mouse models were analyzed to identify commonly differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA), machine learning techniques, and diagnostic tests on transcriptome data from publicly available datasets of type 2 diabetes mellitus (T2DM) patients were employed to assess the clinical relevance of these DEGs. Subsequently, we identified hub biomarkers associated with gluconeogenesis-related glycometabolic disorders, investigated potential correlations with immune cell types, and validated expression using quantitative polymerase chain reaction in the mouse models. RESULTS: Only a few common DEGs were observed in gluconeogenesis-related glycometabolic disorders across different contributing factors. However, these DEGs were consistently associated with cytokine regulation and oxidative stress (OS). Enrichment analysis highlighted significant alterations in terms related to cytokines and OS. Importantly, osteomodulin ( OMD ), apolipoprotein A4 ( APOA4 ), and insulin like growth factor binding protein 6 ( IGFBP6 ) were identified with potential clinical significance in T2DM patients. These genes demonstrated robust diagnostic performance in T2DM cohorts and were positively correlated with resting dendritic cells. CONCLUSIONS Gluconeogenesis-related glycometabolic disorders exhibit considerable heterogeneity, yet changes in cytokine regulation and OS are universally present. OMD , APOA4 , and IGFBP6  may serve as hub biomarkers for gluconeogenesis-related glycometabolic disorders.
Machine Learning ; Humans ; Computational Biology/methods* ; Biomarkers/metabolism* ; Diabetes Mellitus, Type 2/genetics* ; Animals ; Mice ; Gluconeogenesis/physiology* ; Gene Expression Profiling ; Transcriptome/genetics* ; Gene Regulatory Networks/genetics* ; Clinical Relevance

This study aims to investigate the mechanism of Qingrun Decoction in alleviating hepatic insulin resistance in type 2 diabetes mellitus(T2DM) rats through the reprogramming of amino acid metabolism. A T2DM rat model was established by inducing insulin resistance through a high-fat diet combined with intraperitoneal injection of streptozotocin. The model rats were randomly divided into five groups: model group, high-, medium-, and low-dose Qingrun Decoction groups, and metformin group. A normal control group was also established. The rats in the normal and model groups received 10 mL·kg~(-1) distilled water daily by gavage. The metformin group received 150 mg·kg~(-1) metformin suspension by gavage, and the Qingrun Decoction groups received 11.2, 5.6, and 2.8 g·kg~(-1) Qingrun Decoction by gavage for 8 weeks. Blood lipid levels were measured in different groups of rats. Pathological damage in rat liver tissue was assessed by hematoxylin-eosin(HE) staining and oil red O staining. Transcriptome sequencing and untargeted metabolomics were performed on rat liver and serum samples, integrated with bioinformatics analyses. Key metabolites(branched-chain amino acids, BCAAs), amino acid transporters, amino acid metabolites, critical enzymes for amino acid metabolism, resistin, adiponectin(ADPN), and mammalian target of rapamycin(mTOR) pathway-related molecules were quantified using quantitative real-time polymerase chain reaction(qRT-PCR), Western blot, and enzyme-linked immunosorbent assay(ELISA). The results showed that compared with the normal group, the model group had significantly increased serum levels of total cholesterol(TC), triglycerides(TG), low-density lipoprotein cholesterol(LDL-C), and resistin and significantly decreased ADPN levels. Hepatocytes in the model group exhibited loose arrangement, significant lipid accumulation, fatty degeneration, and pronounced inflammatory cell infiltration. In liver tissue, the mRNA transcriptional levels of solute carrier family 7 member 2(Slc7a2), solute carrier family 38 member 2(Slc38a2), solute carrier family 38 member 4(Slc38a4), and arginase(ARG) were significantly downregulated, while the mRNA transcriptional levels of solute carrier family 1 member 4(Slc1a4), solute carrier family 16 member 1(Slc16a1), and methionine adenosyltransferase(MAT) were upregulated. Furthermore, the mRNA transcription and protein expression levels of branched-chain α-keto acid dehydrogenase E1α(BCKDHA) and DEP domain-containing mTOR-interacting protein(DEPTOR) were downregulated, while mRNA transcription and protein expression levels of mTOR, as well as ribosomal protein S6 kinase 1(S6K1), were upregulated. The levels of BCAAs and S-adenosyl-L-methionine(SAM) were elevated. The serum level of 6-hydroxymelatonin was significantly reduced, while imidazole-4-one-5-propionic acid and N-(5-phospho-D-ribosyl)anthranilic acid levels were significantly increased. Compared with the model group, Qingrun Decoction significantly reduced blood lipid and resistin levels while increasing ADPN levels. Hepatocytes had improved morphology with reduced inflammatory cells, and fatty degeneration and lipid deposition were alleviated. Differentially expressed genes and differential metabolites were mainly enriched in amino acid metabolic pathways. The expression levels of Slc7a2, Slc38a2, Slc38a4, and ARG in the liver tissue were significantly upregulated, while Slc1a4, Slc16a1, and MAT expression levels were significantly downregulated. BCKDHA and DEPTOR expression levels were upregulated, while mTOR and S6K1 expression levels were downregulated. Additionally, the levels of BCAAs and SAM were significantly decreased. The serum level of 6-hydroxymelatonin was increased, while those of imidazole-4-one-5-propionic acid and N-(5-phospho-D-ribosyl)anthranilic acid were decreased. In summary, Qingrun Decoction may improve amino acid metabolism reprogramming, inhibit mTOR pathway activation, alleviate insulin resistance in the liver, and mitigate pathological damage of liver tissue in T2DM rats by downregulating hepatic BCAAs and SAM and regulating key enzymes involved in amino acid metabolism, such as BCKDHA, ARG, and MAT, as well as amino acid metabolites and transporters.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Insulin Resistance ; Diabetes Mellitus, Type 2/genetics* ; Male ; Liver/drug effects* ; Amino Acids/metabolism* ; Rats, Sprague-Dawley ; Humans ; Metabolic Reprogramming

OBJECTIVES: To study the clinical manifestations and genetic characteristics of children with maturity-onset diabetes of the young type 2 (MODY2), aiming to enhance the recognition of MODY2 in clinical practice. METHODS: A retrospective analysis was conducted on the clinical data of 13 children diagnosed with MODY2 at the Department of Pediatrics of Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology from August 2017 to July 2023. RESULTS: All 13 MODY2 children had a positive family history of diabetes and were found to have mild fasting hyperglycemia [(6.4±0.5) mmol/L] during health examinations or due to infectious diseases. In the oral glucose tolerance test, two cases met the diagnostic criteria for diabetes with fasting blood glucose, while the others exhibited impaired fasting glucose or impaired glucose tolerance. The one-hour post-glucose load (1-hPG) fluctuated between 8.31 and 13.06 mmol/L, meeting the diagnostic criteria for diabetes recommended by the International Diabetes Federation. All 13 MODY2 children had heterozygous variants in the glucokinase (GCK) gene, with Cases 6 (GCK c.1047C>A, p.Y349X), 11 (GCK c.1146_1147ins GCAGAGCGTGTCTACGCGCGCTGCGCACATGTGC, p.S383Alafs*87), and 13 (GCK c.784_785insC, p.D262Alafs*13) presenting variants that had not been previously reported. CONCLUSIONS This study enriches the spectrum of genetic variations associated with MODY2. Clinically, children with a family history of diabetes, incidental findings of mild fasting hyperglycemia, and negative diabetes-related antibodies should be considered for the possibility of MODY2.
Humans ; Diabetes Mellitus, Type 2/diagnosis* ; Male ; Female ; Child ; Retrospective Studies ; Glucokinase/genetics* ; Adolescent ; Child, Preschool ; Glucose Tolerance Test

Maturity-onset diabetes of the young (MODY) is a special type of diabetes characterized by clinical features including early onset of diabetes (before 30 years of age), autosomal dominant inheritance, impaired glucose-induced insulin secretion, and hyperglycemia. So far, 14 types of MODY have been reported, accounting for about 1%-5% of the patients with diabetes. MODY often presents with an insidious onset, and although 14 subtypes have been identified for MODY, it is frequently misdiagnosed as type 1 or type 2 diabetes due to overlapping clinical features and high costs and limitations of genetic testing. This article reviews the clinical features of MODY subtypes in order to improve the accuracy of the diagnosis and treatment of MODY.
Humans ; Diabetes Mellitus, Type 2/genetics*

OBJECTIVES: The gut microbiota plays a crucial role in the pathophysiology of various types of diabetes. However, the causal relationship between them has yet to be systematically elucidated. This study aims to explore the potential causal associations between gut microbiota and diabetes using a two-sample Mendelian randomization (MR) analysis, based on multiple taxonomic levels. METHODS: Eligible instrumental variables were extracted from the selected genome-wide association study (GWAS) data on gut microbiota. These were combined with GWAS datasets on type 1 diabetes (T1D), type 2 diabetes (T2D), and gestational diabetes mellitus (GDM) to conduct forward MR analysis, sensitivity analysis, reverse MR analysis, and validation of significant estimates. Microbial taxa with causal effects on T1D, T2D, and GDM were identified based on a comprehensive assessment of all analytical stages. RESULTS: A total of 2 179, 2 176, and 2 166 single nucleotide polymorphisms (SNP) were included in the MR analyses for gut microbiota with T1D, T2D, and GDM, respectively. MR results indicated causal associations between: Six microbial taxa (Eggerthella, Lachnospira, Bacillales, Desulfovibrionales, Parasutterella, and Turicibacter) and T1D; 9 microbial taxa (Verrucomicrobia, Deltaproteobacteria, Actinomycetales, Desulfovibrionale, Actinomycetaceae, Desulfovibrionaceae, Actinomyces, Alcaligenaceae, and Lachnospiraceae NC2004 group) and T2D; 10 microbial taxa (Betaproteobacteria, Coprobacter, Ruminococcus2, Tenericutes, Clostridia, Methanobacteria, Mollicutes, Methanobacteriales, Methanobacteriaceae, and Methanobrevibacter) and GDM. CONCLUSIONS This study identified specific gut microbial taxa that may significantly increase or decrease the risk of developing diabetes. Some findings were fully replicated in independent validation datasets. However, the underlying biological mechanisms of these causal relationships warrant further investigation through mechanistic studies and population-based research.
Gastrointestinal Microbiome/genetics* ; Humans ; Mendelian Randomization Analysis ; Genome-Wide Association Study ; Diabetes Mellitus, Type 2/genetics* ; Diabetes Mellitus, Type 1/genetics* ; Female ; Polymorphism, Single Nucleotide ; Diabetes, Gestational/genetics* ; Pregnancy

Gut microbial communities are likely remodeled in tandem with accumulated physiological decline during aging, yet there is limited understanding of gut microbiome variation in advanced age. Here, we performed a metagenomics-based enterotype analysis in a geographically homogeneous cohort of 367 enrolled Chinese individuals between the ages of 60 and 94 years, with the goal of characterizing the gut microbiome of elderly individuals and identifying factors linked to enterotype variations. In addition to two adult-like enterotypes dominated by Bacteroides (ET-Bacteroides) and Prevotella (ET-Prevotella), we identified a novel enterotype dominated by Escherichia (ET-Escherichia), whose prevalence increased in advanced age. Our data demonstrated that age explained more of the variance in the gut microbiome than previously identified factors such as type 2 diabetes mellitus (T2DM) or diet. We characterized the distinct taxonomic and functional profiles of ET-Escherichia, and found the strongest cohesion and highest robustness of the microbial co-occurrence network in this enterotype, as well as the lowest species diversity. In addition, we carried out a series of correlation analyses and co-abundance network analyses, which showed that several factors were likely linked to the overabundance of Escherichia members, including advanced age, vegetable intake, and fruit intake. Overall, our data revealed an enterotype variation characterized by Escherichia enrichment in the elderly population. Considering the different age distribution of each enterotype, these findings provide new insights into the changes that occur in the gut microbiome with age and highlight the importance of microbiome-based stratification of elderly individuals.
Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; Bacteroides ; China ; Diabetes Mellitus, Type 2/microbiology* ; Escherichia coli/classification* ; Gastrointestinal Microbiome/genetics* ; Metagenomics ; East Asian People

OBJECTIVES: To identify the key genes and immunological pathways shared by type 2 diabetes mellitus (T2DM) and chronic obstructive pulmonary disease (COPD) and explore the potential therapeutic targets of T2DM complicated by COPD. METHODS: GEO database was used for analyzing the gene expression profiles in T2DM and COPD to identify the common differentially expressed genes (DEGs) in the two diseases. A protein-protein interaction network was constructed to identify the candidate hub genes, which were validated in datasets and disease sets to obtain the target genes. The diagnostic accuracy of these target genes was assessed with ROC analysis, and their expression levels and association with pulmonary functions were investigated using clinical data and blood samples of patients with T2DM and COPD. The abundance of 22 immune cells was analyzed with CIBERSORT algorithm, and their relationship with the target genes was examined using correlation analysis. DGIdb database was used for analyzing the drug-gene interactions and the druggable genes followed by gene set enrichment analysis. RESULTS: We identified a total of 175 common DEGs in T2DM and COPD, mainly enriched in immune- and inflammation-related pathways. Among these genes, CXCL12 was identified as the final target gene, whose expression was elevated in both T2DM and COPD (P<0.05) and showed good diagnostic efficacy. Immune cell infiltration correlation analysis showed significant correlations of CXCL12 with various immune cells (P<0.01). GESA analysis showed that high CXCL12 expression was significantly correlated with "cytokine-cytokine receptor interaction". Drug-gene analysis showed that most of CXCL12-related drugs were not targeted drugs with significant cytotoxicity. CONCLUSIONS CXCL12 is a potential common key pathogenic gene of COPD and T2DM, and small-molecule targeted drugs against CXCL12 can provide a new strategy for treatment T2DM complicated by COPD.
Humans ; Pulmonary Disease, Chronic Obstructive/complications* ; Diabetes Mellitus, Type 2/genetics* ; Chemokine CXCL12/metabolism* ; Protein Interaction Maps ; Gene Expression Profiling

OBJECTIVES: The intestinal microbial characteristics of patients with simple cerebral infarction (CI) and CI complicated with Type 2 diabetes mellitus (CI-T2DM) are still not clear. This study aims to analyze the differences in the variable characteristics of intestinal flora between patients simply with CI and CI-T2DM. METHODS: This study retrospectively collected the patients who were admitted to the Affiliated Hospital of Putian University from September 2021 to September 2022. The patients were divided into a CI group (n=12) and a CI-T2DM group (n=12). Simultaneously, 12 healthy people were selected as a control group. Total DNA was extracted from feces specimens. Illumina Novaseq sequencing platform was used for metagenomic sequencing. The Knead Data software, Kraken2 software, and Bracken software were applied for sequencing analysis. RESULTS: At phylum level, the average ratio of Firmicutes, Bacteroidetes, and Proteobacteria in the CI-T2DM group were 33.07%, 54.80%, and 7.00%, respectively. In the CI group, the ratios of each were 14.03%, 69.62%, and 11.13%, respectively, while in the control group, the ratios were 50.99%, 37.67%, and 5.24%, respectively. There was significant differences in the distribution of Firmicutes (F=6.130, P=0.011) among the 3 groups. At the family level, compared with the CI group, the relative abundance of Eubacteriaceae (t=8.062, P<0.001) in the CI-T2DM group was significantly increased, while Corynebacteriaceae (t=4.471, P<0.001), Methanobacteriaceae (t=3.406, P=0.003), and Pseudomonadaceae (t=2.352, P=0.028) were decreased significantly. At the genus level, compared with the CI group, there was a relative abundance of Cutibacterium (t=6.242, P<0.001), Eubacterium (t=8.448, P<0.001), and Blautia (t=3.442, P=0.002) in the CI-T2DM group which was significantly increased. In terms of Methanobrevibacter (t=3.466, P=0.002), Pyramidobacter (t=2.846, P=0.009) and Pseudomonas (t=2.352, P=0.028), their distributions were decreased significantly in the CI-T2DM group. At the species level, compared with the CI group, the relative abundance of Cutibacterium acnes (t=6.242, P<0.001) in the CI-T2DM group was significantly increased, while Pseudomonas aeruginosa (t=2.352, P=0.028) was decreased significantly. Still at the genus level, linear discriminant analysis effect size (LEfSe) analysis showed that the distributions of Pseudomonas and Blautia were determined to be the most significantly different between the CI-T2DM and the CI group. At the species level, the total number of operational taxonomic units (OTUs) in the 3 groups was 1 491. There were 169, 221, and 192 kinds of OTUs unique to the CI-T2DM, CI, and control group, respectively. CONCLUSIONS From phylum level to species level, the composition of intestinal flora in the patients with CI-T2DM is different from those in the patients simply with CI. The change in the proportion of Firmicutes, Bacteroidetes and Proteus compared with the healthy population is an important feature of intestinal flora imbalance in the patients with CI and with CI-T2DM. Attention should be paid to the differential distribution of Bacteroides monocytogenes and butyrate producing bacteria.
Humans ; Gastrointestinal Microbiome/genetics* ; Diabetes Mellitus, Type 2/complications* ; Retrospective Studies ; Bacteria/genetics* ; High-Throughput Nucleotide Sequencing

Many natural products can be bio-converted by the gut microbiota to influence pertinent efficiency. Ginsenoside compound K (GCK) is a potential anti-type 2 diabetes (T2D) saponin, which is mainly bio-transformed into protopanaxadiol (PPD) by the gut microbiota. Studies have shown that the gut microbiota between diabetic patients and healthy subjects are significantly different. Herein, we aimed to characterize the biotransformation of GCK mediated by the gut microbiota from diabetic patients and healthy subjects. Based on 16S rRNA gene sequencing, the results indicated the bacterial profiles were considerably different between the two groups, especially Alistipes and Parabacteroides that increased in healthy subjects. The quantitative analysis of GCK and PPD showed that gut microbiota from the diabetic patients metabolized GCK slower than healthy subjects through liquid chromatography tandem mass spectrometry (LC-MS/MS). The selected strain A. finegoldii and P. merdae exhibited a different metabolic capability of GCK. In conclusion, the different biotransformation capacity for GCK may impact its anti-diabetic potency.
Humans ; Gastrointestinal Microbiome/genetics* ; Chromatography, Liquid/methods* ; Healthy Volunteers ; RNA, Ribosomal, 16S ; Feces/microbiology* ; Tandem Mass Spectrometry ; Biotransformation ; Diabetes Mellitus, Type 2/drug therapy*

A 2-year-old boy was admitted to Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine in Nov 30^th, 2018, due to polydipsia, polyphagia, polyuria accompanied with increased glucose levels for more than 2 weeks. He presented with symmetrical short stature [height 81 cm (－2.2 SD), weight 9.8 kg (－2.1 SD), body mass index 14.94 kg/m² (P₁₀-P₁₅)], and with no special facial or physical features. Laboratory results showed that the glycated hemoglobin A1c was 14%, the fasting C-peptide was 0.3 ng/mL, and the islet autoantibodies were all negative. Oral glucose tolerance test showed significant increases in both fasting and postprandial glucose, but partial islet functions remained (post-load C-peptide increased 1.43 times compared to baseline). A heterozygous variant c.1366C>T (p.R456C) was detected in GATA6 gene, thereby the boy was diagnosed with a specific type of diabetes mellitus. The boy had congenital heart disease and suffered from transient hyperosmolar hyperglycemia after a patent ductus arteriosus surgery at 11 months of age. Insulin replacement therapy was prescribed, but without regular follow-up thereafter. The latest follow-up was about 3.5 years after the diagnosis of diabetes when the child was 5 years and 11 months old, with the fasting blood glucose of 6.0-10.0 mmol/L, and the 2 h postprandial glucose of 17.0-20.0 mmol/L.
Male ; Child ; Humans ; Child, Preschool ; Infant ; Diabetes Mellitus, Type 2/complications* ; Mutation, Missense ; C-Peptide/genetics* ; China ; Insulin/genetics* ; Glucose ; Blood Glucose ; GATA6 Transcription Factor/genetics*