Integration of Metabolomics and Transcriptomics Reveals Major Metabolic Pathways and Potential Biomarkers Involved in Aging Mice with Type 2 Diabetes Mellitus
Aging is a natural biological process that leads to significant changes in human metabolic capacity. Among the various metabolic disorders associated with aging, metabolic syndrome is a critical factor contributing to the development of type 2 diabetes mellitus (T2DM). In recent years, T2DM has emerged as one of the top ten leading causes of death globally. Notably, it has been reported that over 25% of individuals aged 65 years and older are affected by T2DM. The liver, being the primary metabolic organ, plays a crucial role in maintaining metabolic homeostasis. However, metabolic disorders in the liver are closely linked to the pathogenesis of T2DM. Despite this, there is a paucity of research focusing on liver metabolic disorders in older adults with T2DM. Therefore, it is imperative to investigate liver metabolism in aging individuals with T2DM using advanced omics technologies. This study employs an integrated approach combining metabolomics and transcriptomics to identify specific metabolites and genes that are altered in the liver of aging mice with T2DM, thereby providing a theoretical foundation for the treatment of older adults with T2DM.
To conduct this study, ten 8-week-old and twenty 20-week-old male Kunming (KM) mice were obtained from the specific pathogen-free (SPF) Laboratory at Gansu University of Chinese Medicine. The 8-week-old mice were assigned to the young group, while the 20-week-old mice were randomly divided into a non-diabetic aging group and an aging-with-T2DM group, each consisting of ten mice. The young group and the non-diabetic aging group were fed a normal diet, whereas the aging-with-T2DM group was given a high carbohydrate and fat diet for 28 consecutive days. Starting from the 29th day, the aging-with-T2DM group received daily injections of 70 mg/kg streptozotocin (STZ) for three days to induce diabetes, while the other groups were injected with an equivalent volume of saline. Blood samples were collected seven days after the last STZ injection, and the mice were subsequently euthanized via cervical dislocation. All experimental procedures adhered to the guidelines of the Institutional Animal Ethics Committee of Gansu University of Chinese Medicine.
The body weight, daily food intake, and water consumption of the mice in each group were measured and recorded every two days. One week after the last STZ injection, the mice were fasted for 12 hours, and fasting blood glucose levels were measured using test strips. The results indicated that the aging mice with T2DM exhibited symptoms of polydipsia, polyphagia, and slow weight gain, or even weight loss. The fasting blood glucose levels in these mice exceeded 20 mmol/L, which is higher than the clinical diagnostic threshold for diabetes. These findings confirmed the successful establishment of the T2DM model.
Following euthanasia, the liver tissues were harvested, fixed in 4% paraformaldehyde, dehydrated, embedded in paraffin, and sectioned into 3 mm thick slices. Hematoxylin and eosin (H&E) staining and Periodic acid-Schiff (PAS) staining were performed on the liver sections. H&E staining revealed that the liver cells of the young mice were intact, while those of the non-diabetic aging mice exhibited some swelling. In contrast, the liver cells of the aging mice with T2DM were significantly swollen and disorganized, with the central vein appearing deformed and collapsed. PAS staining indicated a substantial accumulation of glycogen in the liver cells of the aging mice with T2DM, whereas the liver cells of the young and non-diabetic aging mice appeared normal.
To further investigate the differences in liver metabolism between aging mice with and without T2DM, high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (MS) was employed to analyze the metabolic profiles of frozen liver tissues from the non-diabetic aging mice and the aging mice with T2DM. The MS data were processed using Mass Profiler software and subjected to partial least squares discriminant analysis (PLS-DA) and orthogonal projections to latent structures-discriminant analysis (OPLS) using SIMCA-P 14.1 for multivariate biochemical pattern recognition. The PLS-DA and OPLS analyses revealed significant differences in metabolites between the two groups. Hierarchical clustering analysis and significance analysis for microarrays were performed using Multi Experiment Viewer software, identifying 64 significantly altered metabolites between the non-diabetic aging mice and the aging mice with T2DM. Pathway analysis using Metabolomics Pathway Analysis (MetPA) identified 39 altered pathways, providing insights into the metabolic changes associated with T2DM in aging mice.
To elucidate the underlying reasons for the observed changes in the metabolic profile, messenger RNA (mRNA) expression profiles were examined in the liver tissues of the non-diabetic aging mice and the aging mice with T2DM. GeneSpring software V13.0 was used to calculate the differences in gene expression. The analysis revealed 2486 downregulated and 3131 upregulated mRNAs in the aging mice with T2DM compared to the non-diabetic aging mice. Cluster analysis was performed using Cluster 3.0, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis was conducted using the KEGG Orthology Based Annotation System (KOBAS). This analysis identified 57 significantly enriched KEGG signaling pathways, shedding light on the molecular mechanisms underlying T2DM in aging mice.
To integrate the findings from the metabolomics and transcriptomics analyses, integrated molecular pathway analysis was performed using the IMPaLA web tool. By combining the data from 64 significant metabolites and 5617 differentially expressed genes, 31 pathways were identified, including 13 metabolism-related pathways and six pathways related to human diseases. Notably, signaling pathways associated with carbohydrate, lipid, and amino acid metabolism, as well as insulin resistance, were found to be significantly altered in the aging mice with T2DM.
In conclusion, this study provides a comprehensive analysis of the metabolic and molecular changes in the liver of aging mice with T2DM. The integration of metabolomics and transcriptomics revealed that the pathogenesis of T2DM in aging mice involves disruptions in glucose, lipid, and amino acid metabolism, as well as insulin resistance. These findings offer valuable insights into the metabolic characteristics of T2DM in aging individuals and highlight potential therapeutic targets for the treatment of older adults with T2DM. However, further validation of these findings is necessary to confirm their clinical relevance and applicability.
doi.org/10.1097/CM9.0000000000001554
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