Changes and Significance of Central Carbon Metabolism before and after Metformin Treatment of Type 2 Diabetes Based on Mass Spectrometry.

BACKGROUND: An imbalance in energy metabolism serves as a causal factor for type 2 diabetes (T2D). Although metformin has been known to ameliorate the overall energy metabolism imbalance, but the direct correlation between metformin and central carbon metabolism (CCM) has not been thoroughly investigated. In this study, we employed a high-performance ion chromatography-tandem mass spectrometry (HPIC-MS/MS) technique to examine the alterations and significance of CCM both before and after metformin treatment for T2D. METHODS: We recruited 29 participants, comprising 10 individuals recently diagnosed with T2D (T2D group). Among these, 10 patients underwent a 4-6-week treatment with metformin (MET group). Additionally, we included 9 healthy subjects (CON group). Employing HPIC-MS/MS, we quantitatively analyzed 56 metabolites across 18 biologically relevant metabolic pathways associated with CCM. Univariate and multivariate statistical analyses were utilized to identify differential metabolites. Subsequently, correlation analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted on the identified differential metabolites. RESULTS: We identified seven distinct metabolites in individuals with T2D (p < 0.05). Notably, cyclic 3',5'-Adenosine MonoPhosphate (AMP), Glucose 6-phosphate, L-lactic acid, Maleic acid, and Malic acid exhibited a reversal to normal levels following metformin treatment. Furthermore, Malic acid demonstrated a positive correlation with L-lactic acid (r = 0.94, p < 0.05), as did succinic acid with malic acid (r = 0.81, p < 0.05), L-lactic acid with succinic acid (r = 0.78, p < 0.05), and L-lactic acid with glucose-6-phosphate (r = 0.72, p < 0.05). These metabolites were notably enriched in pyruvate metabolism (p = 0.005), tricarboxylic acid cycle (TCA) (p = 0.007), propanoate metabolism (p = 0.007), and glycolysis or gluconeogenesis (p = 0.009), respectively. CONCLUSIONS: We employed HPIC-MS/MS to uncover alterations in CCM among individuals recently diagnosed with T2D before and after metformin treatment. The findings suggest that metformin may ameliorate the energy metabolism imbalance in T2D by reducing intermediates within the CCM pathway.

Reference intervals for cardiometabolic risk factors in China: a national multicenter cross-sectional study on an adult population sample.

Background: The reference intervals (RIs) of adult blood lipid parameters currently used in China are not derived from the results of research in local populations and have not been adjusted for age and sex. In this study, we aimed to determine accurate RIs for blood lipid parameters and blood glucose (GluG) for Chinese adults using a national multicenter study. Methods: A total of 11,333 adults between 18 and 90 years of age were recruited in seven representative regions in China between June 2020 and December 2020. Hospitals participating in the study were regrouped into two geographical regions, southern China (Changsha, Chengdu, Hangzhou, and Nanning) and northern China (Beijing, Shenyang, and Ningxia), according to their geographical and administrative location. All samples were freshly collected and measured collectively in one laboratory on the Mindray full Automatic biochemical analyzer chemistry BS2000 analytical systems. Outliers were removed using the Tukey test. Three-level nested analysis of variance and scatter plot were used to explore the variations in sex, age, and region. Percentile curves of each indicator were plotted using the least mean square (LMS) method. The lower limit (2.5th percentile) and the upper limit (97.5th percentile) of the RI were determined by using nonparametric statistical methods. We also calculated the 90% confidence interval (CI) for the lower and upper limits. Results: A total of 8,283 participants were enrolled in the final analysis, with 3,593 (43.4%) men and 4,690 (56.6%) women. Regionality was observed in three analytes [small dense low density lipoprotein cholesterol (sd-LDLC), GluG, and apolipoprotein A1 (ApoA1)]. In northern China, the sd-LDLC and GluG levels in Shenyang were significantly higher than those in Ningxia and Beijing (P<0.05). In southern China, the sd-LDLC and GluG levels in Nanning were significantly higher than those in the three other cities (P<0.05), whereas the sd-LDLC and GluG levels in Chengdu were significantly lower than those in the three other cities (P<0.05). The level of ApoA1 in Chengdu was significantly higher than that in the three other cities. The homocysteine (HCY) level in male participants was clearly higher than that in female participants [ratio of standard deviation (SDR)sex =0.56], whereas the levels of high density lipoprotein cholesterol (HDLC) (SDRsex =0.40) and ApoA1 (SDRsex =0.27) in males were lower. The GluG and HCY level increased gradually with age. In females aged 45-55 years, there was an interesting change in scatter charts, where triglyceride (TG) and total cholesterol (TC) increased rapidly. We also found that for the age group of >55 years, the levels of TG and TC in females gradually surpassed those in males. Conclusions: The findings of this study may help establish age- and sex-specific reference values for the blood lipids of Chinese adults and serve as a valuable guide for the screening, diagnosis, treatment, prevention, and monitoring of cardiovascular disease (CVD).

Bibliometrics and visual analysis of metformin and gut microbiota from 2012 to 2022: A systematic review.

BACKGROUND: Metformin is an old drug used for the treatment of type 2 diabetes mellitus and can play a variety of roles by regulating the gut microbiota. The number of research articles on metformin in the gut microbiota has increased annually; however, no bibliometric tools have been used to analyze the research status and hot trends in this field. This study presents a bibliometric analysis of publications on metformin and gut microbiota. METHODS: We searched the Web of Science core collection database on June 8, 2023, for papers related to metformin and gut microbiota from 2012 to 2022. We used Microsoft Excel 2021, VOSviewer1.6.19, CiteSpace 6.2.4, and R software package "bibliometrix" 4.0.0 to analyze the countries, institutions, authors, journals, citations, and keywords of the included publications. RESULTS: We included 517 papers, and the trend in publications increased over the last 11 years. The 517 articles were from 57 countries, including 991 institutions and 3316 authors, and were published in 259 journals. China led all countries (233 papers) and the most influential institution was the Chinese Academy of Sciences (16 papers). PLOS ONE (19 papers) was the most popular journal, and Nature (1598 citations) was the most cited journal. Li and Kim were the 2 most published authors (six papers each), and Cani (272 co-citations) was the most co-cited author. "Metabolites," "aging," and "intestinal barrier" were emerging topics in this field. CONCLUSIONS: This bibliometric study comprehensively summarizes the research trends and progress of metformin and gut microbiota, and provides new research topics and trends for studying the effects of metformin on gut microbiota in different diseases.