Objective To summarize the research progress of postmenopausal breast cancer and estrogen metabolites, which is aimed at providing the basis for early diagnosis and early treatment of postmenopausal breast cancer, at the same time, providing beneficial information for the future study. Methods In recent years, the literatures about postmenopausal breast cancer and estrogen metabolites were reviewed from the databases of WanFang, VIP, CNKI, PubMed, and so on, to make an review. Results Estrogen metabolites had a dual role for postmenopausal breast cancer, such as 2-hydroxyestrone (2-OHE1), 2-methoxyestrone1 (2-MeOE1), and 4-methoxyestrone1 (4-MeOE1) played a protective role for postmenopausal breast cancer, but 4-hydroxyestrone (4-OHE1) and 16α-hydroxyestrone (16α-OHE1) played a carcinogenic role for postmenopausal breast cancer, so it needed to be further studied. Conclusions Estrogen metabolites may be a reliable predictor for the risk of postmenopausal breast cancer, it is not only to provide clues for the mechanism of postmenopausal breast cancer, but also provide new train of thought for early diagnosis and treatment of postmenopausal breast cancer.
Gut microbiota and its metabolites in various human diseases have gradually become a research hotspot in the current medical community. And coronary artery disease is currently one of the most threatening clinical cardiovascular diseases in the world, so the use of gut microbiota and its metabolites in the development of its pathophysiology has also received more and more attention. Therefore, this paper reviews the effects of gut microbiota and its metabolites on coronary artery disease, as well as the research progress of intervening gut microbiota and its metabolites as therapeutic targets, hoping to expand the future research direction in this field and provide new ideas with treating coronary artery disease.
Objective To explore composition of volatile organic compounds (VOCs) in exhaled breath of low-dose radiation-damaged Sprague-Dawely (SD) rats by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS), and search for the differential metabolites of VOCs in the series of rats after radiation damage, and establish a noninvasive radiation damage detection method. Methods SD rats were randomly divided into five groups (a blank group, a 0.5-Gy group, a 1-Gy group, a 2-Gy group, and a 3-Gy group), with 8 rats in each group. A low-dose radiation injury model was established in rats. After the cobalt source radiation damage was performed, the body weight of rats was recorded, peripheral blood hematology was analyzed, and the exhaled breath of rats was collected on the 1st, 5th, 9th and 13th day. The composition of VOCs in the exhaled breath was analyzed by using the TD30-GC-MS technique, and multivariate statistical analyses were carried out to explore and obtain the differentiated metabolites after the radiation damage. Results After radiation damage, the rats showed a short-term decrease in body weight, peripheral blood and lung tissue sections were different, and the content of VOCs components in the exhaled breath of the damaged rats was significantly different from that of the rats in the blank group. Among them, four VOCs, acetophenone, nonanal, decanal and tetradecane increased, while heptane, chlorobenzene, paraxylene and m-dichlorobenzene decreased. Conclusions Through the GC-MS analysis of the exhaled breath of rats, eight components of VOCs in the exhaled breath of rats can be used as differential metabolites of radiation damage. This study lays a foundation for the establishment of a GC-MS analysis method for the components of VOCs in the exhaled breath of rats, as well as for the development of a nondestructive analytical assay for biological radiation damage.
ObjectiveTo investigate the postnatal changes in urinary metabolic amino acid levels in infants with retinopathy of prematurity (ROP) and their effect on ROP, and to analyze the amino acid metabolic pathways that may be involved in the development of ROP. MethodsA retrospective cohort study. From January 2020 to December 2023, 65 premature infants with severe ROP (ROP group) who were hospitalized, born with gestational age ＜32 weeks in Children's Hospital Affiliated to Zhengzhou University were included in the study. Fifty premature infants with matched sex and gestational age and no ROP were selected as the control group. Urine amino acids and their derivatives were detected by gas chromatography-mass spectrometry. The two groups were compared by independent sample t test. The metabonomics of urinary amino acids was analyzed by orthogonal partial least squares discriminant analysis (OPLS-DA) model. The variable projection importance (VIP) score ＞1 suggested that the substance was two groups of differentially expressed amino acids. The predictive value of urinary amino acids for severe ROP was compared by using the receiver's operating characteristic (ROC) curve and the area under the curve. After t test and metabolomics analysis, the two groups of amino acids with large differences were normalized and compared by Pearson correlation analysis. The Kyoto Encyclopedia of Genes and Genomes database was used to analyze the metabolic pathways of differentially expressed amino acids involved in ROP. ResultsCompared with the control group, the concentrations of oxalic acid -2 and thiodiacetic acid-2 in urine metabolites of children in ROP group were significantly decreased, while the concentrations of 4-hydroxybutyric acid-2, 3-methylpentadienoic acid-2(1), 2-ketoglutarate-ox-2(2) and 3, 6-epoxy-dodecanedioic acid-2 were significantly increased, with statistical differences (t=0.036, 0.005, 0.038, 0.032, 0.022, 0.011; P＜0.05). The results of OPLS-DA analysis showed that amino acids of urinary metabolites in ROP group and control group were distributed in the left and right regions of the scatter plot, and there was a satisfactory separation trend between the two groups (R2Ycum=0.057 4, Q2cum=0.025 7, P＜0.05). As shown in the S-Plot, the amino acids biased towards two stages are glycolic acid-2, phosphoric acid-3, oxalic acid-2, thiodiacetic acid-2, 4-hydroxybutyric acid-2, 3-methylcrotonylglycine-1, 3-methylpentadienoic acid-2(1), 2-ketoglutarate-ox-2(2) and 3, 6-epoxy- dodecanedioic acid-2, respectively. Eleven differentially expressed amino acids with VIP score ＞1 were screened, among which the highest VIP score was oxalate-2, glycerate-3, phosphoric acid-3, 3-methylcrotonylglycine-1, uranoic acid -3 and thiodiacetic acid-2. The difference of amino acid concentration between the two groups was the highest in 4-hydroxybutyric acid-2 and thiodiacetic acid-2. The correlation between oxalic acid-2 and glycerate-3 was the highest (r=0.830, P＜0.001), and most amino acids were positive correlated. ROC curve fitting analysis showed that the combined prediction of 11 differenly-expressed amino groups had the largest area under the curve (0.816), the cutoff value was 0.531, and the sensitivity and specificity were 83.1% and 70.0%, respectively. The enrichment analysis of these 11 amino acids with significant differences suggested that the main pathways involved included butyrate metabolism, glyoxylic acid and dicarboxylic acid metabolism and lipoic acid metabolism. ConclusionAbnormal amino acid metabolism of 4-hydroxybutyrate-2, 3-methylpentadienoic acid-2(1), thiodiacetic acid-2, 2-ketoglutarate-ox-2(2), 3, 6-epoxy-dodecanedioic acid-2 may have a certain effect on the occurrence of ROP.
ObjectiveTo explore the causal relationship between immune cells and heart failure (HF), and the mediating role of serum metabolites, in order to identify potential biomarkers and therapeutic targets. MethodsWe employed a two-sample Mendelian randomization (MR) analysis method based on genome-wide association study (GWAS) data, analyzing the direct and indirect effects of 731 types of immune cells and 1 400 metabolites on HF. We selected valid instrumental variables and conducted statistical analyses using R software. The primary analysis was performed using the inverse variance weighted method, supplemented by MR-Egger analysis and weighted median method. The stability of the results was assessed through tests such as Cochran’s Q test. ResultsOur research found a negative causal relationship between PD-L1 on CD14−CD16+ and HF. Sensitivity analysis supported this result. The reverse MR analysis did not find an effect of HF on PD-L1 on CD14−CD16+, indicating that PD-L1 on CD14−CD16+ may play a unidirectional role in reducing the risk of HF. Further mediation MR analysis showed that PD-L1 on CD14−CD16+ might influence the risk of HF onset by regulating the levels of sphingomyelin (d17:1/14:0, d16:1/15:0), with a mediation effect ratio of 6.7%. ConclusionPD-L1 on CD14−CD16+ may reduce the risk of HF by elevating the levels of sphingomyelin (d17:1/14:0, d16:1/15:0), which provides a new perspective for understanding the pathogenesis of HF.
Objective To analyze the causal relationship between cerebrospinal fluid (CSF) metabolites and tic disorder (TD) based on two-sample Mendelian randomization (MR). Methods CSF metabolites data from humans were downloaded from genome-wide association study databases, and CSF metabolites were selected as exposure factors. single nucleotide polymorphisms (SNPs) strongly associated with the exposure factors and independent of each other were selected as instrumental variables. The TD dataset from the Finngen database was downloaded, including 365 cases of TD and 411 816 controls. Analysis was conducted using inverse variance weighting, MR-Egger, weighted median, weighted mode, and simple mode. Sensitivity analysis was conducted using leave-one-out, and multiple-effects testing was conducted using MR-Egger and MR-PRESSO. Heterogeneity was detected using Cochran’s Q. Results A total of 9 CSF metabolites were found to have a causal relationship with the occurrence and development of TD (P<0.05), with a total of 394 SNPs included in the analysis. Inverse variance weighting results showed that N-acetylneuraminic acid [odds ratio (OR)=2.715, 95% confidence interval (CI) (1.102, 6.961), P=0.030], γ-glutamylglutamine [OR=1.402, 95%CI (1.053, 1.868), P=0.021], lysine [OR=2.816, 95%CI (1.084, 7.319), P=0.034] could increase the risk of TD. Cysteinylglycine disulfide [OR=0.437, 95%CI (0.216, 0.885), P=0.021], propionylcarnitine [OR=0.762, 95%CI (0.616, 0.941), P=0.012], pantothenate [OR=0.706, 95%CI (0.523, 0.952), P=0.023], gulareic acid [OR=0.758, 95%CI (0.579, 0.992), P=0.044], and cysteine-glycine [OR=0.799, 95%CI (0.684, 0.934), P=0.005] could reduce the risk of TD. The results of leave-one-out sensitivity analysis were stable, and no horizontal pleiotropy or heterogeneity was observed. Conclusions N-acetylneuraminic acid, γ-glutamylglutamine, and lysine can increase the risk of TD, but cysteinylglycine disulfide, propionylcarnitine, pantothenate, gulagic acid and cysteine-glycine can reduce the risk of TD. However, the mechanism of their effects on TD still needs to be further explored.
In recent years, the diversity of gut microbiota and the role of its metabolites in cardiovascular disease (CVD) have attracted widespread attention. Gut microbiota metabolites not only play an important role in maintaining gut health, but may also influence cardiovascular health through a variety of mechanisms. As one of the important products of gut microbiota metabolism, sulfate’s biosynthetic pathway, metabolic dynamics and potential effects on cardiovascular system have become the focus of research. However, the current research on the relationship between sulfate and cardiovascular disease still has some shortcomings, including the mechanism is not clear, and clinical data are limited. This article reviewed the biosynthesis of sulfate and its mechanism of action in cardiovascular diseases, and combined with the existing clinical research results, aimed to provide new perspectives and ideas for future research, in order to promote the in-depth exploration and development of this field.