Diabetic nephropathy (DN) is the main cause of end stage renal disease (ESRD). Glomerulus damage is one of the primary pathological changes in DN. To reveal the gene expression alteration in the glomerulus involved in DN development, we screened the Gene Expression Omnibus (GEO) database up to December 2020. Eleven gene expression datasets about gene expression of the human DN glomerulus and its control were downloaded for further bioinformatics analysis. By using R language, all expression data were extracted and were further cross-platform normalized by Shambhala. Differentially expressed genes (DEGs) were identified by Student's t-test coupled with false discovery rate (FDR) (P < 0.05) and fold change (FC) ≥1.5. DEGs were further analyzed by the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to enrich the Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. We further constructed a protein-protein interaction (PPI) network of DEGs to identify the core genes. We used digital cytometry software CIBERSORTx to analyze the infiltration of immune cells in DN. A total of 578 genes were identified as DEGs in this study. Thirteen were identified as core genes, in which LYZ, LUM, and THBS2 were seldom linked with DN. Based on the result of GO, KEGG enrichment, and CIBERSORTx immune cells infiltration analysis, we hypothesize that positive feedback may form among the glomerulus, platelets, and immune cells. This vicious cycle may damage the glomerulus persistently even after the initial high glucose damage was removed. Studying the genes and pathway reported in this study may shed light on new knowledge of DN pathogenesis.

Background: Recent studies have shown that obesity may contribute to the pathogenesis of benign prostatic hyperplasia (BPH). However, the mechanism of this pathogenesis is not fully understood. Methods: A prospective case–control study was conducted with 30 obese and 30 nonobese patients with BPH. Prostate tissues were collected and analyzed using ultra performance liquid chromatography ion mobility coupled with quadrupole time-of-flight mass spectrometry (UPLC-IMS-Q-TOF). Results: A total of 17 differential metabolites (3 upregulated and 14 downregulated) were identified between the obese and nonobese patients with BPH. Topological pathway analysis indicated that glycerophospholipid (GP) metabolism was the most important metabolic pathway involved in BPH pathogenesis. Seven metabolites were enriched in the GP metabolic pathway. lysoPC (P16:0/0:0), PE (20:0/20:0), PE (24:1(15Z)/18:0), PC (24:1(15Z)/14:0), PC (15:0/24:0), PE (24:0/18:0), and PC (16:0/18:3(9Z,12Z,15Z)) were all significantly downregulated in the obesity group, and the area under the curve (AUC) of LysoPC (P-16:0/0/0:0) was 0.9922. The inclusion of the seven differential metabolites in a joint prediction model had an AUC of 0.9956. Thus, both LysoPC (P-16:0/0/0:0) alone and the joint prediction model demonstrated good predictive ability for obesity-induced BPH mechanisms. Conclusions: In conclusion, obese patients with BPH had a unique metabolic profile, and alterations in PE and PC in these patients be associated with the development and progression of BPH.

Background: Chronic prostatitis may be a risk factor for developing proliferative changes in the prostate, although the underlying mechanisms are not entirely comprehended. Materials and methods: Fifty individual prostate tissues were examined in this study, consisting of 25 patients diagnosed with prostatic hyperplasia combined with histologic chronic inflammation and 25 patients diagnosed with prostatic hyperplasia alone. We employed UPLC-Q-TOF-MS-based untargeted metabolomics using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry to identify differential metabolites that can reveal the mechanisms that underlie the promotion of prostate hyperplasia by histologic chronic inflammation. Selected differential endogenous metabolites were analyzed using bioinformatics and subjected to metabolic pathway studies. Results: Nineteen differential metabolites, consisting of nine up-regulated and ten down-regulated, were identified between the two groups of patients. These groups included individuals with combined histologic chronic inflammation and those with prostatic hyperplasia alone. Glycerolipids, glycerophospholipids, and sphingolipids were primarily the components present. Metabolic pathway enrichment was conducted on the identified differentially expressed metabolites. Topological pathway analysis revealed the differential metabolites’ predominant involvement in sphingolipid, ether lipid, and glycerophospholipid metabolism. The metabolites involved in sphingolipid metabolism were Sphingosine, Cer (d18:1/24:1), and Phytosphingosine. The metabolites involved in ether lipid metabolism were Glycerophosphocholine and LysoPC (O-18:0/0:0). The metabolites involved in glycerophospholipid metabolism were LysoPC (P-18:0/0:0) and Glycerophosphocholine. with Impact > 0. 1 and FDR < 0. 05, the most important metabolic pathway was sphingolipid metabolism. Conclusions: In conclusion, our findings suggest that patients with prostate hyperplasia and combined histologic chronic inflammation possess distinctive metabolic profiles. These differential metabolites appear to play a significant role in the pathogenesis of histologic chronic inflammation-induced prostate hyperplasia, primarily through the regulation of sphingolipids and glycerophospholipids metabolic pathways. The mechanism by which histologic chronic inflammation promotes prostate hyperplasia was elucidated through the analysis of small molecule metabolites. These findings support the notion that chronic prostatitis may contribute to an increased risk of prostate hyperplasia.

Diabetic kidney disease (DKD) is one of the most severe complications of diabetes mellitus, with limited effective therapeutic interventions. Alternate-day fasting (ADF) shows potential in treating DKD, though its mechanisms are not fully understood. In this study, BTBR ob/ob mice underwent 12 weeks of ADF, and high-resolution untargeted metabolomics were performed to uncover the underlying mechanisms. After 12 weeks of ADF, the BTBR ob/ob mice exhibited weight loss, lower blood glucose and LDL-C levels, reduced 24-h urinary protein excretion, and decreased renal collagen deposition. A total of 44 metabolites were differentially expressed, with 25 up-regulated and 19 down-regulated. Notably, hyocholic acid (HCA) and indole-3-propionic acid (IPA), both products of intestinal bacteria, can modulating inflammation were differentially expressed. Furthermore, the kidneys of BTBR ob/ob mice showed significantly lower NF-κB pathway activity and reduced inflammation after 12 weeks of ADF. This study indicates that ADF may alleviate DKD progression by modulating HCA, IPA, and decreasing inflammation.

Type 2 diabetes mellitus (T2DM) can cause prostate damage and affect male reproductive function, but the underlying mechanisms are not completely understood. In this study, we used liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics to identify endogenous metabolites in the prostate of a T2DM mouse model. The selected endogenous metabolites were then subjected to bioinformatics analysis and metabolic pathway studies to understand their role in the development of T2DM-induced prostate damage. We used male homozygous BTBR ob/ob mice (n = 12) and BTBR WT mice (n = 11) in this study. We monitored changes in blood glucose, body weight, prostate weight, and prostate index, as well as performed hematoxylin and eosin (H&E) staining and observed that the prostate of the BTBR ob/ob was damaged. We then used ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) for metabolomics analysis. The stability of the model was validated using principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA). Using variable importance in projection (VIP) > 1, false discovery rate (FDR) < 0.05, and coefficient of variation (CV) < 30 as criteria, a total of 149 differential metabolites (62 upregulated and 87 downregulated) were identified between the prostates of the two groups of mice. Topological pathway analysis showed that these differential metabolites were mainly involved in sphingolipid (SP) and glycerophospholipid (GP) metabolism. In conclusion, our study not only emphasizes the damage caused by T2DM to the prostate but also provides new insights into the potential mechanisms of T2DM-induced male reproductive dysfunction.

Background: Genetic factors play important roles in the development of type 2 diabetes mellitus and its complications. Diabetic kidney disease, a common microangiopathic complication of diabetes, is linked to an increased risk of major cardiovascular events and overall mortality. Tetrahydrobiopterin deficiency is implicated in DKD pathogenesis, and the QDPR gene is critical for maintaining BH4 homeostasis. The present study was designed to screen single nucleotide polymorphisms in the QDPR coding region, and assess their associations with T2DM and DKD. Methods: Genetic analysis for SNPs in the coding region was conducted using a systematic screening approach. Direct sequencing and statistical analysis tools were employed to identify potentially functional SNPs. Following this, rs3733570 was selected based on its potential biological relevance and frequency in the target population. A total of 1,844 participants from Kai Luan General Hospital (Tangshan, China) were included for validation. Genotyping of QDPR rs3733570 was performed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) in 690 healthy controls, 818 patients with T2DM, and 336 patients with DKD. Results: Regression analysis showed that the rs3733570 AA genotype was associated with increased risk of T2DM (OR = 1.33, 95% CI: 0.99–1.79, p < 0.05). In stratified analysis, carriers of the AA genotype with dyslipidemia had a higher risk of DKD (OR = 1.80, 95% CI: 1.03–3.16, p < 0.05). Conclusion: The QDPR rs3733570 AA genotype may increase susceptibility to T2DM and, in the presence of dyslipidemia, to DKD in the Chinese Han population. After adjustment, the AA genotype showed a borderline association with T2DM risk (OR = 1.33, 95% CI: 0.99–1.79, p = 0.057).