Background: Roux-en-Y gastric bypass surgery (RYGB) improves biochemical and histological parameters of diabetic kidney disease (DKD). Targeted adjunct medical therapy may enhance renoprotection following RYGB.

Methods: The effects of RYGB and RYGB plus fenofibrate, metformin, ramipril, and rosuvastatin (RYGB-FMRR) on metabolic control and histological and ultrastructural indices of glomerular and proximal tubular injury were compared in the Zucker Diabetic Sprague Dawley (ZDSD) rat model of DKD. Renal cortical transcriptomic (RNA-sequencing) and urinary metabolomic (¹H-NMR spectroscopy) responses were profiled and integrated. Transcripts were assigned to kidney cell types through in silico deconvolution in kidney single-nucleus RNA-sequencing and microdissected tubular epithelial cell proteomics datasets. Medication-specific transcriptomic responses following RYGB-FMRR were explored using a network pharmacology approach. Omic correlates of improvements in structural and ultrastructural indices of renal injury were defined using a molecular morphometric approach.

Results: RYGB-FMRR was superior to RYGB alone with respect to metabolic control, albuminuria, and histological and ultrastructural indices of glomerular injury. RYGB-FMRR reversed DKD-associated changes in mitochondrial morphology in the proximal tubule to a greater extent than RYGB. Attenuation of transcriptomic pathway level activation of pro-fibrotic responses was greater after RYGB-FMRR than RYGB. Fenofibrate was found to be the principal medication effector of gene expression changes following RYGB-FMRR, which led to the transcriptional induction of PPARα-regulated genes that are predominantly expressed in the proximal tubule and which regulate peroxisomal and mitochondrial fatty acid oxidation (FAO). After omics integration, expression of these FAO transcripts positively correlated with urinary levels of PPARα-regulated nicotinamide metabolites and negatively correlated with urinary tricarboxylic acid (TCA) cycle intermediates. Changes in FAO transcripts and nicotinamide and TCA cycle metabolites following RYGB-FMRR correlated strongly with improvements in glomerular and proximal tubular injury.

Conclusions: Integrative multi-omic analyses point to PPARα-stimulated FAO in the proximal tubule as a dominant effector of treatment response to combined surgical and medical therapy in experimental DKD. Synergism between RYGB and pharmacological stimulation of FAO represents a promising combinatorial approach to the treatment of DKD in the setting of obesity.

Obesity is an excess accumulation of body fat. Its progression rate has remained high in recent years. Therefore, the aim of this study was to diagnose important differentially expressed genes (DEGs) associated in its development, which may be used as novel biomarkers or potential therapeutic targets for obesity. The gene expression profile of E-MTAB-6728 was downloaded from the database. After screening DEGs in each ArrayExpress dataset, we further used the robust rank aggregation method to diagnose 876 significant DEGs including 438 up regulated and 438 down regulated genes. Functional enrichment analysis was performed. These DEGs were shown to be significantly enriched in different obesity related pathways and GO functions. Then protein–protein interaction network, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. The module analysis was performed based on the whole PPI network. We finally filtered out STAT3, CORO1C, SERPINH1, MVP, ITGB5, PCM1, SIRT1, EEF1G, PTEN and RPS2 hub genes. Hub genes were validated by ICH analysis, receiver operating curve (ROC) analysis and RT-PCR. Finally a molecular docking study was performed to find small drug molecules. The robust DEGs linked with the development of obesity were screened through the expression profile, and integrated bioinformatics analysis was conducted. Our study provides reliable molecular biomarkers for screening and diagnosis, prognosis as well as novel therapeutic targets for obesity.

Purpose: Hyperparathyroidism is the third most common endocrine disease. Parathyroid adenoma (PA) accounts for approximately 85% of cases of primary hyperparathyroidism, but the molecular mechanism is not fully understood. Herein, we aimed to investigate the genetic and transcriptomic profiles of sporadic PA.

Methods: Whole-exome sequencing (WES) and transcriptome sequencing (RNA-seq) of 41 patients with PA and RNA-seq of 5 normal parathyroid tissues were performed. Gene mutations and characterized expression changes were identified. To elucidate the molecular mechanism underlying PA, unsupervised consensus clustering of RNA-seq data was performed. The correlations between the sequencing data and clinicopathological features of these patients were analyzed.

Results: Previously reported PA driver gene mutations, such as MEN1 (9/41), mTOR (4/41), ZFX (3/41), CASR (3/41), EZH2 (2/41) and FAT1 (2/41), were also identified in our cohort. Furthermore, somatic mutation of EZH1, which had not been reported in PA, was found in 4 samples. RNA-seq showed that the expression levels of 84 genes were upregulated and 646 were downregulated in PA samples compared with normal samples. Unsupervised clustering analysis of RNA-seq data clustered these patients into 10 subgroups related to mutation or abnormal expression of a group of potential pathogenic genes.

Conclusion: MEN1, EZH2, CASR, EZH1, ZFX, mTOR and FAT1 mutations in PA were revealed. According to the RNA-seq data clustering analysis, cyclin D1, β-catenin, VDR, CASR and GCM2 may be important factors contributing to the PA gene expression profile.