Urinary Sediment Transcriptomic and Longitudinal Data to Investigate Renal Function Decline in Type 1 Diabetes

A Composite Biomarker Signature of Type 1 Diabetes Risk Identified via Augmentation of Parallel Multi-Omics Data from a Small Cohort

Background

Biomarkers of early pathogenesis of type 1 diabetes (T1D) are crucial to enable effective prevention measures in at-risk populations before significant damage occurs to their insulin producing beta-cell mass. We recently introduced the concept of integrated parallel multi-omics and employed a novel data augmentation approach which identified promising candidate biomarkers from a small cohort of high-risk T1D subjects. We now validate selected biomarkers to generate a potential composite signature of T1D risk.

Methods

Twelve candidate biomarkers, which were identified in the augmented data and selected based on their fold-change relative to healthy controls and cross-reference to proteomics data previously obtained in the expansive TEDDY and DAISY cohorts, were measured in the original samples by ELISA.

Results

All 12 biomarkers had established connections with lipid/lipoprotein metabolism, immune function, inflammation, and diabetes, but only 7 were found to be markedly changed in the high-risk subjects compared to the healthy controls: ApoC1 and PON1 were reduced while CETP, CD36, FGFR1, IGHM, PCSK9, SOD1, and VCAM1 were elevated.

Conclusions

Results further highlight the promise of our data augmentation approach in unmasking important patterns and pathologically significant features in parallel multi-omics datasets obtained from small sample cohorts to facilitate the identification of promising candidate T1D biomarkers for downstream validation. They also support the potential utility of a composite biomarker signature of T1D risk characterized by the changes in the above markers.

Multiomics characterization of cell type repertoires for urine liquid biopsies

Urine is assayed alongside blood in medicine, yet current clinical diagnostic tests utilize only a small fraction of its total biomolecular repertoire, potentially foregoing high-resolution insights into human health and disease. In this work, we characterized the joint landscapes of transcriptomic and metabolomic signals in human urine. We also compared the urine transcriptome to plasma cell-free RNA, identifying a distinct cell type repertoire and enrichment for metabolic signal. Untargeted metabolomic measurements identified a complementary set of pathways to the transcriptomic analysis. Our findings suggest that urine is a promising biofluid yielding prognostic and detailed insights for hard-to-biopsy tissues with low representation in the blood, offering promise for a new generation of liquid biopsies.

Serum glycoprotein non-metastatic melanoma protein B (GPNMB) level as a potential biomarker for diabetes mellitus-related cataract: A cross-sectional study

BACKGROUND

Diabetes mellitus (DM), a metabolic disease that has attracted significant research and clinical attention over the years, can affect the eye structure and induce cataract in patients diagnosed with DM. Recent studies have indicated the relationship between glycoprotein non-metastatic melanoma protein B (GPNMB) and DM and DM-related renal dysfunction. However, the role of circulating GPNMB in DM-associated cataract is still unknown. In this study, we explored the potential of serum GPNMB as a biomarker for DM and DM-associated cataract.

METHODS

A total of 406 subjects were enrolled, including 60 and 346 subjects with and without DM, respectively. The presence of cataract was evaluated and serum GPNMB levels were measured using a commercial enzyme-linked immunosorbent assay kit.

RESULTS

Serum GPNMB levels were higher in diabetic individuals and subjects with cataract than in those without DM or cataract. Subjects in the highest GPNMB tertile group were more likely to have metabolic disorder, cataract, and DM. Analysis performed in subjects with DM elucidated the correlation between serum GPNMB levels and cataract. Receiver operating characteristic (ROC) curve analysis also indicated that GPNMB could be used to diagnose DM and cataract. Multivariable logistic regression analysis illustrated that GPNMB levels were independently associated with DM and cataract. DM was also found to be an independent risk factor for cataract. Further surveys revealed the combination of serum GPNMB levels and presence of DM was associated with a more precise identification of cataract than either factor alone.

CONCLUSIONS

Increased circulating GPNMB levels are associated with DM and cataract and can be used as a biomarker of DM-associated cataract.

Exploring Computational Data Amplification and Imputation for the Discovery of Type 1 Diabetes (T1D) Biomarkers from Limited Human Datasets

Background: Type 1 diabetes (T1D) is a devastating disease with serious health complications. Early T1D biomarkers that could enable timely detection and prevention before the onset of clinical symptoms are paramount but currently unavailable. Despite their promise, omics approaches have so far failed to deliver such biomarkers, likely due to the fragmented nature of information obtained through the single omics approach. We recently demonstrated the utility of parallel multi-omics for the identification of T1D biomarker signatures. Our studies also identified challenges. Methods: Here, we evaluated a novel computational approach of data imputation and amplification as one way to overcome challenges associated with the relatively small number of subjects in these studies. Results: Using proprietary algorithms, we amplified our quadra-omics (proteomics, metabolomics, lipidomics, and transcriptomics) dataset from nine subjects a thousand-fold and analyzed the data using Ingenuity Pathway Analysis (IPA) software to assess the change in its analytical capabilities and biomarker prediction power in the amplified datasets compared to the original. These studies showed the ability to identify an increased number of T1D-relevant pathways and biomarkers in such computationally amplified datasets, especially, at imputation ratios close to the “golden ratio” of 38.2%:61.8%. Specifically, the Canonical Pathway and Diseases and Functions modules identified higher numbers of inflammatory pathways and functions relevant to autoimmune T1D, including novel ones not identified in the original data. The Biomarker Prediction module also predicted in the amplified data several unique biomarker candidates with direct links to T1D pathogenesis. Conclusions: These preliminary findings indicate that such large-scale data imputation and amplification approaches are useful in facilitating the discovery of candidate integrated biomarker signatures of T1D or other diseases by increasing the predictive range of existing data mining tools, especially when the size of the input data is inherently limited.

Downregulation of glycoprotein non-metastatic melanoma protein B prevents high glucose-induced angiogenesis in diabetic retinopathy

Diabetic retinopathy (DR), a microvascular complication characterized by abnormal angiogenesis, is the most common reason for irreversible blindness. Glycoprotein non-metastatic melanoma protein B (GPNMB), as a transmembrane protein, was found to be associated with angiogenesis. This study aims to investigate the role of GPNMB in DR. The levels of GPNMB and Integrin β1 were detected by real-time PCR and western blot and were found to be increased in human retinal microvascular endothelial cells (HRMECs) with high glucose (HG, 25 mmol/L) treatment. Knockdown of GPNMB was mediated by lentivirus carrying shRNA targeting GPNMB in vivo and in vitro. Functional experiments, including cell counting kit-8 (CCK-8), scratch, and tube formation assays, showed the anti-proliferative, anti-migrative, and anti-angiogenic roles of GPNMB knockdown in HRMECs using the lentivirus system following HG challenge. Additionally, increased GPNMB levels were detected in the retina of DR rats induced by a single intraperitoneal injection of streptozotocin (60 mg/kg) using real-time PCR, western blot, and immunofluorescence assays. Downregulation of GPNMB inhibited the angiogenesis and vascular endothelial growth factor production in the retina of rats with DR. Furthermore, overexpression of Integrin β1 led to increased angiogenesis in DR. Integrin β1 was indicated as a target protein of GPNMB. Upregulated-Integrin β1 restored GPNMB knockdown-induced inhibition of cell viability, migration, and tube formation in HRMECs. In conclusion, we provide evidence for the angiogenic role of GPNMB and demonstrate that silencing GPNMB may represent a therapeutic potential in the treatment of DR.

Crosstalk between the liver and kidney in diabetic nephropathy

Diabetic nephropathy (DN) is a serious complication of diabetes, and its pathogenesis has not been fully elucidated. Recently, communication between organs has gradually become a new focus in the study of diseases pathogenesis, and abnormal interorgan communication has been proven to be involved in the occurrence and progression of many diseases. As an important metabolic organ in the human body, the liver plays an important role in maintaining homeostasis in humans. The liver secretes a series of proteins called hepatokines that affect adjacent and distal organs through paracrine or endocrine signaling pathways. In this review, we summarize some of the hepatokines identified to date and describe their roles in DN to discuss the possibility that the liver-renal axis is potentially useful as a therapeutic target for DN. We summarize the important hepatokines identified thus far and discuss their relationship with DN. We propose for the first time that the "liver-renal axis" is a potential therapeutic target in individuals with DN.

LYPD3, a New Biomarker and Therapeutic Target for Acute Myelogenous Leukemia

Background: Acute myelogenous leukemia (AML) is nosocomial with the highest pediatric mortality rates and a relatively poor prognosis. C4.4A(LYPD3) is a tumorigenic and high-glycosylated cell surface protein that has been proven to be linked with the carcinogenic effects in solid tumors, but no hematologic tumors have been reported. We focus on exploring the molecular mechanism of LYPD3 in the regulation of the occurrence and development of AML to provide a research basis for the screening of markers related to the treatment and prognosis.

Methods: Datasets on RNA Sequencing (RNA-seq) and mRNA expression profiles of 510 samples were obtained from The Cancer Genome Atlas Program/The Genotype-Tissue Expression (Tcga-gtex) on 10 March 2021, which included the information on 173 AML tumorous tissue samples and 337 normal blood samples. The differential expression, identification of prognostic genes based on the COX regression model, and LASSO regression were analyzed. In order to better verify, experiments including gene knockdown mediated by small interfering RNA (siRNA), cell proliferation assays, and Western blot were prefomed. We studied the possible associated pathways through which LYPD3 may have an impact on the pathogenesis and prognosis of AML by gene set enrichment analysis (GSEA).

Results: A total of 11,490 differential expression genes (DEGs) were identified. Among them, 4,164 genes were upregulated, and 7,756 genes were downregulated. The univariate Cox regression analysis and LASSO regression analysis found that 28 genes including LYPD3, DNAJC8, and other genes were associated with overall survival (OS). After multivariate Cox analysis, a total of 10 genes were considered significantly correlated with OS in AML including LYPD3, which had a poor impact on AML (p <0.05). The experiment results also supported the above conclusion. We identified 25 pathways, including the E2F signaling pathway, p53 signaling pathway, and PI3K_AKT signaling pathway, that were significantly upregulated in AML samples with high LYPD3 expression (p < 0.05) by GSEA. Further, the results of the experiment suggested that LYPD3 participates in the development of AML through the p53 signaling pathway or/and PI3K/AKT signaling pathway.

Conclusion: This study first proved that the expression of LYPD3 was elevated in AML, which was correlated with poor clinical characteristics and prognosis. In addition, LYPD3 participates in the development of AML through p53 or/and the PI3K/AKT signaling pathway.