The Promise of Systems Biology for Diabetic Kidney Disease

Single-cell RNA sequencing in diabetic kidney disease: a literature review

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease (ESRD), and its pathogenesis has not been clarified. Current research suggests that DKD involves multiple cell types and extra-renal factors, and it is particularly important to clarify the pathogenesis and identify new therapeutic targets. Single-cell RNA sequencing (scRNA-seq) technology is high-throughput sequencing of the transcriptomes of individual cells at the single-cell level, which is an effective technology for exploring the development of diseases by comparing genetic information, reflecting the differences in genetic information between cells, and identifying different cell subpopulations. Accumulating evidence supports the role of scRNA-seq in revealing the pathogenesis of diabetes and strengthening our understanding of the molecular mechanisms of DKD. We reviewed the scRNA-seq data this time. Then, we analyzed and discussed the applications of scRNA-seq technology in DKD research, including annotation of cell types, identification of novel cell types (or subtypes), identification of intercellular communication, analysis of cell differentiation trajectories, gene expression detection, and analysis of gene regulatory networks, and lastly, we explored the future perspectives of scRNA-seq technology in DKD research.

Should we enlarge the indication for kidney biopsy in patients with diabetes? The pro part

Diabetic nephropathy (DN) and non-diabetic renal diseases (NDRD) represent intricate challenges in diagnosis and treatment within the context of the global diabetes epidemic. As the prevalence of diabetes continues to escalate, effective management of renal complications becomes paramount. Recent advancements in comprehending the multifaceted nature of renal damage, fueled by insights from histopathological investigations, offer unprecedented prospects for refining diagnostic strategies and customizing therapeutic interventions. Renal biopsies have emerged as indispensable tools for unraveling the diverse phenotypes of renal damage in diabetes. The pioneering study by Mazzucco identified three classes of renal damage in type 2 diabetes patients: classical diabetic glomerulosclerosis (DN), vascular and ischemic glomerular changes (NDRD), and other glomerulonephritides in the presence (DN + NDRD, mixed forms) or absence of DN (NDRD). The prevalence of these classes varies widely in published studies, influenced by factors such as ethnicity, geography and selection criteria for renal biopsy. Moreover, the international Renal Pathology Society consensus classification system has stratified the classical diabetic nephropathy into progressive categories of renal impairment, a breakthrough that aids in prognostication. Histopathological scrutiny, particularly the intricate correlation between glomerular and tubulointerstitial lesions, contributes profoundly to enhancing our grasp of the phenotype's heterogeneity. This amplified comprehension holds the potential to steer personalized treatment strategies. Cutting-edge interventions, encompassing sodium-glucose cotransporter 2 inhibitors, mineralocorticoid receptor antagonists and anti-endothelin receptor agents, are broadening the arsenal against renal injury in diabetes. When combined with the profound insights garnered from histopathological, omics, imaging and clinical data, these therapeutic avenues promise a transformative shift towards precision-driven care paradigms. Collaborative efforts uniting researchers, clinicians and patients are indispensable for propelling our knowledge of diabetic renal damage and ameliorating patient outcomes. The fusion of histopathological, omics and imaging findings into clinical decision-making harbors the potential to customize interventions and optimize care for individuals grappling with diabetes-associated renal complications. Furthermore, groundbreaking initiatives like the iBeat Study within the BEAt-DKD (Biomarker Enterprise to Attack Diabetic Kidney Disease) project (https://www.beat-dkd.eu/), elucidating distinct phenotypes of renal damage within diabetes, underscore the imperative necessity of integrating histopathological data into the broader framework of diabetic renal management.

Improved Structural Characterization of Glycerophospholipids and Sphingomyelins with Real-Time Library Searching

In mass spectrometry-based lipidomics, complex lipid mixtures undergo chromatographic separation, are ionized, and are detected using tandem MS (MSn) to simultaneously quantify and structurally characterize eluting species. The reported structural granularity of these identified lipids is strongly reliant on the analytical techniques leveraged in a study. For example, lipid identifications from traditional collisionally activated data-dependent acquisition experiments are often reported at either species level or molecular species level. Structural resolution of reported lipid identifications is routinely enhanced by integrating both positive and negative mode analyses, requiring two separate runs or polarity switching during a single analysis. MS3+ can further elucidate lipid structure, but the lengthened MS duty cycle can negatively impact analysis depth. Recently, functionality has been introduced on several Orbitrap Tribrid mass spectrometry platforms to identify eluting molecular species on-the-fly. These real-time identifications can be leveraged to trigger downstream MSn to improve structural characterization with lessened impacts on analysis depth. Here, we describe a novel lipidomics real-time library search (RTLS) approach, which utilizes the lipid class of real-time identifications to trigger class-targeted MSn and to improve the structural characterization of phosphotidylcholines, phosphotidylethanolamines, phosphotidylinositols, phosphotidylglycerols, phosphotidylserine, and sphingomyelins in the positive ion mode. Our class-based RTLS method demonstrates improved selectivity compared to the current methodology of triggering MSn in the presence of characteristic ions or neutral losses.

Identification of miR-3182 and miR-3143 target genes involved in the cell cycle as a novel approach in TNBC treatment: A systems biology approach

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with a poor prognosis, lacking therapeutic targets. miRNAs play crucial roles in TNBC through regulating various mechanisms, including cellular growth and proliferation. This study aims to identify critical target genes of two novel miRNAs (miR-3143 and miR-3182) involved in the cell cycle of TNBC as possible therapeutic targets and investigates their regulatory and therapeutic roles through a systems biology approach and in vitro experiment. Datasets related to the TNBC cell line (MDA-MB-231) were screened and retrieved, and Gene regulatory networks were constructed. Significant regulatory motifs were detected and analyzed using the FANMOD and Cytoscape analyzer, and the clusters and seeds were identified using the MCODE. Functional enrichment analysis was also performed using DAVID and STRING. The most critical genes were determined using the analysis of GRN motifs and PPI clusters. The essential genes involved in the cell cycle were selected and verified using the bc-GenExMiner v4.7. We overexpressed miR-3143 and miR-3182 in the MDA-MB-231 cell line using human umbilical cord mesenchymal stem cell (HUCMSC)-miRNA loaded exosomes, and the expression of the critical target genes was investigated using RT-qPCR. We identified eight critical genes as potential therapeutic targets. Their expression decreased by overexpression of miR-3143 and miR-3182 in RT-qPCR. The identified critical genes have probably significant roles in the pathogenesis of TNBC through the cell cycle. We suggest that the overexpression of miR-3143 and miR-3182 could be a new therapeutic candidate in TNBC and is worth more investigation.

Systems biology and machine learning approaches identify drug targets in diabetic nephropathy

Diabetic nephropathy (DN), the leading cause of end-stage renal disease, has become a massive global health burden. Despite considerable efforts, the underlying mechanisms have not yet been comprehensively understood. In this study, a systematic approach was utilized to identify the microRNA signature in DN and to introduce novel drug targets (DTs) in DN. Using microarray profiling followed by qPCR confirmation, 13 and 6 differentially expressed (DE) microRNAs were identified in the kidney cortex and medulla, respectively. The microRNA-target interaction networks for each anatomical compartment were constructed and central nodes were identified. Moreover, enrichment analysis was performed to identify key signaling pathways. To develop a strategy for DT prediction, the human proteome was annotated with 65 biochemical characteristics and 23 network topology parameters. Furthermore, all proteins targeted by at least one FDA-approved drug were identified. Next, mGMDH-AFS, a high-performance machine learning algorithm capable of tolerating massive imbalanced size of the classes, was developed to classify DT and non-DT proteins. The sensitivity, specificity, accuracy, and precision of the proposed method were 90%, 86%, 88%, and 89%, respectively. Moreover, it significantly outperformed the state-of-the-art (P-value ≤ 0.05) and showed very good diagnostic accuracy and high agreement between predicted and observed class labels. The cortex and medulla networks were then analyzed with this validated machine to identify potential DTs. Among the high-rank DT candidates are Egfr, Prkce, clic5, Kit, and Agtr1a which is a current well-known target in DN. In conclusion, a combination of experimental and computational approaches was exploited to provide a holistic insight into the disorder for introducing novel therapeutic targets.

Integrative Biology of Diabetic Retinal Disease: Lessons from Diabetic Kidney Disease

Diabetic retinal disease (DRD) remains the most common cause of vision loss in adults of working age. Progress on the development of new therapies for DRD has been limited by the complexity of the human eye, which constrains the utility of traditional research techniques, including animal and tissue culture models-a problem shared by those in the field of kidney disease research. By contrast, significant progress in the study of diabetic kidney disease (DKD) has resulted from the successful employment of systems biology approaches. Systems biology is widely used to comprehensively understand complex human diseases through the unbiased integration of genetic, environmental, and phenotypic aspects of the disease with the functional and structural manifestations of the disease. The application of a systems biology approach to DRD may help to clarify the molecular basis of the disease and its progression. Acquiring this type of information might enable the development of personalized treatment approaches, with the goal of discovering new therapies targeted to an individual's specific DRD pathophysiology and phenotype. Furthermore, recent efforts have revealed shared and distinct pathways and molecular targets of DRD and DKD, highlighting the complex pathophysiology of these diseases and raising the possibility of therapeutics beneficial to both organs. The objective of this review is to survey the current understanding of DRD pathophysiology and to demonstrate the investigative approaches currently applied to DKD that could promote a more thorough understanding of the structure, function, and progression of DRD.

Connectivity Mapping Identifies BI-2536 as a Potential Drug to Treat Diabetic Kidney Disease

Diabetic kidney disease (DKD) remains the most common cause of kidney failure, and the treatment options are insufficient. Here, we used a connectivity mapping approach to first collect 15 gene expression signatures from 11 DKD-related published independent studies. Then, by querying the Library of Integrated Network-based Cellular Signatures (LINCS) L1000 data set, we identified drugs and other bioactive small molecules that are predicted to reverse these gene signatures in the diabetic kidney. Among the top consensus candidates, we selected a PLK1 inhibitor (BI-2536) for further experimental validation. We found that PLK1 expression was increased in the glomeruli of both human and mouse diabetic kidneys and localized largely in mesangial cells. We also found that BI-2536 inhibited mesangial cell proliferation and extracellular matrix in vitro and ameliorated proteinuria and kidney injury in DKD mice. Further pathway analysis of the genes predicted to be reversed by the PLK1 inhibitor was of members of the TNF-α/NF-κB, JAK/STAT, and TGF-β/Smad3 pathways. In vitro, either BI-2536 treatment or knockdown of PLK1 dampened the NF-κB and Smad3 signal transduction and transcriptional activation. Together, these results suggest that the PLK1 inhibitor BI-2536 should be further investigated as a novel therapy for DKD.

Genomics, Proteomics and Metabolomics Approaches for Predicting Diabetic Nephropathy in Type 2 Diabetes Mellitus Patients

BACKGROUND

There is a continuous rise in the prevalence of type 2 diabetes mellitus (T2DM) worldwide and most patients are unaware of the presence of this chronic disease at the early stages. T2DM is associated with complications related to long-term damage and failure of multiple organ systems caused by vascular changes associated with glycated end products, oxidative stress, mild inflammation, and neovascularization. Among the most frequent complications of T2DM observed in about 20-40% of T2DM patients is diabetes nephropathy (DN).

METHODS

A literature search was made in view of highlighting the novel applications of genomics, proteomics and metabolomics, as the new prospective strategy for predicting DN in T2DM patients.

RESULTS

The complexity of DN requires a comprehensive and unbiased approach to investigate the main causes of disease and identify the most important mechanisms underlying its development. With the help of evolving throughput technology, rapidly evolving information can now be applied to clinical practice.

DISCUSSION

DN is also the leading cause of end-stage renal disease and comorbidity independent of T2DM. In terms of the comorbidity level, DN has many phenotypes; therefore, timely diagnosis is required to prevent these complications. Currently, urine albumin-to-creatinine ratio and estimated glomerular filtration rate (eGFR) are gold standards for assessing glomerular damage and changes in renal function. However, GFR estimation based on creatinine is limited to hyperfiltration status; therefore, this makes albuminuria and eGFR indicators less reliable for early-stage diagnosis of DN.

CONCLUSION

The combination of genomics, proteomics, and metabolomics assays as suitable biological systems can provide new and deeper insights into the pathogenesis of diabetes, as well as discover prospects for developing suitable and targeted interventions.

The emerging role of dyslipidemia in diabetic microvascular complications

PURPOSE OF REVIEW

To summarize recent advancements in our understanding of the impact of dyslipidemia on microvascular complications in type 2 diabetes (T2D), with an emphasis on peripheral neuropathy and nephropathy.

RECENT FINDINGS

Mounting evidence suggests that rigorous glycemic control only mitigates certain microvascular complications in T2D patients. Particularly, well regulated blood glucose levels only marginally improve peripheral neuropathy in the T2D setting. Dyslipidemia, an abnormal lipid profile, is emerging as a key factor in peripheral neuropathy. Furthermore, although glycemic control may prevent or slow nephropathy, recent developments demonstrate that dyslipidemia can also affect kidney outcomes in normoglycemic patients. Transcriptomic, epigenomic, and lipidomic investigations, as well as integrative approaches, are shedding light on potential pathomechanisms. These molecular studies are identifying possible targets for therapeutic intervention. Complementing molecular research, lifestyle interventions are on-going to assess whether dietary choices and/or exercise, weight-loss, or surgical interventions, such as bariatric surgery, can ameliorate peripheral neuropathy and nephropathy in T2D patients.

SUMMARY

Dyslipidemia is an emerging mechanism in microvascular complications in T2D. Elucidating the molecular pathomechanisms may pinpoint potential lipid-centric treatments. Interventional studies of dietary changes, exercise, or weight-loss surgery may also positively impact these highly prevalent and morbid complications.

Unraveling the Role of Inflammation in the Pathogenesis of Diabetic Kidney Disease

Diabetic kidney disease (DKD) remains the leading cause of end-stage renal disease (ESRD) and is therefore a major burden on the healthcare system. Patients with DKD are highly susceptible to developing cardiovascular disease, which contributes to increased morbidity and mortality rates. While progress has been made to inhibit the acceleration of DKD, current standards of care reduce but do not eliminate the risk of DKD. There is growing appreciation for the role of inflammation in modulating the process of DKD. The focus of this review is on providing an overview of the current status of knowledge regarding the pathologic roles of inflammation in the development of DKD. Finally, we summarize recent therapeutic advances to prevent DKD, with a focus on the anti-inflammatory effects of newly developed agents.

Implementing personalized medicine in diabetic kidney disease: Stakeholders' perspectives

The promise of personalized medicine to deliver "the right treatments at the right time to the right person" is the next frontier in healthcare. However, to implement personalized medicine in chronic diseases such as diabetes mellitus and diabetic kidney disease (DKD), a number of different aspects need to be taken into account. Better risk stratification and more precise options for treatment need to be developed and included in clinical practice guidelines. A patient's unique psychological, social and environmental situation also drive disease progression and outcomes. Appraising the cost effectiveness of precision medicines is necessary, not just as the cost of new therapies, but also the cost of diagnosis with novel methodologies and averted complications. As the prevalence of DKD grows worldwide to epidemic proportions, challenges such as global disparities in resources, access to healthcare and prevalence need to be addressed. This review considers these issues to achieve the short and longer-term goals of implementing personalized medicine in clinical practice.

An integrative systems biology approach for precision medicine in diabetic kidney disease

Current therapeutic approaches are ineffective in many patients with established diabetic kidney disease (DKD), an epidemic affecting one in three patients with diabetes. Early identification of patients at high risk for progression and individualizing therapies have the potential to mitigate kidney complications due to diabetes. To achieve this, a better understanding of the complex pathophysiology of DKD is needed. A system biology approach integrating large-scale omic data is well suited to unravel the molecular mechanisms driving DKD and may offer new perspectives how to personalize therapy. Recent studies indeed show that integrating genome scale data sets generated from prospectively designed clinical cohort studies with model systems using innovative bioinformatics analysis revealed critical molecular pathways in DKD and led to the development of candidate prognostic molecular biomarkers. This review seeks to provide an overview of the recent progress in the application of the integrative systems biology approaches specifically in the field of molecular biomarkers for DKD. We will mainly focus the discussion on how to use integrative system biology approach to first identify patients at high risk of progression, and second to identify patients who may or may not respond to treatment. Challenges and opportunities in applying precision medicine in DKD will also be discussed.

Clinical and multi-omics cross-phenotyping of patients with autoimmune and autoinflammatory diseases: the observational TRANSIMMUNOM protocol

INTRODUCTION

Autoimmune and autoinflammatory diseases (AIDs) represent a socioeconomic burden as the second cause of chronic illness in Western countries. In this context, the TRANSIMMUNOM clinical protocol is designed to revisit the nosology of AIDs by combining basic, clinical and information sciences. Based on classical and systems biology analyses, it aims to uncover important phenotypes that cut across diagnostic groups so as to discover biomarkers and identify novel therapeutic targets.

METHODS AND ANALYSIS

TRANSIMMUNOM is an observational clinical protocol that aims to cross-phenotype a set of 19 AIDs, six related control diseases and healthy volunteers . We assembled a multidisciplinary cohort management team tasked with (1) selecting informative biological (routine and omics type) and clinical parameters to be captured, (2) standardising the sample collection and shipment circuit, (3) selecting omics technologies and benchmarking omics data providers, (4) designing and implementing a multidisease electronic case report form and an omics database and (5) implementing supervised and unsupervised data analyses.

ETHICS AND DISSEMINATION

The study was approved by the institutional review board of Pitié-Salpêtrière Hospital (ethics committee Ile-De-France 48-15) and done in accordance with the Declaration of Helsinki and good clinical practice. Written informed consent is obtained from all participants before enrolment in the study. TRANSIMMUNOM's project website provides information about the protocol (https://www.transimmunom.fr/en/) including experimental set-up and tool developments. Results will be disseminated during annual scientific committees appraising the project progresses and at national and international scientific conferences.

DISCUSSION

Systems biology approaches are increasingly implemented in human pathophysiology research. The TRANSIMMUNOM study applies such approach to the pathophysiology of AIDs. We believe that this translational systems immunology approach has the potential to provide breakthrough discoveries for better understanding and treatment of AIDs.

TRIAL REGISTRATION NUMBER

NCT02466217; Pre-results.