A Review on Affordable Combinations in Type 2 Diabetes Care: Exploring the Cost-Effective Potential of Glipizide + Metformin and Glimepiride + Metformin + Pioglitazone.

Management of type 2 diabetes mellitus (T2DM) largely relies on medication adherence of individuals with diabetes to achieve optimal glycemic control. The economic burden of diabetes could impede adherence, leading to a reduction in treatment efficacy and increased risk of complications. Furthermore, monotherapy in diabetes is losing traction due to its ineffectiveness in achieving early and sustained optimal glycemic control in a significant proportion of the population. Hence, clinicians prefer combination treatment due to their improved efficacy and safety. Considering these factors, the current review highlights the safety and efficacy of the affordable combination therapies, a dual therapy, glipizide + metformin, and a triple-drug combination of glimepiride + metformin + pioglitazone and its applicability in the management of T2DM among individuals with diabetes in India.

Thymic lymphoma detection in RORγ knockout mice using 5-hydroxymethylcytosine profiling of circulating cell-free DNA.

A high incidence of thymic lymphoma has been noted in mice deficient of retinoid-related orphan receptor γ2 (RORγ2), which is required for differentiation of naïve CD4+ T cells into TH17 cells. Using a RORγ homozygous knockout (KO) mouse model of thymic lymphoma, we characterized this tumor progression and investigated the utility of 5-hydroxymethylcytosine (5hmC) signatures as a non-invasive circulating biomarker for early prediction of malignancy. No evidence for malignancy was noted in the wild-type mice, while primary thymic lymphoma with multi-organ metastasis was observed microscopically in 97% of the homozygous RORγ KO mice. The severity of thymic lymphoma was not age-dependent in the KO mice of 2 to 4 months old. Differential enrichment of 5hmC in thymic DNA and plasma cell-free DNA (cfDNA) was compared across different stages of tumor progression. Random forest modeling of plasma cfDNA achieved good predictivity (AUC = 0.74) in distinguishing early non-metastatic thymic lymphoma compared to cancer-free controls, while perfect predictivity was achieved with advanced multi-organ metastatic disease (AUC = 1.00). Lymphoid-specific genes involved in thymocyte selection during T cell development (Themis, Tox) were differentially enriched in both plasma and thymic tissue. This could help in differentiating thymic lymphoma from other tumors commonly detected in rodent carcinogenicity studies used in pharmaceutical drug development to inform human malignancy risk. Overall, these results provide a proof-of-concept for using circulating cfDNA profiles in rodent carcinogenicity studies for early risk assessment of novel pharmaceutical targets.

Tandem mass tag-based quantitative proteomic profiling identifies candidate serum biomarkers of drug-induced liver injury in humans.

Diagnosis of drug-induced liver injury (DILI) and its distinction from other liver diseases are significant challenges in drug development and clinical practice. Here, we identify, confirm, and replicate the biomarker performance characteristics of candidate proteins in patients with DILI at onset (DO; n = 133) and follow-up (n = 120), acute non-DILI at onset (NDO; n = 63) and follow-up (n = 42), and healthy volunteers (HV; n = 104). Area under the receiver operating characteristic curve (AUC) for cytoplasmic aconitate hydratase, argininosuccinate synthase, carbamoylphosphate synthase, fumarylacetoacetase, fructose-1,6-bisphosphatase 1 (FBP1) across cohorts achieved near complete separation (range: 0.94-0.99) of DO and HV. In addition, we show that FBP1, alone or in combination with glutathione S-transferase A1 and leukocyte cell-derived chemotaxin 2, could potentially assist in clinical diagnosis by distinguishing NDO from DO (AUC range: 0.65-0.78), but further technical and clinical validation of these candidate biomarkers is needed.

Circulating neurofilament light chain as a promising biomarker of AAV-induced dorsal root ganglia toxicity in nonclinical toxicology species.

Adeno-associated virus (AAV)-induced dorsal root ganglia (DRG) toxicity has been observed in several nonclinical species, where lesions are characterized by neuronal degeneration/necrosis, nerve fiber degeneration, and mononuclear cell infiltration. As AAV vectors become an increasingly common platform for novel therapeutics, non-invasive biomarkers are needed to better characterize and manage the risk of DRG neurotoxicity in both nonclinical and clinical studies. Based on biological relevance, reagent availability, antibody cross-reactivity, DRG protein expression, and assay performance, neurofilament light chain (NF-L) emerged as a promising biomarker candidate. Dose- and time-dependent changes in NF-L were evaluated in male Wistar Han rats and cynomolgus monkeys following intravenous or intrathecal AAV injection, respectively. NF-L profiles were then compared against microscopic DRG lesions on day 29 post-dosing. In animals exhibiting DRG toxicity, plasma/serum NF-L was strongly associated with the severity of neuronal degeneration/necrosis and nerve fiber degeneration, with elevations beginning as early as day 8 in rats (≥5 × 1013 vg/kg) and day 14 in monkeys (≥3.3 × 1013 vg/dose). Consistent with the unique positioning of DRGs outside the blood-brain barrier, NF-L in cerebrospinal fluid was only weakly associated with DRG findings. In summary, circulating NF-L is a promising biomarker of AAV-induced DRG toxicity in nonclinical species.

Therapeutic silencing of SMOC2 prevents kidney function loss in mouse model of chronic kidney disease.

Chronic kidney disease (CKD) is associated with substantial morbidity and mortality. We developed a mouse model that mimics human CKD with inflammation, extracellular matrix deposition, tubulointerstitial fibrosis, increased proteinuria, and associated reduction in glomerular filtration rate over time. Using this model, we show that genetic deficiency of SMOC2 or therapeutic silencing of SMOC2 with small interfering RNAs (siRNAs) after disease onset significantly ameliorates inflammation, fibrosis, and kidney function loss. Mechanistically, we found that SMOC2 promotes fibroblast to myofibroblast differentiation by activation of diverse cellular signaling pathways including MAPKs, Smad, and Akt. Thus, targeting SMOC2 therapeutically offers an approach to prevent fibrosis progression and CKD after injury.

Safety and disease monitoring biomarkers in Duchenne muscular dystrophy: results from a Phase II trial.

Aim: Evaluate the utility of glutamate dehydrogenase (GLDH) and cardiac troponin I as safety biomarkers, and creatine kinase and muscle injury panel as muscle health biomarkers in Duchenne muscular dystrophy. Patients & methods: Data were collected during a Phase II trial of domagrozumab. Results: GLDH was a more specific biomarker for liver injury than alanine aminotransferase. Cardiac troponin I elevations were variable and not sustained, limiting its applicability as a biomarker. Muscle injury panel biomarkers were no more informative than creatine kinase as a muscle health biomarker. Conclusion: Results support the use of GLDH as a specific biomarker for liver injury in patients with Duchenne muscular dystrophy. Clinical trial registration: ClinicalTrials.gov, NCT02310763.

Cadherin-11, Sparc-related modular calcium binding protein-2, and Pigment epithelium-derived factor are promising non-invasive biomarkers of kidney fibrosis.

Kidney fibrosis constitutes the shared final pathway of nearly all chronic nephropathies, but biomarkers for the non-invasive assessment of kidney fibrosis are currently not available. To address this, we characterize five candidate biomarkers of kidney fibrosis: Cadherin-11 (CDH11), Sparc-related modular calcium binding protein-2 (SMOC2), Pigment epithelium-derived factor (PEDF), Matrix-Gla protein, and Thrombospondin-2. Gene expression profiles in single-cell and single-nucleus RNA-sequencing (sc/snRNA-seq) datasets from rodent models of fibrosis and human chronic kidney disease (CKD) were explored, and Luminex-based assays for each biomarker were developed. Plasma and urine biomarker levels were measured using independent prospective cohorts of CKD: the Boston Kidney Biopsy Cohort, a cohort of individuals with biopsy-confirmed semiquantitative assessment of kidney fibrosis, and the Seattle Kidney Study, a cohort of patients with common forms of CKD. Ordinal logistic regression and Cox proportional hazards regression models were used to test associations of biomarkers with interstitial fibrosis and tubular atrophy and progression to end-stage kidney disease and death, respectively. Sc/snRNA-seq data confirmed cell-specific expression of biomarker genes in fibroblasts. After multivariable adjustment, higher levels of plasma CDH11, SMOC2, and PEDF and urinary CDH11 and PEDF were significantly associated with increasing severity of interstitial fibrosis and tubular atrophy in the Boston Kidney Biopsy Cohort. In both cohorts, higher levels of plasma and urinary SMOC2 and urinary CDH11 were independently associated with progression to end-stage kidney disease. Higher levels of urinary PEDF associated with end-stage kidney disease in the Seattle Kidney Study, with a similar signal in the Boston Kidney Biopsy Cohort, although the latter narrowly missed statistical significance. Thus, we identified CDH11, SMOC2, and PEDF as promising non-invasive biomarkers of kidney fibrosis.

Evaluating the Sensitivity and Specificity of Promising Circulating Biomarkers to Diagnose Liver Injury in Humans.

Early diagnosis of drug-induced liver injury (DILI) continues to be a major hurdle during drug development and postmarketing. The objective of this study was to evaluate the diagnostic performance of promising biomarkers of liver injury-glutamate dehydrogenase (GLDH), cytokeratin-18 (K18), caspase-cleaved K18 (ccK18), osteopontin (OPN), macrophage colony-stimulating factor (MCSF), MCSF receptor (MCSFR), and microRNA-122 (miR-122) in comparison to the traditional biomarker alanine aminotransferase (ALT). Biomarkers were evaluated individually and as a multivariate model in a cohort of acetaminophen overdose (n = 175) subjects and were further tested in cohorts of healthy adults (n = 135), patients with liver damage from various causes (n = 104), and patients with damage to the muscle (n = 74), kidney (n = 40), gastrointestinal tract (n = 37), and pancreas (n = 34). In the acetaminophen cohort, a multivariate model with GLDH, K18, and miR-122 was able to detect DILI more accurately than individual biomarkers alone. Furthermore, the three-biomarker model could accurately predict patients with liver injury compared with healthy volunteers or patients with damage to muscle, pancreas, gastrointestinal tract, and kidney. Expression of K18, GLDH, and miR-122 was evaluated using a database of transcriptomic profiles across multiple tissues/organs in humans and rats. K18 mRNA (Krt18) and MiR-122 were highly expressed in liver whereas GLDH mRNA (Glud1) was widely expressed. We performed a comprehensive, comparative performance assessment of 7 promising biomarkers and demonstrated that a 3-biomarker multivariate model can accurately detect liver injury.

A Biomarker-Centric Approach to Drug Discovery and Development: Lessons Learned from the Coronavirus Disease 2019 Pandemic.

Faced with the health and economic consequences of the global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the biomedical community came together to identify, diagnose, prevent, and treat the novel disease at breathtaking speeds. The field advanced from a publicly available viral genome to a commercialized globally scalable diagnostic biomarker test in less than 2 months, and first-in-human dosing with vaccines and repurposed antivirals followed shortly thereafter. This unprecedented efficiency was driven by three key factors: 1) international multistakeholder collaborations, 2) widespread data sharing, and 3) flexible regulatory standards tailored to meet the urgency of the situation. Learning from the remarkable success achieved during this public health crisis, we are proposing a biomarker-centric approach throughout the drug development pipeline. Although all therapeutic areas would benefit from end-to-end biomarker science, efforts should be prioritized to areas with the greatest unmet medical needs, including neurodegenerative diseases, chronic lower respiratory diseases, metabolic disorders, and malignant neoplasms. SIGNIFICANCE STATEMENT: Faced with the unprecedented threat of the severe acute respiratory syndrome coronavirus 2 pandemic, the biomedical community collaborated to develop a globally scalable diagnostic biomarker (viral DNA) that catalyzed therapeutic development at breathtaking speeds. Learning from this remarkable efficiency, we propose a multistakeholder biomarker-centric approach to drug development across therapeutic areas with unmet medical needs.

Tissue-Engineered Human Myobundle System as a Platform for Evaluation of Skeletal Muscle Injury Biomarkers.

Traditional serum biomarkers used to assess skeletal muscle damage, such as activity of creatine kinase (CK), lack tissue specificity and sensitivity, hindering early detection of drug-induced myopathies. Recently, a novel four-factor skeletal muscle injury panel (MIP) of biomarkers consisting of skeletal troponin I (sTnI), CK mass (CKm), fatty-acid-binding protein 3 (Fabp3), and myosin light chain 3, has been shown to have increased tissue specificity and sensitivity in rodent models of skeletal muscle injury. Here, we evaluated if a previously established model of tissue-engineered functional human skeletal muscle (myobundle) can allow detection of the MIP biomarkers after injury or drug-induced myotoxicity in vitro. We found that concentrations of three MIP biomarkers (sTnI, CKm, and Fabp3) in myobundle culture media significantly increased in response to injury by a known snake venom (notexin). Cerivastatin, a known myotoxic statin, but not pravastatin, induced significant loss of myobundle contractile function, myotube atrophy, and increased release of both traditional and novel biomarkers. In contrast, dexamethasone induced significant loss of myobundle contractile function and myotube atrophy, but decreased the release of both traditional and novel biomarkers. Dexamethasone also increased levels of matrix metalloproteinase-2 and -3 in the culture media which correlated with increased remodeling of myobundle extracellular matrix. In conclusion, this proof-of-concept study demonstrates that tissue-engineered human myobundles can provide an in vitro platform to probe patient-specific drug-induced myotoxicity and performance assessment of novel injury biomarkers to guide preclinical and clinical drug development studies.

Multi omics analysis of fibrotic kidneys in two mouse models.

Kidney fibrosis represents an urgent unmet clinical need due to the lack of effective therapies and an inadequate understanding of the molecular pathogenesis. We have generated a comprehensive and combined multi-omics dataset (proteomics, mRNA and small RNA transcriptomics) of fibrotic kidneys that is searchable through a user-friendly web application: http://hbcreports.med.harvard.edu/fmm/ . Two commonly used mouse models were utilized: a reversible chemical-induced injury model (folic acid (FA) induced nephropathy) and an irreversible surgically-induced fibrosis model (unilateral ureteral obstruction (UUO)). mRNA and small RNA sequencing, as well as 10-plex tandem mass tag (TMT) proteomics were performed with kidney samples from different time points over the course of fibrosis development. The bioinformatics workflow used to process, technically validate, and combine the single omics data will be described. In summary, we present temporal multi-omics data from fibrotic mouse kidneys that are accessible through an interrogation tool (Mouse Kidney Fibromics browser) to provide a searchable transcriptome and proteome for kidney fibrosis researchers.

Kidney Cortical Transporter Expression across Species Using Quantitative Proteomics.

Limited understanding of species differences in kidney transporters is a critical knowledge gap for prediction of drug-induced acute kidney injury, drug interaction, and pharmacokinetics in humans. Here, we report protein abundance data of 19 transporters in the kidney cortex across five species (human, monkey, dog, rat, and mouse). In general, the abundance of all of the 19 membrane transporters was higher in preclinical species compared with human except for multidrug resistance protein 1 (MDR1), organic cation transporter (OCT) 3, and OCTN1. In nonhuman primate, the total abundance of 12 transporters for which absolute data were available was 2.1-fold higher (P = 0.025) relative to human but the percentage of distribution of these transporters was identical in both species. Multidrug resistance-associated protein (MRP) 4, OCTN2, organic anion transporter (OAT) 2, sodium/potassium-transporting ATPase, MRP3, SGLT2, OAT1, MRP1, MDR1, and OCT2 were expressed differently with cross-species variabilities of 8.2-, 7.4-, 6.1-, 5.9-, 5.4-, 5.2-, 4.1-, 3.3-, and 2.8-fold, respectively. Sex differences were only significant in rodents and dog. High protein-protein correlation was observed in OAT1 versus MRP2/MRP4 as well as OCT2 versus MATE1 in human and monkey. The cross-species and sex-dependent protein abundance data are important for animal to human scaling of drug clearance as well as for mechanistic understanding of kidney physiology and derisking of kidney toxicity for new therapeutic candidates in drug development.

A Systems Toxicology Approach for the Prediction of Kidney Toxicity and Its Mechanisms In Vitro.

The failure to predict kidney toxicity of new chemical entities early in the development process before they reach humans remains a critical issue. Here, we used primary human kidney cells and applied a systems biology approach that combines multidimensional datasets and machine learning to identify biomarkers that not only predict nephrotoxic compounds but also provide hints toward their mechanism of toxicity. Gene expression and high-content imaging-derived phenotypical data from 46 diverse kidney toxicants were analyzed using Random Forest machine learning. Imaging features capturing changes in cell morphology and nucleus texture along with mRNA levels of HMOX1 and SQSTM1 were identified as the most powerful predictors of toxicity. These biomarkers were validated by their ability to accurately predict kidney toxicity of four out of six candidate therapeutics that exhibited toxicity only in late stage preclinical/clinical studies. Network analysis of similarities in toxic phenotypes was performed based on live-cell high-content image analysis at seven time points. Using compounds with known mechanism as reference, we could infer potential mechanisms of toxicity of candidate therapeutics. In summary, we report an approach to generate a multidimensional biomarker panel for mechanistic de-risking and prediction of kidney toxicity in in vitro for new therapeutic candidates and chemical entities.

Human kidney on a chip assessment of polymyxin antibiotic nephrotoxicity.

Drug-induced kidney injury, largely caused by proximal tubular intoxicants, limits development and clinical use of new and approved drugs. Assessing preclinical nephrotoxicity relies on animal models that are frequently insensitive; thus, potentially novel techniques - including human microphysiological systems, or "organs on chips" - are proposed to accelerate drug development and predict safety. Polymyxins are potent antibiotics against multidrug-resistant microorganisms; however, clinical use remains restricted because of high risk of nephrotoxicity and limited understanding of toxicological mechanisms. To mitigate risks, structural analogs of polymyxins (NAB739 and NAB741) are currently in clinical development. Using a microphysiological system to model human kidney proximal tubule, we exposed cells to polymyxin B (PMB) and observed significant increases of injury signals, including kidney injury molecule-1 KIM-1and a panel of injury-associated miRNAs (each P < 0.001). Surprisingly, transcriptional profiling identified cholesterol biosynthesis as the primary cellular pathway induced by PMB (P = 1.22 ×10-16), and effluent cholesterol concentrations were significantly increased after exposure (P < 0.01). Additionally, we observed no upregulation of the nuclear factor (erythroid derived-2)-like 2 pathway, despite this being a common pathway upregulated in response to proximal tubule toxicants. In contrast with PMB exposure, minimal changes in gene expression, injury biomarkers, and cholesterol concentrations were observed in response to NAB739 and NAB741. Our findings demonstrate the preclinical safety of NAB739 and NAB741 and reveal cholesterol biosynthesis as a potentially novel pathway for PMB-induced injury. To our knowledge, this is the first demonstration of a human-on-chip platform used for simultaneous safety testing of new chemical entities and defining unique toxicological pathway responses of an FDA-approved molecule.

A High-Throughput Screen Identifies DYRK1A Inhibitor ID-8 that Stimulates Human Kidney Tubular Epithelial Cell Proliferation.

BACKGROUND: The death of epithelial cells in the proximal tubules is thought to be the primary cause of AKI, but epithelial cells that survive kidney injury have a remarkable ability to proliferate. Because proximal tubular epithelial cells play a predominant role in kidney regeneration after damage, a potential approach to treat AKI is to discover regenerative therapeutics capable of stimulating proliferation of these cells. METHODS: We conducted a high-throughput phenotypic screen using 1902 biologically active compounds to identify new molecules that promote proliferation of primary human proximal tubular epithelial cells in vitro. RESULTS: The primary screen identified 129 compounds that stimulated tubular epithelial cell proliferation. A secondary screen against these compounds over a range of four doses confirmed that eight resulted in a significant increase in cell number and incorporation of the modified thymidine analog EdU (indicating actively proliferating cells), compared with control conditions. These eight compounds also stimulated tubular cell proliferation in vitro after damage induced by hypoxia, cadmium chloride, cyclosporin A, or polymyxin B. ID-8, an inhibitor of dual-specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A), was the top candidate identified as having a robust proproliferative effect in two-dimensional culture models as well as a microphysiologic, three-dimensional cell culture system. Target engagement and genetic knockdown studies and RNA sequencing confirmed binding of ID-8 to DYRK1A and upregulation of cyclins and other cell cycle regulators, leading to epithelial cell proliferation. CONCLUSIONS: We have identified a potential first-in-class compound that stimulates human kidney tubular epithelial cell proliferation after acute damage in vitro.

New Frontiers: Approaches to Understand the Mechanistic Basis of Renal Toxicity.

A scientific session entitled "New Frontiers: Approaches to Understand the Mechanistic Basis of Renal Toxicity" focused on novel biomarkers to monitor kidney injury both preclinically and clinically, as well as providing mechanistic insight of the induced injury. Further, the role and impact of kidney membrane transporters in drug-induced kidney toxicity provided additional considerations when understanding kidney injury and the complex role of drug transporters in either sensitivity or resistance to drug-induced injury. The onset of nephropathy in diabetic patients was also presented, focusing on the quest to discover novel biomarkers that would differentiate diabetic populations more susceptible to nephropathy and renal failure. The session highlighted exciting new research areas and novel biomarkers that will enhance our understanding of kidney injury and provide tools for ensuring patient safety clinically.

Industry Perspective on Biomarker Development and Qualification.

Pharmaceutical and biotechnology companies routinely use biomarkers to obtain quantitative metrics for drug exposure, efficacy, and safety and to inform clinical trial design with regard to patient selection, treatments, and outcomes. Biomarker science has the unique capability to catalyze precompetitive collaborations between academia, industry, regulatory agencies, and other stakeholders with the ultimate goal of accelerating the delivery of safe and effective medicines to patients, particularly in areas of high unmet need.