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International Clinical Trials

Early Warning

Diabetes mellitus (DM) – commonly known as diabetes – is a group of metabolic diseases related to high blood glucose levels. According to the International Diabetes Federation, at least 382 million people worldwide have diabetes today – and this figure is expected to grow to 592 million by 2035.

With the rising clinical failure rate for drugs targeting diabetes and other metabolic syndromes, there is an urgent need for improved preclinical evaluation systems that closely represent human disease biology. A dramatic increase in obesity has repercussions for patient health and the healthcare system, the bar is set high to introduce safe new drugs to market, and there are fewer novel targets for researchers to focus on.

A non-human primate (NHP) model is the most predictive animal model system for human metabolic syndrome, presenting complex symptoms such as loss of blood glucose control, diabetic nephropathy, diabetic retinopathy and dyslipidemia. This is especially critical since many next generation drugs for metabolic disease target diabetic complications. Evaluating drugs in such models offers tremendous value towards understanding efficacy, the pharmacokinetic and pharmacodynamic relationship, biomarkers and possible adverse effects.

These studies not only provide deep biological insights into the pharmacological mechanisms of a drug, but also identify biomarkers important to clinical trial design (patient stratifi cation and study rationale). This enables researchers to select appropriate models using phenotypic and genotypic data to investigate efficacy in models which are more reflective of the human disease state.

Successful drug discovery programmes need preclinical models that provide strong correlation with the clinical conditions that patients present. Patient-derived xenograft models are used to replicate the environment in which a disease inhabits, mimicking the disease state across the complete disease progression.

Diabetic Nephropathy

Diabetic nephropathy (DN) – also known as Kimmelstiel-Wilson syndrome, or nodular diabetic glomerulosclerosis and intercapillary glomerulonephritis – is the most common cause of chronic kidney disease and end-stage renal disease in patients with type 2 DN (T2DN). It is most often caused by hyperglycaemia, and is characterised by a progressive angiopathy of capillaries in the kidney glomeruli.

Over time, hyperglycaemia can lead to serious complications and can be fatal if left untreated. Therefore, the scientific community continues to focus on developing ways to manage complications of diabetes, while at the same time searching for a cure.

Despite its serious nature, DN has no noticeable indicators during its early development. In fact, symptoms only develop in the later stages, as a result of the excretion of high amounts of protein in the urine or of renal failure. These symptoms may include edema around the eyes in the mornings, progressing to more general swelling as the condition progresses. Patients may also show excessive frothing of the urine, unintentional weight gain, anorexia, nausea, fatigue and headaches. In Western countries, DN is a prime signal for the initiation of dialysis. Even with treatment, many patients still progress to end-stage renal disease.

Simplifying Diagnosis

The earliest detectable change in the course of DN is a thickening in the glomerulus. At this stage, the kidney may leak more serum albumin than normal into the urine, which can be detected in a simple medical test. However, this method of diagnosis means many patients do not undergo appropriate treatment sufficiently early.

Finding new, specific and sensitive biomarkers to detect DN at an earlier time-point will expedite and simplify diagnosis. In addition, specific and sensitive biomarkers can also guide the way to new therapies that assist in preventing the progression of DN.

This article looks at preclinical data produced by investigating molecular mechanisms of this condition in NHPs. It explores how such preclinical techniques may have an impact on developing new treatments, such as using a set of patient models that more closely reflect the human patient population and the many phenotypic traits and disease complications that are associated with diabetes – enabling the most costly part of drug discovery and development, Phase 2, to be run earlier and faster, and reducing the cost, time and effort of taking candidate drugs into the clinic.

Molecular Mechanisms

To understand how to prevent DN development and reverse its pathophysiology, it is essential to gain a thorough understanding of the molecular mechanisms that cause the disease. In order to relate these results back to the human pathology of DN, these mechanisms must be investigated in a model exposed to persistent hyperglycaemia.

Preclinical data is vital for collecting important information regarding feasibility, iterative testing and drug safety data. The more comprehensive and accurate the data collected during this stage, the more beneficial it is for research. This, consequently, creates a higher chance of success when trials move forward into clinical testing.

Process-Wide Benefits

By having the ability to recognise key gene profiles and molecular mechanisms of DN during trials, researchers are able to carve out much stronger foundations for their continued research. Access to clear data can assist in deciding which compounds to progress to clinical trials, and ultimately will streamline and simplify drug manufacture, leading to cost reductions across the process.

In this particular field, where earlier diagnosis could have a significant impact on the progression and management of the condition, this and similar gene profiling techniques could streamline and enhance the development of new therapies and treatments.

Unlike conventional experimental rodent models, in which the relevance to human in vivo physiological and metabolic kinetics remains unclear, diabetes and its associated complications naturally develop in NHPs. The study outlined below employed the use of 68 monkeys with a long history of hypoglycaemia. All animal weights were stable prior to study initiation. All experimental procedures were approved by the Institutional Animal Care and Use Committee and performed in accordance with the US National Institutes of Health (NIH) Guide for the Care and Use of Laboratory Animals.

Study Methods

Of the 68 NHPs investigated in the study, eight presented with glycosuria, microalbuminuria, elevated urinary cystatin C-to-creatinine ratio and N-acetyl-beta-D-glucosaminidase. These monkeys also presented with increased mesangial matrix expansion, glomerular basement membrane thickening and glomerulosclerosis.

Renal function of each of the eight monkeys was evaluated using the clinically relevant parameters obtained from blood and urine assays. Kidney tissue biopsy was undertaken under anaesthesia in two non-diabetic primates, three diabetic without albuminuria, and six with albuminuria. In this way, it was possible to obtain a gene expression profile.

Of the 14,764 genes profiled on the Affymetrix GeneChip rhesus macaque genome arrays, 11,074 genes were assigned unique gene symbols and selected for further analysis. Background correction was performed using the robust multichip average algorithm and quantile normalisation. Threshold was set to a four-fold change of mRNA expression between two categories, while other parameters used default values.

All data shown is presented as mean ± SEM (the standard error of the mean). The results from different groups were compared using analysis of variance, with Fisher LSD pairwise post hoc comparisons. Statistical significance was set at p<0.05.

Measurements and Results(see the pdf of digital versions for all figures)

Figure 1 demonstrates the total urine excretion of DN monkeys, compared to age-matched diabetic NHPs without nephropathy (A and B). Also shown is the total urine albumin excretion (C and D). Both of these were measured repeatedly in two separate experiments to obtain an accurate result. In addition, Figure 1 indicates the total urine excretion over 24 hours, measured simultaneously with the total drinking volume (E and F). It can be seen that monkeys with DN exhibited an increased level of 24-hour urine volume, urine albumin and drinking volume, compared to the NHPs without nephropathy.

Figure 2 shows the alterations of renal function in diabetic monkeys, including urinary glucose over 24 hours (A), creatinine levels (B) and protein levels (C). Albumin/creatinine ratio in the NHPs is also demonstrated (D). Alterations of renal function due to diabetes are illustrated in Figure 3.

Finally, Figures 4 and 5 demonstrate the renal pathological alterations and gene profiles in DN NHPs, respectively. DN monkeys showed kidney damage similar to those which manifest in human DN patients, including enlarged glomeruli, vacuolar degeneration and thickened basal membrane in the glomeruli. Alongside this, the gene profiles in Figure 5 show the Database of Essential Genes (DEG) expression in diabetic NHPs with and without nephropathy.

Research Value

From these results, it can be seen that hyperglycaemia could lead to albuminuria (DN) in diabetic NHPs. Monkeys with DN showed mesangial matrix expansion, glomerular basement membrane thickening and glomerulosclerosis – all characteristics which are known to manifest in human DN patients. T2DN monkeys were also seen to have reduced lactase DEG expression, and nephropathy was seen to alter the expression of LCT, HAVCR1, MMP7 and SPP1.

Analysis using the NIH’s Database for Annotation, Visualisation and Integrated Discovery indicates that enriched pathways in DN include ‘complement and coagulation cascade’, ‘extracellular matrix-receptor interaction’ and ‘renin-angiotensin system’.

This study demonstrates the research value of naturally occurring DN in NHPs. The identification of unique gene signatures in DN monkeys may have significant relevance to clinical DN diagnosis and therapies.

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Dr Jim Yi-Xin Wang is Senior Vice President of Cardiovascular and Metabolic Disease at Crown Bioscience Inc. He has more than 20 years of experience in academic research and pharmaceutical industry R&D. Jim’s previous positions include Assistant Professor at the University of Tennessee, Senior Scientist at Roche and Berlex, Principal Scientist at Bayer Healthcare, and Director of Pharmacology at Arete Therapeutics.
Dr Jim Yi-Xin Wang
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