Characterization of renal biomarkers for use in clinical trials: effect of preanalytical processing and qualification using samples from subjects with diabetes.

BACKGROUND: Identifying the potential for drug-induced kidney injury is essential for the successful research and development of new drugs. Newer and more sensitive preclinical drug-induced kidney injury biomarkers are now qualified for use in rat toxicology studies, but biomarkers for clinical studies are still undergoing qualification. The current studies investigated biomarkers in healthy volunteer (HV) urine samples with and without the addition of stabilizer as well as in urine from patients with normoalbuminuric diabetes mellitus (P-DM). METHODS: Urine samples from 20 male HV with stabilizer, 69 male HV without stabilizer, and 95 male DM without stabilizer (39 type 1 and 56 type 2) were analyzed for the following bio-markers using multiplex assays: α-1-microglobulin (A1M), ß-2-microglobulin, calbindin, clusterin, connective tissue growth factor (CTGF), creatinine, cystatin-C, glutathione S-transferase α (GSTα), kidney injury marker-1 (KIM-1), microalbumin, neutrophil gelatinase-associated lipocalin, osteopontin, Tamm-Horsfall urinary glycoprotein (THP), tissue inhibitor of metalloproteinase 1, trefoil factor 3 (TFF3), and vascular endothelial growth factor. RESULTS: CTGF and GSTα assays on nonstabilized urine were deemed nonoptimal (>50% of values below assay lower limits of quantification). "Expected values" were determined for HV with stabilizer, HV without stabilizer, and P-DM without stabilizer. There was a statistically significant difference between HV with stabilizer compared to HV without stabilizer for A1M, CTGF, GSTα, and THP. DM urine samples differed from HV (without stabilizer) for A1M CTGF, GSTα, KIM-1, microalbumin, osteopontin, and TFF3. A1M also correctly identified HV and DM with an accuracy of 89.0%. SUMMARY: These studies: 1) determined that nonstabilized urine can be used for assays under qualification; and 2) documented that A1M, CTGF, GSTα, KIM-1, microalbumin, osteopontin, and TFF3 were significantly increased in urine from P-DM. In addition, the 89.0% accuracy of A1M in distinguishing P-DM from HV may allow this biomarker to be used to monitor efficacy of potential renal protective agents.

Characterization of renal biomarkers for use in clinical trials: biomarker evaluation in healthy volunteers.

BACKGROUND: Several preclinical urinary biomarkers have been qualified and accepted by the health authorities (US Food and Drug Administration, European Medicines Agency, and Pharmaceuticals and Medical Devices Agency) for detecting drug-induced kidney injury during preclinical toxicologic testing. Validated human assays for many of these biomarkers have become commercially available, and this study was designed to characterize some of the novel clinical renal biomarkers. The objective of this study was to evaluate clinical renal biomarkers in a typical Phase I healthy volunteer population to determine confidence intervals (pilot reference intervals), intersubject and intrasubject variability, effects of food intake, effect of sex, and vendor assay comparisons. METHODS: Spot urine samples from 20 male and 19 female healthy volunteers collected on multiple days were analyzed using single analyte and multiplex assays. The following analytes were measured: α-1-microglobulin, ß-2-microglobulin, calbindin, clusterin, connective tissue growth factor, creatinine, cystatin C, glutathione S-transferase-α, kidney injury marker-1, microalbumin, N-acetyl-ß-(D) glucosaminidase, neutrophil gelatinase-associated lipocalin, osteopontin, Tamm-Horsfall urinary glycoprotein, tissue inhibitor of metalloproteinase 1, trefoil factor 3, and vascular endothelial growth factor. RESULTS: Confidence intervals were determined from the single analyte and multiplex assays. Intersubject and intrasubject variability ranged from 38% to 299% and from 29% to 82% for biomarker concentration, and from 24% to 331% and from 10% to 67% for biomarker concentration normalized to creatinine, respectively. There was no major effect of food intake or sex. Single analyte and multiplex assays correlated with r (2)≥0.700 for five of six biomarkers when evaluating biomarker concentration, but for only two biomarkers when evaluating concentration normalized to creatinine. CONCLUSION: Confidence intervals as well as intersubject and intrasubject variability were determined for novel clinical renal biomarkers/assays, which should be considered for evaluation in the next steps of the qualification process.

Pretreatment data is highly predictive of liver chemistry signals in clinical trials.

PURPOSE: The goal of this retrospective analysis was to assess how well predictive models could determine which patients would develop liver chemistry signals during clinical trials based on their pretreatment (baseline) information. PATIENTS AND METHODS: Based on data from 24 late-stage clinical trials, classification models were developed to predict liver chemistry outcomes using baseline information, which included demographics, medical history, concomitant medications, and baseline laboratory results. RESULTS: Predictive models using baseline data predicted which patients would develop liver signals during the trials with average validation accuracy around 80%. Baseline levels of individual liver chemistry tests were most important for predicting their own elevations during the trials. High bilirubin levels at baseline were not uncommon and were associated with a high risk of developing biochemical Hy's law cases. Baseline γ-glutamyltransferase (GGT) level appeared to have some predictive value, but did not increase predictability beyond using established liver chemistry tests. CONCLUSION: It is possible to predict which patients are at a higher risk of developing liver chemistry signals using pretreatment (baseline) data. Derived knowledge from such predictions may allow proactive and targeted risk management, and the type of analysis described here could help determine whether new biomarkers offer improved performance over established ones.

Synthesis and physical characterization of a P1 arginine combinatorial library, and its application to the determination of the substrate specificity of serine peptidases.

Serine peptidases are a large, well-studied, and medically important class of peptidases. Despite the attention these enzymes have received, details concerning the substrate specificity of even some of the best known enzymes in this class are lacking. One approach to rapidly characterizing substrate specificity for peptidases is the use of positional scanning combinatorial substrate libraries. We recently synthesized such a library for enzymes with a preference for arginine at P1 and demonstrated the use of this library with thrombin (Edwards et al. Bioorg. Med. Chem. Lett. 2000, 10, 2291). In the present work, we extend these studies by demonstrating good agreement between the theroretical and measured content of portions of this library and by showing that the library permits rapid characterization of the substrate specificity of additional SA clan serine peptidases including factor Xa, tryptase, and trypsin. These results were consistent both with cleavage sites in natural substrates and cleavage of commercially available synthetic substrates. We also demonstrate that pH or salt concentration have a quantitative effect on the rate of cleavage of the pooled library substrates but that correct prediction of optimal substrates for the enzymes studied appeared to be independent of these parameters. These studies provide new substrate specificity data on an important class of peptidases and are the first to provide physical characterization of a peptidase substrate library.

Purification, characterization and catalytic properties of human sterol 8-isomerase.

CHO 2, encoding human sterol 8-isomerase (hSI), was introduced into plasmids pYX213 or pET23a. The resulting native protein was overexpressed in erg 2 yeast cells and purified to apparent homogeneity. The enzyme exhibited a K (m) of 50 microM and a turnover number of 0.423 s(-1) for zymosterol, an isoelectric point of 7.70, a native molecular mass of 107000 Da and was tetrameric. The structural features of zymosterol provided optimal substrate acceptability. Biomimetic studies of acid-catalysed isomerization of zymosterol resulted in formation of cholest-8(14)-enol, whereas the enzyme-generated product was a Delta(7)-sterol, suggesting absolute stereochemical control of the reaction by hSI. Using (2)H(2)O and either zymosterol or cholesta-7,24-dienol as substrates, the reversibility of the reaction was confirmed by GC-MS of the deuterated products. The positional specific incorporation of deuterium at C-9alpha was established by a combination of (1)H- and (13)C-NMR analyses of the enzyme-generated cholesta-7,24-dienol. Kinetic analyses indicated the reaction equilibrium ( K (eq)=14; DeltaG(o')=-6.5 kJ/mol) for double-bond isomerization favoured the forward direction, Delta(8) to Delta(7). Treatment of hSI with different high-energy intermediate analogues produced the following dissociation constants ( K (i)): emopamil (2 microM)=tamoxifen (1 microM)=tridemorph (1 microM)<25-azacholesterol (21 microM)

Induction of CD1-restricted immune responses in guinea pigs by immunization with mycobacterial lipid antigens.

Group 1 CD1 molecules have been shown to present lipid and glycolipid Ags of mycobacteria to human T cells. However, a suitable animal model for the investigation of this component of antimycobacterial immunity has not yet been established. Previously, we found that guinea pigs express multiple isoforms of group 1 CD1 proteins that are homologous to human CD1b and CD1c. In this study, we show that CD1-restricted T cell responses can be generated in guinea pigs following immunization with lipid Ags from Mycobacterium tuberculosis. Splenic T cells from lipid Ag-immunized guinea pigs showed strong proliferative responses to total lipid Ags and partially purified glycolipid fractions from M. tuberculosis. These lipid Ag-reactive T cells were enriched in CD4-negative T cell fractions and showed cytotoxic activity against CD1-expressing guinea pig bone marrow-derived dendritic cells pulsed with M. tuberculosis lipid Ags. Using guinea pig cell lines transfected with individual CD1 isoforms as target cells in cytotoxic T cell assays, we found that guinea pig CD1b and CD1c molecules presented M. tuberculosis glycolipid Ags to T cells raised by mycobacterial lipid immunization. These results were confirmed using a T cell line derived from M. tuberculosis lipid Ag-immunized guinea pigs, which also showed CD1-restricted responses and cytolytic activity. Our results demonstrate that CD1-restricted responses against microbial glycolipid Ags can be generated in vivo by specific immunization and provide support for the use of the guinea pig as a relevant small animal model for the study of CD1-restricted immune responses to mycobacterial pathogens.

Fine specificity of TCR complementarity-determining region residues and lipid antigen hydrophilic moieties in the recognition of a CD1-lipid complex.

alphabeta TCR can recognize peptides presented by MHC molecules or lipids and glycolipids presented by CD1 proteins. Whereas the structural basis for peptide/MHC recognition is now clearly understood, it is not known how the TCR can interact with such disparate molecules as lipids. Recently, we demonstrated that the alphabeta TCR confers specificity for both the lipid Ag and CD1 isoform restriction, indicating that the TCR is likely to recognize a lipid/CD1 complex. We hypothesized that lipids may bind to CD1 via their hydrophobic alkyl and acyl chains, exposing the hydrophilic sugar, phosphate, and other polar functions for interaction with the TCR complementarity-determining regions (CDRs). To test this model, we mutated the residues in the CDR3 region of the DN1 TCR beta-chain that were predicted to project between the CD1b alpha helices in a model of the TCR/CD1 complex. In addition, we tested the requirement for the negatively charged and polar functions of mycolic acid for Ag recognition. Our findings indicate that the CDR loops of the TCR form the Ag recognition domain of CD1-restricted TCRs and suggest that the hydrophilic domains of a lipid Ag can form a combinatorial epitope recognized by the TCR.