Evaluations of tear protein markers in dry eye disease: repeatability of measurement and correlation with disease.

PURPOSE: We characterized tear protein markers in dry eye disease (DED). METHODS: In this prospective study, based on the ocular surface disease index (OSDI) and corneal staining (CS), 95 DED patients (OSDI ≥13) with increasing CS were enrolled into 3 severity groups: DE1 (CS <4), DE2 (CS 4-7), and DE3 (CS >7), while 25 asymptomatic subjects with no CS were enrolled into the control group (OSDI <13 and CS = 0). Tear fluid was collected at day 0 and day 7 visits, and concentrations of 43 protein markers were measured by multiplexed immunoassay. RESULTS: We analyzed 22 control and 80 DED subjects. Among 33 markers detectable, good inter-visit repeatability was observed with 25 markers, with intraclass correlation coefficients (ICC) ranging from 0.85-0.60; ICCs were <0.60 in the other 8. Correlation with clinical measures was found with two markers, with absolute partial correlation coefficients >0.40: Interleukin-1 receptor antagonist (IL-1Ra) and IL-8. IL-1Ra and IL-8 correlated with conjunctival staining (0.43, P < 0.001 and 0.35, P < 0.01, respectively), and with Schirmer test (-0.58 and -0.42, P < 0.001). IL-1Ra and IL-8 in DE3 were 4.4- and 2.1-fold higher than in DE1 (P = 0.0001 and 0.0007), and 1.9- and 1.6-fold higher than in DE2 (P = 0.022 and 0.017). IL-1Ra in DE2 was 2.3-fold higher than in DE1 (P = 0.038). CONCLUSIONS: Tear levels of many immune mediators were highly repeatable between visits in DED. Among them, IL-1Ra and IL-8 were associated with clinical signs and disease severity defined by corneal staining.

Polyomic profiling reveals significant hepatic metabolic alterations in glucagon-receptor (GCGR) knockout mice: implications on anti-glucagon therapies for diabetes.

BACKGROUND: Glucagon is an important hormone in the regulation of glucose homeostasis, particularly in the maintenance of euglycemia and prevention of hypoglycemia. In type 2 Diabetes Mellitus (T2DM), glucagon levels are elevated in both the fasted and postprandial states, which contributes to inappropriate hyperglycemia through excessive hepatic glucose production. Efforts to discover and evaluate glucagon receptor antagonists for the treatment of T2DM have been ongoing for approximately two decades, with the challenge being to identify an agent with appropriate pharmaceutical properties and efficacy relative to potential side effects. We sought to determine the hepatic & systemic consequence of full glucagon receptor antagonism through the study of the glucagon receptor knock-out mouse (Gcgr-/-) compared to wild-type littermates. RESULTS: Liver transcriptomics was performed using Affymetric expression array profiling, and liver proteomics was performed by iTRAQ global protein analysis. To complement the transcriptomic and proteomic analyses, we also conducted metabolite profiling (~200 analytes) using mass spectrometry in plasma. Overall, there was excellent concordance (R = 0.88) for changes associated with receptor knock-out between the transcript and protein analysis. Pathway analysis tools were used to map the metabolic processes in liver altered by glucagon receptor ablation, the most notable being significant down-regulation of gluconeogenesis, amino acid catabolism, and fatty acid oxidation processes, with significant up-regulation of glycolysis, fatty acid synthesis, and cholesterol biosynthetic processes. These changes at the level of the liver were manifested through an altered plasma metabolite profile in the receptor knock-out mice, e.g. decreased glucose and glucose-derived metabolites, and increased amino acids, cholesterol, and bile acid levels. CONCLUSIONS: In sum, the results of this study suggest that the complete ablation of hepatic glucagon receptor function results in major metabolic alterations in the liver, which, while promoting improved glycemic control, may be associated with adverse lipid changes.

iTRAQ experimental design for plasma biomarker discovery.

There is considerable interest in using mass spectrometry for biomarker discovery in human blood plasma. We investigated aspects of experimental design for large studies that require analysis of multiple sample sets using iTRAQ reagents for sample multiplexing and quantitation. Immunodepleted plasma samples from healthy volunteers were compared to immunodepleted plasma from patients with osteoarthritis in eight separate iTRAQ experiments. Our analyses utilizing ProteinPilot software for peptide identification and quantitation showed that the methodology afforded excellent reproducibility from run to run for determining protein level ratios (coefficient of variation 11.7%), in spite of considerable quantitative variances observed between different peptides for a given protein. Peptides with high variances were associated with lower intensity iTRAQ reporter ions, while immunodepletion prior to sample analysis had a negligible affect on quantitative variance. We examined the influence of different reference samples, such as pooled samples or individual samples on calculating quantitative ratios. Our findings are discussed in the context of optimizing iTRAQ experimental design for robust plasma-based biomarker discovery.

Overcoming technical variation and biological variation in quantitative proteomics.

Quantitative proteomics investigates physiology at the molecular level by measuring relative differences in protein expression between samples under different experimental conditions. A major obstacle to reliably determining quantitative changes in protein expression is to overcome error imposed by technical variation and biological variation. In drug discovery and development the issue of biological variation often rises in concordance with the developmental stage of research, spanning from in vitro assays to clinical trials. In this paper we present case studies to raise awareness to the issues of technical variation and biological variation and the impact this places on applying quantitative proteomics. We defined the degree of technical variation from the process of two-dimensional electrophoresis as 20-30% coefficient of variation. On the other hand, biological variation observed experiment-to-experiment showed a broader degree of variation depending upon the sample type. This was demonstrated with case studies where variation was monitored across experiments with bacteria, established cell lines, primary cultures, and with drug treated human subjects. We discuss technical variation and biological variation as key factors to consider during experimental design, and offer insight into preparing experiments that overcome this challenge to provide statistically significant outcomes for conducting quantitative proteomic research.