Metabolomic Profile Predicts Development of Microalbuminuria in Individuals with Type 1 Diabetes.

Elevated urinary albumin excretion (microalbuminuria) is an early marker of diabetic nephropathy, but there is an unmet need for better biomarkers that capture the individuals at risk with higher accuracy and earlier than the current markers do. We performed an untargeted metabolomic study to assess baseline differences between individuals with type 1 diabetes who either developed microalbuminuria or remained normoalbuminuric. A total of 102 individuals progressed to microalbuminuria during a median follow-up of 3.2 years, whereas 98 sex-, age- and body mass index (BMI) matched non-progressors remained normoalbuminuric during a median follow-up of 7.1 years. Metabolomic screening identified 1,242 metabolites, out of which 111 differed significantly between progressors and non-progressors after adjustment for age of diabetes onset, baseline glycosylated hemoglobin A1c (HbA1c), and albumin excretion rate (AER). The metabolites that predicted development of microalbumiuria included several uremic toxins and carnitine metabolism related molecules. Iterative variable selection indicated erythritol, 3-phenylpropionate, and N-trimethyl-5-aminovalerate as the best set of variables to predict development of microalbuminuria. A metabolomic index based on these metabolites improved the prediction of incident microalbuminuria on top of the clinical variables age of diabetes onset, baseline HbA1c and AER (ROCAUC = 0.842 vs 0.797), highlighting their ability to predict early-phase diabetic nephropathy.

Co-crystal structure guided array synthesis of PPARgamma inverse agonists.

PPARgamma-activating thiazolidinediones and carboxylic acids such as farglitazar exert their anti-diabetic effects in part in PPARgamma rich adipose. Both pro- and anti-adipogenic PPARgamma ligands promote glucose and lipid lowering in animal models of diabetes. Herein, we disclose representatives of an array of 160 farglitazar analogues with atypical inverse agonism of PPARgamma in mature adipocytes.

An optimized whole blood method for flow cytometric measurement of ZAP-70 protein expression in chronic lymphocytic leukemia.

BACKGROUND: ZAP-70 protein expression has been proposed as a marker for immunoglobulin heavy chain mutational status, which some studies have correlated with disease course in B-cell chronic lymphocytic leukemia (CLL). Studies published to date measuring levels of expression of ZAP-70 intracellular protein using flow cytometry have demonstrated poor performance, as defined by the difference in signal in known positive and negative lymphocyte populations. METHODS: A recently published method (Chow S, Hedley DW, Grom P, Magari R, Jacobberger JW, Shankey TV, Cytometry A 2005;67:4-17) to measure intracellular phospho-epitopes was optimized using a design of experiments (DOE) approach to provide the best separation of ZAP-70 expression in positive T- or NK-cells as compared to negative B-cells in peripheral blood samples. A number of commercially available anti-ZAP-70 antibody-conjugates were screened using this methodology, and the antibody-conjugate showing the best performance was chosen to develop a four-color, five antibody assays to measure ZAP-70 levels in whole blood specimens. RESULTS: Using the optimized fixation and permeabilization method, improvement in assay performance (signal-to-noise, S/N) was seen in most of the antibodies tested. The custom SBZAP conjugate gave the best S/N when used in conjunction with this optimized fixation /permeabilization method. In conjunction with carefully standardized instrument set-up protocols, we obtained both intra- and interlaboratory reproducibility in the analysis of ZAP-70 expression in whole blood samples from normal and CLL patients. CONCLUSIONS: The development of a sensitive, specific and highly reproducible ZAP-70 assay represents only the first essential step for any clinical assay. The universal implementation of a validated data analysis method and the establishment of methodology-based cutoff points for clinical outcomes must next be established before ZAP-70 protein analysis can be routinely implemented in the clinical laboratory.