Biomarker discovery in serum from patients with carotid atherosclerosis.

BACKGROUND: Blood-based biomarkers of atherosclerosis have been used to identify patients at high risk for developing stroke. We hypothesized that patients with carotid artery disease would have a distinctive proteomic signature in blood as compared to a healthy control population without carotid artery disease. In order to discover protein biomarkers associated with increased atherosclerotic risk, we used two different strategies to identify biomarkers from patients with clinically defined atherosclerosis who were undergoing endarterectomy for atherosclerotic carotid artery disease. These patients were compared with healthy matched controls. METHODS: Serum was obtained from patients undergoing endarterectomy (EA; n = 38) and compared to a group of age-matched healthy controls (n = 40). Serum was fractionated using anion exchange chromatography and three different surface-enhanced laser desorption/ionization (SELDI) chip surfaces and then evaluated with mass spectrometry (MS) and two-dimensional difference gel electrophoresis (2D-DIGE). RESULTS: A random forest (RF) analysis of the SELDI-MS protein peak data distinguished these two groups with 69.2% sensitivity and 73.2% specificity. Four unique SELDI peaks (4.2, 4.4, 16.7 and 28 kDa, all p< 0.01) showed the greatest influence in the RF model. The EA patients with a history of prior clinical atherosclerotic plaque rupture manifested as either stroke or transient ischemic attack (symptomatic; n = 16) were compared to patients with carotid atherosclerosis but no clinical evidence of plaque rupture (asymptomatic; n = 22). Analysis of the SELDI spectra did not separate these two patient subgroups. A subgroup analysis using 2D-DIGE images obtained from albumin-depleted serum comparing symptomatic (n = 10) to asymptomatic EA patients (n = 10) found 4 proteins that were differentially expressed (p < 0.01) in the symptomatic patients. These proteins were identified as α(1)-antitrypsin, haptoglobin and vitamin D binding protein that were downregulated and α(2)-glycoprotein precursor that was upregulated in the symptomatic EA group. CONCLUSIONS: SELDI-MS data analysis of fractionated serum suggests that a distinct protein signature exists in patients with carotid atherosclerosis compared to age-matched healthy controls. Identification of 4 proteins in a subset of patients with symptomatic and asymptomatic carotid atherosclerosis suggests that these and other protein biomarkers may assist in identifying high-risk patients with carotid atherosclerosis.

Protein expression profiles distinguish between experimental invasive pulmonary aspergillosis and Pseudomonas pneumonia.

We hypothesized that invasive pulmonary aspergillosis (IPA) may generate a distinctive proteomic signature in plasma and bronchoalveolar lavage (BAL). Proteins in plasma and BAL from two neutropenic rabbit models of IPA and Pseudomonas pneumonia were analyzed by SELDI-TOF MS. Hierarchical clustering analysis of plasma time course spectra demonstrated two clusters of peaks that were differentially regulated between IPA and Pseudomonas pneumonia (57 and 34 peaks, respectively, p<0.001). PCA of plasma proteins demonstrated a time-dependent separation of the two infections. A random forest analysis that ranked the top 30 spectral points distinguished between late Aspergillus and Pseudomonas pneumonias with 100% sensitivity and specificity. Based on spectral data analysis, three proteins were identified using SDS-PAGE and LC/MS and quantified using reverse phase arrays. Differences in the temporal sequence of plasma haptoglobin (p<0.001), apolipoprotein A1 (p<0.001) and transthyretin (p<0.038) were observed between IPA and Pseudomonas pneumonia, as was C-reactive protein (p<0.001). In summary, proteomic analysis of plasma and BAL proteins of experimental Aspergillus and Pseudomonas pneumonias demonstrates unique protein profiles with principal components and spectral regions that are shared in early infection and diverge at later stages of infection. Haptoglobin, apolipoprotein A1, transthyretin, and C-reactive protein are differentially expressed in these infections suggesting important contributions to host defense against IPA.

A novel peak detection approach with chemical noise removal using short-time FFT for prOTOF MS data.

Peak detection is a pivotal first step in biomarker discovery from MS data and can significantly influence the results of downstream data analysis steps. We developed a novel automatic peak detection method for prOTOF MS data, which does not require a priori knowledge of protein masses. Random noise is removed by an undecimated wavelet transform and chemical noise is attenuated by an adaptive short-time discrete Fourier transform. Isotopic peaks corresponding to a single protein are combined by extracting an envelope over them. Depending on the S/N, the desired peaks in each individual spectrum are detected and those with the highest intensity among their peak clusters are recorded. The common peaks among all the spectra are identified by choosing an appropriate cut-off threshold in the complete linkage hierarchical clustering. To remove the 1 Da shifting of the peaks, the peak corresponding to the same protein is determined as the detected peak with the largest number among its neighborhood. We validated this method using a data set of serial peptide and protein calibration standards. Compared with MoverZ program, our new method detects more peaks and significantly enhances S/N of the peak after the chemical noise removal. We then successfully applied this method to a data set from prOTOF MS spectra of albumin and albumin-bound proteins from serum samples of 59 patients with carotid artery disease compared to vascular disease-free patients to detect peaks with S/N> or =2. Our method is easily implemented and is highly effective to define peaks that will be used for disease classification or to highlight potential biomarkers.

A meta-analysis of N-acetylcysteine in contrast-induced nephrotoxicity: unsupervised clustering to resolve heterogeneity.

BACKGROUND: Meta-analyses of N-acetylcysteine (NAC) for preventing contrast-induced nephrotoxicity (CIN) have led to disparate conclusions. Here we examine and attempt to resolve the heterogeneity evident among these trials. METHODS: Two reviewers independently extracted and graded the data. Limiting studies to randomized, controlled trials with adequate outcome data yielded 22 reports with 2746 patients. RESULTS: Significant heterogeneity was detected among these trials (I2 = 37%; p = 0.04). Meta-regression analysis failed to identify significant sources of heterogeneity. A modified L'Abbé plot that substituted groupwise changes in serum creatinine for nephrotoxicity rates, followed by model-based, unsupervised clustering resolved trials into two distinct, significantly different (p < 0.0001) and homogeneous populations (I2 = 0 and p > 0.5, for both). Cluster 1 studies (n = 18; 2445 patients) showed no benefit (relative risk (RR) = 0.87; 95% confidence interval (CI) 0.68-1.12, p = 0.28), while cluster 2 studies (n = 4; 301 patients) indicated that NAC was highly beneficial (RR = 0.15; 95% CI 0.07-0.33, p < 0.0001). Benefit in cluster 2 was unexpectedly associated with NAC-induced decreases in creatinine from baseline (p = 0.07). Cluster 2 studies were relatively early, small and of lower quality compared with cluster 1 studies (p = 0.01 for the three factors combined). Dialysis use across all studies (five control, eight treatment; p = 0.42) did not suggest that NAC is beneficial. CONCLUSION: This meta-analysis does not support the efficacy of NAC to prevent CIN.

Quality control of serum albumin depletion for proteomic analysis.

BACKGROUND: Prefractionation techniques such as serum albumin depletion are useful precursors to proteomic analysis, but they may introduce preanalytical bias if the depletion is not reproducible. We examined the reproducibility of albumin immunodepletion and describe a method of QC for this process. METHODS: Depletion of albumin from pooled serum, performed using IgY immunoaffinity spin columns, was assessed for 21 runs on each of 4 columns. We measured albumin concentrations, after albumin depletion, by use of an immunoturbidimetric assay on the Beckman LX 20 analyzer and assessed mass spectra of albumin-depleted samples by use of SELDI-TOF mass spectrometry. RESULTS: There was substantial run-to-run variation in efficiency of albumin depletion, with systematic decline in efficiency after multiple uses of the columns. Mean depletion efficiency was >95% for 15 of the 1st 17 runs and <90% for runs 18 to 21. We evaluated the 10 highest-intensity peaks present in all spectra from runs 1, 8, 17, and 21 and assessed the effect of albumin depletion on SELDI-TOF mass spectrometry reproducibility. Comparing the %CV of relative intensities for low and high m/z measurements revealed a significant difference of run 21 compared with runs 1, 8, and 17 (P <0.0001). Six-fold more peaks were found in albumin-depleted than unfractionated serum at both high and low m/z. CONCLUSIONS: Sporadic and systematic variation in efficiency of albumin depletion by spin columns may contribute significant preanalytical bias to proteomic approaches of biomarker discovery. This variation requires ongoing QC of the albumin depletion process by quantification of albumin concentration to assess depletion efficiency.

A canine model of septic shock: balancing animal welfare and scientific relevance.

A shock canine pneumonia model that permitted relief of discomfort with the use of objective criteria was developed and validated. After intrabronchial Staphylococcus aureus challenge, mechanical ventilation, antibiotics, fluids, vasopressors, sedatives, and analgesics were titrated based on algorithms for 96 h. Increasing S. aureus (1 to 8 x 10(9) colony-forming units/kg) produced decreasing survival rates (P = 0.04). From 4 to 96 h, changes in arterial-alveolar oxygen gradients, mean pulmonary artery pressure, IL-1, serum sodium levels, mechanical ventilation, and vasopressor support were ordered based on survival time [acute nonsurvivors (< or =24 h until death, n = 8) > or = subacute nonsurvivors (>24 to 96 h until death, n = 8) > or = survivors (> or =96 h until death, n = 22) (all P < 0.05)]. In the first 12 h, increases in lactate and renal abnormalities were greatest in acute nonsurvivors (all P < 0.05). Compared with survivors, subacute nonsurvivors had greater rises in cytokines and liver enzymes and greater falls in platelets, white cell counts, pH, and urine output from 24 to 96 h (all P < 0.05). Importantly, these changes were not attributable to dosages of sedation, which decreased in nonsurvivors [survivors vs. nonsurvivors: 5.0 +/- 1.0 vs. 3.8 +/- 0.7 ml x h(-1) x (fentanyl/midazolam/ medetomidine)(-1); P = 0.02]. In this model, the pain control regimen did not mask changes in metabolic function and lung injury or the need for more hemodynamic and pulmonary support related to increasing severity of sepsis. The integration into this model of both specific and supportive titrated therapies routinely used in septic patients may provide a more realistic setting to evaluate therapies for sepsis.