Diagnostic efficiency of hemoglobin A1c for newly diagnosed diabetes and prediabetes in community-based Chinese adults aged 40 years or older.

BACKGROUND: Europeans and Americans are gradually accepting the hemoglobin A1c (HbA1c) threshold of 6.5% for diagnosing diabetes proposed by the American Diabetes Association, but the cutoff of HbA1c for the Chinese population is unclear. We evaluated the diagnostic efficiency of HbA1c for diagnosing newly diagnosed diabetes and prediabetes in community-based Chinese adults 40 years of age or older. SUBJECTS AND METHODS: In this study 8,239 subjects (5,496 women) 40-90 years of age underwent HbA1c and oral glucose tolerance test measurement after an overnight fast. Diabetes and prediabetes were defined by the World Health Organization criteria. The area under the receiver operating characteristic curve (AUC) was used to evaluate the diagnostic efficiency of HbA1c, and the optimal cutoff was defined as the point on the receiver operating characteristic curve with the largest Youden index. Spearman correlation was used for correlation analysis. RESULTS: The prevalence of newly diagnosed diabetes and prediabetes was 10.7% (880/8,239) and 19.0% (1,564/8,239), respectively. Fasting plasma glucose and postprandial plasma glucose were positively correlated with HbA1c level (r=0.725 and r=0.673, both P<0.001, respectively). For diagnosing diabetes, the AUC was 0.857 (95% confidence interval, 0.841-0.873), and the optimal cutoff for HbA1c was 6.3%, with the largest Youden index being 0.581. For diagnosing prediabetes, the AUC was 0.681 (95% confidence interval, 0.666-0.697), and the optimal cutoff for HbA1c was 5.9%, with the largest Youden index being 0.280. CONCLUSIONS: An HbA1c threshold of 6.3% was highly valuable for diagnosing newly diagnosed diabetes, and a value of 5.9% was weakly valuable for diagnosing prediabetes in community-based Chinese adults 40 years of age or older.

Optimal waist circumference cut-off values for identifying metabolic risk factors in middle-aged and elderly subjects in Shandong Province of China.

OBJECTIVE: To study the optimal waist circumference (WC) cut-off values for identifying metabolic risk factors in middle-aged and elderly subjects in Shandong Province of China. METHODS: A total of 2,873 men and 5,559 women were included in this cross-sectional study. Metabolic syndrome (MetS) was diagnosed according to the definition of Chinese Diabetes Society in 2004. The relation between WC and MetS was analyzed by multivariate logistic regression analysis. The optimal WC cut-off values were identified using the area under the ROC curve and the different diagnostic criteria for central obesity were compared. RESULTS: The WC was the risk factor for MetS independent of BMI, blood glucose, blood lipid, and blood pressure. The optimal WC cut-off value was 83.8 cm and 91.1 cm for identifying MetS in women and men, respectively. Compared with 80 cm and 85 cm for women and men, 85 cm and 90 cm had a higher Youden index for identifying all metabolic risk factors and MetS in women and men. CONCLUSION: The appropriate WC cut-off value is 85 cm and 90 cm for identifying central obesity and MetS in women and men in Shandong Province of China.

QuaMeter: multivendor performance metrics for LC-MS/MS proteomics instrumentation.

LC-MS/MS-based proteomics studies rely on stable analytical system performance that can be evaluated by objective criteria. The National Institute of Standards and Technology (NIST) introduced the MSQC software to compute diverse metrics from experimental LC-MS/MS data, enabling quality analysis and quality control (QA/QC) of proteomics instrumentation. In practice, however, several attributes of the MSQC software prevent its use for routine instrument monitoring. Here, we present QuaMeter, an open-source tool that improves MSQC in several aspects. QuaMeter can directly read raw data from instruments manufactured by different vendors. The software can work with a wide variety of peptide identification software for improved reliability and flexibility. Finally, QC metrics implemented in QuaMeter are rigorously defined and tested. The source code and binary versions of QuaMeter are available under Apache 2.0 License at http://fenchurch.mc.vanderbilt.edu.

Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines.

Spectral counting has become a widely used approach for measuring and comparing protein abundance in label-free shotgun proteomics. However, when analyzing complex samples, the ambiguity of matching between peptides and proteins greatly affects the assessment of peptide and protein inventories, differentiation, and quantification. Meanwhile, the configuration of database searching algorithms that assign peptides to MS/MS spectra may produce different results in comparative proteomic analysis. Here, we present three strategies to improve comparative proteomics through spectral counting. We show that comparing spectral counts for peptide groups rather than for protein groups forestalls problems introduced by shared peptides. We demonstrate the advantage and flexibility of this new method in two datasets. We present four models to combine four popular search engines that lead to significant gains in spectral counting differentiation. Among these models, we demonstrate a powerful vote counting model that scales well for multiple search engines. We also show that semi-tryptic searching outperforms tryptic searching for comparative proteomics. Overall, these techniques considerably improve protein differentiation on the basis of spectral count tables.

Identifying proteomic LC-MS/MS data sets with Bumbershoot and IDPicker.

The identification of peptides and proteins by LC-MS/MS requires the use of bioinformatics. Tools developed in the Tabb Laboratory contribute significant flexibility and discrimination to this process. The Bumbershoot tools (MyriMatch, DirecTag, TagRecon, and Pepitome) enable the identification of peptides represented by MS/MS scans. All of these tools can work directly from instrument capture files of multiple vendors, such as Thermo RAW format, or from standard XML-based formats, such as mzML or mzXML. Peptide identifications are written to mzIdentML or pepXML format. Protein assembly is handled by the IDPicker algorithm. Raw identifications are filtered to a confident set by use of the target-decoy strategy. IDPicker arranges large sets of input files into a hierarchy for reporting, and the software applies a parsimony algorithm to report the smallest possible number of proteins to explain the observed peptides. This protocol details the use of these tools for new users.

Supporting tool suite for production proteomics.

SUMMARY: The large amount of data produced by proteomics experiments requires effective bioinformatics tools for the integration of data management and data analysis. Here we introduce a suite of tools developed at Vanderbilt University to support production proteomics. We present the Backup Utility Service tool for automated instrument file backup and the ScanSifter tool for data conversion. We also describe a queuing system to coordinate identification pipelines and the File Collector tool for batch copying analytical results. These tools are individually useful but collectively reinforce each other. They are particularly valuable for proteomics core facilities or research institutions that need to manage multiple mass spectrometers. With minor changes, they could support other types of biomolecular resource facilities.

ScanRanker: Quality assessment of tandem mass spectra via sequence tagging.

In shotgun proteomics, protein identification by tandem mass spectrometry relies on bioinformatics tools. Despite recent improvements in identification algorithms, a significant number of high quality spectra remain unidentified for various reasons. Here we present ScanRanker, an open-source tool that evaluates the quality of tandem mass spectra via sequence tagging with reliable performance in data from different instruments. The superior performance of ScanRanker enables it not only to find unassigned high quality spectra that evade identification through database search but also to select spectra for de novo sequencing and cross-linking analysis. In addition, we demonstrate that the distribution of ScanRanker scores predicts the richness of identifiable spectra among multiple LC-MS/MS runs in an experiment, and ScanRanker scores assist the process of peptide assignment validation to increase confident spectrum identifications. The source code and executable versions of ScanRanker are available from http://fenchurch.mc.vanderbilt.edu.

A bioinformatics workflow for variant peptide detection in shotgun proteomics.

Shotgun proteomics data analysis usually relies on database search. However, commonly used protein sequence databases do not contain information on protein variants and thus prevent variant peptides and proteins from been identified. Including known coding variations into protein sequence databases could help alleviate this problem. Based on our recently published human Cancer Proteome Variation Database, we have created a protein sequence database that comprehensively annotates thousands of cancer-related coding variants collected in the Cancer Proteome Variation Database as well as noncancer-specific ones from the Single Nucleotide Polymorphism Database (dbSNP). Using this database, we then developed a data analysis workflow for variant peptide identification in shotgun proteomics. The high risk of false positive variant identifications was addressed by a modified false discovery rate estimation method. Analysis of colorectal cancer cell lines SW480, RKO, and HCT-116 revealed a total of 81 peptides that contain either noncancer-specific or cancer-related variations. Twenty-three out of 26 variants randomly selected from the 81 were confirmed by genomic sequencing. We further applied the workflow on data sets from three individual colorectal tumor specimens. A total of 204 distinct variant peptides were detected, and five carried known cancer-related mutations. Each individual showed a specific pattern of cancer-related mutations, suggesting potential use of this type of information for personalized medicine. Compatibility of the workflow has been tested with four popular database search engines including Sequest, Mascot, X!Tandem, and MyriMatch. In summary, we have developed a workflow that effectively uses existing genomic data to enable variant peptide detection in proteomics.

IDPicker 2.0: Improved protein assembly with high discrimination peptide identification filtering.

Tandem mass spectrometry-based shotgun proteomics has become a widespread technology for analyzing complex protein mixtures. A number of database searching algorithms have been developed to assign peptide sequences to tandem mass spectra. Assembling the peptide identifications to proteins, however, is a challenging issue because many peptides are shared among multiple proteins. IDPicker is an open-source protein assembly tool that derives a minimum protein list from peptide identifications filtered to a specified False Discovery Rate. Here, we update IDPicker to increase confident peptide identifications by combining multiple scores produced by database search tools. By segregating peptide identifications for thresholding using both the precursor charge state and the number of tryptic termini, IDPicker retrieves more peptides for protein assembly. The new version is more robust against false positive proteins, especially in searches using multispecies databases, by requiring additional novel peptides in the parsimony process. IDPicker has been designed for incorporation in many identification workflows by the addition of a graphical user interface and the ability to read identifications from the pepXML format. These advances position IDPicker for high peptide discrimination and reliable protein assembly in large-scale proteomics studies. The source code and binaries for the latest version of IDPicker are available from http://fenchurch.mc.vanderbilt.edu/ .

DirecTag: accurate sequence tags from peptide MS/MS through statistical scoring.

In shotgun proteomics, tandem mass spectra of peptides are typically identified through database search algorithms such as Sequest. We have developed DirecTag, an open-source algorithm to infer partial sequence tags directly from observed fragment ions. This algorithm is unique in its implementation of three separate scoring systems to evaluate each tag on the basis of peak intensity, m/ z fidelity, and complementarity. In data sets from several types of mass spectrometers, DirecTag reproducibly exceeded the accuracy and speed of InsPecT and GutenTag, two previously published algorithms for this purpose. The source code and binaries for DirecTag are available from http://fenchurch.mc.vanderbilt.edu.

Structural analysis of inhibition of E. coli methionine aminopeptidase: implication of loop adaptability in selective inhibition of bacterial enzymes.

BACKGROUND: Methionine aminopeptidase is a potential target of future antibacterial and anticancer drugs. Structural analysis of complexes of the enzyme with its inhibitors provides valuable information for structure-based drug design efforts. RESULTS: Five new X-ray structures of such enzyme-inhibitor complexes were obtained. Analysis of these and other three similar structures reveals the adaptability of a surface-exposed loop bearing Y62, H63, G64 and Y65 (the YHGY loop) that is an integral part of the substrate and inhibitor binding pocket. This adaptability is important for accommodating inhibitors with variations in size. When compared with the human isozymes, this loop either becomes buried in the human type I enzyme due to an N-terminal extension that covers its position or is replaced by a unique insert in the human type II enzyme. CONCLUSION: The adaptability of the YHGY loop in E. coli methionine aminopeptidase, and likely in other bacterial methionine aminopeptidases, enables the enzyme active pocket to accommodate inhibitors of differing size. The differences in this adaptable loop between the bacterial and human methionine aminopeptidases is a structural feature that can be exploited to design inhibitors of bacterial methionine aminopeptidases as therapeutic agents with minimal inhibition of the corresponding human enzymes.

Inhibition of monometalated methionine aminopeptidase: inhibitor discovery and crystallographic analysis.

Two divalent metal ions are commonly seen in the active-site cavity of methionine aminopeptidase, and at least one of the metal ions is directly involved in catalysis. Although ample structural and functional information is available for dimetalated enzyme, methionine aminopeptidase likely functions as a monometalated enzyme under physiological conditions. Information on structure, as well as catalysis and inhibition, of the monometalated enzyme is lacking. By improving conditions of high-throughput screening, we identified a unique inhibitor with specificity toward the monometalated enzyme. Kinetic characterization indicates a mutual exclusivity in binding between the inhibitor and the second metal ion at the active site. This is confirmed by X-ray structure, and this inhibitor coordinates with the first metal ion and occupies the space normally occupied by the second metal ion. Kinetic and structural analyses of the inhibition by this and other inhibitors provide insight in designing effective inhibitors of methionine aminopeptidase.

Structural basis of catalysis by monometalated methionine aminopeptidase.

Methionine aminopeptidase (MetAP) removes the amino-terminal methionine residue from newly synthesized proteins, and it is a target for the development of antibacterial and anticancer agents. Available x-ray structures of MetAP, as well as other metalloaminopeptidases, show an active site containing two adjacent divalent metal ions bridged by a water molecule or hydroxide ion. The predominance of dimetalated structures leads naturally to proposed mechanisms of catalysis involving both metal ions. However, kinetic studies indicate that in many cases, only a single metal ion is required for full activity. By limiting the amount of metal ion present during crystal growth, we have now obtained a crystal structure for a complex of Escherichia coli MetAP with norleucine phosphonate, a transition-state analog, and only a single Mn(II) ion bound at the active site in the position designated M1, and three related structures of the same complex that show the transition from the mono-Mn(II) form to the di-Mn(II) form. An unliganded structure was also solved. In view of the full kinetic competence of the monometalated MetAP, the much weaker binding constant for occupancy of the M2 site compared with the M1 site, and the newly determined structures, we propose a revised mechanism of peptide bond hydrolysis by E. coli MetAP. We also suggest that the crystallization of dimetalated forms of metallohydrolases may, in some cases, be a misleading experimental artifact, and caution must be taken when structures are generated to aid in elucidation of reaction mechanisms or to support structure-aided drug design efforts.

Structural analysis of metalloform-selective inhibition of methionine aminopeptidase.

One of the challenges in the development of methionine aminopeptidase (MetAP) inhibitors as antibacterial and anticancer agents is to define the metal ion actually used by MetAP in vivo and to discover MetAP inhibitors that can inhibit the metalloform that is relevant in vivo. Two distinct classes of novel nonpeptidic MetAP inhibitors that are not only potent but also highly selective for either the Mn(II) or Co(II) form have been identified. Three crystal structures of Escherichia coli MetAP complexed with the metalloform-selective inhibitors 5-(2,5-dichlorophenyl)furan-2-carboxylic acid (2), 5-[2-(trifluoromethyl)phenyl]furan-2-carboxylic acid (3) and N-cyclopentyl-N-(thiazol-2-yl)oxalamide (4) have been solved and analysis of these structures has revealed the structural basis for their metalloform-selective inhibition. The Mn(II)-form selective inhibitors (2) and (3) both use their carboxylate group to coordinate with the two Mn(II) ions at the dinuclear metal site and both adopt a non-coplanar conformation for the two aromatic rings. The unique coordination geometry of these inhibitors may determine their Mn(II)-form selectivity. In contrast, the Co(II)-form selective inhibitor (4) recruits an unexpected third metal ion, forming a trimetallic enzyme-metal-inhibitor complex. Thus, an important factor in the selectivity of (4) for the Co(II) form may be a consequence of a greater preference for a softer N,O-donor ligand for the softer Co(II).

Metal mediated inhibition of methionine aminopeptidase by quinolinyl sulfonamides.

Quinolinyl sulfonamides, such as N-(quinolin-8-yl)methanesulfonamide (10) and N-(5-chloroquinolin-8-yl)methanesulfonamide (11), were identified as potent methionine aminopeptidase (MetAP) inhibitors by high throughput screening of a diverse chemical library of small organic compounds. They showed different inhibitory potencies on Co(II)-, Ni(II)-, Fe(II)-, Mn(II)-, and Zn(II)-forms of Escherichia coli MetAP, and their inhibition is dependent on metal concentration. X-ray structures of E. coli MetAP complexed with 10 revealed that the inhibitor forms a metal complex with the residue H79 at the enzyme active site; the complex is further stabilized by an extended H-bond and metal interaction network. Analysis of the inhibition of MetAP by these inhibitors indicates that this is a typical mechanism of inhibition for many non-peptidic MetAP inhibitors and emphasizes the importance of defining in vitro conditions for identifying and evaluating MetAP inhibitors that will be capable of giving information relevant to the in vivo situation.

Metalloform-selective inhibitors of escherichia coli methionine aminopeptidase and X-ray structure of a Mn(II)-form enzyme complexed with an inhibitor.

Methionine aminopeptidase (MetAP) enzymes require a divalent metal ion such as Mn(II), Fe(II), Co(II), Ni(II), or Zn(II) for its removal of the N-terminal methionine from newly synthesized proteins, but it is not certain which of these ions is most important in vivo. Metalloform-selective MetAP inhibitors could be valuable for defining which metals are physiologically relevant for MetAP activation and could serve as leads for development of new therapeutic agents. We have screened a library of 43 736 small drug-like molecules against Escherichia coli MetAP and identified two groups of potent and highly metalloform-selective inhibitors of the Co(II)-form, and of the Mn(II)-form, of this enzyme. Compound 1 is 790-fold more selective for the Co(II)-form, while compound 4 is over 640-fold more potent toward the Mn(II)-form. The X-ray structure of a di-Mn(II) form of E. coli MetAP complexed with the Mn(II)-form-selective compound 4 was obtained, and it shows that the inhibitor interacts with both Mn(II) ions through the two oxygen atoms of its free carboxylate group. The preferential coordination of the hard (oxygen) donors to Mn(II) may contribute to its superb selectivity toward the Mn(II)-form.