Human urinary peptide database for multiple disease biomarker discovery

Siwy, Justyna; Mullen, William; Golovko, Igor; Franke, Julia; Zürbig, Petra

doi:10.1002/prca.201000155

Cited by 112 publications

(105 citation statements)

References 49 publications

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“…Using a discovery cohort of 25 non-diabetic healthy controls and 25 patients with DN available in the human urinary peptide database 35 (Table 3), we built a classifier based on the orthologs, which significantly distinguished between the 2 groups in the discovery set (Fig. 4A).…”

Section: Validation Of the Humanized Urinary Peptide Based Classifiermentioning

confidence: 99%

“…Human CE-MS data and general patient characteristics (Table 5) were extracted from the human urinary peptide database 35 and from 27 . The study was designed and conducted fulfilling all of the requisites of the laws on the protection of individuals collaborating in medical research and was in accordance with the principles of the Declaration of Helsinki.…”

Section: Human Data Ce-ms and Patient Datamentioning

confidence: 99%

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Urinary peptidomics provides a noninvasive humanized readout of diabetic nephropathy in mice

Klein

Ramírez-Torres

Ericsson

et al. 2016

Kidney International

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Diabetic nephropathy (DN) is among the most frequent complications of diabetes and the first cause of end-stage renal disease. Despite being successful in animal models, the majority of clinical trials for novel drugs targeting DN failed. This lack of translational value may in part be due to an inadequate comparability of human disease and animal models that often capture only a few aspects of disease. Here we overcome this limitation by developing a multimolecular non-invasive humanized readout of DN based on urinary peptidomics. The diseasemodified urinary peptides of two type 2 diabetic (T2D) DN mouse models were identified and compared with previously validated urinary peptide markers of DN in humans to generate a classifier composed of 21 ortholog peptides. This classifier predicted the response to disease and treatment with inhibitors of the renin-angiotensin system (RASi) in mice. The humanized classifier was significantly correlated with glomerular lesions. Using a human T2D validation cohort consisting of 207 patients, the classifier also distinguished between patients with and without DN, and response to RASi. Our approach demonstrates that a combination of multiple molecular features similar in both human and animal disease could provide a step change in translational drug discovery research in T2D-DN nephropathy.

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Section: Validation Of the Humanized Urinary Peptide Based Classifiermentioning

confidence: 99%

Section: Human Data Ce-ms and Patient Datamentioning

confidence: 99%

Urinary peptidomics provides a noninvasive humanized readout of diabetic nephropathy in mice

Klein

Ramírez-Torres

Ericsson

et al. 2016

Kidney International

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“…Those investigated so far range from renal disorders [16,17] to cardiovascular disease [18] and diabetes [19]. Many of these biomarker profiles have been recorded in a database made up from over 13,000 samples [20]. These biomarkers are not based on a single analyte but are composed of a group or panel of proteins/peptides.…”

Section: Introductionmentioning

confidence: 99%

A peptidomic approach to biomarker discovery for bovine mastitis

Mansor

Mullen

Barrett

et al. 2012

Farm Animal Proteomics

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Bovine mastitis is usually caused by either Gram positive or Gram negative bacteria, reducing the quantity and quality of milk produced. This investigation using capillary electrophoresis and mass spectroscopy, studied peptides in milk from cows with clinical mastitis in comparison to milk from healthy cows to identify biomarkers for mastitis. In addition, the milk peptidome from udders infected with Gram positive Staphylococcus aureus (S. aureus) or with Gram negative Escherichia coli (E. coli), was examined to assess differential diagnosis between the causative agent. Comparison of the peptidome between healthy (n = 10) and mastitic milk (n = 27) identified 154 peptides for a biomarker panel which in a model for diagnosis of mastitis showed 100% sensitivity and specificity. β-casein and α s1 casein provided the majority of peptides identified in this model. The peptidome comparison of milk from mastitis cases caused by S. aureus (n = 8) or E. coli (n = 11) revealed a biomarker panel of 47 peptides which discriminated between cause of infection with a sensitivity of 75% and a specificity of 100%. β-casein fragments were the most common of the peptides in this model.

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“…The proteins/peptides in urine can reflect the physiological state of an individual and collection of urine is noninvasive [1]. Accordingly, urine could provide a rich source for cancer biomarkers and offer promise for clinical diagnosis [2]. However, urine is only used for diagnosis of a few diseases directly correlated with the function of kidney [3].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the human urine endogenous peptides by nanoparticle extraction and mass spectrometry identification

Yang

et al. 2014

Analytica Chimica Acta

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Human urinary peptide database for multiple disease biomarker discovery

Cited by 112 publications

References 49 publications

Urinary peptidomics provides a noninvasive humanized readout of diabetic nephropathy in mice

Urinary peptidomics provides a noninvasive humanized readout of diabetic nephropathy in mice

A peptidomic approach to biomarker discovery for bovine mastitis

Analysis of the human urine endogenous peptides by nanoparticle extraction and mass spectrometry identification

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