Literature DB >> 22083824

Using SELDI-TOF mass spectrometry on amniotic fluid and for clinical proteomics and theranostics in disorders of pregnancy.

Irina A Buhimschi1.   

Abstract

Clinical proteomics encompasses a multitude of experimental approaches, tools, and techniques based on proteomics technology which are directly aimed to accelerate and improve diagnosis and treatment of human diseases. Surface-enhanced laser desorption ionization time-of-flight (SELDI-TOF) mass spectrometry is a variant of matrix-enhanced laser desorption ionization (MALDI) that makes use of chemically-modified surfaces to reduce the complexity of biological samples prior to separation in the mass analyzer. Compared to other proteomic techniques, SELDI has several important advantages such as ability to analyze complex biological samples with minimal pre-processing, ease of handling and high throughput. Importantly, once the biomarker or combination of biomarkers with potential clinical value has been established, validation analyses can be conducted in close proximity to clinical settings which is important for establishing the utility of new diagnostics in clinical decision making and perhaps future theranostic interventions. This chapter provides protocols for experimental design and methodology aimed at (1) discovering biologically relevant biomarkers in amniotic fluid using SELDI-TOF; (2) validating the clinical utility of the biomarkers as new diagnostics; (3) translating the biomarker findings into pathophysiological phenomena to provide further insight and extend the current understanding of the disease process. Many of the principles described herein for amniotic fluid could be generalized to studies involving other types of biological samples and other clinical questions.

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Year:  2012        PMID: 22083824      PMCID: PMC3792576          DOI: 10.1007/978-1-61779-418-6_13

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  15 in total

1.  Discriminatory proteomic biomarker analysis identifies free hemoglobin in the cerebrospinal fluid of women with severe preeclampsia.

Authors:  Errol R Norwitz; Lawrence C Tsen; Joong Shin Park; Patricia A Fitzpatrick; David M Dorfman; George R Saade; Catalin S Buhimschi; Irina A Buhimschi
Journal:  Am J Obstet Gynecol       Date:  2005-09       Impact factor: 8.661

2.  Proteomics technology for the accurate diagnosis of inflammation in twin pregnancies.

Authors:  Irina A Buhimschi; Catalin S Buhimschi; Rob Christner; Carl P Weiner
Journal:  BJOG       Date:  2005-02       Impact factor: 6.531

Review 3.  The importance of experimental design in proteomic mass spectrometry experiments: some cautionary tales.

Authors:  Jianhua Hu; Kevin R Coombes; Jeffrey S Morris; Keith A Baggerly
Journal:  Brief Funct Genomic Proteomic       Date:  2005-02

4.  Proteomic technology and delayed interval delivery in multiple pregnancies.

Authors:  C S Buhimschi; C M Pettker; L K Magloire; R Martin; E Norwitz; E Funai; I A Buhimschi
Journal:  Int J Gynaecol Obstet       Date:  2005-07       Impact factor: 3.561

5.  Sample size determination for diagnostic accuracy studies involving binormal ROC curve indices.

Authors:  N A Obuchowski; D K McClish
Journal:  Stat Med       Date:  1997-07-15       Impact factor: 2.373

6.  Proteomic but not enzyme-linked immunosorbent assay technology detects amniotic fluid monomeric calgranulins from their complexed calprotectin form.

Authors:  Irina A Buhimschi; Catalin S Buhimschi; Carl P Weiner; Tatsuji Kimura; Benjamin D Hamar; Anna K Sfakianaki; Errol R Norwitz; Edmund F Funai; Elena Ratner
Journal:  Clin Diagn Lab Immunol       Date:  2005-07

7.  A method of comparing the areas under receiver operating characteristic curves derived from the same cases.

Authors:  J A Hanley; B J McNeil
Journal:  Radiology       Date:  1983-09       Impact factor: 11.105

8.  Proteomic biomarker analysis of amniotic fluid for identification of intra-amniotic inflammation.

Authors:  Irina A Buhimschi; Rob Christner; Catalin S Buhimschi
Journal:  BJOG       Date:  2005-02       Impact factor: 6.531

9.  Proteomic biomarkers of intra-amniotic inflammation: relationship with funisitis and early-onset sepsis in the premature neonate.

Authors:  Catalin S Buhimschi; Irina A Buhimschi; Sonya Abdel-Razeq; Victor A Rosenberg; Stephen F Thung; Guomao Zhao; Erica Wang; Vineet Bhandari
Journal:  Pediatr Res       Date:  2007-03       Impact factor: 3.756

10.  Proteomic biomarkers that predict the clinical success of rescue cerclage.

Authors:  Carl P Weiner; Keun-Young Lee; Catalin S Buhimschi; Rob Christner; Irina A Buhimschi
Journal:  Am J Obstet Gynecol       Date:  2005-03       Impact factor: 8.661

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  6 in total

Review 1.  Advances in medical diagnosis of intra-amniotic infection.

Authors:  Irina A Buhimschi; Unzila A Nayeri; Christine A Laky; Sonya-Abdel Razeq; Antonette T Dulay; Catalin S Buhimschi
Journal:  Expert Opin Med Diagn       Date:  2012-08-17

Review 2.  Amniotic fluid: the use of high-dimensional biology to understand fetal well-being.

Authors:  Beena D Kamath-Rayne; Heather C Smith; Louis J Muglia; Ardythe L Morrow
Journal:  Reprod Sci       Date:  2013-04-18       Impact factor: 3.060

Review 3.  Proteomics/diagnosis of chorioamnionitis and of relationships with the fetal exposome.

Authors:  Irina A Buhimschi; Catalin S Buhimschi
Journal:  Semin Fetal Neonatal Med       Date:  2011-11-21       Impact factor: 3.926

Review 4.  The role of proteomics in the diagnosis of chorioamnionitis and early-onset neonatal sepsis.

Authors:  Irina A Buhimschi; Catalin S Buhimschi
Journal:  Clin Perinatol       Date:  2010-06       Impact factor: 3.430

Review 5.  Power of proteomics in linking oxidative stress and female infertility.

Authors:  Sajal Gupta; Jana Ghulmiyyah; Rakesh Sharma; Jacques Halabi; Ashok Agarwal
Journal:  Biomed Res Int       Date:  2014-05-12       Impact factor: 3.411

Review 6.  Evaluation of the Molecular Mechanisms of Sepsis Using Proteomics.

Authors:  He Miao; Song Chen; Renyu Ding
Journal:  Front Immunol       Date:  2021-10-21       Impact factor: 7.561

  6 in total

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