Literature DB >> 26075473

Profiling Amino Acids of Jordanian Scalp Hair as a Tool for Diabetes Mellitus Diagnosis: A Pilot Study.

Ayat H B Rashaid1, Peter de B Harrington2, Glen P Jackson3.   

Abstract

Hair analysis is an area of increasing interest in the fields of medical and forensic sciences. Human scalp hair has attractive features in clinical studies because hair can be sampled easily and noninvasively from human subjects, and unlike blood and urine samples, it contains a chronological record of medication use. Keratin protein is the major component of scalp hair shaft material and it is composed of 21 amino acids. The method used herein for the amino acid determination in hair included keratin protein acid hydrolysis using 6 M hydrochloric acid (HCl), followed by amino acids derivatization using N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA), and the determination of derivatized amino acids by gas chromatography/mass spectrometry (GC/MS). Amino acid profiles of scalp hair of 27 Jordanian subjects (15 diabetes mellitus (DM) type 2 patients and 12 control subjects) were analyzed. A fuzzy rule-building expert system (FuRES) classified the amino acid profiles into diabetic and control groups based on multivariate analyses of the abundance of 14 amino acids. The sensitivity and specificity were 100% for diabetes detection using leave-one-individual-out cross-validation. The areas under the receiver operative characteristics (ROC) curves were 1.0, which represents a highly sensitive and specific diabetes test. The nonessential amino acids Gly and Glu, and the essential amino acid Ile were more abundant in the scalp hair of diabetic patients compared to the hair of control subjects. The associations between the abundance of amino acids of human hair and health status may have clinical applications in providing diagnostic indicator or predicting other chronic or acute diseases.

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Year:  2015        PMID: 26075473     DOI: 10.1021/acs.analchem.5b00460

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  6 in total

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Authors:  Lesley A Chesson; Janet E Barnette; Gabriel J Bowen; J Renée Brooks; John F Casale; Thure E Cerling; Craig S Cook; Charles B Douthitt; John D Howa; Janet M Hurley; Helen W Kreuzer; Michael J Lott; Luiz A Martinelli; Shannon P O'Grady; David W Podlesak; Brett J Tipple; Luciano O Valenzuela; Jason B West
Journal:  Oecologia       Date:  2018-06-28       Impact factor: 3.225

Review 2.  Minimally Invasive Biospecimen Collection for Exposome Research in Children's Health.

Authors:  Lauren M Petrick; Manish Arora; Megan M Niedzwiecki
Journal:  Curr Environ Health Rep       Date:  2020-09

Review 3.  Biomarkers for nutrient intake with focus on alternative sampling techniques.

Authors:  T Holen; F Norheim; T E Gundersen; P Mitry; J Linseisen; P O Iversen; C A Drevon
Journal:  Genes Nutr       Date:  2016-04-16       Impact factor: 5.523

4.  Position-specific 13 C/12 C analysis of amino acid carboxyl groups - automated flow-injection analysis based on reaction with ninhydrin.

Authors:  Brian Fry; James F Carter; Keita Yamada; Naohiro Yoshida; Dieter Juchelka
Journal:  Rapid Commun Mass Spectrom       Date:  2018-06-30       Impact factor: 2.419

5.  Hair follicle characteristics as early marker of Type 2 Diabetes.

Authors:  J Jaime Miranda; Alvaro Taype-Rondan; Jose Carlos Tapia; Maria Gabriela Gastanadui-Gonzalez; Ricardo Roman-Carpio
Journal:  Med Hypotheses       Date:  2016-08-16       Impact factor: 4.411

6.  Association between maternal exposure to phthalates and lower language ability in offspring derived from hair metabolome analysis.

Authors:  Beatrix Jones; Ting-Li Han; Thibaut Delplancke; Elizabeth J McKenzie; Jamie V de Seymour; Mei Chien Chua; Kok Hian Tan; Philip N Baker
Journal:  Sci Rep       Date:  2018-04-30       Impact factor: 4.379

  6 in total

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