Literature DB >> 33511378

Utilization of electronic health records for the assessment of adiponectin receptor autoantibodies during the progression of cardio-metabolic comorbidities.

Michael J Pugia1, Meeta Pradhan2, Rong Qi2, Doreen L Eastes1, Anna Vorsilak1, Bradley J Mills2, Zane Baird1, Aruna Wijeratne3, Scott M McAhren4, Amber Mosley3, Anantha Shekhar3, Daniel H Robertson2.   

Abstract

BACKGROUND: Diabetes is a complex, multi-symptomatic disease whose complications drives increases in healthcare costs as the diabetes prevalence grows rapidly world-wide. Real-world electronic health records (EHRs) coupled with patient biospecimens, biological understanding, and technologies can characterize emerging diagnostic autoimmune markers resulting from proteomic discoveries.
METHODS: Circulating autoantibodies for C-terminal fragments of adiponectin receptor 1 (IgG-CTF) were measured by immunoassay to establish the reference range using midpoint samples from 1862 participants in a 20-year observational study of type 2 diabetes and cardiovascular arterial disease (CVAD) conducted by the Fairbanks Institute. The White Blood Cell elastase activity in these patients was assessed using immunoassays for Bikunin and Uristatin. Participants were assigned to four cohorts (healthy, T2D, CV, CV+T2D) based on analysis of their EHRs and the diagnostic biomarkers values and patient status were assessed ten-years post-sample.
RESULTS: The IgG-CTF reference range was determined to be 75-821 ng/mL and IgG-CTF out-of-range values did not predict cohort or comorbidity as determined from the EHRs at 10 years after sample collection nor did IgG-CTF demonstrate a significant risk for comorbidity or death. Many patients at sample collection time had other conditions (hypertension, hyperlipidemia, or other risk factors) of which only hypertension, Uristatin and Bikunin values correlated with increased risk of developing additional comorbidities (odds ratio 2.58-13.11, P<0.05).
CONCLUSIONS: This study confirms that retrospective analysis of biorepositories coupled with EHRs can establish reference ranges for novel autoimmune diagnostic markers and provide insights into prediction of specific health outcomes and correlations to other markers.

Entities:  

Year:  2020        PMID: 33511378      PMCID: PMC7839988          DOI: 10.46439/autoimmune.1.004

Source DB:  PubMed          Journal:  Arch Autoimmune Dis


  36 in total

1.  Precision of heavy-light peptide ratios measured by maldi-tof mass spectrometry.

Authors:  N Leigh Anderson; Morteza Razavi; Terry W Pearson; Gary Kruppa; Rainer Paape; Detlef Suckau
Journal:  J Proteome Res       Date:  2012-02-03       Impact factor: 4.466

2.  Immunological evaluation of urinary trypsin inhibitors in blood and urine: role of N- & O-linked glycoproteins.

Authors:  Michael J Pugia; Saeed A Jortani; Manju Basu; Ronald Sommer; Hai-Hang Kuo; Solomon Murphy; Doug Williamson; James Vranish; Patrick J Boyle; Danny Budzinski; Roland Valdes; Subhash C Basu
Journal:  Glycoconj J       Date:  2007-01       Impact factor: 2.916

3.  Intensive diabetes treatment and cardiovascular disease in patients with type 1 diabetes.

Authors:  David M Nathan; Patricia A Cleary; Jye-Yu C Backlund; Saul M Genuth; John M Lachin; Trevor J Orchard; Philip Raskin; Bernard Zinman
Journal:  N Engl J Med       Date:  2005-12-22       Impact factor: 91.245

Review 4.  Adiponectin and adiponectin receptors in insulin resistance, diabetes, and the metabolic syndrome.

Authors:  Takashi Kadowaki; Toshimasa Yamauchi; Naoto Kubota; Kazuo Hara; Kohjiro Ueki; Kazuyuki Tobe
Journal:  J Clin Invest       Date:  2006-07       Impact factor: 14.808

5.  Adiponectin inhibits cell proliferation by interacting with several growth factors in an oligomerization-dependent manner.

Authors:  Yu Wang; Karen S L Lam; Jian Yu Xu; Gang Lu; Lance Yi Xu; Garth J S Cooper; Aimin Xu
Journal:  J Biol Chem       Date:  2005-02-25       Impact factor: 5.157

Review 6.  Insulin resistance: metabolic mechanisms and consequences in the heart.

Authors:  E Dale Abel; Karen M O'Shea; Ravichandran Ramasamy
Journal:  Arterioscler Thromb Vasc Biol       Date:  2012-09       Impact factor: 8.311

7.  Adiponectin-mediated modulation of hypertrophic signals in the heart.

Authors:  Rei Shibata; Noriyuki Ouchi; Masahiro Ito; Shinji Kihara; Ichiro Shiojima; David R Pimentel; Masahiro Kumada; Kaori Sato; Stephan Schiekofer; Koji Ohashi; Tohru Funahashi; Wilson S Colucci; Kenneth Walsh
Journal:  Nat Med       Date:  2004-11-21       Impact factor: 53.440

8.  Association of adiponectin with coronary heart disease and mortality: the Rancho Bernardo study.

Authors:  Gail A Laughlin; Elizabeth Barrett-Connor; Susanne May; Claudia Langenberg
Journal:  Am J Epidemiol       Date:  2006-11-13       Impact factor: 4.897

9.  Adiponectin stimulates glucose utilization and fatty-acid oxidation by activating AMP-activated protein kinase.

Authors:  T Yamauchi; J Kamon; Y Minokoshi; Y Ito; H Waki; S Uchida; S Yamashita; M Noda; S Kita; K Ueki; K Eto; Y Akanuma; P Froguel; F Foufelle; P Ferre; D Carling; S Kimura; R Nagai; B B Kahn; T Kadowaki
Journal:  Nat Med       Date:  2002-10-07       Impact factor: 53.440

10.  Profiling structured product labeling with NDF-RT and RxNorm.

Authors:  Qian Zhu; Guoqian Jiang; Christopher G Chute
Journal:  J Biomed Semantics       Date:  2012-12-20
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