Evaluation of signs of immune or metabolic disturbances among diabetic patients with positive islet cell antibodies

Authors

  • Zhian M. Ibrahim Dezayee Dept. of Immunology, College of Medicine, Hawler Medical University
  • Nabeel E. Waheda Dept. of Immunology, College of Medicine, Hawler Medical University
  • Sabria M. Said Al- Salihi Dept. of Immunology, College of Medicine, Hawler Medical University

DOI:

https://doi.org/10.32007/jfacmedbagdad.541773

Keywords:

Islet cell antibodies, lipid profile, immunoglobulins

Abstract

Background: Autoantibodies to islet cell antigens are known predictors of type 1 diabetes and detected in latent autoimmune diabetes in adults.
Objectives: This study aimed to identify the metabolic and immunological disturbances in diabetic patients with positive and negative islet cell antibodies (ICAs)
Materials and methods: A total number of 235 known cases of diabetes mellitus type 1 (160) and type 2 diabetes (75) were admitted in the study. Serum ICA and immunoglobulins (IgA, IgM, IgG) as well lipid profile were measured.
Results: Positive ICAs was found in 40 out of 120 T1D (33.3%) and 28 out of 75 T2D (37.3%). All the patients were poorly controlled diabetes with the evidence of significant high HbA1c%. There were no significant differences in the lipid profile or immunoglobulin levels between positive and negative ICAs in T1D and T2D.
Conclusions: Autoimmunity in term of positive ICA does not play a role in metabolic or immunologic disturbances that associated with T1D and T2D.

Downloads

Download data is not yet available.

Downloads

Published

01.04.2012

How to Cite

1.
Ibrahim Dezayee ZM, Waheda NE, Said Al- Salihi SM. Evaluation of signs of immune or metabolic disturbances among diabetic patients with positive islet cell antibodies. J Fac Med Baghdad [Internet]. 2012 Apr. 1 [cited 2024 Nov. 21];54(1):63-7. Available from: https://iqjmc.uobaghdad.edu.iq/index.php/19JFacMedBaghdad36/article/view/773

Publication Dates

Similar Articles

11-20 of 256

You may also start an advanced similarity search for this article.