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Unlocking the genetic tapestry of autoimmune diseases: Unveiling common genes across multiple conditions.
Ghosh, Soujanya; Mohanty, Rupali; Santra, Arunava; Saha, Anisha; Agrawal, Anubha; Shrivastava, Sharmishtha; Roy, Chandrashish; Mazumder, Ishanee; Das, Debarup; Mahmood, Syed Haaris.
Affiliation
  • Ghosh S; School of Biotechnology, KIIT University, Bhubaneswar, Odisha, India.
  • Mohanty R; School of Biotechnology, KIIT University, Bhubaneswar, Odisha, India.
  • Santra A; School of Biotechnology, KIIT University, Bhubaneswar, Odisha, India.
  • Saha A; School of Biotechnology, KIIT University, Bhubaneswar, Odisha, India.
  • Agrawal A; School of Biotechnology, KIIT University, Bhubaneswar, Odisha, India.
  • Shrivastava S; School of Biotechnology, KIIT University, Bhubaneswar, Odisha, India.
  • Roy C; School of Biotechnology, KIIT University, Bhubaneswar, Odisha, India.
  • Mazumder I; School of Biotechnology, KIIT University, Bhubaneswar, Odisha, India.
  • Das D; School of Biotechnology, KIIT University, Bhubaneswar, Odisha, India.
  • Mahmood SH; School of Biotechnology, KIIT University, Bhubaneswar, Odisha, India.
Int J Rheum Dis ; 27(5): e15185, 2024 May.
Article in En | MEDLINE | ID: mdl-38742742
ABSTRACT

OBJECTIVES:

This study aimed to unravel the complexities of autoimmune diseases by conducting a comprehensive analysis of gene expression data across 10 conditions, including systemic lupus erythematosus (SLE), psoriasis, Sjögren's syndrome, sclerosis, immune-associated diseases, osteoarthritis, cystic fibrosis, inflammatory bowel disease (IBD), type 1 diabetes, and Guillain-Barré syndrome.

METHODS:

Gene expression profiles were rigorously examined to identify both upregulated and downregulated genes specific to each autoimmune disease. The study employed visual representation techniques such as heatmaps, volcano plots, and contour-MA plots to provide an intuitive understanding of the complex gene expression patterns in these conditions.

RESULTS:

Distinct gene expression profiles for each autoimmune condition were uncovered, with psoriasis and osteoarthritis standing out due to a multitude of both upregulated and downregulated genes, indicating intricate molecular interplays in these disorders. Notably, common upregulated and downregulated genes were identified across various autoimmune conditions, with genes like SELENBP1, MMP9, BNC1, and COL1A1 emerging as pivotal players.

CONCLUSION:

This research contributes valuable insights into the molecular signatures of autoimmune diseases, highlighting the unique gene expression patterns characterizing each condition. The identification of common genes shared among different autoimmune conditions, and their potential role in mitigating the risk of rare diseases in patients with more prevalent conditions, underscores the growing significance of genetics in healthcare and the promising future of personalized medicine.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Autoimmune Diseases / Genetic Predisposition to Disease / Gene Expression Profiling Limits: Humans Language: En Journal: Int J Rheum Dis Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Autoimmune Diseases / Genetic Predisposition to Disease / Gene Expression Profiling Limits: Humans Language: En Journal: Int J Rheum Dis Year: 2024 Document type: Article