Literature DB >> 35066979

GNLY gene polymorphism: A potential role in understanding psoriasis pathogenesis.

Hesham Nabil Khalid1, Yasser Abd Elsattar Elghobashy2, Asmaa Nagy Elsayed3.   

Abstract

BACKGROUND: Psoriasis is a chronic inflammatory illness that affects 2%-3% of the world's population. Granulysin (GNLY), along with granzyme and perforin, is a cytolytic antimicrobial peptide (AMP) released from the granules of both natural killer (NK) cells and cytotoxic T lymphocytes (CTLs). By immunohistochemistry, it has been shown that GNLY expression increases in psoriasis lesions. AIMS: Our work aimed to reveal the potential effect of GNLY gene polymorphism and its association with psoriasis pathogenesis.
METHODS: This case-control research included 25 patients with psoriasis vulgaris and 25 healthy people who were age and gender matched. History taking and medical examination were done for all patients. Venous blood samples were withdrawn, DNA was extracted, and real-time PCR was done.
RESULTS: There was an insignificant difference between psoriasis cases and controls as regards gene sequence (p > 0.05). The polymorphism of GNLY gene regarding genotype distribution G/G was detected in seven patients with psoriasis (28%) and in only two controls (8%). This clarifies that GNLY rs 7908 G/G gene polymorphism may be a strong diagnostic tool for psoriasis.
CONCLUSIONS: In patients with psoriasis, the GNLY rs7908 CC genotype alongside with C allele played a preventative function and reduced disease severity (as shown by PASI score). Detection of GG genotype points out that a psoriatic case will run a progressive course, will have a severe pattern in the future, and will develop multiple site affection.
© 2022 Wiley Periodicals LLC.

Entities:  

Keywords:  gene polymorphism; granulysin; psoriasis

Year:  2022        PMID: 35066979     DOI: 10.1111/jocd.14792

Source DB:  PubMed          Journal:  J Cosmet Dermatol        ISSN: 1473-2130            Impact factor:   2.696


  1 in total

1.  Screening of Sepsis Biomarkers Based on Bioinformatics Data Analysis.

Authors:  Guibin Liang; Jiuang Li; Shiqian Pu; Zhihui He
Journal:  J Healthc Eng       Date:  2022-09-26       Impact factor: 3.822

  1 in total

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