Cytokine genes in susceptibility to coal workers’ pneumoconiosis

Cytokine genes in susceptibility to coal workers’ pneumoconiosis

Abstracts / Toxicology Letters 164S (2006) S1–S324 P3-05 Cytokine genes in susceptibility to coal workers’ pneumoconiosis Asuman Karakaya 1 , Ilker A...

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Abstracts / Toxicology Letters 164S (2006) S1–S324

P3-05 Cytokine genes in susceptibility to coal workers’ pneumoconiosis Asuman Karakaya 1 , Ilker Ates 1 , Berran Yucesoy 2 , Sinan H. Suzen 1 1 Ankara

University, Faculty of Pharmacy, Tandogan, Ankara Turkey; 2 Toxicology and Molecular Biology Branch, National Institute for Occupational Safety and Health, WV, USA Coal workers’ pneumoconiosis (CWP) and silicosis are the most widespread fibrotic lung diseases whose etiopathogenesis are not well defined. Pro-inflammatory cytokines play a pivotal role in the onset, progression and termination of the reactions such as inflammation, fibroblast proliferation and extracellular matrix (ECM) synthesis in CWP and silicosis. Recent studies suggest that these diseases may share genetic risk factors. In this study, the frequency of single nucleotide polymorphisms (SNPs) in the genes coding for TNF-␣, IL-1␣, IL-1␤ and IL-6 and their genotype associations with CWP and disease severity were determined in a 56 Turkish coal workers with CWP (34 pneumoconiotic, 22 fibrotic) and 99 healthy controls without any apparent inflammation or other pulmonary disease. According to the genotyping results, regardless of disease severity, TNF-␣ (−238) and IL-1␤ (+3953) polymorphisms affected CWP occurrence (OR’s 1.86 and 1.52, respectively). On the other hand, both TNF-␣ (−238) and (−308) variants were associated with an increased risk of developing PMF (OR’s 3.44 and 1.47, respectively). IL-1␤ (+3953) variant was also associated with the development of simple CWP (OR: 1.90). No significant association was found between variations in IL-6 and IL-1␣ genes and the occurrence and progression of CWP and PMF. In conclusion, this study suggests that TNF-␣ and IL1␤ polymorphisms may be considered as susceptibility factors for CWP. Supported by Research Fund of Ankara University20030803036. doi:10.1016/j.toxlet.2006.06.220

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P3-06 Bone marrow differentials—Comparison of flow cytometry and manual counting in rats treated with compounds inducing hematological changes Andre Forichon, Fabienne Condevaux, MarieFrancoise Perron-Lepage, Jacques Descotes Poison Center and Pharmacovigilance Unit, France Bone marrow analysis is recommended to screen for hematotoxic as well as immunotoxic pharmaceuticals. Because manual counting is time-consuming and lack sensitivity, a flow cytometry method has been developed to investigate bone marrow cell-specific populations in rats. A series of monoclonal antibodies (Pharmingen, Becton-Dickinson) was selected for immunostaining, which allowed accurate identification of the lymphocyte, erythroid and myeloid populations based on the differential expression of the cell surface antigens CD71, CD3, CD45, CD45RA and CD45R. Bone marrow samples were taken from groups of eight 8-week-old male Sprague–Dawley rats treated with the reference compounds, erythropoietin (EPO), dexamethasone, doxorubicin or LPS, and examined for lineage-specific changes in cell populations. Samples from each rat were evaluated by flow cytometry (FACScan, Becton Dickinson) as well as manual counting from bone marrow smear examination. Expected changes, i.e. lymphopenia (dexamethasone), myelosuppression (doxorubicin), leucocytosis (LPS) or increased immature erythroid population (EPO) were clearly identified by flow cytometry. Bone marrow differentials obtained by flow cytometry were similar to those obtained by manual counting. Cell separation was confirmed by cell sorting (FACS Vantage, Becton Dickinson). Thus, flow cytometry appears to be a sensitive and cost-effective alternative to manual counting for the initial screening of toxic effects on the bone marrow in preclinical safety studies. In addition, this method provides an evaluation of bone marrow cellularity and absolute values for each sub-population. doi:10.1016/j.toxlet.2006.06.221