EVALUATION OF HPV, HHV AND TTV VIRUSES IN SALIVA OF CRACK USERS

• Grant number: 23/06788-0
• Support Opportunities: Scholarships in Brazil - Master
• Start date: July 01, 2024
• End date: February 28, 2025
• Field of knowledge: Health Sciences - Dentistry - Dental Clinics
• Principal Investigator: Janete Dias Almeida
• Grantee: Thaís Xavier Pereira da Silva
• Host Institution: Instituto de Ciência e Tecnologia (ICT). Universidade Estadual Paulista (UNESP). Campus de São José dos Campos. São José dos Campos , SP, Brazil

Abstract

Crack is an illicit drug produced from cocaine. Its low cost favors its accessibility, and its consumption produces effects such as euphoria and a feeling of pleasure. The health consequences are numerous, from neurological, pulmonary, cardiovascular, cognitive, psychological alterations, to oral alterations. A higher rate of caries, tooth loss, periodontal disease and reduced salivary flow rate have already been observed and reported. In addition, the relationship between chemical dependence and the high rate of contamination by the Human Immunodeficiency Virus (HIV), Hepatitis B Virus (HBV) and Hepatitis C Virus (HCV) has been shown in several studies. However, regarding the evaluation of other viral types, mainly using saliva as a means of analysis, studies are scarce. The objective of this work is to evaluate the presence of three viruses (Human Papilloma Virus [HPV], Human Herpes Virus [HHV] and Torque Teno Virus [TTV]) in the saliva of crack users, through the quantification of viral genetic material. For this, saliva samples previously collected from three different groups of individuals will be used - crack users, former crack users and control, totaling 90 samples. For the extraction of viral genetic material, quantitative PCR will be performed. Data will be entered into tables in Excel version 2016 and submitted to statistical analysis using Student's t test (if parametric) or Mann-Whitney test (if non-parametric) in SPSS® (version 20), MiniTab® ( version 16). Associations between variables and clinical data will be explored using Spearman's correlation coefficient.