Genetic and epidemiological study of hip and knee osteoarthritis

• Grant number: 18/05404-6
• Support Opportunities: Scholarships in Brazil - Master
• Start date: April 01, 2018
• End date: March 31, 2020
• Field of knowledge: Health Sciences - Collective Health - Epidemiology
• Principal Investigator: Martha Cecilia Castano Betancourt
• Grantee: Caroline Larissa Morais
• Host Institution: Faculdade de Medicina de Jundiaí (FMJ). Prefeitura Municipal de Jundiaí. Jundiaí , SP, Brazil
• Associated research grant: 16/21039-0 - Genetic and epidemiological study of hip and knee osteoarthritis, AP.JP

Abstract

Osteoarthritis (OA) is the most frequently chronic joint disease worldwide and it is the most prevalent rheumatic disease in Brazil. Till date the only available and effective treatment is joint replacement. In the last years, metabolic traits (diabetes, BMI, and cholesterol, among others) and genetic variants have emerged as important risk factors for OA. Despite progress in genetics study of the disease: 16 polymorphisms have been found associated (6 of my research), discovery only account for 10% of the genetic component of OA. Our study aims to identify genetic and metabolic causes of OA in the Brazilian population. Methods: We collected data from 700 patients older than 35 years old with admissions for joint complaints and diagnoses of hip and/or knee OA in Hospital Sao Vicente de Jundiaí. Data from medical records included history of diabetes, cholesterol, comorbidities, laboratory exams and medication. Interview includes assessment of pain, disability and BMI, between others. Blood samples from patients with family history of OA (at least two affected siblings with clinical- hip and/or knee OA) were0 collected. Additional siblings and living parents from qualifying families, both affected and unaffected, will be invited to participate. DNA will be extracted and samples will be sent for exome sequencing and parametric linkage (within the families). Mutations (common, rare and low frequency variants) and will be analysed using PLINK. Linkage analysis will be developed under a parametric model using Merlin. Epidemiological and genetic association will be verified with generalized linear model, pedigree analysis, multiple- and logistic-regression for continuous and dichotomous variables. Replication efforts might be carried out in the CPMC Research Institute from the University of California (UCSF) and Genetics Laboratory from Eramus Universiteit (Holanda). (AU)