Campos, Julliane Tamara Araújo de MeloSilva, Monique Alvares da2022-03-042022-03-042022-02-14SILVA, Monique Alvares da. O gene LMNA como precursor da Síndrome de Dunnigan: uma análise molecular e de bioinformática. 2022. 60 f. Monografia (Graduação em Biomedicina) – Universidade Federal do Rio Grande do Norte, Natal, 2022.https://repositorio.ufrn.br/handle/123456789/46401The partial or generalized lack of adipose tissue results in lipodystrophies, a group of rare diseases with about 2.84 cases/million people worldwide. Among the existing types, familial partial lipodystrophy (FPLD) has the more challenging diagnosis for the similarity with metabolic comorbidities, such as type 2 diabetes mellitus, dyslipidemia, cardiovascular diseases or metabolic syndromes. Eight FPLD subtypes have been reported, with several related genes, including LMNA and PPARG. Dunnigan's syndrome, also known as type 2 FPLD, has a molecular etiology associated with predominantly missense variants of the LMNA gene on chromosome 1. Patients may present early insulin resistance, hypertriglyceridemia, low levels of high-density lipoprotein cholesterol (HDL), hepatic steatosis, and an increased risk of cardiovascular disease. The present work aims to review the LMNA mutations that can result in Dunnigan syndrome and develop primers for performing conventional PCR (polymerase chain reaction). Thirteen variants were selected for the LMNA review, of which 6 were selected for their prevalence and for being found in Brazilians. The simulations in bioinformatics-2 important that PolyPhen was the most reliable tool with what was observed in the literature – the deleterious and harmful characteristic of both versions. With the analysis of the STRING tool, it was possible to confirm in simulation the relationship between responses and other proteins responsible for repair to cell repair, cell difference between fat and stress. Three pairs of PCR primers were designed and validated that allow the genetic characterization of the syndrome in the state of Rio Grande do Norte, Brazil.tecido adiposolipodistrofia parcialbiologia molecularbioinformáticaadipose tissuepartial lipodystrophymolecular biologybioinformaticsbachelorThesis