@article {10743, title = {A genome-wide association study identifies an association between variants in EFCAB4B gene and periodontal disease in an Italian isolated population.}, journal = {J Periodontal Res}, volume = {53}, year = {2018}, month = {2018 Dec}, pages = {992-998}, abstract = {

BACKGROUND AND OBJECTIVE: Periodontitis in one of the most prevalent dental diseases. Despite numerous studies have investigated its aetiopathogenetic factors, few works have focused on its genetic predisposition and most of them took into account only candidate genes. Therefore, we conducted a Genome Wide Association Study in an Italian isolated population aimed at uncovering genetic variants that predispose to this disorder.

METHODS: Diagnosis of chronic periodontitis was made following the criteria of the American Academy of Periodontology. Patients with chronic periodontitis were grouped into different categories: slight, severe, localized and generalized. A control group composed by people without signs of periodontitis or gingivitis was defined. DNA was genotyped using 370k Illumina chips. Linear mixed model regression was used to test the association between each single nucleotide polymorphism (SNP) (independent variable) and the periodontitis status (dependent variable), controlling for confounders sex, age and smoking. The genomic kinship matrix was also used as random effect.

RESULTS: Four SNPs on the gene EFCAB4B resulted significantly associated to localized periodontitis (P~<~5~{\texttimes}~10 ), with the best hit on the rs242016 SNP (P~=~1.5~{\texttimes}~10 ).

CONCLUSION: We have identified a novel significant association between the EFCAB4B gene and localized periodontitis. These results open a new perspective in the understanding of genetic factors contributing to this common disorder.

}, keywords = {Adolescent, Adult, Aged, Aged, 80 and over, Calcium-Binding Proteins, Chronic Periodontitis, DNA, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Italy, Male, Middle Aged, Polymorphism, Single Nucleotide, Regression Analysis, Young Adult}, issn = {1600-0765}, doi = {10.1111/jre.12598}, author = {Bevilacqua, Lorenzo and Navarra, Chiara O and Pirastu, Nicola and Lenarda, Roberto Di and Gasparini, Paolo and Robino, Antonietta} }