Evaluation of aMMP-8 and IL-1β Levels and Marginal Bone Loss Associated With Peri-Implant Mucositis and Peri-Implantitis in Postmenopausal Women

Peri-implant mucositis and peri-implantitis are among the major biological complications threatening the long-term success of dental implants. Current diagnostic approaches are primarily based on clinical and radiographic assessments; however, there is still a need for reliable biomarkers that can detect biological alterations before extensive tissue destruction occurs. Hormonal changes associated with the postmenopausal period may influence bone metabolism and inflammatory responses, thereby increasing the susceptibility of peri-implant tissues to disease. Nevertheless, studies investigating local inflammatory biomarkers in peri-implant diseases among postmenopausal women remain limited. Active matrix metalloproteinase-8 (aMMP-8) is a key enzyme involved in collagen degradation and connective tissue destruction and is considered one of the most important biomarkers of periodontal and peri-implant tissue breakdown. Interleukin-1 beta (IL-1β) is a potent pro-inflammatory cytokine associated with inflammatory responses, bone resorption, and tissue destruction. Assessment of these biomarkers in peri-implant crevicular fluid may contribute to the early diagnosis and risk assessment of peri-implant diseases. The aim of this project is to evaluate the association between peri-implant health, peri-implant mucositis, peri-implantitis, and peri-implant crevicular fluid levels of aMMP-8 and IL-1β in postmenopausal women, together with clinical and radiographic parameters. Postmenopausal women with at least one functional dental implant will be recruited and classified into three groups according to their peri-implant status. Clinical peri-implant parameters will be recorded, standardized radiographic examinations will be performed, and peri-implant crevicular fluid samples will be collected using the PerioPaper method. Levels of aMMP-8 and IL-1β will be quantified using enzyme-linked immunosorbent assay (ELISA). The obtained data will be analyzed using advanced statistical