Objectives: The learning outcomes of the presentation will focus on the latest advancements in understanding and managing lipoedema. Participants will gain insights into the pathophysiology, diagnosis, and treatment options available, including surgical and non-surgical approaches. The session will also highlight the importance of early diagnosis and the role of multidisciplinary care in improving patient quality of life. Attendees will learn about ongoing research trends and the impact of patient education on treatment outcomes, equipping them with updated knowledge to enhance their clinical practice.

Objectives: - Understand the role of specific genetic markers, such as FTO, MCM6, and MC4R, in influencing BMI and weight loss outcomes.
- Explore the genetic factors that predict responses to dietary, endoscopic, and surgical weight loss interventions.
- Highlight the potential of genetic profiling in designing personalised strategies for improved health and aesthetic results, advancing the application of precision medicine in obesity management.

Introduction: Obesity, a multifactorial condition, presents significant challenges to health and aesthetics. Genetic factors are increasingly recognised for their role in influencing obesity risk and treatment outcomes. This study examines the impact of genetic profiling using a panel of single nucleotide polymorphisms (SNPs) to predict Body Mass Index (BMI) and weight loss responses across various interventions. The findings aim to advance personalised strategies that enhance health outcomes and aesthetic satisfaction.

Materials / method: A cohort of 9,372 patients was assessed for correlations between genetic markers and BMI, while 474 patients were evaluated for their response to weight loss interventions, including dietary plans, intragastric balloon procedures, and bariatric surgery. Key SNPs, such as rs9939609 (FTO), rs4988235 (MCM6), and rs2016520 (PPAR-Delta), were analysed for their impact on weight loss efficacy across treatments.

Results: SNPs like rs9939609 (FTO) and rs4988235 (MCM6) were strongly associated with higher BMI. Weight loss outcomes were significantly influenced by SNPs, with rs6544713 (ABCG8) correlating with dietary success, and MC4R-related SNPs predicting outcomes for surgical and endoscopic procedures. Personalised treatment plans based on genetic profiles demonstrated improved weight loss efficacy and enhanced patient satisfaction with aesthetic outcomes.

Conclusion: Genetic profiling reveals critical insights into obesity risk and weight loss responses, enabling the design of personalised interventions. By integrating genetic data into clinical practice, practitioners can optimise health outcomes and aesthetic satisfaction, marking a significant advancement in precision medicine for weight loss management.