Serum spexin in first-degree relatives of patients with type 2 diabetes

Background and aims: Genetic defects significantly contribute to diabetes development, especially in genetically predisposed individuals. First-degree relatives (FDRs) of type 2 diabetes (T2D) patients face an increased risk of developing diabetes. Spexin, a novel neuropeptide, is emerging as a key player in metabolic diseases due to its role in energy homeostasis. This study aims to evaluate, for the first time, serum spexin levels in normoglycemic FDRs of T2D patients, compared to T2D and healthy controls. It also investigates the relationship between spexin levels, insulin resistance, and metabolic parameters. Methods: Ninety participants were included: 30 with T2D, 35 normoglycemic FDRs of T2D patients, and 25 healthy controls. Serum spexin levels were measured using ELISA, along with and glycemic parameters, lipid profiles, and insulin resistance markers. Results: Spexin levels were significantly lower in FDRs compared to controls and even lower in T2D patients, indicating a progressive decline from healthy individuals to those with T2D. Spexin levels negatively correlated with BMI, triglycerides, total cholesterol, LDL-C, fasting blood glucose, insulin, HbA1c, and HOMA-IR, but positively correlated with HDL-C. Conclusion: Lower spexin levels in FDRs of T2D patients may be associated with a higher risk of developing T2D. Spexin levels showed statistically significant negative correlations with key metabolic and cardiovascular risk factors, including BMI (r=-0.302), triglycerides (r=-0.464), total cholesterol (r=-0.524), fasting insulin (r=-0.703), and HOMA-IR (r=-0.565), suggesting that reduced spexin may reflect or contribute to worsening metabolic health and insulin resistance. Monitoring spexin could be useful for identifying individuals at higher risk for T2D and related metabolic disorders. (c) 2025 Sociedad Espanola de Me<acute accent>dicos de Atencio<acute accent>n Primaria (SEMERGEN). Published by Elsevier Espana, S.L.U. All rights are reserved, including those for text and data mining, AI training, and similar technologies.