Leptin Is Associated with Testosterone, Nutritional Markers, and Vascular Muscular Dysfunction in Chronic Kidney Disease.
Crina Claudia RusuIna Maria KacsoDiana MoldovanAlina PotraDacian TirinescuMaria TicalaRemus OrasanCristian BudureaFlorin AntonAna ValeaCosmina Ioana BondorMara CarsotePublished in: International journal of molecular sciences (2024)
Chronic kidney disease (CKD) causes specific hormonal disturbances, such as variations in leptin and testosterone levels and function. These disturbances can promote errors in signaling interaction and cellular information processing and can be implicated in the pathogenesis of atherosclerosis. This study investigates the factors that affect leptin in CKD patients and examines how leptin is related to markers of vascular disease. We conducted a cross-sectional study of 162 patients with CKD in pre-dialysis and dialysis stages. We recorded clinical and laboratory data, including leptin, testosterone, and subclinical atherosclerosis markers like brachial-ankle pulse wave velocity (ba PWV) in pre-dialysis CKD patients and flow-mediated vasodilation (FMD) and nitroglycerin-mediated vasodilation (NMD) in hemodialysis (HD) patients. Leptin was significantly correlated with testosterone in CKD pre-dialysis stages ( p < 0.001) and also in HD ( p = 0.026), with adipose tissue mass in pre-dialysis stages ( p < 0.001), and also in HD ( p < 0.001). In women HD patients, leptin correlated with NMD ( p = 0.039; r = -0.379); in all HD patients, leptin correlated with C reactive protein ( p = 0.007; r = 0.28) and parathormone ( p = 0.039; r = -0.220). Our research emphasizes the connection between leptin, adipose tissue, and testosterone in all stages of CKD. Leptin was associated with NMD in HD women and correlated with inflammatory syndrome and parathyroid hormone in all HD patients.
Keyphrases
- end stage renal disease
- chronic kidney disease
- peritoneal dialysis
- adipose tissue
- newly diagnosed
- ejection fraction
- cardiovascular disease
- physical activity
- prognostic factors
- pregnant women
- blood pressure
- emergency department
- metabolic syndrome
- patient reported outcomes
- oxidative stress
- skeletal muscle
- machine learning
- deep learning
- electronic health record
- risk factors
- pregnancy outcomes
- big data
- patient safety
- health information