Plasmatic free light chains as inflammatory marker in insulin resistance: comparison of metabolic syndrome with adult growth hormone deficiency.
Umberto BasileCarmine BrunoCecilia NapodanoEdoardo VerganiKrizia PocinoAlessandro BrunettiFrancesca GulliStefano Angelo SantiniAntonio ManciniPublished in: BioFactors (Oxford, England) (2018)
Biological functions of immunoglobulin-free light chains (FLCs), other than in chronic inflammatory diseases, are still poorly defined; the field of insulin resistance (IR) has not been investigated, despite the strict relationships with oxidative stress (OS) and inflammation. Therefore, we evaluated FLCs levels and their relationships with metabolic parameters in adult growth hormone deficiency (GHD) and metabolic syndrome (MetS), both characterized by IR. One hundred subjects were enrolled: group A, patients with GHD [n =31, 24-69 years, mean ± SEM body mass index (BMI) 26.8 ± 1.5 kg/m2 ]; group B, patients with MetS (n = 29, 21-70 years, BMI 31.9 ± 1.3); group C, controls (N = 40, 21-62 years, BMI 21.6 ± 1.1). Groups were matched by age range and, for patients, by BMI. Morning blood sample was collected for metabolic parameters and FLCs, assessed by turbidimetric assay. GHD patients show levels of FLCs significantly higher than MetS and controls (mean ± SEM κ 37.21 ± 6.97, 15.27 ± 0.86, 12.34 ± 0.85 mg/l; λ 19.44 ± 2.61, 11.78 ± 0.72 and 11.67 ± 0.77 mg/l; κ/λ ratio 1.77 ± 0.13, 1.38 ± 0.09; and 1.10 ± 0.06, respectively); only κ were higher in MetS versus controls. Therefore, the ratio showed progressive declining values in GHD versus MetS versus controls. Our data show increased FLCs levels in GHD and MetS, with the highest values in the former. Both conditions show OS, but with different molecular patterns. FLCs may contribute to chronic inflammation, leading to OS, and cardiovascular complications of GHD. Prognostic and therapeutic implications require further investigation. © 2018 BioFactors, 44(5):480-484, 2018.
Keyphrases
- body mass index
- oxidative stress
- metabolic syndrome
- insulin resistance
- growth hormone
- end stage renal disease
- ejection fraction
- newly diagnosed
- weight gain
- type diabetes
- prognostic factors
- multiple sclerosis
- peritoneal dialysis
- high fat diet
- risk factors
- cardiovascular disease
- dna damage
- physical activity
- mass spectrometry
- electronic health record
- deep learning
- replacement therapy
- artificial intelligence
- induced apoptosis