BACKGROUND: Adiponectin, an anti-inflammatory and insulin-sensitizing cytokine, has been shown to reduce proteinuria and glomerulosclerosis in experimental models. We assessed the relationship of plasma adiponectin to the progression of kidney disease in type 2 diabetes (T2D) patients. METHODS: T2D nonnephrotic patients with glomerular filtration rate (GFR) >30 ml/min and without acute cardiovascular/inflammatory conditions were included. Laboratory standard evaluation, urinary albumin/creatinine ratio (UACR), total plasma adiponectin, and CRP (C-reactive protein) were determined at inclusion and the end of study. RESULTS: Eighty-six patients (62.79% male) were followed up for 20.53±5.46 months. Baseline GFR was 72.85±26.29 ml/min and UACR was 20.53 (interquartile range 6.82-86.39) mg/g. At baseline adiponectin was significantly correlated to UACR (r =0.40, p =0.0001), HDL cholesterol (r =0.30, p =0.005), GFR (r =- 0.23, P =0.04), body mass index (BMI) (r =- 0.26, P =0.02) and waist circumference (r =-0.27, p =0.01). In multiple regression UACR (p =0.0003) and BMI (p =0.03) were significantly related to baseline adiponectin. The progression of kidney disease was estimated as the difference (D) between end and baseline UACR/month and between end and baseline GFR/month. None of the baseline parameters correlated to ΔGFR, but adiponectin inversely (r =- 0.26, p =0.02) correlated to ΔUACR. In multiple regression only adiponectin (p <0.0001) predicted ΔUACR. A computed progression index (PI) resulting from a linear combination of GFR and UACR was also used to assess progression. Baseline adiponectin was significantly correlated to ΔPI between end of study and baseline (r =- 0.43, p <0.0001), and predicted ΔPI in multiple regression (p =0.009). CONCLUSION: Low plasma adiponectin predicts progression of kidney disease in T2D patients.
BACKGROUND:Adiponectin, an anti-inflammatory and insulin-sensitizing cytokine, has been shown to reduce proteinuria and glomerulosclerosis in experimental models. We assessed the relationship of plasma adiponectin to the progression of kidney disease in type 2 diabetes (T2D) patients. METHODS:T2D nonnephroticpatients with glomerular filtration rate (GFR) >30 ml/min and without acute cardiovascular/inflammatory conditions were included. Laboratory standard evaluation, urinary albumin/creatinine ratio (UACR), total plasma adiponectin, and CRP (C-reactive protein) were determined at inclusion and the end of study. RESULTS: Eighty-six patients (62.79% male) were followed up for 20.53±5.46 months. Baseline GFR was 72.85±26.29 ml/min and UACR was 20.53 (interquartile range 6.82-86.39) mg/g. At baseline adiponectin was significantly correlated to UACR (r =0.40, p =0.0001), HDL cholesterol (r =0.30, p =0.005), GFR (r =- 0.23, P =0.04), body mass index (BMI) (r =- 0.26, P =0.02) and waist circumference (r =-0.27, p =0.01). In multiple regression UACR (p =0.0003) and BMI (p =0.03) were significantly related to baseline adiponectin. The progression of kidney disease was estimated as the difference (D) between end and baseline UACR/month and between end and baseline GFR/month. None of the baseline parameters correlated to ΔGFR, but adiponectin inversely (r =- 0.26, p =0.02) correlated to ΔUACR. In multiple regression only adiponectin (p <0.0001) predicted ΔUACR. A computed progression index (PI) resulting from a linear combination of GFR and UACR was also used to assess progression. Baseline adiponectin was significantly correlated to ΔPI between end of study and baseline (r =- 0.43, p <0.0001), and predicted ΔPI in multiple regression (p =0.009). CONCLUSION: Low plasma adiponectin predicts progression of kidney disease in T2D patients.
Authors: Tomás P Griffin; William Patrick Martin; Nahidul Islam; Timothy O'Brien; Matthew D Griffin Journal: Curr Diab Rep Date: 2016-05 Impact factor: 4.810
Authors: A Mascali; O Franzese; S Nisticò; U Campia; D Lauro; C Cardillo; N Di Daniele; M Tesauro Journal: Int J Immunopathol Pharmacol Date: 2016-04-04 Impact factor: 3.219
Authors: Sonja Lindfors; Zydrune Polianskyte-Prause; Rim Bouslama; Eero Lehtonen; Miia Mannerla; Harry Nisen; Jukka Tienari; Hanne Salmenkari; Richard Forsgård; Tuomas Mirtti; Markku Lehto; Per-Henrik Groop; Sanna Lehtonen Journal: Diabetologia Date: 2021-05-14 Impact factor: 10.122