Genetic variants in the receptor for advanced glycation end products (RAGE) gene were associated with circulating soluble RAGE level but not with renal function among Asians with type 2 diabetes: a genome-wide association study.

BACKGROUND: The soluble receptor for advanced glycation end products (sRAGE) has been shown to play an important role in diabetic complications. We conducted genome-wide association study (GWAS) of sRAGE in Asian type 2 diabetes mellitus (T2DM) patient and validated the association in an independent cohort of T2DM. METHODS: GWAS for sRAGE was performed in 2058 T2DM patients. Associations between single-nucleotide polymorphisms (SNPs) and plasma sRAGE level were analyzed in an additive model using a linear mixed model. To validate the associations, we performed de novo genotyping in an independent cohort (n = 1984). We selected the top SNP for assessment with diabetic kidney disease (DKD). RESULTS: The strongest SNP, rs2070600C>T (P = 1.21 × 10-52), was a genotyped, missense SNP located on chromosome 6, corresponding to the RAGE (AGER) gene locus, the gene encoding RAGE. Conditioning analysis on rs2070600 revealed that rs2071288C>T was the top genotyped independent SNP (P = 8.36 × 10-10). Both SNPs were strongly and dose-dependently correlated with sRAGE level (TT = 399.6 pg/mL, CT = 737.0 pg/mL and CC = 967.0 pg/mL, P < 0.001 for rs2070600; TT = 687.9 pg/mL, CT = 737.6 pg/mL and CC = 904.7 pg/mL, P < 0.001 for rs2072188). Both SNPs were robustly replicated in the independent cohort, especially among Chinese patients (P = 9.02 × 10-72 for rs2070600; P = 1.13 × 10-9 for rs2071288). Log-transformed sRAGE was associated with DKD after adjustment for age, gender and ethnicity in pooled cohorts [odds ratio 2.536 (95% confidence interval 1.864-3.450), P < 0.001]. However, we did not observe any significant association between rs2070600 and DKD. CONCLUSIONS: Common variants in RAGE are strongly associated with plasma sRAGE level, which is associated with DKD. However, we did not find a causal link between sRAGE and renal function by Mendelian randomization.

Urinary Haptoglobin Predicts Rapid Renal Function Decline in Asians With Type 2 Diabetes and Early Kidney Disease.

CONTEXT: A recent study suggested that urinary haptoglobin may be a novel biomarker to improve predictive performance of albuminuria in type 2 diabetes mellitus (T2DM). However, the finding has not been externally validated. OBJECTIVE: The objective of the study was to evaluate whether urinary haptoglobin improves predictive performance of albuminuria in Asian T2DM with an estimated glomerular filtration rate (eGFR) of 30 mL/min per 1.73 m2 or greater. DESIGN AND PARTICIPANTS: This was a prospective study with 269 T2DM nonprogressors (eGFR changes 0.2 [-0.7 to 1.0] mL/min per 1.73 m2 per y) and 153 T2DM progressors (eGFR decline -7.1 [-10.6 to -5.1] mL/min per 1.73 m2 per y) included. MAIN OUTCOME: The main outcome was an eGFR decline of 3 mL/min per 1.73 m2 or greater per year by trajectory slope. RESULTS: Urinary haptoglobin level increased 11-fold in progressors as compared with nonprogressors at baseline. In comparison with subjects in the lowest quartile, those with haptoglobin in the third and fourth quartiles had 2.25- (1.11-4.59) and 5.41 (2.63-11.1)-fold increased odds for renal progression, whereas those with an albuminuria level in the third and fourth quartiles had 2.53- (1.17-5.51) and 9.01 (4.00-20.5)-fold increased odds. Notably, urinary haptoglobin predicted renal progression independent of albuminuria. Addition of haptoglobin significantly improved the predictive performance of albuminuria beyond traditional risk factors as reflected by a significant increase in the net reclassification index and integrated discrimination index. In the chronic kidney disease stage 3 subpopulation, urinary haptoglobin outperformed albuminuria for the prediction of rapid renal function decline. CONCLUSIONS: Our data confirmed that urinary haptoglobin may improve the predictive performance of albuminuria for renal progression in Asians with T2DM. Moreover, it may potentially outperform albuminuria for the prediction of rapid renal function decline in the T2DM chronic kidney disease stage 3 subpopulation.

Association of plasma soluble α-klotho with pro-endothelin-1 in patients with type 2 diabetes.

OBJECTIVES: To study the relationship between plasma soluble klotho (sKlotho) and pro-endothelin-1 (proET-1) in patients with type 2 diabetes (T2DM). SUBJECTS AND METHODS: In this cross-sectional study, we recruited 175 T2DM subjects and 56 non-diabetic controls. Plasma sKlotho, proET-1 and extracellular superoxide dismutase (SOD) were measured by ELISA and ILMA, respectively. RESULTS: Plasma sKlotho level in patients with T2DM was lower compared to that in non-diabetic controls (416.8±148.1 vs. 494.6±134.3 pg/ml, p=0.001) and showed significant interaction with diabetes status in its association with proET-1. Plasma sKlotho was inversely correlated with proET-1 in T2DM (Rho=-0.410, p<0.0001) but not in non-diabetic controls (Rho=0.091, p=0.505). Multivariable linear regression models revealed that sKlotho was independently associated with proET-1 after adjustment for renal filtration function, albuminuria, diabetes duration, HbA1c, systolic and diastolic blood pressure. CONCLUSIONS: Plasma sKlotho was associated with proET-1 independent of renal function in patients with T2DM.

Relationship between circulating irisin, renal function and body composition in type 2 diabetes.

AIMS: Chronic kidney disease (CKD) secondary to type 2 diabetes mellitus (T2DM) is associated with multifaceted energy dysmetabolism. We aim to study the relationship between renal function, body composition and irisin, the recently identified myokine which is involved in energy regulation, in T2DM. METHODS: Circulating irisin and body composition were measured in 365 T2DM subjects across a wide range of renal function. RESULTS: Circulating irisin was significantly decreased in T2DM with renal insufficiency (77.4 ± 13.7 ng/ml in T2DM with eGFR ≥ 60 ml/min/1.73 m(2) versus 72.5 ± 14.9 ng/ml in those with eGFR<60 ml/min/1.73 m(2), p = 0.001) and the reduction in irisin was most pronounced in stage 5 CKD patients. In T2DM with preserved renal function, irisin was correlated with age (r = -0.242, p = 0.001) and pulse pressure (r = -0.188, p = 0.002). Among those with renal insufficiency, irisin was correlated with BMI (r = 0.171, p = 0.022), fat mass (r = 0.191, p = 0.013), percentage of fat mass (r = 0.210, p = 0.007) and eGFR (r = 0.171, p = 0.020). Multivariate linear regression models revealed that variations in circulating irisin were mainly attributable to eGFR and age in T2DM with and without renal impairment, respectively. CONCLUSION: Our observations suggest that the level of circulating irisin may be associated with renal function in T2DM. The role of reduced irisin in energy dysmetabolism in diabetic patients with renal insufficiency deserves further investigation.

Lower circulating irisin is associated with type 2 diabetes mellitus.

AIMS: Irisin is a novel myokine secreted in response to PPAR-γ co-activator-1α (PGC-1α) activation. Earlier studies suggested that PGC-1α expression and activity were lower in myocytes in type 2 diabetes mellitus (T2DM). Therefore, we hypothesize that circulating irisin levels are lower in T2DM patients. METHODS: In this observational study, we recruited 96 T2DM subjects and 60 non-diabetic control subjects. Among T2DM subjects, 38% were on insulin treatment, 78% were taking statins and 72% were taking renin-angiotensin system antagonists. Circulating irisin was quantified by ELISA and its association with markers of metabolic phenotype was analyzed by Pearson bivariate correlation and multiple linear regression. RESULTS: Circulating irisin was significantly lower in individuals with T2DM compared with non-diabetic controls (T2DM 204 ± 72 ng/ml vs. non-diabetic control 257 ± 24 ng/ml, p < 0.0001). In non-diabetic subjects, circulating irisin was correlated with age (r = 0.398, p < 0.01), BMI (r = 0.387, p < 0.01), total cholesterol (r = 0.341, p < 0.01), total triglycerides (r = 0.299, p < 0.05), fasting blood glucose (r = 0.430, p < 0.01) and diastolic blood pressure (r = 0.306, p < 0.05). Multiple linear regression model revealed that BMI (ß = 0.407, p = 0.012) and FBG (ß = 0.315, p = 0.034) were associated with irisin in non-diabetic subjects after adjusting for multiple co-variates. However, similar analysis in T2DM subjects didn't reveal significant association between circulating irisin and major markers of metabolic phenotype. CONCLUSIONS: Circulating irisin is lower in T2DM compared with non-diabetic controls. Plasma irisin levels appear to be associated with important metabolic factors in non-diabetic subjects but not in individuals with type 2 diabetes.