title: Evaluation of metabolic risk marker in obesity-related glomerulopathy.
abstract: OBJECTIVE
  Insulin resistance is a common metabolic abnormality, which increases the risk of renal events in obesity. The present study is aimed to examine the relation between metabolic factors and obesity-related glomerulopathy (ORG), and then compare the risk markers of insulin resistance for clinical prediction.
  
  
  METHODS
  A total of 112 cases with proven renal ORG and 135 age- and gender-matched lean controls were included. The degree of proteinuria, endogenous creatinine clearance rate, body mass index, amylin, fasting glucose, insulin, lipid and lipoprotein concentrations were measured during the steady state.
  
  
  RESULTS
  The patients with ORG were clinically characterized by increased body mass index and proteinuria, with higher levels of amylin, homeostasis model assessment of insulin resistance (HOMA-IR), insulin, glucose, and lipid proteins when compared with the lean controls. Multiple logistic regression analysis revealed that amylin and HOMA-IR were significantly associated with the prevalence of ORG. In patients with ORG, proteinuria level correlated with amylin, total cholesterol, fasting insulin, and HOMA-IR. Moreover, proteinuria correlated positively with HOMA-IR and amylin in a multiple regression analysis. In addition, the endogenous creatinine clearance rate did not correlate with any metabolic marker.
  
  
  CONCLUSIONS
  This study suggested that screening for HOMA-IR might have predictive value for renal damage in obese patients. In addition to insulin resistance, amylin also showed positive effects on evaluation of such renal impairment.
authors.affiliation: Research Institute of Nephrology, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210002, People's Republic of China.
authors.forename: Hui-Mei
authors.initials: HM
authors.lastname: Chen
authors.forename: Yan
authors.initials: Y
authors.lastname: Chen
authors.forename: Yi-De
authors.initials: YD
authors.lastname: Zhang
authors.forename: Pei-Pei
authors.initials: PP
authors.lastname: Zhang
authors.forename: Hui-Ping
authors.initials: HP
authors.lastname: Chen
authors.forename: Qing-Wen
authors.initials: QW
authors.lastname: Wang
authors.forename: Lei-Shi
authors.initials: LS
authors.lastname: Li
authors.forename: Zhi-Hong
authors.initials: ZH
authors.lastname: Liu
mesh_terms: D000328:Adult; D015415:Biomarkers; D001786:Blood Glucose / Q000032:analysis; D001823:Body Composition; D015992:Body Mass Index; D003430:Cross-Sectional Studies; D005260:Female; D006706:Homeostasis; D006801:Humans; D007328:Insulin / Q000097:blood; D007333:Insulin Resistance; D058228:Islet Amyloid Polypeptide / Q000097:blood; D007674:Kidney Diseases / Q000150:complications / Q000473:pathology*; D016014:Linear Models; D016015:Logistic Models; D008297:Male; D024821:Metabolic Syndrome / Q000150:complications / Q000473:pathology*; D008875:Middle Aged; D015999:Multivariate Analysis; D009765:Obesity / Q000150:complications / Q000473:pathology*; D011507:Proteinuria / Q000150:complications / Q000473:pathology; D012189:Retrospective Studies; D012307:Risk Factors
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D007328:Insulin; D058228:Islet Amyloid Polypeptide