A E Pontiroli1, L D Monti, A Pizzini, P Piatti. 1. Università degli Studi di Milano, Cattedra di Medicina Interna, and the Istituto Scientifico San Raffaele, Unità de Malattie Metaboliche, Milan, Italy. antonio.pontiroli@unimi.it
Abstract
OBJECTIVE: To test the hypothesis that selected abnormalities cluster in type 2 diabetic families. Offspring of patients with type 2 diabetes have a 40-60% chance of developing type 2 diabetes and an increased frequency of impaired glucose tolerance (IGT) or unknown diabetes. These offspring also show metabolic abnormalities of type 2 diabetes, such as insulin resistance, high insulin and pro-insulin, low HDL cholesterol levels, arterial hypertension, and microalbuminuria. RESEARCH DESIGN AND METHODS: We studied 87 families including at least one type 2 diabetic patient, i.e., 87 probands and 146 siblings; 60 spouses of probands with no family history of diabetes were compared with siblings. Familial clustering was evaluated by 2 methods: concordance of siblings and probands for a given abnormality (method 1) and intraclass correlation coefficients of values within each family (method 2). RESULTS: At oral glucose tolerance testing, 24 siblings had type 2 diabetes, 31 siblings had IGT, and 14 spouses had IGT (P = 0.0012 vs. siblings). With method 1, familial clustering occurred for microalbuminuria, insulin resistance, arterial hypertension, HDL cholesterol and pro-insulin levels; with method 2, familial clustering was observed for the same variables except for microalbuminuria. With both method 1 and 2, familial clustering for insulin resistance disappeared, whereas familial clustering for arterial blood pressure, HDL cholesterol, and pro-insulin remained after correction for BMI; after further restriction of analysis to probands and to siblings with normal glucose tolerance, familial clustering for pro-insulin was observed only with method 2. CONCLUSIONS: These data indicate that siblings of diabetic patients are at high risk for selected features of type 2 diabetes.
OBJECTIVE: To test the hypothesis that selected abnormalities cluster in type 2 diabetic families. Offspring of patients with type 2 diabetes have a 40-60% chance of developing type 2 diabetes and an increased frequency of impaired glucose tolerance (IGT) or unknown diabetes. These offspring also show metabolic abnormalities of type 2 diabetes, such as insulin resistance, high insulin and pro-insulin, low HDL cholesterol levels, arterial hypertension, and microalbuminuria. RESEARCH DESIGN AND METHODS: We studied 87 families including at least one type 2 diabeticpatient, i.e., 87 probands and 146 siblings; 60 spouses of probands with no family history of diabetes were compared with siblings. Familial clustering was evaluated by 2 methods: concordance of siblings and probands for a given abnormality (method 1) and intraclass correlation coefficients of values within each family (method 2). RESULTS: At oral glucose tolerance testing, 24 siblings had type 2 diabetes, 31 siblings had IGT, and 14 spouses had IGT (P = 0.0012 vs. siblings). With method 1, familial clustering occurred for microalbuminuria, insulin resistance, arterial hypertension, HDL cholesterol and pro-insulin levels; with method 2, familial clustering was observed for the same variables except for microalbuminuria. With both method 1 and 2, familial clustering for insulin resistance disappeared, whereas familial clustering for arterial blood pressure, HDL cholesterol, and pro-insulin remained after correction for BMI; after further restriction of analysis to probands and to siblings with normal glucose tolerance, familial clustering for pro-insulin was observed only with method 2. CONCLUSIONS: These data indicate that siblings of diabeticpatients are at high risk for selected features of type 2 diabetes.
Authors: Nedal H Arar; Venkata S Voruganti; Subrata D Nath; Farook Thameem; Richard Bauer; Shelley A Cole; John Blangero; Jean W MacCluer; Anthony G Comuzzie; Hanna E Abboud Journal: Nephrol Dial Transplant Date: 2008-04-28 Impact factor: 5.992
Authors: Richard S Legro; Rhonda Bentley-Lewis; Deborah Driscoll; Steve C Wang; Andrea Dunaif Journal: J Clin Endocrinol Metab Date: 2002-05 Impact factor: 5.958