OBJECTIVE: We hypothesized that biological variation in HbA(1c), distinct from variation attributable to mean blood glucose (MBG), would predict risk for microvascular complications in the Diabetes Control and Complications Trial (DCCT). RESEARCH DESIGN AND METHODS: A longitudinal multiple regression model was developed from MBG and HbA(1c) measured in the 1,441 DCCT participants at quarterly visits. A hemoglobin glycation index (HGI = observed HbA(1c) - predicted HbA(1c)) was calculated for each visit to assess biological variation based on the directional deviation of observed HbA(1c) from that predicted by MBG in the model. The population was subdivided by thirds into high-, moderate-, and low-HGI groups based on mean participant HGI during the study. Cox proportional hazard analysis compared risk for development or progression of retinopathy and nephropathy between HGI groups controlled for MBG, age, treatment group, strata, and duration of diabetes. RESULTS: Likelihood ratio and t tests on HGI rejected the assumption that HbA(1c) levels were determined by MBG alone. At 7 years' follow-up, patients in the high-HGI group (higher-than-predicted HbA(1c)) had three times greater risk of retinopathy (30 vs. 9%, P < 0.001) and six times greater risk of nephropathy (6 vs. 1%, P < 0.001) compared with the low-HGI group. CONCLUSIONS: Between-individual biological variation in HbA(1c), which is distinct from that attributable to MBG, was evident among type 1 diabetic patients in the DCCT and was a strong predictor of risk for diabetes complications. Identification of the processes responsible for biological variation in HbA(1c) could lead to novel therapies to augment treatments directed at lowering blood glucose levels and preventing diabetes complications.
OBJECTIVE: We hypothesized that biological variation in HbA(1c), distinct from variation attributable to mean blood glucose (MBG), would predict risk for microvascular complications in the Diabetes Control and Complications Trial (DCCT). RESEARCH DESIGN AND METHODS: A longitudinal multiple regression model was developed from MBG and HbA(1c) measured in the 1,441 DCCTparticipants at quarterly visits. A hemoglobin glycation index (HGI = observed HbA(1c) - predicted HbA(1c)) was calculated for each visit to assess biological variation based on the directional deviation of observed HbA(1c) from that predicted by MBG in the model. The population was subdivided by thirds into high-, moderate-, and low-HGI groups based on mean participant HGI during the study. Cox proportional hazard analysis compared risk for development or progression of retinopathy and nephropathy between HGI groups controlled for MBG, age, treatment group, strata, and duration of diabetes. RESULTS: Likelihood ratio and t tests on HGI rejected the assumption that HbA(1c) levels were determined by MBG alone. At 7 years' follow-up, patients in the high-HGI group (higher-than-predicted HbA(1c)) had three times greater risk of retinopathy (30 vs. 9%, P < 0.001) and six times greater risk of nephropathy (6 vs. 1%, P < 0.001) compared with the low-HGI group. CONCLUSIONS: Between-individual biological variation in HbA(1c), which is distinct from that attributable to MBG, was evident among type 1 diabeticpatients in the DCCT and was a strong predictor of risk for diabetes complications. Identification of the processes responsible for biological variation in HbA(1c) could lead to novel therapies to augment treatments directed at lowering blood glucose levels and preventing diabetes complications.
Authors: Byoung Geun Han; Chuan-Ming Hao; Elena E Tchekneva; Ying-Ying Wang; Chieh Allen Lee; Benyamin Ebrahim; Raymond C Harris; Timothy S Kern; David H Wasserman; Matthew D Breyer; Zhonghua Qi Journal: Am J Physiol Endocrinol Metab Date: 2008-07-29 Impact factor: 4.310