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Biological variation in HbA1c predicts risk of retinopathy and nephropathy in type 1 diabetes
Robert J McCarter1, James M Hempe, Ricardo Gomez
1Endocrinology/Diabetes, Children's Hospital of New Orleans, 200 Henry Clay Avenue, New Orleans, LA 70118, USA.
Insights
Biological variation in hemoglobin A1c (HbA1c), independent of mean blood glucose, predicts microvascular complications in type 1 diabetes. This finding could lead to new therapies for preventing diabetes complications.
Area of Science:
- Endocrinology
- Metabolic Diseases
- Diabetology
Background:
- Hemoglobin A1c (HbA1c) is a key marker for glycemic control in diabetes.
- Biological variation in HbA1c, beyond mean blood glucose (MBG), may influence complication risk.
Purpose of the Study:
- To investigate if biological variation in HbA1c predicts microvascular complications in type 1 diabetes.
- To determine if HbA1c variability, independent of MBG, is associated with retinopathy and nephropathy risk.
Main Methods:
- Developed a longitudinal regression model using MBG and HbA1c from 1,441 participants in the Diabetes Control and Complications Trial (DCCT).
- Calculated a hemoglobin glycation index (HGI) to quantify biological variation in HbA1c.
- Used Cox proportional hazard analysis to compare complication risks between HGI groups.
Main Results:
- HbA1c levels were not solely determined by MBG, indicating significant biological variation.
- High-HGI individuals (higher-than-predicted HbA1c) had a threefold increased risk of retinopathy.
- High-HGI individuals had a sixfold increased risk of nephropathy compared to low-HGI individuals.
Conclusions:
- Biological variation in HbA1c is a significant predictor of microvascular complications in type 1 diabetes.
- Understanding the mechanisms behind HbA1c variability may reveal novel therapeutic targets.
- These findings suggest potential for new treatments beyond glucose-lowering strategies.
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.
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