Exploring C-peptide loss in type 1 diabetes using growth curve analysis

Area of Science:

• Endocrinology
• Metabolic Diseases
• Diabetes Research

Background:

• C-peptide (CP) loss in type 1 diabetes (T1D) exhibits significant inter-individual variability.
• Factors influencing the rate and pattern of CP loss remain incompletely understood.
• Understanding CP dynamics is crucial for predicting disease progression and tailoring therapies.

Purpose of the Study:

• To model C-peptide (CP) values in type 1 diabetes (T1D) patients over time using growth curve analysis.
• To characterize individual patterns of CP loss post-diagnosis.
• To identify baseline patient characteristics that predict individual CP loss trajectories.

Main Methods:

• Utilized the SITAR (SuperImposition by Translation And Rotation) mixed-effects growth curve model to analyze serial CP measurements (AUC) from 442 T1D patients.
• Data included 120-minute mixed meal tolerance tests (MMTT) at multiple time points up to 6 years post-diagnosis.
• Analyzed CP area under the curve (AUC) on a square root scale for optimal model fit.

Main Results:

• The SITAR model effectively captured individual CP loss patterns, distinguishing between mean CP levels and rates of fall.
• Younger age at diagnosis and higher 3-month CP levels were significant predictors of faster CP decline.
• Patient-specific mean CP levels and rates of fall were normally distributed and uncorrelated.

Conclusions:

• SITAR growth curve analysis provides a robust framework for assessing CP loss in T1D, explaining patient variability.
• Defining rapid CP loss based on the rate of fall distribution can facilitate patient stratification.
• This approach can enhance understanding of factors driving CP loss and inform targeted therapeutic strategies in T1D.