Genetics and Epigenetics in Health and Disease, University College London, Great Ormond Street Institute of Child Health, London, United Kingdom.
Department of Clinical and Experimental Medicine, Division of Pediatrics, Medical Faculty, Linköping University, Linköping, Sweden.
PLoS One. 2018 Jul 3;13(7):e0199635. doi: 10.1371/journal.pone.0199635. eCollection 2018.
C-peptide (CP) loss in type 1 diabetes (T1D) is highly variable, and factors influencing it are poorly understood. We modelled CP values in T1D patients from diagnosis for up to 6 years, treating the serial data as growth curves plotted against time since diagnosis. The aims were to summarise the pattern of CP loss (i.e. growth curve shape) in individual patients in simple terms, and to identify baseline characteristics that predict this pattern in individuals.
Between 1976 and 2011, 442 T1D patients initially aged <18y underwent 120-minute mixed meal tolerance tests (MMTT) to calculate area under the curve (AUC) CP, at 3, 9, 18, 30, 48 and 72 months after diagnosis (n = 1537). The data were analysed using the novel SITAR mixed effects growth curve model (SuperImposition by Translation And Rotation). It fits a mean AUC growth curve, but also allows the curve's mean level and rate of fall to vary between individuals so as to best fit the individual patient curves. These curve adjustments define individual curve shape.
The square root (√) AUC scale provided the best fit. The mean levels and rates of fall for individuals were normally distributed and uncorrelated with each other. Age at diagnosis and √AUC at 3 months strongly predicted the patient-specific mean levels, while younger age at diagnosis (p<0.0001) and the 120-minute CP value of the 3-month MMTT (p = 0.002) predicted the patient-specific rates of fall.
SITAR growth curve analysis is a useful tool to assess CP loss in type 1 diabetes, explaining patient differences in terms of their mean level and rate of fall. A definition of rapid CP loss could be based on a quantile of the rate of fall distribution, allowing better understanding of factors determining CP loss and stratification of patients into targeted therapies.
1 型糖尿病（T1D）患者的 C 肽（CP）丢失具有高度变异性，但其影响因素尚不清楚。我们对诊断后 1 至 6 年内的 T1D 患者的 CP 值进行建模，将连续数据视为随诊断后时间变化而绘制的生长曲线。目的是用简单的术语总结个体患者 CP 丢失的模式（即生长曲线形状），并确定预测个体患者 CP 丢失模式的基线特征。
1976 年至 2011 年间，442 名年龄<18 岁的 T1D 患者接受了 120 分钟混合餐耐量试验（MMTT），以计算诊断后 3、9、18、30、48 和 72 个月时的 CP 曲线下面积（AUC）（n=1537）。使用新型 SITAR 混合效应生长曲线模型（平移和旋转叠加）对数据进行分析。它拟合了平均 AUC 生长曲线，但也允许曲线的平均水平和下降速度在个体之间变化，以最佳拟合个体患者曲线。这些曲线调整定义了个体曲线形状。
以 AUC 的平方根（√）为尺度提供了最佳拟合。个体的平均水平和下降速度呈正态分布，彼此之间不相关。诊断时的年龄和 3 个月时的 √AUC 强烈预测了患者的平均水平，而诊断时的年龄越小（p<0.0001）和 3 个月 MMTT 的 120 分钟 CP 值（p=0.002）则预测了患者的下降速度。
SITAR 生长曲线分析是评估 1 型糖尿病 CP 丢失的有用工具，可以根据患者的平均水平和下降速度来解释个体差异。快速 CP 丢失的定义可以基于下降速度分布的分位数，从而更好地了解决定 CP 丢失的因素，并将患者分层为靶向治疗。
