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Abstract：
OBJECTIVE: The duration of type 2 diabetes mellitus (T2DM) and blood glucose levels have a significant impact on the development of T2DM complications. However, currently known risk factors are not good predictors of the onset or progression of diabetic retinopathy (DR). Therefore, we aimed to investigate the differences in the serum lipid composition in patients with T2DM, without and with DR, and search for potential serological indicators associated with the development of DR.
METHODS: A total of 622 patients with T2DM hospitalized in the Department of Endocrinology of the First Affiliated Hospital of Xi\'an JiaoTong University were selected as the discovery set. One-to-one case-control matching was performed according to the traditional risk factors for DR (i.e., age, duration of diabetes, HbA1c level, and hypertension). All cases with comorbid chronic kidney disease were excluded to eliminate confounding factors. A total of 42 pairs were successfully matched. T2DM patients with DR (DR group) were the case group, and T2DM patients without DR (NDR group) served as control subjects. Ultra-performance liquid chromatography-mass spectrometry (LC-MS/MS) was used for untargeted lipidomics analysis on serum, and a partial least squares discriminant analysis (PLS-DA) model was established to screen differential lipid molecules based on variable importance in the projection (VIP) > 1. An additional 531 T2DM patients were selected as the validation set. Next, 1:1 propensity score matching (PSM) was performed for the traditional risk factors for DR, and a combined 95 pairings in the NDR and DR groups were successfully matched. The screened differential lipid molecules were validated by multiple reaction monitoring (MRM) quantification based on mass spectrometry.
RESULTS: The discovery set showed no differences in traditional risk factors associated with the development of DR (i.e., age, disease duration, HbA1c, blood pressure, and glomerular filtration rate). In the DR group compared with the NDR group, the levels of three ceramides (Cer) and seven sphingomyelins (SM) were significantly lower, and one phosphatidylcholine (PC), two lysophosphatidylcholines (LPC), and two SMs were significantly higher. Furthermore, evaluation of these 15 differential lipid molecules in the validation sample set showed that three Cer and SM(d18:1/24:1) molecules were substantially lower in the DR group. After excluding other confounding factors (e.g., sex, BMI, lipid-lowering drug therapy, and lipid levels), multifactorial logistic regression analysis revealed that a lower abundance of two ceramides, i.e., Cer(d18:0/22:0) and Cer(d18:0/24:0), was an independent risk factor for the occurrence of DR in T2DM patients.
CONCLUSIONS: Disturbances in lipid metabolism are closely associated with the occurrence of DR in patients with T2DM, especially in ceramides. Our study revealed for the first time that Cer(d18:0/22:0) and Cer(d18:0/24:0) might be potential serological markers for the diagnosis of DR occurrence in T2DM patients, providing new ideas for the early diagnosis of DR.
METHODS: A total of 622 patients with T2DM hospitalized in the Department of Endocrinology of the First Affiliated Hospital of Xi\'an JiaoTong University were selected as the discovery set. One-to-one case-control matching was performed according to the traditional risk factors for DR (i.e., age, duration of diabetes, HbA1c level, and hypertension). All cases with comorbid chronic kidney disease were excluded to eliminate confounding factors. A total of 42 pairs were successfully matched. T2DM patients with DR (DR group) were the case group, and T2DM patients without DR (NDR group) served as control subjects. Ultra-performance liquid chromatography-mass spectrometry (LC-MS/MS) was used for untargeted lipidomics analysis on serum, and a partial least squares discriminant analysis (PLS-DA) model was established to screen differential lipid molecules based on variable importance in the projection (VIP) > 1. An additional 531 T2DM patients were selected as the validation set. Next, 1:1 propensity score matching (PSM) was performed for the traditional risk factors for DR, and a combined 95 pairings in the NDR and DR groups were successfully matched. The screened differential lipid molecules were validated by multiple reaction monitoring (MRM) quantification based on mass spectrometry.
RESULTS: The discovery set showed no differences in traditional risk factors associated with the development of DR (i.e., age, disease duration, HbA1c, blood pressure, and glomerular filtration rate). In the DR group compared with the NDR group, the levels of three ceramides (Cer) and seven sphingomyelins (SM) were significantly lower, and one phosphatidylcholine (PC), two lysophosphatidylcholines (LPC), and two SMs were significantly higher. Furthermore, evaluation of these 15 differential lipid molecules in the validation sample set showed that three Cer and SM(d18:1/24:1) molecules were substantially lower in the DR group. After excluding other confounding factors (e.g., sex, BMI, lipid-lowering drug therapy, and lipid levels), multifactorial logistic regression analysis revealed that a lower abundance of two ceramides, i.e., Cer(d18:0/22:0) and Cer(d18:0/24:0), was an independent risk factor for the occurrence of DR in T2DM patients.
CONCLUSIONS: Disturbances in lipid metabolism are closely associated with the occurrence of DR in patients with T2DM, especially in ceramides. Our study revealed for the first time that Cer(d18:0/22:0) and Cer(d18:0/24:0) might be potential serological markers for the diagnosis of DR occurrence in T2DM patients, providing new ideas for the early diagnosis of DR.
摘要：
目的：2型糖尿病（T2DM）的持续时间和血糖水平对T2DM并发症的发展有重大影响。然而,目前已知的危险因素不能很好地预测糖尿病性视网膜病变(DR)的发病或进展.因此,我们的目的是研究2型糖尿病患者血脂成分的差异，没有和有DR，并寻找与DR发展相关的潜在血清学指标。
方法：选择在西安交通大学第一附属医院内分泌科住院的622例T2DM患者作为发现集。根据DR的传统危险因素进行一对一的病例对照匹配(即年龄,糖尿病的持续时间，HbA1c水平,和高血压）。排除所有合并慢性肾脏病的病例，以消除混杂因素。共有42对成功配对。T2DM合并DR患者(DR组)为病例组,无DR的T2DM患者（NDR组）作为对照组。超高效液相色谱-质谱(LC-MS/MS)用于血清脂质组学分析,建立了偏最小二乘判别分析(PLS-DA)模型,根据投影中变量重要性(VIP)>1筛选差异脂质分子。选择另外531名T2DM患者作为验证组。接下来,对DR的传统危险因素进行1：1倾向评分匹配（PSM），NDR和DR组的95对配对成功.通过基于质谱的多反应监测(MRM)定量来验证筛选的差异脂质分子。
结果：发现集显示与DR发展相关的传统风险因素没有差异（即，年龄,疾病持续时间,HbA1c,血压,和肾小球滤过率)。在DR组与NDR组相比，三种神经酰胺（Cer）和七种鞘磷脂（SM）的水平显着降低，和一种磷脂酰胆碱（PC），两种溶血磷脂酰胆碱（LPC），和两个SM显著较高。此外，对验证样品组中这15种差异脂质分子的评估显示,DR组中有3种Cer和SM(d18:1/24:1)分子显著较低.排除其他混杂因素后(例如，性别,BMI,降脂药物治疗,和脂质水平)，多因素Logistic回归分析显示，两种神经酰胺的丰度较低，即，Cer(d18:0/22:0)和Cer(d18:0/24:0)，是T2DM患者发生DR的独立危险因素。
结论：脂质代谢紊乱与T2DM患者DR的发生密切相关。尤其是神经酰胺。我们的研究首次揭示Cer(d18:0/22:0)和Cer(d18:0/24:0)可能是诊断T2DM患者DR发生的潜在血清学标志物。为DR的早期诊断提供新思路。
方法：选择在西安交通大学第一附属医院内分泌科住院的622例T2DM患者作为发现集。根据DR的传统危险因素进行一对一的病例对照匹配(即年龄,糖尿病的持续时间，HbA1c水平,和高血压）。排除所有合并慢性肾脏病的病例，以消除混杂因素。共有42对成功配对。T2DM合并DR患者(DR组)为病例组,无DR的T2DM患者（NDR组）作为对照组。超高效液相色谱-质谱(LC-MS/MS)用于血清脂质组学分析,建立了偏最小二乘判别分析(PLS-DA)模型,根据投影中变量重要性(VIP)>1筛选差异脂质分子。选择另外531名T2DM患者作为验证组。接下来,对DR的传统危险因素进行1：1倾向评分匹配（PSM），NDR和DR组的95对配对成功.通过基于质谱的多反应监测(MRM)定量来验证筛选的差异脂质分子。
结果：发现集显示与DR发展相关的传统风险因素没有差异（即，年龄,疾病持续时间,HbA1c,血压,和肾小球滤过率)。在DR组与NDR组相比，三种神经酰胺（Cer）和七种鞘磷脂（SM）的水平显着降低，和一种磷脂酰胆碱（PC），两种溶血磷脂酰胆碱（LPC），和两个SM显著较高。此外，对验证样品组中这15种差异脂质分子的评估显示,DR组中有3种Cer和SM(d18:1/24:1)分子显著较低.排除其他混杂因素后(例如，性别,BMI,降脂药物治疗,和脂质水平)，多因素Logistic回归分析显示，两种神经酰胺的丰度较低，即，Cer(d18:0/22:0)和Cer(d18:0/24:0)，是T2DM患者发生DR的独立危险因素。
结论：脂质代谢紊乱与T2DM患者DR的发生密切相关。尤其是神经酰胺。我们的研究首次揭示Cer(d18:0/22:0)和Cer(d18:0/24:0)可能是诊断T2DM患者DR发生的潜在血清学标志物。为DR的早期诊断提供新思路。
