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脂质组学分析揭示了2型糖尿病患者亚临床颈动脉粥样硬化相关的代谢改变。

Lipidomic analysis reveals metabolism alteration associated with subclinical carotid atherosclerosis in type 2 diabetes.

作者信息

Barranco-Altirriba Maria, Rossell Joana, Alonso Núria, Weber Ralf J M, Ortega Emilio, Lloyd Gavin R, Hernandez Marta, Yanes Oscar, Capellades Jordi, Winder Catherine, Junza Alexandra, Falguera Mireia, Franch-Nadal Josep, Dunn Warwick B, Perera-Lluna Alexandre, Castelblanco Esmeralda, Mauricio Didac

机构信息

Department of Endocrinology & Nutrition, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.

B2SLab, Department of Systems Engineering, Automatics, and Industrial Informatics, Universitat Politècnica de Catalunya, Barcelona, Spain.

出版信息

Cardiovasc Diabetol. 2025 Apr 2;24(1):152. doi: 10.1186/s12933-025-02701-z.

DOI:10.1186/s12933-025-02701-z
PMID:40176064
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11967040/
Abstract

BACKGROUND

Disruption of lipid metabolism contributes to increased cardiovascular risk in diabetes.

METHODS

We evaluated the associations between serum lipidomic profile and subclinical carotid atherosclerosis (SCA) in type 1 (T1D) and type 2 (T2D) diabetes, and in subjects without diabetes (controls) in a cross-sectional study. All subjects underwent a lipidomic analysis using ultra-high performance liquid chromatography-electrospray ionization tandem mass spectrometry, carotid ultrasound (mode B) to assess SCA, and clinical assessment. Multiple linear regression models were used to assess the association between features and the presence and burden of SCA in subjects with T1D, T2D, and controls separately. Additionally, multiple linear regression models with interaction terms were employed to determine features significantly associated with SCA within risk groups, including smoking habit, hypertension, dyslipidaemia, antiplatelet use and sex. Depending on the population under study, different confounding factors were considered and adjusted for, including sample origin, sex, age, hypertension, dyslipidaemia, body mass index, waist circumference, glycated haemoglobin, glucose levels, smoking habit, diabetes duration, antiplatelet use, and alanine aminotransferase levels.

RESULTS

A total of 513 subjects (151 T1D, 155 T2D, and 207 non-diabetic control) were included, in whom the percentage with SCA was 48.3%, 49.7%, and 46.9%, respectively. A total of 27 unique lipid species were associated with SCA in subjects with T2D, in former/current smokers with T2D, and in individuals with T2D without dyslipidaemia. Phosphatidylcholines and diacylglycerols were the main SCA-associated lipidic classes. Ten different species of phosphatidylcholines were up-regulated, while 4 phosphatidylcholines containing polyunsaturated fatty acids were down-regulated. One diacylglycerol was down-regulated, while the other 3 were positively associated with SCA in individuals with T2D without dyslipidaemia. We discovered several features significantly associated with SCA in individuals with T1D, but only one sterol could be partially annotated.

CONCLUSIONS

We revealed a significant disruption of lipid metabolism associated with SCA in subjects with T2D, and a larger SCA-associated disruption in former/current smokers with T2D and individuals with T2D who do not undergo lipid-lowering treatment.

摘要

背景

脂质代谢紊乱会增加糖尿病患者的心血管疾病风险。

方法

在一项横断面研究中,我们评估了1型糖尿病(T1D)、2型糖尿病(T2D)患者以及无糖尿病受试者(对照组)的血清脂质组学特征与亚临床颈动脉粥样硬化(SCA)之间的关联。所有受试者均接受了脂质组学分析,采用超高效液相色谱 - 电喷雾电离串联质谱法、颈动脉超声(B型)以评估SCA,并进行了临床评估。分别使用多元线性回归模型评估T1D、T2D患者及对照组中各特征与SCA的存在及严重程度之间的关联。此外,采用带有交互项的多元线性回归模型来确定在包括吸烟习惯、高血压、血脂异常、抗血小板药物使用和性别等风险组中与SCA显著相关的特征。根据所研究的人群,考虑并调整了不同的混杂因素,包括样本来源、性别、年龄、高血压、血脂异常、体重指数、腰围、糖化血红蛋白、血糖水平、吸烟习惯、糖尿病病程、抗血小板药物使用以及丙氨酸转氨酶水平。

结果

共纳入513名受试者(151名T1D患者、155名T2D患者和207名非糖尿病对照),其中SCA的发生率分别为48.3%、49.7%和46.9%。共有27种独特的脂质种类与T2D患者、T2D既往/当前吸烟者以及无血脂异常的T2D患者的SCA相关。磷脂酰胆碱和二酰甘油是与SCA相关的主要脂质类别。10种不同的磷脂酰胆碱上调,而4种含有多不饱和脂肪酸的磷脂酰胆碱下调。一种二酰甘油下调,而其他3种在无血脂异常的T2D患者中与SCA呈正相关。我们发现了一些与T1D患者的SCA显著相关的特征,但只有一种甾醇能够部分注释。

结论

我们揭示了T2D患者中与SCA相关的脂质代谢显著紊乱,以及T2D既往/当前吸烟者和未接受降脂治疗的T2D患者中与SCA相关的更大程度的紊乱。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1641/11967040/a49ca7507606/12933_2025_2701_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1641/11967040/11b0e9737610/12933_2025_2701_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1641/11967040/a49ca7507606/12933_2025_2701_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1641/11967040/11b0e9737610/12933_2025_2701_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1641/11967040/a49ca7507606/12933_2025_2701_Fig2_HTML.jpg

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