脂质组学分析确定了家族性高胆固醇血症受试者他汀类药物反应的潜在预测生物标志物。

IF 3.4 3区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Chemistry and Physics of Lipids Pub Date : 2023-11-01 DOI:10.1016/j.chemphyslip.2023.105348
Alvaro Cerda , Raul Hernandes Bortolin , Marcos Yukio Yoshinaga , Renata Caroline Costa de Freitas , Carolina Dagli-Hernandez , Jessica Bassani Borges , Victor Fernandes de Oliveira , Rodrigo Marques Gonçalves , Andre Arpad Faludi , Gisele Medeiros Bastos , Rosario Dominguez Crespo Hirata , Mario Hiroyuki Hirata
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引用次数: 0

摘要

家族性高胆固醇血症(FH)是一种脂质代谢紊乱,可导致低密度脂蛋白胆固醇(LDL-c)升高和过早动脉粥样硬化风险增加。他汀类药物抑制内源性胆固醇生物合成,从而降低LDL-c血浆水平并预防心血管事件。本研究旨在探讨他汀类药物治疗对FH患者血清脂质组学的影响,并确定FH患者反应的生物标志物。17名成年FH患者接受了为期6周的冲洗,随后接受了为期4周的阿托伐他汀(80mg/天)或瑞舒伐他汀(40mg/天)治疗。LDL-c反应被认为是好的(减少40-70%,n=9)或差的(减少3-33%,n=8)。通过超高效液相色谱法结合电喷雾电离串联飞行时间质谱法分析血清脂质组学图谱,并使用MetaboAnalyst v5.0分析数据。脂质组学分析鉴定出353种脂质,分为16类。他汀类药物治疗显著降低了13种脂质类别中的8种,产生了磷脂酰肌醇(PI)16:0/18:2、18:0/18:1和18:0/18:2的显著贡献的特征性脂质组学特征;和三酰甘油(TAG)18:2×2/18:3,18:1/18:2/18:3、16:1/18:2×2、16:1/18:12/18:3和16:1/18:2/花生四烯酸(p调节
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Lipidomic analysis identified potential predictive biomarkers of statin response in subjects with Familial hypercholesterolemia

Familial hypercholesterolemia (FH) is a disorder of lipid metabolism that causes elevated low-density lipoprotein cholesterol (LDL-c) and increased premature atherosclerosis risk. Statins inhibit endogenous cholesterol biosynthesis, which reduces LDL-c plasma levels and prevent from cardiovascular events. This study aimed to explore the effects of statin treatment on serum lipidomic profile and to identify biomarkers of response in subjects with FH. Seventeen adult FH patients underwent a 6-week washout followed by 4-week treatment with atorvastatin (80 mg/day) or rosuvastatin (40 mg/day). LDL-c response was considered good (40–70 % reduction, n = 9) or poor (3–33 % reduction, n = 8). Serum lipidomic profile was analyzed by ultra-high-performance liquid chromatography combined with electrospray ionization tandem time-of-flight mass spectrometry, and data were analyzed using MetaboAnalyst v5.0. Lipidomic analysis identified 353 lipids grouped into 16 classes. Statin treatment reduced drastically 8 of 13 lipid classes, generating a characteristic lipidomic profile with a significant contribution of phosphatidylinositols (PI) 16:0/18:2, 18:0/18:1 and 18:0/18:2; and triacylglycerols (TAG) 18:2x2/18:3, 18:1/18:2/18:3, 16:1/18:2x2, 16:1/18:2/18:3 and 16:1/18:2/Arachidonic acid (p-adjusted <0.05). Biomarker analysis implemented in MetaboAnalyst subsequently identified PI 16:1/18:0, 16:0/18:2 and 18:0/18:2 as predictors of statin response with and receiver operating characteristic (ROC) areas under the curve of 0.98, 0.94 and 0.91, respectively. In conclusion, statins extensively modulate the overall serum lipid composition of FH individuals and these findings suggest that phosphatidyl-inositol molecules are potential predictive biomarkers of statin response.

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来源期刊
Chemistry and Physics of Lipids
Chemistry and Physics of Lipids 生物-生化与分子生物学
CiteScore
7.60
自引率
2.90%
发文量
50
审稿时长
40 days
期刊介绍: Chemistry and Physics of Lipids publishes research papers and review articles on chemical and physical aspects of lipids with primary emphasis on the relationship of these properties to biological functions and to biomedical applications. Accordingly, the journal covers: advances in synthetic and analytical lipid methodology; mass-spectrometry of lipids; chemical and physical characterisation of isolated structures; thermodynamics, phase behaviour, topology and dynamics of lipid assemblies; physicochemical studies into lipid-lipid and lipid-protein interactions in lipoproteins and in natural and model membranes; movement of lipids within, across and between membranes; intracellular lipid transfer; structure-function relationships and the nature of lipid-derived second messengers; chemical, physical and functional alterations of lipids induced by free radicals; enzymatic and non-enzymatic mechanisms of lipid peroxidation in cells, tissues, biofluids; oxidative lipidomics; and the role of lipids in the regulation of membrane-dependent biological processes.
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