靶向定量血浆代谢组学发现了区分射血分数降低型心力衰竭和射血分数保留型心力衰竭的代谢物特征

Fawaz Naeem, Teresa C Leone, Christopher Petucci, Clarissa Shoffler, Ravindra Kodihalli, Tiffany Hidalgo, Cheryl Tow-Keogh, Jessica Y Mancuso, Iphigenia Tzameli, Donald Bennett, John D Groarke, Rachel J. Roth Flach, Daniel J Rader, Daniel P Kelly
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Plasma branched-chain amino acids (BCAA) were not different across the groups; however, short-chain acylcarnitine species indicative of BCAA catabolism were significantly elevated in both HF groups. The ketone body 3-hydroxybutyrate (3-HBA) and its metabolite C4-OH carnitine were uniquely elevated in the HFrEF group. Linear regression models demonstrated a significant correlation between plasma 3-HBA and NT-proBNP in both forms of HF, stronger in HFrEF. Conclusions. These results identify plasma signatures that are shared as well as potentially distinguish between HFrEF and HFpEF. Metabolite markers for ketogenic metabolic re-programming in extra-cardiac tissues were identified as unique signatures in the HFrEF group, possibly related to the lipolytic action of increased levels of BNP. 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引用次数: 0

摘要

背景。心力衰竭(HF)有两种一般表型:射血分数降低型心力衰竭(HFrEF)和射血分数保留型心力衰竭(HFpEF)。要开发针对心力衰竭疾病表型的方法来确定和指导治疗,就需要区分的生物标志物。本研究的目的是利用定量代谢组学对大量不同人群进行研究,以复制和扩展有关人类高频血浆代谢特征的现有知识。研究方法对宾夕法尼亚大学医学院生物库收集的 787 份样本进行了定量、靶向 LC/MS 血浆代谢组学研究,这些样本分别来自高频前房颤动受试者(219 人)、高频前房颤动受试者(357 人)和匹配的非衰竭对照组(211 人)。共分析了 90 种代谢物,包括 28 种氨基酸、8 种有机酸和 54 种酰基肉碱。其中 733 份样本还通过 OLINK 蛋白面板进行了蛋白质组分析。研究结果与之前的研究一致,与对照组相比,高频全血细胞生长因子受体组中不饱和形式的中/长链酰基肉碱的升高程度高于高频全血细胞生长因子受体组。一些氨基酸衍生物,包括 1-和 3-甲基组氨酸、同型瓜氨酸、对称(SDMA)和不对称(ADMA)二甲基精氨酸在高房颤动中升高,其中 ADMA 在高房颤动低氧血症组中升高尤为明显。血浆支链氨基酸(BCAA)在各组间无差异;但是,表明 BCAA 分解代谢的短链酰基肉碱种类在两个高频组中都显著升高。酮体 3-hydroxybutyrate (3-HBA) 及其代谢物 C4-OH 肉碱在高频率低氧血症组独特地升高。线性回归模型显示,在两种形式的心房颤动中,血浆 3-HBA 与 NT-proBNP 之间存在显著相关性,而在 HFrEF 中相关性更高。结论。这些结果确定了 HFrEF 和 HFpEF 之间共享的血浆特征,并有可能将两者区分开来。在 HFrEF 组中,心外组织生酮代谢重编程的代谢物标记被确定为独特的特征,这可能与 BNP 水平升高的脂肪分解作用有关。未来的研究将需要进一步验证这些代谢物作为高频生物特征的有效性,从而指导表型特异性疗法,并深入了解高频低氧血症(HFpEF)和高频高氧血症(HFrEF)的全身代谢反应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Targeted Quantitative Plasma Metabolomics Identifies Metabolite Signatures that Distinguish Heart Failure with Reduced and Preserved Ejection Fraction
Background. Two general phenotypes of heart failure (HF) are recognized: HF with reduced ejection fraction (HFrEF) and with preserved EF (HFpEF). To develop HF disease phenotype-specific approaches to define and guide treatment, distinguishing biomarkers are needed. The goal of this study was to utilize quantitative metabolomics on a large, diverse population to replicate and extend existing knowledge of the plasma metabolic signatures in human HF. Methods. Quantitative, targeted LC/MS plasma metabolomics was conducted on 787 samples collected by the Penn Medicine BioBank from subjects with HFrEF (n=219), HFpEF (n=357), and matched non-failing Controls (n=211). A total of 90 metabolites were analyzed, comprising 28 amino acids, 8 organic acids, and 54 acylcarnitines. 733 of these samples were also processed via an OLINK protein panel for proteomic profiling. Results. Consistent with previous studies, unsaturated forms of medium/long chain acylcarnitines were elevated in the HFrEF group to a greater extent than the HFpEF group compared to Controls. A number of amino acid derivatives, including 1- and 3-methylhistidine, homocitrulline, and symmetric (SDMA) and asymmetric (ADMA) dimethylarginine were elevated in HF, with ADMA elevated uniquely in HFpEF. Plasma branched-chain amino acids (BCAA) were not different across the groups; however, short-chain acylcarnitine species indicative of BCAA catabolism were significantly elevated in both HF groups. The ketone body 3-hydroxybutyrate (3-HBA) and its metabolite C4-OH carnitine were uniquely elevated in the HFrEF group. Linear regression models demonstrated a significant correlation between plasma 3-HBA and NT-proBNP in both forms of HF, stronger in HFrEF. Conclusions. These results identify plasma signatures that are shared as well as potentially distinguish between HFrEF and HFpEF. Metabolite markers for ketogenic metabolic re-programming in extra-cardiac tissues were identified as unique signatures in the HFrEF group, possibly related to the lipolytic action of increased levels of BNP. Future studies will be necessary to further validate these metabolites as HF biosignatures that may guide phenotype-specific therapeutics and provide insight into the systemic metabolic responses to HFpEF and HFrEF.
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