Metabolic phenotyping of human atherosclerotic plaques: Metabolic alterations and their biological relevance in plaque-containing aorta

Identification of metabolic components of carotid plaque in high-risk patients utilizing liquid chromatography-tandem mass spectrometry

OBJECTIVE

Carotid atherosclerosis is a chronic progressive vascular disease that can be complicated by stroke in severe cases. Prompt diagnosis and treatment of high-risk patients are quite difficult due to the lack of reliable clinical biomarkers. This study aimed to explore potential plaque metabolic markers of stroke-prone risk and relevant targets for pharmacological intervention.

METHOD

Carotid intima and plaque sample tissues were obtained from 20 patients with cerebrovascular symptoms of carotid origin. An untargeted metabolomics approach based on liquid chromatography-tandem mass spectrometry was utilized to characterize the metabolic profiles of the tissues. Multivariate and univariate analysis tools were used.

RESULTS

A total of 154 metabolites were significantly altered in carotid plaque when compared with thickened intima. Of these, 62 metabolites were upregulated, whereas 92 metabolites were downregulated. Support vector machines identified the 15 most important metabolites, such as N-(cyclopropylmethyl)-N'-phenylurea, 9(S)-HOTrE, ACar 12:2, quinoxaline-2,3-dithiol, and l-thyroxine, as biomarkers for high-risk plaques. Metabolic pathway analysis showed that abnormal purine and nucleotide metabolism, amino acid metabolism, glutathione metabolism, and vitamin metabolism may contribute to the occurrence and progression of carotid atherosclerotic plaque.

CONCLUSIONS

Our study identifies the biomarkers and related metabolic mechanisms of carotid plaque, which is stroke-prone, and provides insights and ideas for the precise prevention and targeted intervention of the disease.

Spatial Metabolomics Identifies LPC(18:0) and LPA(18:1) in Advanced Atheroma With Translation to Plasma for Cardiovascular Risk Estimation

BACKGROUND

The metabolic alterations occurring within the arterial architecture during atherosclerosis development remain poorly understood, let alone those particular to each arterial tunica. We aimed first to identify, in a spatially resolved manner, the specific metabolic changes in plaque, media, adventitia, and cardiac tissue between control and atherosclerotic murine aortas. Second, we assessed their translatability to human tissue and plasma for cardiovascular risk estimation.

METHODS

In this observational study, mass spectrometry imaging (MSI) was applied to identify region-specific metabolic differences between atherosclerotic (n=11) and control (n=11) aortas from low-density lipoprotein receptor-deficient mice, via histology-guided virtual microdissection. Early and advanced plaques were compared within the same atherosclerotic animals. Progression metabolites were further analyzed by MSI in 9 human atherosclerotic carotids and by targeted mass spectrometry in human plasma from subjects with elective coronary artery bypass grafting (cardiovascular risk group, n=27) and a control group (n=27).

RESULTS

MSI identified 362 local metabolic alterations in atherosclerotic mice (log2 fold-change ≥1.5; P≤0.05). The lipid composition of cardiac tissue is altered during atherosclerosis development and presents a generalized accumulation of glycerophospholipids, except for lysolipids. Lysolipids (among other glycerophospholipids) were found at elevated levels in all 3 arterial layers of atherosclerotic aortas. LPC(18:0) (lysophosphatidylcholine; P=0.024) and LPA(18:1) (lysophosphatidic acid; P=0.025) were found to be significantly elevated in advanced plaques as compared with mouse-matched early plaques. Higher levels of both lipid species were also observed in fibrosis-rich areas of advanced- versus early-stage human samples. They were found to be significantly reduced in human plasma from subjects with elective coronary artery bypass grafting (P<0.001 and P=0.031, respectively), with LPC(18:0) showing significant association with cardiovascular risk (odds ratio, 0.479 [95% CI, 0.225-0.883]; P=0.032) and diagnostic potential (area under the curve, 0.778 [95% CI, 0.638-0.917]).

CONCLUSIONS

An altered phospholipid metabolism occurs in atherosclerosis, affecting both the aorta and the adjacent heart tissue. Plaque-progression lipids LPC(18:0) and LPA(18:1), as identified by MSI on tissue, reflect cardiovascular risk in human plasma.

Dysregulation of Ceramide Metabolism Is Linked to Iron Deposition and Activation of Related Pathways in the Aorta of Atherosclerotic Miniature Pigs

The miniature pig is a suitable animal model for investigating human cardiovascular diseases. Nevertheless, the alterations in lipid metabolism within atherosclerotic plaques of miniature pigs, along with the underlying mechanisms, remain to be comprehensively elucidated. In this study, we aim to examine the alterations in lipid composition and associated pathways in the abdominal aorta of atherosclerotic pigs induced by a high-fat, high-cholesterol, and high-fructose (HFCF) diet using lipidomics and RNA-Seq methods. The results showed that the content and composition of aortic lipid species, particularly ceramide, hexosyl ceramide, lysophosphatidylcholine, and triglyceride, were significantly altered in HFCF-fed pigs. Meanwhile, the genes governing sphingolipid metabolism, iron ion homeostasis, apoptosis, and the inflammatory response were significantly regulated by the HFCF diet. Furthermore, C16 ceramide could promote iron deposition in RAW264.7 cells, leading to increased intracellular reactive oxygen species (ROS) production, apoptosis, and activation of the toll-like receptor 4 (TLR4)/nuclear Factor-kappa B (NF-қB) inflammatory pathway, which could be mitigated by deferoxamine. Our study demonstrated that dysregulated ceramide metabolism could increase ROS production, apoptosis, and inflammatory pathway activation in macrophages by inducing iron overload, thus playing a vital role in the pathogenesis of atherosclerosis. This discovery could potentially provide a new target for pharmacological therapy of cardiovascular diseases such as atherosclerosis.

Defining atherosclerotic plaque biology by mass spectrometry-based omics approaches

Atherosclerosis is the principal cause of vascular diseases and one of the leading causes of worldwide death. Even though several insights into its natural course, risk factors and interventions have been identified, it is still an ongoing global pandemic. Since the structure and biochemical composition of the plaques show high heterogeneity, a comprehensive understanding of the intraplaque composition, its microenvironment, and the mechanisms of the progression and instability across different vascular beds at their progression stages is crucial for better risk stratification and treatment modalities. Even though several cell-based studies, animal studies, and extensive multicentric population studies have been conducted concerning cardiovascular diseases for assessing the risk factors and plaque biology, the studies on human clinical samples are very limited. New novel approaches utilize samples from percutaneous coronary interventions, which could possibly gain more access to clinical samples at different stages of the diseases without complex invasive resections. As an emerging technological platform in disease discovery research, mass spectrometry-based omics technologies offer capabilities for a comprehensive understanding of the mechanisms linked to several vascular diseases. Here, we discuss the cellular and molecular processes of atherosclerosis, different mass spectrometry-based omics approaches, and the studies mostly done on clinical samples of atheroma plaque using mass spectrometry-based proteomics, metabolomics and lipidomics approaches.

Landscape of lipidomics in cardiovascular medicine from 2012 to 2021: A systematic bibliometric analysis and literature review

Lipidomics has shaped our knowledge of how lipids play a central role in cardiovascular diseases (CVD), whereas there is a lack of a summary of existing research findings. This study performed a bibliometric analysis of lipidomics research in cardiovascular medicine to reveal the core countries, institutions, key researchers, important references, major journals, research hotspots and frontiers in this field. From 2012 to 2021, a total of 761 articles were obtained from the Web of Science Core Collection database. There is a steady increase of publications yearly. The United States and China are on the top of the list regarding article output. The institutions with the most publications were the Baker Heart and Diabetes Institute, the Chinese Academy of Sciences and Harvard Medical School. Peter J Meikle was both the most published and most co-cited author. The major journal in this field is Journal of lipid research. Keyword co-occurrence analysis indicated that coronary heart disease, mass spectrometry, risk, fatty acid, and insulin resistance have become hot topics in this field and keyword burst detection suggests that metabolomics, activation, liver, low density lipoprotein are the frontiers of research in recent years. Collectively, lipidomics in CVD is still in its infancy with a steady increase yearly. More in-depth studies in this area are warranted in the future.

1H-NMR-Based Metabonomics Study to Reveal the Progressive Metabolism Regulation of SAP Deficiency on ApoE-/- Mice

Atherosclerosis is the most common disease of the vascular system and the metabolic disorder is one of its important molecular mechanisms. SAP protein is found to be highly expressed in atherosclerotic blood vessels. Our previous study found that SAP deficiency can significantly inhibit the development of atherosclerosis. However, the regulatory effect of SAP deficiency on AS metabolism is unknown. Based on ¹H-NMR metabonomics, this study investigated the serum metabolic changes in ApoE^-/-;SAP^-/- mice compared with ApoE^-/- mice during the whole progression of atherosclerosis. The results showed that acetate, pyruvate, choline and VLDL + LDL were statistically regulated to the normal levels as in C57 mice by SAP deficiency in ApoE^-/-;SAP^-/- mice at 8 w (without obvious plaques). With the appearance and aggravation of atherosclerotic plaques (8 + 4 w and 8 + 8 w), the four metabolites of acetate, pyruvate, choline and VLDL + LDL were continuously regulated, which were denoted as the metabolic regulatory markers of SAP deficiency. We also found that the changes in these four metabolites had nothing to do with high-fat diet. Therefore, it was revealed that SAP deficiency regulated the metabolic disorders in ApoE^-/- prior to the appearance of obvious atherosclerotic plaques, which is one of the important mechanisms leading to the inhibition of atherosclerosis, providing a new basis for the application of SAP in atherosclerosis.

Metabolism in atherosclerotic plaques: immunoregulatory mechanisms in the arterial wall

Over the last decade, there has been a growing interest to understand the link between metabolism and the immune response in the context of metabolic diseases but also beyond, giving then birth to a new field of research. Termed 'immunometabolism', this interdisciplinary field explores paradigms of both immunology and metabolism to provided unique insights into different disease pathogenic processes, and the identification of new potential therapeutic targets. Similar to other inflammatory conditions, the atherosclerotic inflammatory process in the artery has been associated with a local dysregulated metabolic response. Thus, recent studies show that metabolites are more than just fuels in their metabolic pathways, and they can act as modulators of vascular inflammation and atherosclerosis. In this review article, we describe the most common immunometabolic pathways characterised in innate and adaptive immune cells, and discuss how macrophages' and T cells' metabolism may influence phenotypic changes in the plaque. Moreover, we discuss the potential of targeting immunometabolism to prevent and treat cardiovascular diseases (CVDs).

Innovative Approaches to Assess Intermediate Cardiovascular Risk Subjects: A Review From Clinical to Metabolomics Strategies

Current risk stratification strategies for coronary artery disease (CAD) have low predictive value in asymptomatic subjects classified as intermediate cardiovascular risk. This is relevant because not all coronary events occur in individuals with traditional multiple risk factors. Most importantly, the first manifestation of the disease may be either sudden cardiac death or acute coronary syndrome, after rupture and thrombosis of an unstable non-obstructive atherosclerotic plaque, which was previously silent. The inaccurate stratification using the current models may ultimately subject the individual to excessive or insufficient preventive therapies. A breakthrough in the comprehension of the molecular mechanisms governing the atherosclerosis pathology has driven many researches toward the necessity for a better risk stratification. In this Review, we discuss how metabolomics screening integrated with traditional risk assessments becomes a powerful approach to improve non-invasive CAD subclinical diagnostics. In addition, this Review highlights the findings of metabolomics studies performed by two relevant analytical platforms in current use-mass spectrometry (MS) hyphenated to separation techniques and nuclear magnetic resonance spectroscopy (NMR) -and evaluates critically the challenges for further clinical implementation of metabolomics data. We also discuss the modern understanding of the pathophysiology of atherosclerosis and the limitations of traditional analytical methods. Our aim is to show how discriminant metabolites originated from metabolomics approaches may become promising candidate molecules to aid intermediate risk patient stratification for cardiovascular events and how these tools could successfully meet the demands to translate cardiovascular metabolic biomarkers into clinical settings.

Metabolomic correlates of coronary atherosclerosis, cardiovascular risk, both or neither. Results of the 2 × 2 phenotypic CAPIRE study

BACKGROUND

Traditional cardiovascular risk factors (RFs) and coronary artery disease (CAD) do not always run parallel. We investigated functional-metabolic correlations of CAD, RFs, or neither in the CAPIRE (Coronary Atherosclerosis in Outlier Subjects: Protective and Novel Individual Risk Factors Evaluation) 2 × 2 phenotypic observational study.

METHODS

Two hundred and fortyone subjects were included based on RF burden, presence/absence of CAD (assessed by computed tomography angiography), age and sex. Participants displayed one of four phenotypes: CAD with ≥3 RFs, no-CAD with ≥3 RFs, CAD with ≤1 RF and no-CAD with ≤1 RF. Metabolites were identified by gas chromatography-mass spectrometry and pathways by metabolite set enrichment analysis.

RESULTS

Characteristic patterns and specific pathways emerged for each phenotypic group: amino sugars for CAD/high-RF; urea cycle for no-CAD/high-RF; glutathione for CAD/low-RF; glycine and serine for no-CAD/low-RF. Presence of CAD correlated with ammonia recycling; absence of CAD with the transfer of acetyl groups into mitochondria; high-risk profile with alanine metabolism (all p < 0.05). The comparative case-control analyses showed a statistically significant difference for the two pathways of phenylalanine, tyrosine and tryptophan biosynthesis and phenylalanine metabolism in the CAD/Low-RF vs NoCAD/Low-RF comparison.

CONCLUSIONS

The present 2 × 2 observational study identified specific metabolic pathways for each of the four phenotypes, providing novel functional insights, particularly on CAD with low RF profiles and on the absence of CAD despite high-risk factor profiles.

Long Noncoding RNAs in the Progression of Atherosclerosis: An Integrated Analysis Based on Competing Endogenous RNA Theory

Long noncoding RNAs (lncRNAs) have been increasingly accepted to function importantly in human diseases by serving as competing endogenous RNAs (ceRNAs). To date, the ceRNA mechanisms of lncRNAs in the progression of atherosclerosis (AS) remain largely unclear. On the basis of ceRNA theory, we implemented a multistep computational analysis to construct an lncRNA-mRNA network for AS progression (ASpLMN). The probe reannotation method and microRNA-target interactions from databases were systematically integrated. Three lncRNAs (GS1-358P8.4, OIP5-AS1, and TUG1) with central topological features in the ASpLMN were firstly identified. By using subnetwork analysis, we then obtained two highly clustered modules and one dysregulated module from the ASpLMN network. These modules, sharing three lncRNAs (GS1-358P8.4, OIP5-AS1, and RP11-690D19.3), were significantly enriched in biological pathways such as regulation of actin cytoskeleton, tryptophan metabolism, lysosome, and arginine and proline metabolism. In addition, random walking in the ASpLMN network indicated that lncRNA RP1-39G22.7 and MBNL1-AS1 may also play an essential role in the pathology of AS progression. The identified six lncRNAs from the aforementioned steps could distinguish advanced- from early-staged AS, with a strong diagnostic power for AS occurrence. In conclusion, the results of this study will improve our understanding about the ceRNA-mediated regulatory mechanisms in AS progression, and provide novel lncRNAs as biomarkers or therapeutic targets for acute cardiovascular events.

Upregulated Kynurenine Pathway Enzymes in Aortic Atherosclerotic Aneurysm: Macrophage Kynureninase Downregulates Inflammation

AIMS

Inflammation and hypertension contribute to the progression of atherosclerotic aneurysm in the aorta. Vascular cell metabolism is regarded to modulate atherogenesis, but the metabolic alterations that occur in atherosclerotic aneurysm remain unknown. The present study aimed to identify metabolic pathways and metabolites in aneurysmal walls and examine their roles in atherogenesis.

METHODS

Gene expression using microarray and metabolite levels in the early atherosclerotic lesions and aneurysmal walls obtained from 42 patients undergoing aortic surgery were investigated (early lesion n=11, aneurysm n=35) and capillary electrophoresis-time-of-flight mass spectrometry (early lesion n=14, aneurysm n=38). Using immunohistochemistry, the protein expression and localization of the identified factors were examined (early lesion n=11, non-aneurysmal advanced lesion n=8, aneurysm n=11). The roles of the factors in atherogenesis were analyzed in macrophages derived from human peripheral blood mononuclear cells.

RESULTS

Enrichment analysis using 35 significantly upregulated genes (log2 ratio, ＞3) revealed the alteration of the kynurenine pathway. Metabolite levels of tryptophan, kynurenine, and quinolinic acid and the kynurenine-to-tryptophan ratio were increased in the aneurysmal walls. Gene and protein expression of kynureninase and kynurenine 3-monooxygenase were upregulated and localized in macrophages in the aneurysmal walls. The silencing of kynureninase in the cultured macrophages enhanced the expression of interleukin-6 and indoleamine 2,3-dioxygenase 1.

CONCLUSION

Our study suggests the upregulation of the kynurenine pathway in macrophages in aortic atherosclerotic aneurysm. Kynureninase may negatively regulate inflammation via the kynurenine pathway itself in macrophages.

Artificial Intelligence, Machine Learning, and Cardiovascular Disease

Artificial intelligence (AI)-based applications have found widespread applications in many fields of science, technology, and medicine. The use of enhanced computing power of machines in clinical medicine and diagnostics has been under exploration since the 1960s. More recently, with the advent of advances in computing, algorithms enabling machine learning, especially deep learning networks that mimic the human brain in function, there has been renewed interest to use them in clinical medicine. In cardiovascular medicine, AI-based systems have found new applications in cardiovascular imaging, cardiovascular risk prediction, and newer drug targets. This article aims to describe different AI applications including machine learning and deep learning and their applications in cardiovascular medicine. AI-based applications have enhanced our understanding of different phenotypes of heart failure and congenital heart disease. These applications have led to newer treatment strategies for different types of cardiovascular diseases, newer approach to cardiovascular drug therapy and postmarketing survey of prescription drugs. However, there are several challenges in the clinical use of AI-based applications and interpretation of the results including data privacy, poorly selected/outdated data, selection bias, and unintentional continuance of historical biases/stereotypes in the data which can lead to erroneous conclusions. Still, AI is a transformative technology and has immense potential in health care.

Plasma Metabolic Signature of Atherosclerosis Progression and Colchicine Treatment in Rabbits

Balloon catheter endothelial denudation in New Zealand white rabbits fed high cholesterol diet is a validated atherosclerosis model. Well-characterized in terms of atherosclerosis induction and progression, the metabolic changes associated with the atherosclerosis progression remain indeterminate. Non-targeted metabolomics permits to develop such elucidation and allows to evaluate the metabolic consequences of colchicine treatment, an anti-inflammatory drug that could revert these changes. 16 rabbits underwent 18 weeks of atherosclerosis induction by diet and aortic denudation. Thereafter animals were randomly assigned to colchicine treatment or placebo for 18 weeks while on diet. Plasma samples were obtained before randomization and at 36 weeks. Multiplatform (GC/MS, CE/MS, RP-HPLC/MS) metabolomics was applied. Plasma fingerprints were pre-processed, and the resulting matrixes analyzed to unveil differentially expressed features. Different chemical annotation strategies were accomplished for those significant features. We found metabolites associated with either atherosclerosis progression, or colchicine treatment, or both. Atherosclerosis was profoundly associated with an increase in circulating bile acids. Most of the changes associated with sterol metabolism could not be reverted by colchicine treatment. However, the variations in lysine, tryptophan and cysteine metabolism among others, have shown new potential mechanisms of action of the drug, also related to atherosclerosis progression, but not previously described.

Biomarkers identified by serum metabolomic analysis to predict biologic treatment response in rheumatoid arthritis patients

OBJECTIVES

Biologic treatment has recently revolutionized the management of RA. Despite this success, ∼30-40% of the patients undergoing biologic treatment respond insufficiently. The aim of this study was to identify several specific reliable metabolites for predicting the response of RA patients to TNF-α inhibitors (TNFi) and abatacept (ABT), using capillary electrophoresis-time-of-flight mass spectrometry (CE-TOFMS).

METHODS

We collected serum from RA patients with moderate or high disease activity prior to biologic treatment, and obtained the serum metabolomic profiles of these samples using CE-TOFMS. The patients' response was determined 12 weeks after starting biologic treatment, according to the EULAR response criteria. We compared the metabolites between the response and non-response patient groups and analysed their discriminative ability.

RESULTS

Among 43 total patients, 14 of 26 patients in the TNFi group and 6 of 17 patients in the ABT group responded to the biologic treatment. Of the metabolites separated by CE-TOFMS, 196 were identified as known substances. Using an orthogonal partial least-squares discriminant analysis, we identified five metabolites as potential predictors of TNFi responders and three as predictors of ABT responders. Receiver operating characteristic analyses for multiple biomarkers revealed an area under the curve (AUC) of 0.941, with a sensitivity of 85.7% and specificity of 100% for TNFi, and an AUC of 0.985, with a sensitivity of 100% and specificity of 90.9% for ABT.

CONCLUSION

By metabolomic analysis, we identified serum biomarkers that have a high ability to predict the response of RA patients to TNFi or ABT treatment.

Barocycler-Based Concurrent Multiomics Method To Assess Molecular Changes Associated with Atherosclerosis Using Small Amounts of Arterial Tissue from a Single Mouse

Atherosclerosis is a complex, multifactorial disease characterized by the buildup of plaque in the arterial wall. Apolipoprotein E gene deficient (Apoe^-/-) mice serve as a commonly used tool to elucidate the pathophysiology of atherosclerosis because of their propensity to spontaneously develop arterial lesions. To date, however, an integrated omics assessment of atherosclerotic lesions in individual Apoe^-/- mice has been challenging because of the small amount of diseased and nondiseased tissue available. To address this current limitation, we developed a multiomics method (Multi-ABLE) based on the proteomic method called accelerated Barocycler lysis and extraction (ABLE) to assess the depth of information that can be obtained from arterial tissue derived from a single mouse by splitting ABLE to allow for a combined proteomics-metabolomics-lipidomics analysis (Multi-ABLE). The new method includes tissue lysis via pressure cycling technology (PCT) in a Barocycler, followed by proteomic analysis of half the sample by nanoLC-MS and sequential extraction of lipids (organic extract) and metabolites (aqueous extract) combined with HILIC and reversed phase chromatography and time-of-flight mass spectrometry on the other half. Proteomic analysis identified 845 proteins, 93 of which were significantly altered in lesion-containing arteries. Lipidomic and metabolomic analyses detected 851 lipid and 362 metabolite features, which included 215 and 65 identified lipids and metabolites, respectively. The Multi-ABLE method is the first to apply a concurrent multiomics pipeline to cardiovascular disease using small (<5 mg) tissue samples, and it is applicable to other diseases where limited size samples are available at specific points during disease progression.

Analysis of serum changes in response to a high fat high cholesterol diet challenge reveals metabolic biomarkers of atherosclerosis

Atherosclerotic plaques are characterized by an accumulation of macrophages, lipids, smooth muscle cells, and fibroblasts, and, in advanced stages, necrotic debris within the arterial walls. Dietary habits such as high fat and high cholesterol (HFHC) consumption are known risk factors for atherosclerosis. However, the key metabolic contributors to diet-induced atherosclerosis are far from established. Herein, we investigate the role of a 2-year HFHC diet challenge in the metabolic changes of development and progression of atherosclerosis. We used a non-human primate (NHP) model (baboons, n = 60) fed a HFHC diet for two years and compared metabolomic profiles in serum from animals on baseline chow with serum collected after the challenge diet using two-dimensional gas chromatography time-of-flight mass-spectrometry (2D GC-ToF-MS) for untargeted metabolomic analysis, to quantify metabolites that contribute to atherosclerotic lesion formation. Further, clinical biomarkers associated with atherosclerosis, lipoprotein measures, fat indices, and arterial plaque formation (lesions) were quantified. Using two chemical derivatization (i.e., silylation) approaches, we quantified 321 metabolites belonging to 66 different metabolic pathways, which revealed significantly different metabolic profiles of HFHC diet and chow diet fed baboon sera. We found heritability of two important metabolites, lactic acid and asparagine, in the context of diet-induced metabolic changes. In addition, abundance of cholesterol, lactic acid, and asparagine were sex-dependent. Finally, 35 metabolites correlated (R2, 0.068-0.271, P < 0.05) with total lesion burden assessed in three arteries (aortic arch, common iliac artery, and descending aorta) which could serve as potential biomarkers pending further validation. This study demonstrates the feasibility of detecting sex-specific and heritable metabolites in NHPs with diet-induced atherosclerosis using untargeted metabolomics allowing understanding of atherosclerotic disease progression in humans.

Metabolic Alterations Associated with Atorvastatin/Fenofibric Acid Combination in Patients with Atherogenic Dyslipidaemia: A Randomized Trial for Comparison with Escalated-Dose Atorvastatin

In the current study, the metabolic effects of atorvastatin dose escalation versus atorvastatin/fenofibric acid combination were compared using metabolomics analyses. Men and women with combined hyperlipidaemia were initially prescribed atorvastatin (10 mg, ≥4 weeks). Patients who reached low-density lipoprotein-cholesterol targets, but had triglyceride and high-density lipoprotein-cholesterol levels ≥150 mg/dL and <50 mg/dL, respectively, were randomized to receive atorvastatin 20 mg or atorvastatin 10 mg/fenofibric acid 135 mg for 12 weeks. Metabolite profiling of serum was performed and changes in metabolites after drug treatment in the two groups were compared. Analysis was performed using patients' samples obtained before and after treatment. Of 89 screened patients, 37 who met the inclusion criteria were randomized, and 34 completed the study. Unlike that in the dose-escalation group, distinct clustering of both lipid and aqueous metabolites was observed in the combination group after treatment. Most lipid metabolites of acylglycerols and many of ceramides decreased, while many of sphingomyelins increased in the combination group. Atorvastatin dose escalation modestly decreased lysophosphatidylcholines; however, the effect of combination therapy was variable. Most aqueous metabolites decreased, while L-carnitine remarkably increased in the combination group. In conclusion, the atorvastatin/fenofibric acid combination induced distinct metabolite clustering. Our results provide comprehensive information regarding metabolic changes beyond conventional lipid profiles for this combination therapy.