Metabonomic biomarkers for risk factors of chronic kidney disease

Integrative transcriptomic and proteomic profile revealed inhibition of oxidative phosphorylation and peroxisomes during renal interstitial fibrosis

Effective therapies of chronic kidney disease (CKD) are lacking due to the unclear molecular pathogenesis. Previous single omics-studies have described potential molecular regulation mechanism of CKD only at the level of transcription or translation. Therefore, this study generated an integrated transcriptomic and proteomic profile to provide deep insights into the continuous transcription-translation process during CKD. The comprehensive datasets identified 14,948 transcripts and 6423 proteins, 233 up-regulated and 364 down-regulated common differentially expressed genes of transcriptome and proteome were selected to further combined bioinformatics analysis. The obtained results revealed reactive oxygen species (ROS) metabolism and antioxidant system due to imbalance of mitochondria and peroxisomes were significantly repressed in CKD. Overall, this study presents a valuable multi-omics analysis that sheds light on the molecular mechanisms underlying CKD. SIGNIFICANCE: Chronic kidney disease (CKD) is a progressive and irreversible condition that results in abnormal kidney function and structure, and is ranked 18th among the leading causes of death globally, leading to a significant societal burden. Hence, there is an urgent need for research to detect new, sensitive, and specific biomarkers. Omics-based studies offer great potential to identify underlying disease mechanisms, aid in clinical diagnosis, and develop novel treatment strategies for CKD. Previous studies have mainly focused on the regulation of gene expression or protein synthesis in CKD, thereby compelling us to conduct a meticulous analysis of transcriptomic and proteomic data from the UUO mouse model. Here, we have performed a unified analysis of CKD model by integrating transcriptomes and protein suites for the first time. Our study contributes to a deeper understanding of the pathogenesis of CKD and provides a basis for subsequent disease management and drug development.

Metabolome evidence of CKDu risks after chronic exposure to simulated Sri Lanka drinking water in zebrafish

It is still a serious public health issue that chronic kidney disease of uncertain etiology (CKDu) in Sri Lanka poses challenges in identification, prevention, and treatment. What environmental factors in drinking water cause kidney damage remains unclear. This study aimed to investigate the risks of various environmental factors that may induce CKDu, including water hardness, fluoride (HF), heavy metals (HM), microcystin-LR (MC-LR), and their combined exposure (HFMM). The research focused on comprehensive metabolome analysis, and correlation with transcriptomic and gut microbiota changes. Results revealed that chronic exposure led to kidney damage and pancreatic toxicity in adult zebrafish. Metabolomics profiling showed significant alterations in biochemical processes, with enriched metabolic pathways of oxidative phosphorylation, folate biosynthesis, arachidonic acid metabolism, FoxO signaling pathway, lysosome, pyruvate metabolism, and purine metabolism. The network analysis revealed significant changes in metabolites associated with renal function and diseases, including 20-Hydroxy-LTE4, PS(18:0/22:2(13Z,16Z)), Neuromedin N, 20-Oxo-Leukotriene E4, and phenol sulfate, which are involved in the fatty acyls and glycerophospholipids class. These metabolites were closely associated with the disrupted gut bacteria of g_ZOR0006, g_Pseudomonas, g_Tsukamurella, g_Cetobacterium, g_Flavobacterium, which belonged to dominant phyla of Firmicutes and Proteobacteria, etc., and differentially expressed genes (DEGs) such as egln3, ca2, jun, slc2a1b, and gls2b in zebrafish. Exploratory omics analyses revealed the shared significantly changed pathways in transcriptome and metabolome like calcium signaling and necroptosis, suggesting potential biomarkers for assessing kidney disease.

Plasma metabolomic profiling reveals factors associated with dose-adjusted trough concentration of tacrolimus in liver transplant recipients

Inter- and intrapatient variability of tacrolimus exposure is a vital prognostic risk factor for the clinical outcome of liver transplantation. New factors or biomarkers characterizing tacrolimus disposition is essential for optimal dose prediction in recipients of liver transplant. The aim of the study was to identify potential plasma metabolites associated with the dose-adjusted trough concentration of tacrolimus in liver transplant recipients by using a global metabolomic approach. A total of 693 plasma samples were collected from 137 liver transplant recipients receiving tacrolimus and regular therapeutic drug monitoring. Untargeted metabolomic analysis was performed by ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry. Univariate and multivariate analyses with a mixed linear model were conducted, and the results showed that the dose-adjusted tacrolimus trough concentration was associated with 31 endogenous metabolites, including medium- and long-chain acylcarnitines such as stearoylcarnitine (β = 0.222, p = 0.001), microbiota-derived uremic retention solutes such as indolelactic acid (β = 0.194, p = 0.007), bile acids such as taurohyodeoxycholic acid (β = -0.056, p = 0.002), and steroid hormones such as testosterone (β = 0.099, p = 0.001). A multiple linear mixed model including 11 metabolites and clinical information was established with a suitable predictive performance (correlation coefficient based on fixed effects = 0.64 and correlation coefficient based on fixed and random effects = 0.78). These data demonstrated that microbiota-derived uremic retention solutes, bile acids, steroid hormones, and medium- and long-chain acylcarnitines were the main metabolites associated with the dose-adjusted trough concentration of tacrolimus in liver transplant recipients.

Shenkang Injection for Treating Renal Fibrosis-Metabonomics and Regulation of E3 Ubiquitin Ligase Smurfs on TGF-β/Smads Signal Transduction

At present, TGF-β is the most critical fibrogenic factor known. Smad ubiquitin ligase Smurfs play an important role in the regulation of the TGF-/Smads signaling pathway, which is linked to metabolite changes in renal fibrosis. Previous studies have shown that Shenkang injection can prevent and treat chronic kidney disease through multiple channels of action. However, the precise relationship between Shenkang injection and the regulation of the TGF-/Smads signaling pathway in the treatment of chronic kidney disease is unknown. Here, we evaluated the pharmacological effects of Shenkang injection on ubiquitination and metabolic changes of the TGF-β/Smads signaling pathway in UUO mice using pathology-related indicators, immunoprecipitation, subcellular co-location, and metabonomics analysis. Our findings indicate that Shenkang injection can promote nuclear translocation of Smurf1 and Smurf2 to TGF- membrane receptors TR-I and Smad2 and ubiquitinated degradation of these proteins. Furthermore, the formation of TβR-I/TβR-II, TβR-I/Smad2, and TβR-I/Smad3 complexes was inhibited to negatively regulate the TGF-β/Smad signaling pathway induced renal tubular epithelial transdifferentiation (EMT). The EMT process is not very relevant in vivo, although it is clear that TGF-β induces EMT in cultured cells, which has been demonstrated by numerous teams around the world. However, this is not the case with the in vivo models of kidney fibrosis, especially UUO. In addition, Shenkang injection can improve amino acid metabolism, purine metabolism, and fatty acid metabolism disorders.

A novel canine nuclear magnetic resonance spectroscopy-based metabolomics platform: Validation and sample handling

BACKGROUND

Metabolomics has been proven to be an invaluable research tool by providing comprehensive insight into systemic metabolism. However, the lack of scalable and quantitative methods with known reference intervals (RIs) and documented reproducibility has prevented the use of metabolomics in the clinical setting.

OBJECTIVE

The objective of this study was to validate the developed quantitative nuclear magnetic resonance (NMR) spectroscopy-based metabolomics platform for canine serum and plasma samples and determine optimal sample handling conditions for its use.

METHODS

Altogether, 8247 canine samples were analyzed using a Bruker's 500 MHz NMR spectrometer. Using statistical approaches derived from international guidelines, we studied method precision, measurand stability in various long- and short-term storage conditions, as well as the effect of prolonged contact with red blood cells (RBCs), and differences among blood collection tubes. We also screened interferences with lipemia, hemolysis, and bilirubinemia. The results were compared against routine clinical chemistry methods, and RIs were defined for all measurands.

RESULTS

We determined RIs for 123 measurands, most of which were previously unpublished. The reproducibility of the results of the NMR platform appeared generally outstanding, and the integrity of the results can be ensured by following standard blood drawing and processing guidelines.

CONCLUSIONS

Owing to the advantages of quantitative results, high reproducibility, and scalability, this canine metabolomics platform holds great potential for numerous clinical and research applications to improve canine health and well-being.

Plasma metabolites associated with chronic kidney disease and renal function in adults from the Baltimore Longitudinal Study of Aging

INTRODUCTION

Chronic kidney disease (CKD) is an important cause of disability and death, but its pathogenesis is poorly understood. Plasma metabolites can provide insights into underlying processes associated with CKD.

OBJECTIVES

To clarify the relationship of plasma metabolites with CKD and renal function in human.

METHODS

We used a targeted metabolomics approach to characterize the relationship of 450 plasma metabolites with CKD and estimated glomerular filtration rate (eGFR) in 616 adults, aged 38-94 years, who participated in the Baltimore Longitudinal Study of Aging.

RESULTS

There were 74 (12.0%) adults with CKD. Carnitine, acetylcarnitine, propionylcarnitine, butyrylcarnitine, trigonelline, trimethylamine N-oxide (TMAO), 1-methylhistidine, citrulline, homoarginine, homocysteine, sarcosine, symmetric dimethylarginine, aspartate, phenylalanine, taurodeoxycholic acid, 3-indolepropionic acid, phosphatidylcholines (PC).aa.C40:2, PC.aa.C40:3, PC.ae.C40:6, triglycerides (TG) 20:4/36:3, TG 20:4/36:4, and choline were associated with higher odds of CKD in multivariable analyses adjusting for potential confounders and using a false discovery rate (FDR) to address multiple testing. Six acylcarnitines, trigonelline, TMAO, 18 amino acids and biogenic amines, taurodeoxycholic acid, hexoses, cholesteryl esters 22:6, dehydroepiandrosterone sulfate, 3-indolepropionic acid, 2 PCs, 17 TGs, and choline were negatively associated with eGFR, and hippuric acid was positively associated with eGFR in multivariable analyses adjusting for potential confounders and using a FDR approach.

CONCLUSION

The metabolites associated with CKD and reduced eGFR suggest that several pathways, such as the urea cycle, the arginine-nitric oxide pathway, the polyamine pathway, and short chain acylcarnitine metabolism are altered in adults with CKD and impaired renal function.

Recent advances in medical image processing for the evaluation of chronic kidney disease

Assessment of renal function and structure accurately remains essential in the diagnosis and prognosis of Chronic Kidney Disease (CKD). Advanced imaging, including Magnetic Resonance Imaging (MRI), Ultrasound Elastography (UE), Computed Tomography (CT) and scintigraphy (PET, SPECT) offers the opportunity to non-invasively retrieve structural, functional and molecular information that could detect changes in renal tissue properties and functionality. Currently, the ability of artificial intelligence to turn conventional medical imaging into a full-automated diagnostic tool is widely investigated. In addition to the qualitative analysis performed on renal medical imaging, texture analysis was integrated with machine learning techniques as a quantification of renal tissue heterogeneity, providing a promising complementary tool in renal function decline prediction. Interestingly, deep learning holds the ability to be a novel approach of renal function diagnosis. This paper proposes a survey that covers both qualitative and quantitative analysis applied to novel medical imaging techniques to monitor the decline of renal function. First, we summarize the use of different medical imaging modalities to monitor CKD and then, we show the ability of Artificial Intelligence (AI) to guide renal function evaluation from segmentation to disease prediction, discussing how texture analysis and machine learning techniques have emerged in recent clinical researches in order to improve renal dysfunction monitoring and prediction. The paper gives a summary about the role of AI in renal segmentation.

Lindera aggregata intervents adenine-induced chronic kidney disease by mediating metabolism and TGF-β/Smad signaling pathway

INTRODUCTION

Lindera aggregata is a main Chinese herb of ancient prescriptions Suoquan pill applied for treating the chronic kidney disease (CKD). A large number of application histories of Lindera aggregata in the treatment of CKD have been recorded in Chinese traditional medical literature. The previous reports revealed that Lindera aggregata can treat CKD.

METHODS

Rats were randomly divided into control, model, Huangkui,Lindera aggregata ethanol extract (LEE) and Lindera aggregata water extract (LWE) groups. hematoxylin-eosin (HE) staining was used to detect the pathology of kidney. The levels of serum creatinine (Scr), serum Neutrophil gelatinase-associated lipocalin (NGAL), blood urea nitrogen (BUN), urine protein (UP), kidney index(KI) were evaluated. The UPLC - QTOF/MS were applied to probe the metabolic profile. Furthermore, Indoxyl sulfate-induced human renal tubular epithelial (HK-2) cell model was built to determine the expression levels of pathogenesis-related proteins.

RESULTS

The results demonstrated that LEE and LWE significantly inhibited the rebound in Scr, BUN, NGAL, UP and KI in models, except for the effect of LWE at low dose (LWE-L) and LEE at low dose (LEE-L) on KI and the effect of LWE-H at high dose (LWE-H) and LEE-L on BUN and NGAL. Moreover,Lindera aggregata extracts alleviated renal tubular dilatation, interstitial fibrosis and interstitial inflammation. By analysis, twenty-eight metabolites were related to CKD. After intervention of Lindera aggregata extracts, some metabolites approach to a normal-like level, such as Indoxyl sulfate. These metabolites are mainly involved in tryptophan, fatty acid, glycerophospholipid, tyrosine and arachidonic acid metabolic pathways. Furthermore, Lindera aggregata extracts mediate the expression of smad2, smad3, smad7 and TGF-β in Indoxyl sulfate-induced HK-2 cell.

CONCLUSIONS

Lindera aggregata extracts can mitigate adenine-induced CKD by modulating the metabolic profile and TGF-β/Smad signaling pathway, providing important supports for developing protective agent of Lindera aggregata for CKD.

Metabolomics Analysis Reveals the Protection Mechanism of Huangqi-Danshen Decoction on Adenine-Induced Chronic Kidney Disease in Rats

Huangqi-Danshen decoction (HDD) is a commonly used drug pair for clinical treatment of chronic kidney disease (CKD) in traditional Chinese medicine with good efficacy. However, the potential mechanisms of this action have not been well elucidated. The aim of this study was to explore the metabolic profiling variations in response to HDD treatment in a CKD rat model. CKD rat model was induced by adding 0.75% adenine to the diet for 4 weeks. The rats in the treatment group received HDD extract orally at the dose of 4.7 g/kg/day during the experiment. At the end of the experiment, serum and kidney samples were collected for biochemical and pathological examination. Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF/MS) was used to analyze metabolic profiling variations in the kidney. The results showed that treatment with HDD markedly attenuated kidney injury and improved renal function. A total of 28 metabolites contributing to CKD phenotype were found and identified in the kidney samples. The primary metabolic pathways disordered in the kidney of CKD rats were glycerophospholipid metabolism, glycosylphosphatidylinositol-anchor biosynthesis, and citrate cycle. Partial least squares discriminant analysis (PLS-DA) score plot showed that the three groups of renal samples were obviously divided into three categories, and the metabolic trajectory of the HDD treatment group moved to the control group. (E)-Piperolein A, phosphatidylcholines (PC) (18:1/22:6), phosphatidylinositols (PI) (13:0/18:1), PI (15:0/20:3), phosphatidylserines (PS) (O-20:0/12:0), and triglyceride (TG) (22:4/24:0/O-18:0) represented potential biomarkers of the renoprotective effects of HDD against CKD. In conclusion, HDD has renoprotective effect against adenine-induced CKD, which may be mediated via partially restoration of perturbed metabolism in the kidney.

Toward a better understanding of chronic kidney disease with complementary chromatographic methods hyphenated with mass spectrometry for improved polar metabolome coverage

The prevalence of chronic kidney disease (CKD) is increasing worldwide. New technical approaches are needed to improve early diagnosis, disease understanding and patient monitoring, and to evaluate new therapies. Metabolomics, as a prime candidate in the field of CKD research, aims to comprehensively analyze the metabolic complexity of biological systems. An extensive analysis of the metabolites contained in biofluids is therefore needed, and the combination of data obtained from multiple analytical platforms constitutes a promising methodological approach. This study presents an original workflow based on complementary chromatographic conditions, reversed-phase and hydrophilic interaction chromatography hyphenated to mass spectrometry to improve the polar metabolome coverage coupled with a univocal metabolite annotation strategy enabling a rapid access to the biological interpretation. This multiplatform workflow was applied in a CKD cohort study to assess plasma metabolic profile modifications related to renal disease. Multivariate analysis of 278 endogenous annotated metabolites enabled patient stratification with respect to CKD stages and helped to generate new biological insights, while also confirming the relevance of tryptophan metabolism pathway in this condition.

Protection Effect of Exogenous Fibroblast Growth Factor 21 on the Kidney Injury in Vascular Calcification Rats

Background:

Chronic kidney disease (CKD) is closely related to the cardiovascular events in vascular calcification (VC). However, little has known about the characteristics of kidney injury caused by VC. Fibroblast growth factor 21 (FGF21) is an endocrine factor, which takes part in various metabolic actions with the potential to alleviate metabolic disorder diseases. Even FGF21 has been regarded as a biomarker in CKD, the role of FGF21 in CKD remains unclear. Therefore, in this study, we evaluate the FGF21 on the kidney injury in VC rats.

Methods:

The male Sprague-Dawley rats were divided into three groups: (1) control group, (2) Vitamin D3 plus nicotine (VDN)-induced VC group, (3) FGF21-treated VDN group. After 4 weeks, the rats were killed and the blood was collected for serum creatinine, urea nitrogen, calcium, and phosphate measurement. Moreover, the renal tissues were homogenized for alkaline phosphatases (ALPs) activity and calcium content. The levels of FGF21 protein were measured by radioimmunoassay. The levels of β-Klotho and FGF receptor 1 (FGFR1) protein were measured by enzyme-linked immunosorbent assay (ELISA). The structural damage and calcifications in aortas were stained by Alizarin-red S. Moreover, the structure of kidney was observed by hematoxylin and eosin staining.

Results:

The renal function impairment caused by VDN modeling was ameliorated by FGF21 treatment, inhibited the elevated serum creatinine and urea level by 20.5% (34.750 ± 4.334 μmol/L vs. 27.630 ± 2.387 μmol/L) and 4.0% (7.038 ± 0.590 mmol/L vs. 6.763 ± 0.374 mmol/L; P < 0.01), respectively, together with the structural damages of glomerular atrophy and renal interstitial fibrosis. FGF21 treatment downregulated the ALP activity, calcium content in the kidney of VC rats by 42.1% (P < 0.01) and 11.7% (P < 0.05) as well as ameliorated the aortic injury and calcification as compared with VDN treatment alone group, indicating an ameliorative effect on VC. ELISA assays showed that the expression of β-Klotho, a component of FGF21 receptor system, was increased in VDN-treated VC rats by 37.4% (6.588 ± 0.957 pg/mg vs. 9.054 ± 0.963 pg/mg; P < 0.01), indicating an FGF21-resistant state. Moreover, FGF21 treatment downregulated the level of β-Klotho in renal tissue by 16.7% (9.054 ± 0.963 pg/mg vs. 7.544 ± 1.362 pg/mg; P < 0.05). However, the level of FGFR1, the receptor of FGF21, kept unchanged under VDN and VDN plus FGF21 administration (0.191 ± 0.0376 ng/mg vs. 0.189 ± 0.032 ng/mg vs. 0.181 ± 0.034 ng/mg; P > 0.05).

Conclusions:

In the present study, FGF21 was observed to ameliorate the kidney injury in VDN-induced VC rats. FGF21 might be a potential therapeutic factor in CKD by cutting off the vicious circle between VC and kidney injury.

Metabolomics in chronic kidney disease: Strategies for extended metabolome coverage

Chronic kidney disease (CKD) is becoming a major public health issue as prevalence is increasing worldwide. It also represents a major challenge for the identification of new early biomarkers, understanding of biochemical mechanisms, patient monitoring and prognosis. Each metabolite contained in a biofluid or tissue may play a role as a signal or as a driver in the development or progression of the pathology. Therefore, metabolomics is a highly valuable approach in this clinical context. It aims to provide a representative picture of a biological system, making exhaustive metabolite coverage crucial. Two aspects can be considered: analytical and biological coverage. From an analytical point of view, monitoring all metabolites within one run is currently impossible. Multiple analytical techniques providing orthogonal information should be carried out in parallel for coverage improvement. The biological aspect of metabolome coverage can be enhanced by using multiple biofluids or tissues for in-depth biological investigation, as the analysis of a single sample type is generally insufficient for whole organism extrapolation. Hence, recording of signals from multiple sample types and different analytical platforms generates massive and complex datasets so that chemometric tools, including data fusion approaches and multi-block analysis, are key tools for extracting biological information and for discovery of relevant biomarkers. This review presents the recent developments in the field of metabolomic analysis, from sampling and analytical strategies to chemometric tools, dedicated to the generation and handling of multiple complementary metabolomic datasets enabling extended metabolite coverage to improve our biological knowledge of CKD.

NMR-based urine metabolic profiling and immunohistochemistry analysis of nephron changes in a mouse model of hypoxia-induced acute kidney injury

Acute kidney injury can be caused by multiple factors, including sepsis, respiratory failure, heart failure, trauma, or nephrotoxic medications, among others. Here, a mouse model was used to investigate potential urinary metabolic biomarkers of hypoxia-induced AKI. Urine metabolic profiles of 48 Swiss Webster mice were assessed using nuclear magnetic resonance spectroscopy (NMR) for 7 days following 72 h exposure to a hypoxic 6.5% oxygen environment. Histological analyses indicated a lack of gross nephron structural changes in the aftermath of hypoxia. Immunohistochemical (IHC) analyses, however, indicated elevated expression of protein injury biomarkers in distal and proximal tubules but not glomeruli. Kidney injury molecule-1 levels peaked in distal tubules at 72 h and were still increasing in proximal tubules at 7 days posthypoxia, whereas cystatin C levels were elevated at 24 h but decreased thereafter, and were elevated and still increasing in proximal tubules at 7 days posthypoxia. Neutrophil gelatinase-associated lipocalin levels were modestly elevated from 24 h to 7 days posthypoxia. NMR-based metabolic profiling revealed that urine metabolites involved in energy metabolism and associated biosynthetic pathways were initially decreased at 24 h posthypoxia, consistent with metabolic suppression as a mechanism for cell survival, but were significantly elevated at 48 and 72 h posthypoxia, indicating a burst in organism metabolism associated with reactivation of cellular energetics during recovery after cessation of hypoxia and return to a normoxic environment. The IHC results indicated that kidney injury persists long after plasma and urine biomarkers of hypoxia return to normal values.

Citric Acid Metabolism in Resistant Hypertension: Underlying Mechanisms and Metabolic Prediction of Treatment Response

Resistant hypertension (RH) affects 9% to 12% of hypertensive adults. Prolonged exposure to suboptimal blood pressure control results in end-organ damage and cardiovascular risk. Spironolactone is the most effective drug for treatment, but not all patients respond and side effects are not negligible. Little is known on the mechanisms responsible for RH. We aimed to identify metabolic alterations in urine. In addition, a potential capacity of metabolites to predict response to spironolactone was investigated. Urine was collected from 29 patients with RH and from a group of 13 subjects with pseudo-RH. For patients, samples were collected before and after spironolactone administration and were classified in responders (n=19) and nonresponders (n=10). Nuclear magnetic resonance was applied to identify altered metabolites and pathways. Metabolites were confirmed by liquid chromatography-mass spectrometry. Citric acid cycle was the pathway most significantly altered (P<0.0001). Metabolic concentrations were quantified and ranged from ng/mL malate to μg/mL citrate. Citrate and oxaloacetate increased in RH versus pseudoresistant. Together with α-ketoglutarate and malate, they were able to discriminate between responders and nonresponders, being the 4 metabolites increased in nonresponders. Combined as a prediction panel, they showed receiver operating characteristiccurve with area under the curve of 0.96. We show that citric acid cycle and deregulation of reactive oxygen species homeostasis control continue its activation after hypertension was developed. A metabolic panel showing alteration before spironolactone treatment and predicting future response of patients is shown. These molecular indicators will contribute optimizing the rate of control of RH patients with spironolactone.

Combined Clinical Phenotype and Lipidomic Analysis Reveals the Impact of Chronic Kidney Disease on Lipid Metabolism

Chronic kidney disease (CKD) results in significant dyslipidemia and profound changes in lipid and lipoprotein metabolism. The associated dyslipidemia, in turn, contributes to progression of CKD and its cardiovascular complications. To gain an in-depth insight into the disorders of lipid metabolism in advanced CKD, we applied UPLC-HDMS-based lipidomics to measure serum lipid metabolites in 180 patients with advanced CKD and 120 age-matched healthy controls. We found significant increases in the levels of total free fatty acids, glycerolipids, and glycerophospholipids in patients with CKD. The levels of free fatty acids, glycerolipids, and glycerophospholipids directly correlated with the level of serum triglyceride and inversely correlated with the levels of total cholesterol and eGFR. A total of 126 lipid species were identified from positive and negative ion modes. Out of 126, 113 identified lipid species were significantly altered in patients with CKD based on the adjusted FDR method. These results pointed to profound disturbance of fatty acid and triglyceride metabolisms in patients with CKD. Logistic regression analysis showed strong correlations between serum methyl hexadecanoic acid, LPC(24:1), 3-oxooctadecanoic acid, and PC(20:2/24:1) levels with eGFR and serum creatinine levels (R > 0.8758). In conclusion, application of UPLC-HDMS-based lipidomic technique revealed profound changes in lipid metabolites in patients with CKD. The observed increases in serum total fatty acids, glycerolipids, and glycerophospholipids levels directly correlated with increased serum triglyceride level and inversely correlated with the eGFR and triglyceride levels.