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Lin W, Mousavi F, Blum BC, Heckendorf CF, Moore J, Lampl N, McComb M, Kotelnikov S, Yin W, Rabhi N, Layne MD, Kozakov D, Chitalia VC, Emili A. Integrated metabolomics and proteomics reveal biomarkers associated with hemodialysis in end-stage kidney disease. Front Pharmacol 2023; 14:1243505. [PMID: 38089059 PMCID: PMC10715419 DOI: 10.3389/fphar.2023.1243505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 11/13/2023] [Indexed: 02/25/2024] Open
Abstract
Background: We hypothesize that the poor survival outcomes of end-stage kidney disease (ESKD) patients undergoing hemodialysis are associated with a low filtering efficiency and selectivity. The current gold standard criteria using single or several markers show an inability to predict or disclose the treatment effect and disease progression accurately. Methods: We performed an integrated mass spectrometry-based metabolomic and proteomic workflow capable of detecting and quantifying circulating small molecules and proteins in the serum of ESKD patients. Markers linked to cardiovascular disease (CVD) were validated on human induced pluripotent stem cell (iPSC)-derived cardiomyocytes. Results: We identified dozens of elevated molecules in the serum of patients compared with healthy controls. Surprisingly, many metabolites, including lipids, remained at an elevated blood concentration despite dialysis. These molecules and their associated physical interaction networks are correlated with clinical complications in chronic kidney disease. This study confirmed two uremic toxins associated with CVD, a major risk for patients with ESKD. Conclusion: The retained molecules and metabolite-protein interaction network address a knowledge gap of candidate uremic toxins associated with clinical complications in patients undergoing dialysis, providing mechanistic insights and potential drug discovery strategies for ESKD.
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Affiliation(s)
- Weiwei Lin
- Center for Network Systems Biology, Boston University, Boston, MA, United States
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Fatemeh Mousavi
- Center for Network Systems Biology, Boston University, Boston, MA, United States
| | - Benjamin C. Blum
- Center for Network Systems Biology, Boston University, Boston, MA, United States
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Christian F. Heckendorf
- Center for Network Systems Biology, Boston University, Boston, MA, United States
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Jarrod Moore
- Center for Network Systems Biology, Boston University, Boston, MA, United States
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Noah Lampl
- Center for Network Systems Biology, Boston University, Boston, MA, United States
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Mark McComb
- Center for Network Systems Biology, Boston University, Boston, MA, United States
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Sergei Kotelnikov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, United States
| | - Wenqing Yin
- Renal Section, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
| | - Nabil Rabhi
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Matthew D. Layne
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
| | - Dima Kozakov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, United States
| | - Vipul C. Chitalia
- Renal Section, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
- Institute of Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Andrew Emili
- Center for Network Systems Biology, Boston University, Boston, MA, United States
- Department of Biochemistry, Boston University School of Medicine, Boston, MA, United States
- Department of Biology, Boston University, Boston, MA, United States
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Xueshuan Xinmaining Tablet Treats Blood Stasis through Regulating the Expression of F13a1, Car1, and Tbxa2r. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2015; 2015:704390. [PMID: 25821496 PMCID: PMC4363612 DOI: 10.1155/2015/704390] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2014] [Revised: 12/10/2014] [Accepted: 12/11/2014] [Indexed: 12/11/2022]
Abstract
Xueshuan Xinmaining Tablet (XXT), the Chinese formula, has long been administered in clinical practice for the treatment of cerebral thrombosis and coronary heart disease. In this study, we aimed to study the effect and the molecular mechanism of activating blood circulation and removing blood stasis. Rat models of cold coagulation blood stasis were induced with ice-water bath and epinephrine to assess the amelioration of blood stasis by XXT. Microarray technique was used to identify gene expression from the model and XXT-treated rats. In addition, Quantitative Real-Time PCR (qPCR) was performed to verify the microarray results. The results showed that XXT had a good therapeutic effect on blood stasis by reducing the whole blood viscosity (WBV), plasma viscosity (PV), increasing PT, APTT and TT, and by inhibiting platelet aggregation. Genes were differentially expressed in rats among the model group and the XXT-pretreated groups. XXT ameliorated blood stasis by regulating the expressions of F13a1, Car1, and Tbxa2r.
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Schweighofer N, Lerchbaum E, Trummer O, Schwetz V, Pilz S, Pieber TR, Obermayer-Pietsch B. Androgen levels and metabolic parameters are associated with a genetic variant of F13A1 in women with polycystic ovary syndrome. Gene 2012; 504:133-9. [PMID: 22565190 DOI: 10.1016/j.gene.2012.04.050] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2011] [Revised: 03/08/2012] [Accepted: 04/18/2012] [Indexed: 12/31/2022]
Abstract
The polycystic ovary syndrome (PCOS), characterized by hyperandrogenism, is one of the most common hormonal disorders among premenopausal women and is associated with infertility, obesity, and insulin resistance. Accumulating evidence suggests a role of the blood coagulation factor gene F13A1 in obesity (GeneBank ID: NM_000129.3). The aim of this study was to investigate the association of intronic allelic variants of the F13A1 gene with PCOS susceptibility and metabolic parameters in lean and obese PCOS women. In a case-control study, we determined an intronic F13A1 single nucleotide polymorphism (SNP) (dbSNP ID: rs7766109) in 585 PCOS and 171 control women and tested for PCOS susceptibility and associations with anthropometric, metabolic and hormonal parameters. Genotype frequencies of the F13A1 SNP rs7766109 were equivalent in PCOS and control women. In PCOS women, F13A1 gene variants were significantly associated with body mass index (BMI) (p=0.013), systolic blood pressure (p=0.042), insulin response (AUCins) (p=0.015), triglycerides (TG) (p=0.001), and high density lipoprotein cholesterol (HDL) (p=0.012). In the subgroup of obese PCOS women free androgen index (FAI), free testosterone and sex hormone binding globulin (SHBG) as well as glucose measurements showed a significantly different pattern across F13A1 gene variants (p=0.043; p=0.039 and p=0.013, respectively). We report for the first time an association of the F13A1 SNP rs7766109 with BMI, androgens, and insulin resistance in PCOS women. Further studies are needed to confirm our findings and to evaluate whether F13A1 is causally involved in the pathogenesis of PCOS related metabolic and hormonal disturbances.
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Affiliation(s)
- N Schweighofer
- Medical University of Graz, Division of Endocrinology and Metabolism, Department of Internal Medicine, Auenbruggerplatz 15, 8036 Graz, Austria
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