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Govender MA, Stoychev SH, Brandenburg JT, Ramsay M, Fabian J, Govender IS. Proteomic insights into the pathophysiology of hypertension-associated albuminuria: Pilot study in a South African cohort. Clin Proteomics 2024; 21:15. [PMID: 38402394 PMCID: PMC10893729 DOI: 10.1186/s12014-024-09458-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 02/06/2024] [Indexed: 02/26/2024] Open
Abstract
BACKGROUND Hypertension is an important public health priority with a high prevalence in Africa. It is also an independent risk factor for kidney outcomes. We aimed to identify potential proteins and pathways involved in hypertension-associated albuminuria by assessing urinary proteomic profiles in black South African participants with combined hypertension and albuminuria compared to those who have neither condition. METHODS The study included 24 South African cases with both hypertension and albuminuria and 49 control participants who had neither condition. Protein was extracted from urine samples and analysed using ultra-high-performance liquid chromatography coupled with mass spectrometry. Data were generated using data-independent acquisition (DIA) and processed using Spectronaut™ 15. Statistical and functional data annotation were performed on Perseus and Cytoscape to identify and annotate differentially abundant proteins. Machine learning was applied to the dataset using the OmicLearn platform. RESULTS Overall, a mean of 1,225 and 915 proteins were quantified in the control and case groups, respectively. Three hundred and thirty-two differentially abundant proteins were constructed into a network. Pathways associated with these differentially abundant proteins included the immune system (q-value [false discovery rate] = 1.4 × 10- 45), innate immune system (q = 1.1 × 10- 32), extracellular matrix (ECM) organisation (q = 0.03) and activation of matrix metalloproteinases (q = 0.04). Proteins with high disease scores (76-100% confidence) for both hypertension and chronic kidney disease included angiotensinogen (AGT), albumin (ALB), apolipoprotein L1 (APOL1), and uromodulin (UMOD). A machine learning approach was able to identify a set of 20 proteins, differentiating between cases and controls. CONCLUSIONS The urinary proteomic data combined with the machine learning approach was able to classify disease status and identify proteins and pathways associated with hypertension-associated albuminuria.
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Affiliation(s)
- Melanie A Govender
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
| | - Stoyan H Stoychev
- Council for Scientific and Industrial Research, NextGen Health, Pretoria, South Africa
- ReSyn Biosciences, Edenvale, South Africa
| | - Jean-Tristan Brandenburg
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Strengthening Oncology Services, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Michèle Ramsay
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - June Fabian
- Wits Donald Gordon Medical Centre, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Medical Research Council/Wits University Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Ireshyn S Govender
- Council for Scientific and Industrial Research, NextGen Health, Pretoria, South Africa.
- ReSyn Biosciences, Edenvale, South Africa.
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Kounatidis D, Vallianou NG, Poulaki A, Evangelopoulos A, Panagopoulos F, Stratigou T, Geladari E, Karampela I, Dalamaga M. ApoB100 and Atherosclerosis: What's New in the 21st Century? Metabolites 2024; 14:123. [PMID: 38393015 PMCID: PMC10890411 DOI: 10.3390/metabo14020123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 02/08/2024] [Accepted: 02/09/2024] [Indexed: 02/25/2024] Open
Abstract
ApoB is the main protein of triglyceride-rich lipoproteins and is further divided into ApoB48 in the intestine and ApoB100 in the liver. Very low-density lipoprotein (VLDL) is produced by the liver, contains ApoB100, and is metabolized into its remnants, intermediate-density lipoprotein (IDL) and low-density lipoprotein (LDL). ApoB100 has been suggested to play a crucial role in the formation of the atherogenic plaque. Apart from being a biomarker of atherosclerosis, ApoB100 seems to be implicated in the inflammatory process of atherosclerosis per se. In this review, we will focus on the structure, the metabolism, and the function of ApoB100, as well as its role as a predictor biomarker of cardiovascular risk. Moreover, we will elaborate upon the molecular mechanisms regarding the pathophysiology of atherosclerosis, and we will discuss the disorders associated with the APOB gene mutations, and the potential role of various drugs as therapeutic targets.
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Affiliation(s)
- Dimitris Kounatidis
- Second Department of Internal Medicine, Hippokration General Hospital, School of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece
| | - Natalia G Vallianou
- Department of Internal Medicine, Evangelismos General Hospital, 10676 Athens, Greece
| | - Aikaterini Poulaki
- Hematology Unit, Second Department of Internal Medicine, School of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece
| | | | - Fotis Panagopoulos
- Department of Internal Medicine, Evangelismos General Hospital, 10676 Athens, Greece
| | - Theodora Stratigou
- Department of Endocrinology and Metabolism, Evangelismos General Hospital, 10676 Athens, Greece
| | - Eleni Geladari
- Department of Internal Medicine, Evangelismos General Hospital, 10676 Athens, Greece
| | - Irene Karampela
- Second Department of Critical Care, Attikon General University Hospital, Medical School, National and Kapodistrian University of Athens, 12462 Athens, Greece
| | - Maria Dalamaga
- Department of Biological Chemistry, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
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Xu Y, Liu B, Lin L, Lei F, Sun T, Zhang X, Song X, Huang X, Zeng Q, Cai J, Wang Z, Li H. The association of apolipoprotein B with chronic kidney disease in the Chinese population. Front Endocrinol (Lausanne) 2023; 14:1083614. [PMID: 37124758 PMCID: PMC10132458 DOI: 10.3389/fendo.2023.1083614] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Accepted: 03/27/2023] [Indexed: 05/02/2023] Open
Abstract
Background Whether serum apolipoprotein B (ApoB) is a risk factor for the development of Chronic kidney disease (CKD) has not been fully established in the general population. Therefore, our study evaluated the correlation between serum ApoB level and CKD to look for an alternative approach for CKD prevention and treatment in the general population. Methods There were 146,533 participants in this cross-sectional study. 3,325 participants with more than 2 measurements were enrolled in the retrospective longitudinal study with at least a 3-year follow-up. ApoB was measured by the immunoturbidimetric method in 6 centers. Our study defined CKD as an estimated glomerular filtration rate (eGFR) < 90 mL/min/1.73 m2. The Spearman rank correlation analysis and the Random Forest algorithm were applied to rank the importance of variables determining the levels of eGFR. We used the logistic regression model to explain the correlation between serum ApoB and CKD. We used the Cox model to detect the correlation between baseline serum ApoB and the subsequent occurrence of CKD. Results Based on a cross-sectional study, 66.5% of the participants were males, with a median age of 49 (interquartile range [IQR] 43-55). Compared to the non-CKD group, the CKD group has higher levels of lipid profile and fasting glucose as well as the proportion of hypertension and hyperuricemia. The Spearman rank correlation analysis and the Random Forest algorithm revealed that ApoB has the highest correlation with eGFR decline among lipid profiles. The logistic regression analysis revealed that ApoB had a positive correlation with the prevalence of CKD after fully controlling confounders (odds ratio [OR], 1.07; 95% confidence interval [CI]: 1.02-1.11). Moreover, baseline ApoB level was correlated with a new-onset CKD in the longitudinal cohort after full adjustment for confounding factors (hazard ratio [HR], 1.61; 95% CI: 1.02-2.54). The correlation between ApoB level and the new-onset CKD was consistently observed in all sensitivity analyses. Conclusion Serum ApoB had the strongest correlation with CKD among all lipid variables. Moreover, high serum ApoB levels might precede the occurrence of CKD, suggesting that monitoring and reducing serum ApoB levels may provide an alternative method to prevent and treat CKD.
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Affiliation(s)
- Yu Xu
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Department of Anesthesiology, Changsha Central Hospital, Changsha, China
- Institute of Model Animal, Wuhan University, Wuhan, China
| | - Bo Liu
- Medical Science Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Lijin Lin
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
| | - Fang Lei
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
| | - Tao Sun
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
| | - Xingyuan Zhang
- Institute of Model Animal, Wuhan University, Wuhan, China
- School of Basic Medical Science, Wuhan University, Wuhan, China
| | - Xiaohui Song
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
| | - Xuewei Huang
- Department of Cardiology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Qiang Zeng
- Health Management Institute, The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Jingjing Cai
- Institute of Model Animal, Wuhan University, Wuhan, China
- Department of Cardiology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Zhifang Wang
- Department of Nephrology Huanggang Central Hospital of Yangtze University, Huanggang, China
- *Correspondence: Hongliang Li, ; Zhifang Wang,
| | - Hongliang Li
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
- Medical Science Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
- Huanggang Institute of Translational Medicine, Huanggang Central Hospital of Yangtze University, Huanggang, China
- *Correspondence: Hongliang Li, ; Zhifang Wang,
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Host-microbiome interactions: Gut-Liver axis and its connection with other organs. NPJ Biofilms Microbiomes 2022; 8:89. [PMID: 36319663 PMCID: PMC9626460 DOI: 10.1038/s41522-022-00352-6] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 10/18/2022] [Indexed: 11/26/2022] Open
Abstract
An understanding of connections between gut microbiome and liver has provided important insights into the pathophysiology of liver diseases. Since gut microbial dysbiosis increases gut permeability, the metabolites biosynthesized by them can reach the liver through portal circulation and affect hepatic immunity and inflammation. The immune cells activated by these metabolites can also reach liver through lymphatic circulation. Liver influences immunity and metabolism in multiple organs in the body, including gut. It releases bile acids and other metabolites into biliary tract from where they enter the systemic circulation. In this review, the bidirectional communication between the gut and the liver and the molecular cross talk between the host and the microbiome has been discussed. This review also provides details into the intricate level of communication and the role of microbiome in Gut-Liver-Brain, Gut-Liver-Kidney, Gut-Liver-Lung, and Gut-Liver-Heart axes. These observations indicate a complex network of interactions between host organs influenced by gut microbiome.
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Grgurevic L, Novak R, Salai G, Hrkac S, Mocibob M, Vojtusek IK, Laganovic M. Stage II of Chronic Kidney Disease-A Tipping Point in Disease Progression? Biomedicines 2022; 10:1522. [PMID: 35884827 PMCID: PMC9313233 DOI: 10.3390/biomedicines10071522] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 06/20/2022] [Accepted: 06/25/2022] [Indexed: 11/17/2022] Open
Abstract
Chronic kidney disease (CKD) is the progressive loss of renal function. Although advances have been made in understanding the progression of CKD, key molecular events in complex pathophysiological mechanisms that mark each stage of renal failure remain largely unknown. Changes in plasma protein profiles in different disease stages are important for identification of early diagnostic markers and potential therapeutic targets. The goal of this study was to determine the molecular profile of each CKD stage (from 1 to 5), aiming to specifically point out markedly expressed or downregulated proteins. We performed a cross-sectional shotgun-proteomic study of pooled plasma across CKD stages and compared them to healthy controls. After sample pooling and heparin-column purification we analysed proteomes from healthy to CKD stage 1 through 5 participants' plasma by liquid-chromatography/mass-spectrometry. We identified 453 proteins across all study groups. Our results indicate that key events, which may later affect the course of disease progression and the overall pathophysiological background, are most pronounced in CKD stage 2, with an emphasis on inflammation, lipoprotein metabolism, angiogenesis and tissue regeneration. We hypothesize that CKD stage 2 is the tipping point in disease progression and a suitable point in disease course for the development of therapeutic solutions.
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Affiliation(s)
- Lovorka Grgurevic
- Department of Anatomy, School of Medicine, University of Zagreb, 10000 Zagreb, Croatia
- Center for Translational and Clinical Research, Department of Proteomics, School of Medicine, University of Zagreb, 10000 Zagreb, Croatia; (R.N.); (G.S.); (S.H.)
| | - Rudjer Novak
- Center for Translational and Clinical Research, Department of Proteomics, School of Medicine, University of Zagreb, 10000 Zagreb, Croatia; (R.N.); (G.S.); (S.H.)
| | - Grgur Salai
- Center for Translational and Clinical Research, Department of Proteomics, School of Medicine, University of Zagreb, 10000 Zagreb, Croatia; (R.N.); (G.S.); (S.H.)
- Department of Pulmonology, University Hospital Dubrava, 10000 Zagreb, Croatia
| | - Stela Hrkac
- Center for Translational and Clinical Research, Department of Proteomics, School of Medicine, University of Zagreb, 10000 Zagreb, Croatia; (R.N.); (G.S.); (S.H.)
- Department of Emergency Medicine, University Hospital Centre Zagreb, 10000 Zagreb, Croatia
| | - Marko Mocibob
- Department of Chemistry, Faculty of Science, University of Zagreb, 10000 Zagreb, Croatia;
| | - Ivana Kovacevic Vojtusek
- Department of Nephrology, Arterial Hypertension, Dialysis and Transplantation, University Hospital Center Zagreb, 10000 Zagreb, Croatia;
| | - Mario Laganovic
- Department of Nephrology, University Hospital Merkur, 10000 Zagreb, Croatia;
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Pan X. The Roles of Fatty Acids and Apolipoproteins in the Kidneys. Metabolites 2022; 12:metabo12050462. [PMID: 35629966 PMCID: PMC9145954 DOI: 10.3390/metabo12050462] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 05/15/2022] [Accepted: 05/17/2022] [Indexed: 12/10/2022] Open
Abstract
The kidneys are organs that require energy from the metabolism of fatty acids and glucose; several studies have shown that the kidneys are metabolically active tissues with an estimated energy requirement similar to that of the heart. The kidneys may regulate the normal and pathological function of circulating lipids in the body, and their glomerular filtration barrier prevents large molecules or large lipoprotein particles from being filtered into pre-urine. Given the permeable nature of the kidneys, renal lipid metabolism plays an important role in affecting the rest of the body and the kidneys. Lipid metabolism in the kidneys is important because of the exchange of free fatty acids and apolipoproteins from the peripheral circulation. Apolipoproteins have important roles in the transport and metabolism of lipids within the glomeruli and renal tubules. Indeed, evidence indicates that apolipoproteins have multiple functions in regulating lipid import, transport, synthesis, storage, oxidation and export, and they are important for normal physiological function. Apolipoproteins are also risk factors for several renal diseases; for example, apolipoprotein L polymorphisms induce kidney diseases. Furthermore, renal apolipoprotein gene expression is substantially regulated under various physiological and disease conditions. This review is aimed at describing recent clinical and basic studies on the major roles and functions of apolipoproteins in the kidneys.
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Affiliation(s)
- Xiaoyue Pan
- Department of Foundations of Medicine, New York University Long Island School of Medicine, Mineola, New York, NY 11501, USA;
- Diabetes and Obesity Research Center, NYU Langone Hospital—Long Island, Mineola, New York, NY 11501, USA
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Discordance between LDL-C and Apolipoprotein B Levels and Its Association with Renal Dysfunction: Insights from a Population-Based Study. J Clin Med 2022; 11:jcm11020313. [PMID: 35054008 PMCID: PMC8781725 DOI: 10.3390/jcm11020313] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 12/07/2021] [Accepted: 12/14/2021] [Indexed: 02/04/2023] Open
Abstract
Low-density lipoprotein cholesterol (LDL-C) and apolipoprotein B (ApoB) are established markers of atherosclerotic cardiovascular disease (ASCVD), but when concentrations are discordant ApoB is the superior predictor. Chronic kidney disease (CKD) is associated with ASCVD, yet the independent role of atherogenic lipoproteins is contentious. Four groups were created based upon high and low levels of ApoB and LDL-C. Continuous and categorical variables were compared across groups, as were adjusted markers of CKD. Logistic regression analysis assessed association(s) with CKD based on the groups. Subjects were categorised by LDL-C and ApoB, using cut-off values of >160 mg/dL and >130 mg/dL, respectively. Those with low LDL-C and high ApoB, compared to those with high LDL-C and high ApoB, had significantly higher body mass index (30.7 vs. 30.1 kg/m2) and waist circumference (106.1 vs. 102.7 cm) and the highest fasting blood glucose (117.5 vs. 112.7 mg/dL), insulin (16.6 vs. 13.1 μU/mL) and homeostatic model assessment of insulin resistance (5.3 vs. 3.7) profiles (all p < 0.001). This group, compared to those with high LDL-C and high ApoB, also had the highest levels of urine albumin (2.3 vs. 2.2 mg/L), log albumin-creatinine ratio (2.2 vs. 2.1 mg/g) and serum uric acid (6.1 vs. 5.6 mg/dL) and the lowest estimated glomerular filtration rate (81.3 vs. 88.4 mL/min/1.73 m2) (all p < 0.001). In expanded logistic regression models, using the low LDL-C and low ApoB group as a reference, those with low LDL-C and high ApoB had the strongest association with CKD, odds ratio (95% CI) 1.12 (1.08-1.16). Discordantly high levels of ApoB are independently associated with increased likelihood of CKD. ApoB remains associated with metabolic dysfunction, regardless of LDL-C.
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