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van der Ark-Vonk EM, Puijk MV, Pasterkamp G, van der Laan SW. The Effects of FABP4 on Cardiovascular Disease in the Aging Population. Curr Atheroscler Rep 2024; 26:163-175. [PMID: 38698167 PMCID: PMC11087245 DOI: 10.1007/s11883-024-01196-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/05/2024] [Indexed: 05/05/2024]
Abstract
PURPOSE OF REVIEW Fatty acid-binding protein 4 (FABP4) plays a role in lipid metabolism and cardiovascular health. In this paper, we cover FABP4 biology, its implications in atherosclerosis from observational studies, genetic factors affecting FABP4 serum levels, and ongoing drug development to target FABP4 and offer insights into future FABP4 research. RECENT FINDINGS FABP4 impacts cells through JAK2/STAT2 and c-kit pathways, increasing inflammatory and adhesion-related proteins. In addition, FABP4 induces angiogenesis and vascular smooth muscle cell proliferation and migration. FABP4 is established as a reliable predictive biomarker for cardiovascular disease in specific at-risk groups. Genetic studies robustly link PPARG and FABP4 variants to FABP4 serum levels. Considering the potential effects on atherosclerotic lesion development, drug discovery programs have been initiated in search for potent inhibitors of FABP4. Elevated FABP4 levels indicate an increased cardiovascular risk and is causally related to acceleration of atherosclerotic disease, However, clinical trials for FABP4 inhibition are lacking, possibly due to concerns about available compounds' side effects. Further research on FABP4 genetics and its putative causal role in cardiovascular disease is needed, particularly in aging subgroups.
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Affiliation(s)
- Ellen M van der Ark-Vonk
- Central Diagnostics Laboratory, Division Laboratory, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Mike V Puijk
- Central Diagnostics Laboratory, Division Laboratory, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Gerard Pasterkamp
- Central Diagnostics Laboratory, Division Laboratory, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Sander W van der Laan
- Central Diagnostics Laboratory, Division Laboratory, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands.
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Vadadokhau U, Varga I, Káplár M, Emri M, Csősz É. Examination of the Complex Molecular Landscape in Obesity and Type 2 Diabetes. Int J Mol Sci 2024; 25:4781. [PMID: 38732002 PMCID: PMC11084226 DOI: 10.3390/ijms25094781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Revised: 04/10/2024] [Accepted: 04/25/2024] [Indexed: 05/13/2024] Open
Abstract
The escalating prevalence of metabolic disorders, notably type 2 diabetes (T2D) and obesity, presents a critical global health challenge, necessitating deeper insights into their molecular underpinnings. Our study integrates proteomics and metabolomics analyses to delineate the complex molecular landscapes associated with T2D and obesity. Leveraging data from 130 subjects, including individuals with T2D and obesity as well as healthy controls, we elucidate distinct molecular signatures and identify novel biomarkers indicative of disease progression. Our comprehensive characterization of cardiometabolic proteins and serum metabolites unveils intricate networks of biomolecular interactions and highlights differential protein expression patterns between T2D and obesity cohorts. Pathway enrichment analyses reveal unique mechanisms underlying disease development and progression, while correlation analyses elucidate the interplay between proteomics, metabolomics, and clinical parameters. Furthermore, network analyses underscore the interconnectedness of cardiometabolic proteins and provide insights into their roles in disease pathogenesis. Our findings may help to refine diagnostic strategies and inform the development of personalized interventions, heralding a new era in precision medicine and healthcare innovation. Through the integration of multi-omics approaches and advanced analytics, our study offers a crucial framework for deciphering the intricate molecular underpinnings of metabolic disorders and paving the way for transformative therapeutic strategies.
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Affiliation(s)
- Uladzislau Vadadokhau
- Proteomics Core Facility, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary
- Doctoral School of Molecular Cellular and Immune Biology, University of Debrecen, 4032 Debrecen, Hungary
| | - Imre Varga
- Department of IT Systems and Networks, Faculty of Informatics, University of Debrecen, 4028 Debrecen, Hungary;
| | - Miklós Káplár
- Department of Internal Medicine, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary;
| | - Miklós Emri
- Department of Medical Imaging, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary;
| | - Éva Csősz
- Proteomics Core Facility, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary
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Ahmad A, Lim LL, Morieri ML, Tam CHT, Cheng F, Chikowore T, Dudenhöffer-Pfeifer M, Fitipaldi H, Huang C, Kanbour S, Sarkar S, Koivula RW, Motala AA, Tye SC, Yu G, Zhang Y, Provenzano M, Sherifali D, de Souza RJ, Tobias DK, Gomez MF, Ma RCW, Mathioudakis N. Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis. COMMUNICATIONS MEDICINE 2024; 4:11. [PMID: 38253823 PMCID: PMC10803333 DOI: 10.1038/s43856-023-00429-z] [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: 05/12/2023] [Accepted: 12/14/2023] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D). METHODS We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. RESULTS Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. CONCLUSIONS Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.
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Affiliation(s)
- Abrar Ahmad
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Lee-Ling Lim
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Asia Diabetes Foundation, Hong Kong SAR, China
| | - Mario Luca Morieri
- Metabolic Disease Unit, University Hospital of Padova, Padova, Italy
- Department of Medicine, University of Padova, Padova, Italy
| | - Claudia Ha-Ting Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Feifei Cheng
- Health Management Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China
| | - Tinashe Chikowore
- MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, 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
| | | | - Hugo Fitipaldi
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Chuiguo Huang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | | | - Sudipa Sarkar
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Robert Wilhelm Koivula
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Ayesha A Motala
- Department of Diabetes and Endocrinology, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Sok Cin Tye
- Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, Groningen, the Netherlands
- Sections on Genetics and Epidemiology, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Gechang Yu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yingchai Zhang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Michele Provenzano
- Nephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Diana Sherifali
- Heather M. Arthur Population Health Research Institute, McMaster University, Ontario, Canada
| | - Russell J de Souza
- Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences Corporation, Hamilton, Ontario, Canada
| | | | - Maria F Gomez
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden.
- Faculty of Health, Aarhus University, Aarhus, Denmark.
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China.
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China.
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China.
| | - Nestoras Mathioudakis
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
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Ahmad A, Lim LL, Morieri ML, Tam CHT, Cheng F, Chikowore T, Dudenhöffer-Pfeifer M, Fitipaldi H, Huang C, Kanbour S, Sarkar S, Koivula RW, Motala AA, Tye SC, Yu G, Zhang Y, Provenzano M, Sherifali D, de Souza R, Tobias DK, Gomez MF, Ma RCW, Mathioudakis NN. Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes: A Systematic Review and Meta-analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.26.23289177. [PMID: 37162891 PMCID: PMC10168509 DOI: 10.1101/2023.04.26.23289177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Background Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with type 2 diabetes (T2D). Methods We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Results Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Conclusions Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.
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Skau E, Wagner P, Leppert J, Ärnlöv J, Hedberg P. Are the results from a multiplex proteomic assay and a conventional immunoassay for NT-proBNP and GDF-15 comparable? Clin Proteomics 2023; 20:5. [PMID: 36694116 PMCID: PMC9872369 DOI: 10.1186/s12014-023-09393-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 01/13/2023] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND We aimed to compare absolute plasma concentrations of N-terminal pro-brain natriuretic peptide (NT-proBNP) and growth differentiation factor 15 (GDF-15) obtained by a conventional immunoassay with the corresponding relative concentrations from a proximity extension assay (PEA) and compare the prognostic impact of the protein levels obtained from these assays. METHODS We evaluated 437 patients with peripheral arterial disease (PAD) and a population-based cohort of 643 individuals without PAD. Correlations were calculated using Spearman's rank correlation coefficients (rho). The discriminatory accuracy of the protein levels to predict future cardiovascular events was analyzed with Cox regression and presented as time-dependent areas under the receiver-operator-characteristic curves (tdAUCs). RESULTS For NT-proBNP, the two assays correlated with rho 0.93 and 0.93 in the respective cohort. The PEA values leveled off at higher values in both cohorts. The corresponding correlations for GDF-15 were 0.91 and 0.89. At 5 years follow-up, the tdAUCs in the patient cohort were similar for NT-proBNP and GDF-15 regardless of assay used (0.65-0.66). The corresponding tdAUCs in the population-based cohort were between 0.72 and 0.77. CONCLUSION Except for the highest levels of NT-proBNP, we suggest that PEA data for NT-proBNP and GDF-15 reliably reflects absolute plasma levels and contains similar prognostic information.
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Affiliation(s)
- Emma Skau
- grid.8993.b0000 0004 1936 9457Centre for Clinical Research, Västmanland County Hospital, Uppsala University, SE-72 189 Västerås, Sweden ,grid.412154.70000 0004 0636 5158Department of Cardiology, Danderyd University Hospital, Stockholm, Sweden
| | - Philippe Wagner
- grid.8993.b0000 0004 1936 9457Centre for Clinical Research, Västmanland County Hospital, Uppsala University, SE-72 189 Västerås, Sweden
| | - Jerzy Leppert
- grid.8993.b0000 0004 1936 9457Centre for Clinical Research, Västmanland County Hospital, Uppsala University, SE-72 189 Västerås, Sweden
| | - Johan Ärnlöv
- grid.411953.b0000 0001 0304 6002School of Health and Social Studies, Dalarna University, Falun, Sweden ,grid.4714.60000 0004 1937 0626Division of Family Medicine and Primary Care, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Huddinge, Sweden
| | - Pär Hedberg
- grid.8993.b0000 0004 1936 9457Centre for Clinical Research, Västmanland County Hospital, Uppsala University, SE-72 189 Västerås, Sweden ,Department of Clinical Physiology, Västmanland County Hospital, Västerås, Sweden
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Isung J, Granqvist M, Trepci A, Huang J, Schwieler L, Kierkegaard M, Erhardt S, Jokinen J, Piehl F. Differential effects on blood and cerebrospinal fluid immune protein markers and kynurenine pathway metabolites from aerobic physical exercise in healthy subjects. Sci Rep 2021; 11:1669. [PMID: 33462306 PMCID: PMC7814004 DOI: 10.1038/s41598-021-81306-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 01/04/2021] [Indexed: 02/01/2023] Open
Abstract
Mounting evidence shows that physical exercise modulates systemic inflammation. However, its effect on cerebrospinal fluid (CSF) immune-marker profiles in man are largely unknown. We here report a study on healthy subjects (n = 27, males = 12, mean age 28.7, range 22-52) allocated to either an acute exercise setting over four consecutive days, or a training intervention over 4 weeks. Paired plasma and CSF samples collected at baseline, after 7 days of exercise abstention, and the day after completion of the exercise interventions, were analyzed for protein inflammation markers using a multiplex proximity extension assay and neurotransmitters and kynurenine pathway (KP) metabolites using liquid chromatography, respectively. Routine cell counts, and albumin, immunoglobulin G and neurofilament light chain concentrations in CSF remained unchanged in both paradigms, while several inflammatory proteins became upregulated after acute exercise. However, only changes in three CSF (vascular endothelial growth factor-A, interleukin-7 and matrix metalloproteinase-10) and 12 plasma proteins reached significance levels after adjustment for multiple comparisons and exclusion of less stable proteins. Similarly, KP metabolites only changed among participants after acute exercise, while neurotransmitter levels, except for increased CSF serine, remained stable. Both in plasma and CSF changes in KP metabolites and inflammatory proteins correlated, suggesting that these processes are functionally linked. These findings suggest that acute aerobic physical exercise affects immune markers and KP metabolites systemically and in the CSF.
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Affiliation(s)
- Josef Isung
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.
| | - Mathias Granqvist
- Division of Physiotherapy, Division of Neurology, Department of Clinical Neuroscience, Karolinska Institutet, and Academic Specialist Center, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Ada Trepci
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Jesse Huang
- Division of Physiotherapy, Division of Neurology, Department of Clinical Neuroscience, Karolinska Institutet, and Academic Specialist Center, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Lilly Schwieler
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Marie Kierkegaard
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Academic Specialist Center, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Sophie Erhardt
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Jussi Jokinen
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, and Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.,Department of Clinical Sciences, Umeå University, Umeå, Sweden
| | - Fredrik Piehl
- Division of Physiotherapy, Division of Neurology, Department of Clinical Neuroscience, Karolinska Institutet, and Academic Specialist Center, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
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