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Current Cardiology Reviews

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ISSN (Print): 1573-403X
ISSN (Online): 1875-6557

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Meta-Analysis

Galectin-3 is Associated with Heart Failure Incidence: A Meta-Analysis

Author(s): Basil M. Baccouche*, Mattia A. Mahmoud, Corrine Nief, Karan Patel and Barbara Natterson-Horowitz

Volume 19, Issue 3, 2023

Published on: 17 January, 2023

Article ID: e171122211004 Pages: 13

DOI: 10.2174/1573403X19666221117122012

Price: $65

Abstract

Introduction: Heart failure (HF) is a leading cause of death worldwide. The global prevalence of heart failure is projected to increase rapidly in the coming decades, and significant attention has turned to improving biomarker-based risk prediction of incident HF. This paper aimed to qualitatively and quantitatively evaluate the evidence associating levels of galectin-3 with the risk of incident HF.

Methods: A review of PUBMED-indexed peer-reviewed literature was performed. Nine studies met the inclusion criteria, and all nine had data eligible for conversion and pooling. A randomeffects meta-analysis was performed using hazard ratios and 95% confidence intervals from a minimally adjusted model, a further adjusted model, and from subgroups within the further-adjusted model.

Results: The minimally-adjusted model provided an HR of 1.97 (95% CI 1.74-2.23) when comparing the top quartile of log-gal-3 to the bottom quartile. The further-adjusted model provided an HR of 1.32 (95% CI 1.21-1.44) for the same comparison. The positive, significant association was conserved during sensitivity analysis.

Conclusion: There is a significant positive association between circulating galectin-3 and the risk of incident heart failure. Given the complex mechanistic relationship between galectin-3 and cardiovascular pathophysiology, further investigation is recommended for the possible implementation of galectin-3 into clinical risk prediction models.

Keywords: Incident HF, heart failure, cardiovascular disease, biomarker, galectin-3, hazard ratio, risk ratio.

[1]
Heron M. Deaths: Leading causes for 2017. Natl Vital Stat Rep 2019; 68(6): 1-77.
[PMID: 32501203]
[2]
Ahmad FB, Anderson RN. The leading causes of death in the US for 2020. JAMA 2021; 325(18): 1829-30.
[http://dx.doi.org/10.1001/jama.2021.5469] [PMID: 33787821]
[3]
Inamdar A, Inamdar A. Heart failure: Diagnosis, management and utilization. J Clin Med 2016; 5(7): 62.
[http://dx.doi.org/10.3390/jcm5070062] [PMID: 27367736]
[4]
Baccouche BM, Natterson-Horowitz B. Giraffe myocardial hypertrophy as an evolved adaptation and natural animal model of resistance to diastolic heart failure in humans. Preprint 2019.
[5]
Natterson-Horowitz B, Baccouche BM, Head JM, et al. Did giraffe cardiovascular evolution solve the problem of heart failure with preserved ejection fraction? Evol Med Public Health 2021; 9(1): 248-55.
[http://dx.doi.org/10.1093/emph/eoab016] [PMID: 34447575]
[6]
Baccouche BM. The burden of heart failure with preserved ejection fraction in American women is growing: An epidemiological review. NMJ Sci 2021; 55: 1-10.
[7]
Savarese G, Lund LH. Global public health burden of heart failure. Card Fail Rev 2017; 3(1): 7-11.
[http://dx.doi.org/10.15420/cfr.2016:25:2] [PMID: 28785469]
[8]
Dong R, Zhang M, Hu Q, et al. Galectin-3 as a novel biomarker for disease diagnosis and a target for therapy. Int J Mol Med 2018; 41(2): 599-614.
[PMID: 29207027]
[9]
Suthahar N, Meijers WC, Silljé HHW, Ho JE, Liu FT, de Boer RA. Galectin-3 activation and inhibition in heart failure and cardiovascular disease: An update. Theranostics 2018; 8(3): 593-609.
[http://dx.doi.org/10.7150/thno.22196] [PMID: 29344292]
[10]
Ziaeian B, Fonarow GC. Epidemiology and aetiology of heart failure. Nat Rev Cardiol 2016; 13(6): 368-78.
[http://dx.doi.org/10.1038/nrcardio.2016.25] [PMID: 26935038]
[11]
Ilieșiu AM, Hodorogea AS. Treatment of heart failure with preserved ejection fraction. Adv Exp Med Biol 2018; 1067: 67-87.
[http://dx.doi.org/10.1007/5584_2018_149] [PMID: 29498023]
[12]
Howard BE, Phillips J, Miller K, et al. Swift-review: A text-mining workbench for systematic review. Syst Rev 2016; 5(1): 87.
[http://dx.doi.org/10.1186/s13643-016-0263-z] [PMID: 27216467]
[13]
Baccouche BM, Shivkumar TE. Using swift-review as a new and robust tool for comprehensive systematic review. NMJ Sci 2020; 5: 87.
[14]
Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ 2009; 339(1): b2535.
[http://dx.doi.org/10.1136/bmj.b2535] [PMID: 19622551]
[15]
de Boer RA, Nayor M, deFilippi CR, et al. Association of cardiovascular biomarkers with incident heart failure with preserved and reduced ejection fraction. JAMA Cardiol 2018; 3(3): 215-24.
[http://dx.doi.org/10.1001/jamacardio.2017.4987] [PMID: 29322198]
[16]
Kaptoge S. Stata Programs.. Cardiovascular Epidemiology Unit. 2005. Available from: https://www.phpc.cam.ac.uk/ceu/erfc/programs/
[17]
Stata | StataCorp LLC. Available from: https://www.stata.com/company/
[18]
Asleh R, Enriquez-Sarano M, Jaffe AS, et al. Galectin-3 levels and outcomes after myocardial infarction. J Am Coll Cardiol 2019; 73(18): 2286-95.
[http://dx.doi.org/10.1016/j.jacc.2019.02.046] [PMID: 31072572]
[19]
Bansal N, Zelnick L, Go A, et al. Cardiac biomarkers and risk of incident heart failure in chronic kidney disease: The CRIC (Chronic Renal Insufficiency Cohort) study. J Am Heart Assoc 2019; 8(21): e012336.
[http://dx.doi.org/10.1161/JAHA.119.012336] [PMID: 31645163]
[20]
Chêne G, Thompson SG. Methods for summarizing the risk associations of quantitative variables in epidemiologic studies in a consistent form. Am J Epidemiol 1996; 144(6): 610-21.
[http://dx.doi.org/10.1093/oxfordjournals.aje.a008971] [PMID: 8797521]
[21]
Ho JE, Liu C, Lyass A, et al. Galectin-3, a marker of cardiac fibrosis, predicts incident heart failure in the community. J Am Coll Cardiol 2012; 60(14): 1249-56.
[http://dx.doi.org/10.1016/j.jacc.2012.04.053] [PMID: 22939561]
[22]
Djoussé L, Matsumoto C, Petrone A, Weir NL, Tsai MY, Gaziano JM. Plasma galectin 3 and heart failure risk in the Physicians’ Health Study. Eur J Heart Fail 2014; 16(3): 350-4.
[http://dx.doi.org/10.1002/ejhf.21] [PMID: 24464746]
[23]
Brouwers FP, van Gilst WH, Damman K, et al. Clinical risk stratification optimizes value of biomarkers to predict new-onset heart failure in a community-based cohort. Circ Heart Fail 2014; 7(5): 723-31.
[http://dx.doi.org/10.1161/CIRCHEARTFAILURE.114.001185] [PMID: 25057112]
[24]
Jagodzinski A, Havulinna AS, Appelbaum S, et al. Predictive value of galectin-3 for incident cardiovascular disease and heart failure in the population-based FINRISK 1997 cohort. Int J Cardiol 2015; 192: 33-9.
[http://dx.doi.org/10.1016/j.ijcard.2015.05.040] [PMID: 25985013]
[25]
AbouEzzeddine OF, McKie PM, Scott CG, et al. Biomarker-based risk prediction in the community. Eur J Heart Fail 2016; 18(11): 1342-50.
[http://dx.doi.org/10.1002/ejhf.663] [PMID: 27813304]
[26]
Aguilar D, Sun C, Hoogeveen RC, et al. Levels and change in galectin-3 and association with cardiovascular events: The ARIC study. J Am Heart Assoc 2020; 9(13): e015405.
[http://dx.doi.org/10.1161/JAHA.119.015405] [PMID: 32573308]
[27]
International Classification of Diseases, Ninth Revision. 2015. Available from: http://www.cdc.gov/nchs/icd/icd9.htm
[28]
Mähönen M, Jula A, Harald K, et al. The validity of heart failure diagnoses obtained from administrative registers. Eur J Prev Cardiol 2013; 20(2): 254-9.
[http://dx.doi.org/10.1177/2047487312438979] [PMID: 22345696]
[29]
Alhajj M, Farhana A. Enzyme Linked Immunosorbent Assay. StatPearls. StatPearls Publishing 2021.
[30]
Cinquanta L, Fontana DE, Bizzaro N. Chemiluminescent immunoassay technology: What does it change in autoantibody detection? Auto Immun Highlights 2017; 8(1): 9.
[http://dx.doi.org/10.1007/s13317-017-0097-2] [PMID: 28647912]
[31]
McKee PA, Castelli WP, McNamara PM, Kannel WB. The natural history of congestive heart failure: The Framingham study. N Engl J Med 1971; 285(26): 1441-6.
[http://dx.doi.org/10.1056/NEJM197112232852601] [PMID: 5122894]
[32]
Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J 2016; 37(27): 2129-200.
[http://dx.doi.org/10.1093/eurheartj/ehw128] [PMID: 27206819]
[33]
Fried LP, Borhani NO, Enright P, et al. The cardiovascular health study: Design and rationale. Ann Epidemiol 1991; 1(3): 263-76.
[http://dx.doi.org/10.1016/1047-2797(91)90005-W] [PMID: 1669507]
[34]
Wells G. Ottawa Hospital Research Institute.. The Newcastle- Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. 2015. Available from: http://www.ohri.ca/programs/clinical_ epidemiology/ oxford.asp

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