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Published in: Cardiovascular Drugs and Therapy 4/2019

01-08-2019 | Obesity | ORIGINAL ARTICLE

Obesity-Related Genetic Determinants of Heart Failure Prognosis

Authors: R. M. Agra, M. Gago-Dominguez, B. Paradela-Dobarro, M. Torres-Español, L. Alvarez, A. Fernandez-Trasancos, A. Varela-Roman, M. Calaza, S. Eiras, E. Alvarez, A. Carracedo, J. R. Gonzalez-Juanatey

Published in: Cardiovascular Drugs and Therapy | Issue 4/2019

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Abstract

Purpose

Recent advances in genomics offer a smart option for predicting future risk of disease and prognosis. The objective of this study was to examine the prognostic value in heart failure (HF) patients, of a series of single nucleotide polymorphisms (SNPs).

Methods

A selection of 192 SNPs found to be related with obesity, body mass index, circulating lipids or cardiovascular diseases were genotyped in 191 patients with HF. Anthropometrical and clinical variables were collected for each patient, and death and readmission by HF were registered as the primary endpoint.

Results

A total of 53 events were registered during a follow-up period of 438 (263–1077) days (median (IQR)). Eight SNPs strongly related to obesity and HF prognosis were selected as possible prognostic variables. From these, rs10189761 and rs737337 variants were independently associated with HF prognosis (HR 2.295 (1.287–4.089, 95% CI); p = 0.005), whereas rs10423928, rs1800437, rs737337 and rs9351814 were related with bad prognosis only in obese patients (HR 2.142 (1.438–3.192, 95% CI); p = 0.00018). Combined scores of the genomic variants were highly predictive of poor prognosis.

Conclusions

SNPs rs10189761 and rs737337 were identified, for the first time, as independent predictors of major clinical outcomes in patients with HF. The data suggests an additive predictive value of these SNPs for a HF prognosis. In particular for obese patients, SNPs rs10423928, rs1800437, rs737337 and rs9351814 were related with a bad prognosis. Combined scores weighting the risk of each genomic variant could effect interesting new tools to stratify the prognostic risk of HF patients.
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Literature
1.
go back to reference Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JG, Coats AJ, et al. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur J Heart Fail. 2016;18(8):891–975.CrossRefPubMed Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JG, Coats AJ, et al. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur J Heart Fail. 2016;18(8):891–975.CrossRefPubMed
2.
go back to reference Krumholz HM, Chen YT, Wang Y, Vaccarino V, Radford MJ, Horwitz RI. Predictors of readmission among elderly survivors of admission with heart failure. Am Heart J. 2000;139(1 Pt 1):72–7.CrossRefPubMed Krumholz HM, Chen YT, Wang Y, Vaccarino V, Radford MJ, Horwitz RI. Predictors of readmission among elderly survivors of admission with heart failure. Am Heart J. 2000;139(1 Pt 1):72–7.CrossRefPubMed
3.
go back to reference Go AS, Mozaffarian D, Roger VL, Benjamin EJ, Berry JD, Borden WB, et al. Heart disease and stroke statistics--2013 update: a report from the American Heart Association. Circulation. 2013;127(1):e6–e245.PubMed Go AS, Mozaffarian D, Roger VL, Benjamin EJ, Berry JD, Borden WB, et al. Heart disease and stroke statistics--2013 update: a report from the American Heart Association. Circulation. 2013;127(1):e6–e245.PubMed
4.
6.
go back to reference Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature. 2010;466(7307):707–13.CrossRefPubMedPubMedCentral Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature. 2010;466(7307):707–13.CrossRefPubMedPubMedCentral
7.
go back to reference Willer CJ, Schmidt EM, Sengupta S, Peloso GM, Gustafsson S, Kanoni S, et al. Discovery and refinement of loci associated with lipid levels. Nat Genet. 2013;45(11):1274–83.CrossRefPubMedPubMedCentral Willer CJ, Schmidt EM, Sengupta S, Peloso GM, Gustafsson S, Kanoni S, et al. Discovery and refinement of loci associated with lipid levels. Nat Genet. 2013;45(11):1274–83.CrossRefPubMedPubMedCentral
8.
go back to reference Lavie CJ, Sharma A, Alpert MA, De Schutter A, Lopez-Jimenez F, Milani RV, et al. Update on obesity and obesity paradox in heart failure. Prog Cardiovasc Dis. 2016;58(4):393–400.CrossRefPubMed Lavie CJ, Sharma A, Alpert MA, De Schutter A, Lopez-Jimenez F, Milani RV, et al. Update on obesity and obesity paradox in heart failure. Prog Cardiovasc Dis. 2016;58(4):393–400.CrossRefPubMed
9.
go back to reference Kenchaiah S, Evans JC, Levy D, Wilson PW, Benjamin EJ, Larson MG, et al. Obesity and the risk of heart failure. N Engl J Med. 2002;347(5):305–13.CrossRefPubMed Kenchaiah S, Evans JC, Levy D, Wilson PW, Benjamin EJ, Larson MG, et al. Obesity and the risk of heart failure. N Engl J Med. 2002;347(5):305–13.CrossRefPubMed
10.
go back to reference Reis JP, Allen N, Gunderson EP, Lee JM, Lewis CE, Loria CM, et al. Excess body mass index- and waist circumference-years and incident cardiovascular disease: the CARDIA study. Obesity (Silver Spring). 2015;23(4):879–85.CrossRef Reis JP, Allen N, Gunderson EP, Lee JM, Lewis CE, Loria CM, et al. Excess body mass index- and waist circumference-years and incident cardiovascular disease: the CARDIA study. Obesity (Silver Spring). 2015;23(4):879–85.CrossRef
11.
go back to reference Horwich TB, Fonarow GC, Hamilton MA, MacLellan WR, Woo MA, Tillisch JH. The relationship between obesity and mortality in patients with heart failure. J Am Coll Cardiol. 2001;38(3):789–95.CrossRefPubMed Horwich TB, Fonarow GC, Hamilton MA, MacLellan WR, Woo MA, Tillisch JH. The relationship between obesity and mortality in patients with heart failure. J Am Coll Cardiol. 2001;38(3):789–95.CrossRefPubMed
12.
go back to reference Sharma A, Lavie CJ, Borer JS, Vallakati A, Goel S, Lopez-Jimenez F, et al. Meta-analysis of the relation of body mass index to all-cause and cardiovascular mortality and hospitalization in patients with chronic heart failure. Am J Cardiol. 2015;115(10):1428–34.CrossRefPubMed Sharma A, Lavie CJ, Borer JS, Vallakati A, Goel S, Lopez-Jimenez F, et al. Meta-analysis of the relation of body mass index to all-cause and cardiovascular mortality and hospitalization in patients with chronic heart failure. Am J Cardiol. 2015;115(10):1428–34.CrossRefPubMed
13.
go back to reference Lavie CJ, Osman AF, Milani RV, Mehra MR. Body composition and prognosis in chronic systolic heart failure: the obesity paradox. Am J Cardiol. 2003;91(7):891–4.CrossRefPubMed Lavie CJ, Osman AF, Milani RV, Mehra MR. Body composition and prognosis in chronic systolic heart failure: the obesity paradox. Am J Cardiol. 2003;91(7):891–4.CrossRefPubMed
14.
go back to reference Clark AL, Fonarow GC, Horwich TB. Waist circumference, body mass index, and survival in systolic heart failure: the obesity paradox revisited. J Card Fail. 2011;17(5):374–80.CrossRefPubMed Clark AL, Fonarow GC, Horwich TB. Waist circumference, body mass index, and survival in systolic heart failure: the obesity paradox revisited. J Card Fail. 2011;17(5):374–80.CrossRefPubMed
15.
go back to reference Khalid U, Ather S, Bavishi C, Chan W, Loehr LR, Wruck LM, et al. Pre-morbid body mass index and mortality after incident heart failure: the ARIC study. J Am Coll Cardiol. 2014;64(25):2743–9.CrossRefPubMedPubMedCentral Khalid U, Ather S, Bavishi C, Chan W, Loehr LR, Wruck LM, et al. Pre-morbid body mass index and mortality after incident heart failure: the ARIC study. J Am Coll Cardiol. 2014;64(25):2743–9.CrossRefPubMedPubMedCentral
16.
go back to reference American Diabetes Association (Corporate Author). 2. Classification and diagnosis of diabetes: standards of medical care in diabetes-2018. Diabetes Care. 2018;41(Suppl 1):S13–27. American Diabetes Association (Corporate Author). 2. Classification and diagnosis of diabetes: standards of medical care in diabetes-2018. Diabetes Care. 2018;41(Suppl 1):S13–27.
17.
go back to reference Dichgans M, Malik R, Konig IR, Rosand J, Clarke R, Gretarsdottir S, et al. Shared genetic susceptibility to ischemic stroke and coronary artery disease: a genome-wide analysis of common variants. Stroke. 2014;45(1):24–36.CrossRefPubMed Dichgans M, Malik R, Konig IR, Rosand J, Clarke R, Gretarsdottir S, et al. Shared genetic susceptibility to ischemic stroke and coronary artery disease: a genome-wide analysis of common variants. Stroke. 2014;45(1):24–36.CrossRefPubMed
18.
go back to reference Ikram MA, Seshadri S, Bis JC, Fornage M, DeStefano AL, Aulchenko YS, et al. Genomewide association studies of stroke. N Engl J Med. 2009;360(17):1718–28.CrossRefPubMedPubMedCentral Ikram MA, Seshadri S, Bis JC, Fornage M, DeStefano AL, Aulchenko YS, et al. Genomewide association studies of stroke. N Engl J Med. 2009;360(17):1718–28.CrossRefPubMedPubMedCentral
19.
go back to reference Gretarsdottir S, Thorleifsson G, Manolescu A, Styrkarsdottir U, Helgadottir A, Gschwendtner A, et al. Risk variants for atrial fibrillation on chromosome 4q25 associate with ischemic stroke. Ann Neurol. 2008;64(4):402–9.CrossRefPubMed Gretarsdottir S, Thorleifsson G, Manolescu A, Styrkarsdottir U, Helgadottir A, Gschwendtner A, et al. Risk variants for atrial fibrillation on chromosome 4q25 associate with ischemic stroke. Ann Neurol. 2008;64(4):402–9.CrossRefPubMed
20.
go back to reference Matarin M, Brown WM, Scholz S, Simon-Sanchez J, Fung HC, Hernandez D, et al. A genome-wide genotyping study in patients with ischaemic stroke: initial analysis and data release. Lancet Neurol. 2007;6(5):414–20.CrossRefPubMedPubMedCentral Matarin M, Brown WM, Scholz S, Simon-Sanchez J, Fung HC, Hernandez D, et al. A genome-wide genotyping study in patients with ischaemic stroke: initial analysis and data release. Lancet Neurol. 2007;6(5):414–20.CrossRefPubMedPubMedCentral
21.
go back to reference Traylor M, Farrall M, Holliday EG, Sudlow C, Hopewell JC, Cheng YC, et al. Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE collaboration): a meta-analysis of genome-wide association studies. Lancet Neurol. 2012;11(11):951–62.CrossRefPubMedPubMedCentral Traylor M, Farrall M, Holliday EG, Sudlow C, Hopewell JC, Cheng YC, et al. Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE collaboration): a meta-analysis of genome-wide association studies. Lancet Neurol. 2012;11(11):951–62.CrossRefPubMedPubMedCentral
22.
go back to reference Holliday EG, Maguire JM, Evans TJ, Koblar SA, Jannes J, Sturm JW, et al. Common variants at 6p21.1 are associated with large artery atherosclerotic stroke. Nat Genet. 2012;44(10):1147–51.CrossRefPubMed Holliday EG, Maguire JM, Evans TJ, Koblar SA, Jannes J, Sturm JW, et al. Common variants at 6p21.1 are associated with large artery atherosclerotic stroke. Nat Genet. 2012;44(10):1147–51.CrossRefPubMed
23.
go back to reference Bellenguez C, Bevan S, Gschwendtner A, Spencer CC, Burgess AI, Pirinen M, et al. Genome-wide association study identifies a variant in HDAC9 associated with large vessel ischemic stroke. Nat Genet. 2012;44(3):328–33.CrossRefPubMed Bellenguez C, Bevan S, Gschwendtner A, Spencer CC, Burgess AI, Pirinen M, et al. Genome-wide association study identifies a variant in HDAC9 associated with large vessel ischemic stroke. Nat Genet. 2012;44(3):328–33.CrossRefPubMed
24.
go back to reference El-Sayed Moustafa JS, Froguel P. From obesity genetics to the future of personalized obesity therapy. Nat Rev Endocrinol. 2013;9(7):402–13.CrossRefPubMed El-Sayed Moustafa JS, Froguel P. From obesity genetics to the future of personalized obesity therapy. Nat Rev Endocrinol. 2013;9(7):402–13.CrossRefPubMed
25.
go back to reference Rudolph A, Milne RL, Truong T, Knight JA, Seibold P, Flesch-Janys D, et al. Investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors. Int J Cancer. 2015;136(6):E685–96.CrossRefPubMed Rudolph A, Milne RL, Truong T, Knight JA, Seibold P, Flesch-Janys D, et al. Investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors. Int J Cancer. 2015;136(6):E685–96.CrossRefPubMed
26.
go back to reference R: a language and environment for statistical computing. R Foundation for Statistical Computing, Viena, Austria. URL https://www.R-project.org/. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Viena, Austria. URL https://www.​R-project.​org/.
27.
go back to reference Nakagomi A, Seino Y, Noma S, Kohashi K, Kosugi M, Kato K, et al. Relationships between the serum cholesterol levels, production of monocyte proinflammatory cytokines and long-term prognosis in patients with chronic heart failure. Intern Med. 2014;53(21):2415–24 DN/JST.JSTAGE/internalmedicine/53.2672.CrossRefPubMed Nakagomi A, Seino Y, Noma S, Kohashi K, Kosugi M, Kato K, et al. Relationships between the serum cholesterol levels, production of monocyte proinflammatory cytokines and long-term prognosis in patients with chronic heart failure. Intern Med. 2014;53(21):2415–24 DN/JST.JSTAGE/internalmedicine/53.2672.CrossRefPubMed
28.
go back to reference Kahn MR, Kosmas CE, Wagman G, Serrao GW, Fallahi A, Grady KM, et al. Low-density lipoprotein levels in patients with acute heart failure. Congest Heart Fail. 2013;19(2):85–91.CrossRefPubMed Kahn MR, Kosmas CE, Wagman G, Serrao GW, Fallahi A, Grady KM, et al. Low-density lipoprotein levels in patients with acute heart failure. Congest Heart Fail. 2013;19(2):85–91.CrossRefPubMed
29.
go back to reference Berndt SI, Gustafsson S, Magi R, Ganna A, Wheeler E, Feitosa MF, et al. Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nat Genet. 2013;45(5):501–12.CrossRefPubMedPubMedCentral Berndt SI, Gustafsson S, Magi R, Ganna A, Wheeler E, Feitosa MF, et al. Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nat Genet. 2013;45(5):501–12.CrossRefPubMedPubMedCentral
30.
go back to reference den Hoed M, Ekelund U, Brage S, Grontved A, Zhao JH, Sharp SJ, et al. Genetic susceptibility to obesity and related traits in childhood and adolescence: influence of loci identified by genome-wide association studies. Diabetes. 2010;59(11):2980–8.CrossRef den Hoed M, Ekelund U, Brage S, Grontved A, Zhao JH, Sharp SJ, et al. Genetic susceptibility to obesity and related traits in childhood and adolescence: influence of loci identified by genome-wide association studies. Diabetes. 2010;59(11):2980–8.CrossRef
31.
go back to reference Holzapfel C, Grallert H, Huth C, Wahl S, Fischer B, Doring A, et al. Genes and lifestyle factors in obesity: results from 12,462 subjects from MONICA/KORA. Int J Obes. 2010;34(10):1538–45.CrossRef Holzapfel C, Grallert H, Huth C, Wahl S, Fischer B, Doring A, et al. Genes and lifestyle factors in obesity: results from 12,462 subjects from MONICA/KORA. Int J Obes. 2010;34(10):1538–45.CrossRef
32.
go back to reference Almen MS, Jacobsson JA, Shaik JH, Olszewski PK, Cedernaes J, Alsio J, et al. The obesity gene, TMEM18, is of ancient origin, found in majority of neuronal cells in all major brain regions and associated with obesity in severely obese children. BMC Med Genet. 2010;11:58.CrossRefPubMedPubMedCentral Almen MS, Jacobsson JA, Shaik JH, Olszewski PK, Cedernaes J, Alsio J, et al. The obesity gene, TMEM18, is of ancient origin, found in majority of neuronal cells in all major brain regions and associated with obesity in severely obese children. BMC Med Genet. 2010;11:58.CrossRefPubMedPubMedCentral
34.
go back to reference Tang CS, Zhang H, Cheung CY, Xu M, Ho JC, Zhou W, et al. Exome-wide association analysis reveals novel coding sequence variants associated with lipid traits in Chinese. Nat Commun. 2015;6:10206.CrossRefPubMed Tang CS, Zhang H, Cheung CY, Xu M, Ho JC, Zhou W, et al. Exome-wide association analysis reveals novel coding sequence variants associated with lipid traits in Chinese. Nat Commun. 2015;6:10206.CrossRefPubMed
35.
go back to reference Dijk W, Kersten S. Regulation of lipid metabolism by angiopoietin-like proteins. Curr Opin Lipidol. 2016;27(3):249–56.CrossRefPubMed Dijk W, Kersten S. Regulation of lipid metabolism by angiopoietin-like proteins. Curr Opin Lipidol. 2016;27(3):249–56.CrossRefPubMed
37.
go back to reference Gomez-Ambrosi J, Pascual-Corrales E, Catalan V, Rodriguez A, Ramirez B, Romero S, et al. Altered concentrations in dyslipidemia evidence a role for ANGPTL8/betatrophin in lipid metabolism in humans. J Clin Endocrinol Metab. 2016;101(10):3803–11.CrossRefPubMed Gomez-Ambrosi J, Pascual-Corrales E, Catalan V, Rodriguez A, Ramirez B, Romero S, et al. Altered concentrations in dyslipidemia evidence a role for ANGPTL8/betatrophin in lipid metabolism in humans. J Clin Endocrinol Metab. 2016;101(10):3803–11.CrossRefPubMed
38.
go back to reference Maurer L, Brachs S, Decker AM, Brachs M, Leupelt V, Jumpertz von Schwartzenberg R, et al. Weight loss partially restores glucose-driven Betatrophin response in humans. J Clin Endocrinol Metab. 2016;101(11):4014–20.CrossRefPubMed Maurer L, Brachs S, Decker AM, Brachs M, Leupelt V, Jumpertz von Schwartzenberg R, et al. Weight loss partially restores glucose-driven Betatrophin response in humans. J Clin Endocrinol Metab. 2016;101(11):4014–20.CrossRefPubMed
39.
go back to reference McIntosh CH, Widenmaier S, Kim SJ. Pleiotropic actions of the incretin hormones. Vitam Horm. 2010;84:21–79.CrossRefPubMed McIntosh CH, Widenmaier S, Kim SJ. Pleiotropic actions of the incretin hormones. Vitam Horm. 2010;84:21–79.CrossRefPubMed
40.
go back to reference Berglund LM, Lyssenko V, Ladenvall C, Kotova O, Edsfeldt A, Pilgaard K, et al. Glucose-dependent insulinotropic polypeptide stimulates osteopontin expression in the vasculature via endothelin-1 and CREB. Diabetes. 2016;65(1):239–54.PubMed Berglund LM, Lyssenko V, Ladenvall C, Kotova O, Edsfeldt A, Pilgaard K, et al. Glucose-dependent insulinotropic polypeptide stimulates osteopontin expression in the vasculature via endothelin-1 and CREB. Diabetes. 2016;65(1):239–54.PubMed
41.
go back to reference Ussher JR, Campbell JE, Mulvihill EE, Baggio LL, Bates HE, McLean BA, et al. Inactivation of the glucose-dependent Insulinotropic polypeptide receptor improves outcomes following experimental myocardial infarction. Cell Metab. 2018;27(2):450–60 e6.CrossRefPubMed Ussher JR, Campbell JE, Mulvihill EE, Baggio LL, Bates HE, McLean BA, et al. Inactivation of the glucose-dependent Insulinotropic polypeptide receptor improves outcomes following experimental myocardial infarction. Cell Metab. 2018;27(2):450–60 e6.CrossRefPubMed
Metadata
Title
Obesity-Related Genetic Determinants of Heart Failure Prognosis
Authors
R. M. Agra
M. Gago-Dominguez
B. Paradela-Dobarro
M. Torres-Español
L. Alvarez
A. Fernandez-Trasancos
A. Varela-Roman
M. Calaza
S. Eiras
E. Alvarez
A. Carracedo
J. R. Gonzalez-Juanatey
Publication date
01-08-2019
Publisher
Springer US
Published in
Cardiovascular Drugs and Therapy / Issue 4/2019
Print ISSN: 0920-3206
Electronic ISSN: 1573-7241
DOI
https://doi.org/10.1007/s10557-019-06888-8

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