Vol. 27 No. 4 (2023)
PATHOPHYSIOLOGY

Genetic predictors of abdominal complications after cardiac surgery: a prospective study

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  • D.V. Belov,
  • O.S. Abramovskikh,
  • M.A. Zotova,
  • Yu.V. Loginova,
  • A.A. Fokin
D.V. Belov
South Ural State Medical University, Ministry of Health of Russian Federation, Chelyabinsk; Federal Center for Cardiovascular Surgery, Ministry of Health of Russian Federation, Chelyabinsk, Russian Federation
Bio
O.S. Abramovskikh
South Ural State Medical University, Ministry of Health of Russian Federation, Chelyabinsk
M.A. Zotova
South Ural State Medical University, Ministry of Health of Russian Federation, Chelyabinsk
Yu.V. Loginova
South Ural State Medical University, Ministry of Health of Russian Federation, Chelyabinsk
A.A. Fokin
South Ural State Medical University, Ministry of Health of Russian Federation, Chelyabinsk
Frequency of abdominal complications in patients enrolled in the molecular genetic study
DOI: https://doi.org/10.21688/1681-3472-2023-4-77-88

Published 2023-12-26

Keywords

  • Alleles,
  • Genes,
  • Genotype,
  • Polymorphism, Single Nucleotide,
  • Prospective Studies,
  • Real-Time Polymerase Chain Reaction
    • ...More
    Less

How to Cite

Belov, D., Abramovskikh, O., Zotova, M., Loginova, Y., & Fokin, A. (2023). Genetic predictors of abdominal complications after cardiac surgery: a prospective study. Patologiya Krovoobrashcheniya I Kardiokhirurgiya, 27(4), 77–88. https://doi.org/10.21688/1681-3472-2023-4-77-88

Copyright (c) 2023 Belov D.V., Abramovskikh O.S., Zotova M.A., Loginova Yu.V., Fokin A.A.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Introduction: The prediction of postoperative abdominal complications is a continuing concern in the cardiac surgery. Identifying genetic predictors will allow a better understanding of the pathophysiological mechanisms underlying postoperative disorders and their prevention.
Objective: To identify genetic predictors of abdominal complications after heart surgery.
Methods: A prospective study was carried out at the Federal Center for Cardiovascular Surgery (Chelyabinsk) involving 72 patients with abdominal complications and 102 controls without such complications. The distribution of genotypes was assessed for adherence to the Hardy-Weinberg distribution using the exact method according to the SNP-HWE algorithm in the PLINK package (version 1.9). To identify marker genes associated with the risk of abdominal complications, 6 models were evaluated for each polymorphic gene: allelic, codominant, dominant, recessive, overdominant, and log-additive. To analyze the SNPs of the IL6 (rs1800795), TNF (rs1800629), and SERPINE1 (rs1799768) genes, real-time polymerase chain reaction (PCR) was performed on a Rotor-Gene 6000 detecting cycler (Corbett Research Pty Ltd., Mortlake, Australia) using primers and probes manufactured by Syntol CJSC (Moscow, Russia) according to the manufacturer's instructions. To analyze the SNPs of the IL1B (rs1143634), CXCL8 (rs4073), IL10 (rs1800872), APOE (rs429358), FABP2 (rs1799883), NOS3 (rs1799983), VEGFA (rs699947) genes, real-time PCR was performed on a DTprime 4 analyzer (DNA-Technology, Moscow, Russia) using primers and probes manufactured by TestGene LLC (Ulyanovsk, Russia) according to the manufacturer's instructions. The determination of the SNP of the TLR3 gene (rs3775291) relied on real-time PCR according to melting curves using TestGene LLC reagent kits on a DTprime 4 device.
Results: Two genes, IL1B rs1143634 and FABP2 rs1799883, were found to be associated with the risk of abdominal complications. Following the adjustment for multiple comparisons, only FABP2 rs1799883 remained statistically significant. The rs1799883 polymorphism of the FABP2 gene can be considered a predictor of the risk of abdominal complications and can be evaluated within the codominant and dominant models, which exhibit similar p-values (0.003 and 0.002, respectively). Overall, the analysis of the obtained data suggests that the risk of abdominal complications is associated with the presence of the mutant allele C in the genome, likely due to its dominance. Specifically, in the dominant model, the odds ratio was 3.53 (95% CI 1.62 to 7.70).
Conclusion: The most significant markers of the risk of abdominal complications were the IL1B (rs1143634) and FABP2 (rs1799883) genes, of which FABP2 (rs1799883) remained statistically significant after adjusting for multiple comparisons. Its polymorphism as a predictor of abdominal complications can be evaluated within the codominant and dominant models.

Received 13 June 2023. Revised 28 November 2023. Accepted 29 November 2023.

Funding: The study was supported by the Russian Science Foundation, project No. 22-25-20016, https://rscf.ru/project/22-25-20016/

Conflict of interest: The authors declare no conflict of interest.

Contribution of the authors
Conception and study design: O.S. Abramovskikh, A.A. Fokin, D.V. Belov
Data collection and analysis: Yu.V. Loginova
Statistical analysis: M.A. Zotova
Drafting the article: D.V. Belov
Critical revision of the article: Yu.V. Loginova
Final approval of the version to be published: D.V. Belov, O.S. Abramovskikh, M.A. Zotova, Yu.V. Loginova, A.A. Fokin

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References

  1. Кокшенева И.В., Закарая И.Т., Малороева А.И. Генетические факторы риска развития периоперационного инфаркта миокарда. Часть 2. Клиническая физиология кровообращения. 2021;18(2):109-117. https://dx.doi.org/10.24022/1814-6910-2021-18-2-109-117 Koksheneva I.V., Zakaraya I.T., Maloroeva A.I. Genetic risk factors of perioperative myocardial infarction. Part 2. Klinicheskaya fiziologiya krovoobrashcheniya = Clinical Physiology of Circulation. 2021;18(2):109-117. (In Russ.) https://dx.doi.org/10.24022/1814-6910-2021-18-2-109-117
  2. Кокшенева И.В., Закарая И.Т. Генетические маркеры риска неврологических осложнений в кардиохирургии. Часть 3. Клиническая физиология кровообращения. 2021;18(3):193-200. https://dx.doi.org/10.24022/1814-6910-2021-18-3-193-200 Koksheneva I.V., Zakaraya I.T. Genetic markers of risk of neurological complications in cardiac surgery. Part 3. Klinicheskaya fiziologiya krovoobrashcheniya = Clinical Physiology of Circulation. 2021;18(3):193-200. (In Russ.) https://dx.doi.org/10.24022/1814-6910-2021-18-3-193-200
  3. Белов Д.В., Лукин О.П., Фокин А.А., Абрамовских О.С., Наймушина Ю.В. Абдоминальные осложнения после операций на сердце в условиях искусственного кровообращения: анализ данных за 2011–2021 гг. Клиническая и экспериментальная хирургия. Журнал имени академика Б.В. Петровского. 2022;10(1):96-102. https://dx.doi.org/10.33029/2308-1198-2022-10-1-96-102 Belov D.V., Lukin O.P., Fokin A.A., Abramovskikh O.S., Naimushina Yu.V. Abdominal complications after cardiopulmonary bypass surgery: data analysis for 2011–2021. Clinical and Experimental Surgery. Petrovsky Journal. 2022;10(1):96-102. (In Russ.) https://dx.doi.org/10.33029/2308-1198-2022-10-1-96-102
  4. Кутихин А.Г., Южалин А.Е., Понасенко А.В. Современные тенденции статистической обработки данных и представления результатов в кандидатных генетико-эпидемиологических исследованиях. Фундаментальная и клиническая медицина. 2017;2(2):77-82. https://doi.org/10.23946/2500-0764-2017-2-2-77-82 Kutikhin A.G., Yuzhalin A.E., Ponasenko A.V. How to analyze and present genetic epidemiology data in candidate studies. Fundamental and Clinical Medicine. 2017;2(2):77-82. (In Russ.) https://doi.org/10.23946/2500-0764-2017-2-2-77-82
  5. Gholamipoor Z., Rahimzadeh M., Montazerghaem H., Naderi N. RORC gene polymorphism is associated with acute kidney injury following cardiac surgery. Acta Anaesthesiol Scand. 2021;65(10):1397-1403. PMID: 34252205. https://dx.doi.org/10.1111/aas.13949
  6. Dumeny L., Chantra M., Langaee T., Duong B.Q., Zambrano D.H., Han F., Lopez-Colon D., Humma J.F., Dacosta J., Lovato T., Mei C., Duarte J.D., Johnson J.A., Peek G.J., Jacobs J.P., Bleiweis M.S., Cavallari L.H. β1-receptor polymorphisms and junctional ectopic tachycardia in children after cardiac surgery. Clin Transl Sci. 2022;15(3):619-625. PMID: 34713976; PMCID: PMC8932827. https://dx.doi.org/10.1111/cts.13178
  7. Белов Д.В., Гарбузенко Д.В., Фокин А.А., Наймушина Ю.В., Милиевская Е.Б., Лукин О.П., Пешиков О.В. Шкала прогнозирования риска ранних абдоминальных осложнений после коронарного шунтирования в условиях искусственного кровообращения. Грудная и сердечно-сосудистая хирургия. 2019;61(3):190-196. https://dx.doi.org/10.24022/0236-2791-2019-61-3-190-196 Belov D.V., Garbuzenko D.V., Fokin A.A., Naymushina Yu.V., Milievskaya E.B., Lukin O.P., Peshikov O.V. A prognostic scale for the prediction of early abdominal complications after coronary artery bypass surgery with cardiopulmonary bypass. Russian Journal of Thoracic and Cardiovascular Surgery. 2019;61(3):190-196. (In Russ.) https://dx.doi.org/10.24022/0236-2791-2019-61-3-190-196
  8. Белов Д.В., Гарбузенко Д.В., Наймушина Ю.В., Лукин О.П., Милиевская Е.Б., Леонтьев С.Н., Мезенцев В.И. Шкала прогнозирования риска ранних абдоминальных осложнений после коррекции пороков сердца в условиях искусственного кровообращения. Грудная и сердечно-сосудистая хирургия. 2020;62(5):426-431. https://dx.doi.org/10.24022/0236-2791-2020-62-5-426-431 Belov D.V., Garbuzenko D.V., Naymushina Yu.V., Lukin O.P., Milievskaya E.B., Leontev S.N., Mezentsev V.I. Prognostic scale for the prediction of early abdominal complications after correction of heart diseases with cardiopulmonary bypass. Russian Journal of Thoracic and Cardiovascular Surgery. 2020;62(5):426-431. (In Russ.) https://dx.doi.org/10.24022/0236-2791-2020-62-5-426-431
  9. Chen B., Cole J.W., Grond-Ginsbach C. Departure from Hardy Weinberg equilibrium and genotyping error. Front Genet. 2017;8:167. PMID: 29163635; PMCID: PMC5671567. https://dx.doi.org/10.3389/fgene.2017.00167
  10. Chamberlain A.M., Schreiner P.J., Fornage M., Loria C.M., Siscovick D., Boerwinkle E. Ala54Thr polymorphism of the fatty acid binding protein 2 gene and saturated fat intake in relation to lipid levels and insulin resistance: the Coronary Artery Risk Development in Young Adults (CARDIA) study. Metabolism. 2009;58(9):1222-1228. PMID: 19439328; PMCID: PMC2728792. https://dx.doi.org/10.1016/j.metabol.2009.04.007
  11. de Luis D.A., Gonzalez Sagrado M., Aller R., Izaola O., Conde R. Metabolic syndrome and ALA54THR polymorphism of fatty acid-binding protein 2 in obese patients. Metabolism. 2011;60(5):664-668. PMID: 20723947. https://dx.doi.org/10.1016/j.metabol.2010.06.018
  12. Yamada Y., Kato K., Oguri M., Yoshida T., Yokoi K., Watanabe S., Metoki N., Yoshida H., Satoh K., Ichihara S., Aoyagi Y., Yasunaga A., Park H., Tanaka M., Nozawa Y. Association of genetic variants with atherothrombotic cerebral infarction in Japanese individuals with metabolic syndrome. Int J Mol Med. 2008;21(6):801-808. PMID: 18506375. https://doi.org/10.3892/ijmm.21.6.801
  13. Georgopoulos A., Bloomfield H., Collins D., Brousseau M.E., Ordovas J.M., O'Connor J.J., Robins S.J., Schaefer E.J. Codon 54 polymorphism of the fatty acid binding protein (FABP) 2 gene is associated with increased cardiovascular risk in the dyslipidemic diabetic participants of the Veterans Affairs HDL intervention trial (VA-HIT). Atherosclerosis. 2007;194(1):169-174. PMID: 16945373. https://dx.doi.org/10.1016/j.atherosclerosis.2006.07.022
  14. de Luis D.A., Aller R., Izaola O., Sagrado M.G., Conde R. Influence of ALA54THR polymorphism of fatty acid binding protein 2 on lifestyle modification response in obese subjects. Ann Nutr Metab. 2006;50(4):354-360. PMID: 16809903. https://dx.doi.org/10.1159/000094299
  15. Liu P.J., Liu Y.P., Qin H.K., Xing T., Li S.S., Bao Y.Y. Effects of polymorphism in FABP2 Ala54Thr on serum lipids and glycemic control in low glycemic index diets are associated with gender among Han Chinese with type 2 diabetes mellitus. Diabetes Metab Syndr Obes. 2019;12:413-421. PMID: 30988637; PMCID: PMC6441458. https://dx.doi.org/10.2147/DMSO.S196738
  16. Song X., Wang D., Ben B., Xiao C., Bai L., Xiao H., Zhang W., Li W., Jia J., Qi Y. Association between interleukin gene polymorphisms and susceptibility to gastric cancer in the Qinghai population. J Int Med Res. 2021;49(5):3000605211004755. PMID: 33942631; PMCID: PMC8113958. https://dx.doi.org/10.1177/03000605211004755
  17. Yang T.-C., Chang P.-Y., Lu S.-C. L5-LDL from ST-elevation myocardial infarction patients induces IL-1beta production via LOX-1 and NLRP3 inflammasome activation in macrophages. Am J Physiol Heart Circ Physiol. 2017;312(2):H265-H274. PMID: 27864235. https://dx.doi.org/10.1152/ajpheart.00509.2016
  18. Chen B., Geng J., Gao S.-X., Yue W.-W., Liu Q. Eplerenone modulates interleukin-33/sST2 signaling and IL-1beta in left ventricular systolic dysfunction after acute myocardial infarction. J Interferon Cytokine Res. 2018;38(3):137-144. PMID: 29565745. https://dx.doi.org/10.1089/jir.2017.0067
  19. Daraei A., Mansoori Y., Zendebad Z., Tavakkoly-Bazzaz J., Madadizadeh F., Naghizadeh M.M., Arghavani A., Mansoori B. Influences of IL-1b-3953 C>T and MMP-9-1562 C>T gene variants on myocardial infarction susceptibility in a subset of the Iranian population. Genet Test Mol Biomarkers. 2017;21(1):33-38. PMID: 27824519. https://dx.doi.org/10.1089/gtmb.2016.0240
  20. Wang S., Dai Y.X., Chen L.L., Jiang T., Zheng M.Q., Li C.G., Chen Y.P., Lin W.H., Zhang J.F., Jiang J. Effect of IL-1beta, IL-8, and IL-10 polymorphisms on the development of myocardial infarction. Genet Mol Res. 2015;14(4):12016-12021. PMID: 26505348. https://dx.doi.org/10.4238/2015.October.5.14
  21. Fang Y., Xie H., Lin Z. Association between IL-1beta + 3954C/T polymorphism and myocardial infarction risk: a meta-analysis. Medicine (Baltimore). 2018;97(30):11645. PMID: 30045312; PMCID: PMC6078675. https://dx.doi.org/10.1097/MD.0000000000011645
  22. Pan Q., Hui D., Hu C. A variant of IL1B is associated with the risk and blood lipid levels of myocardial infarction in Eastern Chinese individuals. Immunol Invest. 2022;51(5):1162-1169. PMID: 33941028. https://dx.doi.org/10.1080/08820139.2021.1914081