Gene-by-Environment Interaction in Non-Alcoholic Fatty Liver Disease and Depression: The Role of Hepatic Transaminases
Main Article Content
Abstract
Non-alcoholic fatty liver disease (NAFLD) encompasses a range of liver conditions, from benign fatty accumulation to severe fibrosis. The global prevalence of NAFLD has risen to 25-30%, with variations across ethnic groups. NAFLD may advance to hepatocellular carcinoma, increases cardiovascular risk, is associated with chronic kidney disease, and is an independent metabolic disease risk factor. Assessment methods for liver health include liver biopsy, magnetic resonance imaging, ultrasound, and vibration-controlled transient elastography (VCTE by FibroScan). Hepatic transaminases are cost-effective and minimally invasive liver health assessment methods options.
This study focuses on the interaction between genetic factors underlying the traits (hepatic transaminases and the FibroScan results) on the one hand and the environment (depression) on the other. We examined 525 individuals at risk for metabolic disorders. We utilized variance components models and likelihood-based statistical inference to examine potential GxE interactions in markers of NAFLD, including aspartate aminotransferase (AST), alanine aminotransferase (ALT), and the AST/ALT ratio, and Vibration-Controlled Transient Elastography (VCTE by FibroScan). We calculated the Fibroscan-AST (FAST) score (a score that identifies the risk of progressive non-alcoholic steatohepatitis (NASH) and screened for depression using the Beck Depression Inventory-II (BDI-II). We identified significant G x E interactions for AST/ALT ratio x BDI-II, but not AST, ALT, or the FAST score. Our findings support that genetic factors play a role in hepatic transaminases, especially the AST/ALT ratio, with depression influencing this relationship. These insights contribute to understanding the complex interplay of genetics, environment, and liver health, potentially guiding future personalized interventions.
Keywords:
Mexican Americans, GxE, Transaminases, FAST Score, De Ritis ratio, FibroScan, Genetics, Heritability, Depression
Article Details
How to Cite
MANUSOV, Eron G et al.
Gene-by-Environment Interaction in Non-Alcoholic Fatty Liver Disease and Depression: The Role of Hepatic Transaminases.
Medical Research Archives, [S.l.], v. 11, n. 9, sep. 2023.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/4408>. Date accessed: 21 dec. 2024.
doi: https://doi.org/10.18103/mra.v11i9.4408.
Section
Research Articles
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
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doi: 10.3389/fmed.2021.69169
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2. Makri E, Goulas A, Polyzos SA. Epidemiology, Pathogenesis, Diagnosis and Emerging Treatment of Non-alcoholic Fatty Liver Disease. Arch Med Res. 2021;52(1):25-37. doi: 10.1016/j.arcmed.2020.11.010
3. Younossi Z, Anstee QM, Marietti M, Hardy T, Henry L, Eslam M, et al. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol. 2018;15(1):11-20.
doi: 10.1038/nrgastro.2017.109
4. Younossi ZM, Golabi P, de Avila L, Paik JM, Srishord M, Fukui N, et al. The global epidemiology of NAFLD and NASH in patients with type 2 diabetes: A systematic review and meta-analysis. J Hepatol. 2019;71(4):793-801. doi: 10.1016/j.jhep.2019.06.021
5. Huang DQ, El-Serag HB, Loomba R. Global epidemiology of NAFLD-related HCC: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol. 2021;18(4):223-38. doi: 10.1038/s41575-020-00381-6
6. Mitchell BD, Kammerer CM, Blangero J, Mahaney MC, Rainwater DL, Dyke B, et al. Genetic and environmental contributions to cardiovascular risk factors in Mexican Americans. The San Antonio Family Heart Study. Circulation. 1996;94(9):2159-70.
doi: 10.1161/01.cir.94.9.2159
7. Eslam M, Sanyal AJ, George J. MAFLD: A Consensus-Driven Proposed Nomenclature for Metabolic Associated Fatty Liver Disease. Gastroenterology. 2020;158(7):1999-2014.e1. doi: 10.1016/j.jhep.2017.09.003
8. Newsome PN, Sasso M, Deeks JJ, Paredes A, Boursier J, Chan WK, et al. FibroScan-AST (FAST) score for the non-invasive identification of patients with non-alcoholic steatohepatitis with significant activity and fibrosis: a prospective derivation and global validation study. Lancet Gastroenterol Hepatol. 2020;5(4):362-73. doi: 10.1016/s2468-1253(19)30383-8
9. Grob SR, Suter F, Katzke V, Rohrmann S. The Association between Liver Enzymes and Mortality Stratified by Non-Alcoholic Fatty Liver Disease: An Analysis of NHANES III. Nutrients. 2023 Jul 7;15(13):3063. doi: 10.3390/nu15133063. PMID: 37447388; PMCID: PMC10346959.
10. Scheipner L, Smolle MA, Barth D, Posch F, Stotz M, Pichler M, et al. The AST/ALT Ratio Is an Independent Prognostic Marker for Disease-free Survival in Stage II and III Colorectal Carcinoma. Anticancer Res. 2021;41(1):429-36. doi: 10.21873/anticanres.14792
11. Martinou E, Pericleous M, Stefanova I, Kaur V, Angelidi AM. Diagnostic Modalities of Non-Alcoholic Fatty Liver Disease: From Biochemical Biomarkers to Multi-Omics Non-Invasive Approaches. Diagnostics (Basel). 2022 Feb 4;12(2):407.
doi: 10.3390/diagnostics12020407.
12. Oeda S, Tanaka K, Oshima A, Matsumoto Y, Sueoka E, Takahashi H. Diagnostic Accuracy of FibroScan and Factors Affecting Measurements. Diagnostics (Basel). 2020 Nov 12;10(11):940. doi: 10.3390/diagnostics10110940.
13. de Lédinghen V, Vergniol J. Transient elastography (FibroScan). Gastroenterol Clin Biol. 2008 Sep;32(6 Suppl 1):58-67. doi: 10.1016/S0399-8320(08)73994-0.
14. Cassinotto C, Boursier J, de Lédinghen V, Lebigot J, Lapuyade B, Cales P, Hiriart JB, Michalak S, Bail BL, Cartier V, Mouries A, Oberti F, Fouchard-Hubert I, Vergniol J, Aubé C. Liver stiffness in non-alcoholic fatty liver disease: A comparison of supersonic shear imaging, FibroScan, and ARFI with liver biopsy. Hepatology. 2016 Jun;63(6):1817-27. doi: 10.1002/hep.28394.
15. Manusov EG, Diego VP, Sheikh K, Laston S, Blangero J, Williams-Blangero S. Non-alcoholic Fatty Liver Disease and Depression: Evidence for Genotype × Environment Interaction in Mexican Americans. Front Psychiatry. 2022 Jul 1;13:936052.
doi: 10.3389/fpsyt.2022.936052.
16. van Beek JH, Lubke GH, de Moor MH, Willemsen G, de Geus EJ, Hottenga JJ; LivGen consortium; Walters RK, Smit JH, Penninx BW, Boomsma DI. Heritability of liver enzyme levels estimated from genome-wide SNP data. Eur J Hum Genet. 2015 Sep;23(9):1223-8. doi: 10.1038/ejhg.2014.259.
17. Lee K, Kim D, Cho Y. Exploratory Factor Analysis of the Beck Anxiety Inventory and the Beck Depression Inventory-II in a Psychiatric Outpatient Population. J Korean Med Sci. 2018 Apr 16;33(16):e128.
doi: 10.3346/jkms.2018.33.e128.
18. Penley JA, Wiebe JS, Nwosu A. Psychometric properties of the Spanish Beck Depression Inventory-II in a medical sample. Psychol Assess. 2003 Dec;15(4):569-77. doi: 10.1037/1040-3590.15.4.569.
19. Wiebe JS, Penley JA. A psychometric comparison of the Beck Depression Inventory-II in English and Spanish. Psychol Assess. 2005;17(4):481-5.
doi: 10.1037/1040-3590.17.4.481
20. do Nascimento RLF, Fajardo-Bullon F, Santos E, Landeira-Fernandez J, Anunciação L. Psychometric Properties and Cross-Cultural Invariance of the Beck Depression Inventory-II and Beck Anxiety Inventory among a Representative Sample of Spanish, Portuguese, and Brazilian Undergraduate Students. Int J Environ Res Public Health. 2023 May 31;20(11):6009. doi: 10.3390/ijerph20116009.
21. Blangero J, Diego VP, Dyer TD, Almeida M, Peralta J, Kent JW, Jr., et al. A kernel of truth: statistical advances in polygenic variance component models for complex human pedigrees. Adv Genet. 2013;81:1-31. doi: 10.1016/b978-0-12-407677-8.00001-4
22. Diego VP, Almasy L, Dyer TD, Soler JM, Blangero J. Strategy and model building in the fourth dimension: a null model for genotype x age interaction as a Gaussian stationary stochastic process. BMC Genet. 2003;4 Suppl 1(Suppl 1):S34. doi: 10.1186/1471-2156-4-s1-s34
23. Quillen EE, Voruganti VS, Chittoor G, Rubicz R, Peralta JM, Almeida MA, et al. Evaluation of estimated genetic values and their application to genome-wide investigation of systolic blood pressure. BMC Proc. 2014;8(Suppl 1 Genetic Analysis Workshop 18Vanessa Olmo):S66. doi: 10.1186/1753-6561-8-S1-S66
24. Blangero J. Update to Blangero's "Statistical genetic approaches to human adaptability" (1993): a unified theory of genotype x environment interaction. Hum Biol. 2009;81(5-6):547-50. doi: 10.3378/027.081.0604
25. Diego VP, Atwood L, Mathias RA, Almasy L. Consistency of genetic analyses in longitudinal data: observations from the GAW13 Framingham Heart Study data. Genet Epidemiol. 2003;25 Suppl 1:S29-35. doi: 10.1002/gepi.10281
26. Hazuda, H. P., Haffner, S. M., Stern, M. P., and Eifler, C. W. (1988). Effects of acculturation and socioeconomic status on obesity and diabetes in Mexican Americans. The San Antonio Heart Study. Am. J. Epidemiol. 128 (6), 1289–1301. doi:10.1093/oxfordjournals.aje.a115082
27. Hazuda, H. P., Mitchell, B. D., Haffner, S. M., and Stern, M. P. (1991). Obesity in Mexican American subgroups: Findings from the San Antonio heart study. Am. J. Clin.Nutr. 53 (6), 1529S–1534S. doi:10.1093/ajcn/53.6.1529S
28. Benyamin B, Visscher PM, McRae AF. Family-based genome-wide association studies. Pharmacogenomics. 2009 Feb;10(2):181-90. doi: 10.2217/14622416.10.2.181
29. Rahmioglu N, Andrew T, Cherkas L, Surdulescu G, Swaminathan R, Spector T, Ahmadi KR. Epidemiology and genetic epidemiology of the liver function test proteins. PLoS One. 2009;4(2):e4435.
doi: 10.1371/journal.pone.0004435
30. Whitfield JB, Zhu G, Nestler JE, Heath AC, Martin NG. Genetic covariation between serum gamma-glutamyltransferase activity and cardiovascular risk factors. Clin Chem. 2002; 48:1426–1431.
31. Whitfield JB, Martin NG. Individual differences in plasma ALT, AST and GGT: contributions of genetic and environmental factors, including alcohol consumption. Enzyme. 1985;33:61–69.
32. Makkonen J, Pietiläinen KH, Rissanen A, Kaprio J, Yki-Järvinen H. Genetic factors contribute to variation in serum alanine aminotransferase activity independent of obesity and alcohol: a study in monozygotic and dizygotic twins. J Hepatol. 2009;50:1035–1042. doi 10.1016/j.jhep.2008.12.025
33. Sung J, Lee K, Song YM. Heritabilities of Alcohol Use Disorders Identification Test (AUDIT) scores and alcohol biomarkers in Koreans: the KoGES (Korean Genome Epi Study) and Healthy Twin Study. Drug Alcohol Depend. 2011;113:104–109. doi: 10.1016/j.drugalcdep.2010.07.012
34. Lin JP, O’Donnell CJ, Fox CS, Cupples LA. Heritability of serum glutamyltransferase level: genetic analysis from the Framingham Offspring Study. Liver Int. 2009;29:776–777. doi: 10.1111/j.1478-3231.2008.01965.x
35. Nilsson SE, Read S, Berg S, Johansson B. Heritabilities for fifteen routine biochemical values: findings in 215 Swedish twin pairs 82 years of age or older. Scand J Clin Lab Invest. 2009;69:562–569. doi 10.1080/00365510902814646
36. 36. Glahn DC, Curran JE, Winkler AM, Carless MA, Kent JW Jr, Charlesworth JC, Johnson MP, Göring HH, Cole SA, Dyer TD, Moses EK, Olvera RL, Kochunov P, Duggirala R, Fox PT, Almasy L, Blangero J. High dimensional endophenotype ranking in the search for major depression risk genes. Biol Psychiatry. 2012 Jan 1;71(1):6-14.
doi: 10.1016/j.biopsych.2011.08.022.
37. Xiao J, Lim LKE, Ng CH, Tan DJH, Lim WH, Ho CSH, et al. Is Fatty Liver Associated With Depression? A Meta-Analysis and Systematic Review on the Prevalence, Risk Factors, and Outcomes of Depression and Non-alcoholic Fatty Liver Disease. Front Med (Lausanne). 2021;8:691696.
doi: 10.3389/fmed.2021.69169
38. Balakrishnan M, Kanwal F, El-Serag HB, Thrift AP. Acculturation and Non-alcoholic Fatty Liver Disease Risk Among Hispanics of Mexican Origin: Findings From the National Health and Nutrition Examination Survey. Clin Gastroenterol Hepatol. 2017;15(2):310-2.
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