Figures
Abstract
Introduction
We investigated the epidemiology of Cytochrome P450 (CYP) 3A4 genotype and the relationship between CYP3A4 genotype and alcohol drinking habits.
Materials and methods
A single-centered retrospective study was conducted on 630 patients who underwent CYP3A4*1G genetic testing. Their relevant information on epidemiology and etiology was collected. Laboratory testing, including CYP3A4*1G genotype, liver function tests, and serum lipid measurements were performed. Bi-variate logistic regressions were used to examine the relationship between variables. The relationship between alcohol drinking and CYP3A4*1G genotype was estimated. Demographic and clinical features were analyzed. Participants with drinking history were divided into non-heavy drinking and heavy drinking groups. Liver function and dyslipidemia of participants with drinking histories were compared between CYP3A4*1G mutation (GA+AA) and wild-type (GG) groups.
Results
Participants with CYP3A4*1G mutation(GA+AA) had an increased adjusted odds ratio (AOR) of 2.56 (95% CI, 1.4–4.65; P = 0.00) for alcohol abuse when compared with participants without CYP3A4 mutation (GG). In the subgroup of participants with alcohol abuse, there are no significant differences in liver injury levels and serum lipid levels between CYP3A4*1G mutant and wild-type groups. Patients with CYP3A4*1G mutation had an increased AOR of cardiac-vascular diseases and malignant diseases compared with patients without CYP3A4*1G mutation. The epidemiology had no difference between GA and AA group.
Conclusion
The study indicated that there was association between alcohol drinking and CYP3A4*1G genetic mutation. In the subgroup of participants with alcohol abuse, there are no significant differences in liver injury and dyslipidemia between CYP3A4*1G mutant and wild-type groups. CYP3A4*1G mutation was also related to cardiac-vascular diseases and malignant diseases.
Citation: Jia X, Zhang X, Zhou T, Sun D, Li R, Yang N, et al. (2023) Cyp3A4 *1G polymorphism is associated with alcohol drinking: A 5-year retrospective single centered population-based study in China. PLoS ONE 18(12): e0295184. https://doi.org/10.1371/journal.pone.0295184
Editor: Edmund Tetteh Nartey, University of Ghana, GHANA
Received: June 27, 2023; Accepted: November 16, 2023; Published: December 20, 2023
Copyright: © 2023 Jia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Abbreviations: CYP, Cytochrome P450; ALT, alanine aminotransferase; AST, aspartate aminotransferase; TG, triglyceride; Cho, cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; NEFA, non-esterified fatty acids
Introduction
Cytochrome P450 (CYP) is located in liver microsomes, which is indispensable in metabolizing a large group of clinical drugs [1]. Human CYP includes 18 families and 44 subfamily members [2]. CYP 3A4 metabolizes more than 50% of clinically used drugs [3–5]. Genetic factors are known to be responsible for the variability in the CYP3A4 activity [6, 7]. CYP3A4*1G (IVS10+12G >A, rs2242480) is a single nucleotide polymorphism site with a high mutation frequency in Chinese population, which includes wild-type homozygote (CYP3A4*1/*1, GG), mutant heterozygote (CYP3A4*1/*1G, GA), and mutant homozygote (CYP3A4*1G/*1G, AA) [8–10]. A synonymous G-A transition has been confirmed to be associated with CYP3A4 enzyme activity, which decrease metabolism of clinical drugs and requires distinct treatment among different patients [10, 11]. CYP3A4*1G genetic mutation has been found to decrease the activity of CYP3A4 which increase the fentanyl and sufentanil concentration in peripheral circulation and decrease the drug consumption for operative and postoperative pain control [12]. Researches have also shown that the genetic polymorphism of CYP3A4*1G has been associated with altered pharmacokinetics of several drugs, such as atorvastatin, tacrolimus, but may not be a significant contributor to clopidogrel metabolism [13–15].
Alcohol abuse is common in the general population. An estimated 2.4 billion people worldwide consumed alcohol, including 1.5 billion men and 900 million women in 2016 [16]. The harmful use of alcohol is responsible for 5.1% of the global burden of disease [17]. Chronic alcohol consumption is strongly related to several pathological consequences like liver injury, brain damage, type 2 diabetes mellitus, dyslipidemia and high blood pressure [18, 19]. Even low-level alcohol consumption could result in premature brain aging [20]. Common drinking patterns include light alcohol consumption, moderate alcohol consumption (MAC), binge drinking and chronic heavy drinking [19, 21, 22].
The alcohol-metabolizing in the human liver is a collection of multiple P450 species co-localized in the membrane of the endoplasmic reticulum (ER) [23]. The cytochrome P450 isozymes, mainly CYP2E1 contribute to alcohol oxidation in the liver and brain [24, 25]. Recent research indicates that alcohol exposure may induce CYP2E1-dependent activation of CYP3A4, CYP2E1-CYP3A4 interactions may play a role in the effects of alcohol exposure on drug metabolism in human liver microsomes [26]. But the clinical study on CYP3A4 activity and its association with alcohol drinking is limited. The association between polymorphisms of CYP3A4 genotypes and alcohol abuse is not clear.
Therefore, a retrospective population-based study was carried on to investigate the epidemiology of CYP3A4*1G genetic polymorphism and its association with alcohol drinking in China.
Materials and methods
A retrospective observational study was conducted from January 2017 to December 2021at the Qilu Hospital of Shandong University in China. Sample size was calculated by the corresponding formula using PASS version 11.0 for windows. The ratio of alcohol abuse in control group was 18.95% in our research, and the expected odd ratio was 2 in a recent study (α = 0.05, β = 0.2) [27]. After calculation, the sample size of DILI group and the control group were at least 229. A total of 620 participants scheduled for surgery under general anesthesia in the Qilu hospital who underwent routine test of CYP3A4*1G genotype from January 2017 to December 2021 were enrolled in this study. More than two researchers participated in data collection and entry to reduce bias. Two researchers collected data simultaneously, then another researcher check the data to identify faulty or missing data and correct them. Incomplete data of participants were not included in the statistical analysis. Participants were recruited and medical records of participants were retrospectively collected from January 2017 to December 2021. Data assessment was carried on from December 2021 to December 2022. This study had access to information that could identify individual participants during data collection from medical records of participants in hospital. The Independent Institutional Review Board of Qilu Hospital of Shandong University authorized the recruitment of study participants and the study protocol number is KYLL-202008-097 (S1 and S2 Appendices). Data were collected after the ethic committee approval. All collected data is anonymous, and the requirement for informed consent was accordingly waived. The informed consent waiver statement was approved by the ethics committee of Qilu Hospital. All methods were conducted in accordance with the relevant guidelines and regulations. The raw data were supplied in S3 Appendix.
Participants
Participants who underwent CYP3A4*1G genotype test at the Qilu Hospital of Shandong University from January 2017 to December 2021 were enrolled in the study. Participants less than 18 were not included in previous clinical study on CYP3A4 genotype [13, 15, 28, 29].
The exclusion criteria were as follows:
Under the age of 18;
Incomplete serologic results, demographic and clinical characteristics.
CYP3A4*1G genotyping
The G-A synonymous transition of CYP3A4*1G genotypes were detected in the Department of Laboratory of Qilu Hospital. The blood samples were tested immediately after extraction or restored in 4 centigrade in refrigerator within 24 hours before genetic test. Genome DNA was isolated from 2 ml of peripheral venous blood with ethylenediaminetetraacetic acid as an anticoagulant and analyzed by using the TaqMan probe for genotyping. Primer sequence were as follows: F: 5’‑TGGTGAGGAGGCATTTTTGC‑3’ and R: 5’‑TGCAGGAGGAAATTGATGCA‑3’ according to previous researches [28]. PCR was carried out in a reaction mixture containing 0.4 μg of genomic DNA, 1.6 μmol/L of each primer, 0.25 μmol/L TaqMan probes and 1× PCR Mix (GeneCopoeia, Rockville, MD, USA). The PCR conditions included an initial denaturation at 95°C for 10 minutes, followed by 40 cycles of denaturation at 95°C for 10 seconds, annealing at 60°C for 30 seconds. The probe which contains a fluorescence reporter gene and a fluorescence quenching gene at both ends was digested and degraded by a 5’ nuclease of Taq enzyme and genotyping was quantified by the resulting fluorescence. All methods were carried out in accordance with the relevant guidelines and regulations of the Department of Laboratory of Qilu Hospital and previous researches [13, 15, 28].
Data were collected and analyzed, there were three genotypes, which include wild‑type homozygote (CYP3A4*1/*1, GG), mutant heterozygote (CYP3A4*1/*1G, GA), and mutant homozygote (CYP3A4*1G/*1G, AA). Participants were divided into two groups, which include CYP3A4*1G genetic wild-type group (GG) and CYP3A4*1G genetic mutant-type group (GA+AA).
Classification of drinking patterns
Drinking patterns were divided into four classes [30]:
Light alcohol consumption: Regular alcohol drinking <10–20 g/day.
Moderate alcohol consumption: Regular alcohol drinking <30–42 g/day for men and <20–28 g/day for women
Binge drinking: Alcohol consumption >40 g for women and >50 g for men within about 2 h
Chronic heavy drinking: Chronic alcohol consumption (generally more than 5 years) more than 60 g on one occasion
In previous research, light alcohol consumption and moderate alcohol consumption belong to non-heavy drinking pattern [31]. Binge drinking is a pattern of heavy drinking in previous researches [32, 33]. In this study, participants with drinking history were then divided into non-heavy drinking group (light alcohol consumption and moderate alcohol consumption participants) and heavy drinking group (binge drinking and chronic heavy drinking participants). Participants with incomplete information of drinking quantity were excluded in the subgroup analysis.
Diagnosis of dyslipidemia
Participants were considered to suffer from dyslipidemia if they had total cholesterol (Cho) >240 mg/dL or 6.00 mmol/L, high-density lipoprotein cholesterol (HDL-C) <40 mg/dL or 0.8 mmol/L, low-density lipoprotein cholesterol (LDL-C) ≥160 mg/dL or 3.37 mmol/L, or triglyceride (TG) ≥200 mg/dL or 1.7 mmol/L [34, 35].
Data collection
The demographic and clinical characteristics evaluated in our study were collected from medical records in hospital, which include sex, age, smoking history, drinking alcohol history, allergy history, heart diseases, hypertension, type 2 diabetes, malignancy and history of family chronic disease. Biochemical parameters from routine laboratory tests of the patients were collected and analyzed, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), Cho, HDL-C, LDL-C, TG and non-esterified fatty acids (NEFA).
Statistical analysis
Percentages were used for qualitative parameters. Differences in proportions of drinking style between different genotype groups were evaluated using χ2-test. Mean ± standard deviation (mean ± SD) was used for normally distributed continuous variables including liver function levels and serum lipid levels in alcohol drinking participants. Spearman correlation analysis was performed on variables including sex, age, smoking, alcoholic abuse, hypertension, heart disease, diabetes, malignant disease, allergic history, family chronic disease and dyslipidemia to explore the relationship between variables and gene mutation. Bi-variate logistic regressions were used to investigate the relationship between genetic mutation and variables. Reference category of the exposure was designated of 1 to obtain OR value. We used multivariate analysis to select variables with P < 0.1 to adjust for potential confounding effects, entry method was used in selecting covariates in the multiple logistic regression model. Besides, sensitivity analysis were carried on which include multivariate logistic regression analysis of all participants’ information, the result were supported in supplementary data (S4 Apendix). Missing data were not included in statistical analysis. P value less than 0.05 was considered statistically significant. SPSS version 17.0 (SPSS, Chicago, IL) and GraphPad Prism 8.0 for Windows were used to perform statistical analysis.
Results
Characteristics of participants
A total of 620 participants were enrolled in this study and 30 participants under 18 years old were excluded from the research. CYP3A4*1G mutant-type include mutant heterozygote (GA) and homozygote (AA), and there is no statistic difference between GA and AA in drug metabolism and epidemiology in previous study [13, 14, 28]. In the present study, all the individuals were divided into two groups according to the results of CYP3A4*1G genotype, including 343 with wild-type genotype (GG) and 247 with mutant-type genotype (GA+AA). The CYP3A4*1G mutant-type group includes 223 participants with mutant heterozygote (GA), and 24 participants with mutant homozygote (AA). In the CYP3A4*1G wild-type group, 55.98% were males and 44.02% were females; the median age of patients was 54.05 years. In the CYP3A4*1G mutant-type group, 56.28% were males and 43.72% were females; the median age of patients was 54.04 years. Demographic and clinical characteristics are shown in Table 1. Study cohort is shown in Fig 1.
Participants under CYP3A4*1G genetic tests were included and separated into CYP3A4*1G mutant type and CYP3A4*1G wild type group. Clinical and epidemiology characters were analyzed and the result showed that CYP3A4*1G genetic mutation is associated with alcohol abuse. Participants with alcohol abuse were collected in subgroup analysis. The clinical and epidemiology characters were analyzed in alcohol abuse subgroup.
Clinical and demographic characteristics of CYP3A4*1G genotype
CYP3A4*1G genetic mutation is associated with alcohol abuse and malignant diseases, with the correlation coefficient 0.09 and 0.1 (P<0.05) (Fig 2). Sex, age, smoking, allergic history, family chronic disease and CYP3A4*1G mutation were analyzed as exposure variables and alcoholic abuse, malignant disease, hypertension, heart disease, diabetes and dyslipidemia were analyzed as outcomes in logistic regression analysis. Study participants with mutant CYP3A4*1G had an increased odds (2.56 (1.4–4.65), P = 0.00) of alcohol drinking compared with those with wild type CYP3A4*1G, which indicated that participants with CYP3A4*1G genetic mutation had an increased incidence of alcohol drinking than patients without genetic mutation. Study participants of genetic mutant-type group with a history of cardiac vascular disease had an OR of 1.59 (95% CI, 1.03–2.46; P = 0.04) compared with those without genetic mutation, which showed that participants with CYP3A4*1G genetic mutation had an increased incidence of cardiac vascular diseases than patients without genetic mutation. CYP3A4*1G mutant-type group participants who had malignant diseases had an OR of 1.56 (95% CI, 1.08–2.24; P = 0.02) compared with those without genetic mutation, which indicated that participants with CYP3A4*1G genetic mutation had an increased risk of malignant diseases than patients without genetic mutation. There was no statistical significance association between hypertension, type 2 diabetes or dyslipidemia and the CYP3A4*1G genetic mutation. The epidemiology had no difference between CYP3A4*1G mutant heterozygote and homozygote. The above data are shown in Table 2. Multivariate regressions of all the participants were carried on and alcohol drinking still has increased OR in mutant-type group, the result was supplied in supplementary data (S4 Appendix).
The clinical and epidemiology characters were analyzed by Spearman correlation coefficient. * P≤0.05; ** P≤0.01.
Drinking patterns and CYP3A4*1G genetic polymorphism
Participants with drinking history were collected in subgroup analysis. The clinical and epidemiology characters were analyzed in alcohol abuse subgroup (Fig 1). Patients with were selected and divided into 4 patterns according to drinking patterns. Of 121 patients with drinking history, 60 patients with complete information were analyzed. Among patients with alcoholic abuse, 2 (3.33%) patients have light alcohol consumption, 11 (18.33%) patients have moderate alcohol consumption, 4 (6.67%) patients have binge drinking habits and 43 (71.67%) patients have chronic heavy drinking habits. Patients with alcoholic abuse were divided into non-heavy drinking (13, 21.67%) and heavy drinking (47, 78.33%) groups. There was no statistical significant association between CYP3A4*1G genetic mutation and drinking patterns (Table 3).
Liver injury, dyslipidemia and CYP3A4*1G genetic polymorphism
Participants in the non-heavy drinking group had no statistically significant difference in ALT, AST, TG, Cho, HDL-C, LDL-C, NEFA levels between CYP3A4*1G wild-type and mutant-type. Patients in the heavy drinking group had no statistically significant difference in liver injury and dyslipidemia levels between CYP3A4*1G wild-type and mutant-type (Table 3).
Discussion
CYP3A4 contributes to the metabolism of 45% of pharmaceutical drugs. Studies have shown that CYP3A4*1G genetic mutation decreases activity of CYP3A, resulting in a high plasma concentration of certain drugs like fentanyl and sufentanil [12, 28]. Previous studies have demonstrated that humans are primed to consume greater amounts of alcohol after a small dose, which is called rewarding effects [36]. Some drinkers who had greater sensitivity to these rewarding effects were prompt to have alcohol abuse, which is related to metabolism of alcohol in liver and blood alcohol concentration (BAC) [37]. The acetaldehyde is the oxidation product of ethanol which is generated by hepatic alcohol dehydrogenase (ADH) and the microsomal ethanol-oxidizing system (MEOS) [38]. The metabolism of acetaldehyde is mainly dependent on cytochrome P450 2E1 (CYP 2E1) [39]. Researches have shown that chronic alcohol exposure results in CYP3A4 activation through increased content of CYP2E1 which has high catalytic activity with ethanol, which indicated that CYP3A4 may play a role in ethanol metabolism [26, 40]. This study showed that participants with CYP3A4*1G mutation had an increased risk in the occurrence of alcohol drinking compared to participants with wild-type CYP3A4*1G genotype. The mechanism may be CYP3A4*1G mutation decrease the activity of CYP3A4 and CYP2E1 which increase BAC, therefore improve sensitivity to rewarding effects and neurotoxicity. However, there is no difference in liver injury between CYP3A4*1G wild-type and mutant-type in alcohol abuse sub-group.
This study showed that participants with CYP3A4*1G genetic mutation had a 1-fold to 2-fold increase in the incidence of malignant diseases than patients without genetic mutation. In recent research, CYP3A might play an important role in susceptibility to cancer, like leukemia, renal cancer and breast cancer [41–43]. Besides, alcohol consumption has a causative effect in a number of malignant tumors, such as cancers of the oral cavity, pharynx, larynx, esophagus, colorectum, liver, cervix and breast of female [44, 45]. The genetic mutation of CYP3A4*1G is supposed to be associated with malignant disease through the mechanism related to genetic mutation and alcohol abuse.
In this study, participants with CYP3A4*1G genetic mutation had a 1-fold to 2-fold increase in the incidence of cardiac diseases than participants without genetic mutation. Recent researches have shown that certain CYP450 enzymes contribute to cardiovascular diseases [46–48]. Alcohol consumption is related to increased risk of coronary artery disease, alcoholic cardiomyopathy, atrial and ventricular dysrhythmias, and hypertension, while high consumption or binge drinking significantly increases the risk [49]. The genetic mutation of CYP3A4*1G affects the activity of CYP3A4 and may be related to the susceptibility to cardiovascular disease. The pathology may be related to CYP3A4 activity and alcohol drinking.
Previous researches have demonstrated that CYP3A4 genetic mutation is associated with malignant diseases and cardiovascular diseases, which is in keep with the result of this study. The relationship between alcohol drinking and CYP3A4 genetic mutation has not been investigated in previous studies. This study has demonstrated that CYP3A4*1G genetic mutation has an increased risk of alcohol drinking.
Study strengths and limitations
Compared with previous researches, firstly, this is the first work in China to study the correlation between CYP3A4 genetic mutation and alcohol drinking. Secondly, CYP3A4 genetic mutation, which may be associated with alcohol abuse, was related to heart diseases and malignant diseases, a regular check-up for specific population of alcohol abuse is essential. Thirdly, alcohol drinking which may be related to individual genotype should be understood and cared for, health education of quitting drinking as early as possible is essential.
This was a retrospective study that relied on the accuracy of medical records. Although our study has shown that CYP3A4 mutation is related to alcohol abuse, the mechanism is unclear, and the number of participants with drinking habits was limited, which may have potential bias. Clinical research needs to be improved by increasing sample size. Animal and molecular biology researches are needed to investigate the association between CYP3A4 genotype and alcohol drinking.
Conclusion
Our research showed that CYP3A4*1G genetic polymorphism is related to alcohol abuse. In sub-group of participants with alcohol drinking, liver injury and dyslipidemia has no statistical significance between CYP3A4*1G mutation and wild-type group. The findings that have emerged can be utilized to further understand the epidemiological outcomes related to CYP3A4*1G mutation.
Supporting information
S2 Appendix. Ethic committe approval in English.
https://doi.org/10.1371/journal.pone.0295184.s002
(PDF)
S4 Appendix. Sensitive analysis of multivariable logistic regression.
https://doi.org/10.1371/journal.pone.0295184.s004
(XLS)
References
- 1. Wilkinson GR. Drug metabolism and variability among patients in drug response. The New England journal of medicine. 2005;352(21):2211–21. pmid:15917386
- 2. Barzi M, Pankowicz FP, Zorman B, Liu X, Legras X, Yang D, et al. A novel humanized mouse lacking murine P450 oxidoreductase for studying human drug metabolism. Nature communications. 2017;8(1):39.
- 3. Lolodi O, Wang YM, Wright WC, Chen T. Differential Regulation of CYP3A4 and CYP3A5 and its Implication in Drug Discovery. Current drug metabolism. 2017;18(12):1095–105.
- 4. van Dyk M, Marshall JC, Sorich MJ, Wood LS, Rowland A. Assessment of inter-racial variability in CYP3A4 activity and inducibility among healthy adult males of Caucasian and South Asian ancestries. European journal of clinical pharmacology. 2018;74(7):913–20.
- 5. Guengerich FP. Cytochrome P-450 3A4: regulation and role in drug metabolism. Annual review of pharmacology and toxicology. 1999;39:1–17. pmid:10331074
- 6. Rodríguez-Antona C, Sayi JG, Gustafsson LL, Bertilsson L, Ingelman-Sundberg M. Phenotype-genotype variability in the human CYP3A locus as assessed by the probe drug quinine and analyses of variant CYP3A4 alleles. Biochemical and biophysical research communications. 2005;338(1):299–305. pmid:16171783
- 7. Gulati S, Yadav A, Kumar N, Kanupriya , Kumar G, Aggarwal N, et al. Frequency distribution of high risk alleles of CYP2C19, CYP2E1, CYP3A4 genes in Haryana population. Environmental toxicology and pharmacology. 2014;37(3):1186–93. pmid:24814262
- 8. Yang W, Zhao D, Han S, Tian Z, Yan L, Zhao G, et al. CYP3A4*1G regulates CYP3A4 intron 10 enhancer and promoter activity in an allelic-dependent manner. International journal of clinical pharmacology and therapeutics. 2015;53(8):647–57. pmid:25997547
- 9. Zhou S, Tao M, Wang Y, Wang L, Xie L, Chen J, et al. Effects of CYP3A4*1G and CYP3A5*3 polymorphisms on pharmacokinetics of tylerdipine hydrochloride in healthy Chinese subjects. Xenobiotica; the fate of foreign compounds in biological systems. 2019;49(3):375–80. pmid:29521134
- 10. Li J, Peng P, Mei Q, Xia S, Tian Y, Hu L, et al. The impact of UGT2B7 C802T and CYP3A4*1G polymorphisms on pain relief in cancer patients receiving oxycontin. Supportive care in cancer: official journal of the Multinational Association of Supportive Care in Cancer. 2018;26(8):2763–7. pmid:29502154
- 11. Kuip EJ, Zandvliet ML, Koolen SL, Mathijssen RH, van der Rijt CC. A review of factors explaining variability in fentanyl pharmacokinetics; focus on implications for cancer patients. British journal of clinical pharmacology. 2017;83(2):294–313. pmid:27619152
- 12. Zhang W, Chang YZ, Kan QC, Zhang LR, Li ZS, Lu H, et al. CYP3A4*1G genetic polymorphism influences CYP3A activity and response to fentanyl in Chinese gynecologic patients. European journal of clinical pharmacology. 2010;66(1):61–6. pmid:19784640
- 13. He BX, Shi L, Qiu J, Zeng XH, Zhao SJ. The effect of CYP3A4*1G allele on the pharmacokinetics of atorvastatin in Chinese Han patients with coronary heart disease. Journal of clinical pharmacology. 2014;54(4):462–7. pmid:24214373
- 14. Uesugi M, Hosokawa M, Shinke H, Hashimoto E, Takahashi T, Kawai T, et al. Influence of cytochrome P450 (CYP) 3A4*1G polymorphism on the pharmacokinetics of tacrolimus, probability of acute cellular rejection, and mRNA expression level of CYP3A5 rather than CYP3A4 in living-donor liver transplant patients. Biological & pharmaceutical bulletin. 2013;36(11):1814–21. pmid:24189425
- 15. Danielak D, Karaźniewicz-Łada M, Wiśniewska K, Bergus P, Burchardt P, Komosa A, et al. Impact of CYP3A4*1G Allele on Clinical Pharmacokinetics and Pharmacodynamics of Clopidogrel. European journal of drug metabolism and pharmacokinetics. 2017;42(1):99–107. pmid:26891871
- 16. Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet (London, England). 2018;392(10152):1015–35. pmid:30146330
- 17. Fakhari S, Waszkiewicz N. Old and New Biomarkers of Alcohol Abuse: Narrative Review. 2023;12(6).
- 18. Zakhari S. Overview: how is alcohol metabolized by the body? Alcohol research & health: the journal of the National Institute on Alcohol Abuse and Alcoholism. 2006;29(4):245–54.
- 19. Sun FR, Wang BY. Alcohol and Metabolic-associated Fatty Liver Disease. 2021;9(5):719–30.
- 20. Angebrandt A, Abulseoud OA, Kisner M, Diazgranados N, Momenan R, Yang Y, et al. Dose-dependent relationship between social drinking and brain aging. Neurobiology of aging. 2022;111:71–81. pmid:34973470
- 21. Eslam M, Newsome PN, Sarin SK, Anstee QM, Targher G, Romero-Gomez M, et al. A new definition for metabolic dysfunction-associated fatty liver disease: An international expert consensus statement. Journal of hepatology. 2020;73(1):202–9. pmid:32278004
- 22. Singal AK, Bataller R, Ahn J, Kamath PS, Shah VH. ACG Clinical Guideline: Alcoholic Liver Disease. The American journal of gastroenterology. 2018;113(2):175–94. pmid:29336434
- 23. Reed JR, Backes WL. The functional effects of physical interactions involving cytochromes P450: putative mechanisms of action and the extent of these effects in biological membranes. Drug metabolism reviews. 2016;48(3):453–69. pmid:27500687
- 24. Cederbaum AI. Ethanol-related cytotoxicity catalyzed by CYP2E1-dependent generation of reactive oxygen intermediates in transduced HepG2 cells. BioFactors (Oxford, England). 1998;8(1–2):93–6. pmid:9699015
- 25. Cederbaum AI. CYP2E1—biochemical and toxicological aspects and role in alcohol-induced liver injury. The Mount Sinai journal of medicine, New York. 2006;73(4):657–72. pmid:16878272
- 26. Dangi B, Davydova NY, Maldonado MA, Abbasi A, Vavilov NE, Zgoda VG, et al. Effects of alcohol-induced increase in CYP2E1 content in human liver microsomes on the activity and cooperativity of CYP3A4. Archives of biochemistry and biophysics. 2021;698:108677. pmid:33197431
- 27. Li X, Wang L, Li D, Niu J, Gao P. Dyslipidemia is a Risk Factor for the Incidence and Severity of Drug-Induced Liver Injury (DILI): A Retrospective Population-Based Study in China. Medical science monitor: international medical journal of experimental and clinical research. 2019;25:3344–53. pmid:31059494
- 28. Yan Q, Su Y, Gao L, Ding N, Zhang HY, E W, et al. Impact of CYP3A4*1G Polymorphism on Fentanyl Analgesia Assessed by Analgesia Nociception Index in Chinese Patients Undergoing Hysteroscopy. Chinese medical journal. 2018;131(22):2693–8. pmid:30381583
- 29. Shetkar SS, Ramakrishnan S, Seth S, Chandna P, Verma SK, Bhargava B, et al. CYP 450 2C19 polymorphisms in Indian patients with coronary artery disease. Indian heart journal. 2014;66(1):16–24. pmid:24581091
- 30. EASL Clinical Practice Guidelines: Management of alcohol-related liver disease. Journal of hepatology. 2018;69(1):154–81. pmid:29628280
- 31. Ardinger CE, Lapish CC. A critical review of front-loading: A maladaptive drinking pattern driven by alcohol’s rewarding effects. 2022;46(10):1772–82. pmid:36239713
- 32. Farke W, Anderson P. Binge drinking in Europe. Adicciones. 2007;19(4):333–9. pmid:18173097
- 33. Day E, Rudd JHF. Alcohol use disorders and the heart. 2019;114(9):1670–8.
- 34. Ballard-Hernandez J, Sall J. Dyslipidemia Update. The Nursing clinics of North America. 2023;58(3):295–308. pmid:37536782
- 35. Berberich AJ, Hegele RA. A Modern Approach to Dyslipidemia. 2022;43(4):611–53.
- 36. Fillmore MI, Rush CR. Alcohol effects on inhibitory and activational response strategies in the acquisition of alcohol and other reinforcers: priming the motivation to drink. Journal of studies on alcohol. 2001;62(5):646–56. pmid:11702804
- 37. Allen HC, Weafer J, Wesley MJ, Fillmore MT. Acute rewarding and disinhibiting effects of alcohol as indicators of drinking habits. Psychopharmacology. 2021;238(1):181–91. pmid:33151374
- 38. Teschke R. Microsomal Ethanol-Oxidizing System: Success Over 50 Years and an Encouraging Future. Alcoholism, clinical and experimental research. 2019;43(3):386–400. pmid:30667528
- 39. Lu Y, Cederbaum AI. CYP2E1 and oxidative liver injury by alcohol. Free radical biology & medicine. 2008;44(5):723–38. pmid:18078827
- 40. Zastrozhin MS, Simirnov VV, Sychev DA, Savchenko LM, Bryun EA, Gushchina YS, et al. Effect of Carbamazepine on the Activity of CYP3A4 Isoenzyme in Patients with Alcohol Addiction. Eksperimental’naia i klinicheskaia farmakologiia. 2016;79(10):18–21.
- 41. Zheng Y, Xu Y, Zhou BY, Sun L, Yu PB, Zhang L, et al. CYP3A4*1B Polymorphism and Cancer Risk: A Meta-Analysis Based on 55 Case-control Studies. Annals of clinical and laboratory science. 2018;48(4):538–45. pmid:30143500
- 42. Murray GI, McFadyen MC, Mitchell RT, Cheung YL, Kerr AC, Melvin WT. Cytochrome P450 CYP3A in human renal cell cancer. British journal of cancer. 1999;79(11–12):1836–42. pmid:10206301
- 43. Murray GI, Patimalla S, Stewart KN, Miller ID, Heys SD. Profiling the expression of cytochrome P450 in breast cancer. Histopathology. 2010;57(2):202–11. pmid:20716162
- 44. Barron KA, Jeffries KA, Krupenko NI. Sphingolipids and the link between alcohol and cancer. Chemico-biological interactions. 2020;322:109058. pmid:32171848
- 45. Boffetta P, Hashibe M. Alcohol and cancer. The Lancet Oncology. 2006;7(2):149–56. pmid:16455479
- 46. Froogh G, Garcia V, Laniado Schwartzman M. The CYP/20-HETE/GPR75 axis in hypertension. Advances in pharmacology. 2022;94:1–25. pmid:35659370
- 47. Luoma PV. Cytochrome P450—physiological key factor against cholesterol accumulation and the atherosclerotic vascular process. Annals of medicine. 2007;39(5):359–70. pmid:17701478
- 48. Song CY, Ghafoor K, Ghafoor HU, Khan NS, Thirunavukkarasu S, Jennings BL, et al. Cytochrome P450 1B1 Contributes to the Development of Atherosclerosis and Hypertension in Apolipoprotein E-Deficient Mice. Hypertension (Dallas, Tex: 1979). 2016;67(1):206–13. pmid:26573711
- 49. Masip J, Germà Lluch JR. Alcohol, health and cardiovascular disease. Revista clinica espanola. 2021;221(6):359–68. pmid:34059235