Non-Alcoholic Fatty Liver Disease as a Coronary Heart Disease Severity Predictor ()
1. Introduction
Non-alcoholic fatty liver disease (NAFLD) represents a worldwide health problem with an increasing prevalence reaching about 75% of chronic liver disease (CLD) in the developed countries, which makes it the most common CLD in the western world [1]. In a recent meta-analysis, the global prevalence of NAFLD was estimated to be around 25% with highest prevalence in the Middle East and South America and lowest in Africa [2].
Traditionally, NAFLD has linked to liver-related morbidities through its progression to non-alcoholic steatohepatitis (NASH) with subsequent liver cirrhosis, and it is expected that NAFLD related liver diseases will be the leading cause of liver transplantation by 2030 [3]. In addition to this obvious link between NAFLD and end-stage liver disease, several studies suggested the presence of an association between NAFLD and cardiovascular disease (CVD). Recently, a large body of evidence has supported this suggestion and classified CVD as the main cause of death in patients with NAFLD [4] and considered NAFLD as a significant independent risk factor for subclinical and clinical CVD in the absence of the classic cardiovascular risk factors [5] [6].
In contrary to the traditional cardiovascular risk factors like diabetes and obesity, and despite the growing evidence for the association of CVD with NAFLD, the exact mechanism of this association and the degree of correlation between the grade of NAFLD and the severity of CVD are not well-studied [7] [8] [9]. The aim of our work was to study the correlation between NAFLD and the severity of coronary heart disease (CHD) as determined by Gensini score.
2. Materials and Method
2.1. Patients
Patients without prior history of definite ischemic event who were scheduled for coronary angiography from July 2019 - December 2019 at Qena university hospital, Qena, Egypt were included, while those with known history of definite CVD or heart failure were initially excluded. Patients with prior history of CLD including chronic hepatitis C (CHC), chronic hepatitis B (CHB) and NAFLD/NASH or renal impairment were excluded. After initial abdominal ultrasound (US), patients with definite cirrhotic echo pattern or any confounding factor interferes with accurate transient elastography (TE) reading such as hepatocellular carcinoma, ascites or morbid obesity were excluded.
2.2. Transient Elastography (TE)
Liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) were obtained by an expert operator using FibroScan® device (Echosense, Paris, France). The procedure was performed after 8-hour fasting while the patient in the supine position. Result was not considered reliable except after acquisition of 12 successful readings with interquartile range/median ratio less than 30% [10]. LSM was used to estimate the METAVIR fibrosis stage as follows: F0-F1: 2.5 - 6.9 kPa; F2: 7.0 - 9.4 kPa; F3: 9.5 - 12.4 kPa; F4: ≥ 12.5 kPa [11]. CAP was expressed in dB/m and its values were used to estimate steatosis stage as follows: S0 < 238 dB/m, S1: 238 - 258 dB/m, S2: 259 - 291 dB/m and S3: ≥ 292 dB/m [12].
2.3. Coronary Angiography
Coronary angiography was performed within 4 weeks of enrollment by an expert cardiologist blinded about the LSM & CAP readings of the patients. Gensini score was then calculated as mentioned in the literature [13] [14].
2.4. The Studied Variables
Gensini score will be correlated to the continuous variables including: age, fasting blood sugar (FBS), total serum cholesterol (TC), triglycerides, high density lipoprotein (HDL), alanine transaminase (ALT), aspartate transaminase (AST) and serum bilirubin, and categorical variables including: gender, diabetes mellitus (DM), hypertension (HTN), smoking, liver fibrosis (F0-F4) and liver steatosis (S0-S3).
2.5. Statistical Analysis
Categorical variables are expressed as number and percent, continuous variables as median and interquartile ranges (IQR). Chi squared test was used to compare non-parametric variables. Pearson correlation was used to study the correlation between Gensini score and other variables. Univariate and multivariate logistic regression was calculated to identify the statistically significant CVD risk predictors. Analysis was performed using SPSS®, version 22. p < 0.05 was considered statistically significant.
2.6. Ethical Clearance
The study protocol was concomitant with the ethical guidelines of the 1975 Declaration of Helsinki and approved by the ethical committee of Qena Faculty of Medicine, South Valley University, Qena, Egypt. A written informed consent was obtained from all included patients before enrollment in this study.
3. Result
A total of 104 patients were initially enrolled in this work, 4 patients were excluded from our analysis; 3 had abnormal renal biochemistry and 1 had microalbuminuria. The baseline criteria of the finally included 100 patients are shown in Table 1; the mean age was 48 years (±8 SD), 30% were females, 52% were smokers, 30% had type 2 diabetes and 36% had essential hypertension. The rest
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Table 1. Baseline criteria in the studied patients. Categorical variables are expressed as number and percent while continuous variables are expressed as median and interquartile ranges (IQR 25 & IQR 75) except the age which is expressed as mean and standard deviation.
of the baseline criteria including liver fibrosis (F0-F5) & steatosis (S0-S3), lipid profile, random blood sugar (RBS), serum creatinine, alanine transaminase (ALT), aspartate transaminase (AST), serum bilirubin and serum albumin were also shown.
Correlation between the result of coronary angiography and the continuous baseline variables has revealed statistically significant positive correlation between Gensini score with ALT (r = 0.4, p = 0.002) and FBS (r = 0.6, p < 0.001), while the rest of variables showed statistically insignificant correlation, Table 2.
Correlation between Gensini score and categorical variables is shown in Table 3, in which fibrosis, steatosis and diabetes have shown statistically significant positive correlation (p < 0.001). The other categorical variables including hypertension, smoking and female gender had statistically insignificant correlation.
Figure 1 shows a statistically significant difference between the Gensini score in patients with early fibrosis versus those with significant fibrosis (median: 24 versus 74, p = 0.002), while Figure 2 shows gradual increment in the Gensini
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Table 2. Correlation between Gensini score and the continuous variables.
(r): Pearson correlation coefficient.
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Table 3. Correlation between Gensini score and the categorical variables.
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Figure 1. Difference between the median Gensini score in patients with early fibrosis (F0-F1) versus those with significant fibrosis (F2-F4), p = 0.02.
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Figure 2. Difference among Gensini scores in patients with the different steatosis groups, p = 0.01.
score with the higher steatosis grades; medians: 10.5, 21.7, 57.6 and 102.6 in S0, S1, S2 and S3 respectively, p = 0.01.
Independent variables that have significantly predicted higher Gensini score in univariable regression analysis were: diabetes (OR: 55.6, 95% CI: (41 - 70), p = 0.001), hypertension (OR: 19, 95% CI: (2 - 37), p = 0.02), F2-F4 fibrosis (OR: 33, 95% CI: (24 - 38), p = 0.001) and S2-S3 steatosis (OR: 34, 95% CI: (23 - 40), p = 0.001), while in multivariable regression analysis; the statistically significant variables were: diabetes (OR: 23, 95% CI: (10 - 37), p = 0.001), hypertension (OR: 11, 95% CI: (4.8 - 22), p = 0.04) and S2-S3 steatosis (OR: 24, 95% CI: (17 - 31), p = 0.001), Table 4.
4. Discussion
Regarding its pathologic features, disease onset and progression, NAFLD is strongly linked to obesity, diabetes and metabolic syndrome. However; recent studies have recognized NAFLD as a separate entity independent of these diseases based on the notice that not all diabetics have NAFLD and not all NAFLD patients are obese [9] [15], also genetic predisposition to NAFLD has recently been identified in genome-wide studies [16] [17] [18] [19]. Therefore, NAFLD may play a direct role in the development and progression of CVD [20]. In the other hand; as CVD is the most common cause of death in patients with NAFLD, the 2016 European Association for the Study of the Liver (EASL) and the 2018 American Association for the Study of Liver Diseases (AASLD) guidelines recommend mandatory screening for cardiovascular health and aggressive modification of CVD risk for all NAFLD people [9] [15].
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Table 4. Univariate and multivariate regression of the studied variables.
In two cross-sectional studies by Targher et al. [21] [22] on 343 type 1 and 2839 type 2 diabetics, authors have concluded that NAFLD is associated with higher prevalence of CVD after adjusting for conventional CVD risk factors and metabolic syndrome components with odds ratios of 7.6 (CI: 3.6 - 24) and 1.49 (CI: 1.1 - 2) respectively. Interestingly; a meta-analysis of 34 studies reported an association between NAFLD and increased risk of prevalent and incident CVD (OR: 1.81, CI: 1.23 - 2.66) and (HR: 1.37, CI: 1.10 - 1.72) respectively, but no association was reported between it and the cardiovascular overall mortality [23].
Our current study yielded similar relationship between S2-S3 NAFLD and CVD (OR: 24, CI: 17 - 31), and despite the smaller number of included patients in our study, the used tools for diagnosis of NAFLD and CVD; either transient elastography and coronary angiography, are more accurate and objective than those in the previous two studies [21] [22] that were observational and depended only on the history for diagnosis of CVD (coronary, cerebrovascular, and peripheral vascular disease), and abdominal US for diagnosis of NAFLD. Figure 3 shows an example of 33-year-old male patient with S3 liver steatosis (CAP = 368) and his angiography findings showed significant stenosis at the left circumflex coronary artery (LCX), chronic total occlusion at the left anterior descending (LAD) and normal right coronary artery (RCA), with moderate-severity coronary ischemia as indicated by Gensini score of 56. Amazingly; this patient had a body mass index of 31 kg/m2 with no other cardiovascular risk factors.
In contrary to the above-mentioned data, NAFLD as estimated by fatty liver index was not a significant predictor of acute myocardial infarction in a long-term prospective study which also emphasized interplay of confounders [24]. Another large-scale prospective study by Chang et al. has shown similar findings with insignificant association between NAFLD and CVD hospitalization after further adjusting for potential mediators [25].
The discrepancy between the results of the latter two studies and the previous ones could be assumed to the wide array of cardiovascular presentations that considered in each study as well as the variable methods of NAFLD diagnosis which included the US, computerized tomography and non-invasive markers.
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Figure 3. Transient elastography of 33-year-old male patient with S3 liver steatosis (CAP = 368 dB/m), F0-F1 fibrosis (3.6 kilopascal); both appear red-encircled, and angiographic findings showed significant stenosis (yellow horizontal arrow) at the left circumflex coronary artery (LCX), chronic total occlusion (yellow vertical arrow) at the left anterior descending (LAD) and normal right coronary artery (RCA), with calculated Gensini score of 56.
The main advantage of our study is using CAP as a diagnostic tool for NAFLD which allows not just diagnosis of NAFLD but also its stratification from S0 to S3, and coronary angiography with Gensini score calculation which reflects more realistic assessment of the cardiovascular risk. However, we had certain limitations including small sample size and lack of long-term follow up.
5. Conclusion
In conclusion, NAFLD is an independent cardiovascular risk predictor with statistically significant increase in Gensini score with the higher grades of NAFLD.
Acknowledgements
We acknowledge Dr: Albair Abdul-Maseh for his kind effort in arranging the patients’ schedules.
Abbreviations
CAP: Controlled Attenuation Parameter.
CLD: Chronic Liver Disease.
CVD: Cardiovascular Disease.
LSM: Liver Stiffness Measurement.
NAFLD: Non-Alcoholic Fatty Liver Disease.
NASH: Non-Alcoholic Steatohepatitis.
TE: Transient Elastography.
US: Abdominal Ultrasound.
NOTES
*Corresponding author.