Elevated Liver Enzymes and its Association with Type Two Diabetes Melli- tus: The Occurrence in Yemeni Population

This case-control study was aimed to investigate the association between elevated liver enzymes and type 2 diabetes mellitus (T2DM) in Yemeni patients. This present study comprising 142 T2D patients and 142 healthy control subjects were recruited from the diabetic outpatient clinic of Ibn-Sina Hospital in Mukalla during the period from 1st January to 30th May 2020. Serum fasting blood glucose (FBG), total cholesterol, triglyceride, high-density lipoprotein cholesterol (HDL-C), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and gamma-glutamyl transferase (GGT) were analyzed using the Cobas Integra Plus 400 autoanalyzer. Anthropometric and blood pressure measurements were taken from each participant. T2D patients had significantly higher FBG (P ≤ 0.0001), total cholesterol (P ≤ 0.0001), LDL-C (P ≤ 0.0001), and GGT (P ≤ 0.0001) while, HDL-C was significantly lower in T2D patients (P= 0.021). Serum ALT and GGT levels were significantly associated with increased incident T2D risk (P= 0.006 for ALT and 0.022 for GGT), and the odds ratios at 95% CI comparing the highest versus lower tertiles of ALT and GGT were 2.75(2.01-3.48) and 1.17(1.83-6.42) respectively. In conclusion, markedly elevated ALT and GGT are positively associated with increased blood glucose levels and are used as predictive biomarkers for developing a higher risk of diabetes. Thus, routine screening of ALT and GGT in T2D patients is recommended for the early detection of liver disorders.


Introduction
Diabetes mellitus is a metabolic disorder characterized by chronic hyperglycemia, which results from defective insulin action and secretion or both [1]. World Health Organization explores that the number of diabetic patients will exceed 350 million by 2030 [1]. Previous data have documented liver disease is a major cause of morbidity and mortality of type 2 diabetes patients [2,3]. It is known that the liver is a vital organ in the metabolism of carbohydrates and in maintaining glucose homeostasis during fasting and postprandial periods [2,4].
Research indicates that diabetes is associated with several liver diseases. Non-Alcoholic Fatty Liver Disease (NAFLD) is the scope of chronic liver disease in patients with T2D [5], which is characterized by excess deposition of fat in the liver and associated with hepatic insulin resistance (IR) [3] and T2D risk [5]. Serum alanine aminotransferase (ALT) and gamma-glutamyltransferase (GGT) are good biomarkers of NAFLD. ALT has been considered a specific marker of liver injury, as found in high concentrations in hepatocytes [6], while GGT is

Study design and subject selection
This case-control study was carried out at the College of Medicine and Health Sciences, Hadhramout University, and the subjects were recruited from the diabetic outpatient clinic of Ibn-Sina hospital, Mukalla during the period from 1 st January to 30 th May 2020. A total of 284 Yemeni adult subjects randomly selected and recruited into this study. At recruitment, an in-person interview was conducted using a structured questionnaire to collect health-related information. The study group was subdivided into two groups: 142 healthy control subjects composed of 51 males and 91 females (age: 46.0 ± 7.94 yr.), and 142 T2D patients composed of 64 males and 78 females (age: 54.0 ± 8.29 yr) T2D patients were those who reported being diagnosed with T2D. Healthy control subjects were selected from the remaining participants who were free of T2D and were matched for age, sex, and dialect group with cases on a 1:1 ratio. Moreover, the selected healthy control subjects were screened for the presence of undiagnosed T2D at the time of blood donation by measuring fasting blood glucose (FBG). Healthy control subjects with FBG ≥ 7.0mmol/L were excluded from the study. Written consent was obtained from each participant entered into the study. The study was approved by the Ethics Committee of the Medicine and Health Sciences College, Hadhramout University, Mukalla, Yemen. Patients with comorbidities such as chronic liver disease, chronic renal disease, cardiovascular disease, and malignancy were excluded.

Data collection
A gave questionnaire form focusing on demographic information, and diabetes history was given to all subjects. The patient's demographic data, clinical presentation, medical history, and physical findings were taken from each participant. These data are included: The patient's age, sex, smoking status (never, current or past), hypertension status (yes or no), diabetes status (yes or no), diabetes duration (years), diabetes medication, and diabetes complications. Participants were diagnosed with diabetes according to medical history, present intake of diabetes medications, or the American Diabetes Association (ADA) criteria [22]. Patients with T2DM were defined as fasting blood glucose level ≥ 126mg/dl (≥7.0mmol/L), 2-hour postprandial plasma glucose level ≥ 200mg/dl (≥ 11.1mmol/L), or HbA1c ≥ 6.5% [22]. Classification of Body Mass Index (BMI) was based on WHO [23].

Anthropometric and blood pressure measurements
Weight and height were measured according to WHO guidelines [15]. Body mass index (BMI) was calculated as weight/height 2 (Kg/m 2 ). Obese subjects were defined as BMI ≥ 30kg/m 2 and normal-weight subjects having a BMI of 18-25 according to WHO guidelines [23]. Patients who had a blood pressure of ≥ 140/90mmHg or were taking antihypertensive medications were diagnosed with hypertension [24]. A true healthy normal ALT level ranges from 29 to 33 IU/l for males and 19 to 25 IU/l for females as classified by the American College of Gastroenterology (ACG) [25].

Blood Sampling Biochemical Analysis
Ten milliliters of the venous blood sample was obtained from consenting subjects. The blood samples were collected by vein puncture in tubes without anticoagulant. The blood samples were then transported to the laboratory immediately. The serum was then separated and stored at -20°C freezers till analyses. The serum samples of matched case-control pairs were randomly placed next to each other with the case/control status blinded to the laboratory personnel and were processed and tested in the same batch. All laboratory equipment was calibrated. Thawing freezing was avoided by dividing the samples into aliquots. Plasma Fasting Blood Glucose (FBG), total cholesterol, triglycerides, and HDL-cholesterol (HDL-C) were determined enzymatically using a chemical autoanalyzer (Cobas Integra 400 Plus, Roche diagnostic GmbH, Mannheim, Switzerland), following the standard procedures as described by the manufacturer. Concentrations of LDL-cholesterol (LDL-C) were calculated using Friedwald's formula [26]. The biochemical investigations were analyzed in the National Center for Public Health Labs-Mukalla, Yemen.

Statistical analysis
The results analyzed using the statistical package for the social sciences for windows (version 24) and are expressed by Mean ± Standard Deviation (SD) for continuous variables (normally distributed). Non-continuous variables are expressed by median (inter-quartile range) and n (percentage) for categorical variables. Independent Student's t-test used for normally distributed continuous variables and Wilcoxon signed-rank test for skewed continuous variables. The Pearson correlation test was performed with ALT, AST, and GGT as the dependent variables. ALT, AST, and GGT were divided into tertiles according to their distribution in the healthy control group, and the lowest tertile served as the reference group. We also used conditional logistic regression to model their associations with T2D, adjusting for age (continuous), smoking (never, current, and past smoker), and BMI (continuous) (model 1). Total cholesterol (mmol/L), triglyceride (mmol/L), HDL-C (mmol/L), and LDL-C (mmol/L) were added to model 1 as model 2 in all in tertiles. We repeated the same analysis in 176 cases and control pairs with baseline FBG <7.0 mmol/L. Conditional regression analyses were done to estimate the odds ratios (ORs) and 95% CIs for T2D patients. The statistical analysis was conducted at a 95% confidence level, and a P-value <0.05 was considered statistically significant.

Results
Descriptive statistics of anthropometric and biochemical data of the study population were studied (Table 1). T2D patients had significantly increased BMI (P=0.008), systolic BP (P ≤ 0.0001), diastolic BP (P ≤ 0.0001), FBG (P ≤ 0.0001), total cholesterol (P ≤ 0.0001), LDL-C (P ≤ 0.0001), and GGT (P=0.016) compared to healthy control subjects. No significant difference was found in serum triglyceride (P=0.097) and ALT (P=0.07). Healthy control subjects had significantly increased HDL-C (P=0.021) and AST (P=0.001) compared to T2D patients. On the other hand, 31.7% of T2D patients had hypertension, whereas 6.3% of healthy control subjects had hypertension. Besides, in T2D patients, the current smokers were 4.2%, and the former smokers were 3.5%. According to BMI criteria, 38.7% of T2D patients were overweight and 24.6% were obese and 40.1% and 14.1% of healthy control subjects were overweight or obese, respectively.
Furthermore, the relationship between liver enzymes and incident T2D risk was studied. Higher ALT and GGT levels were associated with higher T2D risk (OR comparing extreme tertiles 2.75 (95% CI 2.01 to 3.  Table 4). In contrast, ALT and GGT levels showed no significant association among case-control pairs with FBG <7.0mmol/L, while higher AST levels were positively associated with increased T2D risk among case-controls with FBG <7.0mmol/L in the final model (or comparing highest versus lowest tertile 1.578(95% CI 2.718 to 3.466, P= 0.023) ( Table 4).

Discussion
Although the incidence of diabetes is increasing worldwide and its prevalence is higher in developing countries, no studies have examined the relationship between elevated liver enzymes and T2D risk in Yemeni patients. Our research, therefore, was focused on the liver as the vital organ contributing to glucose homeostasis during the fasting and postprandial stage. Also, most people aged ≥ 45 years in developing countries have diabetes [27]. These findings were Open Access Journal convenient with our study showed that T2D patients had significantly higher mean age compared to healthy control subjects (Table 1).

Sci Forschen
Our present findings also observed significantly increased BMI, systolic BP, and diastolic BP in T2D patients than healthy control subjects. The current results also showed that serum FBG, total cholesterol, and LDL-C were significantly higher in T2D patients than healthy control subjects. At the same time, no significant difference among both groups for serum triglycerides was found. In contrast, HDL-C was significantly lower in T2D patients. Our study further revealed higher levels of GGT in T2D patients. At the same time, AST was considerably lower in T2D patients. Besides, no significant difference between both groups for ALT was observed.
Our study also revealed positive correlations between GGT with FBG, total cholesterol, triglycerides, and LDL-C across the combined group before and after adjustment for age and BMI. The association between ALT with FBG and triglycerides was no longer significant after adjustment for age and BMI. Such a positive relationship between liver enzymes and blood lipid profile in T2D patients has been observed in previous studies [4,[28][29][30][31][32]. This finding supports the role of hepatic IR in NAFLD's pathogenesis in patients with T2D [6,33].
Moreover, Cho NH, et al. reported a correlation between ALT activity and increased fatty liver [16]. The impairment of the normal process of synthesis and elimination of triglycerides may progress to fibrosis, cirrhosis, and hepatocellu lar carcinoma [34,35]. A triglyceride is a significant form of lipids stored in the liver of patients with NAFLD.
In addition to its effect on lipid metabolism, insulin also contributes a pro-inflammatory effect to liver abrasion [29]. Thus, inflammation contributes to IR. Moreover, Pro-inflammatory cytokines and transcription factors are highly expressed in white adipose tissue and the liver. In contrast, obesity, a state of chronic low-grade inflammation and a risk factor for IR and NAFLD, is induced by over nutrition. It is a primary cause of decreased insulin sensitivity. Obesity leads to lipid accumulation and activates the c-Jun N-terminal kinase (JNK) and nuclear factor-kappa B (NF-κB) signaling pathways, which consequently increase the production of pro-inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6) [36]. Besides, various adipose tissue-derived proteins, such as adiponectin and leptin, are considered significant links between obesity, IR, and related inflammatory disorders [37].
GGT is known as a marker of hepatobiliary disorders and is associated with other pathological conditions like diabetes. Free radicals generated by diabetes consume glutathione which induces the increased expression of GGT in hepatocytes. Various studies have suggested the association of GGT concentrations with T2D [37][38][39][40][41], and hyperlipidemia [42]. These findings agree with our study; GGT was significantly associated with the hyperglycemic and hyperlipidemia profile. We observed ALT and GGT together were positively correlated. Moreover, some data also reported elevated GGT levels with ALT in T2D patients with dyslipidemia [39,40,43]. Even though we did not confirm the presence of fatty liver by ultrasound techniques, we showed the relationship of ALT, AST, and GGT with the predictors of diabetes and lipid profile parameters, presenting hepatocellular injury.
A study of male Korean workers found that AST was independently associated with diabetes [44], while in a study of male Japanese office workers; AST was not associated with T2D risk [40]. Some studies also reported that ALT is a signifi cant predictor of diabetes while AST is not [45]. These findings agree with our conclusions as AST does not show a considerable relation ship with the studied parameters. Besides, Clark JM, et al. also suggested that mild or chronic elevation of these aminotransferases may be due to NAFLD [46,47]. However, our study is limited to the standard method of liver biopsy for the prediction of NAFLD. Still, it goes with the analysis of the third national health and nutritional examination survey, where individuals with NAFLD have elevated aminotransferases.
Besides, our study also found that increased ALT and GGT levels improve the prediction of T2D risk. Several previous studies supported this: a meta-analysis reported a pooled relative risk of 1.34 (95% CI 1.27 to 1.42) comparing the highest versus lowest tertiles of GGT levels [48] and 1.66 (95% CI 1.31 to 2.09) for ALT [49]. Besides, a case-control study in a Chinese population also reported higher levels of ALT and GGT with increased risk of T2D 2.00 (1.01 to 3.96; ALT) and 2.38 (1.21 to 4.66; GGT) [21]. A Mendelian randomization study further provided evidence for the relationship between higher GGT levels and the hepatic IR studies [50]. In contrast, our study did not observe any relationship of AST incident T2D risk, which was consistent with previous studies [18,30,38,51]. This may be due to a lack of specificity of AST for liver diseases [18]. However, one Korean study showed a positive correlation between GGT/ALT and T2D risk among patients without fatty liver, suggesting alternative pathways exist [17]. Thus, increased GGT and ALT levels were linked to T2D development as surrogate NAFLD measures [52]. NAFLD also may indicate fat deposition in other organs such as skeletal muscle, myocardium, and  0.826 ORs of liver enzymes in the whole dataset and among cases with baseline FBG (<7.0mmol/L) and their matched controls were analysed using conditional logistic regression models with adjustment for the following covariates. Model 1: Adjusted for age, BMI, smoking status and history of hypertension (yes/no).
The present study's strength included adjustment for wellestablished diabetes risk factors, including BMI, blood lipids, and hypertension, and using comprehensive statistical methods (Pearson correlation coefficient and regression analysis) to explore the predictive utility of liver enzymes with other risk factors. However, there are some limitations: Our sample size may be small and thus underpowered to detect the interaction with ALT and GGT. We measured liver enzymes only once and may not represent a long-term profile. We did not measure hepatitis B and C infection, resulting in elevated liver enzymes. We did not measure hs-CRP, insulin, C-peptide, leptin, and adiponectin as predictive biomarkers linked between obesity, hepatic IR, and related inflammatory disorders in T2D patients. Thus, a further large sample size with measurements of insulin, hs-CRP, leptin, adiponectin, and interleukins are required to confirm these correlations. In conclusion, higher ALT and GGT are positively