Study the Impact of Cytomegalovirus (CMV) Infection and the Risk Factor for Liver Dysfunction in Saudi Patients.
Human cytomegalovirus (CMV) as a member of the herpes virus family is one of the most common infecting viruses in humans. The prevalence of congenital CMV infection varies from 0.2% to 2% (). In developing countries, the reported prevalence of congenital CMV infection varies dramatically within and between populations, with some recorded prevalence ranged from 6.1% to 14.0% (2). Cytomegalovirus is human-to-human transmissible through close bodily contact, coughs and sneezes (3). Because CMV infection may occur during delivery, through infected breast milk or by blood transfusion-perinatal transmission are much more prevalent than other congenital infections (4).Cytomegalovirus (CMV) remains an important etiological factor for morbidity and mortality of many organ transplant recipients, patients who receive chemotherapy or high-dose corticosteroids or persons infected with human immunodeficiency virus type 1 (HIV-1) (5). It is also a major cause of infantile hepatitis (6). Based on the World Health Organization (WHO) records, about 40% of all adults worldwide are infected in 2011, indicated by the presence of IgG and IgM in the general population (7).
Presence of both IgM and IgG in the same sample necessitates avidity testing which helps in differentiating between a recent and non-recent primary infection (8). Clinically concomitant with the remarkable increase of these antibodies, there is a mild-moderate increase of transaminases, markers of liver function and lymphomonocytosis. There is study by Vujacich, et al.,2006 (9) reported a 6 and 3.5 fold increase in alanine transaminase (ALT) and aspartate transaminase (AST) respectively in patients with CMV infection. Here in this study we investigated CMV seroprevalence and liver enzyme profiles in different age groups of saudi Arabia patients to find the relationship between CMV infection and risk factors for liver dysfunction.
Subjects and Methods
Study Population and Specimens
The focus of our study was tested 455 serum samples of patients with elevation of liver profiles (ALT, AsT, ALP and GGT) and controls categorized in different age groups were collected from different general hospitals and polyclinics in KSA from March 2014 to June 2016 in different ages and gender. Serum samples which were tested for CMV seropositive (by detection of CMV- IgG and IgM and non- A to G hepatitis virus (non HAV, HBV, HCV, HDV, HEV and HGV). where molecular technical for Extraction of virus nucleic acid, PCR and real-time PCR were performed according to methods described by Lin and Floros, 2000 (10) for selected the samples non- A to G hepatitis virus. Whole blood samples were collected and centrifuged at 2,000 g for 15 min. Sera were taken and stored at -20 [degrees] C. The samples were coded by date of collection, sample number, gender and age. The IRB in the Faculty of Medicine at KSU (Riyadh, KSA) approved the study. Informed consent for the collection of specimens was obtained from all cases to the collection of specimens. Serology tests
The CMV IgG and IgM were screened in patients' sera by using a commercially available capture enzyme-linked immunosorbent assay (ELISA) (CMV IgM and CMV IgG, Dia.Pro; Diagnostic BioprobesSrl, Italy). Samples with concentrations e" 1.10 IU/ml (WHO) were considered to be positive for anti-CMV IgG antibody and samples with concentrations d" 0.9 Iu/mlwere interpreted as negative, while samples with concentrations 0.91 - 1.09 IU/ml were considered equivocal. For CMV IgM, samples were considered positive when the ratio of the sample optical density at 450 nm to the cutoff value (signal to cutoff) was >1.1;equivocal, 0.9 - 1.0; and negative, d" 0.8. ELISA assay results were analyzed in all samples included in the study.
Statistical analysis
SPSS software was used for statistical analysis. Results were expressed as mean [+ or -] SD and all statistical comparisons were made by means of independent t-test with pd"0.05 considered as significant. Pearson's correlations between measured parameters were also presented. Receiver Operating Characteristic (ROC) analysis was performed as a comprehensive way to assess the accuracy of the studied markers as previously described (11). The area under the curve (AUC) was used provides a useful metric to compare IgG and IgM as two CMV seropositivity markers. Whereas an AUC value close to 1 indicates an excellent diagnostic and predictive marker, a curve that lies close to the diagonal (AUC = 0.5) has no diagnostic utility. AUC close to 1 is always accompanied by satisfactory values of specificity and sensitivity of the biomarker.
Multiple regression analysis was also used to find the correlation between the IgG, IgM and different liver enzymes. In this analysis [R.sup.2] described the proportion or percentage of variance in the dependent variable (IgG and IgM) explained by the variance in the independent variables together which sometimes called the predictor variables (AsT, ALT, ALP and GGT). An [R.sup.2] of 1.00 indicates that 100% of the variation in the dependent variable is explained by the independent variables. Conversely, an [R.sup.2] of 0.0 indicates the absence of variation in the dependent variable due to the independent variables. The [beta] coefficients values showed the direction either positive or negative and the contribution of the independent variable relative to the other independent variables in explaining the variation of the dependent variable. [R.sup.2] and ([beta]) coefficient provide most of what we need to interpret our multiple regression data.
RESULTS
Table 1 and figure 1 demonstrate the high significant elevations of AST, ALT and GGT together with the non-significant change in ALP. It can be easily noticed that both transaminases (ALT and AST) together with GGT were markedly higher in the three studied age groups with the first age group (18-25 years) recording the much higher percentage increase for of ALT (139.21%) and for AST (153.95%)compared to a much lower increase in the other two studied age groups.
While the data in and Table 2 and figure 2 show the significant correlations between both IgG and IgM as measures of CMV seropositivity. In addition, significant correlations were also recorded between these two antibodies and AST, ALT, and GGT as measures of liver injury risk (e.g. liver cirrhosis).
Table 3 and figure 3 represent the receiver operating characteristics (ROC) analysis of IgG and IgM in male and females CMV- seropositive patients. An area under the curve equal to 1 together with 100% sensitivity and specificity were recorded for both antibodies in the three age groups of CMV patients.
The results in Table 4 and 5 show the stepwise multiple regression analysis using IgG and IgM as dependent variable respectively and AST, ALT, ALP and GGT as independent variables.
Adjusted [R.sup.2] and [beta] coefficients of the different variables are listed.
DISCUSSION
CMV infection may have important health consequences. Many studies propose that infection with CM reduce the performance of the immune system to respond to further antigenic challenge and increase the risk of developing liver dysfunction (12), (13, 14). This work aims to extend these findings by investigating the effect of age on prevalence of CMV as non hepatotropic agent infection in a large number of samples that included different range of ages. The provision of information on hygiene may be an effective and inexpensive method for preventing CMV infection and control its role on liver dysfunction in future.
Patients with liver enzyme deviations are usually divided into two categories either alkaline phosphatase (ALK) or transaminases (ALT and AST) elevation. In case of alkaline phosphatase, patients generally have either cholestasis disease or infiltrative disease. Transaminases elevation is predominant and can be a marker of hepatocellular dysfunction due to viral hepatitis, autoimmune hepatitis or liver toxins. (3) -Glutamyltranspeptidase (GGT) levels tend to parallel alkaline phosphatase elevations that originate from the liver (15,16).
The data in Table 1 demonstrates the high significant increase of both AST and ALT together with the non-significant elevation of ALP. This can ascertain the possibility to develop liver dysfunction in CMV patients. It can be easily noticed that age group 118-25 was at higher risk to develop liver dysfunction compared to the other 2 elder groups (26-35 & 36-45) which recorded much lower increase in both transaminases. Effect of CMV infection in inducing both transaminases as markers of liver dysfunction was confirmed through the elevation of IgG and IgM. as antibodies against CMV infection.
Elevated transaminases were significantly associated with both CMV seropositivity (i.e CMV patients compared to control) and high CMV antibody levels (age group 1 compared to age groups 2 and 3). Comparisons of the 3 specific age groups revealed that this association was detectable early in life (18-25 years of age).
This is in good agreement with the previous study of Lopo et al, 201113 in which they study the prevalence of CMV infection in 8 age groups of Portuguese population range from 2 to 65. They recorded that while the antibody prevalence in children at school age (age groups 5-9 years and 10-14 years) was more or less similar to that at pre-school age, it was increased to reach 71.3% in the age group between 15 and 19 years, which corresponds to a greater sexual exposure. In addition to non- sexual contact (11,12,15).
Studies with similar age groups conducted in other countries, such as the United States, Japan, France, England, Poland and Russia, describe seroprevalences ranging between 51.5% and 78.0% (17, 18, 19) which is still lower than the 136% increase recorded for 18-25 years age group of the present study. As it is well known that sexual transmission is a likely risk factor for exposure to CMV (20) so the remarkable high seropositivity in the 18-25 age group compared to the other 2 groups can be attributed to the more frequent sex intercourse, as a significant predictor of CMV infection. This much higher CMV seropositivity can be connected with the ethnic/ socioeconomic status of Saudi population. This can be supported by the study of Ghazi et al. 2002, which recorded a prevalence of 92.1% CMV total IgG antibodies in pregnant Saudi women (20).
In Table 2 and figure 2 the data showing Pearson's correlations between ALT, AST, ALP and GGT in one hand and IgG and IgM in the other hand. It can be easily noticed that both antibodies were positively correlated with high significant difference. This can suggest the importance of both as markers of CMV seropositivity. In addition both antibodies were independently correlated with the four measured liver enzymes which can ascertain the concomitant liver dysfunction associated with CMV infection. This can find a support in the recent work of (21-22) which prove that CMV infection usually induces autoimmune hepatitis and primary biliary cirrhosis. This can explain the high significant positive correlation between CMV antibodies and AST, ALT and ALP in the three age groups tested.
The receiver operating characteristics (ROC) curve as a fundamental tool for biomarkers evaluation was performed. using the same computer program. In a ROC curve the true positive rate (sensitivity) is plotted as a function of the false positive rate (100-specificity) for different cut-off points of a parameter. Each point on the ROC curve represents a sensitivity/specificity pair corresponding to a particular decision threshold. The area under the ROC curve is a measure of how well a parameter can distinguish between CMV seropositive and control subjects. The area under the curve (AUC) provides a useful measure to compare different biomarkers. Whereas an AUC value close to 1 indicates an excellent diagnostic and predictive marker, a curve that lies close to the diagonal (AUC = 0.5) has no diagnostic utility. AUC close to 1 is always accompanied by satisfactory values of specificity and sensitivity of the biomarker. From 0.9 to 1 considered as excellent, 0.8 to 0.9 as good, 0.7-0.8 as fair, 0.6-0.7 as poor and 0.5-0.6 as fail. Based on this information, both antibodies can be used as excellent predictive markers for CMV infection in all three tested age groups.
1. In the present study, the general purpose of multiple regressions is to learn more about the relationship between several independent or predictor variables (AST, ALT, ALP and GGT), and a dependent or criterion variable(IgG or IgM) through the recorded [R.sup.2] and [beta] coefficient values. In this analysis [R.sup.2] describes the proportion or percentage of variance in the dependent variable explained by the variance in the independent variables together which sometimes called the predictor variables. An [R.sup.2] of 1.00 indicates that 100% of the variation in the dependent variable is explained by the independent variables. Conversely, an [R.sup.2] of 0.0 indicates the absence of variation in the dependent variable due to the independent variables. The [beta] coefficients values show the direction either positive or negative and the contribution of the independent variable relative to the other independent variables in explaining the variation of the dependent variable. [R.sup.2] and ([beta]) coefficient provide most of what we need to interpret our multiple regression data. Table 4 and 5demonstrate the linear regression analysis between the measured parameters using IgG and IgM as dependent variables respectively. it can be easily noticed that both IgG and IgM show low [R.sup.2] values. This suggests was expected as CMV as viral infectious disease never induced in case of liver dysfunction (22).On the other hand, [beta] coefficients values for AST, ALT and GGT as independent variables point out that ALT is the most important enzyme related to CMV seropositivity measured by high IgG and IgM. ALT recorded [beta] coefficients values of 0.840 and 0.711 in 18-25 and 26-35 age groups respectively.
In Conclusion, our results indicate a high significant association between CMV seropositivity and increased levels of AST, ALT, and GGT, as markers of liver dysfunction that may lead to liver cirrhosis in patients without hepatotropic viruses suchas HCV and HBV. Based on other studies showing that CMV seroprevalence in patients with hepatocellular carcinoma (HCC) is significantly higher than in patients without HCC and is positively correlated with liver cirrhosis (23,24). Therefore, elimination of CMV infection via the development and administration of treatments or vaccines may reduce HCC mortality rates (24), Therefore, elimination of CMV infection whichis a potentially feasible and important task for preventing diseases linked to CMV infection (25). Future studies will be needed to further define the role of CMV in liver disorder.
http://dx.doi.org/10.22207/JPAM.12.3.27
(Received: 06 July 2018; accepted: 29 August 2018)
ACKNOWLEDGEMENTS
The authors would like to thank King Abdul Aziz City for Science and Technology (KACST) for supporting the present work as part of NTPC funded projects No. AT-34-208.
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Randa Mohamed Ahmed Farag [1], Dujana AlAyobi [2], Khalid A Alsaleh [3], Hye-Joo Kwon [4], Afaf EL-Ansary [5] and Emad Anwar Dawoud [6]
[1] Assistant Prof of Virology and Molecular Biology, Health Sciences Research Center (HSCR), Princess Nourah bint Abdulrahman university (PNu), Kingdom of Saudi arabia (KSA).
[2] Prof of Genetic, biology Department, Princess nourah bint abdulrahman university (PNu), Kingdom of Saudi arabia (KSA).
[3] Prof of oncology and Hematology, college of Medicine, King Saud university (KSu), Kingdom of Saudi arabia (KSA).
[4] Assistant Prof of Molecular biology, Princess nourah bint Abdulrahman university (PNu), Kingdom of Saudi Arabia (KSA).
[5] Prof biochemistry, central Labe, King Saud University (KSU).
[6] Assistant Prof of Hepatopathology, Faculty of Medicine, EL-Azher University and Specialist Physician, oncology clinic-Medical Affaies, Tawam Hospital, Al Ain, UAE.
* To whom all correspondence should be addressed. E-mail: randa792006@gmail.com
Caption: Fig. 2. Correlation between all parameters according in each age group (18 - 25, 26 - 35 and 36 - 45) with best fit line curve (positive correlation)
Caption: Fig. 3. ROC Curve of IgG according the age (18 - 25 and 26 - 35) and IgM according age group of patients 18 - 25, 26-35 and 36 - 45
Table 1. Comparisons of ALT, AST, ALP, GGT, IgG and IgM in
the three studiedn age groups of CMV seropositive patients compared
to healthy control participants
Parameter Age Groups Group N Min. Max.
ALT ([micro]/L) 18-25 Control 15 17.06 35.09
Patients 150 55.78 95.47
26-35 Control 10 33.01 55.80
Patients 165 56.20 76.22
36-45 Control 15 35.29 45.25
Patients 140 56.33 76.22
AST ([micro]/L) 18-25 Control 15 12.56 22.23
Patients 150 35.08 62.71
26-35 Control 10 22.72 27.72
Patients 165 35.08 62.01
36-45 Control 15 26.42 32.90
Patients 140 35.23 58.50
ALP (IU/L) 18-25 Control 15 49.31 148.20
Patients 150 45.34 148.20
26-35 Control 10 78.45 120.00
Patients 165 45.02 148.20
36-45 Control 15 67.23 137.30
Patients 140 45.02 147.30
GGT ([micro]/L) 18-25 Control 15 12.02 58.46
Patients 150 34.23 88.32
26-35 Control 10 27.37 48.82
Patients 165 34.23 88.32
36-45 Control 15 40.34 57.37
Patients 140 40.34 72.01
IgG 18-25 Control 15 0.15 0.62
Patients 150 3.81 35.05
26-35 Control 10 0.24 0.72
Patients 165 4.05 19.06
36-45 Control 15 0.14 0.82
Patients 140 5.22 19.06
IgM 18-25 Control 15 0.11 0.37
Patients 150 12.34 90.29
26-35 Control 10 0.10 0.52
Patients 165 12.04 33.56
36-45 Control 15 0.11 0.42
Patients 140 12.34 34.74
Parameter Age Groups Group Mean [+ or -] S.D.
ALT ([micro]/L) 18-25 Control 25.62 [+ or -] 5.37
Patients 61.29 [+ or -] 7.35
26-35 Control 40.94 [+ or -] 10.14
Patients 59.81 [+ or -] 3.71
36-45 Control 40.77 [+ or -] 3.33
Patients 63.25 [+ or -] 5.35
AST ([micro]/L) 18-25 Control 17.09 [+ or -] 2.70
Patients 43.39 [+ or -] 6.29
26-35 Control 25.24 [+ or -] 2.05
Patients 42.15 [+ or -] 5.58
36-45 Control 29.39 [+ or -] 1.92
Patients 43.15 [+ or -] 5.11
ALP (IU/L) 18-25 Control 84.89 [+ or -] 31.69
Patients 84.54 [+ or -] 32.61
26-35 Control 96.50 [+ or -] 17.86
Patients 82.63 [+ or -] 31.58
36-45 Control 94.97 [+ or -] 21.87
Patients 76.35 [+ or -] 30.98
GGT ([micro]/L) 18-25 Control 31.80 [+ or -] 12.17
Patients 59.34 [+ or -] 14.73
26-35 Control 39.39 [+ or -] 9.07
Patients 59.26 [+ or -] 13.68
36-45 Control 50.71 [+ or -] 6.53
Patients 60.50 [+ or -] 11.90
IgG 18-25 Control 0.38 [+ or -] 0.16
Patients 11.85 [+ or -] 6.38
26-35 Control 0.48 [+ or -] 0.21
Patients 9.78 [+ or -] 4.08
36-45 Control 0.40 [+ or -] 0.21
Patients 10.60 [+ or -] 5.23
IgM 18-25 Control 0.24 [+ or -] 0.09
Patients 26.89 [+ or -] 16.95
26-35 Control 0.34 [+ or -] 0.18
Patients 20.26 [+ or -] 4.64
36-45 Control 0.27 [+ or -] 0.09
Patients 20.21 [+ or -] 4.22
Parameter Age Groups Group Percent Change P value
ALT ([micro]/L) 18-25 Control 100.00 0.001
Patients 239.21
26-35 Control 100.00 0.033
Patients 146.11
36-45 Control 100.00 0.001
Patients 155.16
AST ([micro]/L) 18-25 Control 100.00 0.001
Patients 253.95
26-35 Control 100.00 0.001
Patients 167.05
36-45 Control 100.00 0.001
Patients 146.83
ALP (IU/L) 18-25 Control 100.00 0.971
Patients 99.58
26-35 Control 100.00 0.397
Patients 85.62
36-45 Control 100.00 0.133
Patients 80.40
GGT ([micro]/L) 18-25 Control 100.00 0.001
Patients 186.61
26-35 Control 100.00 0.008
Patients 150.43
36-45 Control 100.00 0.010
Patients 119.30
IgG 18-25 Control 100.00 0.001
Patients 3143.43
26-35 Control 100.00 0.001
Patients 2037.04
36-45 Control 100.00 0.001
Patients 2641.17
IgM 18-25 Control 100.00 0.001
Patients 11135.82
26-35 Control 100.00 0.001
Patients 6001.57
36-45 Control 100.00 0.001
Patients 7379.55
* Table 1 describes the independent f-test between control and
patients categorized in 3 different age groups (18-25, 26-35
and 36-45)for all parameters
Table 2. Pearson's correlations between the measured Parameters
Parameters Age R (Person Sig.
Groups Correlation)
IgG ~ IgM 18-25 0.791** 0.001 P (a)
26-35 0.734** 0.001 P (a)
36-45 0.717** 0.001 P (a)
IgG ~ ALT ([micro]/L) 18-25 0.695** 0.001 P (a)
26-35 0.544** 0.001 P (a)
36-45 0.697** 0.001 P (a)
IgG ~ AST ([micro]/L) 18-25 0.580** 0.001 P (a)
26-35 0.570** 0.001 P (a)
36-45 0.694** 0.001 P (a)
IgG ~ GGT ([micro]/L) 18-25 0.464** 0.001 P (a)
26-35 0.240 0.137 P (a)
36-45 0.331 0.080 P (a)
IgM ~ ALT ([micro]/L) 18-25 0.695** 0.001 P (a)
26-35 0.659** 0.001 P (a)
36-45 0.825** 0.001 P (a)
IgM ~ AST ([micro]/L) 18-25 0.586** 0.001 P (a)
26-35 0.707** 0.001 P (a)
36-45 0.800** 0.001 P (a)
IgM ~ GGT ([micro]/L) 18-25 0.532** 0.001 P (a)
26-35 0.383* 0.015 P (a)
36-45 0.548** 0.002 P (a)
* Correlation is significant at the 0.05 level.
** Correlation is significant at the 0.01 level.
(a) Positive Correlation.
Table 3. ROC-Curve of IgG and IgM olaccording the Age groups
(18-25, 26-35 and 36-45) in Patients group
Group Area under Cut-off Sensitivity Specificity
the curve value % %
IgG 18-25 1.000 2.215 100.0% 100.0%
26-35 1.000 2.385 100.0% 100.0%
36-45 1.000 3.020 100.0% 100.0%
IgM 18-25 1.000 6.355 100.0% 100.0%
26-35 1.000 6.280 100.0% 100.0%
36-45 1.000 6.380 100.0% 100.0%
Table 4. Multiple Regression using stepwise method for
IgG as a dependent variable
Age Groups Predictor Beta P value
Variable
18-25 ALT ([micro]/L) 0.331 0.001
26-35 AST ([micro]/L) 0.369 0.001
36-45 ALT ([micro]/L) 0.395 0.001
Age Groups Adjusted Model
[R.sup.2]
F value P value
18-25 0.476 69.196 0.001
26-35 0.307 18.270 0.001
36-45 0.467 25.520 0.001
Table 5. Multiple Regression using stepwise method for
IgM as a dependent variable
Age Groups Predictor Beta P value Adjusted
Variable [R.sup.2]
18-25 ALT ([micro]/L) 0.840 0.001 0.475
26-35 AST ([micro]/L) 0.715 0.001 0.487
AST ([micro]/L) 0.358 0.017 0.548
36-45 ALT ([micro]/L) 0.711 0.001 0.669
GGT ([micro]/L) 0.258 0.006
ALT ([micro]/L) 0.402 0.003 0.784
GGT ([micro]/L) 0.434 0.024
AST ([micro]/L) 0.231 0.008
Age Groups Predictor Model
Variable
F value P value
18-25 ALT ([micro]/L) 68.953 0.001
26-35 AST ([micro]/L) 37.967 0.001
AST ([micro]/L) 24.675 0.001
36-45 ALT ([micro]/L) 57.468 0.001
GGT ([micro]/L)
ALT ([micro]/L) 34.896 0.001
GGT ([micro]/L)
AST ([micro]/L)
Fig. 1. (a,b,c) Percentage change of IgG and IgM
all parameters in each age group
18-25 26-35 36-45
ALT ([mu]/L) 239.21% 146.11% 155.16%
AST ([mu]/L) 253.95% 167.05% 146.83%
ALP (IU/L) 99.58% 85.62% 50.40%
GGT (IU/L) 156.61% 150.43% 119.30%
IgG 3143.43% 2037.04% 2641.17%
IgM 11135.82% 6001.57% 7379.55%
Note: Table made from bar graph.
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| Author: | Farag, Randa Mohamed Ahmed; AlAyobi, Dujana; Alsaleh, Khalid A.; Kwon, Hye-Joo; EL-Ansary, Afaf; Daw |
|---|---|
| Publication: | Journal of Pure and Applied Microbiology |
| Article Type: | Report |
| Geographic Code: | 7SAUD |
| Date: | Sep 1, 2018 |
| Words: | 4726 |
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