Hematological and Oxidative Stress Markers Analysis for Detection and Prediction of Osteoporosis in Post-menopausal Women
Derouiche Samir1,2*, Haddig Nour El-houda1, Zerzour Aicha1
1Department of Cellular and Molecular Biology, Faculty of Natural Sciences and Life, University of El Oued, El-Oued 39000, Algeria
2Laboratory of Biodiversity and Application of Biotechnology in the Agricultural Field, University of El Oued, El-Oued 39000, Algeria.
ABSTRACT
The main purpose of this work was to analyze some biological and oxidative stress markers to predict and diagnose osteoporosis in postmenopausal women. For the experiment, we have chosen 20 healthy menopausal women as control and 20 menopausal women who had osteoporosis. Some biochemical, hematological, and oxidative stress parameters were measured. The sensitivity and specificity of oxidative stress biomarkers in serum, erythrocytes, and leucocytes were estimated using Receiver Operating Characteristics (ROC) curve design. The results of the study demonstrate a significant change (P<0.05) in biochemical and hematological markers during osteoporosis in post-menopausal women. In addition, results show a significant enhancement of MDA content and reduction in GSH, SOD, Catalase, and TAC levels in patients compared to control. Some oxidative stress markers identify as risk factors (P<0.05, OR>1) and represented an important significant specificity (P<0.05) for osteoporosis diagnosis such as serum MDA (AUC=99.6%), erythrocytic GSH (AUC=100%), and leukocytic SOD (AUC=62.5%), with a strong correlation (P<0.05) between GSH levels and serum calcium and ALP changes. In conclusion, several clinical factors contributed to the evolution of osteoporosis in postmenopausal women. Oxidative stress and hematologic markers represent very important diagnostic and predictive factors for osteoporosis in women during the post-menopause period.
Keywords: Osteoporosis, Post-menopause, Risk factors, Oxidative stress
Introduction
Menopause implies the continual cessation of the monthly cycle and the conclusion of regenerative ability (Weiss et al., 2004). The menopausal evolution includes a period of dynamic alterations in non-reproductive and reproductive tissues. This evolution is considered to have a main effect on the etiology of symptoms including night sweats, uterine bleeding problems, vulvovaginal atrophy, hot flashes, and mood changes (Zeidabadi et al., 2020). Osteoporosis is defined as an illness that is specified by disruption of bone microarchitecture, deterioration of bone tissue, and low bone mass: it may result in compromised bone quality and an increment in the chance of breaks (Al-Shali et al., 2019; Nambi et al., 2020; Zerzour et al., 2020). The social and economic burden of osteoporosis is enhancing continuously due to the world population’s aging (Sözen et al., 2017). Nowadays, osteoporosis is projected to affect about 14 million adults above 50 years old by the year 2020, affecting above 10 million people in the United States; (Wright et al., 2014). Several late landmarks in scientific studies have indicated that oxidative stress is a significant factor in human beings, resulting in physiological and metabolic modifications and different illnesses in the body (Atoussi et al., 2021). Oxidative stress is an unusual condition as a result of an overabundance generation of oxidants in comparison to the antioxidants (Derouiche et al., 2017) that has been regarded as the major cause of many pathologies (Chetehouna et al., 2020). Minerals have a significant effect on the blood clotting, receiving and sending signals, formation of bones, production of cell energy, oxygen transportation, keeping normal heartbeat, synthesizing and metabolizing proteins and fats, providing immunity to the body, acting as coenzymes, and helping nervous system work properly (Tomlinson et al., 2020). Considering this information, the purpose of our work is based on the determination of the variation and specificity of some oxidative and hematological stress markers in the prediction and diagnosis following up of osteoporosis in menopausal women.
MATERIALS AND METHODS
Subjects and study design
Ethical approval was obtained from the ethics committee (28 EC/DCMB/FNSL/EU2020) of the department of cellular and molecular biology, Faculty of Natural Sciences and Life, El-Oued University. This work was applied to 40 volunteer women aged between 43-54 years, they were divided into two groups; a group of 20 healthy control women with an average age of 48.26±0.43 years old, a group of 20 menopause women having osteoporosis with the mean age 48.77±0.21 years old. In addition, in this study, we included voluntary women living in the Guemar El-Oued region, who were women suffering from osteoporosis aged from 43 to 54 and like control women were in good health and did not have any pathology. Moreover, in the present research, we excluded all women who were suffering from other acute or chronic pathology and all women using drugs for 30 days or during post-menopausal periods.
Sample collection and analyses
Blood sampling for both groups was done during morning fasting. After the blood sampling, the blood was collected in two types of tubes, in the anticoagulant tube (EDTA), for hematological and oxidative stress (MDA, GSH, SOD, and CAT) parameters assays. In dry tubes, samples were centrifuged at 3000 rpm for 10 minutes, and then the serum was recovered to achieve the dosage of biochemistry parameters: Glucose, calcium, iron, PAL, vitamin C, and total antioxidant ORAC. Serum glucose, calcium, iron, and PAL were determined by the Semi-auto Analyzer Mindray BA-88A and measured using commercial kits from Biomaghreb, (Biomaghreb: glucose-20121, calcium-20051, iron-20064, and PAL-20015. Hematological analysis (FNS) was performed by the hematology Auto analyzer (Mindray).
Oxidative markers measurement
MDA was measured using TBA reagent according to the method described by Sastre et al. (2000). The level of reduced Glutathione is determined according to the Weak and Cory (1988). The catalase activity consisting measuring the catalase-induced loss of H2O2 contained in the sample according to the method of Aebi (1984). The assay method of SOD activity was the method of Beauchamp and Fridovich, (1971). The plasma vitamin C is measured according to the method of Jagota and Dani (1982) using the Folin reagent. The total antioxidant power of the serum and its capacity to absorb free oxygen radicals (ORAC: Oxygen Radical Absorbance Capacity) were evaluated according to the method of Oyaizu, (1986).
Statistical analysis
Statistical analysis was performed by the SPSSV20.0 software. Results comparisons were carried out by using the Student T-test to contrast means among the groups. Correlation analysis was carried out using the Pearson Correlation test and regression analysis was used for other analyses and statistical data. Differences were considered statically significant at p <0.05.
rESULTS AND DISCUSSION
Description of the study population
The general data of socioeconomic characteristics of the two groups of subjects include age, Body Weight, BMI, social case, number of children, job, educational level, and Blood group. Most of these indicators do not have any statistically significant (P > 0.05) differences but serum calcium was decreased in the patients' group compared to the control. Other baseline characteristics between the two main groups are summarized in Table 1.
Table 1. Demographic, Clinical and Laboratory Features between the Study Groups
|
Parameter |
Control (n=20) |
Patients (n=20) |
P- value |
|
|
Age (ys) |
48.26±0.43 |
48.77±0.21 |
0.114 |
|
|
Body Weight (kg) |
68.60±0.243 |
71.40±0.61 |
0.080 |
|
|
Height (cm) |
162.76±0.164 |
161.98±0.130 |
0.204 |
|
|
Body Mass index |
26.01±0.182 |
27.39±0.108 |
0.152 |
|
|
Blood glucose (g/l) |
0.82±0.023 |
0.92±0.018 |
0.009 |
|
|
Serum Calcium (g/l) |
74.31±1.08 |
65.15±2.04 |
0.006 |
|
|
Serum ALP (U/l) |
129.0±10.2 |
182±13.9 |
0.002 |
|
|
Number of children |
5,333±0,18 |
6,06±0,18 |
0,081 |
|
|
Social Case (%) |
Married |
81 |
96 |
0.014 |
|
Single |
7 |
2 |
0.024 |
|
|
Divorced |
10 |
1 |
0.000 |
|
|
Widow |
2 |
1 |
0.072 |
|
|
Job (%) |
Worker |
25 |
10 |
0.000 |
|
Housewife |
75 |
90 |
0.000 |
|
|
Educational Level (%) |
Illiterate |
13 |
14 |
0.062 |
|
Primary |
15 |
28 |
0.002 |
|
|
Junior high |
26 |
24 |
0.123 |
|
|
High School |
26 |
23 |
0.092 |
|
|
Higher education |
20 |
11 |
0.014 |
|
|
Blood Group (%) |
A |
43.33 |
20 |
0.000 |
|
B |
10 |
10 |
0.231 |
|
|
AB |
6.67 |
13 |
0.002 |
|
|
O |
40 |
57 |
0.051 |
|
The illustrated results of the hematological parameters in (Table 2) show that in the osteoporosis patients group there was a significant increase (P˂0.05) in WBC, Lymphocytes, RBC, and in HCT and PLT (P0.001>) levels and no significant change of hemoglobin level in comparison with the control group.
Table 2. Changes in the Haematological Levels in Control and Osteoporosis Patients
|
Parameter |
Control (n=20) |
patients (n=20) |
P-value |
|
White Blood Cells (×103/µl) |
5,669±0,286 |
7,169±0,56 |
0,020 |
|
Lymphocytes (×103/µ) |
2,042±0,073 |
2,200±0,195 |
0,432 |
|
Hemoglobin (g/dl) |
125,73±2,49 |
130,06±1,83 |
0,032 |
|
Red Blood Cells (×106 /µl) |
4,562±0,055 |
4,752±0,086 |
0,043 |
|
Hematocrite (%) |
39,8±0,719 |
43,256±0,603 |
0,000 |
|
Platelets (×103/µl) |
136,06±1,86 |
255,6±16,4 |
0,000 |
Oxidative stress markers
The analysis of blood oxidative stress parameters in control and patient are shown in Table 3, The results show a significant decrease of GSH level in erythrocyte (P˂0.001), leukocyte (P˂0.001) and serum (P˂0.001) and also decrease of catalase and SOD activities in leukocyte (P˂0.001) and in serum (P˂0.001, P˂0.05) and TAC activity in serum and a significant increase of MDA level in leukocyte (P˂0.05) and serum (P˂0.001) in osteoporosis patients group in comparison to the control group.
Table 3. Parameters of Oxidative Stress in Blood of Control and Osteoporosis Patients
|
Parameter |
Control (n=20) |
Patient (n=20) |
P-value |
|
|
MDA (nM/mg of Hb) |
Erythrocytes |
9,06±1,03 |
7,587±0,780 |
0,083 |
|
Leukocytes |
7,566±0,785 |
12,11±1,76 |
0,021 |
|
|
Serum |
28,02±2,84 |
92,5±10,4 |
0,000 |
|
|
GSH (nM/mg of Hb) |
Erythrocytes |
1,065±0,041 |
0,898± 0,027 |
0,000 |
|
Leukocytes |
1,448±0,217 |
0,765±0,107 |
0,000 |
|
|
Serum |
3,751±0,146 |
2,969±0,295 |
0,021 |
|
|
CAT (UI/g of Hb) |
Leukocytes |
0,032±0,003 |
0,021±0,001 |
0,000 |
|
Serum |
0,11±0,006 |
0,099±0,004 |
0,031 |
|
|
SOD (U/mg of Hb) |
Leukocytes |
15,250±0,423 |
12,929±0,339 |
0,000 |
|
Serum |
78,56±1,99 |
73,43±1,03 |
0,000 |
|
|
Vit C (μg/ml) |
Serum |
61,63±3,47 |
66,38±3,86 |
0,238 |
|
TAC (U/l) |
Serum |
21,24±1,55 |
14,88±1,69 |
0,002 |
Study of odds ratio values of biochemical and oxidative stress markers
Odds Ratio (OR) values for some oxidative stress parameters and biochemical markers of controls and patients groups (Table 4) show that decreased serum ORAC, leukocyte SOD, erythrocyte GSH, leukocyte GSH, leukocyte catalase, and serum calcium are shown to be important risk factors for osteoporosis OR (6.303-106.375) with P<0.05. Reciprocally, decreased serum MDA and serum PAL are protective factors against osteoporosis in the study population (OR=0.032; P=0.000, OR=0.084; P=0.000), respectively.
Table 4. Odds Ratio Value of Biochemical and Oxidative Stress Markers
|
|
Control % |
Patient % |
OR |
CI95% |
P-value |
|
Serum ORAC |
|
|
6.303 |
2.604-15.255 |
0.000 |
|
Positive |
32 |
11 |
|
|
|
|
Negative |
18 |
39 |
|
|
|
|
Leukocyte SOD |
|
|
106.375 |
13.475-839.745 |
0.000 |
|
Positive |
37 |
01 |
|
|
|
|
Negative |
16 |
46 |
|
|
|
|
Erythrocyte GSH |
|
|
37.161 |
4.796-287.936 |
0.000 |
|
Positive |
32 |
01 |
|
|
|
|
Negative |
31 |
36 |
|
|
|
|
Leukocyte GSH |
|
|
18.951 |
2.428-147.909 |
0.000 |
|
Positive |
21 |
01 |
|
|
|
|
Negative |
41 |
37 |
|
|
|
|
Leukocyte catalase |
|
|
8.957 |
2.424-33.103 |
0.000 |
|
Positive |
17 |
3 |
|
|
|
|
Negative |
31 |
49 |
|
|
|
|
Serum MDA |
|
|
0.032 |
0.004-0.248 |
0.000 |
|
Positive |
30 |
50 |
|
|
|
|
Negative |
19 |
1 |
|
|
|
|
Serum calcium |
|
|
18.222 |
5.035-65.946 |
0.000 |
|
Positive |
32 |
3 |
|
|
|
|
Negative |
24 |
41 |
|
|
|
|
Serum PAL |
|
|
0.084 |
0.030-0.233 |
0.000 |
|
Positive |
19 |
44 |
|
|
|
|
Negative |
31 |
6 |
|
|
|
Predictive factors study
The results obtained (Figure 1 and Table 5) show that serum MDA, Erythrocytic GSH, and Leukocytic SOD levels are the highest percentage of specificity (100%) and important percentage of sensitivity (50.0, 43.8, 75%) respectively for women with osteoporosis. In addition, Serum TAC, Leukocyte GSH, and Leukocytic catalase were significant predictive factors for osteoporosis in postmenopausal women.
Table 5. Sensitivity, Specificity and AUC Values of Biological Markers for Women with Osteoporosis
|
Test Result Variable(s) |
Sensitivity (%) |
Specificity (%) |
AUC (%) |
SE |
CI95% |
P-value |
|
|
Serum TAC |
50.0 |
25 |
19.1 |
0.076 |
0.043 |
0.340 |
0.003 |
|
Leukocytic SOD |
75.0 |
100 |
62.5 |
0.063 |
0.001 |
0.249 |
0.000 |
|
Serum SOD |
68.8 |
31.2 |
32.2 |
0.099 |
0.129 |
0.516 |
0.086 |
|
Erythrocytic GSH |
43.8 |
100 |
100 |
0.000 |
0.000 |
0.000 |
0.000 |
|
Leukocyte GSH |
18.8 |
25 |
10.5 |
0.058 |
0.000 |
0.219 |
0.000 |
|
Serum GSH |
81.3 |
12.5 |
42.8 |
0.103 |
0.226 |
0.630 |
0.486 |
|
Serum vitamin C |
43.8 |
62.5 |
58.6 |
0.103 |
0.384 |
0.788 |
0.407 |
|
Leukocytic catalase |
50.0 |
62 |
15.8 |
0.071 |
0.019 |
0.298 |
0.001 |
|
Serum catalase |
31.3 |
43.7 |
30.9 |
0.096 |
0.121 |
0.496 |
0.065 |
|
Erythrocytic MDA |
43.8 |
25 |
34.0 |
0.100 |
0.145 |
0.535 |
0.122 |
|
Leukocytic MDA |
43.8 |
100 |
70.7 |
0.098 |
0.515 |
0.899 |
0.064 |
|
Serum MDA |
50.0 |
100 |
99.6 |
0.006 |
0.983 |
1.000 |
0.000 |
|
|
|
Figure 1. ROC Curve for Biological Markers in Women with Osteoporosis |
Correlation between biological markers
The results (Table 6) represent the correlation between oxidative stress parameters (serum ORAC, leukocyte SOD, erythrocyte GSH, leukocyte GSH, leukocyte catalase, and serum MDA), hematological parameters (WBC, HGB, RBC, HCT, PLT), and biochemical parameters (calcium, ALP) in patients group with osteoporosis. There was a positive correlation (P<0.05) between erythrocyte GSH and calcium (P=0,005 and R=0,381), erythrocyte GSH and ALP (P=0,047 and R=0,393), Leukocyte GSH and serum calcium (P=0,046 and R=0,34). There was no correlation (P>0.05) between the rest of the correlation test in the patients' groups.
Table 6. Correlation between Biological Markers for Women with Osteoporosis
|
Parameters |
WBC |
HGB |
RBC |
HCT |
PLT |
Serum Calcium |
Serum ALP |
||
|
Serum ORAC |
P |
0,926 |
0.565 |
0,729 |
0,642 |
0,429 |
0,447 |
0,734 |
|
|
R |
0,019 |
0.118 |
0,071 |
0,096 |
0,162 |
-0,108 |
0,070 |
||
|
Leukocyte SOD |
P |
0,580 |
0,879 |
0,582 |
0,420 |
0,644 |
0,435 |
0,146 |
|
|
R |
-0,114 |
-0,031 |
-0,113 |
-0,165 |
-0,095 |
0,111 |
-0,293 |
||
|
Erythrocyte GSH |
P |
0,624 |
0,221 |
0,665 |
0,303 |
0,617 |
0,005 |
0,047 |
|
|
R |
-0,101 |
-0,248 |
-0,089 |
-0,210 |
0,103 |
0,381 |
0,393 |
||
|
Leukocyte GSH |
P |
0,458 |
0,463 |
0,929 |
0,700 |
0,320 |
0,046 |
0,955 |
|
|
R |
0,152 |
-0,151 |
-0,018 |
-0,079 |
0,203 |
0,340 |
-0,012 |
||
|
Leukocyte Catalase |
P |
0,318 |
0,379 |
0,962 |
0,722 |
0,761 |
0,375 |
0,115 |
|
|
R |
-0,204 |
-0,180 |
-0,010 |
-0,073 |
-0,063 |
-0,126 |
0,317 |
||
|
Serum MDA |
P |
0,938 |
0,870 |
0,715 |
0,619 |
0,285 |
0,582 |
0,521 |
|
|
R |
0,016 |
0,034 |
-0,075 |
0,102 |
-0,218 |
0,078 |
-0,132 |
||
The obtained results show a significant increase in PAL level in the patient group as compared to control. This result is in line with the research of Pardhe et al., (2017), who show that the PAL level was slightly higher in the post-menopausal group. All Bone Mineral Density (BMD) results were remarkably reduced by PAL increment, while bone-specific alkaline phosphatase, is an indicator of bone turnover and formation and is utilized in the skeletal status evaluation (Hailing et al., 2018). On the other hand, we found a significant decrease in calcium level in the patients' group as compared to the control group. This result is consistent with the research of (Beto, 2015), whose findings demonstrated that the serum calcium level was significantly lower in the post-menopausal group. Calcium plays a key role in human physiology. As a main constituent of the mineral component calcium provides stiffness to the collagen network of the mature bone. Inadequate calcium accrual, resulting in a sub-optimal bone mass peak and low bone mineralization, is a significant parameter favoring osteoporosis and fracture (Kelly et al., 2020). The results of hematological parameters indicated a remarkable increment in WBC, HGB, HCT, and PLT in the osteoporosis patients group in comparison to the control group. These results support a possible linkage between bone metabolism and hematopoiesis. Hematopoiesis is the process by which immature blood cells develop into mature cells (Paspaliaris & Kolios, 2019). According to Schyrr et al., (2018), differences in the osteoporotic bone microenvironment translate into altered dynamics upon hematopoietic stress. Moreover, Valderrábano et al., (2018) found that low bone health would result in enhanced cells of myeloid lineage such as neutrophils and monocytes. Osteoblastic lineage cells might affect neutrophils and monocytes differentiation. The enhancement in neutrophils can be associated with the chronic inflammation that happens with aging. The results of the oxidative stress study showed for the osteoporosis patients group a very high significant increase in serum MDA level as compared to the control women. The results showed that serum MDA has a high specificity in ROC statistics, which showed the importance of MDA in the prognostic of osteoporosis. The results found were similar to those observed in the study of Berköz et al. (2017) which showed that serum MDA levels were significantly higher in postmenopausal women with osteoporosis than in the healthy controls. Sakuraba et al., (2020) reported that MDA had an osteoclastic activity. Our results show that leukocyte MDA is significantly increased in the osteoporosis patients group as compared to control women, with high specificity in the ROC statistic test, which showed the importance of this parameter in the identification of the disease. These results are supported by Ahmedian et al., (2017) study. Raghavan et al. (2012) found that MDA could significantly induce key inflammatory cytokine expression in lymphocyte via oxidant stress, signaling pathways (p38MAPK), and transcriptional factors (NF-κB), which in turn enhance lymphocyte activation. The results also show that for the osteoporosis patients group, a very high significant decrease in leukocyte and serum SOD level (P˂0.001) in comparison to that in the control. Depressing actions of the antioxidant enzymes such as SOD indicated a defense mechanism that has been overwhelmed in mitigating the enhanced superoxide production by the osteoclasts showed by enhanced contents of MDA in the serum (Kuyumcu & Aycan, 2018) and it might cause markedly increased bone demineralization and, as a result, may increase destructive free radical levels (Bacou et al., 2021). The results show that for the osteoporosis patients group, a highly significant decrease in serum TAC level (P˂0.01) as compared to that in the control. TAC method is relevant to in vivo conditions since it uses a biologically relevant free radical source (peroxyl radical) that is the highest common free radical in human biology. It considers both degrees of inhibition and inhibition time of free radical action as a result of antioxidants (Hunyadi, 2019). The results of the oxidative stress study showed that there is a significant decrease in GSH, catalase, and SOD level of WBC, in GSH level of RBC, and both of GSH and catalase level of serum in the patients' group compared to controls. Glutathione (GSH) is a non-enzymatic antioxidant that aids the defense mechanism against oxidative stress created by free radicals (Derouiche et al., 2019). To reduce the cell-damaging impacts of ROS (reactive oxygen species), aerobic organisms evolved by expressing different antioxidant defenses, such as catalase. The mechanisms by which cells sense H2O2 and O2• are not comprehended; however, many transcriptional parameters that adjust the expression of antioxidant genes are adjusted by decrease counteractions and oxidation (Tonelli et al., 2018). Intracellular Redox Imbalance resulting from SOD shortage has a vital impact on the progress and development ion of bone fragility both in vitro and in vivo (Tan et al., 2018).
CONCLUSION
This study indicates that hematological parameters change and Oxidative stress were correlated with the osteoporosis disease of menopause in women as a reason or as a developmental factor for it. And through the ROC analysis results MDA, GSH, SOD, and TAC were considered to be the most important markers which contribute in the early detection of osteoporosis disease in post-menopause women.
ACKNOWLEDGMENTS: This research was made possible by the D01N01UN390120190001 research project, which was funded by the Algerian Ministry of Higher Education and the Directorate General for Scientific Research and Technological Development.
CONFLICT OF INTEREST: None
FINANCIAL SUPPORT: None
ETHICS STATEMENT: Ethical approval was obtained from the ethics committee (28 EC/DCMB/FNSL/EU2020) of the department of cellular and molecular biology, Faculty of Natural Sciences and Life, University of El Oued.
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