Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by persistent synovial inflammation and progressive joint destruction [1-4]. The pathogenesis of RA involves a complex interplay of immune dysregulation, inflammatory mediators and oxidative stress, leading to irreversible joint damage and functional disability [2,5]. Identifying reliable biomarkers reflecting disease activity and severity is crucial for early diagnosis, disease progression monitoring and therapeutic outcomes [1,6,7]. RA arises from a complex interplay of genetic, environmental and immunological factors that result in dysregulated immune responses and chronic inflammation [8,9]. The etiologies of RA are incompletely understood [10,11]. The destruction of cartilage and bone in RA is mediated by the abnormal release of proteolysis enzymes such as matrix metalloproteinases (MMPs) in rheumatoid synovium, which is stimulated by persistent inflammation [10,12]. The pathogenesis of RA involves a complex interplay of immune dysregulation, inflammatory mediators and oxidative stress, leading to irreversible joint damage and functional disability. Identifying reliable biomarkers reflecting disease activity and severity is crucial for early diagnosis, disease progression monitoring and therapeutic outcomes [13]. 

Rheumatoid arthritis (RA) is a chronic autoimmune disease that leads to progressive joint inflammation, causing bone and cartilage erosion, in addition to its systemic effects on multiple organs, including the liver and kidneys [14]. 

Methotrexate (MTX) is used as the main treatment in the management of the disease due to its ability to suppress the immune response and reduce inflammation [15]. However, its effect on vital organ functions remains of wide interest, especially its combined effect on the liver and kidneys with disease severity. The DAS-28 (Disease Activity Score-28) is used to assess the severity of RA, as it reflects the degree of disease activity and associated systemic inflammation [7,16]. Studies have shown that disease severity may play a major role in affecting liver and kidney function due to the continuous increase in inflammatory processes and the release of cytokines that cause oxidative stress and tissue damage [17]. Furthermore, methotrexate, as a primary treatment for patients, may contribute to the aggravation of the effects on these organs, making it difficult to distinguish between the pathological effect and the pharmacological effect [18]. Fernando De Ritis originally described the De Ritis ratio, sometimes called the AST/ALT ratio, in 1957. Since then, it has been used as a liver function test to distinguish between different types of hepatotoxicity or liver injury [19]. Accordingly, this study aims to study the effect of disease severity (DAS-28) on liver and kidney function for RA patients.

Study Design and Participants

This cross-sectional study evaluated selected biomarkers' diagnostic and prognostic potential in patients with rheumatoid arthritis (RA). 

A total of 220 participants were recruited, including 120 patients (26 males, 132 females), their ages ranged between (19-and 83) years, admitted to the rheumatology unit at Teaching Hospital in Anbar Governorate and diagnosed by a rheumatologist.

Control subjects (100) were randomly selected from volunteers and companions of other patients. Members of this group had an adverse history of any significant illness, including arthritis, arthralgia and other diseases (apparently healthy). Their ages were between (17–70) years from both sexes, which comprised (65) males and (131) females.

RA patients are diagnosed according to the American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) criteria.

All patients were diagnosed with RA for at least one year. Moreover, they were all treated with disease-modifying anti-rheumatic drugs (DMARDs) such as Methotrexate and non-steroidal anti-inflammatory drugs (NSAIDs) and disease-modifying anti-rheumatic drugs (DMARDs), with or without a combination. Include in this study included all patients affected with RA only. While excluded, this study included all patients affected with another type of arthritis or another disease, such as hepatic disease, kidney disease and cardiac disease. 

Sample Collection and Preparation         

Samples were collected from 10 January -2024 to 1st Jun- 2024. According to the ethics committee, blood samples were collected from all participants after obtaining informed consent. Venous blood was drawn into a plain tube. The serum was separated by centrifugation at 3000 xg for 15 minutes and stored at −20°C until further analysis [1,20].

All patients were diagnosed as having RA for at least one year. Moreover, they were all under treatment with non-steroidal anti-inflammatory drugs (NSAIDs) and disease-modifying anti-rheumatic drugs (DMARDs), with or without combination. The cases were not affected by other diseases. At the same time, these patients were divided according to disease activity score 28 (DAS-28) into three groups: mild, moderate and severe.

According to Administrative Order 365, dated 7/1/2024, all procedures followed ethical guidelines and were approved by the institutional ethics committee for the University of Mosul and Anbar Health Department.

Calculation of Disease Activity Score-28 (DAS-28)

Disease activity score-28 (DAS-28) is based on the calculated number of tender and swollen joints (28-joint count). The 28 joints count includes the shoulders, elbows, wrists, first to fifth metacarpophalangeal (MCP) joints, first to fifth proximal interphalangeal (PIP) joints and knees on both sides of the body and serum C-reactive protein (CRP) level [21]. Disease activity score-28-ESR (DAS28-ESR) was calculated using an online calculator by entering each patient's tender joint count, swollen joint count and ESR data [21].

Disease activity in RA patients was assessed using the Disease Activity Score-28 (DAS-28). At the same time, these patients were divided into three groups according to DAS-28: mild, moderate and severe.

Laboratory Analysis

The study included 220 adults divided into two groups: 120 adults affected with RA and the rest (100) adults selected as control groups for comparison. Aspartate aminotransferase (AST), urea and creatinine levels were measured.

Estimation of The Activities of ALP

Alkaline phosphatase activity was estimated by using a kit supplied by Biolabo. The principle assay deepened on the estimated of free phenol released from phenol phosphate by alkaline phosphatase reacts with 4-amino-antipyrine in the presence of alkaline potassium ferricyanide to form a red complex. The absorbance of the red complex was estimated at a wavelength of 510 nm in units of U/l.

Estimation of the ALT and AST

Both ALT and AST are determined in serum using the Biolabo kit. This is a colorimetric method developed by Tonhazy, White and Umbreit where pyruvate or oxalate reacts with 2,4-DNPH to form 2,4-Dinitrophenylhydrazone whose absorbance at 505 nm in the basic solution is proportional to the activity of AST or ALT in the reaction mixture and is measured in U/l [22]. Used the Japanese-origin Fuji automated analyzer device and follow the manufacturer's instructions.

Table (1):  Comparison of Biochemical Variables between Control Group and RA Patients 

Assay The Level of De-Ritis Ratio

Then, the De-ritis ratio (AST/ALT ratio) was calculated by dividing the AST result by the ALT result [23].

Measuring The Concentration of Urea

Urea was estimated using several kits supplied by Biosystem Company using the enzymatic method, as urea is decomposed by the enzyme urease into ammonia and carbon dioxide. The resulting ammonia reacts with salicylate and sodium hypochlorite in the presence of nitroprusside, forming the green complex Indophenol, which is measured at a wavelength of 600 nm (in mmol/l).

Measuring The Concentration of Creatinine

Creatinine was estimated using kits by Biolabo Company. The principle assay depended on the Jaffe reaction method and by colorimetric reactions, that creatinine reacts with picric acid in an alkaline medium. The absorbance is measured at a wavelength of 490nm, the concentration of creatinine expressed in a concentration of mmol/l.

Calculation of The Urea-to-Creatinine Ratio

The measured values are applied in the formula above, either manually or via automated laboratory software.

Determination of C-Reactive Protein Concentration

CRP was estimated in serum using a kit manufactured by Bio ditch Med Inc./ United Kingdom [24].

Statistical Analysis

All data were analyzed using SPSS software (version 25.0). Continuous variables were presented as mean ± standard deviation (SD). The diagnostic performance of biomarkers was evaluated using receiver operating characteristic (ROC) curve analysis, with sensitivity, specificity and area under the curve (AUC) reported. Pearson’s correlation was used to assess the relationship between arginase and visible studies. A p-value < 0.05 was considered statistically significant [25].

The results of this study demonstrate a significant alteration in liver and kidney function markers in rheumatoid arthritis (RA) patients compared to the control group. As shown in Table 1, levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were significantly elevated in RA patients (AST: 52.8 ± 24.1 U/L, ALT: 34.7 ± 7 U/L) compared to the control group (AST: 52.8 ± 24.1 U/L, ALT: 29.8 ± 6.2 U/L), with a p-value of ≤ 0.0001. This suggests hepatic dysfunction, which is commonly reported in RA patients, particularly in those receiving methotrexate (MTX) therapy [26,27]. Additionally, the De-Ritis ratio (AST/ALT) was significantly higher in RA patients (1.6 ± 0.8) compared to controls (0.53 ± 0.08, p ≤ 0.0001), indicating potential hepatic dysfunction. Elevated liver enzymes in RA patients may result from chronic inflammation and the hepatotoxic effects of MTX, which is widely used in RA treatment and known to cause hepatic fibrosis and elevated transaminase levels [28,29].

Renal function markers were also significantly altered in RA patients. Urea and creatinine levels were markedly increased in patients (urea: 33.1 ± 15.6 mg/dL, creatinine: 1.5 ± 0.4 mg/dL) compared to controls (urea: 21.9 ± 3.04 mg/dL, creatinine: 1.3 ± 0.2 mg/dL, p ≤ 0.0001). Furthermore, the urea/creatinine ratio was significantly elevated in RA patients (26.7± 10.7) versus controls (17 ± 3.1, p≤ 0.0001). This suggests possible renal impairment, which has been linked to prolonged inflammation and MTX nephrotoxicity [30,31]. suggesting an imbalance in renal clearance capacity [32]. 

Effect of DAS-28 on Biochemical Parameters

Table 2 highlights the effect of RA severity on biochemical markers. AST levels were significantly elevated in severe RA patients (74.8 ± 16.6 U/L) compared to mild (34.9 ± 19.4 U/L) and moderate cases (46.4 ± 17 U/L). Similarly, the De Ritis ratio showed a substantial increase in severe cases (2.4 ± 0.7, p ≤ 0.0001). The progression of RA severity was also associated with a significant rise in urea (47.8 ± 18.7 mg/dL) and creatinine (1.6 ± 0.5 mg/dL) in severe cases, highlighting the impact of disease severity on renal function. Moreover, CRP levels significantly increased in severe cases (53.7 ± 18.7 mg/dL), reinforcing the systemic inflammatory burden in advanced RA. These findings align with previous studies indicating that higher RA disease activity correlates with greater hepatic and renal dysfunction, partly due to chronic inflammation and drug-induced toxicity [33,34].

Correlation of DAS-28 with Biochemical Variables in RA Patients

Table 3 presents the correlation between DAS-28 and biochemical variables in RA patients. AST (r = 0.64, p ≤ 0.01) and ALT (r = 0.62, p ≤ 0.01) showed significant positive correlations with disease activity, confirming that liver enzyme elevation is associated with RA severity this is in line with previous studies that reported increased transaminase levels due to systemic inflammation and potential hepatotoxicity induced by methotrexate (MTX) therapy, which is commonly used in RA management [35,36]. Also, the De-Ritis ratio (AST/ALT) showed no significant correlation with DAS-28 (r = 0.08, p = 0.41), suggesting

Table (2): Effect of the DAS-28 on the Arginase activity and variables studies

that while individual enzyme levels increase, their relative ratio remains less affected by disease severity. However, in advanced cases with hepatic involvement, a higher De-Ritis ratio has been reported as a marker of hepatic fibrosis and methotrexate-induced liver injury [37]. The findings of this study provide strong evidence linking RA disease severity (DAS-28 score) with biochemical markers of liver and kidney function, suggesting that systemic inflammation and treatment-related hepatotoxicity play a significant role in disease progression. Notably, the elevation in AST and ALT levels, along with increased urea and creatinine, indicates potential hepatic and renal impairment in patients with severe RA [38]. Furthermore, methotrexate (MTX) therapy, which is a cornerstone treatment for RA, has been widely associated with hepatotoxicity and nephrotoxicity. Increased transaminase levels characterize MTX-induced liver injury, while chronic use can lead to hepatic fibrosis in a subset of patients [38].

Additionally, urea (r = 0.58, p ≤ 0.01) and creatinine (r = 0.57, p ≤ 0.01) were significantly correlated with DAS-28. These findings align with studies indicating that chronic inflammation, oxidative stress and prolonged use of NSAIDs and MTX contribute to renal dysfunction in RA patients [39]. The urea/creatinine ratio (r = 0.68, p = 0.01) also demonstrated a significant association, highlighting the potential for RA to accelerate kidney damage through inflammatory and vascular mechanisms [40] indicating that renal dysfunction worsens with increasing disease severity. 

Additionally, MTX and NSAIDs contribute to glomerular dysfunction and reduced renal clearance, explaining the significant elevation of urea and creatinine in high-DAS-28 patients [41].

Moreover, CRP is an inflammatory marker. Also, exhibited a strong correlation (r = 0.61, p ≤ 0.01), supporting the link between systemic inflammation and organ dysfunction in RA patients [42, 43]. Elevated CRP levels are indicative of persistent inflammation, which not only exacerbates joint destruction but also contributes to cardiovascular and hepatic complications [44]. Supporting the link between systemic inflammation and organ dysfunction in RA patients [45,46]. The strong correlation between CRP and DAS-28 further supports the role of chronic inflammation in multi-organ involvement in RA [47]. Systemic inflammation not only contributes to joint destruction but also predisposes patients to hepatic fibrosis, cardiovascular diseases and renal dysfunction [48].

ROC Analysis

The provided results represent the Area Under the Curve (AUC) values from a Receiver Operating Characteristic (ROC) analysis, which is a tool for evaluating the ability of various test variables to distinguish between positive and negative states. The AUC values reflect the discriminatory power of each test: an AUC of 1 indicates perfect discrimination and an AUC of 0.5 suggests no discrimination, equivalent to random chance.

ROC analysis is used to assess the diagnostic ability of various tests in distinguishing between positive and negative states. 

In this analysis, several test result variables were evaluated, including De-ritis Ratio, AST (U/L), ALT (U/L), C-reactive Protein (CRP) (mg/L) in one part of the study and Urea Level (mg/dl), Creatinine Level (mg/dl), Urea/Creatinine Ratio, C-reactive Protein (CRP) (mg/L) in another part. Below is a detailed discussion of the results as shown in Figure 1 and Table 4.

Table (3.): Correlation of DAS-28 with Biochemical Variables in RA patients

Table 4. ROC Curve Analysis of De-ritis Ratio, AST, ALT and C-reactive Protein as Diagnostic Biomarkers in Rheumatoid Arthritis

De-Ritis Ratio

The De-ritis Ratio showed a strong ability to differentiate between the positive and negative groups, with an Area Under the Curve (AUC) of 0.906, indicating excellent diagnostic performance. The p-value of 0.000 confirms statistical significance. The confidence interval (0.865 to 0.948) further supports the robustness of the result.

AST (U/L)

AST also demonstrated strong diagnostic ability, with an AUC of 0.889, indicating good discrimination between the groups. Similarly, the p-value of 0.000 supports the statistical significance and the confidence interval (0.844 to 0.934) confirms the reliability of this result.

ALT (U/L)

Compared to De-ritis Ratio and AST, ALT showed moderate diagnostic performance with an AUC of 0.719. Although the result was statistically significant (p-value = 0.000), its ability to distinguish between the groups is less than the other variables. The confidence interval (0.651 to 0.788) reflects this lower discriminatory power.

C-Reactive Protein (CRP) (mg/L)

CRP also demonstrated excellent ability to differentiate between states, with an AUC of 0.903 and a p-value of 0.000, indicating high significance. The confidence interval (0.858 to 0.948) further emphasizes CRP's strong discriminatory power.

Overall, most of the variables showed excellent diagnostic performance, making them strong indicators for distinguishing between positive and negative states.

Urea level (AUC = 0.829), the test demonstrates good discrimination ability, with a standard error of 0.027, indicating a high level of precision. The AUC is statistically significant (p ≤ 0.0001), suggesting that urea is a reliable marker for distinguishing between the two states, with a 95% confidence interval ranging from 0.776 to 0.881. 

Creatinine level (AUC = 0.515) shows poor discrimination, as the value is close to 0.5, implying it is nearly as effective as random chance. The standard error is 0.040 and the p-value of 0.694 indicates that the test does not significantly distinguish between the groups. The 95% confidence interval for creatinine (0.437 to 0.594) further confirms its limited ability.

Urea /creatinine ratio (AUC = 0.809) demonstrates good discriminatory power, though slightly lower than urea and CRP. With a standard error of 0.029 and a statistically significant p-value (p ≤ 0.0001), it shows strong potential as a marker, with a 95% confidence interval between 0.753 and 0.865.

Table. 5. ROC Curve Analysis of urea, Creatinine, Urea/Creatinine Ratio and C-reactive Protein as Diagnostic Biomarkers in Rheumatoid Arthritis

C-reactive protein (CRP) (AUC = 0.903) exhibits excellent discriminatory ability, the highest among the variables tested. The standard error is 0.023 and the test is highly statistically significant (p ≤ 0.0001). The 95% confidence interval (0.858 to 0.948) supports the reliability of CRP in distinguishing between the states. In brief, CRP provides the most reliable test for differentiating between the conditions, followed by urea level and the urea/creatinine ratio, while creatinine level offers limited discriminatory value.

The findings of this study demonstrate that the severity of rheumatoid arthritis (RA) significantly impacts liver and kidney function. Elevated levels of liver enzymes (AST, ALT), the De-Ritis ratio, as well as renal function markers (urea, creatinine), are strongly associated with disease severity. Notably, these biochemical alterations were more pronounced in severe RA cases, emphasizing the critical role of inflammation and methotrexate (MTX) therapy in contributing to hepatic and renal dysfunction. Furthermore, the positive correlations between disease activity (DAS-28 score) and biochemical markers of organ function further validate the systemic effects of chronic inflammation in RA. The high diagnostic potential of markers like De-Ritis ratio, CRP and urea levels, as indicated by their Area Under the Curve (AUC) values in ROC analysis, supports their utility in clinical settings for monitoring RA patients. 

Given the potential hepatotoxic and nephrotoxic effects of MTX, it is advised to regularly assess liver and kidney function to prevent long-term complications. Future research should focus on exploring alternative treatment options that reduce the adverse effects on liver and kidney functions while effectively controlling RA progression.

Conflict of Interest

The authors declare no conflict of interest.

Funding

No external funding was received for this study.

1. Hammodat, Zahraa, and Layla Mustafa. “Biochemical studies on synovial fluid and serum from rheumatoid arthritis patients.” Rafidain Journal of Science, vol. 27, no. 3, September 2018. Pp. 37-46. http://dx.doi.org/ 10.33899/ rjs.2018.159385

2. López-Armada, María José, et al. “Mitochondrial dysfunction and oxidative stress in rheumatoid arthritis.” Antioxidants, vol. 11, no. 6, June 2022. http://dx.doi.org/10.3390/antiox11061151.

3. Abass, Shuja, et al. “Systemic Autoimmune Disorders.” Role of Medicinal Plants in Autoimmune Diseases, edited by Reetika Mahajan, Faheem Shehjar, Sajad Majeed Zargar, Khalid Z. Masoodi, Zahoor A. Shah, UK & USA, Elsevier, 2025, pp. 85-116. http://dx.doi.org/10.1016/ b978-0-443-18776-6.00004-9.

4. Cao, Shan, et al. “L-arginine metabolism inhibits arthritis and inflammatory bone loss.” Annals of the Rheumatic Diseases, vol. 83, no. 1, January 2024. http://dx.doi.org /10.1136/ard-2022-223626.

5. Zamudio-Cuevas, Yessica, et al. “Rheumatoid arthritis and oxidative stress, a review of a decade.” Cellular and Molecular Biology, vol. 68, no. 6, June 2022, pp. 174-184. http://dx.doi.org/10.14715/cmb/2022.68.6.28.

6. Mueller, Anna Lena, et al. “Recent advances in understanding the pathogenesis of rheumatoid arthritis: New treatment strategies.” Cells, vol. 10, no. 11, November 2021, pp. 3017-0. http://dx.doi.org/10.3390/ cells10113017.

7. Hamodat, Zahraa Mohammed Ali Ahmed. “Adenosine deaminase activity a biomarker for rheumatoid arthritis: Review.” BASRA JOURNAL OF SCIENCE, vol. 38, no. 2, April 2020, pp. 271-293. http://dx.doi.org/ 10.29072/ basjs.202027.

8. Klareskog, L., et al. “The importance of differences; on environment and its interactions with genes and immunity in the causation of rheumatoid arthritis.” Journal of Internal Medicine, vol. 287, no. 5, April 2020, pp. 514-533. http://dx.doi.org/ 10.1111/ joim.13058.

9. Hamodat, Zahraa Mohammed Ali Ahmed. “Study of serum adenosine deaminase -2 (ada-2) activity in rheumatoid arthritis.” BASRA JOURNAL OF SCIENCE, vol. 39, no. 1, January 2021, pp. 119-134. http://dx.doi.org/ 10.29072/basjs.202118.

10. Hamodat, Zahraa Mohammed Ali Ahmed., et al. “Study of latent matrix metalloproteinase- 1 activity in serum and synovial fluid of patients with rheumatoid arthritis.” Rafidain Journal of Science, vol. 25, no. 1, February 2014, pp. 31-39. http://dx.doi.org/ 10.33899/rjs.2014.86062.

11. Brown, Philip, et al. “Therapeutic advances in rheumatoid arthritis.” BMJ, vol. 17, January 2024. http://dx.doi.org/ 10.1136/bmj-2022-070856.

12. Mukherjee, Anwesha, and Bodhisatwa Das. “The Role of Inflammatory Mediators and Matrix Metalloproteinases (MMPS) in The Progression of Osteoarthritis.” Biomaterials and Biosystems, vol. 13, no. 100090, March 2024. http://dx.doi.org/ 10.1016/j.bbiosy. 2024.100090.

13. Ma, Ke, et al. “Mechanism of Action of NRF2 and Its Related Natural Regulators in Rheumatoid Arthritis.” Journal of Orthopaedic Surgery and Research, vol. 19, no. 1, November 2024. http://dx.doi.org/10.1186/s13018-024-05221-w.

14. Ghahfarrokhi, Shahrzad Habibi, et al. “Efficacy and mechanisms of silybum marianum, silymarin, and silibinin on rheumatoid arthritis and osteoarthritis symptoms: A systematic review.” Current Rheumatology Reviews, vol. 20, no. 4, September 2024, pp. 414-425. http://dx.doi.org/10.2174/0115733971266397231122080247.

15. Bedoui, Yosra, et al. “Methotrexate an old drug with new tricks.” International Journal of Molecular Sciences, vol. 20, no. 20, October 2019, pp. 5023-0. http://dx.doi.org/10.3390/ijms20205023.

16. Salaffi, Fausto et al. “Rheumatoid arthritis disease activity assessment in routine care: Performance of the most widely used composite disease activity indices and patient-reported outcome measures.” Acta bio-medica: Atenei Parmensis, vol. 92, no. 4. Sep. 2021, http://dx.doi.org/10.23750/abm.v92i4.10831.

17. Portes, J.K.S., Funcionalidade avaliada pelo core set da Classificação Internacional de Funcionalidade e Saúde para artrite reumatóide: um estudo de coorte Master's thesis. http://hdl.handle.net/10183/246216.

18. Koźmiński, Przemysław, et al. “Overview of dual-acting drug methotrexate in different neurological diseases, autoimmune pathologies and cancers.” International Journal of Molecular Sciences, vol. 21, no. 10, May 2020, pp. 3483-0. http://dx.doi.org/10.3390/ijms21103483.

19. Hamodat, Zahraa Mohammed Ali Ahmed, et al. “Alpha-l-fucosidase as a putative prognostic biomarker in breast cancer.” The Ukrainian Biochemical Journal, vol. 96, no. 3, June 2024, pp. 57-65. http://dx.doi.org/10.15407 /ubj96.03.057.

20. Sami, Zereen Mustafa. “Evaluate the correlation serum afamin level with some biochemical parameters in the sera of patients with type 2 diabetes mellitus.” BASRA JOURNAL OF SCIENCE, vol. 41, no. 2, July 2023, pp. 370-391. http://dx.doi.org/10.29072/basjs.20230211.

21. Nair, Anugrah, et al. “|Assessment of disease activity in rheumatoid arthritis: A comparative study of clinical and laboratory evaluation with musculoskeletal ultrasonography assessment.” Journal of the Association of Physicians of India, vol. 70, no. 2, February 2022, pp. 11-12. https://pubmed.ncbi.nlm.nih.gov/35436826/.

22. Alramadhany, Ruaa Waleed, et al. “Study the level of arginase activity and its correlation with liver and kidney functions for patients with type-2 diabetes in Nineveh governorate.” Egyptian Journal of Chemistry, vol. 064, no. 12, June 2021, pp. 7075-7082. http://dx.doi.org/ 10.21608/ejchem.2021.80046.3942.

23. Adhvaryu, Meghna R, et al. “Prevention of hepatotoxicity due to anti tuberculosis treatment: A novel integrative approach.” World Journal of Gastroenterology, vol. 14, no. 30, 2008, pp. 4753-4762. http://dx.doi.org/10.3748/ wjg.14.4753.

24. Calarco, Serafina, et al. “Analytical performance of 17 commercially available point-of-care tests for crp to support patient management at lower levels of the health system.” PLoS One, vol. 18, no. 1, January 2023. http://dx.doi.org/10.1371/journal.pone.0267516.

25. Taha, et al. “The Effect of Disease Severity on the Liver and Kidney Functions for Patients with Osteoarthritis.” International Academic Research Journal of Clinical and Medical Biochemistry. vol. 4, no. 1, 2024, pp. 1-6. https://iarconsortium.org/ iarjcmb/ 149/546/ Volume%204-Issue%202-ra-2893/.

26. Padjen, Ivan, et al. “Conventional disease-modifying agents in rheumatoid arthritis – a review of their current use and role in treatment algorithms.” Rheumatology, vol. 58, no. 6, December 2020, pp. 390-400. http://dx.doi.org/10.5114/reum.2020.101400.

27. Guo, Hongtao, et al. “Inappropriate treatment response to DMARDs: A pathway to difficult-to-treat rheumatoid arthritis.” International Immunopharmacology, vol. 122, no. 1, September 2023. http://dx.doi.org/10.1016/ j.intimp.2023.110655.

28. Ezhilarasan, Devaraj. “Hepatotoxic potentials of methotrexate: Understanding the possible toxicological molecular mechanisms.” Toxicology, vol. 458, June 2021. http://dx.doi.org/10.1016/j.tox.2021.152840.

29. Olago-Rakuomi, Agatha A., Prevalence of abnormal liver function tests in rheumatoid arthritis. Master's thesis. https://erepository.uonbi.ac.ke/handle/11295/101717.

30. Kandahari, Adrese M, et al. “A review of UHMWPE wear-induced osteolysis: The role for early detection of the immune response.” Bone Research, vol. 4, no. 1, July 2016. http://dx.doi.org/10.1038/boneres.2016.14.

31. Yzeiri Havziu, Drita, et al. “Nephrotoxicity of NSAIDs and MTX.” ACTA MEDICA BALKANICA vol. 3, no. 5, 2018, pp. 13-18. https://eprints.unite.edu.mk/62/.

32. Levitt, David, and Michael Levitt. “Human serum albumin homeostasis: A new look at the roles of synthesis, catabolism, renal and gastrointestinal excretion, and the clinical value of serum albumin measurements.” International Journal of General Medicine, vol. Volume 9, July 2016, pp. 229-255. http://dx.doi.org/ 10.2147/ijgm.s102819.

33. Barnett, Lillie M A, and Brian S Cummings. “Nephrotoxicity and renal pathophysiology: A contemporary perspective.” Toxicological Sciences, vol. 164, no. 2, June 2018, pp. 379-390. http://dx.doi.org/ 10.1093/toxsci/kfy159.

34. Janssen, Lando, et al. “Muscle toxicity of drugs: When drugs turn physiology into pathophysiology.” Physiological Reviews, vol. 100, no. 2, April 2020, pp. 633-672. http://dx.doi.org/ 10.1152/physrev.00002.2019.

35. Sahin, Didem, et al. “Biomarkers in the diagnosis, prognosis and management of rheumatoid arthritis: A comprehensive review.” Annals of Clinical Biochemistry: International Journal of Laboratory Medicine, vol. 62, no. 1, October 2024, pp. 3-21. http://dx.doi.org/ 10.1177/00045632241285843.

36. Rosa, I Arias de la, et al. “Clinical features and immune mechanisms directly linked to the altered liver function in patients with rheumatoid arthritis.” European Journal of Internal Medicine, vol. 118, December 2023. http://dx.doi.org/10.1016/j.ejim.2023.08.002.

37. Giletti, Andrea, et al. “Methotrexate pharmacogenetics in uruguayan adults with hematological malignant diseases.” European Journal of Pharmaceutical Sciences, vol. 109, November 2017. http://dx.doi.org/ 10.1016/j.ejps.2017.09.006.

38. Hoque, Mohammad Razuanul, et al. “Status of renal and liver function in rheumatoid arthritis (RA) patients of Chattogram, Bangladesh treated with methotrexate (MTX).” Journal of Biosciences and Medicines, vol. 11, no. 09, 2023, pp. 114-126. http://dx.doi.org/ 10.4236/ jbm.2023.119010.

39. T, Sheela Rani, et al. “Anti-inflammatory and anti-arthritic activities of ethanolic extract of myxopyrum serratulum a.w. hill.” Laboratory Animal Research, vol. 40, no. 1, September 2024. http://dx.doi.org/10.1186/ s42826-024-00220-8.

40. Manan, Maria, et al. “Antiarthritic potential of comprehensively standardized extract of Alternanthera bettzickiana: In vitro and In vivo studies.” ACS Omega, vol. 5, no. 31, July 2020, pp. 19478-19496. http://dx.doi.org/10.1021/acsomega.0c01670.

41. Zayat, Ahmed S., et al. “Middle East Immunology Summit of the Gulf Cooperation Council Association of Immunology and Rheumatology (GCC AIR), 2023 Dubai, United Arab Emirate. Scientific abstracts and case reports.” Saudi Medical Journal vol. 45, no. 9, 2024, pp. 968-999. https://pubmed.ncbi.nlm.nih.gov/39218464/.

42. Sebastiani, Marco, et al. “Italian consensus recommendations for the management of hepatitis C infection in patients with rheumatoid arthritis.” Modern Rheumatology, vol. 29, no. 6, January 2019, pp. 895-902. http://dx.doi.org/10.1080/14397595.2018.1558918.

43. Sebastiani, Marco, et al. “Italian consensus guidelines for the management of hepatitis B virus infections in patients with rheumatoid arthritis.” Joint Bone Spine, vol. 84, no. 5, October 2017, pp. 525-530. http://dx.doi.org/10.1016/j.jbspin.2017.05.013.

44. Jennifer Ann Moran Investigation of serum monomeric C-reactive protein and associated auto-antibodies in rheumatoid arthritis. https://keele-repository. worktribe. com/output/413132.

45. Natalucci, Francesco. Synovial macrophages in patients with reumatoid arthritis: Predictors of response and their modifications to treatment. https://hdl.handle.net/ 11573/1733389.

46. Chepchirchir, Angeline. Inflammatory Cytokine Profiles in HIV/AIDS Patients with Hypertension Comorbidity at Kenyatta National Hospital Comprehensive Care Center. http://erepository.uonbi.ac.ke/handle/11295/109316.

47. Jiang, Yong, et al. “Biomarkers (MRNAS and non-coding RNAS) for the diagnosis and prognosis of rheumatoid arthritis.” Frontiers in Immunology, vol. 14, February 2023. http://dx.doi.org/10.3389/fimmu.2023.1087925.

48. Figus, Fabiana Assunta, et al. “Rheumatoid arthritis: Extra-articular manifestations and comorbidities.” Autoimmunity Reviews, vol. 20, no. 4, April 2021. http://dx.doi.org/ 10.1016/j.autrev. 2021. 102776.