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Journals / Black Sea Journal of Engineering and Science / 2026 / Cilt: 9 Sayı: 5

Mitochondrial Dysfunction across Synovial and Peripheral Compartments in Rheumatoid Arthritis: A Multi-tissue Transcriptomic Integration of PBMC, Synovial Biopsy and Whole Blood

Sevinç Akçay(KIRŞEHİR AHİ EVRAN ÜNİVERSİTESİ)0000-0003-2961-3970
Pages
2175–2187
Publication Date
2026-09-15
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

These findings provide a multi-tissue resource for targeting mitochondrial pathways in RA.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Rheumatoid arthritis (RA) is a chronic autoimmune disease with synovial inflammation and systemic immune alterations.
📊
Key Findings & Data:We performed an integrative transcriptomic analysis of three public datasets: GSE17755 (PBMC), GSE89408 (synovial biopsy), and GSE93272 (whole blood).
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Conclusion & Impact:These findings provide a multi-tissue resource for targeting mitochondrial pathways in RA.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Rheumatoid arthritis · Mitochondrial dysfunction · Transcriptomics

Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disease with synovial inflammation and systemic immune alterations. Mitochondrial dysfunction has been implicated in RA pathogenesis, but its tissue-specific and shared molecular signatures remain poorly characterized. We performed an integrative transcriptomic analysis of three public datasets: GSE17755 (PBMC), GSE89408 (synovial biopsy), and GSE93272 (whole blood). Differentially expressed genes (DEGs) were identified (P<0.05, |log2FC| ≥ 1) and intersected with MitoCarta 3.0 to obtain mitochondria-related DEGs (mito-DEGs). Protein-protein interaction networks, hub genes (identified using the MCC algorithm), functional enrichment (GO/KEGG), and regulatory networks (miRNA-TF-mRNA) were constructed. PBMC, synovial biopsy, and whole blood yielded 37, 220, and 119 mito-DEGs, respectively. Only one gene (AKAP1) was common across all three tissues. Hub genes predominantly encoded subunits of mitochondrial respiratory chain complexes (NDUF family and UQCR genes). Enriched pathways included oxidative phosphorylation, thermogenesis, and neurodegeneration-related pathways. Regulatory analysis identified FOXC1, GATA2, and hsa-miR-16-5p as key transcriptional and post-transcriptional regulators. Mitochondrial dysfunction in RA is tissue-specific, but converges on the dysregulation of oxidative phosphorylation. AKAP1 emerges as a potential systemic mitochondrial biomarker, pending validation in independent cohorts. These findings provide a multi-tissue resource for targeting mitochondrial pathways in RA.

Özet

Rheumatoid arthritis (RA) is a chronic autoimmune disease with synovial inflammation and systemic immune alterations. Mitochondrial dysfunction has been implicated in RA pathogenesis, but its tissue-specific and shared molecular signatures remain poorly characterized. We performed an integrative transcriptomic analysis of three public datasets: GSE17755 (PBMC), GSE89408 (synovial biopsy), and GSE93272 (whole blood). Differentially expressed genes (DEGs) were identified (P<0.05, |log2FC| ≥ 1) and intersected with MitoCarta 3.0 to obtain mitochondria-related DEGs (mito-DEGs). Protein-protein interaction networks, hub genes (identified using the MCC algorithm), functional enrichment (GO/KEGG), and regulatory networks (miRNA-TF-mRNA) were constructed. PBMC, synovial biopsy, and whole blood yielded 37, 220, and 119 mito-DEGs, respectively. Only one gene (AKAP1) was common across all three tissues. Hub genes predominantly encoded subunits of mitochondrial respiratory chain complexes (NDUF family and UQCR genes). Enriched pathways included oxidative phosphorylation, thermogenesis, and neurodegeneration-related pathways. Regulatory analysis identified FOXC1, GATA2, and hsa-miR-16-5p as key transcriptional and post-transcriptional regulators. Mitochondrial dysfunction in RA is tissue-specific, but converges on the dysregulation of oxidative phosphorylation. AKAP1 emerges as a potential systemic mitochondrial biomarker, pending validation in independent cohorts. These findings provide a multi-tissue resource for targeting mitochondrial pathways in RA.

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Cite This Article

Akçay, S. (2026). Mitochondrial Dysfunction across Synovial and Peripheral Compartments in Rheumatoid Arthritis: A Multi-tissue Transcriptomic Integration of PBMC, Synovial Biopsy and Whole Blood. Black Sea Journal of Engineering and Science, Cilt: 9 Sayı: 5, 2175–2187. https://doi.org/10.34248/bsengineering.1964431

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References (43)

  1. Abbasifard, A., Solgi, G., Khodadadi, I., Doosti-Irani, A., Tayebinia, H., & Fazaeli, A. (2024). Peripheral blood mononuclear cells show markers of mitochondrial dysfunction in rheumatoid arthritis. Cell Biochemistry and Function, 42(4), e4025. https://doi.org/10.1002/cbf.4025
  2. Alivernini, S., Firestein, G. S., & McInnes, I. B. (2022). The pathogenesis of rheumatoid arthritis. Immunity, 55(12), 2255–2270. https://doi.org/10.1016/j.immuni.2022.11.009
  3. Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., Harris, M. A., Hill, D. P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J. C., Richardson, J. E., Ringwald, M., Rubin, G. M., & Sherlock, G. (2000). Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nature Genetics, 25(1), 25–29. https://doi.org/10.1038/75556
  4. Bellocchi, C., Favalli, E. G., Maioli, G., Agape, E., Rossato, M., Paini, M., Severino, A., Vigone, B., Biggioggero, M., Trombetta, E., Caporali, R., & Beretta, L. (2025). Whole-blood RNA sequencing profiling of patients with rheumatoid arthritis treated with tofacitinib. ACR Open Rheumatology, 7(7), e11761. https://doi.org/10.1002/acr2.11761
  5. Berry, F. B., Skarie, J. M., Mirzayans, F., Fortin, Y., Hudson, T. J., Raymond, V., Link, B. A., & Walter, M. A. (2008). FOXC1 is required for cell viability and resistance to oxidative stress in the eye through the transcriptional regulation of FOXO1A. Human Molecular Genetics, 17(4), 490–505. https://doi.org/10.1093/hmg/ddm326
  6. Binvignat, M., Miao, B. Y., Wibrand, C., Yang, M. M., Rychkov, D., Flynn, E., Nititham, J., Tamaki, W., Khan, U., Carvidi, A., Krueger, M., Niemi, E., Sun, Y., Fragiadakis, G. K., Sellam, J., Mariotti-Ferrandiz, E., Klatzmann, D., Gross, A. J., Ye, C. J., Butte, A. J., … Sirota, M. (2024). Single-cell RNA-Seq analysis reveals cell subsets and gene signatures associated with rheumatoid arthritis disease activity. JCI Insight, 9(16), e178499. https://doi.org/10.1172/jci.insight.178499
  7. Bozdemir, N., Cakir, C., Topcu, U., & Uysal, F. (2025). A Comprehensive Review of Mitochondrial Complex I During Mammalian Oocyte Maturation. Genesis (New York, N.Y.: 2000), 63(3), e70017. https://doi.org/10.1002/dvg.70017
  8. Chin, C. H., Chen, S. H., Wu, H. H., Ho, C. W., Ko, M. T., & Lin, C. Y. (2014). cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Systems Biology, 8 Suppl 4(Suppl 4), S11. https://doi.org/10.1186/1752-0509-8-S4-S11
  9. Fearon, U., Canavan, M., Biniecka, M., & Veale, D. J. (2016). Hypoxia, mitochondrial dysfunction and synovial invasiveness in rheumatoid arthritis. Nature Reviews. Rheumatology, 12(7), 385–397. https://doi.org/10.1038/nrrheum.2016.69
  10. Finckh, A., Gilbert, B., Hodkinson, B., Bae, S. C., Thomas, R., Deane, K. D., Alpizar-Rodriguez, D., & Lauper, K. (2022). Global epidemiology of rheumatoid arthritis. Nature reviews. Rheumatology, 18(10), 591–602. https://doi.org/10.1038/s41584-022-00827-y
  11. Gao, C., Zhang, C., Wen, L., Zhang, G., Liu, X., Wang, J., Cui, L., Li, R., Nie, T., Duan, J., & Guo, Y. (2025). Regulation of reactive oxygen species and the role of mitochondrial apoptotic-related genes in rheumatoid arthritis. Scientific Reports, 15(1), 2165. https://doi.org/10.1038/s41598-025-85460-x
  12. Gao, Y., Zhang, Y., & Liu, X. (2024). Rheumatoid arthritis: pathogenesis and therapeutic advances. MedComm, 5(3), e509. https://doi.org/10.1002/mco2.509
  13. Gökhan, A., Kılıç, K. D., Gülle, K., Uyanıkgil, Y., & Çavuşoğlu, T. (2020). Apoptotik Yolaklar ve Hedefe Yönelik Tedaviler. Medical Journal of Süleyman Demirel University, 27(4), 565-573. https://doi.org/10.17343/sdutfd.619417
  14. Hou, Y., Yang, X., Zhao, T., Guo, Y., & Shi, J. (2025). Targeting mitochondrial oxidative stress: A novel therapeutic strategy for degenerative joint diseases (Review). Biomedical Reports, 24(2),26. https://doi.org/10.3892/br.2025.2099
  15. Huang, H. Y., Lin, Y. C., Li, J., Huang, K. Y., Shrestha, S., Hong, H. C., Tang, Y., Chen, Y. G., Jin, C. N., Yu, Y., Xu, J. T., Li, Y. M., Cai, X. X., Zhou, Z. Y., Chen, X. H., Pei, Y. Y., Hu, L., Su, J. J., Cui, S. D., Wang, F., … Huang, H. D. (2020). miRTarBase 2020: updates to the experimentally validated microRNA-target interaction database. Nucleic Acids Research, 48(D1), D148–D154. https://doi.org/10.1093/nar/gkz896
  16. Huang, Q., Cai, X. Q., Li, Z. Q., Liu, Y., & Pan, H. F. (2026). Association of peripheral blood mitochondrial DNA gene variation and methylation levels with rheumatoid arthritis. Clinical Immunology(Orlando, Fla.), 282, 110641. https://doi.org/10.1016/j.clim.2025.110641
  17. Jackson-Strong, M., Ganguly, S., Francis, A., Rago, F., Kanshana, J., Michalides, B. A., Teng, L., Betsur, O. S., Kruszelnicki, S., Shoger, K. E., Kim, A., Bajpai, K., Suleyman, A., Sekyere, A., Hara, M., Sriram, V., Kumar, A., Delgoffe, G. M., Natarajan, N., Alcorn, J. F., … Gottschalk, R. A. (2026). GATA2 controls alveolar macrophage inflammatory gene expression and metabolic function. JCI Insight, 11(7), e196246. https://doi.org/10.1172/jci.insight.196246
  18. Jaramillo Ramos, J. J., Galindo Pupo, N. M., Mena, D., Solis, R. P., Bedoya Jaramillo, J. E., & Vega Solano, M. (2025). Cognitive Decline in Chronic Inflammatory Conditions: Exploring Links Between Systemic Inflammation and Neurodegeneration. Cureus, 17(7), e88397. https://doi.org/10.7759/cureus.88397
  19. Kanehisa, M., Furumichi, M., Sato, Y., Kawashima, M., & Ishiguro-Watanabe, M. (2023). KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Research, 51(D1), D587–D592. https://doi.org/10.1093/nar/gkac963
  20. Lee, E. J., Lilja, S., Li, X., Schäfer, S., Zhang, H., & Benson, M. (2020). Bulk and single cell transcriptomic data indicate that a dichotomy between inflammatory pathways in peripheral blood and arthritic joints complicates biomarker discovery. Cytokine, 127, 154960. https://doi.org/10.1016/j.cyto.2019.154960.
  21. Li, Y., Cai, M., Qin, Y., Dai, X., Liang, L., Li, Z., Wen, X., Jin, H., Yang, C., & Chen, Z. (2025). MTHFD2 promotes osteoclastogenesis and bone loss in rheumatoid arthritis by enhancing CKMT1-mediated oxidative phosphorylation. BMC Medicine, 23(1), 124. https://doi.org/10.1186/s12916-025-03945-y
  22. Liu, Y., Merrill, R. A., & Strack, S. (2020). A-Kinase Anchoring Protein 1: Emerging Roles in Regulating Mitochondrial Form and Function in Health and Disease. Cells, 9(2), 298. https://doi.org/10.3390/cells9020298
  23. Ma, C., Wang, J., Hong, F., & Yang, S. (2022). Mitochondrial Dysfunction in Rheumatoid Arthritis. Biomolecules, 12(9), 1216. https://doi.org/10.3390/biom12091216
  24. Mihaylova, V., Kazakova, M., Batalov, Z., Karalilova, R., Batalov, A., & Sarafian, V. (2024). JAK inhibitors improve ATP production and mitochondrial function in rheumatoid arthritis: a pilot study. Rheumatology International, 44(1), 57–65. https://doi.org/10.1007/s00296-023-05501-4
  25. Mitrović, J., Hrkač, S., Tečer, J., Golob, M., Ljilja Posavec, A., Kolar Mitrović, H., & Grgurević, L. (2023). Pathogenesis of Extraarticular Manifestations in Rheumatoid Arthritis-A Comprehensive Review. Biomedicines, 11(5), 1262. https://doi.org/10.3390/biomedicines11051262
  26. Nesci, S., & Rubattu, S. (2024). UCP2, a Member of the Mitochondrial Uncoupling Proteins: An Overview from Physiological to Pathological Roles. Biomedicines, 12(6), 1307. https://doi.org/10.3390/biomedicines12061307
  27. Ovek Baydar, D., Rauluseviciute, I., Aronsen, D. R., Blanc-Mathieu, R., Bonthuis, I., de Beukelaer, H., Ferenc, K., Jegou, A., Kumar, V., Lemma, R. B., Lucas, J., Pochon, M., Yun, C. M., Ramalingam, V., Deshpande, S. S., Patel, A., Marinov, G. K., Wang, A. T., Aguirre, A., Castro-Mondragon, J. A., … Mathelier, A. (2026). JASPAR 2026: expansion of transcription factor binding profiles and integration of deep learning models. Nucleic Acids Research, 54(D1), D184–D193. https://doi.org/10.1093/nar/gkaf1209
  28. Rahmati, M., Kwesiga, M. P., Lou, J., Tan, A. L., & McDermott, M. F. (2024). Novel Targeted Therapies for Rheumatoid Arthritis Based on Intracellular Signalling and Immunometabolic Changes: A Narrative Review. Frontiers in Bioscience(Landmark Edition), 29(1), 42. https://doi.org/10.31083/j.fbl2901042
  29. Rath, S., Sharma, R., Gupta, R., Ast, T., Chan, C., Durham, T. J., Goodman, R. P., Grabarek, Z., Haas, M. E., Hung, W. H. W., Joshi, P. R., Jourdain, A. A., Kim, S. H., Kotrys, A. V., Lam, S. S., McCoy, J. G., Meisel, J. D., Miranda, M., Panda, A., Patgiri, A., … Mootha, V. K. (2021). MitoCarta3.0: an updated mitochondrial proteome now with sub-organelle localization and pathway annotations. Nucleic Acids Research, 49(D1), D1541–D1547. https://doi.org/10.1093/nar/gkaa1011
  30. Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003). Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Research, 13(11), 2498–2504. https://doi.org/10.1101/gr.1239303
  31. Sherman, B. T., Hao, M., Qiu, J., Jiao, X., Baseler, M. W., Lane, H. C., Imamichi, T., & Chang, W. (2022). DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Research, 50(W1), W216–W221. https://doi.org/10.1093/nar/gkac194
  32. Smiljanovic, B., Grützkau, A., Sörensen, T., Grün, J. R., Vogl, T., Bonin, M., Schendel, P., Stuhlmüller, B., Claussnitzer, A., Hermann, S., Ohrndorf, S., Aupperle, K., Backhaus, M., Radbruch, A., Burmester, G. R., & Häupl, T. (2020). Synovial tissue transcriptomes of long-standing rheumatoid arthritis are dominated by activated macrophages that reflect microbial stimulation. Scientific Reports, 10(1), 7907. https://doi.org/10.1038/s41598-020-64431-4
  33. Smolen, J. S., Aletaha, D., & McInnes, I. B. (2016). Rheumatoid arthritis. Lancet(London, England), 388(10055), 2023–2038. https://doi.org/10.1016/S0140-6736(16)30173-8
  34. Smolen, J. S., Aletaha, D., Barton, A., Burmester, G. R., Emery, P., Firestein, G. S., Kavanaugh, A., McInnes, I. B., Solomon, D. H., Strand, V., & Yamamoto, K. (2018). Rheumatoid arthritis. Nature Reviews. Disease Primers, 4, 18001. https://doi.org/10.1038/nrdp.2018.1
  35. Soundararajan, R., Hernández-Cuervo, H., Stearns, T. M., Griswold, A. J., Patil, S. S., Fukumoto, J., Narala, V. R., Galam, L., Lockey, R., & Kolliputi, N. (2022). A-Kinase Anchor Protein 1 deficiency causes mitochondrial dysfunction in mouse model of hyperoxia induced acute lung injury. Frontiers in Pharmacology, 13, 980723. https://doi.org/10.3389/fphar.2022.980723
  36. Szklarczyk, D., Kirsch, R., Koutrouli, M., Nastou, K., Mehryary, F., Hachilif, R., Gable, A. L., Fang, T., Doncheva, N. T., Pyysalo, S., Bork, P., Jensen, L. J., & von Mering, C. (2023). The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Research, 51(D1), D638–D646. https://doi.org/10.1093/nar/gkac1000
  37. Tariq, M. H., Advani, D., Almansoori, B. M., AlSamahi, M. E., Aldhaheri, M. F., Alkaabi, S. E., Mousa, M., & Kohli, N. (2025). The Identification of Novel Therapeutic Biomarkers in Rheumatoid Arthritis: A Combined Bioinformatics and Integrated Multi-Omics Approach. International Journal of Molecular Sciences, 26(6), 2757. https://doi.org/10.3390/ijms26062757
  38. Uke, P., Maharaj, A., & Adebajo, A. (2025). A review on the epidemiology of rheumatoid arthritis: An update and trends from current literature. Best Practice & Research. Clinical Rheumatology, 39(1), 102036. https://doi.org/10.1016/j.berh.2025.102036
  39. West, A. P., & Shadel, G. S. (2017). Mitochondrial DNA in innate immune responses and inflammatory pathology. Nature Reviews. Immunology, 17(6), 363–375. https://doi.org/10.1038/nri.2017.21
  40. Weyand, C. M., & Goronzy, J. J. (2017). Immunometabolism in early and late stages of rheumatoid arthritis. Nature Reviews. Rheumatology, 13(5), 291–301. https://doi.org/10.1038/nrrheum.2017.49
  41. Xia, J., Gill, E. E., & Hancock, R. E. (2015). NetworkAnalyst for statistical, visual and network-based meta-analysis of gene expression data. Nature Protocols, 10(6), 823–844. https://doi.org/10.1038/nprot.2015.052
  42. Zhou, G., Soufan, O., Ewald, J., Hancock, R. E. W., Basu, N., & Xia, J. (2019). NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis. Nucleic Acids Research, 47(W1), W234–W241. https://doi.org/10.1093/nar/gkz240
  43. Bozdemir, N., Cakir, C., Topcu, U., & Uysal, F. (2025). A Comprehensive Review of Mitochondrial Complex I During Mammalian Oocyte Maturation. Genesis (New York, N.Y.: 2000), 63(3), e70017. https://doi.org/10.1002/dvg.70017