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image of CD4+ Effector Memory T Cells Related Marker Gene Signatures in Osteoporosis and Aging: Insight From Single-Cell Analysis and Mendelian Randomization

Abstract

Objective

With the accelerated aging of the population, aging has emerged as a major risk factor for osteoporosis (OP). This study aims to investigate the relationship and shared molecular mechanisms between OP and aging through various genetic approaches.

Methods

Single-cell data from the peripheral blood of osteoporosis patients, aging individuals, and healthy controls were integrated to analyze characteristic changes in cell subpopulations. Differentially expressed genes (DEGs) were then identified within core subpopulations, and Mendelian randomization (MR) analysis was employed to explore potential causal links between key genes and OP. Additionally, an OP model was established in rats, and mRNA levels of key genes were measured using RT-qPCR.

Results

Through the integration, filtering, and analysis of scRNA-seq data, an increased proportion of CD4+ effector memory T (CD4+ T) cells were identified in OP and aging samples, marking them as a core subpopulation. Differential expression analysis identified 49 DEGs, and further analysis through Mendelian Randomization (MR) identified three key genes (KLRB1, NR4A2, and S100A4) significantly associated with OP. Notably, the upregulation of KLRB1 and S100A4 may enhance the interactions within T cells and with other cell subgroups. At the same time, the downregulation of NR4A2 could impede communication between T cells and other cell subpopulations. The RT-qPCR results indicated that NR4A2 was significantly downregulated in the OP group.

Conclusion

This study conducted a comprehensive analysis of the potential link between OP and aging, identifying CD4+ T cells as the core cell subgroup in OP and aging samples. It further revealed the causal relationship between KLRB1, NR4A2, and S100A4 and the occurrence of OP. The upregulation of KLRB1 and S100A4 may contribute to OP pathogenesis by promoting interactions between CD4+ TEM cells and other cell subgroups, providing new insights for molecular targeting and immunotherapy of OP.

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2025-02-04
2025-04-01
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References

  1. Foessl I. Dimai H.P. Obermayer-Pietsch B. Long-term and sequential treatment for osteoporosis. Nat. Rev. Endocrinol. 2023 19 9 520 533 10.1038/s41574‑023‑00866‑9 37464088
    [Google Scholar]
  2. Adejuyigbe B. Kallini J. Chiou D. Kallini J.R. Osteoporosis: Molecular pathology, diagnostics, and therapeutics. Int. J. Mol. Sci. 2023 24 19 14583 10.3390/ijms241914583 37834025
    [Google Scholar]
  3. Gao Y. Patil S. Jia J. The development of molecular biology of osteoporosis. Int. J. Mol. Sci. 2021 22 15 8182 10.3390/ijms22158182 34360948
    [Google Scholar]
  4. Anam A.K. Insogna K. Update on osteoporosis screening and management. Med. Clin. North Am. 2021 105 6 1117 1134 10.1016/j.mcna.2021.05.016 34688418
    [Google Scholar]
  5. Blake G.M. Fogelman I. The role of DXA bone density scans in the diagnosis and treatment of osteoporosis. Postgrad. Med. J. 2007 83 982 509 517 10.1136/pgmj.2007.057505 17675543
    [Google Scholar]
  6. Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. Report of a WHO Study Group. World Health Organ. Tech. Rep. Ser. 1994 843 1 129 7941614
    [Google Scholar]
  7. Vásquez E. Alam M.T. Murillo R. Race and ethnic differences in physical activity, osteopenia, and osteoporosis: results from NHANES 2009-2010, 2013-2014, 2017-2018. Arch. Osteoporos. 2023 19 1 7 10.1007/s11657‑023‑01356‑1 38150070
    [Google Scholar]
  8. Youssef E.F. Shanb A.A. The impact of adding weight-bearing exercise versus nonweight bearing programs to the medical treatment of elderly patients with osteoporosis. J. Family Community Med. 2014 21 3 176 181 10.4103/2230‑8229.142972 25374469
    [Google Scholar]
  9. de Labra C. Guimaraes-Pinheiro C. Maseda A. Lorenzo T. Millán-Calenti J.C. Effects of physical exercise interventions in frail older adults: A systematic review of randomized controlled trials. BMC Geriatr. 2015 15 1 154 10.1186/s12877‑015‑0155‑4 26626157
    [Google Scholar]
  10. Ramchand S.K. Leder B.Z. Sequential therapy for the long-term treatment of postmenopausal osteoporosis. J. Clin. Endocrinol. Metab. 2024 109 2 303 311 10.1210/clinem/dgad496 37610985
    [Google Scholar]
  11. Mondo I. Hannou S. D’Amelio P. Using sequential pharmacotherapy for the treatment of osteoporosis: an update of the literature. Expert Opin. Pharmacother. 2023 24 18 2175 2186 10.1080/14656566.2023.2296543 38100542
    [Google Scholar]
  12. Rosen R.S. Yarmush M.L. Current trends in anti-aging strategies. Annu. Rev. Biomed. Eng. 2023 25 1 363 385 10.1146/annurev‑bioeng‑120122‑123054 37289554
    [Google Scholar]
  13. Khandelwal S. Lane N.E. Osteoporosis. Endocrinol. Metab. Clin. North Am. 2023 52 2 259 275 10.1016/j.ecl.2022.10.009 36948779
    [Google Scholar]
  14. Li Y. Hu M. Xie J. Li S. Dai L. Dysregulation of histone modifications in bone marrow mesenchymal stem cells during skeletal ageing: roles and therapeutic prospects. Stem Cell Res. Ther. 2023 14 1 166 10.1186/s13287‑023‑03393‑6 37357311
    [Google Scholar]
  15. Xu J. Cai X. Miao Z. Yan Y. Chen D. Yang Z. Yue L. Hu W. Zhuo L. Wang J. Xue Z. Fu Y. Xu Y. Zheng J.S. Guo T. Chen Y. Proteome‐wide profiling reveals dysregulated molecular features and accelerated aging in osteoporosis: A 9.8‐year prospective study. Aging Cell 2024 23 2 e14035 10.1111/acel.14035 37970652
    [Google Scholar]
  16. Enko D. Michaelis S. Schneider C. Schaflinger E. Baranyi A. Schnedl W. Muller D. The use of next-generation sequencing in pharmacogenomics. Clin. Lab. 2023 69 08/2023 10.7754/Clin.Lab.2023.230103 37560847
    [Google Scholar]
  17. Moqri M. Herzog C. Poganik J.R. Justice J. Belsky D.W. Higgins-Chen A. Moskalev A. Fuellen G. Cohen A.A. Bautmans I. Widschwendter M. Ding J. Fleming A. Mannick J. Han J.D.J. Zhavoronkov A. Barzilai N. Kaeberlein M. Cummings S. Kennedy B.K. Ferrucci L. Horvath S. Verdin E. Maier A.B. Snyder M.P. Sebastiano V. Gladyshev V.N. Biomarkers of aging for the identification and evaluation of longevity interventions. Cell 2023 186 18 3758 3775 10.1016/j.cell.2023.08.003 37657418
    [Google Scholar]
  18. Zhang H. Pros and cons of Mendelian randomization. Fertil. Steril. 2023 119 6 913 916 10.1016/j.fertnstert.2023.03.029 36990264
    [Google Scholar]
  19. Yip S.H. Sham P.C. Wang J. Evaluation of tools for highly variable gene discovery from single-cell RNA-seq data. Brief. Bioinform. 2019 20 4 1583 1589 10.1093/bib/bby011 29481632
    [Google Scholar]
  20. Korsunsky I. Millard N. Fan J. Slowikowski K. Zhang F. Wei K. Baglaenko Y. Brenner M. Loh P. Raychaudhuri S. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods 2019 16 12 1289 1296 10.1038/s41592‑019‑0619‑0 31740819
    [Google Scholar]
  21. Aran D. Looney A.P. Liu L. Wu E. Fong V. Hsu A. Chak S. Naikawadi R.P. Wolters P.J. Abate A.R. Butte A.J. Bhattacharya M. Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage. Nat. Immunol. 2019 20 2 163 172 10.1038/s41590‑018‑0276‑y 30643263
    [Google Scholar]
  22. Jin S. Guerrero-Juarez C.F. Zhang L. Chang I. Ramos R. Kuan C.H. Myung P. Plikus M.V. Nie Q. Inference and analysis of cell-cell communication using CellChat. Nat. Commun. 2021 12 1 1088 10.1038/s41467‑021‑21246‑9 33597522
    [Google Scholar]
  23. Rasooly D. Peloso G.M. Giambartolomei C. Bayesian genetic colocalization test of two traits using coloc. Curr. Protoc. 2022 2 12 e627 10.1002/cpz1.627 36515558
    [Google Scholar]
  24. Liu B. Gloudemans M.J. Rao A.S. Ingelsson E. Montgomery S.B. Abundant associations with gene expression complicate GWAS follow-up. Nat. Genet. 2019 51 5 768 769 10.1038/s41588‑019‑0404‑0 31043754
    [Google Scholar]
  25. Morris J.A. Gayther S.A. Jacobs I.J. Jones C. A suite of Perl modules for handling microarray data. Bioinformatics 2008 24 8 1102 1103 10.1093/bioinformatics/btn085 18353790
    [Google Scholar]
  26. Xu J. Su W. Chen J. Ye Z. Wu C. Jiang J. Yan X. Cai J. Zhao J. The effect of antiosteoporosis therapy with risedronate on rotator cuff healing in an osteoporotic rat model. Am. J. Sports Med. 2021 49 8 2074 2084 10.1177/03635465211011748 33998839
    [Google Scholar]
  27. Zhan W. Deng M. Huang X. Xie D. Gao X. Chen J. Shi Z. Lu J. Lin H. Li P. Pueraria lobata-derived exosome-like nanovesicles alleviate osteoporosis by enhacning autophagy. J. Control. Release 2023 364 644 653 10.1016/j.jconrel.2023.11.020 37967723
    [Google Scholar]
  28. Liu X. Wan M. A tale of the good and bad: Cell senescence in bone homeostasis and disease. Int. Rev. Cell Mol. Biol. 2019 346 97 128 10.1016/bs.ircmb.2019.03.005 31122396
    [Google Scholar]
  29. Huo S. Tang X. Chen W. Gan D. Guo H. Yao Q. Liao R. Huang T. Wu J. Yang J. Xiao G. Han X. Epigenetic regulations of cellular senescence in osteoporosis. Ageing Res. Rev. 2024 99 102235 10.1016/j.arr.2024.102235 38367814
    [Google Scholar]
  30. Fang C.L. Liu B. Wan M. “Bone-SASP” in skeletal aging. Calcif. Tissue Int. 2023 113 1 68 82 10.1007/s00223‑023‑01100‑4 37256358
    [Google Scholar]
  31. Khosla S. Farr J.N. Monroe D.G. Cellular senescence and the skeleton: pathophysiology and therapeutic implications. J. Clin. Invest. 2022 132 3 e154888 10.1172/JCI154888 35104801
    [Google Scholar]
  32. Tyagi A.M. Srivastava K. Kureel J. Kumar A. Raghuvanshi A. Yadav D. Maurya R. Goel A. Singh D. Premature T cell senescence in Ovx mice is inhibited by repletion of estrogen and medicarpin: a possible mechanism for alleviating bone loss. Osteoporos. Int. 2012 23 3 1151 1161 10.1007/s00198‑011‑1650‑x 21562872
    [Google Scholar]
  33. González-Osuna L. Sierra-Cristancho A. Rojas C. Cafferata E.A. Melgar-Rodríguez S. Cárdenas A.M. Vernal R. Premature senescence of T-cells favors bone loss during osteolytic diseases. A new concern in the osteoimmunology arena. Aging Dis. 2021 12 5 1150 1161 10.14336/AD.2021.0110 34341698
    [Google Scholar]
  34. McDaniel M.M. Chawla A.S. Jain A. Meibers H.E. Saha I. Gao Y. Jain V. Roskin K. Way S.S. Pasare C. Effector memory CD4+ T cells induce damaging innate inflammation and autoimmune pathology by engaging CD40 and TNFR on myeloid cells. Sci. Immunol. 2022 7 67 eabk0182 35061504
    [Google Scholar]
  35. Haylock D.N. Nilsson S.K. Osteopontin: a bridge between bone and blood. Br. J. Haematol. 2006 134 5 467 474 10.1111/j.1365‑2141.2006.06218.x 16848793
    [Google Scholar]
  36. Denhardt D.T. Giachelli C.M. Rittling S.R. Role of osteopontin in cellular signaling and toxicant injury. Annu. Rev. Pharmacol. Toxicol. 2001 41 1 723 749 10.1146/annurev.pharmtox.41.1.723 11264474
    [Google Scholar]
  37. Bai R.J. Li Y.S. Zhang F.J. Osteopontin, a bridge links osteoarthritis and osteoporosis. Front. Endocrinol. (Lausanne) 2022 13 1012508 10.3389/fendo.2022.1012508 36387862
    [Google Scholar]
  38. Zhang B. Dai J. Wang H. Wei H. Zhao J. Guo Y. Fan K. Anti-osteopontin monoclonal antibody prevents ovariectomy-induced osteoporosis in mice by promotion of osteoclast apoptosis. Biochem. Biophys. Res. Commun. 2014 452 3 795 800 10.1016/j.bbrc.2014.08.149 25201732
    [Google Scholar]
  39. Yin P. Chen M. Rao M. Lin Y. Zhang M. Xu R. Hu X. Chen R. Chai W. Huang X. Yu H. Yao Y. Zhao Y. Li Y. Zhang L. Tang P. Deciphering immune landscape remodeling unravels the underlying mechanism for synchronized muscle and bone aging. Adv. Sci. (Weinh.) 2024 11 5 2304084 10.1002/advs.202304084 38088531
    [Google Scholar]
  40. Shi X. Wu Y. Ni H. Li M. Qi B. Xu Y. Macrophage migration inhibitory factor (MIF) inhibitor iSO-1 promotes staphylococcal protein A-induced osteogenic differentiation by inhibiting NF-κB signaling pathway. Int. Immunopharmacol. 2023 115 109600 10.1016/j.intimp.2022.109600 36577150
    [Google Scholar]
  41. Salminen A. Kaarniranta K. Control of p53 and NF-κB signaling by WIP1 and MIF: Role in cellular senescence and organismal aging. Cell. Signal. 2011 23 5 747 752 10.1016/j.cellsig.2010.10.012 20940041
    [Google Scholar]
  42. Lilley C.M. Alarcon A. Ngo M.H. Araujo J.S. Marrero L. Mix K.S. Orphan nuclear receptor NR4A2 is constitutively expressed in cartilage and upregulated in inflamed synovium From hTNF-alpha transgenic mice. Front. Pharmacol. 2022 13 835697 10.3389/fphar.2022.835697 35529439
    [Google Scholar]
  43. Lammi J. Huppunen J. Aarnisalo P. Regulation of the osteopontin gene by the orphan nuclear receptor NURR1 in osteoblasts. Mol. Endocrinol. 2004 18 6 1546 1557 10.1210/me.2003‑0247 14988426
    [Google Scholar]
  44. Glaab E. Schneider R. Comparative pathway and network analysis of brain transcriptome changes during adult aging and in Parkinson’s disease. Neurobiol. Dis. 2015 74 1 13 10.1016/j.nbd.2014.11.002 25447234
    [Google Scholar]
  45. Phillipson O.T. Alpha-synuclein, epigenetics, mitochondria, metabolism, calcium traffic, & circadian dysfunction in Parkinson’s disease. An integrated strategy for management. Ageing Res. Rev. 2017 40 149 167 10.1016/j.arr.2017.09.006 28986235
    [Google Scholar]
  46. Jeon S.G. Yoo A. Chun D.W. Hong S.B. Chung H. Kim J. Moon M. The critical role of Nurr1 as a mediator and therapeutic target in Alzheimer’s disease-related pathogenesis. Aging Dis. 2020 11 3 705 724 10.14336/AD.2019.0718 32489714
    [Google Scholar]
  47. Kwapis J.L. Alaghband Y. López A.J. Long J.M. Li X. Shu G. Bodinayake K.K. Matheos D.P. Rapp P.R. Wood M.A. HDAC3-mediated repression of the Nr4a family contributes to age-related impairments in long-term memory. J. Neurosci. 2019 39 25 4999 5009 10.1523/JNEUROSCI.2799‑18.2019 31000586
    [Google Scholar]
  48. Dera A.A. Ranganath L. Barraclough R. Vinjamuri S. Hamill S. Mandourah A.Y. Barraclough D.L. Altered levels of mRNAs for calcium-binding/associated proteins, annexin A1, S100A4, and TMEM64, in peripheral blood mononuclear cells are associated with osteoporosis. Dis. Markers 2019 2019 1 9 10.1155/2019/3189520 31814858
    [Google Scholar]
  49. Studentsova V. Knapp E. Loiselle A.E. Insulin Receptor deletion in S100a4-lineage cells accelerates age-related bone loss. Bone Rep. 2019 10 100197 10.1016/j.bonr.2019.100197 30805422
    [Google Scholar]
  50. Jiang C. Jiang W. Liu P. Sun W. Teng W. Exploring the relationship between immune heterogeneity characteristic genes of rheumatoid arthritis and acute myeloid leukemia. Discover Oncology 2024 15 1 1 10.1007/s12672‑023‑00852‑7 38165493
    [Google Scholar]
  51. Di W. Fan W. Wu F. Shi Z. Wang Z. Yu M. Zhai Y. Chang Y. Pan C. Li G. Kahlert U.D. Zhang W. Clinical characterization and immunosuppressive regulation of CD161 (KLRB1) in glioma through 916 samples. Cancer Sci. 2022 113 2 756 769 10.1111/cas.15236 34881489
    [Google Scholar]
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