Skip to main content

Advertisement

Log in

Causal Effects of Plasma Proteome on Osteoporosis and Osteoarthritis

  • Original Research
  • Published:
Calcified Tissue International Aims and scope Submit manuscript

Abstract

The two-sample Mendelian randomization (MR) study revealed a causal association of plasma proteins with osteoporosis (OP) and osteoarthritis (OA). Bone mineral density (BMD) is the gold standard for the clinical assessment of OP. Recent studies have shown that plasma proteins play an essential role in the regulation of bone development. However, the causal association of plasma proteins with BMD and OA remains unclear. We estimated the effects of 2889 plasma proteins on 2 BMD phenotypes and 6 OA phenotypes using two-sample MR analysis based on the genome-wide association study summary statistics. Then, we performed sensitivity analysis and reverse-direction MR analysis to evaluate the robustness of the MR analysis results, followed by gene ontology (GO) enrichment analysis and KEGG pathway analysis to explore the functional relevance of the identified plasma proteins. Overall, we observed a total of 257 protein-estimated heel BMD associations, 17 protein-total-body BMD associations, 2 protein-all-OA associations, and 2 protein-knee-OA associations at PFDR < 0.05. Reverse-direction MR analysis demonstrated that there was little evidence of the causal association of BMD and OA with plasma proteins. GO enrichment analysis and KEGG pathway analysis identified multiple pathways, which may be involved in the development of OP and OA. Our findings recognized plasma proteins that could be used to regulate changes in OP and OA, thus, providing new insights into protein-mediated mechanisms of bone development.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Data Availability

Data generated or analyzed during this study are included in this published article or in the data repositories listed in References. Some datasets generated during and/or analyzed during the current study are not publicly accessible but are available from the corresponding author on reasonable request.

References

  1. Ensrud KE, Crandall CJ (2017) Osteoporosis. Ann Intern Med 167:3

    Article  Google Scholar 

  2. Blake GM, Fogelman I (2009) The clinical role of dual energy X-ray absorptiometry. Eur J Radiol 71:406–414

    Article  PubMed  Google Scholar 

  3. Notelovitz M (1993) Osteoporosis: screening, prevention, and management. Fertil Steril 59:707–725

    Article  CAS  PubMed  Google Scholar 

  4. Wang L, Yu W, Yin X, Cui L, Tang S, Jiang N, Cui L, Zhao N, Lin Q, Chen L, Lin H, Jin X, Dong Z, Ren Z, Hou Z, Zhang Y, Zhong J, Cai S, Liu Y, Meng R, Deng Y, Ding X, Ma J, Xie Z, Shen L, Wu W, Zhang M, Ying Q, Zeng Y, Dong J, Cummings SR, Li Z, Xia W (2021) Prevalence of osteoporosis and fracture in China: the China osteoporosis prevalence study. JAMA Netw Open 4:e2121106

    Article  PubMed  PubMed Central  Google Scholar 

  5. Clynes MA, Harvey NC, Curtis EM, Fuggle NR, Dennison EM, Cooper C (2020) The epidemiology of osteoporosis. Br Med Bull 133:105–117

    PubMed  Google Scholar 

  6. Steinberg J, Southam L, Roumeliotis TI, Clark MJ, Jayasuriya RL, Swift D, Shah KM, Butterfield NC, Brooks RA, McCaskie AW, Bassett JHD, Williams GR, Choudhary JS, Wilkinson JM, Zeggini E (2021) A molecular quantitative trait locus map for osteoarthritis. Nat Commun 12:1309

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Bliddal H (2020) Definition, pathology and pathogenesis of osteoarthritis. Ugeskr Laeger 182:42

    Google Scholar 

  8. Diseases GBD, Injuries C (2020) Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global burden of disease study 2019. Lancet 396:1204–1222

    Article  Google Scholar 

  9. Sun X, Zhen X, Hu X, Li Y, Gu S, Gu Y, Dong H (2019) Osteoarthritis in the middle-aged and elderly in China: prevalence and influencing factors. Int J Environ Res Public Health 16:23

    Article  Google Scholar 

  10. Santos R, Ursu O, Gaulton A, Bento AP, Donadi RS, Bologa CG, Karlsson A, Al-Lazikani B, Hersey A, Oprea TI, Overington JP (2017) A comprehensive map of molecular drug targets. Nat Rev Drug Discov 16:19–34

    Article  CAS  PubMed  Google Scholar 

  11. Imming P, Sinning C, Meyer A (2006) Drugs, their targets and the nature and number of drug targets. Nat Rev Drug Discov 5:821–834

    Article  CAS  PubMed  Google Scholar 

  12. Qundos U, Drobin K, Mattsson C, Hong MG, Sjoberg R, Forsstrom B, Solomon D, Uhlen M, Nilsson P, Michaelsson K, Schwenk JM (2016) Affinity proteomics discovers decreased levels of AMFR in plasma from Osteoporosis patients. Proteomics Clin Appl 10:681–690

    Article  CAS  PubMed  Google Scholar 

  13. Ni F, Zhang Y, Peng X, Li J (2020) Correlation between osteoarthritis and monocyte chemotactic protein-1 expression: a meta-analysis. J Orthop Surg Res 15:516

    Article  PubMed  PubMed Central  Google Scholar 

  14. Yoon V, Maalouf NM, Sakhaee K (2012) The effects of smoking on bone metabolism. Osteoporos Int 23:2081–2092

    Article  CAS  PubMed  Google Scholar 

  15. Ferkingstad E, Sulem P, Atlason BA, Sveinbjornsson G, Magnusson MI, Styrmisdottir EL, Gunnarsdottir K, Helgason A, Oddsson A, Halldorsson BV, Jensson BO, Zink F, Halldorsson GH, Masson G, Arnadottir GA, Katrinardottir H, Juliusson K, Magnusson MK, Magnusson OT, Fridriksdottir R, Saevarsdottir S, Gudjonsson SA, Stacey SN, Rognvaldsson S, Eiriksdottir T, Olafsdottir TA, Steinthorsdottir V, Tragante V, Ulfarsson MO, Stefansson H, Jonsdottir I, Holm H, Rafnar T, Melsted P, Saemundsdottir J, Norddahl GL, Lund SH, Gudbjartsson DF, Thorsteinsdottir U, Stefansson K (2021) Large-scale integration of the plasma proteome with genetics and disease. Nat Genet 53:1712–1721

    Article  CAS  PubMed  Google Scholar 

  16. Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J, Downey P, Elliott P, Green J, Landray M, Liu B, Matthews P, Ong G, Pell J, Silman A, Young A, Sprosen T, Peakman T, Collins R (2015) UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med 12:e1001779

    Article  PubMed  PubMed Central  Google Scholar 

  17. Morris JA, Kemp JP, Youlten SE, Laurent L, Logan JG, Chai RC, Vulpescu NA, Forgetta V, Kleinman A, Mohanty ST, Sergio CM, Quinn J, Nguyen-Yamamoto L, Luco AL, Vijay J, Simon MM, Pramatarova A, Medina-Gomez C, Trajanoska K, Ghirardello EJ, Butterfield NC, Curry KF, Leitch VD, Sparkes PC, Adoum AT, Mannan NS, Komla-Ebri DSK, Pollard AS, Dewhurst HF, Hassall TAD, Beltejar MG, andMe Research T, Adams DJ, Vaillancourt SM, Kaptoge S, Baldock P, Cooper C, Reeve J, Ntzani EE, Evangelou E, Ohlsson C, Karasik D, Rivadeneira F, Kiel DP, Tobias JH, Gregson CL, Harvey NC, Grundberg E, Goltzman D, Adams DJ, Lelliott CJ, Hinds DA, Ackert-Bicknell CL, Hsu YH, Maurano MT, Croucher PI, Williams GR, Bassett JHD, Evans DM, Richards JB (2019) An atlas of genetic influences on osteoporosis in humans and mice. Nat Genet 51:258–266

    Article  CAS  PubMed  Google Scholar 

  18. Medina-Gomez C, Kemp JP, Trajanoska K, Luan J, Chesi A, Ahluwalia TS, Mook-Kanamori DO, Ham A, Hartwig FP, Evans DS, Joro R, Nedeljkovic I, Zheng HF, Zhu K, Atalay M, Liu CT, Nethander M, Broer L, Porleifsson G, Mullin BH, Handelman SK, Nalls MA, Jessen LE, Heppe DHM, Richards JB, Wang C, Chawes B, Schraut KE, Amin N, Wareham N, Karasik D, Van der Velde N, Ikram MA, Zemel BS, Zhou Y, Carlsson CJ, Liu Y, McGuigan FE, Boer CG, Bonnelykke K, Ralston SH, Robbins JA, Walsh JP, Zillikens MC, Langenberg C, Li-Gao R, Williams FMK, Harris TB, Akesson K, Jackson RD, Sigurdsson G, den Heijer M, van der Eerden BCJ, van de Peppel J, Spector TD, Pennell C, Horta BL, Felix JF, Zhao JH, Wilson SG, de Mutsert R, Bisgaard H, Styrkarsdottir U, Jaddoe VW, Orwoll E, Lakka TA, Scott R, Grant SFA, Lorentzon M, van Duijn CM, Wilson JF, Stefansson K, Psaty BM, Kiel DP, Ohlsson C, Ntzani E, van Wijnen AJ, Forgetta V, Ghanbari M, Logan JG, Williams GR, Bassett JHD, Croucher PI, Evangelou E, Uitterlinden AG, Ackert-Bicknell CL, Tobias JH, Evans DM, Rivadeneira F (2018) Life-course genome-wide association study meta-analysis of total body bmd and assessment of age-specific effects. Am J Hum Genet 102:88–102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Boer CG, Hatzikotoulas K, Southam L, Stefansdottir L, Zhang Y, Coutinho de Almeida R, Wu TT, Zheng J, Hartley A, Teder-Laving M, Skogholt AH, Terao C, Zengini E, Alexiadis G, Barysenka A, Bjornsdottir G, Gabrielsen ME, Gilly A, Ingvarsson T, Johnsen MB, Jonsson H, Kloppenburg M, Luetge A, Lund SH, Magi R, Mangino M, Nelissen R, Shivakumar M, Steinberg J, Takuwa H, Thomas LF, Tuerlings M, arc OC, Pain HA-I, Consortium A, Regeneron Genetics C, Babis GC, Cheung JPY, Kang JH, Kraft P, Lietman SA, Samartzis D, Slagboom PE, Stefansson K, Thorsteinsdottir U, Tobias JH, Uitterlinden AG, Winsvold B, Zwart JA, Davey Smith G, Sham PC, Thorleifsson G, Gaunt TR, Morris AP, Valdes AM, Tsezou A, Cheah KSE, Ikegawa S, Hveem K, Esko T, Wilkinson JM, Meulenbelt I, Lee MTM, van Meurs JBJ, Styrkarsdottir U, Zeggini E (2021) Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations. Cell 184(4784–4818):e4717

    Google Scholar 

  20. Davey Smith G, Davies NM, Dimou N, Egger M, Gallo V, Golub R, Higgins JPT, Langenberg C, Loder EW, Richards JB, Richmond RC, Skrivankova VW, Swanson SA, Timpson NJ, Tybjaerg-Hansen A, VanderWeele TJ, Woolf BAR, Yarmolinsky J (2019) STROBEMR: guidelines for strengthening the reporting of Mendelian randomization studies.

  21. Burgess S, Thompson SG (2017) Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol 32:377–389

    Article  PubMed  PubMed Central  Google Scholar 

  22. Consortium GT (2013) The Genotype-Tissue Expression (GTEx) project. Nat Genet 45:580–585

    Article  Google Scholar 

  23. Mullin BH, Tickner J, Zhu K, Kenny J, Mullin S, Brown SJ, Dudbridge F, Pavlos NJ, Mocarski ES, Walsh JP, Xu J, Wilson SG (2020) Characterisation of genetic regulatory effects for osteoporosis risk variants in human osteoclasts. Genome Biol 21:80

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Mullin BH, Zhu K, Brown SJ, Mullin S, Tickner J, Pavlos NJ, Dudbridge F, Xu J, Walsh JP, Wilson SG (2019) Genetic regulatory mechanisms in human osteoclasts suggest a role for the STMP1 and DCSTAMP genes in Paget’s disease of bone. Sci Rep 9:1052

    Article  PubMed  PubMed Central  Google Scholar 

  25. Mullin BH, Zhu K, Xu J, Brown SJ, Mullin S, Tickner J, Pavlos NJ, Dudbridge F, Walsh JP, Wilson SG (2018) Expression quantitative trait locus study of bone mineral density GWAS variants in human osteoclasts. J Bone Miner Res 33:1044–1051

    Article  CAS  PubMed  Google Scholar 

  26. Qu Z, Yang F, Yan Y, Hong J, Wang W, Li S, Jiang G, Yan S (2021) Relationship between serum nutritional factors and bone mineral density: a mendelian randomization study. J Clin Endocrinol Metab 106:e2434–e2443

    Article  PubMed  Google Scholar 

  27. Kemp JP, Morris JA, Medina-Gomez C, Forgetta V, Warrington NM, Youlten SE, Zheng J, Gregson CL, Grundberg E, Trajanoska K, Logan JG, Pollard AS, Sparkes PC, Ghirardello EJ, Allen R, Leitch VD, Butterfield NC, Komla-Ebri D, Adoum AT, Curry KF, White JK, Kussy F, Greenlaw KM, Xu C, Harvey NC, Cooper C, Adams DJ, Greenwood CMT, Maurano MT, Kaptoge S, Rivadeneira F, Tobias JH, Croucher PI, Ackert-Bicknell CL, Bassett JHD, Williams GR, Richards JB, Evans DM (2017) Identification of 153 new loci associated with heel bone mineral density and functional involvement of GPC6 in osteoporosis. Nat Genet 49:1468–1475

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Schousboe JT, Shepherd JA, Bilezikian JP, Baim S. (2013) Executive summary of the 2013 international society for clinical densitometry position development conference on bone densitometry. J Clin Densitom. 16: 455–466

  29. Weimer A, Madry H, Venkatesan JK, Schmitt G, Frisch J, Wezel A, Jung J, Kohn D, Terwilliger EF, Trippel SB, Cucchiarini M (2012) Benefits of recombinant adeno-associated virus (rAAV)-mediated insulinlike growth factor I (IGF-I) overexpression for the long-term reconstruction of human osteoarthritic cartilage by modulation of the IGF-I axis. Mol Med 18:346–358

    Article  CAS  PubMed  Google Scholar 

  30. Cardon LR, Palmer LJ (2003) Population stratification and spurious allelic association. Lancet 361:598–604

    Article  PubMed  Google Scholar 

  31. Burden AM, Tanaka Y, Xu L, Ha YC, McCloskey E, Cummings SR, Gluer CC (2021) Osteoporosis case ascertainment strategies in European and Asian countries: a comparative review. Osteoporos Int 32:817–829

    Article  CAS  PubMed  Google Scholar 

  32. Burgess S, Davies NM, Thompson SG (2016) Bias due to participant overlap in two-sample Mendelian randomization. Genet Epidemiol 40:597–608

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We are grateful to all studies that released GWAS summary statistics for use in this study.

Funding

YFP was partially supported by the funding from the national natural science foundation of China (32170670) and a project funded by the Priority Academic Program Development (PAPD) of Jiangsu higher education institutions. The numerical calculations in this manuscript have been done on the supercomputing system of the National Supercomputing Center in Changsha.

Author information

Authors and Affiliations

Authors

Contributions

YFP and LZ: designed the study. BXH and YFP: collected the data. BXH and YFP: analyzed the data. SSY, YH, QX, QGZ, XLM, JJN, and BXH: performed the literature search. BXH: drafted the early version of the manuscript. YFP and LZ: jointly supervised the study. All authors were involved in writing the paper and had final approval of the submitted and published versions.

Corresponding authors

Correspondence to Lei Zhang or Yu-Fang Pei.

Ethics declarations

Conflict of interest

Bai-Xue Han, Shan-Shan Yan, Yu Han, Qian Xu, Qi-Gang Zhao, Xin-Ling Ma, Jing-Jing Ni, Lei Zhang, and Yu-Fang Pei declare they have no conflict of interest.

Human and Animal Rights

All the exposure and outcome data were released by previous studies that had passed the ethical review of institutional review boards (IRBs). This study does not require additional ethical review.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Han, BX., Yan, SS., Yu Han et al. Causal Effects of Plasma Proteome on Osteoporosis and Osteoarthritis. Calcif Tissue Int 112, 350–358 (2023). https://doi.org/10.1007/s00223-022-01049-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00223-022-01049-w

Keywords

Navigation