Exploring the Causal Relationship Between Plasma Proteins and Systemic Lupus Erythematosus: A Mendelian Randomization Study
DOI:
https://doi.org/10.71321/ma96k735Keywords:
Systemic Lupus Erythematosus, Mendelian Randomization, Circulating Proteins, Colocalization Analysis, Protein-Protein Interaction NetworkAbstract
Background: Systemic lupus erythematosus (SLE) is a complex autoimmune disease that severely impacts patient quality of life. Current treatments primarily manage symptoms rather than cure the disease, emphasizing the need for a deeper understanding of its pathogenesis and the discovery of novel therapeutic targets. Circulating proteins are thought to play a critical role in SLE risk, but their causal relationships remain underexplored.
Methods: This study used pQTL and genome-wide association study (GWAS) data to perform a two-sample Mendelian randomization (MR) analysis to investigate the genetic causal relationships between circulating proteins and SLE. We identified proteins potentially associated with SLE risk and further analyzed their roles in immune regulation and inflammation using Protein-Protein Interaction (PPI) networks. Colocalization analysis was conducted to validate the associations of key proteins with SLE.
Results: Our analysis identified 82 plasma proteins potentially causally linked to SLE risk (p < 0.05). Colocalization analysis confirmed the association of proteins such as TNFAIP3, PDHX, and CTSF with SLE, underscoring their critical role in disease pathogenesis. Additionally, PPI network analysis revealed that these proteins are involved in immune modulation and inflammatory pathways, further supporting their relevance as therapeutic targets.
Conclusion: This study identifies 82 plasma proteins that may play a causal role in SLE, with TNFAIP3, PDHX, and CTSF emerging as promising therapeutic targets. These findings provide a foundation for future research aimed at developing precision therapies for SLE.
References
[1] Durcan L, O'Dwyer T, Petri M. Management strategies and future directions for systemic lupus erythematosus in adults. Lancet. 2019;393(10188):2332-43.
[2] Rees F, Doherty M, Grainge MJ, Lanyon P, Zhang W. The worldwide incidence and prevalence of systemic lupus erythematosus: a systematic review of epidemiological studies. Rheumatology (Oxford). 2017;56(11):1945-61.
[3] Fava A, Petri M. Systemic lupus erythematosus: Diagnosis and clinical management. J Autoimmun. 2019;96:1-13.
[4] Navarra SV, Guzmán RM, Gallacher AE, Hall S, Levy RA, Jimenez RE, et al. Efficacy and safety of belimumab in patients with active systemic lupus erythematosus: a randomised, placebo-controlled, phase 3 trial. Lancet. 2011;377(9767):721-31.
[5] Fanouriakis A, Kostopoulou M, Alunno A, Aringer M, Bajema I, Boletis JN, et al. 2019 update of the EULAR recommendations for the management of systemic lupus erythematosus. Ann Rheum Dis. 2019;78(6):736-45.
[6] Liu Z, Davidson A. Taming lupus-a new understanding of pathogenesis is leading to clinical advances. Nat Med. 2012;18(6):871-82.
[7] Weinstein A, Alexander RV, Zack DJ. A Review of Complement Activation in SLE. Curr Rheumatol Rep. 2021;23(3):16.
[8] Finan C, Gaulton A, Kruger FA, Lumbers RT, Shah T, Engmann J, et al. The druggable genome and support for target identification and validation in drug development. Sci Transl Med. 2017;9(383).
[9] Baker T, Sharifian H, Newcombe PJ, Gavin PG, Lazarus MN, Ramaswamy M, et al. Type I interferon blockade with anifrolumab in patients with systemic lupus erythematosus modulates key immunopathological pathways in a gene expression and proteomic analysis of two phase 3 trials. Ann Rheum Dis. 2024;83(8):1018-27.
[10] Henry A, Gordillo-Marañón M, Finan C, Schmidt AF, Ferreira JP, Karra R, et al. Therapeutic Targets for Heart Failure Identified Using Proteomics and Mendelian Randomization. Circulation. 2022;145(16):1205-17.
[11] He J, Tang D, Liu D, Hong X, Ma C, Zheng F, et al. Serum proteome and metabolome uncover novel biomarkers for the assessment of disease activity and diagnosing of systemic lupus erythematosus. Clin Immunol. 2023;251:109330.
[12] Zhou G, Wei P, Lan J, He Q, Guo F, Guo Y, et al. TMT-based quantitative proteomics analysis and potential serum protein biomarkers for systemic lupus erythematosus. Clin Chim Acta. 2022;534:43-9.
[13] Emdin CA, Khera AV, Kathiresan S. Mendelian Randomization. Jama. 2017;318(19):1925-6.
[14] Davey Smith G, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Human Molecular Genetics. 2014;23(R1):R89-R98.
[15] Pietzner M, Wheeler E, Carrasco-Zanini J, Cortes A, Koprulu M, Wörheide MA, et al. Mapping the proteo-genomic convergence of human diseases. Science. 2021;374(6569):eabj1541.
[16] Kurki MI, Karjalainen J, Palta P, Sipilä TP, Kristiansson K, Donner KM, et al. FinnGen provides genetic insights from a well-phenotyped isolated population. Nature. 2023;613(7944):508-18.
[17] Zheng J, Baird D, Borges MC, Bowden J, Hemani G, Haycock P, et al. Recent Developments in Mendelian Randomization Studies. Curr Epidemiol Rep. 2017;4(4):330-45.
[18] Sun J, Zhao J, Jiang F, Wang L, Xiao Q, Han F, et al. Identification of novel protein biomarkers and drug targets for colorectal cancer by integrating human plasma proteome with genome. Genome Med. 2023;15(1):75.
[19] Lai R, Deng X, Lv X, Zhong Y. Causal relationship between inflammatory proteins, immune cells, and gout: a Mendelian randomization study. Sci Rep. 2024;14(1):30070.
[20] Burgess S, Thompson SG. Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol. 2011;40(3):755-64.
[21] Zhao H, Zhou Y, Wang Z, Zhang X, Chen L, Hong Z. Plasma proteins and psoriatic arthritis: a proteome-wide Mendelian randomization study. Front Immunol. 2024;15:1417564.
[22] Wei T, Zhu Z, Liu L, Liu B, Wu M, Zhang W, et al. Circulating levels of cytokines and risk of cardiovascular disease: a Mendelian randomization study. Front Immunol. 2023;14:1175421.
[23] Burgess S, Dudbridge F, Thompson SG. Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods. Stat Med. 2016;35(11):1880-906.
[24] Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol. 2017;32(5):377-89.
[25] Morin PA, Martien KK, Taylor BL. Assessing statistical power of SNPs for population structure and conservation studies. Mol Ecol Resour. 2009;9(1):66-73.
[26] Hemani G, Tilling K, Davey Smith G. Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS Genet. 2017;13(11):e1007081.
[27] Giambartolomei C, Vukcevic D, Schadt EE, Franke L, Hingorani AD, Wallace C, et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet. 2014;10(5):e1004383.
[28] Yao P, Iona A, Pozarickij A, Said S, Wright N, Lin K, et al. Proteomic Analyses in Diverse Populations Improved Risk Prediction and Identified New Drug Targets for Type 2 Diabetes. Diabetes Care. 2024;47(6):1012-9.
[29] Szklarczyk D, Kirsch R, Koutrouli M, Nastou K, Mehryary F, Hachilif R, et al. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 2023;51(D1):D638-d46.
[30] Tsai YG, Liao PF, Hsiao KH, Wu HM, Lin CY, Yang KD. Pathogenesis and novel therapeutics of regulatory T cell subsets and interleukin-2 therapy in systemic lupus erythematosus. Front Immunol. 2023;14:1230264.
[31] Ameer MA, Chaudhry H, Mushtaq J, Khan OS, Babar M, Hashim T, et al. An Overview of Systemic Lupus Erythematosus (SLE) Pathogenesis, Classification, and Management. Cureus. 2022;14(10):e30330.
[32] Mooney EC, Sahingur SE. The Ubiquitin System and A20: Implications in Health and Disease. J Dent Res. 2021;100(1):10-20.
[33] Catrysse L, Vereecke L, Beyaert R, van Loo G. A20 in inflammation and autoimmunity. Trends Immunol. 2014;35(1):22-31.
[34] Witt A, Vucic D. Diverse ubiquitin linkages regulate RIP kinases-mediated inflammatory and cell death signaling. Cell Death Differ. 2017;24(7):1160-71.
[35] Guo C, Fu R, Zhou M, Wang S, Huang Y, Hu H, et al. Pathogenesis of lupus nephritis: RIP3 dependent necroptosis and NLRP3 inflammasome activation. J Autoimmun. 2019;103:102286.
[36] Mele A, Cervantes JR, Chien V, Friedman D, Ferran C. Single nucleotide polymorphisms at the TNFAIP3/A20 locus and susceptibility/resistance to inflammatory and autoimmune diseases. Adv Exp Med Biol. 2014;809:163-83.
[37] Kawasaki A, Ito I, Ito S, Hayashi T, Goto D, Matsumoto I, et al. Association of TNFAIP3 polymorphism with susceptibility to systemic lupus erythematosus in a Japanese population. J Biomed Biotechnol. 2010;2010:207578.
[38] Musone SL, Taylor KE, Lu TT, Nititham J, Ferreira RC, Ortmann W, et al. Multiple polymorphisms in the TNFAIP3 region are independently associated with systemic lupus erythematosus. Nat Genet. 2008;40(9):1062-4.
[39] Liu Y, Dan G, Wu L, Chen G, Wu A, Zeng P, et al. Functional effect of polymorphisms in the promoter of TNFAIP3 (A20) in acute pancreatitis in the Han Chinese population. PLoS One. 2014;9(7):e103104.
[40] Harris RA, Bowker-Kinley MM, Wu P, Jeng J, Popov KM. Dihydrolipoamide dehydrogenase-binding protein of the human pyruvate dehydrogenase complex. DNA-derived amino acid sequence, expression, and reconstitution of the pyruvate dehydrogenase complex. J Biol Chem. 1997;272(32):19746-51.
[41] Lessard CJ, Adrianto I, Kelly JA, Kaufman KM, Grundahl KM, Adler A, et al. Identification of a systemic lupus erythematosus susceptibility locus at 11p13 between PDHX and CD44 in a multiethnic study. Am J Hum Genet. 2011;88(1):83-91.
[42] Jiang R, Sun Y, Li Y, Tang X, Hui B, Ma S, et al. Cuproptosis-related gene PDHX and heat stress-related HSPD1 as potential key drivers associated with cell stemness, aberrant metabolism and immunosuppression in esophageal carcinoma. Int Immunopharmacol. 2023;117:109942.
[43] Turk V, Stoka V, Vasiljeva O, Renko M, Sun T, Turk B, et al. Cysteine cathepsins: from structure, function and regulation to new frontiers. Biochim Biophys Acta. 2012;1824(1):68-88.
[44] Somoza JR, Palmer JT, Ho JD. The crystal structure of human cathepsin F and its implications for the development of novel immunomodulators. J Mol Biol. 2002;322(3):559-68.
[45] Zhou X, Chen H, Huang D, Guan G, Ma X, Cai W, et al. Reduced expression of cathepsin F predicts poor prognosis in patients with clear cell renal cell carcinoma. Sci Rep. 2024;14(1):13556.
[46] Gureeva TA, Timoshenko OS, Kugaevskaya EV, Solovyova NI. [Cysteine cathepsins: structure, physiological functions and their role in carcinogenesis]. Biomed Khim. 2021;67(6):453-64.
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The data that support the findings of this study are available in the supplementary material of this article.
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