Cathepsin F as a potential serum biomarker for stroke risk prediction: GWAS database data analysis

doi:10.12307/2026.606

Abstract

Abstract: BACKGROUND: Prior research has indicated a correlation between cathepsins and stroke, but the nature of this relationship—whether causal—has yet to be established.
OBJECTIVE: To scrutinize the potential causal links between cathepsins and stroke using the Mendelian randomization method.
METHODS: Leveraging summary statistics from genome-wide association studies (GWAS, developed jointly by the U.S. National Human Genome Research Institute and the European Bioinformatics Institute), we performed Mendelian randomization analyses using both univariable and multivariable approaches to investigate the causal associations of various cathepsin types with stroke risk and its specific subtypes. The inverse variance weighting method was used as the main method to assess the causal association effect, and the weighted median method and MR-Egger regression were used to assess the reliability and stability of the results.
RESULTS AND CONCLUSION: (1) The univariable Mendelian randomization analysis revealed that elevated Cathepsin S levels were associated with a reduced likelihood of cardioembolic stroke (odds ratio [OR]=0.901, 95% confidence interval [CI]: 0.832-0.976, P=0.010). However, this causal effect was not corroborated in the reverse Mendelian randomization analysis. The reverse Mendelian randomization analysis suggested that Cathepsin E Subtype (CES) could contribute to lower Cathepsin L2 levels (P=0.020, OR = 0.984, 95% CI=0.972-0.998), yet this finding lacked statistical significance in the multivariable context. A multivariable analysis, incorporating nine cathepsin types, indicated that elevated Cathepsin F levels were associated with an increased risk of all-cause stroke and ischemic stroke (OR=4.667, 95% CI=1.000-21.782, P=0.050, OR=4.771, 95% CI=1.044-21.804, P=0.044). Even after accounting for potential confounding factors, the Mendelian randomization analysis indicated that Cathepsin F holds promise as a serum biomarker for predicting stroke risk. (2) This study is primarily based on the analyses of international databases and European population data, which can serve as a reference for large-scale cohort studies in China and provide technical insights for the development of precision medicine research in China. However, it is essential to consider the differences in genetic background, environmental factors, and lifestyle among the Chinese population, and to conduct biomedical research that aligns with the unique characteristics of Chinese individuals.

Key words: Cathepsins, stroke, Mendelian randomization, multivariate analysis, risk prediction, biomarkers

CLC Number:

Tian Meng, Lou Tianwei, Zhang Yongchen, Jia Hongling . Cathepsin F as a potential serum biomarker for stroke risk prediction: GWAS database data analysis[J]. Chinese Journal of Tissue Engineering Research, 2026, 30(10): 2662-2670.

Figures/Tables 8

2.2 反向孟德尔随机化分析结果为了探索反向因果关系的可能性，进行了反向孟德尔随机化分析，结果显示组织蛋白酶S与心源性脑卒中风险之间缺乏反向因果关系(表3)。然而，反向孟德尔随机化-逆方差加权分析结果表明，心源性栓塞性脑卒中可能导致组织蛋白酶L2水平的下降(OR=0.984，95%CI：0.972-0.998，P=0.020)。孟德尔随机化-逆方差加权分析检测的Q_pval=0.327，MR-Egger截距检验P=0.490，异质性和敏感性分析均验证了上述结果的稳健性(P > 0.05)，见表4。在留一法分析中，排除每个单核苷酸多态性后，剩余单核苷酸多态性的效应值基本围绕整体效应值分布，且置信区间较窄，表明孟德尔随机化结果对单个单核苷酸多态性的依赖性较低，结果较为稳健(图1B)。没有证据支持其他亚型脑卒中与各种类型的组织蛋白酶之间存在因果关系，见表3。 2.3 多变量孟德尔随机化分析结果进行了多变量孟德尔随机化分析，以评估多种组织蛋白酶的遗传易感性与不同亚型脑卒中风险的关系，结果显示，组织蛋白酶F水平升高与全因脑卒中风险增加相关，高水平的组织蛋白酶F最高能增加21.782倍的全因脑卒中发病风险(OR=4.667，95%CI=1.000-21.782，P=0.050)。 MR-Egger截距检验未检测到单核苷酸多态性多效性(P=0.818)，见图2A，表5，6。组织蛋白酶F水平升高会增加缺血性脑卒中的发病风险，当组织蛋白酶F水平升高时，缺血性脑卒中的发病风险增加了4.771倍(OR=4.771)，这一结果具有统计学意义(P=0.044)，表明结果不太可能是偶然发生的。可以以95%CI断言，组织蛋白酶F水平升高与缺血性脑卒中发病风险的真实关系至少是1.044倍，可能高达21.804倍(95%CI：1.044-21.804)。MR-Egger截距分析也未显示水平多效性(P=0.838)，见图2B，表5，6。其他类型组织蛋白酶与任何脑卒中及其亚型之间均未显示出统计学意义上的因果关系，见图2，表5。"

References

[1] GBD 2016 LIFETIME RISK OF STROKE COLLABORATORS, FEIGIN VL, NGUYEN G, et al. Global, Regional, and Country-Specific Lifetime Risks of Stroke, 1990 and 2016. N Engl J Med. 2018;379(25):2429-2437.
[2] GBD 2016 STROKE COLLABORATORS. Global, regional, and national burden of stroke, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(5):439-458.
[3] LINDSAY MP, NORRVING B, SACCO RL, et al. World Stroke Organization (WSO): Global Stroke Fact Sheet 2019. Int J Stroke. 2019;14(8):806-817.
[4] KAHL A, BLANCO I, JACKMAN K, et al. Publisher Correction: Cerebral ischemia induces the aggregation of proteins linked to neurodegenerative diseases. Sci Rep. 2018;8(1):6802.
[5] GIFFARD RG, XU L, ZHAO H, et al. Chaperones, protein aggregation, and brain protection from hypoxic/ischemic injury. J Exp Biol. 2004;207(Pt 18):3213-3220.
[6] LIU Y, XUE X, ZHANG H, et al. Neuronal-targeted TFEB rescues dysfunction of the autophagy-lysosomal pathway and alleviates ischemic injury in permanent cerebral ischemia. Autophagy. 2019;15(3):493-509.
[7] REISER J, ADAIR B, REINHECKEL T. Specialized roles for cysteine cathepsins in health and disease. J Clin Invest. 2010;120(10):3421-3431.
[8] PATEL S, HOMAEI A, EL-SEEDI HR, et al. Cathepsins: Proteases that are vital for survival but can also be fatal. Biomed Pharmacother. 2018;105:526-532.
[9] HU K, GAIRE BP, SUBEDI L, et al. Interruption of Endolysosomal Trafficking After Focal Brain Ischemia. Front Mol Neurosci. 2021; 14:719100.
[10] YUAN D, HU K, LOKE CM, et al. Interruption of endolysosomal trafficking leads to stroke brain injury. Exp Neurol. 2021;345:113827.
[11] CARLONI S, BUONOCORE G, BALDUINI W. Protective role of autophagy in neonatal hypoxia-ischemia induced brain injury. Neurobiol Dis. 2008;32(3):329-339.
[12] WEN YD, SHENG R, ZHANG LS, et al. Neuronal injury in rat model of permanent focal cerebral ischemia is associated with activation of autophagic and lysosomal pathways. Autophagy. 2008;4(6):762-769.
[13] RAMI A, LANGHAGEN A, STEIGER S. Focal cerebral ischemia induces upregulation of Beclin 1 and autophagy-like cell death. Neurobiol Dis. 2008;29(1):132-141.
[14] ZHANG X, YAN H, YUAN Y, et al. Cerebral ischemia-reperfusion-induced autophagy protects against neuronal injury by mitochondrial clearance. Autophagy. 2013;9(9):1321-1333.
[15] Nakanishi H. Microglial cathepsin B as a key driver of inflammatory brain diseases and brain aging. Neural Regen Res. 2020; 15(1):25-29.
[16] BRENNAN P, HAINAUT P, BOFFETTA P. Genetics of lung-cancer susceptibility. Lancet Oncol. 2011;12(4):399-408.
[17] JULIAN TH, BODDY S, ISLAM M, et al. A review of Mendelian randomization in amyotrophic lateral sclerosis. Brain. 2022;145(3):832-842.
[18] SUN BB, MARANVILLE JC, PETERS JE, et al. Genomic atlas of the human plasma proteome. Nature. 2018;558(7708):73-79.
[19] MALIK R, CHAUHAN G, TRAYLOR M, et al. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat Genet. 2018;50(4):524-537.
[20] LIN Z, DENG Y, PAN W. Combining the strengths of inverse-variance weighting and Egger regression in Mendelian randomization using a mixture of regressions model. PLoS Genet. 2021; 17(11):e1009922.
[21] BOWDEN J, DAVEY SMITH G, HAYCOCK PC, et al. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator. Genet Epidemiol. 2016;40(4):304-314.
[22] BOWDEN J, DAVEY SMITH G, BURGESS S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44(2):512-525.
[23] COHEN JF, CHALUMEAU M, COHEN R, et al. Cochran’s Q test was useful to assess heterogeneity in likelihood ratios in studies of diagnostic accuracy. J Clin Epidemiol. 2015;68(3):299-306.
[24] Gala H, Tomlinson I. The use of Mendelian randomisation to identify causal cancer risk factors: promise and limitations. J Pathol. 2020;250(5):541-554.
[25] HILKENS NA, CASOLLA B, LEUNG TW, et al. Stroke. Lancet. 2024;403(10446):2820-2836.
[26] EKKER MS, VERHOEVEN JI, VAARTJES I, et al. Stroke incidence in young adults according to age, subtype, sex, and time trends. Neurology. 2019;92(21):e2444-e2454.
[27] YIIN GS, HOWARD DP, PAUL NL, et al. Age-specific incidence, outcome, cost, and projected future burden of atrial fibrillation-related embolic vascular events: a population-based study. Circulation. 2014;130(15):1236-1244.
[28] BOGIATZI C, HACKAM DG, MCLEOD AI, et al. Secular trends in ischemic stroke subtypes and stroke risk factors. Stroke. 2014;45(11):3208-3213.
[29] FERNLUND E, GYLLENHAMMAR T, JABLONOWSKI R, et al. Serum Biomarkers of Myocardial Remodeling and Coronary Dysfunction in Early Stages of Hypertrophic Cardiomyopathy in the Young. Pediatr Cardiol. 2017;38(4):853-863.
[30] CUVELLIEZ M, VANDEWALLE V, BRUNIN M, et al. Circulating proteomic signature of early death in heart failure patients with reduced ejection fraction. Sci Rep. 2019;9(1):19202.
[31] STYPMANN J, GLÄSER K, ROTH W, et al. Dilated cardiomyopathy in mice deficient for the lysosomal cysteine peptidase cathepsin L. Proc Natl Acad Sci U S A. 2002; 99(9):6234-6239.
[32] TANG Q, CAI J, SHEN D, et al. Lysosomal cysteine peptidase cathepsin L protects against cardiac hypertrophy through blocking AKT/GSK3beta signaling. J Mol Med (Berl). 2009;87(3):249-260.
[33] BEVAN S, TRAYLOR M, ADIB-SAMII P, et al. Genetic heritability of ischemic stroke and the contribution of previously reported candidate gene and genomewide associations. Stroke. 2012;43(12):3161-3167.
[34] OLSON OC, JOYCE JA. Cysteine cathepsin proteases: regulators of cancer progression and therapeutic response. Nat Rev Cancer. 2015;15(12):712-729.
[35] LIN Z, ZHAO S, LI X, et al. Cathepsin B S-nitrosylation promotes ADAR1-mediated editing of its own mRNA transcript via an ADD1/MATR3 regulatory axis. Cell Res. 2023;33(7):546-561.
[36] LI J, CHEN Z, KIM G, et al. Cathepsin W restrains peripheral regulatory T cells for mucosal immune quiescence. Sci Adv. 2023;9(28):eadf3924.
[37] ARORA K, HERROON M, AL-AFYOUNI MH, et al. Catch and Release Photosensitizers: Combining Dual-Action Ruthenium Complexes with Protease Inactivation for Targeting Invasive Cancers. J Am Chem Soc. 2018;140(43):14367-14380.
[38] FRUGÉ AD, SMITH KS, BAIL JR, et al. Biomarkers Associated With Tumor Ki67 and Cathepsin L Gene Expression in Prostate Cancer Patients Participating in a Presurgical Weight Loss Trial. Front Oncol. 2020;10:544201.
[39] BARARIA D, HILDEBRAND JA, STOLZ S, et al.Cathepsin S Alterations Induce a Tumor-Promoting Immune Microenvironment in Follicular Lymphoma. Cell Rep. 2020; 31(5):107522.
[40] SONG L, WANG X, CHENG W, et al. Expression signature, prognosis value and immune characteristics of cathepsin F in non-small cell lung cancer identified by bioinformatics assessment. BMC Pulm Med. 2021;21(1):420.
[41] WEI S, LIU W, XU M, et al. Cathepsin F and Fibulin-1 as novel diagnostic biomarkers for brain metastasis of non-small cell lung cancer. Br J Cancer. 2022;126(12):1795-1805.
[42] SANTAMARÍA I, VELASCO G, PENDÁS AM, et al. Molecular cloning and structural and functional characterization of human cathepsin F, a new cysteine proteinase of the papain family with a long propeptide domain. J Biol Chem. 1999;274(20): 13800-13809.
[43] ZDRAVKOVA K, MIJANOVIC O, BRANKOVIC A, et al. Unveiling the Roles of Cysteine Proteinases F and W: From Structure to Pathological Implications and Therapeutic Targets. Cells. 2024;13(11):917.
[44] HSU A, PODVIN S, HOOK V. Lysosomal Cathepsin Protease Gene Expression Profiles in the Human Brain During Normal Development. J Mol Neurosci. 2018;65(4):420-431.
[45] TANG CH, LEE JW, GALVEZ MG, et al. Murine cathepsin F deficiency causes neuronal lipofuscinosis and late-onset neurological disease. Mol Cell Biol. 2006;26(6):2309-2316.
[46] DALTON JP, ROBINSON MW, BRINDLEY PJ. Cathepsin// BARRETT AJ, RAWLINGS ND, WOESSNER JF, eds. Handbook of Proteolytic Enzymes. 3rd ed. Cambridge, MA: Academic Press; 2013.
[47] FINN RD, BATEMAN A, CLEMENTS J, et al.Pfam: the protein families database. Nucleic Acids Res. 2014;42(Database issue): D222-D230.
[48] DI FABIO R, MORO F, PESTILLO L, et al. Pseudo-dominant inheritance of a novel CTSF mutation associated with type B Kufs disease. Neurology. 2014;83(19):1769-1770.