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. 2024 Nov;416(28):6357-6366.
doi: 10.1007/s00216-024-05521-4. Epub 2024 Sep 10.

Identification of novel protein biomarkers and therapeutic targets for ankylosing spondylitis using human circulating plasma proteomics and genome analysis

Affiliations

Identification of novel protein biomarkers and therapeutic targets for ankylosing spondylitis using human circulating plasma proteomics and genome analysis

Zhongxian Zhou et al. Anal Bioanal Chem. 2024 Nov.

Abstract

The proteome serves as the primary basis for identifying targets for treatment. This study conducted proteomic range two-sample Mendelian randomization (MR) analysis to pinpoint potential protein markers and treatment targets for ankylosing spondylitis (AS). A total of 4907 data points on circulating protein expression were collected from a large-scale protein quantitative trait locus investigation involving 35,559 individuals. Using data from a Finnish study on AS as the outcome, the dataset comprised 166,144 individuals of European ancestry (1462 cases and 164,682 controls), and causal relationships were determined through bidirectional Mendelian randomization of two samples. Proteins were further validated and identified through single-cell expression analysis, certain cells showing enriched expression levels were detected, and possible treatment targets were optimized. Increased HERC5 expression predicted by genes was related to increased AS risk, whereas the expression of the remaining five circulating proteins, AIF1, CREB3L4, MLN, MRPL55, and SPAG11B, was negatively correlated with AS risk. For each increase in gene-predicted protein levels, the ORs of AS were 2.11 (95% CI 1.44-3.09) for HERC5, 0.14 (95% CI 0.05-0.41) for AIF1, 0.48 (95% CI 0.34-0.68) for CREB3L4, 0.54 (95% CI 0.42-0.68) for MLN, 0.23 (95% CI 0.13-0.38) for MRPL55, and 0.26 (95% CI 0.17-0.39) for SPAG11B. The hypothesis of a reverse causal relationship between these six circulating proteins and AS is not supported. Three of the six protein-coding genes were expressed in both the AS and healthy control groups, while CREB3L4, MLN, and SPAG11B were not detected. Increased levels of HERC5 predicted by genes are related to increased AS risk, whereas the levels of the remaining five circulating proteins, AIF1, CREB3L4, MLN, MRPL55, and SPAG11B, negatively correlate with AS risk. HERC5, AIF1, and MRPL55 are potential therapeutic targets for AS. This study advanced the field by employing a novel combination of proteomic range two-sample MR analysis and single-cell expression analysis to identify potential protein markers and therapeutic targets for AS. This approach enabled a comprehensive understanding of the causal relationships between circulating proteins and AS, which has not been extensively explored in previous studies.

Keywords: Ankylosing spondylitis; Mendelian randomization; Novel protein biomarkers; scRNA-seq.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Flowchart of the study design
Fig. 2
Fig. 2
The MR estimation of the causal effect of exposure (circulating proteins) on outcomes (ankylosing spondylitis) obtained through different MR methods is represented in the forest plot (MR, Mendelian randomization; OR, odds ratio; CI, confidence interval)
Fig. 3
Fig. 3
Volcano plot showing the results of MR of the circulating proteins
Fig. 4
Fig. 4
Single-cell sequencing was used to identify the protein-coding genes of the AS group and the healthy group and to verify the Mendelian randomization results of the proteome. A A total of 19 cell clusters and 11 cell types were identified in the AS group. B A total of 19 cell clusters and 11 cell types were identified in the healthy group. The expression of protein-coding genes in each cluster of the AS group (C, E) and healthy group (D, F)

References

    1. Braun J, Sieper J. Ankylosing spondylitis. Lancet. 2007;369(9570):1379–90. - PubMed
    1. Zhang X, Sun Z, Zhou A, Tao L, Chen Y, Shi X, et al. Association between infections and risk of ankylosing spondylitis: a systematic review and meta-analysis. Front Immunol. 2021;12:768741. - PMC - PubMed
    1. Hwang MC, Ridley L, Reveille JD. Ankylosing spondylitis risk factors: a systematic literature review. Clin Rheumatol. 2021;40(8):3079–93. - PMC - PubMed
    1. Song ZY, Yuan D, Zhang SX. Role of the microbiome and its metabolites in ankylosing spondylitis. Front Immunol. 2022;13:1010572. - PMC - PubMed
    1. Tavasolian F, Lively S, Pastrello C, Tang M, Lim M, Pacheco A, et al. Proteomic and genomic profiling of plasma exosomes from patients with ankylosing spondylitis. Ann Rheum Dis. 2023;82(11):1429–43. - PubMed