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Journal of Peking University (Health Sciences) ›› 2025, Vol. 57 ›› Issue (6): 1024-1031. doi: 10.19723/j.issn.1671-167X.2025.06.003

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Serum inter-alpha-trypsin inhibitor heavy chain H3 is identified as a potential biomarker for myopenia in patients with rheumatoid arthritis using proteomic profiling

Tao WU1, Jianzi LIN1, Yafeng ZHU2, Jianda MA1, Peiwen JIA1, Lijuan YANG1, jie PAN1, Yaowei ZOU1, Ying YANG1, Ye LU1, Lie DAI1,*()   

  1. 1. Department of Rheumatology and Immunology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China
    2. Basic and Translational Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China
  • Received:2025-08-14 Online:2025-12-18 Published:2025-10-24
  • Contact: Lie DAI
  • Supported by:
    National Natural Science Foundation of China(82471832); Guangzhou Science and Technology Joint Funding Project for University-Enterprise Collaboration(2024A03J0912); Guangzhou Municipal Science and Technology Project and Yat-sen Excellent Yong Scientists Fund(2023A03J0709); Yixian Clinical Research 5010 Program Project(SYS-5010-202407)

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Abstract:

Objective: To explore the serum biomarkers of myopenia in patients with rheumatoid arthritis (RA) via serum proteomic profiling. Methods: This cross-sectional study recruited active RA patients who either sustained non-myopenic or myopenia state over a 2-year follow-up period and unlabeled liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to analyze the serum proteomic profiles. Bioinformatics analyses were then applied to identify differentially expressed proteins between the two groups. Further validation cohort enrolled 102 RA patients (including 51 cases of non-myopenia group and 51 cases of myopenia group) and 51 healthy controls (HC) with age- and gender- matched propensity score at a 1 ∶ 1 ∶ 1 ratio. Enzyme-linked immunosorbent assay (ELISA) was used to verify the expression levels of the candidate protein. Multivariate logistic regression analysis was performed to identify baseline factors associated with myopenia in the RA patients. Results: Initial proteomic analysis of baseline serum samples from 9 non-myopenia RA patients and 10 myopenia RA patients identified 38 differentially expressed proteins. Among them, inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3) showed a significant upregulation in the myopenia group (log2FC=2.09) and was consistently detected across all the samples. Subsequent ELISA validation confirmed that the serum ITIH3 level in 102 RA patients was significantly higher than that in 51 HC [(119.4±79.7) mg/L vs. (42.3±16.6) mg/L, P < 0.001], in which both myopenia group and non-myopenia group of the RA patients showed higher levels of serum ITIH3 than the HC group (both P < 0.001). Importantly, the serum ITIH3 level in the 51 patients with myopenia were significantly higher than that in the 51 patients without myopenia [(148.1±94.7) mg/L vs. (90.8±46.6) mg/L, P < 0.001]. After adjustment for confounding covariates including gender, age, disease duration, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), radiological joint destruction and previous treatment, the multivariate Logistic regression analysis showed that the baseline serum ITIH3 level was an independent risk factor for myopenia in the RA patients (OR=1.024, 95%CI: 1.013-1.038, P < 0.001). Conclusion: This study identifies serum ITIH3 as a significant and independent risk factor for myopenia in patients with RA, which imply that ITIH3 might be a potential biomarker of myopenia. Further longitudinal large-sample multicenter validation is warranted to elucidate the precise role of ITIH3 in the pathophysiology of RA-associated myopenia and the clinical utility in risk stratification and management.

Key words: Rheumatoid arthritis, Myopenia, Proteomics, Biomarker, Inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3)

CLC Number: 

  • R593.22

Table 1

Comparisons of baseline characteristics of RA patients in serum LC-MS/MS analysis"

Items Non-myopenia RA patients (n=9) Myopenia RA patients (n=10) Statistics P
Female, n (%) 7(77.8) 8(80.0) χ2=0.000 >0.999
Age/years, $\bar x \pm s$ 45.1±9.5 40.0±10.0 t=1.139 0.271
ASMI/(kg/m2), $\bar x \pm s$ 6.50±0.55 5.17±0.62 t=4.932 ＜0.001
Disease duration/month, M (Q1, Q3) 8.0(5.5, 10.0) 10.0(1.0, 12.5) Z=-0.369 0.712
Active smoking, n (%) 0(0.0) 1(10.0) - >0.999*
CDAI, M (Q1, Q3) 19.0(14.5, 29.0) 22.5(11.8, 27.0) Z=-0.286 0.775

Figure 1

Serum LC-MS/MS and bioinformatics analysis of myopenia and non-mypoenia RA patients Serum protein profile analysis showing principal component analysis plot (A), DEPs volcano plot (B), DEPs heatmap (C), DEPs sample distribution plot (D) of myopenia and non-mypoenia RA patients. DEPs, differentially expressed proteins; PC, principal component; FC, fold change."

Table 2

Comparisons of baseline characteristics between RA patients and healthy controls"

Items HC(n=51) Non-myopenia RA patients (n=51) Myopenia RA patients (n=51) All RA patients(n=102) Statistics P
Female, n (%) 44 (86.3) 39(76.5) 42(82.4) 81 (79.4) χ2 =2.753a 0.252
Age/years, $\bar x \pm s$ 46.9±8.8 48.7±9.8 49.5±13.0 49.1±11.5 F=0.811a 0.446
ASMI/(kg/m2), $\bar x \pm s$ 6.31±0.73 6.81±0.67 5.23±0.63 6.0±1.0 F=72.335a < 0.001
Myopenia, n (%) 10 (19.6) 0(0.0) 51(100.0) 51 (50.0) - < 0.001b*
Disease duration/month, M(Q1, Q3) - 39 (6, 111) 65 (14, 133) 41 (10, 120) Z=-2.202c 0.028
Active smoking, n (%) - 7(13.7) 6(11.8) 13 (14.6) χ2=0.088c 0.767
Positive RF, n (%) - 38(74.5) 42(82.4) 80 (78.4) χ2=0.927c 0.336
Positive ACPA, n (%) - 37(72.5) 41(80.4) 78 (76.5) χ2=0.872c 0.350
28TJC, M (Q1, Q3) - 3 (1, 8) 4 (1, 7) 3 (1, 7) Z=-0.199c 0.842
28SJC, M (Q1, Q3) - 2 (1, 6) 2 (0, 5) 2 (1, 5) Z=-0.149c 0.882
PtGA/cm, M (Q1, Q3) - 4 (2, 7) 4 (3, 6) 4 (2, 6) Z=-0.236c 0.814
PrGA/cm, M (Q1, Q3) - 3 (2, 7) 4 (3, 6) 4 (2, 6) Z=-0.508c 0.611
Pain VAS/cm, M (Q1, Q3) - 3 (2, 7) 4 (2, 5) 4 (2, 5) Z=-0.784c 0.433
ESR/(mm/h), M (Q1, Q3) - 32 (19, 50) 49 (24, 77) 37 (21, 64) Z=-2.534c 0.011
CRP/(mg/L), M (Q1, Q3) - 5.9 (3.3, 10.6) 10.2 (3.3, 25.5) 6.8 (3.3, 17.9) Z=-1.581c 0.114
CDAI, M (Q1, Q3) - 13 (6, 28) 16 (9, 23) 14 (8, 24) Z=-0.378c 0.705
Active disease, n (%) 44 (86.3) 43(84.3) 87 (85.3) χ2=0.078c 0.780
HAQ-DI, M (Q1, Q3) - 0.25 (0.00, 1.00) 0.50 (0.13, 1.25) 0.38 (0.00, 1.06) Z=-0.892c 0.372
Physical dysfunction, n (%) 14 (27.5) 15(29.4) 29(28.4) χ2=0.048c 0.826
mTSS, M (Q1, Q3) - 5 (0, 32) 11 (3, 46) 8 (0, 36) Z=-1.564c 0.118
Radiological joint destruction, n (%) 19 (37.3) 27 (52.9) 46 (45.1) χ2=2.534c 0.111

Figure 2

Comparisons of baseline serum ITIH3 levels of RA patients and healthy controls A, the serum ITIH3 levels of RA patients and healthy controls were detected by ELISA; B, comparison of serum ITIH3 levels among myopenia/non-mypoenia RA patients and healthy controls. RA, rheumatoid arthritis; HC, healthy controls; ELISA, enzyme- linked immunosorbent assay; ITIH3, inter- alpha-trypsin inhibitor heavy chain 3."

Table 3

Logistic regression analysis of factors related to baseline myopenia in RA patients"

Items Univariate Multivariate1 Multivariate2
OR(95%CI) P OR(95%CI) P OR(95%CI) P
ITIH3 1.012 (1.005-1.019) < 0.001 1.018 (1.009-1.029) < 0.001 1.024 (1.013-1.038) < 0.001
Female 1.436 (0.548-3.875) 0.462 1.137 (0.215-6.436) 0.880
Age 1.006 (0.972-1.042) 0.721 1.002 (0.949-1.059) 0.939
Disease duration 1.004 (0.999-1.009) 0.112 1.000 (0.993-1.007) 0.977 1.000 (0.993-1.008) 0.960
Active smoking 0.813 (0.241-2.667) 0.731
Positive RF 1.596 (0.619-4.271) 0.335
Positive ACPA 1.551 (0.619-4.003) 0.350
28TJC 0.990 (0.918-1.065) 0.779
28SJC 0.961 (0.865-1.063) 0.442
PtGA 1.002 (0.874-1.150) 0.972
PrGA 1.010 (0.877-1.165) 0.886
Pain VAS 1.036 (0.885-1.215) 0.660
ESR 1.016 (1.003-1.031) 0.013 1.021 (1.000-1.045) 0.056 1.024 (0.999-1.052) 0.065
CRP 1.009 (0.995-1.026) 0.213 0.986 (0.959-1.015) 0.321 0.986 (0.954-1.022) 0.403
CDAI 0.995 (0.966-1.026) 0.761
HAQ-DI 1.039 (0.617-1.758) 0.884
Physical dysfunction 1.112 (0.449-2.771) 0.818
mTSS 1.005 (0.996-1.016) 0.289
Radiological joint destruction 1.945 (0.851-4.531) 0.115 1.435 (0.4595-4.463) 0.530 1.833 (0.521-6.576) 0.344
Previous treatment
Treatment naÏve 0.804 (0.316-2.013) 0.641 0.805 (0.052-16.06) 0.881
Glucocorticoids 1.314 (0.569-3.060) 0.522 3.126 (0.874-13.37) 0.097
csDMARDs 1.458 (0.545-4.013) 0.453 0.436 (0.040-5.478) 0.494
bDAMRDs/tsDMARDs 1.537 (0.243-12.12) 0.644 1.022 (0.099-10.94) 0.985
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