Candidate biomarker identification for blood stasis syndrome among coronary artery disease patients using the Olink proteomics platform

doi:10.19852/j.cnki.jtcm.2026.02.020

Journal of Traditional Chinese Medicine ›› 2026, Vol. 46 ›› Issue (2): 490-500.DOI: 10.19852/j.cnki.jtcm.2026.02.020

• Original Articles • Previous Articles Next Articles

Candidate biomarker identification for blood stasis syndrome among coronary artery disease patients using the Olink proteomics platform

LI Hongzheng¹^,², LIN Guosheng³, PENG Yuxuan¹, Churov Alexey Viktorovich⁴, YANG Wenwen⁵, WANG Jie¹, LU Jieming¹, LIAO Feifei⁶, YU Ruotong¹, WEI Yue¹, ZHAO Zhiru¹, LU Aimei⁶, LI Peng⁷, SHEN Aling³, LONG Linzi¹(), QU Hua¹, FU Changgeng¹()

¹ National Clinical Research Center for Chinese Medicine Cardiology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing 100091, China
² Postdoctoral Research Center, Guang’an Men Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
³ Academy of Integrative Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
⁴ Institute of General Pathology and Pathophysiology, Pirogov Russian National Research Medical University, Moscow 125315, Russia
⁵ Department of Cardiology, Shaanxi Provincial Hospital of Chinese Medicine, Xi’an 710003, China
⁶ Academy of Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China
⁷ Department of Cardiology I, TCM Hospital Affiliated to Xinjiang Medical University, Urumqi 830000, China

Received:2025-01-15 Accepted:2025-07-02 Online:2026-04-15 Published:2026-04-04
Contact: Prof. FU Changgeng, National Clinical Research Center for Chinese Medicine Cardiology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing 100091, China. fucgbs@163.com; Dr. LONG Linzi, National Clinical Research Center for Chinese Medicine Cardiology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing 100091, China. qixiang830803@163.com; Telephone: +86-15101038490
Supported by:
Formulation of International Diagnostic Criteria for Blood Stasis Syndrome in Coronary Heart Disease and Screening of Specific Protein Biomarkers(CMC2022010);Screening of Inflammatory Biomarkers and Analysis of Perivascular Adipose Tissue Characteristics in Patients with Blood Stasis Syndrome due to Coronary Heart Disease(GWJJMB202510021048);Comprehensive Investigation into Diagnostic Criteria and a Risk Prediction Model for Coronary Heart Disease with "Dryness-Blood Stasis Complex" Syndrome in Xinjiang(2022E02114)

1. .docx(2655KB)

Abstract

Abstract:

OBJECTIVE: To identify candidate biomarkers of blood stasis syndrome (BSS) associated with coronary artery disease (CAD) and explore the underlying inflammatory mechanisms.

Methods: Using the Olink Target 96 Inflammation panel, we identified plasma proteins in a group of 88 patients comprised of healthy controls (HCs), those with CAD and BSS (CAD-BSS), those with CAD without BSS (CAD-non-BSS), and those with BSS without CAD (non-CAD-BSS) (n = 22 in each group). Protein molecules that were specifically expressed in CAD or BSS were identified by differential expression analyses. Subsequently, potential protein biomarkers were identified using least absolute shrinkage and selection operator regression to enable CAD and BSS differentiation. The potential functional mechanisms of identified proteins were then determined by Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses.

RESULTS: Patients with CAD had 31/92 upregulated and 4/92 downregulated proteins compared with those without. Chemokine (C-C motif) ligand 11 (CCL11), CUB domain-containing protein 1, hepatocyte growth factor, sirtuin 2 (SIRT2), eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1), CCL25, and tumor necrosis factor (TNF) showed the strongest upregulation (all P <0.0001). Patients with BSS had 8/92 downregulated proteins, specifically CCL28, CCL11, cystatin D, STAM-binding protein, 4E-BP1, matrix metalloproteinase-10, SIRT2, and monocyte chemotactic protein 4, compared with those without (all P < 0.05). The CAD-BSS group had one interleukin-17 (IL-17) upregulated and 10/92 downregulated proteins compared with the CAD-non-BSS group. When compared with the non-CAD-BSS group, the CAD-BSS group had 8 upregulated proteins but only 2 downregulated proteins, namely interleukin-10 receptor subunit alpha (IL-10RA) and TNF-related activation-induced cytokine (both P < 0.05). Totally 10 proteins were identified as potential candidate biomarkers of BSS in CAD patients. After least absolute shrinkage and selection operator regression analysis, two proteins that distinguished between BSS and non-BSS individuals among CAD patients were identified (SIRT2 and 4E-BP1). These proteins are primarily associated with the mechanistic target of rapamycin signaling pathway, which regulates inflammation and oxidative stress.

CONCLUSIONS: Results suggest that the inflammatory response and mechanistic target of rapamycin signaling pathway participate in CAD and BSS development, and that SIRT2 and 4E-BP1 are prospective protein biomarkers for patients with CAD and BSS.

Key words: coronary artery disease, inflammation, blood stasis syndrome, hepatocyte growth factor, sirtuin 2, eukaryotic translation initiation factor 4E-binding protein 1, Olink platform

LI Hongzheng, LIN Guosheng, PENG Yuxuan, Churov Alexey Viktorovich, YANG Wenwen, WANG Jie, LU Jieming, LIAO Feifei, YU Ruotong, WEI Yue, ZHAO Zhiru, LU Aimei, LI Peng, SHEN Aling, LONG Linzi, QU Hua, FU Changgeng. Candidate biomarker identification for blood stasis syndrome among coronary artery disease patients using the Olink proteomics platform[J]. Journal of Traditional Chinese Medicine, 2026, 46(2): 490-500.

Figures/Tables 5

Table 1 Basic clinical information of all patients ($ \bar{x} \pm s$)

Item	CAD-BSS (n = 22)	CAD-non-BSS (n = 22)	Non-CAD-BSS (n = 22)	HC (n = 22)	P value
Age (years)	61.32±15.88	71.05±7.69	52.05±11.45	54.91±11.04	<0.001
Gender (M/F, n)	13/9	12/10	6/16	12/10	-
BMI (kg/m²)	24.47±2.91	23.35±3.08	23.46±2.70	25.44±3.99	0.292
SBP (mm Hg)	140.09±17.56	131.64±17.21	133.14±15.82	129.14±12.96	0.221
DBP (mm Hg)	78.59±9.79	78.59±10.93	84.32±13.91	84.86±8.45	0.106
Hypertension [n (%)]	17 (77.27)	15 (68.18)	5 (22.73)	9 (40.91)	-
T2DM [n (%)]	7 (31.82)	10 (45.45)	4 (18.18)	1 (4.55)	-
Stroke [n (%)]	2 (9.09)	4 (18.18)	0 (0.00)	1 (4.55)	-
Hyperlipidemia [n (%)]	3 (13.64)	3 (13.64)	1 (4.55)	2 (9.09)	-
Antilaminate [n (%)]	8 (36.36)	5 (22.73)	2 (9.09)	1 (4.55)	-
TG (mmol/L)	1.17±0.51	1.35±1.06	1.09±0.65	1.47±0.60	0.163
TCHO (mmol/L)	3.71±0.89	3.62±0.85	4.33±1.41	4.41±1.21	0.005
LDL-C (mmol/L)	2.24±0.83	2.18±0.89	2.90±0.94	2.98±0.96	0.003
HDL-C (mmol/L)	1.19±0.27	1.13±0.29	1.34±0.32	1.07±0.32	0.049
ApoA-1 (mg/L)	1.28±0.13	1.25±0.15	1.24±0.15	1.16±0.12	0.030
ApoA (mg/dL)	17.80±20.61	26.95±27.35	10.53±19.94	6.93±12.56	<0.001
PT (s)	11.37±0.70	11.60±0.78	11.26±0.70	11.25±0.47	0.219
PTT (%)	101.95±6.79	99.81±7.80	103.00±6.96	103.14±5.17	0.219
INR (%)	0.96±0.06	0.98±0.07	0.95±0.06	0.95±0.04	0.239
APTT (s)	27.37±1.92	27.72±1.76	27.11±2.23	28.65±1.79	0.024
FIB (g/L)	3.13±0.74	3.16±0.86	3.62±3.27	2.88±0.58	0.461
TT (s)	16.86±1.23	18.54±12.48	16.01±3.37	17.60±0.89	0.007
RBC (×10¹²/L)	4.50±0.74	4.23±0.56	4.32±0.64	4.79±0.57	0.041
PLT (×10⁹/L)	230.41±54.63	202.27±60.44	239.95±76.80	233.77±43.82	0.057
HBG (g/L)	135.23±16.41	131.50±17.65	130.91±21.09	147.91±15.61	0.015
PCT (%)	0.24±0.05	0.22±0.06	0.25±0.06	0.24±0.05	0.415
WBC (×10⁹/L)	6.50±2.19	6.45±1.36	5.48±1.63	5.96±1.61	0.117
NEUT (×10⁹/L)	4.44±1.61	4.29±1.35	3.36±1.33	3.51±1.34	0.027
LYMP (×10⁹/L)	1.55±0.76	1.70±0.50	1.66±0.45	2.00±0.51	0.013
Score of BSS (scores)	3.50±1.41	0.00±0.00	3.59±1.62	0.00±0.00	<0.001

Table 1 Basic clinical information of all patients ($ \bar{x} \pm s$)

Item	CAD-BSS (n = 22)	CAD-non-BSS (n = 22)	Non-CAD-BSS (n = 22)	HC (n = 22)	P value
Age (years)	61.32±15.88	71.05±7.69	52.05±11.45	54.91±11.04	<0.001
Gender (M/F, n)	13/9	12/10	6/16	12/10	-
BMI (kg/m²)	24.47±2.91	23.35±3.08	23.46±2.70	25.44±3.99	0.292
SBP (mm Hg)	140.09±17.56	131.64±17.21	133.14±15.82	129.14±12.96	0.221
DBP (mm Hg)	78.59±9.79	78.59±10.93	84.32±13.91	84.86±8.45	0.106
Hypertension [n (%)]	17 (77.27)	15 (68.18)	5 (22.73)	9 (40.91)	-
T2DM [n (%)]	7 (31.82)	10 (45.45)	4 (18.18)	1 (4.55)	-
Stroke [n (%)]	2 (9.09)	4 (18.18)	0 (0.00)	1 (4.55)	-
Hyperlipidemia [n (%)]	3 (13.64)	3 (13.64)	1 (4.55)	2 (9.09)	-
Antilaminate [n (%)]	8 (36.36)	5 (22.73)	2 (9.09)	1 (4.55)	-
TG (mmol/L)	1.17±0.51	1.35±1.06	1.09±0.65	1.47±0.60	0.163
TCHO (mmol/L)	3.71±0.89	3.62±0.85	4.33±1.41	4.41±1.21	0.005
LDL-C (mmol/L)	2.24±0.83	2.18±0.89	2.90±0.94	2.98±0.96	0.003
HDL-C (mmol/L)	1.19±0.27	1.13±0.29	1.34±0.32	1.07±0.32	0.049
ApoA-1 (mg/L)	1.28±0.13	1.25±0.15	1.24±0.15	1.16±0.12	0.030
ApoA (mg/dL)	17.80±20.61	26.95±27.35	10.53±19.94	6.93±12.56	<0.001
PT (s)	11.37±0.70	11.60±0.78	11.26±0.70	11.25±0.47	0.219
PTT (%)	101.95±6.79	99.81±7.80	103.00±6.96	103.14±5.17	0.219
INR (%)	0.96±0.06	0.98±0.07	0.95±0.06	0.95±0.04	0.239
APTT (s)	27.37±1.92	27.72±1.76	27.11±2.23	28.65±1.79	0.024
FIB (g/L)	3.13±0.74	3.16±0.86	3.62±3.27	2.88±0.58	0.461
TT (s)	16.86±1.23	18.54±12.48	16.01±3.37	17.60±0.89	0.007
RBC (×10¹²/L)	4.50±0.74	4.23±0.56	4.32±0.64	4.79±0.57	0.041
PLT (×10⁹/L)	230.41±54.63	202.27±60.44	239.95±76.80	233.77±43.82	0.057
HBG (g/L)	135.23±16.41	131.50±17.65	130.91±21.09	147.91±15.61	0.015
PCT (%)	0.24±0.05	0.22±0.06	0.25±0.06	0.24±0.05	0.415
WBC (×10⁹/L)	6.50±2.19	6.45±1.36	5.48±1.63	5.96±1.61	0.117
NEUT (×10⁹/L)	4.44±1.61	4.29±1.35	3.36±1.33	3.51±1.34	0.027
LYMP (×10⁹/L)	1.55±0.76	1.70±0.50	1.66±0.45	2.00±0.51	0.013
Score of BSS (scores)	3.50±1.41	0.00±0.00	3.59±1.62	0.00±0.00	<0.001

Figure 1 Identification of differentially expressed proteins in the CAD and non-CAD groups A: volcano plot of differentially expressed proteins in the CAD groups compared with the non-CAD groups; B: top 30 of GO enrichment; C: top 30 of pathway enrichment; D: COG classification of the differentially expressed proteins.CAD: coronary artery disease; GO: Geno Ontology; COG: clusters of orthologous groups; CCL: CC chemokine ligand; 4E-BP1: 4E-binding protein 1; CDCP1: CUB domain-containing protein 1; SIRT2: sirtuin 2; HGP: SLC25A16, solute carrier family 25 member 16; TNF: tumor necrosis factor; CXCL9: C-X-C motif chemokine ligand 9; TRAIL: TNF-related apoptosis-inducing ligand; TRANCE: TNF-related activation-induced cytokine; IL: interleukin; Beta-NGF: Beta nerve growth factor.

Figure 2 Identification of differentially expressed proteins in the CAD-BSS and CAD-non-BSS groups A: volcano plot of differentially expressed proteins in the CAD-BSS group compared with the CAD-non-BSS group; B: GO enrichment analysis of the differentially expressed proteins; C: pathway enrichment analysis of the differentially expressed proteins; D: COG classification of the differentially expressed protein. CAD: coronary artery disease; BSS: blood stasis syndrome; GO: Geno Ontology; COG: clusters of orthologous groups; CCL: CC chemokine ligand; CST5: cystatin D; STAMBP: STAM binding protein; SIRT2: sirtuin 2; MMP-10: matrix metalloproteinase 10; MCP-4: monocyte chemoattractant protein 4; IL: interleukin.

Figure 3 Identification of differentially expressed proteins in the CAD-BSS and non-CAD-BSS groups A: volcano plot of differentially expressed proteins in the CAD-BSS group compared with the non-CAD-BSS group; B: GO enrichment analysis of the differentially expressed proteins; C: pathway enrichment analysis of the differentially expressed proteins; D: COG classification of the differentially expressed protein. CAD: coronary artery disease; BSS: blood stasis syndrome; GO: Geno Ontology; COG: clusters of orthologous groups; 4E-BP1: 4E-binding protein 1; CASP-8: caspase-8; CCL: CC chemokine ligand; CDCP1: CUB domain-containing protein 1; IL-10RA: interleukin-10 receptor subunit alpha; MCP-4: monocyte chemoattractant protein 4; SIRT2: sirtuin 2; STAMBP: STAM binding protein; TRANCE: TNF-related activation-induced cytokine.

Figure 4 Identification of differentially expressed proteins between the HC, CAD-BSS, non-CAD-BSS, and CAD-non-BSS groups A: venn diagram of differentially expressed proteins in the four groups; B: LASSO regression analysis of the five proteins identified according to the presence/absence of a CAD diagnosis; C: LASSO regression analysis of the five proteins identified according to BSS scores; D: correlation analysis of the expression of the identified proteins with commonly used clinical indicators; E: the protein-protein interactional network of identified proteins, constructed according to the GeneMan database. CAD: coronary artery disease; BSS: blood stasis syndrome; 4E-BP1: 4e-binding protein 1; BMI: body mass index; BUB1: budding uninhibited by benzimidazoles 1; CDC20: cell division cycle 20; EIF4E: eukaryotic translation initiation factor 4e; EIF4EBP1: eukaryotic translation initiation factor 4e binding protein 1; FZR1: fizzy and cell division cycle 20 related 1; GARS1: glycyl-trna synthetase 1; HAT1: histone acetyltransferase 1; HDL-C: high-density lipoprotein cholesterol; HOXA10: homeobox a10; LDL-C: low-density lipoprotein cholesterol; MAPKAPK5: mapk activated protein kinase 5; MLST8: mtor associated protein, lst8 homolog; MTOR: mechanistic target of rapamycin; RHEB: ras homolog, mtorc1 binding; RPTOR: regulatory associated protein of mtor complex 1; SIRT: sirtuin; TACO1: translational activator of cytochrome c oxidase I; TCHO: total cholesterol; TG: triglyceride; TUBA1B: tubulin alpha 1b; TUBB2A: tubulin beta 2a class IIa; WBC: white blood cell count.

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Candidate biomarker identification for blood stasis syndrome among coronary artery disease patients using the Olink proteomics platform

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