基于数据非依赖性采集定量蛋白质组学分析的原发性干燥综合征潜在唾液生物标志物研究

doi:10.24920/004338

Abstract

Objective As primary Sjögren’s syndrome (pSS) primarily affects the salivary glands, saliva can serve as an indicator of the glands’ pathophysiology and the disease’s status. This study aims to illustrate the salivary proteomic profiles of pSS patients and identify potential candidate biomarkers for diagnosis.

Methods The discovery set contained 49 samples (24 from pSS and 25 from age- and gender-matched healthy controls [HCs]) and the validation set included 25 samples (12 from pSS and 13 from HCs). Totally 36 pSS patients and 38 HCs were centrally randomized into the discovery set or to the validation set at a 2:1 ratio. Unstimulated whole saliva samples from pSS patients and HCs were analyzed using a data-independent acquisition (DIA) strategy on a 2D LC-HRMS/MS platform to reveal differential proteins. The crucial proteins were verified using DIA analysis and annotated using gene ontology (GO) and International Pharmaceutical Abstracts (IPA) analysis. A prediction model for SS was established using random forests.

Results A total of 1,963 proteins were discovered, and 136 proteins exhibited differential representation in pSS patients. The bioinformatic research indicated that these proteins were primarily linked to immunological functions, metabolism, and inflammation. A panel of 19 protein biomarkers was identified by ranking order based on P-value and random forest algorichm, and was validated as the predictive biomarkers exhibiting good performance with area under the curve (AUC) of 0.817 for discovery set and 0.882 for validation set.

Conclusions The candidate protein panel discovered may aid in pSS diagnosis. Salivary proteomic analysis is a promising non-invasive method for prognostic evaluation and early and precise treatments for pSS patients. DIA offers the best time efficiency and data dependability and may be a suitable option for future research on the salivary proteome.

Key words: primary Sjögren’s syndrome, salivia, proteomic analysis, mass spectrometry, diagnosis

Yi-Chao Tian, Chun-Lan Guo, Zhen Li, Xin You, Xiao-Yan Liu, Jin-Mei Su, Si-Jia Zhao, Yue Mu, Wei Sun, Qian Li. Data-Independent Acquisition-Based Quantitative Proteomic Analysis Reveals Potential Salivary Biomarkers of Primary Sjögren’s Syndrome[J].Chinese Medical Sciences Journal, 2024, 39(1): 19-28.

Figures/Tables 8

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References 34.

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Characteristics	pSS group		HCs group		t/X²	P value
Characteristics	Discovery (n=24)	Validation (n=12)	Discovery (n=25)	Validation (n=13)	t/X²	P value
Age, yrs, mean±SD	41.1±10.9	40.6±12.8	41.4±12.2	44.1±12.7	0.049	0.88
Sex, females [n(%)]	21(87.5)	10(83.3)	23 (92)	12 (92.3)	0.075	0.60
Anti-SSA/Ro antibody + [n(%)]	16(66.7)	9(75.0)	/	/	0.574	0.682
Anti-SSB/La antibody + [n(%)]	3(12.5)	1(8.3)	/	/	0.112	1
Immunoglobulin G + [n(%)]	12(50.0)	6(50.0)	/	/	0	1
Labial gland biopsy + [n(%)]	13(54.2)	9(75.0)	/	/	2.595	0.205

No.	Protein name	AUC	P value	Fold change
1	Q13217	0.86285	0.002438	2.0129
2	P01034	0.85764	0.006314	2.6949
3	P07711	0.85243	0.001923	1.831
4	P09958	0.85069	0.001031	1.8654
5	P28065	0.85069	7.72E-06	-1.2467
6	O43852	0.84201	6.80E-04	1.4389
7	O43505	0.83854	2.39E-04	1.4676
8	P25789	0.82812	9.41E-05	-1.276
9	Q9UBX7	0.81771	0.00464	1.3578
10	Q9NRJ3	0.81597	0.024021	1.4358
11	P35030	0.81424	0.001265	1.3919
12	P12109	0.8125	0.008958	1.3342
13	O75976	0.80903	6.50E-04	1.3292
14	Q92743	0.80035	0.46752	1.0645
15	P16870	0.7934	0.001147	1.3544
16	P13798	0.78646	5.01E-04	-1.0262
17	P01011	0.75347	0.018898	2.5295
18	P32320	0.74306	0.001919	-0.88055
19	P08670	0.73785	0.006534	-1.581

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