Investigative ophthalmology & visual science · 2026
Deep Proteomic Analysis With Machine Learning Identifies Aqueous Humor Biomarkers of ADAMTSL4-associated Congenital Ectopia Lentis.
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Chen Xinyao, Shen Xin, Jia Wannan, Wang Yalei, Huo Qiuyi, Xiao Yanbo, Zhang Yulin, Li Linzhao, Gao Xuqing, A Guangqi, Yang Fengjing, Chen Yilin, Chen Tianhui, Zhang Min, Yang Jin, Pi Yan, Chen Zexu, Jiang Yongxiang
Аннотация
PURPOSE: To systematically characterize aqueous humor (AH) proteomic alterations in ADAMTSL4-associated congenital ectopia lentis (CEL) and to identify disease-related molecular features.
METHODS: Mass spectrometry-based deep data-independent acquisition (deep DIA) proteomics was employed to profile AH proteomes from pediatric ADAMTSL4-associated CEL patients. Differentially expressed proteins (DEPs) were analyzed using functional enrichment and gene set enrichment analysis. Weighted gene co-expression network analysis (WGCNA) identified disease-related protein modules. Candidate biomarkers were prioritized using machine learning, followed by technical confirmation using intelligent parallel reaction monitoring (iPRM) and clinical correlation analysis. Transcriptional changes of selected candidates were assessed by quantitative PCR in ADAMTSL4-knockdown human retinal pigment epithelial cells, human fibroblasts, and adamtsl4-knockout zebrafish.
RESULTS: Deep DIA quantified 1865 AH proteins, among which 265 DEPs were identified and enriched in extracellular matrix (ECM) remodeling, complement-coagulation cascades, and lipid transport pathways. Expression-based stratification revealed tier-specific functional patterns. WGCNA identified modules significantly associated with ocular phenotypes. Machine learning prioritized six candidate biomarkers (ADAMTS3, APOC2, AMBP, KLKB1, SDC4, and ENPP2), of which APOC2, AMBP, KLKB1, and ENPP2 achieved targeted confirmation by iPRM; APOC2, KLKB1, and ENPP2 were correlated with axial length or choroidal thickness. In ADAMTSL4-knockdown cells, ENPP2, MYDGF, and CA2 were downregulated and LCAT was upregulated, consistent with proteomic findings. MYDGF further showed a concordant directional change in the zebrafish model.
CONCLUSIONS: This study established a high-resolution AH proteomic profile of ADAMTSL4-associated CEL, revealing coordinated molecular alterations in ECM disruption, complement-coagulation activation, and dysregulated lipid homeostasis, providing integrated molecular insights and candidate molecular features for understanding this rare ocular disorder.
METHODS: Mass spectrometry-based deep data-independent acquisition (deep DIA) proteomics was employed to profile AH proteomes from pediatric ADAMTSL4-associated CEL patients. Differentially expressed proteins (DEPs) were analyzed using functional enrichment and gene set enrichment analysis. Weighted gene co-expression network analysis (WGCNA) identified disease-related protein modules. Candidate biomarkers were prioritized using machine learning, followed by technical confirmation using intelligent parallel reaction monitoring (iPRM) and clinical correlation analysis. Transcriptional changes of selected candidates were assessed by quantitative PCR in ADAMTSL4-knockdown human retinal pigment epithelial cells, human fibroblasts, and adamtsl4-knockout zebrafish.
RESULTS: Deep DIA quantified 1865 AH proteins, among which 265 DEPs were identified and enriched in extracellular matrix (ECM) remodeling, complement-coagulation cascades, and lipid transport pathways. Expression-based stratification revealed tier-specific functional patterns. WGCNA identified modules significantly associated with ocular phenotypes. Machine learning prioritized six candidate biomarkers (ADAMTS3, APOC2, AMBP, KLKB1, SDC4, and ENPP2), of which APOC2, AMBP, KLKB1, and ENPP2 achieved targeted confirmation by iPRM; APOC2, KLKB1, and ENPP2 were correlated with axial length or choroidal thickness. In ADAMTSL4-knockdown cells, ENPP2, MYDGF, and CA2 were downregulated and LCAT was upregulated, consistent with proteomic findings. MYDGF further showed a concordant directional change in the zebrafish model.
CONCLUSIONS: This study established a high-resolution AH proteomic profile of ADAMTSL4-associated CEL, revealing coordinated molecular alterations in ECM disruption, complement-coagulation activation, and dysregulated lipid homeostasis, providing integrated molecular insights and candidate molecular features for understanding this rare ocular disorder.