Related Experiment Video
Updated: Nov 13, 2025
Fingerprinting Cardiolipin in Leukocytes by Mass Spectrometry for a Rapid Diagnosis of Barth Syndrome
Published on: March 23, 2022
Comparative proteomics analysis for identifying the lipid metabolism related pathways in patients with Klippel-Feil
Ziquan Li1,2, Cong Zhang3, Bintao Qiu4
1Department of Orthopedic Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Background:
Klippel-Feil syndrome (KFS) represents the rare and complex deformity characterized by congenital defects in the formation or segmentation of the cervical vertebrae. There is a wide gap in understanding the detailed mechanisms of KFS because of its rarity, heterogeneity, small pedigrees, and the broad spectrum of anomalies.
Methods:
We recruited eight patients of Chinese Han ethnicity with KFS, five patients with congenital scoliosis (CS) who presented with congenital fusion of the thoracic or lumbar spine and without known syndrome or cervical deformity, and seven healthy controls. Proteomic analysis by data-independent acquisition (DIA) was performed to identify the differential proteome among the three matched groups and the data were analyzed by bioinformatics tools including Gene Ontology (GO) categories and Ingenuity Pathway Analysis (IPA) database, to explore differentially abundant proteins (DAPs) and canonical pathways involved in the pathogenesis of KFS.
Results:
A total of 49 DAPs were detected between KFS patients and the controls, and moreover, 192 DAPs were identified between patients with KFS and patients with CS. Fifteen DAPs that were common in both comparisons were considered as candidate biomarkers for KFS, including membrane primary amine oxidase, noelin, galectin-3-binding protein, cadherin-5, glyceraldehyde-3-phosphate dehydrogenase, peroxiredoxin-1, CD109 antigen, and eight immunoglobulins. Furthermore, the same significant canonical pathways of LXR/RXR activation and FXR/RXR activation were observed in both comparisons. Seven of DAPs were apolipoproteins related to these pathways that are involved in lipid metabolism.
Conclusions:
This study provides the first proteomic profile for understanding the pathogenesis and identifying predictive biomarkers of KFS. We detected 15 DAPs that were common in both comparisons as candidate predictive biomarkers of KFS. The lipid metabolism-related canonical pathways of LXR/RXR and FXR/RXR activation together with seven differentially abundant apolipoproteins may play significant roles in the etiology of KFS and provide possible pathogenesis correlation between KFS and CS.
