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Updated: Jul 15, 2025

A High Throughput, Multiplexed and Targeted Proteomic CSF Assay to Quantify Neurodegenerative Biomarkers and Apolipoprotein E Isoforms Status
Published on: October 20, 2016
Cerebrospinal Fluid Metabolomic Pattern of Different Pituitary Stalk Lesions
Linjie Wang1, Xiaoxue Chen1,2, Xiaoyan Liu3
1Department of Endocrinology, Key Laboratory of Endocrinology of National Health and Family Planning Commission, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China.
Objective:
To describe the cerebrospinal fluid (CSF) metabolomic pattern of pituitary stalk lesions.
Methods:
CSF was collected from patients with different pituitary stalk lesions treated at Peking Union Medical College Hospital: germ cell tumor (GCT, n = 27); hypophysitis (n = 10); and Langerhans cell histiocytosis (LCH) or Erdheim-Chester disease (ECD) (LCH + ECD, n = 10). The CSF metabolome profiles were characterized by liquid chromatography-mass spectrometry (LC-MS).
Results:
There were 44 metabolites that significantly differed between patients with GCT and those with hypophysitis (P < .05). Between patients with GCT with CSF level of beta subunit of human chorionic gonadotrophin (β-hCG) < 5 mIU/mL and those with hypophysitis, there were 15 differential metabolites (P < .05, fold change > 1.5 or < 1/1.5). All of the metabolites had an area under the curve (AUC) above 0.7. There were 9 metabolites that significantly differed between patients with GCT and those with LCH + ECD (P < .05) and 7 metabolites had significant differences between GCT (CSF β-hCG < 5 mIU/mL) and LCH + ECD (P < .05, fold change > 1.5 or < 1/1.5). We found 6 metabolites that were significantly different between patients with hypophysitis and those with LCH + ECD (P < .05) and 5 of these had fold change more than 1.5 or less than 1/1.5. Three metabolites, 5-deoxydiplosporin, cloversaponin I, and phytosphingosine, showed excellent capabilities to differentiate the 3 disease categories. Furthermore, we identified 67 metabolites associated with clinical test results (ρ > 0.2, P < .05) and 29 metabolites showed strong correlation (ρ > 0.4, P < .05).
Conclusion:
Our study is the first to systematically investigate the metabolomics of CSF in different pituitary stalk lesions. CSF metabolomics is a useful strategy for biomarker discovery.

