TY - JOUR
T1 - Investigation of diagnostic performance of five urinary cholesterol metabolites for Niemann-Pick disease type C
AU - Maekawa, Masamitsu
AU - Jinnoh, Isamu
AU - Narita, Aya
AU - Iida, Takashi
AU - Saigusa, Daisuke
AU - Iwahori, Anna
AU - Nittono, Hiroshi
AU - Okuyama, Torayuki
AU - Eto, Yoshikatsu
AU - Ohno, Kousaku
AU - Clayton, Peter T.
AU - Yamaguchi, Hiroaki
AU - Mano, Nariyasu
N1 - Funding Information:
This work was supported in part by Japan Society for the Promotion of Science KAKENHI Grants 16K20900 and 18K15699. Manuscript received 19 March 2019 and in revised form 30 September 2019. Published, JLR Papers in Press, October 4, 2019 DOI https://doi.org/10.1194/jlr.M093971
Publisher Copyright:
© 2019 American Society for Biochemistry and Molecular Biology Inc.. All rights reserved.
PY - 2019
Y1 - 2019
N2 - Niemann-Pick disease type C (NPC) is an autosomal recessive disorder characterized by progressive nervous degeneration. Because of the diversity of clinical symptoms and onset age, the diagnosis of this disease is difficult. Therefore, biomarker tests have attracted significant attention for earlier diagnostics. In this study, we developed a simultaneous analysis method for five urinary conjugated cholesterol metabolites, which are potential diagnostic biomarkers for a rapid, convenient, and noninvasive chemical diagnosis, using LC/MS/MS. By the method, their urinary concentrations were quantified and the NPC diagnostic performances were evaluated. The developed LC/MS/MS method showed high accuracy and satisfied all analytical method validation criteria. When the urine of healthy controls and patients with NPC was analyzed, three of five urinary conjugated cholesterol metabolite concentrations corrected by urinary creatinine were significantly higher in the patients with NPC. As a result of receiver operating characteristics analysis, these urinary metabolites might have excellent diagnostic marker performance. 3β-Sulfooxy-7β-hydroxy-5-cholenoic acid showed particularly excellent diagnostic performance with both 100% clinical sensitivity and specificity, suggesting that it is a useful NPC diagnostic marker. The urinary conjugated cholesterol metabolites exhibited high NPC diagnostic marker performance and could be used for NPC diagnosis. 2019 Maekawa et al.
AB - Niemann-Pick disease type C (NPC) is an autosomal recessive disorder characterized by progressive nervous degeneration. Because of the diversity of clinical symptoms and onset age, the diagnosis of this disease is difficult. Therefore, biomarker tests have attracted significant attention for earlier diagnostics. In this study, we developed a simultaneous analysis method for five urinary conjugated cholesterol metabolites, which are potential diagnostic biomarkers for a rapid, convenient, and noninvasive chemical diagnosis, using LC/MS/MS. By the method, their urinary concentrations were quantified and the NPC diagnostic performances were evaluated. The developed LC/MS/MS method showed high accuracy and satisfied all analytical method validation criteria. When the urine of healthy controls and patients with NPC was analyzed, three of five urinary conjugated cholesterol metabolite concentrations corrected by urinary creatinine were significantly higher in the patients with NPC. As a result of receiver operating characteristics analysis, these urinary metabolites might have excellent diagnostic marker performance. 3β-Sulfooxy-7β-hydroxy-5-cholenoic acid showed particularly excellent diagnostic performance with both 100% clinical sensitivity and specificity, suggesting that it is a useful NPC diagnostic marker. The urinary conjugated cholesterol metabolites exhibited high NPC diagnostic marker performance and could be used for NPC diagnosis. 2019 Maekawa et al.
KW - Liquid chromatography/tandem mass spectrometry
KW - Niemann-Pick disease type C
KW - Urinary biomarkers
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U2 - 10.1194/jlr.M093971
DO - 10.1194/jlr.M093971
M3 - Article
C2 - 31586016
AN - SCOPUS:85075962624
SN - 0022-2275
VL - 60
SP - 2074
EP - 2081
JO - Journal of Lipid Research
JF - Journal of Lipid Research
IS - 12
ER -