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Characterizing plasma phospholipid fatty acid profiles of polycystic ovary syndrome patients with and without insulin resistance using GC-MS and chemometrics approach
Zhang X.-J.2; Huang L.-L.1; Su H.2; Chen Y.-X.1; Huang J.1; He C.2; Li P.2; Yang D.-Z.1; Wan J.-B.2
2014
Source PublicationJournal of Pharmaceutical and Biomedical Analysis
ISSN1873264X 07317085
Volume95Pages:85-92
Abstract

Polycystic ovary syndrome (PCOS), a heterogeneous endocrine and metabolic disorder, is the leading cause of infertility in women of reproductive age. Insulin resistance (IR) occurs in 50-70% of women with PCOS. In this study, we aimed to characterize the plasma phospholipid fatty acid profile for PCOS patients with and without IR, as well as for the early prognosis of PCOS and its IR complication. A gas chromatography-mass spectrometry (GC-MS) followed by multivariate statistical analysis was established to globally characterize the phospholipid fatty acid profiles in plasma from non-IR PCOS, IR PCOS, and eligible healthy controls, and subsequently discovered fatty acid biomarkers. A total of 22 fatty acids were identified and quantified. Their proportions varied among three groups, suggesting each group has its own fatty acid pattern. Orthogonal partial least squares discriminant analysis (OPLS-DA) according to their fatty acid profiles showed that 29 tested samples could be clearly differentiated according to groups. More importantly, nervonic acid (C24:1 n-9) and dihomo-γ-linolenic acid (C20:3 n-6) were identified as the potential fatty acid biomarkers of PCOS and its IR complication, respectively, for their most contribution to group separation. Pearson correlation analysis indicated that C24:1 n-9 and C20:3 n-6 were well correlated with clinical characteristics of PCOS and IR indicators, respectively. These findings demonstrated that GC-MS-based plasma phospholipid fatty acid profile might provide a complementary approach for clinical diagnosis of PCOS and its IR complication. © 2014 Elsevier B.V.

KeywordPolycystic Ovary Syndrome Insulin Resistance Plasma Phospholipid Fatty Acid Profile Gas Chromatography-mass Spectrometry Multivariate Statistical Analysis
DOI10.1016/j.jpba.2014.02.014
URLView the original
Indexed BySCIE
WOS Research AreaChemistry ; Pharmacology & Pharmacy
WOS SubjectChemistry, Analytical ; Pharmacology & Pharmacy
WOS IDWOS:000336558600011
Scopus ID2-s2.0-84896339136
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Citation statistics
Document TypeJournal article
CollectionInstitute of Chinese Medical Sciences
Corresponding AuthorYang D.-Z.; Wan J.-B.
Affiliation1.Sun Yat-Sen University
2.Universidade de Macau
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Zhang X.-J.,Huang L.-L.,Su H.,et al. Characterizing plasma phospholipid fatty acid profiles of polycystic ovary syndrome patients with and without insulin resistance using GC-MS and chemometrics approach[J]. Journal of Pharmaceutical and Biomedical Analysis, 2014, 95, 85-92.
APA Zhang X.-J.., Huang L.-L.., Su H.., Chen Y.-X.., Huang J.., He C.., Li P.., Yang D.-Z.., & Wan J.-B. (2014). Characterizing plasma phospholipid fatty acid profiles of polycystic ovary syndrome patients with and without insulin resistance using GC-MS and chemometrics approach. Journal of Pharmaceutical and Biomedical Analysis, 95, 85-92.
MLA Zhang X.-J.,et al."Characterizing plasma phospholipid fatty acid profiles of polycystic ovary syndrome patients with and without insulin resistance using GC-MS and chemometrics approach".Journal of Pharmaceutical and Biomedical Analysis 95(2014):85-92.
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