Lipidomic analysis of plasma samples from women with polycystic ovary syndrome
Abstract Polycystic ovary syndrome (PCOS) is a common disorder affecting between 5 and 18 % of females of reproductive age and can be diagnosed based on a combination of clinical, ultrasound and biochemical features, none of which on its own is diagnostic. A lipidomic approach using liquid chromatog...
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| Format: | Article |
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Springer
2015
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| Online Access: | https://eprints.nottingham.ac.uk/37979/ |
| _version_ | 1848795573681913856 |
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| author | Haoula, Zeina Ravipati, Srinivasarao Stekel, Dov J. Ortori, Catharine A. Hodgman, Charlie Daykin, Clare Raine-Fenning, Nick Barrett, David A. Atiomo, William |
| author_facet | Haoula, Zeina Ravipati, Srinivasarao Stekel, Dov J. Ortori, Catharine A. Hodgman, Charlie Daykin, Clare Raine-Fenning, Nick Barrett, David A. Atiomo, William |
| author_sort | Haoula, Zeina |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Abstract Polycystic ovary syndrome (PCOS) is a common disorder affecting between 5 and 18 % of females of reproductive age and can be diagnosed based on a combination of clinical, ultrasound and biochemical features, none of which on its own is diagnostic. A lipidomic approach using liquid chromatography coupled with accurate mass high-resolution mass-spectrometry (LCHRMS) was used to investigate if there were any differences in plasma lipidomic profiles in women with PCOS compared with control women at different stages of menstrual cycle. Plasma samples from 40 women with PCOS and 40 controls aged between 18 and 40 years were analysed in combination with multivariate statistical analyses. Multivariate data analysis (LASSO regression and OPLSDA) of the sample lipidomics datasets showed a weak prediction model for PCOS versus control samples from the follicular and mid-cycle phases of the menstrual cycle, but a stronger model (specificity 85 % and sensitivity 95 %) for PCOS versus the luteal phase menstrual cycle controls. The PCOS vs luteal phase model showed increased levels of plasma triglycerides and sphingomyelins and decreased levels of lysophosphatidylcholines and phosphatidylethanolamines in PCOS women compared with controls. Lipid biomarkers of PCOS were tentatively identified which may be useful in distinguishing PCOS from controls especially when performed during the menstrual cycle luteal phase. |
| first_indexed | 2025-11-14T19:34:14Z |
| format | Article |
| id | nottingham-37979 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:34:14Z |
| publishDate | 2015 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-379792020-05-04T17:09:33Z https://eprints.nottingham.ac.uk/37979/ Lipidomic analysis of plasma samples from women with polycystic ovary syndrome Haoula, Zeina Ravipati, Srinivasarao Stekel, Dov J. Ortori, Catharine A. Hodgman, Charlie Daykin, Clare Raine-Fenning, Nick Barrett, David A. Atiomo, William Abstract Polycystic ovary syndrome (PCOS) is a common disorder affecting between 5 and 18 % of females of reproductive age and can be diagnosed based on a combination of clinical, ultrasound and biochemical features, none of which on its own is diagnostic. A lipidomic approach using liquid chromatography coupled with accurate mass high-resolution mass-spectrometry (LCHRMS) was used to investigate if there were any differences in plasma lipidomic profiles in women with PCOS compared with control women at different stages of menstrual cycle. Plasma samples from 40 women with PCOS and 40 controls aged between 18 and 40 years were analysed in combination with multivariate statistical analyses. Multivariate data analysis (LASSO regression and OPLSDA) of the sample lipidomics datasets showed a weak prediction model for PCOS versus control samples from the follicular and mid-cycle phases of the menstrual cycle, but a stronger model (specificity 85 % and sensitivity 95 %) for PCOS versus the luteal phase menstrual cycle controls. The PCOS vs luteal phase model showed increased levels of plasma triglycerides and sphingomyelins and decreased levels of lysophosphatidylcholines and phosphatidylethanolamines in PCOS women compared with controls. Lipid biomarkers of PCOS were tentatively identified which may be useful in distinguishing PCOS from controls especially when performed during the menstrual cycle luteal phase. Springer 2015-06-30 Article PeerReviewed Haoula, Zeina, Ravipati, Srinivasarao, Stekel, Dov J., Ortori, Catharine A., Hodgman, Charlie, Daykin, Clare, Raine-Fenning, Nick, Barrett, David A. and Atiomo, William (2015) Lipidomic analysis of plasma samples from women with polycystic ovary syndrome. Metabolomics, 11 . pp. 657-666. ISSN 1573-3890 Polycystic ovary syndrome Lipidomics Biomarkers Menstrual cycle http://link.springer.com/article/10.1007/s11306-014-0726-y doi:10.1007/s11306-014-0726-y doi:10.1007/s11306-014-0726-y |
| spellingShingle | Polycystic ovary syndrome Lipidomics Biomarkers Menstrual cycle Haoula, Zeina Ravipati, Srinivasarao Stekel, Dov J. Ortori, Catharine A. Hodgman, Charlie Daykin, Clare Raine-Fenning, Nick Barrett, David A. Atiomo, William Lipidomic analysis of plasma samples from women with polycystic ovary syndrome |
| title | Lipidomic analysis of plasma samples from women with polycystic ovary syndrome |
| title_full | Lipidomic analysis of plasma samples from women with polycystic ovary syndrome |
| title_fullStr | Lipidomic analysis of plasma samples from women with polycystic ovary syndrome |
| title_full_unstemmed | Lipidomic analysis of plasma samples from women with polycystic ovary syndrome |
| title_short | Lipidomic analysis of plasma samples from women with polycystic ovary syndrome |
| title_sort | lipidomic analysis of plasma samples from women with polycystic ovary syndrome |
| topic | Polycystic ovary syndrome Lipidomics Biomarkers Menstrual cycle |
| url | https://eprints.nottingham.ac.uk/37979/ https://eprints.nottingham.ac.uk/37979/ https://eprints.nottingham.ac.uk/37979/ |