Novel lipidomic signature associated with metabolic risk in women with and without polycystic ovary syndrome

Author(s):  
Aya Mousa ◽  
Kevin Huynh ◽  
Stacey J Ellery ◽  
Boyd J Strauss ◽  
Anju E Joham ◽  
...  

Abstract Background Dyslipidaemia is a feature of polycystic ovary syndrome (PCOS) and may augment metabolic dysfunction in this population. Objective Using comprehensive lipidomic profiling and gold-standard metabolic measures, we examined whether distinct lipid biomarkers were associated with metabolic risk in women with and without PCOS. Methods Using pre-existing data and bio-banked samples from 76 women (n=42 with PCOS), we profiled >700 lipid species by mass spectrometry. Lipids were compared between women with and without PCOS and correlated with direct measures of adiposity (dual X-ray absorptiometry and computed tomography) and insulin sensitivity (hyperinsulinaemic-euglycaemic clamp), as well as fasting insulin, HbA1c, and hormonal parameters (luteinizing and follicle stimulating hormones; total and free testosterone; sex hormone-binding globulin [SHBG]; and free androgen index [FAI]). Multivariable linear regression was used with correction for multiple testing. Results Despite finding no differences by PCOS status, lysophosphatidylinositol (LPI) species esterified with an 18:0 fatty acid were the strongest lipid species associated with all the metabolic risk factors measured in women with and without PCOS. Across the cohort, higher concentrations of LPI(18:0) and lower concentrations of lipids containing docosahexaenoic acid (DHA, 22:6) n-3 polyunsaturated fatty acids (PUFA) were associated with higher adiposity, insulin resistance, fasting insulin, HbA1c and FAI, and lower SHBG. Conclusions Our data indicate that a distinct lipidomic signature comprising high LPI(18:0) and low DHA-containing lipids are associated with key metabolic risk factors that cluster in PCOS, independent of PCOS status. Prospective studies are needed to corroborate these findings in larger cohorts of women with varying PCOS phenotypes.

PLoS ONE ◽  
2015 ◽  
Vol 10 (9) ◽  
pp. e0137609 ◽  
Author(s):  
Fahimeh Ramezani Tehrani ◽  
Seyed Ali Montazeri ◽  
Farhad Hosseinpanah ◽  
Leila Cheraghi ◽  
Hadi Erfani ◽  
...  

Metabolism ◽  
2011 ◽  
Vol 60 (10) ◽  
pp. 1475-1481 ◽  
Author(s):  
Hang Wun Raymond Li ◽  
Rebecca E. Brereton ◽  
Richard A. Anderson ◽  
A. Michael Wallace ◽  
Clement K.M. Ho

2019 ◽  
Vol 13 (3) ◽  
pp. 2098-2105 ◽  
Author(s):  
Shayaq Ul Abeer Rasool ◽  
Sairish Ashraf ◽  
Mudasar Nabi ◽  
Fouzia Rashid ◽  
Khalid Majid Fazili ◽  
...  

2008 ◽  
pp. S91-S98
Author(s):  
T Grimmichová ◽  
J Vrbíková ◽  
P Matucha ◽  
K Vondra ◽  
PP Veldhuis ◽  
...  

The aim of our study was to evaluate rapid insulin pulses and insulin secretion regularity in fasting state in lean women with polycystic ovary syndrome (PCOS) in comparison to lean healthy women. PCOS (n=8) and controls (n=7) underwent every minute blood sampling for 60 min. Insulin pulsatility was assessed by deconvolution and insulin secretion regularity by approximate entropy methodology. PCOS had higher testosterone (p<0.02), prolactin (p<0.05) and lower sex hormone binding globulin (SHBG) (p<0.0006) levels than controls. Approximate entropy, insulin pulse frequency, mass, amplitude and interpulse interval did not differ between PCOS and controls. PCOS had broader insulin peaks determined by a common half-duration (p<0.07). Burst mass correlated positively with testosterone (p<0.05) and negatively with SHBG (p 0.0004) and common half-duration correlated positively with prolactin (p<0.008) and cortisol levels (p<0.03). Approximate entropy positively correlated with BMI (p<0.04) and prolactin (p<0.03). Lean PCOS patients tended to have broader insulin peaks in comparison to healthy controls. Prolactin, androgens and cortisol might participate in alteration of insulin secretion in PCOS-affected women. Body weight and prolactin levels could influence insulin secretion regularity.


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