Novel Lipidomic Signature Associated With Metabolic Risk in Women With and Without Polycystic Ovary Syndrome

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Abstract

CONTEXT: Dyslipidemia 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 preexisting data and biobanked 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 (hyperinsulinemic-euglycemic 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 were associated with higher adiposity, insulin resistance, fasting insulin, HbA1c and FAI, and lower SHBG. CONCLUSION: 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.

Original languageEnglish
Pages (from-to)e1987-e1999
Number of pages13
JournalThe Journal of Clinical Endocrinology and Metabolism
Volume107
Issue number5
DOIs
Publication statusPublished - May 2022

Keywords

  • biomarkers
  • cardiometabolic risk
  • insulin resistance
  • lipidomics
  • obesity
  • polycystic ovary syndrome

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