There is no clear acceptance of specific follicular fluid biomarker and its correlation with oocyte quality or related embryo variable till now. Most of the studies analyze correlation between certain biomolecules and the oocyte quality using single variable, instead of multivariate analysis algorithms. Our hypothesis is not based on single biomarker discovery, but attempts to explain oocyte quality in terms of energy metabolic pathways by considering its various intermediates. Reduced availability of glucose in the oocytes and follicular cells caused by defective transportation of glucose is expected in polycystic ovary syndrome (PCOS). This initiates alternative pathways to utilize fatty acid, amino acids etc. for energy as a compensatory mechanism to deal with the energy requirement. These compensations can be reflected by altered levels of various biomolecules in follicular fluid (e.g. ketone bodies, lipids, amino acids, lactate, pyruvate etc.). The amount of compensation, in order to meet the energy requirement can be directly correlated to quality of oocytes and better outcome after in vitro fertilization (IVF) in PCOS cases. This can be predicted with fair accuracy by doing a multivariate analysis of altered levels of various biomolecules in follicular fluid. Various supervised and unsupervised classification techniques based on spectroscopic data, obtained from follicular fluid samples may certainly prove to be an important tool to predict oocytes quality and IVF outcome with better accuracy in women with PCOS.

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http://dx.doi.org/10.1016/j.mehy.2012.01.009DOI Listing

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