ArticleJournal of assisted reproduction and genetics2023
Gene expression and demographic analyses in women with the poor ovarian response: a computational approach.
Article in Journal of assisted reproduction and genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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6 authors at 2 institutions in 1 country.
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Abstract
purposePoor response to ovarian stimulation (POR) typically is reflected as decreased follicular response and low estradiol (E2) levels following ovarian stimulation by FSH/HMG. Many genes are involved in oocyte maturation, and demographic features and lifestyle can affect the oocyte maturity and developmental competence. The present study was conducted to investigate the magnitude of gene expression and lifestyle habits in POR women as compared to healthy women, using different statistical and computational methods.
methodsFifty women in the two groups were studied. The study groups included POR women (n = 25) with 1-9 released oocytes, and the control group (normal women, n = 25) with 9-15 released oocytes. Quantitative PCR was used to estimate the expression of FIGLA, ZAR1, WNT4, LHX8, APC, H1FOO, MOS, and DMC1 genes in granulosa cells.
resultsThe results showed no significant difference in the magnitude of the studied genes' expression and linear discriminant analysis did not differentiate the studied groups based on all the genes together. Redundancy analysis (RDA) and latent factor mixed model (LFMM) results produce no significant association between the genes' expression magnitude and the geographical variables of the patients' local habitat. Linear discriminant analysis (LDA) of the demographic features differentiated the two groups of women.
conclusionOur results indicate that demographic features may have an effect on sample gene expression levels.
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