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Pregnancy Increases CYP3A Enzymes Activity as Measured by the 4β-Hydroxycholesterol/Cholesterol Ratio.

Eulambius M MluguOmary M MinziAppolinary A R KamuhabwaUlf DiczfalusyEleni Aklillu
Published in: International journal of molecular sciences (2022)
Changes in cortisol and other hormones during pregnancy may alter CYP3A enzymes activity, but data from sub-Saharan Africa are sparse. We investigated the effect of pregnancy and CYP3A5 genotypes on CYP3A enzymes activity using the plasma 4β-hydroxycholesterol (4β-OHC)/cholesterol (Chol) ratio, a known endogenous biomarker. Tanzanian pregnant women (n = 110) and non-pregnant women (n = 59) controls were enrolled. Plasma 4β-OHC and Chol were determined in the second and third trimesters for pregnant women and once for non-pregnant women using gas chromatography−mass spectrometry. Genotyping for CYP3A5 (*3, *6, *7) was performed. Wilcoxon Signed-Rank Test and Mann−Whitney U test were used to compare the median 4β-OHC/Chol ratio between trimesters in pregnant women and between pregnant and non-pregnant women. Repeated-measure ANOVA was used to evaluate the effect of the CYP3A5 genotypes on the 4β-OHC/Chol ratio in pregnant women. No significant effect of the pregnancy status or the CYP3A5 genotype on the cholesterol level was observed. The plasma 4β-OHC/Chol ratio significantly increased by 7.3% from the second trimester to the third trimester (p = 0.02). Pregnant women had a significantly higher mean 4β-OHC/Chol ratio than non-pregnant women, (p < 0.001). In non-pregnant women, the mean 4β-OHC/Chol ratio was significantly lower in carriers of defective CYP3A5 alleles (*3, *6 or *7) as compared to women with the CYP3A5*1/*1 genotypes (p = 0.002). Pregnancy increases CYP3A enzymes activity in a gestational-stage manner. The CYP3A5 genotype predicts CYP3A enzymes activity in the black Tanzanian population, but not during pregnancy-mediated CYP3A enzyme induction.
Keyphrases
  • pregnant women
  • pregnancy outcomes
  • preterm birth
  • gas chromatography mass spectrometry
  • body mass index
  • gene expression
  • single cell
  • deep learning
  • high resolution
  • weight loss
  • low density lipoprotein
  • data analysis