Enzyme Activity of Natural Products on Cytochrome P450.

Drug-metabolizing enzymes, particularly the cytochrome P450 (CYP450) monooxygenases, play a pivotal role in pharmacokinetics. CYP450 enzymes can be affected by various xenobiotic substrates, which will eventually be responsible for most metabolism-based herb-herb or herb-drug interactions, usually involving competition with another drug for the same enzyme binding site. Compounds from herbal or natural products are involved in many scenarios in the context of such interactions. These interactions are decisive both in drug discovery regarding the synergistic effects, and drug application regarding unwanted side effects. Herein, this review was conducted as a comprehensive compilation of the effects of herbal ingredients on CYP450 enzymes. Nearly 500 publications reporting botanicals' effects on CYP450s were collected and analyzed. The countries focusing on this topic were summarized, the identified herbal ingredients affecting enzyme activity of CYP450s, as well as methods identifying the inhibitory/inducing effects were reviewed. Inhibitory effects of botanicals on CYP450 enzymes may contribute to synergistic effects, such as herbal formulae/prescriptions, or lead to therapeutic failure, or even increase concentrations of conventional medicines causing serious adverse events. Conducting this review may help in metabolism-based drug combination discovery, and in the evaluation of the safety profile of natural products used therapeutically.

[Evaluation of the diagnostic criteria of gestational metabolic syndrome and analysis of the risk factors].

OBJECTIVES: To investigate gestational multiple metabolic abnormalities aggregation and diagnostic criteria for gestational metabolic syndrome (GMS), and to analyze the risk factors of GMS. METHODS: A cohort study recruiting 309 pregnant women with preeclampsia, 627 pregnant women with gestational diabetes mellitus (GDM) and 1245 normal pregnant women was performed from January 2008 to December 2011 in Guangdong Women and Children's Hospital. Information regarding age, gestational weeks, basic blood pressure, admission blood pressure, height and body mass index(BMI)before pregnancy was recorded. Biochemical indicators including fasting plasma glucose (FPG), fasting insulin (FINS), total cholesterol (TC), triglyceride (TG), high density lipoprotein (HDL-C), low density lipoprotein (LDL-C), free fatty acids (FFA) were tested. GMS was diagnosed with three or all of the following conditions: (1) overweight and/or obesity before pregnancy (BMI ≥ 25 kg/m(2)); (2) hypertension with blood pressure ≥ 140/90 mm Hg (1 mm Hg = 0.133 kPa); (3) hyperglycemia:diagnosed as GDM; (4) dyslipidemia with TG ≥ 3.23 mmol/L. The incidence of GMS of the three groups were calculated and the risk factors were analyzed. RESULTS: (1) The age, gestational weeks, basic blood pressure, admission blood pressure, BMI before pregnancy of women with preeclampsia and women with GDM were significantly different compared to normal women, respectively (P < 0.01). (2) Biochemical indicators of women with preeclampsia were as following: FPG (4.6 ± 1.0) mmol/L, FINS (10.1 ± 5.6) mU/L, TC (6.3 ± 1.6) mmol/L, TG (3.9 ± 1.8) mmol/L, HDL-C (1.4 ± 0.4) mmol/L, LDL-C (3.0 ± 1.0) mmol/L, FFA (0.8 ± 0.4) mmol/L. And those in women with GDM were: FPG (4.7 ± 0.9) mmol/L, FINS (10.2 ± 5.8) mU/L, TC (5.7 ± 1.3) mmol/L, TG (3.2 ± 1.1) mmol/L, HDL-C (1.4 ± 0.4) mmol/L, LDL-C (2.7 ± 0.9) mmol/L, FFA (0.6 ± 0.3) mmol/L. In normal pregnant women they were: FPG (4.3 ± 0.5) mmol/L, FINS (9.0 ± 4.4) mU/L, TC (5.7 ± 1.1) mmol/L, TG (2.8 ± 1.1) mmol/L, HDL-C (1.5 ± 0.4) mmol/L, LDL-C (2.9 ± 0.8) mmol/L, FFA (0.6 ± 0.2) mmol/L. Statistic differences were found in preeclampsia and GDM women compared to normal women respectively (P < 0.01). (3) The prevalence of GMS in preeclampsia group and in GDM group was 26.2% (81/309) and 13.6% (85/627), statistically different from that of the control group (0)(P < 0.01). (4) Compared to normal women, women with preeclampsia had higher risk of developing GMS (OR = 1.62, 95%CI 1.31 - 2.00, P < 0.01). The risk factors were BMI (OR = 1.29, 95%CI 1.13 - 1.47) and TG (OR = 2.49, 95%CI 1.87 - 3.31). Also, women with GDM had higher risk of developing GMS than normal women (OR = 1.27, 95%CI 1.09 - 1.49, P < 0.01), and the risk factors were BMI (OR = 1.13, 95%CI 1.04 - 1.23) and TG (OR = 1.16, 95%CI 1.02 - 1.33). TG was the independent risk factor in both preeclampsia women and GDM women (P < 0.01, P < 0.05). HDL-C seemed to have less importance in identifying GMS (P > 0.05). CONCLUSIONS: According to the GMS diagnostic criteria used in this study, some preeclampsia patients and some GDM women had aggregation of multiple metabolic abnormalities including pre-pregnancy overweight/obesity, hyperglycemia, high blood pressure and dyslipidemia. TG was the independent risk factor for GMS. HDL-C seemed to have less importance in identifying GMS.

Prehypertension During Normotensive Pregnancy and Postpartum Clustering of Cardiometabolic Risk Factors: A Prospective Cohort Study.

The nonstratification of blood pressure (BP) levels may underestimate future cardiovascular risk in pregnant women who present with BP levels in the range of prehypertension (120-139/80-89 mm Hg). We prospectively evaluated the relationship between multiple antepartum BP measurements (from 11(+0) to 13(+6) weeks' gestation to term) and the occurrence of postpartum metabolic syndrome in 507 normotensive pregnant women after a live birth. By using latent class growth modeling, we identified the following 3 distinctive diastolic BP (DBP) trajectory groups: the low-J-shaped group (34.2%; DBP from 62.5±5.8 to 65.0±6.8 mm Hg), the moderate-U-shaped group (52.6%; DBP from 71.0±5.9 to 69.8±6.2 mm Hg), and the elevated-J-shaped group (13.2%; DBP from 76.2±6.7 to 81.8±4.8 mm Hg). Notably, the elevated-J-shaped trajectory group had mean DBP and systolic BP levels within the range of prehypertension from 37(+0) and 26(+0) weeks of pregnancy, respectively. Among the 309 women who completed the ≈1.6 years of postpartum follow-up, the women in the elevated-J-shaped group had greater odds of developing postpartum metabolic syndrome (adjusted odds ratio, 6.55; 95% confidence interval, 1.79-23.92; P=0.004) than the low-J-shaped group. Moreover, a parsimonious model incorporating DBP (membership in the elevated-J-shaped group but not in the DBP prehypertension group as identified by a single measurement) and elevated levels of fasting glucose (>4.99 mmol/L) and triglycerides (>3.14 mmol/L) at term was developed, with good discrimination and calibration for postpartum metabolic syndrome (c-statistic, 0.764; 95% confidence interval, 0.674-0.855; P<0.001). Therefore, prehypertension identified by DBP trajectories throughout pregnancy is an independent risk factor for predicting postpartum metabolic syndrome in normotensive pregnant women.