Association between Plasma Urotensin II and Risk of Hypertension: Findings from a Prospective Study.

Up to date, human urotensin II (UII) is the most potent vasoconstrictor in mammalian animals. To explore whether UII played an important role in the development of hypertension, we conducted a prospective study in Changshu city, China. The baseline investigation was carried out in 2007, and the first follow-up investigation was conducted in 2013. From the participants, we randomly obtained 2000 normotensive subjects aged 40 years and older without any severe disease at baseline and examined plasma UII and endothelin-1 (ET-1) with their blood samples at baseline. Logistic models were used to analyze the association between baseline UII, baseline ET-1, and newly occurring hypertension. In 1,819 subjects with complete data, 723 subjects developed into hypertensive in about five years. After adjusting some potential confounders, the odds ratio (95% confidence interval) for risk of hypertension comparing the highest with the lowest quartile of baseline UII was 0.888 (0.689-1.144). The role of UII in the development of hypertension was not found in the current study; therefore, further research studies should be conducted to explore the relationship between UII and hypertension.

Solid-phase extraction of seventeen alternative flame retardants in water as determined by ultra-high-performance liquid chromatography-tandem mass spectrometry.

Flame retardants have evoked public concerns owing to their extensive usage in consumer products and potential adverse effects on human health. In this study, a rapid and sensitive solid-phase extraction-ultra-high-performance liquid chromatography-tandem mass spectrometry (SPE-UPLC-MS/MS) method was developed to determine hexabromocyclododecane (HBCD), tetrabromobisphenol-A (TBBPA), six bromophenols (BPs), and nine organophosphate flame retardants (OPFRs) in water. Because of the differences in elution conditions and ionization modes for group 1 (HBCD, TBBPA, and the BPs) and group 2 (OPFRs), we had to run them twice under the different conditions to analyse group 1 and group 2 using UPLC-MS/MS. The method detection limits were 0.1-2.5 ng/L, linearity range was 0.1-100.0 ng/L for group 1 (HBCD, TBBPA, and the BPs). The method detection limit was 0.10 ng/L, and the linearity range was 0.25-250 ng/L for the OPFRs. First, the pH values of the water samples were adjusted to the range of 2-3. Then, the acidified water samples were extracted by hydrophilic-lipophilic-balance solid phase extraction (HLB-SPE) cartridges, which were eluted with 12 mL of acetonitrile. Finally, the recoveries of HBCD, TBBPA, and the BPs were 76.2-98.1%, and the relative standard deviations (RSDs, n = 5) were 2.0-28.5%. Regarding the OPFRs, the recoveries were 72.4-110.3%, and the RSDs were 0.6-6.9%. The stability experiment showed that the concentration differences were less than 15%, meeting the requirement for quality control samples. This proposed method was successfully applied to surface water, ground water, raw water, finished water, tap water, and bottled water samples.

Haplotype Analysis of PPARγ Gene Polymorphisms and the Lipoprotein (a) Level.

BACKGROUND: Lipoprotein (a) [Lp(a)], as an independent risk factor for cardiovascular disease, is more likely to be genetically determined according to the increasing evidence of epidemiologic and clinical studies in recent years. Peroxisome proliferator-activated receptor (PPAR) γ, the ligand-activated transcription factors, was considered as an indispensable role in the process of lipid metabolism. This study was designed to explore the associations of three single-nucleotide polymorphisms (SNPs) and the haplotypes of the peroxisome proliferator-activated receptor (PPAR)γ gene with the level of Lp(a). METHODS: Participants were recruited under the framework of the PMMJS (The Prevention of Metabolic Syndrome (MS) and Multi-metabolic Disorders in Jiangsu Province of China Study) from Apr 1999 to Jun 2004. Overall, 644 subjects were randomly selected and 3 SNPs of PPARγ gene (rs10865710, rs1805192, rs4684847) were genotyped. RESULTS: After adjusting for age, sex, cigarette smoking, alcohol drinking, waist circumference and body mass index, rs4684847 was significantly associated with Lp (a). The presence of the rs4684847 T allele (CT+TT) have a lower level of Lp (a) than the allele (CC) in the dominant model, mean difference was -27.30 (95% CI: -52.88∼-1.73) mg/L, P<0.05. G-P-T and G-A-T haplotype were associated with lower levels of Lp (a) (P=0.0041 and <0.0001), mean difference was 49.79 (95% CI: -97.52∼-2.06) mg/L and 17.75 (95% CI: -25.75∼-9.75) mg/L. CONCLUSION: PPAR gamma polymorphisms (rs10865710, rs1805192, rs4684847) and haplotypes may be the genetic risk factors for Lp (a) level.

[Association between peroxisome proliferator-activated receptor and gene-gene interactions with the apolipoprotein A I/apolipoprotein B100 ratio].

OBJECTIVE: To investigate the association between ten single nucleotide polymorphisms (SNPs) in the peroxisome proliferator-activated receptors (PPARα, ß, γ) with apolipoprotein A I/apolipoprotein B100 (ApoA I/ApoB100) ratio and the additional role of a gene-gene interactions among the 10 SNPs. METHODS: Participants were recruited under the framework of the Prevention of Multiple Metabolic Disorders and Metabolic Syndrome in Jiangsu Province (PMMJS) cohort population survey in the urban community of Jiangsu province of China.A total of 630 subjects were randomly selected and no individual was related.Ten SNPs (rs135539, rs4253778, rs1800206, rs2016520, rs9794, rs10865710, rs1805192, rs709158, rs3856806 and rs4684847) were selected from the HapMap database,which covered PPARα, PPARß and PPARγ. A linear regression model was used to analyze the relations between ten SNPs in the PPARs and ApoA I/ApoB100 ratio level. Mean difference and 95% CI were calculated. Interactions were explored by using the method of Generalized Multifactor Dimensionality Reduction (GMDR). RESULTS: After adjusting for age, gender, smoking status, alcohol consumption, occupational physical activity, high-fat diet as well as low-fiber diet, both rs1800206 and rs3856806 were significantly associated with a decreased level of ApoA I/ApoB100 ratio, mean difference (95% CI) values were -1.19 (-1.88 to -0.50) and -0.77 (-1.40 to -0.14). Whereas rs4253778 was significantly associated with an increased level of ApoA I/ApoB100 ratio, Mean difference (95% CI) values was 0.80 (0.08 to 1.52). GMDR analysis showed a significant gene-gene interaction among rs4253778, rs1800206 of PPARα, rs9794, rs2016520 of PPARß and rs10865710, rs3856806, rs709158, rs1805192 of PPARγ for eight-dimension models (P = 0.01), in which prediction accuracy was 0.624 and cross-validation consistency was 7/10. CONCLUSIONS: The rs1800206 of PPARα and rs3856806 of PPARγ are significantly associated with a decreased level of ApoA I/ApoB100 ratio while rs4253778 of PPARα is associated with an increased level of ApoA I/ApoB100 ratio. There is a gene-gene interaction between multiple SNPs.

[Association between polymorphisms, haplotypes of peroxisome proliferators activated receptor a gene and the level of lipoprotein (a)].

OBJECTIVE: The aim of this study was to investigate the association between three single-nucleotide polymorphisms (SNP) of in the peroxisome proliferator-activated receptor (PPAR) α gene and the level of lipoprotein (a) [Lp(a)]. METHODS: Participants were recruited under the framework of a cohort populations survey from the PMMJS (Prevention of Multiple Metabolic Disorders and MS in Jiangsu Province) which was conducted in the urban community of Jiangsu province from 1999 to 2007. 644 subjects (234 males, 410 females) were randomly selected and genotyped for three polymorphisms which were used as genetic marker for PPARα gene (rs1800206, rs4253778 and rs135539). Data related to individual polymorphism and haplotype were available for analysis. χ² test was used to determine if the whole population was in Hardy-Weinberg genetic equilibrium. Linear regression models were used to analyze the association between SNPs in PPARα gene and the level of Lp(a). Associations between PPARα haplotypes and serum Lp(a) levels were analyzed by the SNPstats software. RESULTS: In the dominant model, after factors as sex, age, smoking, alcohol and BMI were adjusted, the presence of the V162 allele of L162V appeared associated with a high level of Lp(a) (mean difference was 57.70 mg/L (95% CI: 32.03-83.37 mg/L), P < 0.001. Data from the haplotype analysis revealed that A-G-V and C-G-V haplotype (established by 1A > C, 7G > C L162V) were significantly associated with a higher level of Lp(a) (P = 0.012 0 and 0.009 7). CONCLUSION: Results from our study might help to clarify the role of PPARα gene in regulation of Lp(a) and the evaluation of its polymorphisms and haplotypes which were characterized as genetic factors for Lp(a).

Analysis on the association between PPARα/γ polymorphisms and lipoprotein(a) in a Chinese Han population.

Lipoprotein(a) [Lp(a)], a low-density lipoprotein-like particle, is recognized as an independent risk factor for atherosclerosis, cardiovascular diseases, and diabetic vascular diseases. Our recent studies revealed that the single nucleotide polymorphisms (SNPs) of peroxisome proliferator-activated receptors (PPARα/δ/γ) gene are involved in the regulation of lipid storage and metabolism. In order to investigate the relationships between the SNPs of PPARα/γ gene and plasma levels of Lp(a), 644 participants were randomly selected from Chinese Han population in the present study. As the results shown, Lp(a) was significantly associated with L162V (rs1800206) in PPARα. Compared with those subjects with widetype (LL), significantly higher Lp(a) concentration was determined in the individuals with mutant (LV + VV) (mean difference: 49.07 mg/l, 95% CI 23.32-74.82 mg/l, p = 0.0002). Moreover, with generalized multifactor dimensionality reduction analysis, our present results indicated that there was a significant association between plasma Lp(a) level and gene-gene interaction among the polymorphisms rs1800206, rs135539 in PPARα and rs10865710, rs1805192, and rs4684847 in PPARγ. Therefore, our presented study indicated that PPARα/γ polymorphisms should be involved in the regulation of plasma Lp(a) in independently and/or in an interactive manner, suggesting that PPARα/γ gene may influence the risk of hypertension, cardiovascular diseases, and dyslipidemia by regulating Lp(a) level.

Gene-Gene Interactions among Pparα/δ/γ Polymorphisms for Apolipoprotein (Apo) A-I/Apob Ratio in Chinese Han Population.

BACKGROUND: The peroxisome proliferator-activated receptors (PPARs) -α, -δ/ß and -γ are the ligand-activated transcription factors involved in the regulation of fatty acid and lipoprotein metabolism, energy balance, cell proliferation and differentiation and atherosclerosis, etc. We investigated the associations of 10 single-nucleotide polymorphisms (SNPs) in PPARs with apolipoprotein (apo) A-I/apoB ratio in Chinese Han population. METHODS: Overall, 630 subjects (212 males, 418 females) were randomly selected from the Prevention of Metabolic Syndrome and Multiple Metabolic Disorders in Jiangsu Province of China Study Cohort. Population analyzed was as the general population which involved healthy people and individuals with disorders of apoA-I or apoB. 10 SNPs (rs1800206, rs135539, rs4253778, rs2016520, rs9794, rs10865710, rs1805192, rs709158, rs3856806 and rs4684847) were genotyped. Mean difference (Difference) and 95% confident interval (95%CI) were calculated. RESULTS: After covariates adjustment, rs1800206-V allele (LV+VV) and rs3856806-T allele (CT+TT) were significantly associated with a decreased apoA-I/apoB ratio than those wild type carriers, Difference (95%CI) were -1.29 (-1.96-0.62) and -0.8 (-1.42~-0.17), respectively. Rs4253778-C allele was significantly associated with an increased apoA-I/apoB ratio compared to the wild type carriers (GG), Difference (95%CI) was 0.76 (0.04-1.48). Generalized multifactor dimensionality reduction analysis showed that three-to-eight-locus models were significant with apoA-I/apoB ratio (P<0.05). We chose the seven-locus model (P=0.0010) as the best GMDR model (cross-validation consistency was 7/10 and testing accuracy was 62.97%). CONCLUSION: Our data provided the evidence that PPARs polymorphisms might be involved in regulation of apoA-I/apoB ratio in independently and/or in an interactive manner.

[Association of both peroxisome proliferator-activated receptor, gene-gene interactions and the lipid accumulation product].

OBJECTIVE: To investigate the association of ten single nucleotide polymorphisms (SNPs) in the peroxisome proliferator-activated receptors (PPARα, δ, γ) with lipid accumulation product (LAP) and the additional role of a gene-gene interactions among the 10 SNPs. METHODS: Participants were recruited under the framework of the PMMJS (Prevention of Multiple Metabolic Disorders and Metabolic Syndrome in Jiangsu province) cohort populations survey in the urban community of Jiangsu province of China. A total of 820 subjects were randomly selected and no individual was related. Ten SNPs (rs135539, rs4253778, rs1800206, rs2016520, rs9794, rs10865710, rs1805192, rs709158, rs3856806 and rs4684847) were selected from the HapMap database, which covered PPARα, PPARδ and PPARγ. A linear regression model was used to analyze the relations between ten SNPs in the PPARs and LAP. Mean difference (Difference) and 95% confident interval (95%CI)were calculated. Interactions were explored by using the method of Generalized Multifactor Dimensionality Reduction (GMDR). RESULTS: After adjusting the factors as age, gender, smoking status, occupational physical activity, educational level, high-fat diet as well as low-fiber diet, both rs1800206, s1805192 and rs3856806 were significantly associated with the increased level of LAP. Difference (95% CI) values were 32.47 (22.62-42.31), 12.97 (4.61-21.33) and 12.49 (4.24-20.75). Whereas rs2016520 was significantly associated with the decreased level of LAP. Difference (95%CI) values was -14.67 ( -22.97--6.55). GMDR analysis showed a significant gene-gene interaction among rs135539, rs1800206 of PPARα, rs2016520 of PPARδ and rs10865710, rs3856806, rs709158, rs1805192, rs4684847 of PPARγ for eight-dimension models (P < 0.05), in which prediction accuracy was 0.5902 and cross-validation consistency was 10/10. CONCLUSION: The rs1800206 of PPARα and rs1805192, rs3856806 of PPARγ were significantly associated with the increased level of LAP; rs2016520 of PPARδ was associated with the decreased level of LAP. There was a gene-gene interaction between multiple SNPs.