Maternal TLR4 and NOD2 Gene Variants, Pro-Inflammatory Phenotype and Susceptibility to Early-Onset Preeclampsia and HELLP Syndrome

Background: Altered maternal inflammatory responses play a role in the development of preeclampsia and the hemolysis, elevated liver enzymes and low platelets (HELLP) syndrome. We examined whether allelic variants of the innate immune receptors toli-like receptor 4 (TLR4) and nucleotide-binding oligomerization domain (NOD2), that impair the inflammatory response to endotexin are related to preeclampsia and HELLP syndrome. Methods and Finding: We determined five common mutations in TLR4 (D299G and T399I and NOD2 (R70W, G908R and L1007fs) in 340 primiparous women with a histo

Rapid and Easy Procedure for the Determination of Immunoglobulin Class and Light Chain Type of Anti-Lactate Dehydrogenase Antibodies in Macro-Lactate Dehydrogenase

We developed an easy to perform and rapid method for determination of the immunoglobulin class and light chain type of anti-enzyme antibodies present in macro-enzymes. The procedure is a combination of two routinely used laboratory kits, and it allows identification of the antibody involved within 1.5 hour. The applicability of the method was demonstrated for macro-lactate dehydrogenase.Peer Reviewe

Lactate to creatinine ratio in amniotic fluid:a pilot study

<p>Measurement of amniotic fluid (AF) lactate concentration in complicated pregnancies may provide information on the extent of fetal acidemia. However, normalisation for AF volume may be necessary by calculating the lactate: creatinine (L: C) ratio. We measured these AF parameters and compared them to arterial cord blood lactate in 28 term and 10 preterm pregnancies. Cord blood lactate was not correlated to AF lactate, but was correlated to the L: C ratio in the complete study population (R = 0.54, p = 0.001) and the subgroups. Correlation was strongest in a preterm intrauterine growth restricted subgroup (n = 7, R = 0.83, p = 0.02). The L: C ratio is more accurate in estimating fetal lacticaemia than AF lactate.</p>

Variation at the paraoxonase gene locus contributes to carotid arterial wall thickness in subjects with familial hypercholesterolemia

Objectives: Paraoxonase (PON1) is a potent enzyme, physically associated with the high-density lipoprotein particle. PON1 may protect against cardiovascular disease (CVD), since it is capable of hydrolyzing oxidized LDL-cholesterol, thereby negating the detrimental effects of this lipoprotein on the arterial wall. Design and methods: In 187 patients with familial hypercholesterolemia, we studied the seven most common single nucleotide polymorphisms (SNPs) in both the coding and promoter sequences of PON1 (L55M, Q192R, T-107C, C-126G, G-162A, G-824A, and C-907G) in terms of PON1 activity and intima media thickness (IMT) of the carotid arterial wall, a validated surrogate marker for CVD. Results: In concordance with several previous studies, we observed that the L55M, T-107C, G-162A, G-824A, and C-907G SNPs conferred PON1 activity towards phenylacetate, while this was not the case for the Q192R and C-126G SNPs. Importantly, in a multivariate regression analysis, G-824A proved to be an independent predictor of carotid IMT. Additionally, the two fully discordant homozygous haplotypes, C-907/G-824/G-162/C-126/T-107/55M versus -907G/-824A/-162A/-126G/-107C/L55, differed by 22% in carotid IMT (P = 0.007). Conclusions: Genetic variation at the PON1 locus has a strong influence on PON1 activity as well as on carotid IMT. These data indicate that PON1 is indeed involved in the pathogenesis of atherosclerosis. Whether this also translates into a role for PON1 in the occurrence of CVD events needs to be confirmed by large prospective studies in the general population. (C) 2004 The Canadian Society of Clinical Chemists. All rights reserve

Genotype-Phenotype Interactions for TLR4 and NOD2 Genotypes and Plasma Inflammatory Markers, among Women with a History of Early-Onset Preeclampsia and Controls with Only Uneventful Pregnancies ^*

*<p>Data represent odds ratios and 95% CIs for early-onset preeclampsia compared to controls with at least one uneventful pregnancy, with respect to the reference group (R) of women negative for the all minor allelic variants of TLR4 and NOD2 and with low values for plasma inflammatory markers. High values are values within the highest tertiles of the distribution of plasma levels of the control group. Low values are values within the lowest tertiles (reference group) and values within the lower two tertiles (TLR4 and NOD2 positive group), respectively; CRP denotes C-reactive protein, IL-6 interleukin-6, sICAM soluble intercellular adhesion molecule-1 and vWf von Willebrand factor.</p>†<p>P values for trend between groups, compared to the reference group (R) of women negative for allelic variants of TLR4 and NOD2, and with low levels of plasma inflammatory markers, by univariable logistic regression analysis.</p>¶<p>P_a values for trend between groups, compared to the reference group (R), after adjustment for age at inclusion, interval between delivery and enrolment, body-mass index, smoking and chronic hypertension, by multivariable logistic regression analysis.</p

Baseline Characteristics, First Pregnancy Outcome and Plasma Markers of Inflammation and the Acute-Phase Response

<p>Data are expressed as means±SD, or as number (%) and compared by the independent sample T-test. Plasma inflammatory markers were measured in a subset of 214 women at least six months after delivery and are expressed as medians±interquartile range and compared by the nonparametric Mann-Whitney <i>U</i> test.</p>†<p>Data represent outcomes of first pregnancy.</p

Odds Ratios (95 Percent Confidence Intervals) for Women with a History of Early-Onset Preeclampsia, Compared to Controls with Only Uneventful Pregnancies, According to Plasma Levels of Acute-Phase Inflammatory Biomarkers At Least Six Months After Delivery

*<p>P values represent trends accross increasing tertiles of plasma levels, by logistic regression analysis.</p>†<p>Model 1 includes tertiles of plasma levels and interval between delivery and enrolment.</p>§<p>Model 2 includes tertiles of plasma levels, interval between delivery and enrolment, age at inclusion, body-mass index, current smoking and chronic hypertension.</p