Sébastien Thériault

Linking preeclampsia and cardiovascular disease later in life.

Abstract Preeclampsia (PE), which is defined as new onset hypertension after 20 weeks of pregnancy accompanied by proteinuria, is characterized by inadequate placentation, oxidative stress, inflammation and widespread endothelial dysfunction. A link between PE and long-term risk of cardiovascular disease (CVD) was suggested by retrospective studies, which found that PE was associated with a 2–3-fold risk of CVD later in life, with a 5–7-fold risk in the case of severe and/or early-onset PE. Recently, meta-analyses and prospective studies have confirmed the association between PE and the emergence of an unfavorable CVD risk profile, in particular a 3–5-fold increased prevalence of the metabolic syndrome only 8 years after the index pregnancy. PE and CVD share many risk factors, including obesity, hypertension, dyslipidemia, hypercoagulability, insulin resistance and both entities are characterized by endothelial dysfunction. PE and CVD are complex traits sharing common risk factors and pathophysiological processes, but the genetic link between both remains to be elucidated. However, recent evidence suggests that genetic determinants associated with the metabolic syndrome, inflammation and subsequent endothelial dysfunction are involved. As the evidence now supports that PE represents a risk factor for the emergence of the metabolic syndrome and CVD later in life, the importance of long-term follow-up assessment of CVD risk beginning early in women with a history of PE must be considered and translated into new preventive measures.

Screening for pre-eclampsia early in pregnancy: performance of a multivariable model combining clinical characteristics and biochemical markers.

To investigate the performance of a multivariable model combining a priori clinical characteristics and biomarkers to detect, early in pregnancy, women at higher risk of developing pre‐eclampsia (PE).

Validation of early risk-prediction models for gestational diabetes based on clinical characteristics

AIMS Gestational diabetes (GDM) is generally diagnosed late in pregnancy, precluding early preventive interventions. This study aims to validate, in a large Caucasian population of pregnant women, models based on clinical characteristics proposed in the literature to identify, early in pregnancy, those at high risk of developing GDM in order to facilitate follow up and prevention. METHODS This is a cohort study including 7929 pregnant women recruited prospectively at their first prenatal visit. Clinical information was obtained by a self-administered questionnaire and extraction of data from the medical records. The performance of four proposed clinical risk-prediction models was evaluated for identifying women who developed GDM and those who required insulin therapy. RESULTS The four models yielded areas under the receiver operating characteristic curve (AUC) between 0.668 and 0.756 for the identification of women who developed GDM, a performance similar to those obtained in the original studies. The best performing model, based on ethnicity, body-mass index, family history of diabetes and past history of GDM, resulted in sensitivity, specificity and AUC of 73% (66-79), 81% (80-82) and 0.824 (0.793-0.855), respectively, for the identification of GDM cases requiring insulin therapy. CONCLUSIONS External validation of four risk-prediction models based exclusively on clinical characteristics yielded a performance similar to those observed in the original studies. In our cohort, the strategy seems particularly promising for the early prediction of GDM requiring insulin therapy. Addition of recently proposed biochemical markers to such models has the potential to reach a performance justifying clinical utilization.

Soluble Fms-like tyrosine kinase-1 to placental growth factor ratio in mid-pregnancy as a predictor of preterm preeclampsia in asymptomatic pregnant women.

Abstract Background: This study aims to evaluate the performance of the soluble Fms-like tyrosine kinase-1/placental growth factor (sFlt-1/PlGF) ratio to predict early-onset, preterm and severe preeclampsia at mid-pregnancy in asymptomatic women. Methods: Based on a prospective cohort of 7929 pregnant women from the Quebec City metropolitan area, a nested case-control study was performed including 111 women who developed preeclampsia and 69 women with gestational hypertension matched with 338 normotensive women. Serum sFlt-1 and PlGF were measured between 20 and 32 weeks of gestation. The performance of the sFlt-1/PlGF ratio, expressed as raw values and multiples of the median (MoM) for the prediction of early-onset, preterm and severe preeclampsia was evaluated. Results: Women who developed preeclampsia had significantly higher MoM sFlt-1/PlGF ratio (p<0.001). In the early-onset preeclampsia group, the median of the MoM distribution was 24.0 and the area under the receiver operating characteristic curve (AUC) was 0.977, giving sensitivities of 77.8% and 88.9% at false-positive rates of 5% and 10%. Positive predictive values (PPV) were 2.5% and 1.5%, respectively. In a subset between 26 and 32 weeks of gestation, at a threshold of 30, the sFlt-1/PlGF ratio yielded 100% specificity and identified, respectively, 85.7% and 65.2% of women who developed early-onset and preterm preeclampsia. Conclusions: The sFlt-1/PlGF ratio has the potential to predict early-onset and preterm preeclampsia at mid-pregnancy in asymptomatic women. However, care must be paid to the prevalence of early-onset preeclampsia in the population since low prevalence reduces PPV and may hamper clinical utility.

Absence of association between serum folate and preeclampsia in women exposed to food fortification.

OBJECTIVE: To evaluate serum folate concentration early in pregnancy and any association with hypertensive disorders of pregnancy in a population exposed to folic acid supplementation and food fortification. METHODS: This is a nested case–control study based on a prospective cohort of 7,929 pregnant women recruited in the Quebec City metropolitan area, including 214 participants who developed a hypertensive disorder of pregnancy and 428 normotensive participants in the control group matched for parity, multiple pregnancy, smoking status, gestational, and maternal age at inclusion, and duration of blood sample storage. Serum folate levels were measured at a mean of 14 weeks of gestation. RESULTS: More than 98% of the participants took folic acid or multivitamins before the end of the first trimester. Mean serum folate levels were accordingly high and there were no differences between women who further developed a hypertensive disorder of pregnancy compared with women in the control group (60.1 nmol/L compared with 57.9 nmol/L; P=.51). The proportion of participants with serum folate below the 10th percentile (less than 22.3 nmol/L) of age-matched women in our outpatient population was similar between groups (P=.66) and no participant had levels generally defined as folate deficiency (less than 10 nmol/L). CONCLUSION: In a general cohort of pregnant women benefiting from a national policy of folic acid food fortification combined with a high adherence to folic acid supplementation, serum folate levels are high and do not differ between women who develop a hypertensive disorder of pregnancy and women who remain normotensive. Further supplementation with higher doses is unlikely to be beneficial in such populations. LEVEL OF EVIDENCE: II

HDL Cholesterol, LDL Cholesterol, and Triglycerides as Risk Factors for CKD: A Mendelian Randomization Study

BACKGROUND High-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglyceride concentrations are heritable risk factors for vascular disease, but their role in the progression of chronic kidney disease (CKD) is unclear. STUDY DESIGN 2-sample Mendelian randomization analysis of data derived from the largest published lipid and CKD studies. SETTING & PARTICIPANTS Effect of independent genetic variants significantly associated with lipid concentrations was obtained from the Global Lipids Genetics Consortium (n=188,577), and the effect of these same variants on estimated glomerular filtration rate (eGFR), CKD (defined as eGFR<60mL/min/1.73m2), and albuminuria was obtained from the CKD Genetics Consortium (n=133,814). FACTOR Using conventional, multivariable, and Egger Mendelian randomization approaches, we assessed the causal association between genetically determined lipid concentrations and kidney traits. OUTCOME eGFR, dichotomous eGFR<60mL/min/1.73m2, and albuminuria. RESULTS In multivariable analysis, a 17-mg/dL higher HDL cholesterol concentration was associated with an 0.8% higher eGFR (95% CI, 0.4%-1.3%; P=0.004) and lower risk for eGFR<60mL/min/1.73m2 (OR, 0.85; 95% CI, 0.77-0.93; P<0.001), while Egger analysis showed no evidence of pleiotropy. There was no evidence for a causal relationship between LDL cholesterol concentration and any kidney disease measure. Genetically higher triglyceride concentrations appeared associated with higher eGFRs, but this finding was driven by a single pleiotropic variant in the glucokinase regulator gene (GCKR). After exclusion, genetically higher triglyceride concentration was not associated with any kidney trait. LIMITATIONS Individual patient-level phenotype and genotype information were unavailable. CONCLUSIONS 2-sample Mendelian randomization analysis of data from the largest lipid and CKD cohorts supports genetically higher HDL cholesterol concentration as causally associated with better kidney function. There was no association between genetically altered LDL cholesterol or triglyceride concentration and kidney function. Further analysis of CKD outcomes in HDL cholesterol intervention trials is warranted.

Early prediction of gestational diabetes: a practical model combining clinical and biochemical markers.

Abstract Background: Gestational diabetes (GDM) is usually diagnosed late in pregnancy, precluding early preventive interventions. This study aims to develop a predictive model based on clinical factors and selected biochemical markers for the early risk assessment of GDM. Methods: Based on a prospective cohort of 7929 pregnant women from the Quebec City metropolitan area, a nested case-control study was performed including 264 women who developed GDM. Each woman who developed GDM was matched with two women with normal glycemic profile. Risk prediction models for GDM and GDM requiring insulin therapy were developed using multivariable logistic regression analyses, based on clinical characteristics and the measurement of three clinically validated biomarkers: glycated hemoglobin (HbA1c), sex hormone binding globulin (SHBG) and high-sensitivity C-reactive protein (hsCRP) measured between 14 and 17 weeks of gestation. Results: HbA1c and hsCRP were higher and SHBG was lower in women who developed GDM (p<0.001). The selected model for the prediction of GDM, based on HbA1c, SHBG, BMI, past history of GDM, family history of diabetes and soft drink intake before pregnancy yielded an area under the ROC curve (AUC) of 0.79 (0.75–0.83). For the prediction of GDM requiring insulin therapy, the selected model including the same six variables yielded an AUC of 0.88 (0.84–0.92) and a sensitivity of 68.9% at a false-positive rate of 10%. Conclusions: A simple model based on clinical characteristics and biomarkers available early in pregnancy could allow the identification of women at risk of developing GDM, especially GDM requiring insulin therapy.

Relationships of Measured and Genetically Determined Height With the Cardiac Conduction System in Healthy Adults

Background— Increasing height is an independent risk factor for atrial fibrillation, but the underlying mechanisms are unknown. We hypothesized that height-related differences in electric conduction could be potential mediators of this relationship. Methods and Results— We enrolled 2149 adults aged 25 to 41 years from the general population. Height was directly measured, and a resting 12-lead ECG obtained under standardized conditions. Multivariable linear regression models were used to evaluate the association between measured height and ECG parameters. Mendelian randomization analyses were then performed using 655 independent height-associated genetic variants previously identified in the GIANT consortium. Median age was 37 years, and median height was 1.71 m. Median PR interval, QRS duration, and QTc interval were 156, 88, and 402 ms, respectively. After multivariable adjustment, &bgr;-coefficients (95% confidence intervals) per 10 cm increase in measured height were 4.17 (2.65–5.69; P<0.0001) for PR interval and 2.06 (1.54–2.58; P<0.0001) for QRS duration. Height was not associated with QTc interval or the Sokolow–Lyon index. An increase of 10 cm in genetically determined height was associated with increases of 4.33 ms (0.76–7.96; P=0.02) in PR interval and 2.57 ms (1.33–3.83; P<0.0001) in QRS duration but was not related to QTc interval or Sokolow–Lyon index. Conclusions— In this large population-based study, we found significant associations of measured and genetically determined height with PR interval and QRS duration. Our findings suggest that adult height is a marker of altered cardiac conduction and that these relationships may be causal.

Genetic Interactions with Age, Sex, Body Mass Index, and Hypertension in Relation to Atrial Fibrillation: The AFGen Consortium

It is unclear whether genetic markers interact with risk factors to influence atrial fibrillation (AF) risk. We performed genome-wide interaction analyses between genetic variants and age, sex, hypertension, and body mass index in the AFGen Consortium. Study-specific results were combined using meta-analysis (88,383 individuals of European descent, including 7,292 with AF). Variants with nominal interaction associations in the discovery analysis were tested for association in four independent studies (131,441 individuals, including 5,722 with AF). In the discovery analysis, the AF risk associated with the minor rs6817105 allele (at the PITX2 locus) was greater among subjects ≤ 65 years of age than among those > 65 years (interaction p-value = 4.0 × 10−5). The interaction p-value exceeded genome-wide significance in combined discovery and replication analyses (interaction p-value = 1.7 × 10−8). We observed one genome-wide significant interaction with body mass index and several suggestive interactions with age, sex, and body mass index in the discovery analysis. However, none was replicated in the independent sample. Our findings suggest that the pathogenesis of AF may differ according to age in individuals of European descent, but we did not observe evidence of statistically significant genetic interactions with sex, body mass index, or hypertension on AF risk.

OS090. Performance of candidate clinical and biochemical markers in screening early in pregnancy to detect women at high risk to develop preeclampsia

INTRODUCTION The advent of early preventive measures, such as low-dose aspirin targeting women at high risk of preeclampsia (PE), emphasizes the need for better detection. Despite the emergence of promising biochemical markers linked to the pathophysiological processes, systematic reviews have shown that, until now, no single tests fulfill the criteria set by WHO for biomarkers to screen for a disease. However, recent literature reveals that by combining various clinical, biophysical and biochemical markers into multivariate algorithms, one can envisage to estimate the risk of PE with a performance that would reach clinical utility and cost-effectiveness, but this remains to be demonstrated in various environments and health care settings. OBJECTIVES To investigate, in a prospective study, the clinical utility of candidate biomarkers and clinical data to detect, early in pregnancy, women at risk to develop PE and to propose a multivariate prediction algorithm combining clinical parameters to biochemical markers. METHODS 7929 pregnant women prospectively recruited at the first prenatal visit, provided blood samples, clinical and sociodemographic information. 214 pregnant women developed hypertensive disorders of pregnancy (HDP) of which 88 had PE (1.2%), including 44 with severe PE (0.6%). A nested case-control study was performed including for each case of HDP two normal pregnancies matched for maternal age, gestational age at recruitment, ethnicity, parity, and smoking status. Based on the literature we selected the most promising markers in a multivariate logistic regression model: mean arterial pressure (MAP), BMI, placental growth factor (PlGF), soluble Flt-1, inhibin A and PAPP-A. Biomarker results measured between 10-18 weeks gestation were expressed as multiples of the median. Medians were determined for each gestational week. RESULTS When combined with MAP at the time of blood sampling and BMI at the beginning of pregnancy, the four biochemical markers discriminate normal pregnancies from those with HDP. At a 5% false positive rate, 37% of the affected pregnancies would have been detected. However, considering the prevalence of HDP in our population, the positive predictive value would have been only 15%. If all the predicted positive women would have been proposed a preventive intervention, only one out 6.7 women could have potentially benefited. In the case of severe PE, performance was not improved, sensitivity was the same, but the positive predictive value decreased to 3% (lower prevalence of severe PE). CONCLUSION In our low-risk Caucasian population, neither individual candidate markers nor multivariate risk algorithm using an a priori combination of selected markers reached a performance justifying implementation. This also emphasizes the necessity to take into consideration characteristics of the population and environment influencing prevalence before promoting wide implementation of such screening strategies. In a perspective of personalized medicine, it appears more than ever mandatory to tailor recommendations for HDP screening according not only to individual but also to population characteristics.