2. Patients and Methods
Study design and participants. We recruited 134 healthy pregnant women at the “Clinica Mangiagalli”, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy. The women were randomly selected from individuals who were attending prenatal healthcare clinics during the 11–12th week of pregnancy. Exclusion criteria included a history of illicit drug use, diabetes, hypertension, previous pregnancy with pre-eclampsia/eclampsia or gestational hypertension, and current use of acetylsalicylic acid or low-molecular-weight heparin. Information about demographics and lifestyle characteristics of the mother, such as smoking habits and alcohol consumption, were collected. An informed consent form was signed by all participants and the study was approved by the ethics committee of the Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico (approval number 681/2017).
Clinical and laboratory measurements. Body weight and height were determined on a standard scale. Body mass index (BMI) was expressed as Kg/m2. Systolic and diastolic blood pressure (SBP and DBP, respectively) were taken on the left arm using a mercury sphygmomanometer (mean of two measurements taken after 5 min of rest). Plasma lipids/lipoproteins and glucose were measured by certified enzymatic techniques on a Roche c311 autoanalyzer. Lipoprotein (a) [Lp(a)] levels were measured by immunoturbidimetry on a Roche c311 autoanalyzer. Standard evaluations for early pregnancy in Italy are serum pregnancy-associated plasma protein-A (PAPP-A), α-fetoprotein, and human chorionic gonadotropin (hCG). These parameters were measured at 11–12 weeks of gestation. Gestational age was calculated from the last menstrual period, and was verified by ultrasound parameters. In particular, fetal crown-rump length was used to estimate gestational age, and women were included if this parameter ranged between 45 and 84 mm.
Enzyme-linked immunosorbent assay (ELISA). Plasma PCSK9 concentrations were measured by a commercial ELISA kit (R&D Systems, MN). All patients fasted overnight and had blood sampled at around 09:00, thus minimizing any possible confounding effects of circadian variation in PCSK9 levels. In brief, samples were diluted 1:20 and incubated onto a microplate pre-coated with a monoclonal human PCSK9-specific antibody. Sample concentrations were obtained by a four-parameter logistic curve-fit, with a minimum detectable PCSK9 concentration of 0.219 ng/mL (25). Intra- and inter-assay CVs were 3.8% and 6.2%, respectively.
Air pollutant assessments. Daily air pollutant (PM10, PM2.5, and NO2,) concentrations were derived from the archives of the Regional Environmental Protection Agency (ARPA Lombardy). This organization collects data at a regional scale using the FARM (Flexible Air quality Regional Model) chemical-physical model of air quality (26). This model is a three-dimensional Eulerian model that simulates the dispersion and chemical reactions of atmospheric pollutants. The estimated levels of daily PM10, PM2.5, and NO2concentrations were assigned to each subject for the day of evaluation and 14 days before blood was sampled. We also calculated the average exposure from the first week before the clinical visit and 12 weeks earlier (i.e., weeks 0–1 being the mean over the first week of exposure and weeks 0–12 being the mean over the 12 weeks before the visit. All participants were assigned pollutant levels that were estimated in the Municipality of Milano, as 93% of the women lived or worked there.
Statistical analysis. Descriptive statistics were performed on all variables. Continuous variables were expressed as the mean ± standard deviation (SD) or as the median with first-, and third-quartile (Q1–Q3), as appropriate. Categorical data were reported as frequencies with percentages. Descriptions of each exposure variable were given by the means of box-plots, describing pollutants at each averaged time window. We applied univariate and multivariable linear regression models to evaluate the relationship between pollutant exposure (for each averaged one-week period from week 0–1 to week 0–12) and circulating PCSK9 levels. Each model was tested for normality and linearity. All potential confounders were included in the multivariate model after verifying the presence of an association in a univariate model. Best model selection was based on the minimization of the Akaike information criterion and maximization of the explained variance of the model. The final models were adjusted for low-density lipoprotein cholesterol (LDL-C), interleukine (IL)-6, fibrinogen, season, BMI, and smoking habit. Estimated effects are reported as β and standard error (SE) associated with an increase of 1 unit in each pollutant.
We examined the association between PCSK9 and the variables measured on the newborn (gestational age at birth, weight, length, cranial circumference, APGAR score), after adjusting each model for the pollutants most associated with PCSK9 levels in the multivariate analysis. Each model was also adjusted for birth mode (urgent caesarean, elective caesarean, and spontaneous delivery) and for the interaction between pollutant and PCSK9 concentrations. Using a univariate logistic regression, we evaluated the odds ratio of urgent cesarean delivery associated with a 100 mg/dL increase in PCSK9.
We calculated the q-FDR values using the multiple comparison method based on Benjamini-Hochberg False Discovery Rate (FDR), which takes the high number of comparisons into account, with a threshold of 0.10 to detect significance.
A sensitivity analysis was performed using the residential address for pollutant imputation, with no relevant changes being made to the results (data not shown). Statistical analyses were performed with SAS software, version 9.4.