Immunoturbidimetric Assay

The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective population-based birth cohort study that recruited 14,541 pregnant women resident in Avon, UK with expected dates of delivery 1^st April 1991 to 31^st December 1992 (http://www.alspac.bris.ac.uk.).^{13 (link)} There were 13,678 mother-offspring pairs from singleton live births who survived to at least one year of age; only singleton pregnancies are considered in this paper. We further restricted analyses in this paper to women with term deliveries (between 37-44weeks gestation): N = 12,447. Of these women 11,702 (94%) gave consent for abstraction of data from their obstetric records. 6,668 (57%) offspring of these 11,702 women attended the 9-year follow-up clinic. Of the 6,668 mother-offspring eligible pairs, complete data on GWG, offspring anthropometry, blood pressure and potential confounders were available for 5,154 (77% of attendees; 41% of 12,447 total). In addition, 3,457 (52% of attendees; 28% of total) had complete data on offspring blood assays.
Six trained research midwives abstracted data from obstetric medical records. There was no between-midwife variation in mean values of abstracted data and repeat data entry checks demonstrated error rates consistently < 1%. Obstetric data abstractions included every measurement of weight entered into the medical records and the corresponding gestational age and date. To allocate women to IOM categories (box 1) we used weight measurements from the obstetric notes and subtracted the first from the last weight measurement in pregnancy to derive absolute weight gain. Pre-pregnancy BMI was based on the predicted pre-pregnancy weight using multilevel models (see below) and maternal report of height.
Maternal age, parity, mode of delivery (caesarean section / vaginal delivery) and the child’s sex were obtained from the obstetric records. Based on questionnaire responses, the highest parental occupation was used to allocate the children to family social class groups (classes I (professional / managerial) to V (unskilled manual workers)). Maternal smoking in pregnancy, categorised as - never smoked; smoked before pregnancy or in the first trimester and then stopped; smoked throughout pregnancy – was obtained from questionnaire responses.
Offspring weight and height were measured in light clothing, without shoes. Weight was measured to the nearest 0.1kg using Tanita scales. Height was measured to the nearest 0.1cm using a Harpenden stadiometer. WC was measured to the nearest 1mm at the mid-point between the lower ribs and the pelvic bone with a flexible tape and with the child breathing normally. Fat mass was assessed using dual energy X-ray densitometry (DXA). We examined BMI, WC and fat mass as continuously measured variables. We also examined binary outcomes of overweight/obese (BMI) and abdominally obese (WC) using age- and sex-specific thresholds for both child BMI (International Obesity Task Force) ^{14 (link)} and WC (>=90^th percentile^{15 (link)} based on WC percentile curves derived for British children^{16 (link)}).
Blood pressure was measured using a Dinamap 9301 Vital Signs Monitor with the child rested and seated and their arm supported at chest level on a table. Two readings of systolic and diastolic blood pressure (SBP and DBP) were recorded and the mean of each was used. Non-fasting blood samples were taken using standard procedures with samples immediately spun and frozen at −80°C. The measurements were assayed in plasma in 2008 after a median of 7.5 years in storage with no previous freeze-thaw cycles during this period. Lipids (total cholesterol, triglycerides and HDL-C) were performed by modification of the standard Lipid Research Clinics Protocol using enzymatic reagents for lipid determinations. Apolipoprotein (apo) A1 and apoB were measured by immunoturbidimetric assays (Hitachi/Roche). Leptin was measured by an in house ELISA validated against commercial methods. Adiponectin and high sensitivity IL-6 were measured by ELISA (R&D systems) and CRP was measured by automated particle-enhanced immunoturbidimetric assay (Roche UK, Welwyn Garden City, UK). All assay coefficients of variation were <5%. Non-HDLc was calculated as total cholesterol minus HDLc.
All pregnancy weight measurements (median number of repeat measurements per woman: 10,range: 1, 17) were used to develop a linear spline multilevel model (with two levels: woman and measurement occasion) relating weight (outcome) to gestational age (exposure). Full details of this statistical modelling are provided in supplementary web-material. High levels of agreement were found between estimated and observed weights (Web-table1 and Web-figure2). We scaled maternal pre-pregnancy weight and gestational weight change to be clinically meaningful – examining the variation in offspring outcomes per additional 1kg of maternal weight at conception and per 400g gain per week of gestation for GWG.² Sensitivity analyses were conducted in which we repeated analyses including only those women who had at least 9 measurements of gestational weight.
Associations of offspring outcomes with the IOM categories and with the estimates of maternal pre-pregnancy weight and early-, mid- and late-pregnancy GWG were undertaken using linear regression. We explored the linearity of the relationships between all outcomes and the exposures using fractional polynomials. Where there was evidence of non-linearity, we used spline models to approximate the relationship. In the basic model we adjusted for offspring gender and age at the time of outcome measurement and for all models with fat mass for height and height-squared. We considered the following potential confounders: pre-pregnancy weight and GWG in the previous period (for the multilevel model exposures only), gestational age (for IOM categories only, since this is taken account of in the multilevel models), maternal age, parity, pregnancy smoking, social class, and mode of delivery. In order to examine whether effects were mediated by birthweight we adjusted for it and for non-adiposity outcomes we also examined potential mediation by adiposity. Triglycerides, leptin, CRP and IL-6 were log transformed in order to normalize their distributions. The resultant regression coefficients were exponentiated to give a ratio of geometric means per change in exposure. Results are presented jointly for mothers of female and male offspring as associations were all very similar in both genders.

EDTA blood samples were obtained at the time of enrollment into the WHS and stored in vapor phase liquid nitrogen (−170° C). Samples for lipoprotein particle analysis by proton NMR spectroscopy were thawed, aliquoted (200 ul), refrozen, and shipped on dry ice to LipoScience, Inc. (Raleigh, NC). Particle concentrations of lipoproteins of different sizes were calculated from the measured amplitudes of their spectroscopically distinct lipid methyl group NMR signals. Weighted-average lipoprotein particle sizes are derived from the sum of the diameter of each subclass multiplied by its relative mass percentage based on the amplitude of its methyl NMR signal.5 Particle diameters and coefficients of variation (CVs) are shown in Supplementary Table 1. The NMR lipoprotein variables that we examined are those that are provided when ordering an NMR lipoprotein profile for clinical use.
In a laboratory (N. Rifai, Children's Hospital, Boston, MA) certified by the National Heart, Lung, and Blood Institute/Centers for Disease Control and Prevention Lipid Standardization program, baseline samples were thawed and analyzed for standard lipids and apolipoproteins. Standard lipids were directly measured using reagents from Roche Diagnostics (Indianapolis, IN), with CVs <3%. Apolipoproteins B₁₀₀ and A-1 were measured using immunoturbidimetric assays (DiaSorin, Stillwater, Minn), with CVs of 5% and 3%, respectively.

In 1987-89, the ARIC Study recruited to a baseline examination a cohort of 15,792 men and women aged 45-64 years, predominantly whites or African Americans, from four U.S. communities (12 (link)). Participants were re-examined in 1990-92 (93% response), 1993-95 (86%) and 1996-98 (80%). Participants in the ARIC Visit 4 examination serve as the cohort for the present analysis.
CRP was measured in 2008 on plasma frozen at −70°C from Visit 4 by the immunoturbidimetric assay using the Siemens (Dade Behring) BNII analyzer (Dade Behring, Deerfield, Ill), performed according to the manufacturer's protocol. Approximately 4% of samples were split and measured as blinded replicates on different dates to assess repeatability. The reliability coefficient for blinded quality control replicates of CRP was 0.99 (421 blinded replicates). Body mass index was assessed as weight (kg) in a scrub suit divided by height (m) squared. Statins were assessed by reviewing participants' medication containers. After Visit 4, cholesterol-lowering medications were self-reported during annual telephone contact. Factor VIII_c and aPTT were not measured at Visit 4 so the Visit 1 value (3 (link), 13 (link)) was used. Factor V Leiden and the prothrombin G20210A polymorphism were not measured in the whole ARIC cohort.
Participants were followed from Visit 4 (1996-98, n = 11,573) through 2005 to identify hospitalized VTE events. These were validated by physician review using a standardized protocol (14 (link)). A total of 263 VTE events were identified, of which only 7 had been included in our previous analysis of baseline CRP and VTE through June 1997 (3 (link)). Excluding these 7 events had no impact on this analysis, so we chose to include them.
Our hypothesis was that CRP would be associated positively with VTE incidence. From the 11,573 participants at Visit 4, we excluded 320 who were missing CRP; 331 with CRP values >20 mg/L, due to possible acute phase response; 342 who had a prior history of VTE; or 204 who were taking warfarin. This left 10,505 at risk: 8,219 whites, 2,255 African Americans, and 31 others, who were grouped with African Americans for this analysis. Follow-up time ended when the participant had a VTE, died, was lost to follow-up, or else until December 31, 2005. Cox proportional hazards regression was used to model the association between CRP and VTE incidence, and to derive hazard ratios and 95% confidence intervals. Hazard ratios were calculated for each of the four highest quintile groups compared with the first, but also for high CRP categories (90^th or 95^th percentile) versus all others, to study the possible impact of high CRP on VTE. Covariates included previous VTE risk factors measured in the whole ARIC cohort, measured at Visit 4 unless otherwise specified: age (continuous), race (African American, white), sex/hormone replacement therapy (men, women taking HRT, women not taking HRT), diabetes (yes, no), body mass index (continuous), Visit 1 factor VIII_c, and Visit 1 aPTT. Other factors related to CRP (e.g., smoking, lipid levels, physical activity) were not VTE risk factors in ARIC, and thus not included.