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Whole-chromosome painting probes were developed for each of the 10 chromosomes of maize by producing amplifiable libraries of unique sequences of oligonucleotides that can generate labeled probes through transcription reactions. These paints allow identification of individual homologous chromosomes for many applications as demonstrated in somatic root tip metaphase cells, in the pachytene stage of meiosis, and in interphase nuclei. Several chromosomal aberrations were examined as proof of concept for study of various rearrangements using probes that cover the entire chromosome and that label diverse varieties. The relationship of the supernumerary B chromosome and the normal chromosomes was examined with the finding that there is no detectable homology between any of the normal A chromosomes and the B chromosome. Combined with other chromosome-labeling techniques, a complete set of whole-chromosome oligonucleotide paints lays the foundation for future studies of the structure, organization, and evolution of genomes., Competing Interests: Conflict of interest statement: K.S. and J.-M.R. are employees of Arbor Biosciences., (Copyright © 2019 the Author(s). Published by PNAS.)

Group testing has its origin in the identification of syphilis in the U.S. army during World War II. Much of the theoretical framework of group testing was developed starting in the late 1950s, with continued work into the 1990s. Recently, with the advent of new laboratory and genetic technologies, there has been an increasing interest in group testing designs for cost saving purposes. In this article, we compare different nested designs, including Dorfman, Sterrett and an optimal nested procedure obtained through dynamic programming. To elucidate these comparisons, we develop closed-form expressions for the optimal Sterrett procedure and provide a concise review of the prior literature for other commonly used procedures. We consider designs where the prevalence of disease is known as well as investigate the robustness of these procedures, when it is incorrectly assumed. This article provides a technical presentation that will be of interest to researchers as well as from a pedagogical perspective. Supplementary material for this article available online.

Accurate assessment of gestational age at birth is necessary for optimal pediatric care. In high resource countries, several methods using ultrasound have been proposed to assess gestational age at birth; however, these methods are not easily accessible for low-resource populations. We develop a shared random parameter model for estimating gestational age at birth from longitudinal maternal anthropometry that incorporates additional maternal information from the last menstrual period, a measure of gestational age collected with sizable measurement error. The proposed methodology is evaluated using simulation studies under a training-test set paradigm. In addition, we propose methodology to validate prediction when some measurements of the gold standard are collected with measurement error. We illustrate the proposed methodologies with data from the NICHD Fetal Growth Studies., (Published 2018. This article is a U.S. Government work and is in the public domain in the USA.)

Objective: To determine whether multiple daily injections of parathyroid hormone (PTH) 1-34 are safe and effective as long-term therapy for children with hypoparathyroidism., Study Design: Linear growth, bone accrual, renal function, and mineral homeostasis were studied in a long-term observational study of PTH 1-34 injection therapy in 14 children., Methods: Subjects were 14 children with hypoparathyroidism attributable to autoimmune polyglandular syndrome type 1 (N = 5, ages 7-12 years) or calcium receptor mutation (N = 9, ages 7-16 years). Mean daily PTH 1-34 dose was 0.75 ± 0.15 µg/kg/day. Treatment duration was 6.9 ± 3.1 years (range 1.5-10 years). Patients were evaluated semiannually at the National Institutes of Health Clinical Center., Results: Mean height velocity and lumbar spine, whole body, and femoral neck bone accretion velocities were normal throughout the study. In the first 2 years, distal one-third radius bone accrual velocity was reduced compared with normal children (P < .003). Serum alkaline phosphatase correlated with PTH 1-34 dose (P < .006) and remained normal (235.3 ± 104.8 [SD] U/L, N: 51-332 U/L). Mean serum and 24-hour urine calcium levels were 2.05 ± 0.11 mmol/L (N: 2.05-2.5 mmol/L) and 6.93 ± 1.3 mmol/24 hour (N: 1.25-7.5 mmol/24 hour), respectively-with fewer high urine calcium levels vs baseline during calcitriol and calcium treatment (P < .001). Nephrocalcinosis progressed in 5 of 12 subjects who had repeated renal imaging although renal function remained normal., Conclusions: Twice-daily or thrice-daily subcutaneous PTH 1-34 injections provided safe and effective replacement therapy for up to 10 years in children with hypoparathyroidism because of autoimmune polyglandular syndrome type 1 or calcium receptor mutation., (Published by Elsevier Inc.)

The goal of quantitative traits genome-wide association studies is to identify associations between a phenotypic variable, such as a vitamin level and genetic variants, often single-nucleotide polymorphisms. When funding limits the number of assays that can be performed to measure the level of the phenotypic variable, a subgroup of subjects is often randomly selected from the genotype database and the level of the phenotypic variable is then measured for each subject. Because only a proportion of the genotype data can be used, such a simple random sampling method may suffer from substantial loss of efficiency, especially when the number of assays is relative small and the frequency of the less common variant (minor allele frequency) is low. We propose a pooling strategy in which subjects in a randomly selected reference subgroup are aligned with randomly selected subjects from the remaining study subjects to form independent pools; blood samples from subjects in each pool are mixed; and the level of the phenotypic variable is measured for each pool. We demonstrate that the proposed pooling approach produces considerable gains in efficiency over the simple random sampling method for inference concerning the phenotype-genotype association, resulting in higher precision and power. The methods are illustrated using genotypic and phenotypic data from the Trinity Students Study, a quantitative genome-wide association study., (Published 2018. This article is a U.S. Government work and is in the public domain in the USA.)

Studies of host-associated and environmental microbiomes often incorporate longitudinal sampling or paired samples in their experimental design. Longitudinal sampling provides valuable information about temporal trends and subject/population heterogeneity, offering advantages over cross-sectional and pre-post study designs. To support the needs of microbiome researchers performing longitudinal studies, we developed q2-longitudinal, a software plugin for the QIIME 2 microbiome analysis platform (https://qiime2.org). The q2-longitudinal plugin incorporates multiple methods for analysis of longitudinal and paired-sample data, including interactive plotting, linear mixed-effects models, paired differences and distances, microbial interdependence testing, first differencing, longitudinal feature selection, and volatility analyses. The q2-longitudinal package (https://github.com/qiime2/q2-longitudinal) is open-source software released under a 3-clause Berkeley Software Distribution (BSD) license and is freely available, including for commercial use. IMPORTANCE Longitudinal sampling provides valuable information about temporal trends and subject/population heterogeneity. We describe q2-longitudinal, a software plugin for longitudinal analysis of microbiome data sets in QIIME 2. The availability of longitudinal statistics and visualizations in the QIIME 2 framework will make the analysis of longitudinal data more accessible to microbiome researchers.

Background: Somatic copy number alternation (SCNA) is a common feature of the cancer genome and is associated with cancer etiology and prognosis. The allele-specific SCNA analysis of a tumor sample aims to identify the allele-specific copy numbers of both alleles, adjusting for the ploidy and the tumor purity. Next generation sequencing platforms produce abundant read counts at the base-pair resolution across the exome or whole genome which is susceptible to hypersegmentation, a phenomenon where numerous regions with very short length are falsely identified as SCNA., Results: We propose hsegHMM, a hidden Markov model approach that accounts for hypersegmentation for allele-specific SCNA analysis. hsegHMM provides statistical inference of copy number profiles by using an efficient E-M algorithm procedure. Through simulation and application studies, we found that hsegHMM handles hypersegmentation effectively with a t-distribution as a part of the emission probability distribution structure and a carefully defined state space. We also compared hsegHMM with FACETS which is a current method for allele-specific SCNA analysis. For the application, we use a renal cell carcinoma sample from The Cancer Genome Atlas (TCGA) study., Conclusions: We demonstrate the robustness of hsegHMM to hypersegmentation. Furthermore, hsegHMM provides the quantification of uncertainty in identifying allele-specific SCNAs over the entire chromosomes. hsegHMM performs better than FACETS when read depth (coverage) is uneven across the genome.

Objective: Accurate assessment of gestational age (GA) is critical to paediatric care, but is limited in developing countries without access to ultrasound. Our objectives were to assess the accuracy of prediction of GA at birth and preterm birth classification using routinely collected anthropometry measures., Design: Prospective cohort study., Setting: United States., Population or Sample: A total of 2334 non-obese and 468 obese pregnant women., Methods: Enrolment GA was determined based on last menstrual period, confirmed by first-trimester ultrasound. Maternal anthropometry and fundal height (FH) were measured by a standardised protocol at study visits; FH alone was additionally abstracted from medical charts. Neonatal anthropometry measurements were obtained at birth. To estimate GA at delivery, we developed three predictor models using longitudinal FH alone and with maternal and neonatal anthropometry. For all predictors, we repeatedly sampled observations to construct training (60%) and test (40%) sets. Linear mixed models incorporated longitudinal maternal anthropometry and a shared parameter model incorporated neonatal anthropometry. We assessed models' accuracy under varied scenarios., Main Outcome Measures: Estimated GA at delivery., Results: Prediction error for various combinations of anthropometric measures ranged between 13.9 and 14.9 days. Longitudinal FH alone predicted GA within 14.9 days with relatively stable prediction errors across individual race/ethnicities [whites (13.9 days), blacks (15.1 days), Hispanics (15.5 days) and Asians (13.1 days)], and correctly identified 75% of preterm births. The model was robust to additional scenarios., Conclusions: In low-risk, non-obese women, longitudinal FH measures alone can provide a reasonably accurate assessment of GA when ultrasound measures are not available., Tweetable Abstract: Longitudinal fundal height alone predicts gestational age at birth when ultrasound measures are unavailable., (© 2018 Royal College of Obstetricians and Gynaecologists.)

Joint modeling of multivariate paired longitudinal data and time-to-event data presents computational challenges that supersede full likelihood estimation due to the large dimensional random effects vector needed to capture correlation due to clustering with respect to pairs, subjects, and outcomes. We propose an alternative, computationally simpler approach to estimation of complex shared parameter models where missing data is imputed based on the Posterior Predictive Distribution from a Conditional Linear Model (CLM) approximation. Existing methods for complete data are then implemented to obtain estimates of the event time model parameters. Our method is applied to examine the effects of discordant growth in anthropometric measures of longitudinal fetal growth in twin fetuses and the timing of birth. Simulation results are presented to show that our method performs relatively well with moderate measurement errors under certain CLM approximations., (© 2018, The International Biometric Society.)

Background: Accurately identifying pregnancies with accelerated or diminished fetal growth is challenging and generally based on cross-sectional percentile estimates of fetal weight. Longitudinal growth velocity might improve identification of abnormally grown fetuses., Objective: We sought to complement fetal size standards with fetal growth velocity, develop a model to compute fetal growth velocity percentiles for any given set of gestational week intervals, and determine association between fetal growth velocity and birthweight., Study Design: This was a prospective cohort study with data collected at 12 US sites (2009 through 2013) from 1733 nonobese, low-risk pregnancies included in the singleton standard. Following a standardized sonogram at 10w0d-13w6d, each woman was randomized to 1 of 4 follow-up visit schedules with 5 additional study sonograms (targeted ranges: 16-22, 24-29, 30-33, 34-37, and 38-41 weeks). Study visits could occur ± 1 week from the targeted GA. Ultrasound biometric measurements included biparietal diameter, head circumference, abdominal circumference, and femur length, and estimated fetal weight was calculated. We used linear mixed models with cubic splines for the fixed effects and random effects to flexibly model ultrasound trajectories. We computed velocity percentiles in 2 ways: (1) difference between 2 consecutive weekly measurements (ie, weekly velocity), and (2) difference between any 2 ultrasounds at a clinically reasonable difference between 2 gestational ages (ie, velocity calculator). We compared correlation between fetal growth velocity percentiles and estimated fetal weight percentiles at 4-week intervals, with 32 (±1) weeks' gestation for illustration. Growth velocity was computed as estimated fetal growth rate (g/wk) between ultrasound at that gestational age and from prior visit [ie, for 28-32 weeks' gestational age: velocity = (estimated fetal weight 32-28)/(gestational age 32-28)]. We examined differences in birthweight by whether or not estimated fetal weight and estimated fetal weight velocity were <5th or ≥5th percentiles using χ 2 ., Results: Fetal growth velocity was nonmonotonic, with acceleration early in pregnancy, peaking at 13, 14, 15, and 16 weeks for biparietal diameter, head circumference, femur length, and abdominal circumference, respectively. Biparietal diameter, head circumference, and abdominal circumference had a second acceleration at 19-22, 19-21, and 27-31 weeks, respectively. Estimated fetal weight velocity peaked around 35 weeks. Fetal growth velocity varied slightly by race/ethnicity although comparisons reflected differences for parameters at various gestational ages. Estimated fetal weight velocity percentiles were not highly correlated with fetal size percentiles (Pearson r = 0.40-0.41, P < .001), suggesting that these measurements reflect different aspects of fetal growth and velocity may add additional information to a single measure of estimated fetal weight. At 32 (SD ± 1) weeks, if both estimated fetal weight velocity and size were <5th percentile, mean birthweight was 2550 g; however, even when size remained <5th percentile but velocity was ≥5th percentile, birthweight increased to 2867 g, reflecting the important contribution of higher growth velocities. For estimated fetal weight ≥5th percentile, but growth velocity <5th, birthweight was smaller (3208 vs 3357 g, respectively, P < .001)., Conclusion: We provide fetal growth velocity data to complement our previous work on fetal growth size standards, and have developed a calculator to compute fetal growth velocity. Preliminary findings suggest that growth velocity adds additional information over knowing fetal size alone., (Published by Elsevier Inc.)

We aimed to examine the prospective association between first trimester HbA 1c and gestational diabetes (GDM) and explore the utility of HbA 1c for prediction of GDM. We used data from a case-control study within the prospective NICHD Fetal Growth Studies-Singleton Cohort (2009-2013), which enrolled 2,802 women at 12 U.S. clinical centers. HbA 1c was measured in GDM cases (n = 107) and matched controls (n = 214) targeted at 8-13, 16-22, 24-29, and 34-37 gestational weeks. We excluded women with HbA 1c  ≥ 6.5% (48 mmol/mol) at enrollment (n = 3) or who had a hemoglobin variant (n = 6). At 8-13 gestational weeks, women who later developed GDM had significantly higher HbA 1c (5.3[standard deviation 0.3]%; 34[4]mmol/mol) than women without GDM (5.1[0.3]%; 32[3] mmol/mol) (P ≤ 0.001); this difference remained significant throughout pregnancy. Each 0.1% (1 mmol/mol) HbA 1c increase at 8-13 weeks was associated with an adjusted 22% increased GDM risk (95% confidence interval 1.09-1.36). First trimester HbA 1c significantly improved GDM prediction over conventional risk factors (AUC 0.59 vs 0.65; P = 0.04). In conclusion, women who develop GDM may have impaired glucose homeostasis early in or prior to pregnancy, as indicated by their elevated first trimester HbA 1c . First trimester HbA 1c may aid in early identification of at risk women.

Context: T3 is the biologically active thyroid hormone involved in glucose metabolism. The free T3 (fT3)/free T4 (fT4) ratio, a marker indicating conversion of fT4 to fT3, is also implicated in glucose homeostasis., Objective: To examine associations of fT3 and the fT3/fT4 ratio with gestational diabetes mellitus (GDM)., Design: In a case-control study, thyroid markers (fT3, fT4, TSH) were measured and the fT3/fT4 ratio was derived across four visits in pregnancy, including first (gestational weeks 10 to 14) and second (weeks 15 to 26) trimester. Conditional logistic regression adjusting for thyroid autoimmunity status and major GDM risk factors estimated trimester-specific associations of thyroid markers with subsequent GDM risk., Setting: Twelve US clinical centers., Participants: One hundred seven GDM cases and 214 non-GDM controls from a multiracial pregnancy cohort of 2802 women., Main Outcome Measures: GDM diagnosis ascertained from medical records., Results: Both fT3 and the fT3/fT4 ratio were positively associated with GDM: adjusted OR (95% CI) comparing the highest vs lowest fT3 quartile was 4.25 (1.67, 10.80) at the first trimester and 3.89 (1.50, 10.10) at the second trimester. Similarly, the corresponding risk estimates for the fT3/fT4 ratio were 8.63 (2.87, 26.00) and 13.60 (3.97, 46.30) at the first and second trimester, respectively. Neither TSH nor fT4 was significantly associated with GDM., Conclusions: Higher fT3 levels, potentially resulting from de novo synthesis or increased fT4 to fT3 conversion, may be an indicator of GDM risk starting early in pregnancy.

Background: Data on saturated fatty acids (SFAs) in relation to metabolic function and glucose homeostasis remain controversial. Such data are lacking among pregnant women., Objective: We prospectively investigated objectively measured individual and subclasses of plasma phospholipid SFAs throughout pregnancy in relation to cardiometabolic markers and gestational diabetes mellitus (GDM) risk., Design: Within the National Institute of Child Health and Human Development Fetal Growth Studies-Singleton Cohort of 2802 singleton pregnancies, 107 GDM cases were ascertained via medical record review and matched to 214 non-GDM controls on age, race/ethnicity, and gestational week (GW) at blood collection. Individual plasma phospholipid SFA concentrations were repeatedly measured throughout pregnancy at GWs 10-14, 15-26, 23-31, and 33-39 and also grouped into subclasses of even- or odd-chain SFAs., Results: From GW 10, even-chain SFA concentrations were significantly higher among women who later developed GDM, whereas odd-chain SFAs were significantly lower among GDM cases compared with controls. At GWs 10-14, the SFA palmitic acid (16:0) was positively associated with impaired insulin resistance and cardiometabolic markers and the risk of GDM [adjusted OR comparing the highest with the lowest quartile (aORQ4-Q1): 4.76; 95% CI: 1.72, 13.10; P-trend = 0.001]. In contrast, odd-chain SFAs were inversely related to the previously mentioned markers and GDM risk [aORQ4-Q1 for pentadecanoic acid (15:0): 0.32; 95% CI: 0.11, 0.92; P-trend = 0.025; for heptadecanoic acid (17:0): 0.20; 95% CI: 0.07, 0.58; P-trend = 0.003]. Women with high (median or greater) even-chain SFA concentrations and low (less than median) odd-chain SFAs had a 9.43-fold (95%: CI 3.26-, 27.30-fold) increased risk compared with women with low even-chain and high odd-chain SFA concentrations. Similar results were observed at GWs 15-26., Conclusions: The study provided one of the first lines of evidence suggesting that circulating concentrations of SFAs varying by SFA chain length, as early as GWs 10-14, were significantly and differentially associated with subsequent risk of GDM. Our findings highlight the importance of assessing objectively measured, individual, and subclasses of SFAs to investigate their distinct biological and pathophysiologic roles in glucose homeostasis and cardiometabolic outcomes. This study was registered at www.clinicaltrials.gov as NCT00912132.

Determining the date of conception is important for estimating gestational age and monitoring whether the fetus and mother are on track in their development and pregnancy. Various methods based on ultrasound have been proposed for dating a pregnancy in high resource countries. However, such techniques may not be available in under-resourced countries. We develop a shared random parameter model for estimating the date of conception using longitudinal assessment of multiple maternal anthropometry and cross-sectional neonatal anthropometry. The methodology is evaluated with a training-test set paradigm as well as with simulations to examine the robustness of the method to model misspecification. We illustrate this new methodology with data from the NICHD Fetal Growth Studies.

Objective: To assess the relationship between first-trimester vaginal bleeding and fetal growth patterns., Methods: We conducted a secondary analysis of the Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies-Singletons, a prospective cohort study of low-risk, nonobese women with healthy lifestyles. Duration of bleeding was self-reported at enrollment (10 0/7 to 13 6/7 weeks of gestation) and categorized as 0, 1, or more than 1 day. Longitudinal measures of fetal biometrics were obtained in up to six study visits, and estimated fetal weight was computed. Growth trajectories were created for biometrics and estimated fetal weight. When global tests among groups was significant (P<.05), week-specific global and pairwise differences were tested. Birth weight and risk of a small-for-gestational-age (SGA) neonate were secondary outcomes. All analyses were adjusted for maternal age, weight, height, parity, and racial-ethnic group and neonatal sex in a sensitivity analysis., Results: In 2,307 eligible women, 410 (17.8%) reported first-trimester bleeding, of whom 176 bled for 1 day and 234 bled for more than 1 day. Women with more than 1 day of bleeding demonstrated decreased fetal abdominal circumference from 34 to 39 weeks of gestation compared with women without bleeding. For women with more than 1 day of bleeding, compared with women without bleeding, estimated fetal weight was 68-107 g smaller from 35 to 39 weeks of gestation. Mean birth weight at term was 88 g smaller, confirming differences in calculated fetal weight, and SGA neonates were delivered to 148 (8.5%), 9 (5.7%), and 33 (15.7%) women in the no bleeding, 1 day, and more than 1 day of bleeding groups, respectively., Conclusion: More than 1 day of first-trimester vaginal bleeding was associated with smaller estimated fetal weight late in pregnancy driven by smaller abdominal circumference. The magnitude of decrease in birth weight was small, albeit comparable with observed decreases associated with maternal smoking. It remains unknown whether early pregnancy bleeding is associated with short-term or long-term morbidity and whether additional intervention would be of benefit., Clinical Trial Registration: ClinicalTrials.gov, NCT00912132.

Objective: This article aims to determine if the number of maternal ultrasound scans where the highest thermal (TI) or mechanical (MI) indices recorded during obstetrical ultrasound exceed 1.0 were associated with neonatal anthropometric measurements., Study Design: A prospective cohort of 2,334 nonobese low-risk pregnant women from 12 U.S. clinical sites underwent a total of six ultrasound scans, for which the highest TI and MI values were recorded. Neonatal anthropometric measurements were obtained within 12 to 24 hours of delivery. Multiple linear regression models adjusted for maternal race/ethnicity, body mass index, weight gain, and gestational age were used to examine associations between the number of maternal ultrasounds during gestation with a TI or MI exceeding 1.0 and the mean change in neonatal anthropometry., Results: Ultrasounds with TI or MI >1.0 were not associated with birth weight, neonatal length, nor head, chest, and abdominal circumferences. TI >1.0 was negatively associated with neonatal mid-upper arm and mid-upper thigh circumferences. MI >1.0 was negatively associated with neonatal skinfold measurements of the anterior thigh and triceps, and neonatal circumferences of the mid-upper thigh and umbilicus., Conclusion: Prenatal ultrasound examinations in which TI or MI intermittently exceeded 1.0 did not identify a pattern of alterations of birth size., Competing Interests: None., (Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.)

Prediction of preterm birth as well as characterizing the etiological factors affecting both the recurrence and incidence of preterm birth (defined as gestational age at birth ≤ 37 wk) are important problems in obstetrics. The National Institute of Child Health and Human Development (NICHD) consecutive pregnancy study recently examined this question by collecting data on a cohort of women with at least 2 pregnancies over a fixed time interval. Unfortunately, measurement error due to the dating of conception may induce sizable error in computing gestational age at birth. This article proposes a flexible approach that accounts for measurement error in gestational age when making inference. The proposed approach is a hidden Markov model that accounts for measurement error in gestational age by exploiting the relationship between gestational age at birth and birth weight. We initially model the measurement error as being normally distributed, followed by a mixture of normals that has been proposed on the basis of biological considerations. We examine the asymptotic bias of the proposed approach when measurement error is ignored and also compare the efficiency of this approach to a simpler hidden Markov model formulation where only gestational age and not birth weight is incorporated. The proposed model is compared with alternative models for estimating important covariate effects on the risk of subsequent preterm birth using a unique set of data from the NICHD consecutive pregnancy study., (Published 2018. This article is a U.S. Government work and is in the public domain in the USA.)

While the vast majority of genome size variation in plants is due to differences in repetitive sequence, we know little about how selection acts on repeat content in natural populations. Here we investigate parallel changes in intraspecific genome size and repeat content of domesticated maize (Zea mays) landraces and their wild relative teosinte across altitudinal gradients in Mesoamerica and South America. We combine genotyping, low coverage whole-genome sequence data, and flow cytometry to test for evidence of selection on genome size and individual repeat abundance. We find that population structure alone cannot explain the observed variation, implying that clinal patterns of genome size are maintained by natural selection. Our modeling additionally provides evidence of selection on individual heterochromatic knob repeats, likely due to their large individual contribution to genome size. To better understand the phenotypes driving selection on genome size, we conducted a growth chamber experiment using a population of highland teosinte exhibiting extensive variation in genome size. We find weak support for a positive correlation between genome size and cell size, but stronger support for a negative correlation between genome size and the rate of cell production. Reanalyzing published data of cell counts in maize shoot apical meristems, we then identify a negative correlation between cell production rate and flowering time. Together, our data suggest a model in which variation in genome size is driven by natural selection on flowering time across altitudinal clines, connecting intraspecific variation in repetitive sequence to important differences in adaptive phenotypes.

Objectives: To evaluate the frequency with which gestational weight gain and estimated fetal weight do not track across gestation and to assess the risk of small-for-gestational-age (SGA) and large-for-gestational-age (LGA) birth weight as a function of tracking., Methods: This study included a pregnancy cohort (2009-2013) of 2438 women from 4 racial/ethnic groups in the United States. We calculated race- and trimester-specific gestational weight gain and estimated fetal weight z scores. The prevalence of how often gestational weight gain and estimated fetal weight did not or did directly track was examined by grouping z scores into measure-specific categories (<-1 SD, -1 to + 1 SD, and >1 SD) and then examining 2-measure combinations. Trimester-specific relative risks for SGA and LGA births were estimated with a gestational weight gain and estimated fetal weight z score interaction. We estimated coefficients for selected gestational weight gain and estimated fetal weight values (-1 SD, 0 SD, and +1 SD) compared with the referent of 0 SD for both measures. Small and large for gestational age were calculated as birth weight below the 10th and at or above the 90th percentiles, respectively., Results: Gestational weight gain and estimated fetal weight were within 1 SD 55.5%, 51.5%, and 48.2% of the time in the first, second, and third trimesters, respectively. There was no significant interaction between gestational weight gain and estimated fetal weight on the risk of SGA in the first and second trimesters (interaction term P = .48; P = .79). In the third trimester, there was a significant interaction (P = .002), resulting in a 71% (95% confidence interval, 1.45-2.02) increased risk of SGA when estimated fetal weight was low and gestational weight gain was high. These relationships were similar for the risk of LGA., Conclusions: Deviations in either measure, even in the presence of average gestational weight gain or estimated fetal weight, still suggest an increased risk of SGA and LGA., (© 2017 by the American Institute of Ultrasound in Medicine.)

Gestational inflammation may contribute to brain abnormalities associated with childhood neuropsychiatric disorders. Limited knowledge exists regarding the associations of maternal cytokine levels during pregnancy with offspring neurocognitive development. We assayed the concentrations of five cytokines (interleukin (IL)-6, IL-1β, IL-8, tumor necrosis factor alpha (TNF-α), and IL-10) up to four times in the 2nd and 3rd trimesters of pregnancy using stored prenatal sera from 1366 participants in the New England Family Study (enrollment 1959-1966). Intelligence (IQ), academic achievement, and neuropsychological functioning of singleton offspring were assessed at age 7 years using standardized tests. We used linear mixed models with random effects to estimate the cumulative exposure to each cytokine during 2nd and 3rd trimesters, and then related cumulative cytokine exposure to a wide range of offspring neurocognitive outcomes. We found that children of women with higher levels of the pro-inflammatory cytokine, TNF-α, in the 2nd and 3rd trimesters had lower IQ (B = -2.51, 99% CI: -4.84,-0.18), higher problem scores in visual-motor maturity (B = 0.12, 99% CI: 0.001,0.24), and lower Draw-a-Person test scores (B = -1.28, 99% CI: -2.49,-0.07). Higher gestational levels of IL-8, another pro-inflammatory molecule, were associated with better Draw-a-Person test scores and tactile finger recognition scores. Other cytokines were not associated with our outcome of interest. The opposing directions of associations observed between TNF-α and IL-8 with childhood outcomes suggest pleiotropic effects of gestational inflammation across the domains of neurocognitive functioning. Although the path to psychopathological disturbances in children is no doubt multifactorial, our findings point to a potential role for immune processes in the neurocognitive development of children.

The incomplete informative cluster size problem is motivated by the NICHD Consecutive Pregnancies Study, aiming to study the relationship between pregnancy outcomes and parity. These pregnancy outcomes are potentially associated with the number of births over a woman's lifetime, resulting in an incomplete informative cluster size (censored at the end of the study window). We develop a pattern mixture model for informative cluster size by treating the lifetime number of births as a latent variable. We compare this approach with a simple alternative method that approximates the pattern mixture model. We show that the latent variable approach possesses good statistical properties for estimating both the mean trajectory of birthweight and the proportion of gestational hypertension with increasing parity.

Importance: Despite the increasing prevalence of pregravid obesity, systematic evaluation of the association of maternal obesity with fetal growth trajectories is lacking., Objective: To characterize differences in fetal growth trajectories between obese and nonobese pregnant women, and to identify the timing of any observed differences., Design, Setting, and Participants: The Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies-Singletons study enrolled cohorts of pregnant women at 12 US health care institutions. Obese women (with prepregnancy body mass index > 30) and nonobese women (prepregnancy body mass indexes, 19-29.9) without major chronic diseases were recruited between 8 weeks and 0 days' gestation and 13 weeks and 6 days' gestation. A mixed longitudinal randomization scheme randomized participants into 1 of 4 schedules for 2-dimensional and 3-dimensional ultrasonograms to capture weekly fetal growth data throughout the remainder of their pregnancies., Main Outcomes and Measures: On each ultrasonogram, fetal humerus length, femur length, biparietal diameter, head circumference, and abdominal circumference were measured. Fetal growth curves were estimated using linear mixed models with cubic splines. Median differences in the fetal measures at each gestational week of the obese and nonobese participants were examined using the likelihood ratio and Wald tests after adjustment for maternal characteristics., Results: The study enrolled 468 obese and 2334 nonobese women between 8 weeks and 0 days' gestation and 13 weeks and 6 days' gestation. After a priori exclusion criteria, 443 obese and 2320 nonobese women composed the final cohort. Commencing at 21 weeks' gestation, femur length and humerus length were significantly longer for fetuses of obese woman than those of nonobese women. Differences persisted in obese and nonobese groups through 38 weeks' gestation (median femur length, 71.0 vs 70.2 mm; P = .01; median humerus length, 62.2 vs 61.6 mm; P = .03). Averaged across gestation, head circumference was significantly larger in fetuses of obese women than those of nonobese women (P = .02). Fetal abdominal circumference was not greater in the obese cohort than in the nonobese cohort but was significantly larger than in fetuses of normal-weight women (with body mass indexes between 19.0-24.9) commencing at 32 weeks (median, 282.1 vs 280.2 mm; P = .04). Starting from 30 weeks' gestation, estimated fetal weight was significantly larger for the fetuses of obese women (median, 1512 g [95% CI, 1494-1530 g] vs 1492 g [95% CI, 1484-1499 g]) and the difference grew as gestational age increased. Birth weight was higher by almost 100 g in neonates born to obese women than to nonobese women (mean, 3373.2 vs 3279.5 g)., Conclusions and Relevance: As early as 32 weeks' gestation, fetuses of obese women had higher weights than fetuses of nonobese women. The mechanisms and long-term health implications of these findings are not yet established.

Many researchers in biology and medicine have focused on trying to understand biological rhythms and their potential impact on disease. A common biological rhythm is circadian, where the cycle repeats itself every 24 hours. However, a disturbance of the circadian pattern may be indicative of future disease. In this article, we develop new statistical methodology for assessing the degree of disturbance or irregularity in a circadian pattern for count sequences that are observed over time in a population of individuals. We develop a latent variable Poisson modeling approach with both circadian and stochastic short-term trend (autoregressive latent process) components that allow for individual variation in the degree of each component. A parameterization is proposed for modeling covariate dependence on the proportion of these two model components across individuals. In addition, we incorporate covariate dependence in the overall mean, the magnitude of the trend, and the phase-shift of the circadian pattern. Innovative Markov chain Monte Carlo sampling is used to carry out Bayesian posterior computation. Several variations of the proposed models are considered and compared using the deviance information criterion. We illustrate this methodology with longitudinal physical activity count data measured in a longitudinal cohort of adolescents.

Background: Maternal metabolic demands are much greater with twin gestations; however, there are no accepted recommendations for maternal weight gain in twin pregnancies. Objective: We assessed the association of maternal weight gain and fetal growth in dichorionic twins throughout pregnancy. Design: This was a prospective US cohort study ( n = 143, 2012-2013) of dichorionic twin pregnancies with known birth outcomes followed from enrollment (11-13 wk) and for ≤6 research visits throughout gestation. Maternal prepregnancy weight was self-reported, and current weight was measured at each research visit and abstracted from prenatal records. Fetal biometry was assessed by ultrasound at each research visit. Maternal weight and twin-pair fetal size trajectories across gestation were modeled. The adjusted associations between maternal weight gain from 0 to 13, 14 to 20, 21 to 27, and 28 to 34 wk and fetal growth at the subsequent week (i.e., 14, 21, 28, and 35 wk, respectively) were estimated with the use of linear regression. Results: The mean ± SD maternal weight gain from 0 to 13, 14 to 20, 21 to 27, and 28 to 34 wk was 2.8 ± 3.0 kg, 3.9 ± 1.2 kg, 3.8 ± 1.4 kg, and 4.4 ± 2.2 kg, respectively, with a total gain of 17.7 ± 7.4 kg. Maternal weight gain from 0 to 13 wk (first trimester) was not associated with fetal size at 14 wk. Maternal weight gain from 14 to 20 and 21 to 27 wk (second trimester) was significantly associated with increased fetal weight at 21 wk [increase of 10.5 g/kg maternal weight gain (95% CI: 1.2, 19.8 g)] and 28 wk [increase of 21.3 g/kg maternal weight gain (95% CI: 0.6, 42.0 g)]. Maternal weight gain from 14 to 20 wk was associated with increased twin abdominal circumference (AC) and biparietal diameter at 21 wk. Maternal weight gain from 21 to 27 wk was associated with increased femur and humerus lengths at 28 wk. Conclusion: Maternal weight gain was associated with dichorionic twin fetal growth in the second trimester only, driven by an association with AC earlier in second trimester and long bones later in the second trimester., (© 2017 American Society for Nutrition.)

Background: Inadequate or excessive total gestational weight gain is associated with increased risks of small- and large-for-gestational-age births, respectively, but evidence is sparse regarding overall and trimester-specific patterns of gestational weight gain in relation to these risks. Characterizing the interrelationship between patterns of gestational weight gain across trimesters can reveal whether the trajectory of gestational weight gain in the first trimester sets the path for gestational weight gain in subsequent trimesters, thereby serving as an early marker for at-risk pregnancies., Objective: We sought to describe overall trajectories of gestational weight gain across gestation and assess the risk of adverse birthweight outcomes associated with the overall trajectory and whether the timing of gestational weight gain (first vs second/third trimester) is differentially associated with adverse outcomes., Study Design: We conducted a secondary analysis of a prospective cohort of 2802 singleton pregnancies from 12 US prenatal centers (2009 through 2013). Small and large for gestational age were calculated using sex-specific birthweight references <5th, <10th, or ≥90th percentiles, respectively. At each of the research visits, women's weight was measured following a standardized anthropometric protocol. Maternal weight at antenatal clinical visits was also abstracted from the prenatal records. Semiparametric, group-based, latent class, trajectory models estimated overall gestational weight gain and separate first- and second-/third-trimester trajectories to assess tracking. Robust Poisson regression was used to estimate the relative risk of small- and large-for-gestational-age outcomes by the probability of trajectory membership. We tested whether relationships were modified by prepregnancy body mass index., Results: There were 2779 women with a mean of 15 (SD 5) weights measured across gestation. Four distinct gestational weight gain trajectories were identified based on the lowest Bayesian information criterion value, classifying 10.0%, 41.8%, 39.2%, and 9.0% of the population from lowest to highest weight gain trajectories, with an inflection at 14 weeks. The average rate in each trajectory group from lowest to highest for 0-<14 weeks was -0.20, 0.04, 0.21, and 0.52 kg/wk and for 14-39 weeks was 0.29, 0.48, 0.63, and 0.79 kg/wk, respectively; the second lowest gaining trajectory resembled the Institute of Medicine recommendations and was designated as the reference with the other trajectories classified as low, moderate-high, or high. Accuracy of assignment was assessed and found to be high (median posterior probability 0.99, interquartile range 0.99-1.00). Compared with the referent trajectory, a low overall trajectory, but not other trajectories, was associated with a 1.55-fold (95% confidence interval, 1.06-2.25) and 1.58-fold (95% confidence interval, 0.88-2.82) increased risk of small-for-gestational-age <10th and <5th, respectively, while a moderate-high and high trajectory were associated with a 1.78-fold (95% confidence interval, 1.31-2.41) and 2.45-fold (95% confidence interval, 1.66-3.61) increased risk of large for gestational age, respectively. In a separate analysis investigating whether early (<14 weeks) gestational weight gain tracked with later (≥14 weeks) gestational weight gain, only 49% (n = 127) of women in the low first-trimester trajectory group continued as low in the second/third trimester, and had a 1.59-fold increased risk of small for gestational age; for the other 51% (n = 129) of women without a subsequently low second-/third-trimester gestational weight gain trajectory, there was no increased risk of small for gestational age (relative risk, 0.75; 95% confidence interval, 0.47-1.38). Prepregnancy body mass index did not modify the association between gestational weight gain trajectory and small for gestational age (P = 0.52) or large for gestational age (P = .69)., Conclusion: Our findings are reassuring for women who experience weight loss or excessive weight gain in the first trimester; however, the risk of small or large for gestational age is significantly increased if women gain weight below or above the reference trajectory in the second/third trimester., (Published by Elsevier Inc.)

Background: Self-report is often used in identifying gestational diabetes events in epidemiologic studies; however, validity data are limited, with little to no data on self-reported severity or treatment., Methods: We aimed to assess the validity of self-reported gestational diabetes diagnosis and evaluate the accuracy of glucose diagnosis results and gestational diabetes treatment self-reported at 6-week postpartum. Data were from 82 and 83 women with and without gestational diabetes, respectively, within the prospective National Institute Child Health and Human Development Fetal Growth Studies-Singletons (2009-2013). Medical record data were considered the gold standard., Results: Sensitivity was 95% (95% confidence interval [CI] = 88, 98), and specificity was 100% (95% CI = 96, 100); four women with gestational diabetes incorrectly reported not having the disease, and none of the women without gestational diabetes reported having gestational diabetes. Sensitivity did not vary substantially across maternal characteristics including race/ethnicity. For women who attempted to recall their values (84/159 women), self-reported glucose challenge test results did not differ from the medical records (median difference: 0; interquartile range: 0-0 mg/dl). Medical records indicated that 42 (54%) of 78 women with confirmed gestational diabetes were treated by diet only and 33 (42%) were treated by medication. All 42 women with diet-treated gestational diabetes correctly reported having had diet and lifestyle modification, and 28 (85%) of 33 women with medication-treated gestational diabetes indicated postpartum that they had medication treatment., Conclusions: At 6-week postpartum, regardless of race/ethnicity or socioeconomic status, women accurately recalled whether they had gestational diabetes and, as applicable, their treatment method.

We described physical activity measures and hourly patterns in patients with chronic obstructive pulmonary disease (COPD) after stratification for generic and COPD-specific characteristics and, based on multiple physical activity measures, we identified clusters of patients. In total, 1001 patients with COPD (65% men; age, 67 years; forced expiratory volume in the first second [FEV 1 ], 49% predicted) were studied cross-sectionally. Demographics, anthropometrics, lung function and clinical data were assessed. Daily physical activity measures and hourly patterns were analysed based on data from a multisensor armband. Principal component analysis (PCA) and cluster analysis were applied to physical activity measures to identify clusters. Age, body mass index (BMI), dyspnoea grade and ADO index (including age, dyspnoea and airflow obstruction) were associated with physical activity measures and hourly patterns. Five clusters were identified based on three PCA components, which accounted for 60% of variance of the data. Importantly, couch potatoes (i.e. the most inactive cluster) were characterised by higher BMI, lower FEV 1 , worse dyspnoea and higher ADO index compared to other clusters ( p < 0.05 for all). Daily physical activity measures and hourly patterns are heterogeneous in COPD. Clusters of patients were identified solely based on physical activity data. These findings may be useful to develop interventions aiming to promote physical activity in COPD.

Joint modeling and within-cluster resampling are two approaches that are used for analyzing correlated data with informative cluster sizes. Motivated by a developmental toxicity study, we examined the performances and validity of these two approaches in testing covariate effects in generalized linear mixed-effects models. We show that the joint modeling approach is robust to the misspecification of cluster size models in terms of Type I and Type II errors when the corresponding covariates are not included in the random effects structure; otherwise, statistical tests may be affected. We also evaluate the performance of the within-cluster resampling procedure and thoroughly investigate the validity of it in modeling correlated data with informative cluster sizes. We show that within-cluster resampling is a valid alternative to joint modeling for cluster-specific covariates, but it is invalid for time-dependent covariates. The two methods are applied to a developmental toxicity study that investigated the effect of exposure to diethylene glycol dimethyl ether.

Objective: To compare the accuracy of a new formula with one developed in 1984 (and still in common use) and to develop and compare racial and ethnic-specific and racial and ethnic-neutral formulas., Methods: The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-Singletons was a prospective cohort study that recruited women in four self-reported racial-ethnic groups-non-Hispanic black, Hispanic, non-Hispanic white, and Asian-with singleton gestations from 12 U.S. centers (2009-2013). Women with a certain last menstrual period confirmed by first-trimester ultrasonogram had longitudinal fetal measurements by credentialed study ultrasonographers blinded to the gestational age at their five follow-up visits. Regression analyses were performed with linear mixed models to develop gestational age estimating formulas. Repeated cross-validation was used for validation. The estimation error was defined as the mean squared difference between the estimated and observed gestational age and was used to compare the formulas' accuracy., Results: The new formula estimated the gestational age (±2 SD) within ±7 days from 14 to 20 weeks of gestation, ±10 days from 21 to 27 weeks of gestation, and ±17 days from 28 to 40 weeks of gestation. The new formula performed significantly better than a formula developed in 1984 with an estimation error of 10.4 compared with 11.2 days from 21 to 27 weeks of gestation and 17.0 compared with 19.8 days at 28-40 weeks of gestation, respectively. Racial and ethnic-specific formulas did not outperform the racial and ethnic-neutral formula., Conclusion: The NICHD gestational age estimation formula is associated with smaller errors than a well-established historical formula. Racial and ethnic-specific formulas are not superior to a racial-ethnic-neutral one.

Background: The effect of maternal mood disorders on neonatal measurements is not well-defined. The Fetal Growth Studies-Singletons provide a unique opportunity to evaluate the relationship between perceived maternal stress and neonatal growth measurements., Objective: The purpose of this study was to determine whether perceived maternal stress during pregnancy is associated with anthropometric measurements in the neonate., Study Design: This analysis was based on a prospective, multicenter longitudinal study of fetal growth. Women 18-40 years old with a body mass index of 19.0-29.9 kg/m 2 were screened at 8+0 to 13+6 weeks gestation for low-risk status associated with optimal fetal growth (eg, healthy, nonsmoking) and underwent serial sonographic examination at 6 study visits throughout gestation. At each study visit, women completed the Cohen's Perceived Stress Survey, which could have a score that ranges from 0-40. We used a latent class trajectory model to identify distinct groupings (ie, classes) of the Perceived Stress Survey trajectories over pregnancy. Trend analysis was used to determine whether neonatal measurements including birthweight, length, head circumference, and abdominal circumference differed by Perceived Stress Survey class and whether this relationship was modified by maternal race/ethnicity, after adjustment for gestational age at delivery, maternal height, age, and parity., Results: Of the 2334 women enrolled in the study, 1948 women had complete neonatal anthropometry and were included in the analysis. Latent class analysis identified 3 Perceived Stress Survey trajectory classes, with mean Perceived Stress Survey scores of 2.82 (low), 7.95 (medium), and 14.80 (high). Neonatal anthropometric measures of birthweight, length, head circumference and abdominal circumference were similar (P=.78, =.10, =.18, and =.40 respectively), regardless of the participants' Perceived Stress Survey class. There was no effect modification by maternal race/ethnicity., Conclusion: Neonatal measurements did not differ by levels of perceived stress among low-risk pregnant women., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Children raised in economically disadvantaged households face increased risks of poor health in adulthood, suggesting that inequalities in health have early origins. From the child's perspective, exposure to economic hardship may begin as early as conception, potentially via maternal neuroendocrine-immune responses to prenatal stressors, which adversely impact neurodevelopment. Here we investigate whether socioeconomic disadvantage is associated with gestational immune activity and whether such activity is associated with abnormalities among offspring during infancy. We analyzed concentrations of five immune markers (IL-1β, IL-6, IL-8, IL-10, and TNF-α) in maternal serum from 1,494 participants in the New England Family Study in relation to the level of maternal socioeconomic disadvantage and their involvement in offspring neurologic abnormalities at 4 mo and 1 y of age. Median concentrations of IL-8 were lower in the most disadvantaged pregnancies [-1.53 log(pg/mL); 95% CI: -1.81, -1.25]. Offspring of these pregnancies had significantly higher risk of neurologic abnormalities at 4 mo [odds ratio (OR) = 4.61; CI = 2.84, 7.48] and 1 y (OR = 2.05; CI = 1.08, 3.90). This higher risk was accounted for in part by fetal exposure to lower maternal IL-8, which also predicted higher risks of neurologic abnormalities at 4 mo (OR = 7.67; CI = 4.05, 14.49) and 1 y (OR = 2.92; CI = 1.46, 5.87). Findings support the role of maternal immune activity in fetal neurodevelopment, exacerbated in part by socioeconomic disadvantage. This finding reveals a potential pathophysiologic pathway involved in the intergenerational transmission of socioeconomic inequalities in health., Competing Interests: The authors declare no conflict of interest.

Background: Both short and prolonged sleep duration have been linked to impaired glucose metabolism. Sleep patterns change during pregnancy, but prospective data are limited on their relation to gestational diabetes., Objective: We sought to prospectively examine the trimester-specific (first and second trimester) association between typical sleep duration in pregnancy and subsequent risk of gestational diabetes, as well as the influence of compensatory daytime napping on this association., Study Design: In the prospective, multiracial Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies-Singleton Cohort, 2581 pregnant women reported their typical sleep duration and napping frequency in the first and second trimesters. Diagnosis of gestational diabetes (n = 107; 4.1%) was based on medical records review. Adjusted relative risks with 95% confidence intervals for gestational diabetes were estimated with Poisson regression, adjusting for demographics, prepregnancy body mass index, and other risk factors., Results: From the first and second trimester, sleep duration and napping frequency declined. Sleeping duration in the second but not first trimester was significantly related to risk of gestational diabetes. The association between second-trimester sleep and gestational diabetes differed by prepregnancy obesity status (P for interaction = .04). Among nonobese but not obese women, both sleeping >8-9 hours or <8-9 hours were significantly related to risk of gestational diabetes: 5-6 hours (adjusted relative risk, 2.52; 95% confidence interval, 1.27-4.99); 7 hours (adjusted relative risk, 2.01; 95% confidence interval, 1.09-3.68); or ≥10 hours (adjusted relative risk, 2.17; 95% confidence interval, 1.01-4.67). Significant effect modification by napping frequency was also observed in the second trimester (P for interaction = .03). Significant and positive association between reduced sleep (5-7 hours) and gestational diabetes was observed among women napping rarely/never (adjusted relative risk, 2.48; 95% confidence interval, 1.20-5.13), whereas no comparable associations were observed among women napping most/sometimes., Conclusion: Our data suggest a U-shaped association between sleep duration and gestational diabetes, and that napping and prepregnancy obesity status may modify this association., (Published by Elsevier Inc.)

Aims/hypothesis: The aim of this study was to prospectively and longitudinally investigate maternal iron status during early to mid-pregnancy, and subsequent risk of gestational diabetes mellitus (GDM), using a comprehensive panel of conventional and novel iron biomarkers., Methods: A case-control study of 107 women with GDM and 214 controls (matched on age, race/ethnicity and gestational week during blood collection) was conducted within the the Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies-Singleton Cohort (2009-2013), a prospective and multiracial pregnancy cohort. Plasma hepcidin, ferritin and soluble transferrin receptor (sTfR) were measured and sTfR:ferritin ratio was derived, twice before GDM diagnosis (gestational weeks 10-14 and 15-26) and at weeks 23-31 and 33-39. GDM diagnosis was ascertained from medical records. Adjusted ORs (aORs) for GDM were estimated using conditional logistic regression analysis, adjusting for demographics, prepregnancy BMI and other major risk factors., Results: Hepcidin concentrations during weeks 15-26 were 16% higher among women with GDM vs controls (median 6.4 vs 5.5 ng/ml; p = 0.02 ), and were positively associated with GDM risk; the aOR (95% CI) for highest vs lowest quartile was 2.61 (1.07, 6.36). Ferritin levels were also positively associated with GDM risk; the aOR (95% CI) for highest vs lowest quartile was 2.43 (1.12, 5.28) at weeks 10-14 and 3.95 (1.38, 11.30) at weeks 15-26. The sTfR:ferritin ratio was inversely related to GDM risk; the aOR (95% CI) for highest vs lowest quartile was 0.33 (0.14, 0.80) at weeks 10-14 and 0.15 (0.05, 0.48) at weeks 15-26., Conclusions/interpretation: Our findings suggest that elevated iron stores may be involved in the development of GDM from as early as the first trimester. This raises potential concerns for the recommendation of routine iron supplementation among iron-replete pregnant women.

Longitudinal monitoring of biomarkers is often helpful for predicting disease or a poor clinical outcome. In this paper, We consider the prediction of both large and small-for-gestational-age births using longitudinal ultrasound measurements, and attempt to identify subgroups of women for whom prediction is more (or less) accurate, should they exist. We propose a tree-based approach to identifying such subgroups, and a pruning algorithm which explicitly incorporates a desired type-I error rate, allowing us to control the risk of false discovery of subgroups. The proposed methods are applied to data from the Scandinavian Fetal Growth Study, and are evaluated via simulations.

Aims/hypothesis: Depression and glucose intolerance commonly co-occur among non-pregnant individuals; however, the temporal relationship between gestational diabetes (GDM) and depression during pregnancy and the postpartum period is less understood. Our objective was to assess longitudinal associations between depression early in pregnancy and GDM risk, as well as GDM and subsequent risk of postpartum depression., Methods: Data came from the prospective National Institute of Child Health and Human Development Fetal Growth Studies-Singleton cohort (2009-2013), and had been collected at 12 US clinical centres. Pregnant women without psychiatric disorders, diabetes or other chronic conditions before pregnancy were followed throughout pregnancy (n = 2477). Only women with GDM and matched controls were followed up at 6 weeks postpartum (n = 162). GDM was ascertained by a review of the medical records. Depression was assessed in the first (8-13 gestational weeks) and second (16-22 weeks) trimesters and at 6 weeks postpartum using the Edinburgh Postnatal Depression Scale. Postpartum depression was defined as a depressive symptom score ≥10 or antidepressant medicine use after delivery. RR and 95% CI were adjusted for pre-pregnancy BMI and other risk factors. GDM was considered to be the outcome for the first set of analyses, with depression in the first and second trimesters as the exposures. Postpartum depression was considered as the outcome for the second set of analyses, with GDM as the exposure., Results: Overall, comparing the highest and lowest quartiles of first-trimester depression scores, the scores from the highest quartile were associated with a significant twofold (95% CI 1.06, 3.78) increased risk of GDM, but this was attenuated to 1.72-fold (95% CI 0.92, 3.23) after adjustment; the second-trimester results were similar. The risk was stronger and significant in both trimesters among non-obese women (p for trend 0.02 and 0.01, respectively), but null for obese women. Women with persistently high depression scores in both trimesters had the greatest risk of GDM (highest vs lowest quartile in both trimesters: adjusted RR 3.21, 95% CI 1.00, 10.28). GDM was associated with an adjusted 4.62-fold (95% CI 1.26, 16.98) increased risk of subsequent postpartum depression., Conclusions/interpretation: This prospective study demonstrates a modest association between depressive symptoms early in pregnancy and an increased risk of incident GDM, as well as between GDM and subsequent postpartum depression risk, highlighting pregnancy and the postpartum period as an important susceptible time window during the life course for the interplay between depression and glucose intolerance phenotypes. GDM risk associated with elevated depressive symptoms was particularly high among non-obese women and women with symptoms persisting across the first two trimesters of pregnancy., Competing Interests: Duality of interest statement The authors declare that there is no duality of interest associated with this manuscript.

The insulin-like growth factor (IGF) axis may be implicated in glucose homeostasis, but its longitudinal profile across gestation in relation to the development of gestational diabetes mellitus (GDM) is largely unknown. We prospectively investigated IGF axis biomarkers in early-to-midpregnancy in relation to subsequent GDM risk in a case-control study of 107 case subjects with GDM and 214 control subjects without GDM, with blood sample collection at gestational weeks 10-14, 15-26, 23-31, and 33-39. Conditional logistic regression was used, adjusting for major risk factors including prepregnancy BMI. Plasma IGF-I and IGF binding protein 3 (IGFBP-3) concentrations and molar ratio of IGF-I to IGFBP-3 increased, whereas IGFBP-2 decreased throughout pregnancy. At gestational weeks 10-14, both IGF-I and IGF-I/IGFBP-3 were positively associated with GDM risk; adjusted odds ratio (OR) comparing the highest versus lowest quartile (OR Q4-Q1 ) was 2.93 (95% CI 1.18, 7.30) for IGF-I and 3.31 (1.10, 9.98) for IGF-I/IGFBP-3. In contrast, higher IGFBP-2 levels were related to a substantially lower risk of GDM (OR Q4-Q1 0.04 [0.01, 0.06]). Similar results were observed at gestational weeks 15-26. In sum, the IGF axis, IGFBP-2 in particular, may be implicated in the pathogenesis of GDM, with significant associations and incremental predictive value detected as early as gestational weeks 10-14, ∼10-18 weeks earlier before GDM is typically screened for., (© 2016 by the American Diabetes Association.)

Objective: To assess differences in small-for-gestational age (SGA) classifications for the detection of neonates with increased perinatal mortality risk among obese women and subsequently assess the association between prepregnancy body mass index (BMI) status and SGA., Design: Hospital-based cohort., Setting: Twelve US clinical centres (2002-08)., Population: A total of 114 626 singleton, nonanomalous pregnancies., Methods: Data were collected using electronic medical record abstraction. Relative risks (RR) with 95% CI were estimated., Main Outcome Measures: SGA trends (birthweight < 10th centile) classified using population-based (SGA POP ), intrauterine (SGA IU ) and customised (SGA CUST ) references were assessed. The SGA-associated perinatal mortality risk was estimated among obese women. Using the SGA method most associated with perinatal mortality, the association between prepregnancy BMI and SGA was estimated., Results: The overall perinatal mortality prevalence was 0.55% and this increased significantly with increasing BMI (P < 0.01). Among obese women, SGA IU detected the highest proportion of perinatal mortality cases (2.49%). Perinatal mortality was 5.32 times (95% CI 3.72-7.60) more likely among SGA IU neonates than non-SGA IU neonates. This is in comparison with the 3.71-fold (2.49-5.53) and 4.81-fold (3.41-6.80) increased risk observed when SGA POP and SGA CUST were used, respectively. Compared with women of normal weight, overweight women (RR = 0.82, 95% CI 0.78-0.86) and obese women (RR = 0.80; 95% CI 0.75-0.83) had a lower risk for delivering an SGA IU neonate., Conclusion: Among obese women, the intrauterine reference best identified neonates at risk of perinatal mortality. Based on SGA IU , SGA is less common among obese women but these SGA babies are at a high risk of death and remain an important group for surveillance., Tweetable Abstract: SGA is less common among obese women but these SGA babies are at a high risk of death., (Published 2016. This article is a U.S. Government work and is in the public domain in the USA.)

In longitudinal studies, it is sometimes of interest to estimate the distribution of the time a longitudinal process takes to traverse from one threshold to another. For example, the distribution of the time it takes a woman's cervical dilation to progress from 3 to 4 cm can aid the decision-making of obstetricians as to whether a stalled labor should be allowed to proceed or stopped in favor of other options. Often researchers treat this type of data structure as interval censored and employ traditional survival analysis methods. However, the traditional interval censoring approaches are inefficient in that they do not use all of the available data. In this paper, we propose utilizing a longitudinal threshold model to estimate the distribution of the elapsed time between two thresholds of the longitudinal process from repeated measurements. We extend this modeling framework to be used with multiple thresholds. A Wiener process under the first hitting time framework is used to represent survival distribution. We demonstrate our model through simulation studies and an analysis of data from the Consortium on Safe Labor study. Published 2016. This article is a U.S. Government work and is in the public domain in the USA., (Published 2016. This article is a U.S. Government work and is in the public domain in the USA.)

Predicting binary events such as newborns with large birthweight is important for obstetricians in their attempt to reduce both maternal and fetal morbidity and mortality. Such predictions have been a challenge in obstetric practice, where longitudinal ultrasound measurements taken at multiple gestational times during pregnancy may be useful for predicting various poor pregnancy outcomes. The focus of this article is on developing a flexible class of joint models for the multivariate longitudinal ultrasound measurements that can be used for predicting a binary event at birth. A skewed multivariate random effects model is proposed for the ultrasound measurements, and the skewed generalized t-link is assumed for the link function relating the binary event and the underlying longitudinal processes. We consider a shared random effect to link the two processes together. Markov chain Monte Carlo sampling is used to carry out Bayesian posterior computation. Several variations of the proposed model are considered and compared via the deviance information criterion, the logarithm of pseudomarginal likelihood, and with a training-test set prediction paradigm. The proposed methodology is illustrated with data from the NICHD Successive Small-for-Gestational-Age Births study, a large prospective fetal growth cohort conducted in Norway and Sweden., (© 2016, The International Biometric Society.)

Two lines of Zea mays were developed as a short-generation model for maize. The Fast-Flowering Mini-Maize (FFMM) lines A and B are robust inbred lines with a significantly shorter generation time, much smaller stature, and better greenhouse adaptation than traditional maize varieties. Five generations a year are typical. FFMM is the result of a modified double-cross hybrid between four fast-flowering lines: Neuffer's Early ACR (full color), Alexander's Early Early Synthetic, Tom Thumb Popcorn, and Gaspe Flint, followed by selection for early flowering and desirable morphology throughout an 11-generation selfing regime. Lines A and B were derived from different progeny of the initial hybrid, and crosses between Mini-Maize A and B exhibit heterosis. The ancestry of each genomic region of Mini-Maize A and B was inferred from the four founder populations using genotyping by sequencing. Other genetic and genomic tools for these lines include karyotypes for both lines A and B, kernel genetic markers y1 (white endosperm) and R1-scm2 (purple endosperm and embryo) introgressed into Mini-Maize A, and ∼24× whole-genome resequencing data for Mini-Maize A., (Copyright © 2016 by the Genetics Society of America.)

Objectives: To report on the ultrasound quality assurance program for the National Institute of Child Health and Human Development Fetal Growth Studies and describe both its advantages and generalizability., Methods: After training on an ultrasound system and software, research sonographers were expected to capture blank (unmeasured) images in triplicate for crown-rump length, biparietal diameter, head circumference, abdominal circumference, and femur length. A primary expert sonographer was designated and validated. A 5% sample (n = 740 of 14,785 scans) was randomly selected in 3 distinct rounds from within strata of maternal body mass index (round 1 only), gestational age, and research site. Unmeasured images were extracted from selected scans and measured with the ultrasound software by an expert sonographer. Correlations and coefficients of variation (CVs) were calculated, and the within-measurement standard deviation (ie, technical error of the measurement), was calculated., Results: The reliability between the site sonographers and the expert was high, with correlations exceeding 0.99 for all dimensions in all rounds. The CV % values showed low variability, with the percentage differences being less than 2%, except for abdominal circumference in rounds 2 and 3, in which it averaged about 3%. Correlations remained high (>0.90) with increasing fetal size; there was a monotonic increase in technical errors of the measurement but without a corresponding increase in the CV %., Conclusions: Using rigorous procedures for training sonographers, coupled with quality assurance oversight, we determined that the measurements acquired longitudinally for singletons are both accurate and reliable for establishment of an ultrasound standard for fetal growth.

Background: Systematic evaluation and estimation of growth trajectories in twins require ultrasound measurements across gestation that are performed in controlled clinical settings. Currently, there are few such data for contemporary populations. There is also controversy about whether twin fetal growth should be evaluated with the use of the same benchmarks as singleton growth., Objectives: Our objective was to define the trajectory of fetal growth in dichorionic twins empirically using longitudinal 2-dimensional ultrasonography and to compare the fetal growth trajectories for dichorionic twins with those based on a growth standard that was developed by our group for singletons., Study Design: A prospective cohort of 171 women with twin gestations was recruited from 8 US sites from 2012-2013. After an initial sonogram at 11 weeks 0 days-13 weeks 6 days of gestation during which dichorionicity was confirmed, women were assigned randomly to 1 of 2 serial ultrasonography schedules. Growth curves and percentiles were estimated with the use of linear mixed models with cubic splines. Percentiles were compared statistically at each gestational week between the twins and 1731 singletons, after adjustment for maternal age, race/ethnicity, height, weight, parity, employment, marital status, insurance, income, education, and infant sex. Linear mixed models were used to test for overall differences between the twin and singleton trajectories with the use of likelihood ratio tests of interaction terms between spline mean structure terms and twin-singleton indicator variables. Singleton standards were weighted to correspond to the distribution of maternal race in twins. For those ultrasound measurements in which there were significant global tests for differences between twins and singletons, we tested for week-specific differences using Wald tests that were computed at each gestational age. In a separate analysis, we evaluated the degree of reclassification in small for gestational age, which was defined as <10th percentile that would be introduced if fetal growth estimation for twins was based on an unweighted singleton standard., Results: Women underwent a median of 5 ultrasound scans. The 50th percentile abdominal circumference and estimated fetal weight trajectories of twin fetuses diverged significantly beginning at 32 weeks of gestation; biparietal diameter in twins was smaller from 34-36 weeks of gestation. There were no differences in head circumference or femur length. The mean head circumference/abdominal circumference ratio was progressively larger for twins compared with singletons beginning at 33 weeks of gestation, which indicated a comparatively asymmetric growth pattern. At 35 weeks of gestation, the average gestational age at delivery for twins, the estimated fetal weights for the 10th, 50th, and 90th percentiles were 1960, 2376, and 2879 g for dichorionic twins, respectively, and 2180, 2567, and 3022 g for the singletons, respectively. At 32 weeks of gestation, the initial week when the mean estimated fetal weight for twins was smaller than that of singletons, 34% of twins would be classified as small for gestational age with the use of a singleton, non-Hispanic white standard. By 35 weeks of gestation, 38% of twins would be classified as small for gestational age., Conclusion: The comparatively asymmetric growth pattern in twin gestations, initially evident at 32 weeks of gestation, is consistent with the concept that the intrauterine environment becomes constrained in its ability to sustain growth in twin fetuses. Near term, nearly 40% of twins would be classified as small for gestational age based on a singleton growth standard., (Published by Elsevier Inc.)

Objective: Serious crashes are more likely when teenage drivers have teenage passengers. One likely source of this increased risk is social influences on driving performance. This driving simulator study experimentally tested the effects of peer influence (i.e., risk-accepting compared to risk-averse peer norms reinforced by pressure) on the driving risk behavior (i.e., risky driving behavior and inattention to hazards) of male teenagers. It was hypothesized that peer presence would result in greater driving risk behavior (i.e., increased driving risk and reduced latent hazard anticipation), and that the effect would be greater when the peer was risk-accepting., Methods: Fifty-three 16- and 17-year-old male participants holding a provisional U.S., State of Michigan driver license were randomized to either a risk-accepting or risk-averse condition. Each participant operated a driving simulator while alone and separately with a confederate peer passenger. The simulator world included scenarios designed to elicit variation in driving risk behavior with a teen passenger present in the vehicle., Results: Significant interactions of passenger presence (passenger present vs. alone) by risk condition (risk-accepting vs. risk-averse) were observed for variables measuring: failure to stop at yellow light intersections (Incident Rate Ratio (IRR)=2.16; 95% Confidence Interval [95CI]=1.06, 4.43); higher probability of overtaking (IRR=10.17; 95CI=1.43, 73.35); shorter left turn latency (IRR=0.43; 95CI=0.31,0.60); and, failure to stop at an intersection with an occluded stop sign (IRR=7.90; 95CI=2.06,30.35). In all cases, greater risky driving by participants was more likely with a risk-accepting passenger versus a risk-averse passenger present and a risk-accepting passenger present versus driving alone., Conclusions: Exposure of male teenagers to a risk-accepting confederate peer passenger who applied peer influence increased simulated risky driving behavior compared with exposure to a risk-averse confederate peer passenger or driving alone. These results are consistent with the contention that variability in teenage risky driving is in part explained by social influences.

Background: There has been concern that low gestational weight gain may cause poor fetal neurodevelopment., Methods: The association between maternal weight gain and child IQ was examined using serial antenatal weight measurements (median 12) from a prospective cohort of non-obese Scandinavian women (1986-1988). Linear mixed models with piecewise regression were used to estimate participants' (n=552) trimester-specific average rate of weight gain. Linear regression was used to assess the association between weight gain and children's (n=344) full-scale, performance and verbal IQ measured at age 5 using the Wechsler Preschool and Primary Scales of Intelligence-Revised., Results: Children born to mothers who gained below versus within the 2nd trimester 2009 recommendations tended to have lower IQ scores (Full-scale: 106.6 (SD 15.1) vs 110.2 (15.2), p=0.04; verbal: 102.5 (14.3) vs 105.0 (14.9), p=0.10; performance: 109.5 (15.4) vs 113.4 (14.5), p=0.03). After adjustment there were no differences in child IQ by weight gain adequacy (full-scale: βbelow=-1.1 (95% CI -5.1 to 2.9), βabove=1.5 (-3.8 to 6.8); verbal: βbelow=-0.2 (-3.1 to 2.6), βabove=1.8 (-3.6 to 7.3); performance βbelow=-1.2 (-4.6 to 2.2), βabove=1.0 (-4.6 to 6.7)). No differences were observed based on 3rd trimester adequacy. No differences were observed in IQ scores by quintile of weight gain for any trimester, particularly after adjustment for maternal IQ., Conclusions: Our findings are reassuring that among normal weight women, pregnancy weight gain is not associated with child cognitive development. Further investigation should be conducted in contemporary cohorts that also include obese mothers, who are at the greatest risk for low weight gain., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/)

Pooling, or physically mixing biospecimens, prior to evaluating biomarkers dramatically reduces biomarker evaluation cost, reduces the quantity of biospecimens required of each individual, and may reduce the percentage of laboratory measurements below the lower limit of detection. Motivated by a case-control study on miscarriage (binary outcome) and cytokines (continuous exposures), we are interested in estimating parameters in a logistic regression, where individuals with the same disease status (with or without a miscarriage) are paired and their pooled cytokine concentrations are assessed. Previous research has proposed a set-based logistic model to evaluate the relationship between a disease and pooled exposures. While the set-based logistic model is very useful for estimating main effects, it cannot estimate interactions of continuous exposures when both are measured in pools. Therefore, we propose using the expectation maximization (EM) algorithm to obtain estimators of all parameters in logistic regression model, including interactions effects. Using a simulation study, we present comparisons of efficiency under different scenarios where exposures have been measured in pools and individually. Our simulations show that randomly sampling half of the available biospecimens has less efficiency than pooling pairs of biospecimens stratified by disease status. The EM algorithm provides a method for estimating interaction effects when biospecimens have already been pooled for other reasons such as the gain in efficiency for estimating main effects demonstrated by previous research. This manuscript demonstrates that the EM algorithm offers a promising approach to estimate interaction effects of pooled biospecimens., (Copyright © 2015 John Wiley & Sons, Ltd.)

The ancestral centromeres of maize contain long stretches of the tandemly arranged CentC repeat. The abundance of tandem DNA repeats and centromeric retrotransposons (CR) has presented a significant challenge to completely assembling centromeres using traditional sequencing methods. Here, we report a nearly complete assembly of the 1.85 Mb maize centromere 10 from inbred B73 using PacBio technology and BACs from the reference genome project. The error rates estimated from overlapping BAC sequences are 7 × 10(-6) and 5 × 10(-5) for mismatches and indels, respectively. The number of gaps in the region covered by the reassembly was reduced from 140 in the reference genome to three. Three expressed genes are located between 92 and 477 kb from the inferred ancestral CentC cluster, which lies within the region of highest centromeric repeat density. The improved assembly increased the count of full-length CR from 5 to 55 and revealed a 22.7 kb segmental duplication that occurred approximately 121,000 years ago. Our analysis provides evidence of frequent recombination events in the form of partial retrotransposons, deletions within retrotransposons, chimeric retrotransposons, segmental duplications including higher order CentC repeats, a deleted CentC monomer, centromere-proximal inversions, and insertion of mitochondrial sequences. Double-strand DNA break (DSB) repair is the most plausible mechanism for these events and may be the major driver of centromere repeat evolution and diversity. In many cases examined here, DSB repair appears to be mediated by microhomology, suggesting that tandem repeats may have evolved to efficiently repair frequent DSBs in centromeres.

In the context of group testing screening, McMahan, Tebbs, and Bilder (2012, Biometrics 68, 287-296) proposed a two-stage procedure in a heterogenous population in the presence of misclassification. In earlier work published in Biometrics, Kim, Hudgens, Dreyfuss, Westreich, and Pilcher (2007, Biometrics 63, 1152-1162) also proposed group testing algorithms in a homogeneous population with misclassification. In both cases, the authors evaluated performance of the algorithms based on the expected number of tests per person, with the optimal design being defined by minimizing this quantity. The purpose of this article is to show that although the expected number of tests per person is an appropriate evaluation criteria for group testing when there is no misclassification, it may be problematic when there is misclassification. Specifically, a valid criterion needs to take into account the amount of correct classification and not just the number of tests. We propose, a more suitable objective function that accounts for not only the expected number of tests, but also the expected number of correct classifications. We then show how using this objective function that accounts for correct classification is important for design when considering group testing under misclassification. We also present novel analytical results which characterize the optimal Dorfman (1943) design under the misclassification., (© 2015, The International Biometric Society.)

There is a wide body of literature in biostatistics and epidemiology literature about estimating diagnostic accuracy, such as sensitivity and specificity of a binary test, without a gold standard. This methodology is very attractive since obtaining gold standard information is impossible, difficult, or very expensive in some situations. Although there are many proponents of these approaches, there have also been some serious criticisms. We review important methodological developments as well as discuss problems with the approaches. We propose alternative designs that may be less controversial and present ideas for future research. Lastly, we provide recommendations about how these methods should be used in practice.