We conducted a population-based case-control study of single nucleotide polymorphisms (SNPs) in selected genes to find common variants that play a role in the etiology of limb deficiencies (LD)s. Included in the study were 389 infants with LDs of unknown cause and 980 unaffected controls selected from all births in New York State (NYS) for the years 1998 to 2005. We used cases identified from the NYS Department of Health (DOH) Congenital Malformations Registry. Genotypes were obtained for 132 SNPs in genes involved in limb development (SHH, WNT7A, FGF4, FGF8, FGF10, TBX3, TBX5, SALL4, GREM1, GDF5, CTNNB1, EN1, CYP26A1, CYP26B1), angiogenesis (VEGFA, HIF1A, NOS3), and coagulation (F2, F5, MTHFR). Genotype call rates were >97% and SNPs were tested for departure from Hardy-Weinberg expectations by race/ethnic subgroups. For each SNP, odds ratios (OR)s and confidence intervals (CI)s were estimated and corrected for multiple comparisons for all LDs combined and for LD subtypes. Among non-Hispanic white infants, associations between FGF10 SNPs rs10805683 and rs13170645 and all LDs combined were statistically significant following correction for multiple testing (OR=1.99; 95% CI=1.43-2.77; uncorrected p=0.000043 for rs10805683 heterozygous genotype, and OR=2.37; 95% CI=1.48-3.78; uncorrected p=0.00032 for rs13170645 homozygous minor genotype). We also observed suggestive evidence for associations with SNPs in other genes including CYP26B1 and WNT7A. Animal studies have shown that FGF10 induces formation of the apical ectodermal ridge and is necessary for limb development. Our data suggest that common variants in FGF10 increase the risk for a wide range of non-syndromic limb deficiencies.
limb deficiencies; polymorphisms; FGF10
Hirschsprung’s disease (HSCR) results from failed colonization of the embryonic gut by enteric neural crest cells (ENCCs); colonization requires RET proto-oncogene (RET) signaling. We sequenced RET to identify coding and splice-site variants in a population-based case group and we tested for associations between HSCR and common variants in RET and candidate genes (ASCL1, HOXB5, L1CAM, PHOX2B, PROK1, PROKR1) chosen because they are involved in ENCC proliferation, migration, and differentiation in animal models. We conducted a nested case-control study of 304 HSCR cases and 1 215 controls. Among 38 (12.5%) cases with 34 RET coding and splice-site variants, 18 variants were previously unreported. We confirmed associations with common variants in HOXB5 and PHOX2B but the associations with variants in ASCL1, L1CAM, and PROK1 were not significant after multiple comparisons adjustment. RET variants were strongly associated with HSCR (P values between 10−3 and 10−31) but this differed by race/ethnicity: associations were absent in African-Americans. Our population-based study not only identified novel RET variants in HSCR cases, it showed that common RET variants may not contribute to HSCR in all race/ethnic groups. The findings for HOXB5 and PHOX2B provide supportive evidence that genes regulating ENCC proliferation, migration, and differentiation could be risk factors for HSCR.
congenital abnormalities; enteric nervous system; Hirschsprung disease; RET
To test the effect on diabetes management outcomes of a low-intensity, clinic-integrated behavioral intervention for families of youth with type 1 diabetes.
Families (n = 390) obtaining care for type 1 diabetes participated in a 2-year randomized clinical trial of a clinic-integrated behavioral intervention designed to improve family diabetes management practices. Measurement of hemoglobin A1c, the primary outcome, was obtained at each clinic visit and analyzed centrally. Blood glucose meter data were downloaded at each visit. Adherence was assessed by using a semistructured interview at baseline, mid-study, and follow-up. Analyses included 2-sample t tests at predefined time intervals and mixed-effect linear-quadratic models to assess for difference in change in outcomes across the study duration.
A significant overall intervention effect on change in glycemic control from baseline was observed at the 24-month interval (P = .03). The mixed-effect model showed a significant intervention by age interaction (P < .001). Among participants aged 12 to 14, a significant effect on glycemic control was observed (P = .009 for change from baseline to 24-month interval; P = .035 for mixed-effect model across study duration), but there was no effect among those aged 9 to 11. There was no intervention effect on child or parent report of adherence; however, associations of change in adherence with change in glycemic control were weak.
This clinic-integrated behavioral intervention was effective in preventing the deterioration in glycemic control evident during adolescence, offering a potential model for integrating medical and behavioral sciences in clinical care.
type 1 diabetes; children; adolescents; adherence; behavioral intervention; glycemic control
Several optimality properties of Dorfman’s (1943) group testing procedure are derived for estimation of the prevalence of a rare disease whose status is classified with error. Exact ranges of disease prevalence are obtained for which group testing provides more efficient estimation when group size increases.
Binary outcome; Maximum likelihood estimation; Pooling; Prevalence; Sensitivity; Specificity
Diagnostic accuracy can be improved considerably by combining multiple biomarkers. Although the likelihood ratio provides optimal solution to combination of biomarkers, the method is sensitive to distributional assumptions which are often difficult to justify. Alternatively simple linear combinations can be considered whose empirical solution may encounter extensive computation when the number of biomarkers is relatively large. Moreover, the optimal linear combinations derived under multivariate normality may suffer substantial loss of efficiency if the distributions are apart from normality. In this paper we propose a new approach that linearly combines the minimum and maximum values of the biomarkers. Such combination only involves searching for a single combination coefficient that maximizes the area under the receiver operating characteristic (ROC) curves and is thus computation-effective. Simulation results show that the min-max combination may yield larger partial or full area under the ROC curves and is more robust against distributional assumptions. The methods are illustrated using the growth-related hormones data from the Growth and Maturation in Children with Autism or Autistic Spectrum Disorder (ASD) Study (Autism/ASD Study).
Area under curves; linear combinations; receiver operating characteristic (ROC) curve; robustness; sensitivity; specificity
Both taking folic acid-containing vitamins around conception and consuming food fortified with folic acid have been reported to reduce omphalocele rates. Genetic factors are etiologically important in omphalocele as well; our pilot study showed a relationship with the folate metabolic enzyme gene methylenetetrahydrofolate reductase (MTHFR). We studied 169 non-aneuploid omphalocele cases and 761 unaffected, matched controls from all New York State births occurring between 1998 and 2005 to look for associations with single nucleotide polymorphisms (SNPs) known to be important in folate, vitamin B12, or choline metabolism. In the total study population, variants in the transcobalamin receptor gene (TCblR), rs2232775 (Q8R), and the MTHFR gene, rs1801131 (1298A>C), were significantly associated with omphalocele. In African-Americans significant associations were found with SNPs in genes for the vitamin B12 transporter (TCN2) and the vitamin B12 receptor (TCblR). A SNP in the homocysteine-related gene, betaine-homocysteine S-methyltransferase (BHMT), rs3733890 (R239Q), was significantly associated with omphalocele in both African-Americans and Asians. Only the TCblR association in the total population remained statistically significant if Bonferroni correction was applied. The finding that transcobalamin receptor (TCblR) and transporter (TCN2) SNPs and a BHMT SNP were associated with omphalocele suggests that disruption of methylation reactions, in which folate, vitamin B12, and homocysteine play critical parts, may be a risk factor for omphalocele. Our data, if confirmed, suggest that supplements containing both folic acid and vitamin B12 may be beneficial in preventing omphaloceles.
omphalocele; folate; vitamin B12; homocysteine; transcobalamin; transcobalamin receptor
Cigarette smoking has been implicated in reproductive outcomes including delayed conception, but mechanisms underlying these associations remain unclear. One potential mechanism is the effect of cigarette smoking on reproductive hormones; however, studies evaluating associations between smoking and hormone levels are complicated by variability of hormones and timing of specimen collection. We evaluated smoking and its relationship to reproductive hormones among women participating in the BioCycle study, a longitudinal study of menstrual cycle function in healthy, premenopausal, regularly menstruating women (n=259). Fertility monitors were used to help guide timing of specimen collection. Serum levels of estradiol, progesterone, follicle-stimulating hormone (FSH), luteinizing hormone (LH) and total sex-hormone binding globulin (SHBG) across phases of the menstrual cycle were compared between smokers and nonsmokers.
We observed statistically significant phase-specific differences in hormone levels between smokers and nonsmokers. Compared to nonsmokers, smokers had higher levels of FSH in the early follicular phase higher LH at menses after adjusting for potential confounding factors of age, race, BMI, nulliparity, vigorous exercise, and alcohol and caffeine intake through inverse probability of treatment weights. No statistically significant differences were observed for estradiol, progesterone or SHBG. These phase-specific differences in levels of LH and FSH in healthy, regularly menstruating women who are current smokers compared to nonsmokers reflect one mechanism by which smoking may impact fertility and reproductive health.
For comparison of multiple outcomes commonly encountered in biomedical research, Huang et al. (2005) improved O’Brien’s (1984) rank-sum tests through the replacement of the ad hoc variance by the asymptotic variance of the test statistics. The improved tests control the Type I error rate at the desired level and gain power when the differences between the two comparison groups in each outcome variable fall into the same direction. However, they may lose power when the differences are in different directions (e.g., some are positive and some are negative). These tests and the popular Bonferroni correction failed to show important significant difference when applied to compare heart rates from a clinical trial to evaluate the effect of a procedure to remove the cardioprotective solution HTK. We propose an alternative test statistic, taking the maximum of the individual rank-sum statistics, which controls the type I error and maintains satisfactory power regardless of the directions of the differences. Simulation studies show the proposed test to be of higher power than other tests in certain alternative parameter space of interest. Furthermore, when used to analyze the heart rates data the proposed test yields more satisfactory results.
Autism spectrum disorder; Behrens-Fisher problem; Cardioprotective solution; Case-control studies; Growth hormones; Multiple outcomes; Non-parametrics; Rank-sum statistics
The cost efficient two-stage design is often used in genome-wide association studies (GWASs) in searching for genetic loci underlying the susceptibility for complex diseases. Replication-based analysis, which considers data from each stage separately, often suffers from loss of efficiency. Joint test that combines data from both stages has been proposed and widely used to improve efficiency. However, existing joint analyses are based on test statistics derived under an assumed genetic model, and thus might not have robust performance when the assumed genetic model is not appropriate.
In this paper, we propose joint analyses based on two robust tests, MERT and MAX3, for GWASs under a two-stage design. We developed computationally efficient procedures and formulas for significant level evaluation and power calculation. The performances of the proposed approaches are investigated through the extensive simulation studies and a real example. Numerical results show that the joint analysis based on the MAX3 test statistic has the best overall performance.
MAX3 joint analysis is the most robust procedure among the considered joint analyses, and we recommend using it in a two-stage genome-wide association study.
Before a comparative diagnostic trial is carried out, maximum sample sizes for the diseased group and the nondiseased group need to be obtained to achieve a nominal power to detect a meaningful difference in diagnostic accuracy. Sample size calculation depends on the variance of the statistic of interest, which is the difference between receiver operating characteristic summary measures of 2 medical diagnostic tests. To obtain an appropriate value for the variance, one often has to assume an arbitrary parametric model and the associated parameter values for the 2 groups of subjects under 2 tests to be compared. It becomes more tedious to do so when the same subject undergoes 2 different tests because the correlation is then involved in modeling the test outcomes. The calculated variance based on incorrectly specified parametric models may be smaller than the true one, which will subsequently result in smaller maximum sample sizes, leaving the study underpowered. In this paper, we develop a nonparametric adaptive method for comparative diagnostic trials to update the sample sizes using interim data, while allowing early stopping during interim analyses. We show that the proposed method maintains the nominal power and type I error rate through theoretical proofs and simulation studies.
Diagnostic accuracy; Error spending function; ROC; Sensitivity; Specificity
Large comparative clinical trials usual target a wide-range of patients population in which subgroups exist according to certain patients’ characteristics. Often, scientific knowledge or existing empirical data support the assumption that patients’ improvement is larger among certain subgroups than the others. Such information can be used to design a more cost-effective clinical trial.
The goal of the article is to use such information to design a more cost-effective clinical trial.
A two-stage sample-enrichment design strategy is proposed that begins with enrollment from certain subgroup of patients and allows the trial to be terminated for futility in that subgroup.
Simulation studies show that the two-stage sample-enrichment strategy is cost-effective if indeed the null hypothesis of no treatment improvement is true, as also so illustrated with data from a completed trial of calcium to prevent preeclampsia.
Feasibility of the proposed enrichment design relies on the knowledge prior to the start of the trial that certain patients can benefit more than others from the treatment.
The two-stage sample-enrichment approach borrows strength from treatment heterogeneity among target patients in a large scale comparative clinical trial, and is more cost-effective if the treatment are of no difference.
Sample size and power; stopping for futility; subgroup analysis; treatment heterogeneity
Intraclass correlation models with missing data at random are considered. With a properly reduced model, a general method, which allows repeated observations with missing in non-monotone pattern, is proposed to construct exact test statistics and simultaneous confidence intervals for linear contrasts in the means. Simulation results are given to compare exact and asymptotic simultaneous confidence intervals. A real example is provided for illustration of the proposed method.
Contrast; Exact test; Intraclass correlation model; Linear mixed model; Simultaneous confidence intervals
Additive measurement errors and pooling design are objectively two different issues, which have been separately and extensively dealt with in the biostatistics literature. However, these topics usually correspond to problems of reconstructing a summand’s distribution of the biomarker by the distribution of the convoluted observations. Thus, we associate the two issues into one stated problem. The integrated approach creates an opportunity to investigate new fields, e.g. a subject of pooling errors, issues regarding pooled data affected by measurement errors. To be specific, we consider the stated problem in the context of the receiver operating characteristic (ROC) curves analysis, which is the well-accepted tool for evaluating the ability of a biomarker to discriminate between two populations. The present paper considers a wide family of biospecimen distributions. In addition, applied assumptions, which are related to distribution functions of biomarkers, are mainly conditioned by the reconstructing problem. We propose and examine maximum likelihood techniques based on the following data: a biomarker with measurement error; pooled samples; and pooled samples with measurement error. The obtained methods are illustrated by applications to real data studies.
deconvolution; design of experiments; Fourier inversion; infinitely divisible distribution; measurement error; pooling blood samples; receiver operating characteristic curves; stable distribution; summand’s distribution
In this article, we consider comparing the areas under correlated receiver operating characteristic (ROC) curves of diagnostic biomarkers whose measurements are subject to a limit of detection (LOD), a source of measurement error from instruments’ sensitivity in epidemiological studies. We propose and examine the likelihood ratio tests with operating characteristics that are easily obtained by classical maximum likelihood methodology.
Area under curve (AUC); Censoring; Hypothesis testing; Limit of detection (LOD); Maximum likelihood; Receiver operating characteristics (ROC)
For comparing the distribution of two samples with multiple endpoints, O’Brien (1984) proposed rank-sum-type test statistics. Huang et al. (2005) extended these statistics to the general nonparametric Behrens-Fisher hypothesis problem and obtained improved test statistics by replacing the ad hoc variance with the asymptotic variance of the rank-sum statistics. In this paper we generalize the work of O’Brien (1984) and Huang et al. (2005) and propose a weighted rank-sum statistic. We show that the weighted rank-sum statistic is asymptotically normally distributed, permitting the computation of power, p-values and confidence intervals. We further demonstrate via simulation that the weighted rank-sum statistic is efficient in controlling the type I error rate and under certain alternatives, is more powerful than the statistics of O’Brien (1984) and Huang et al.(2005).
Asymptotic normality; Behrens-Fisher problem; Case-Control; Clinical trials; Multiple endpoints; Rank-sum statistics; Weights
We consider evaluation and comparison of the diagnostic accuracy of biomarkers with continuous test outcomes, possibly correlated due to repeated measurements. We develop nonparametric group sequential testing procedures to evaluate and compare the area of biomarkers under their receiver operating characteristic curves, with either independent or paired test outcomes. These procedures rely on the construction of a two-dimensional statistic of Whitehead so that design methods based on Brownian motion can be applied.
biomarkers; correlated measurements; diagnostic tests; interim looks and early stopping; correlated U-statistics
Studies in both human and animal species have suggested that oxidative stress may be associated with health outcomes, including the risk of infertility in both males and females. Sex hormones have been shown to have antioxidant properties. The difficulty in studying the role of oxidative stress in females is partly due to fluctuation in these endogenous sex hormones across the menstrual cycle.
The aim of this study was to determine the association of oxidative stress levels with endogenous reproductive hormone levels and antioxidants, including vitamin levels, across the menstrual cycle in a prospective cohort of premenopausal women. The goal was to enrol 250 healthy, regularly menstruating premenopausal women for two menstrual cycles. Participants visited the clinic up to 8 times per cycle, at which time blood and urine were collected. The visits occurred at key hormonally defined phases of the menstrual cycle, with the help of an algorithm based on cycle length and data from a fertility monitor. In addition, participants were administered standardised questionnaires, had various physical measures taken, and had other pertinent data collected. A total of 259 women were enrolled in this study, with 250 completing two cycles, despite a demanding study protocol which participants were required to follow. This report describes the study design, baseline characteristics and visit completion rate for the BioCycle study.
menstrual cycle; sex hormones; antioxidants; BioCycle study; study design; oxidative stress
Considered in the paper is the problem of selecting a diagnostic biomarker that has the highest classification rate among several candidate markers with dichotomous outcomes. The probability of correct selection depends on a number of nuisance parameters from the joint distribution of the biomarkers and thus can be substantially affected if these nuisance parameters are misspecified. A two-stage procedure is proposed to compute the needed sample size that achieves the desired level of correct selection, as so confirmed by simulation results.
classification rate; diagnosis; nuisance parameters; probability of correct selection; sensitivity; specificity
The etiology and pathophysiology of preeclampsia are not fully understood. However, oxidative stress has been strongly linked to the occurrence of this multi-system disease. This has led to many theories of the pathogenesis of preeclampsia involving placental oxidative stress. In this study, we hypothesized that polymorphisms of anti-oxidant genes in the placental tissue contributed to susceptibility to preeclampsia. Polymorphisms in copper/zinc superoxide dismutase (CuZn-SOD), manganese superoxide dismutase (MnSOD), glutathione-s-transferase M1 (GSTM1), and glutathione-s-transferase T1 (GSTT1) in the umbilical cord tissue were assayed by polymerase chain reaction (PCR) in 23 nulliparous preeclampsia cases and 32 nulliparous normotensive controls. Corresponding enzyme activity levels and an oxidative stress biomarker (8-isoprostane) of the placental tissue were also measured. In addition, maternal plasma 8-isoprostane levels were also determined. Our results showed that no significant differences in polymorphism frequency of the tested genes, enzyme activity levels or 8-isoprostane levels in the placental tissue were detected between the cases and controls. However, maternal plasma 8-isoprostane level was significantly higher in the cases than in the controls (105.8 vs. 27.9 pg/ml, p = 0.03). In conclusion, our study showed that polymorphisms of CuZn-SOD, MnSOD, GSTM1 and GSTT1 in the placental tissue were not associated with preeclampsia.
Little information is available on the intra-individual variability of oxidative stress biomarkers in healthy individuals and even less in the context of the menstrual cycle. The objective of this study was to characterize the analytical and biological variability of a panel of 21 markers of oxidative damage, antioxidant defence and micronutrients in nine healthy, regularly menstruating women aged 18–44 years. Analyses included measurement of lipid peroxidation, antioxidant enzymes and antioxidant vitamins. Blood specimens were collected, processed and stored using standardized procedures on days 2, 7, 12, 13, 14, 18, 22 and 28 in one cycle for each subject. Replicate analyses of markers were performed and two-way nested random effects ANOVA was used to describe analytical, intra-individual and inter-individual variability. No statistically significant differences at α = 0.05, or temporal effects across the menstrual cycle were observed. Analytical variability was the smallest component of variance for all variables. The ICC among replicates ranged from 0.80 to 0.98. Imprecision based on quality control materials ranged from 1 to 11%. The critical differences between serial results varied greatly between assays ranging from 6 to 216% of the mean level. These results provide important initial information on the variability of biomarkers of oxidative stress, antioxidant defence and micronutrients across the menstrual cycle.
Oxidative stress; antioxidants; biological variation; menstrual cycle
GPR30 is a cell surface estrogen receptor that has been shown to mediate a number of non-genomic rapid effects of estrogen and appear to balance the signaling of estrogen and growth factors. In addition, progestins appear to use GPR30 for their actions. Therefore, GPR30 could play a critical role in hormonal regulation of breast epithelial cell integrity. Deregulation of the events mediated by GPR30 could contribute to tumorigenesis.
To understand the role of GPR30 in the deregulation of estrogen signaling processes during breast carcinogenesis, we have undertaken this study to investigate its expression at mRNA levels in tumor tissues and their matched normal tissues. We compared its expression at mRNA levels by RT quantitative real-time PCR relative to GAPDH in ERα”—positive (n = 54) and ERα”—negative (n = 45) breast cancer tissues to their matched normal tissues.
We report here, for the first time, that GPR30 mRNA levels were significantly down-regulated in cancer tissues in comparison with their matched normal tissues (p < 0.0001 by two sided paired t-test). The GPR30 expression levels were significantly lower in tumor tissues from patients (n = 29) who had lymph node metastasis in comparison with tumors from patients (n = 53) who were negative for lymph node metastasis (two sample t-test, p < 0.02), but no association was found with ERα, PR and other tumor characteristics.
Down-regulation of GPR30 could contribute to breast tumorigenesis and lymph node metastasis.
breast tumorigenesis; estrogen signaling; G protein coupled receptor 30 (GPR30); cell surface estrogen receptor and lymph node metastasis
Biomarker use in exposure assessment is increasingly common and consideration of related issues is of growing importance. Exposure quantification may be compromised when measurement is subject to a lower threshold. Statistical modeling of such data requires a decision regarding the handling of such readings. Various authors have considered this problem. In the context of linear regression analysis, Richardson and Ciampi proposed replacement of data below a threshold by a constant equal to the expectation for such data to yield unbiased estimates. Use of such an imputation has some limitations; distributional assumptions are required, and bias reduction in estimation of regression parameters is asymptotic, thereby presenting concerns to small studies. In this paper the authors propose distribution-free methods for managing values below detection limits and evaluate the biases that may result when exposure measurement is constrained by a lower threshold. The authors utilize an analytical approach as well as a simulation study to assess the effects of the proposed replacement method on estimates. These results may inform decisions regarding analytical plans for future studies as well as provide possible explanation for some amount of discordance seen in extant literature.
Regression analysis; limit of detection; bias; biomarkers; molecular epidemiology; threshold; LOD, limit of detection; LOQ, limit of quantification; ELISA, enzyme linked immunosorbent assay
Few data are available on polychlorinated biphenyl (PCB) concentrations over critical windows of human reproduction and development inclusive of the periconception window.
Our goal was to measure changes in PCB concentrations from preconception to pregnancy, through pregnancy, or after a year without becoming pregnant.
Seventy-nine women planning pregnancies were prospectively enrolled and followed for up to 12 menstrual cycles of attempting pregnancy. Blood specimens were obtained from participating women preconceptionally (n = 79), after a positive pregnancy test leading to a live birth (n = 54) or pregnancy loss (n = 10), at approximately 6 weeks postpartum (n = 53), and after 12 unsuccessful cycles (n = 9) for toxicologic analysis of 76 PCB congeners. We estimated overall and daily rate of change in PCB concentration (nanograms per gram serum) adjusting for relevant covariates, serum lipids, and baseline PCB concentration.
Significant (p < 0.0001) decreases in the mean overall and daily rate of change in PCB concentrations were observed between the preconception and first pregnancy samples for total (–1.012 and –0.034, respectively), estrogenic (–0.444 and –0.016, respectively), and antiestrogenic (–0.106 and –0.004, respectively) PCBs among women with live births. Similar significant decreases in total (–1.452 and –0.085), estrogenic (–0.647 and –0.040), and antiestrogenic (–0.093 and –0.004) PCB concentrations were seen for women with pregnancy losses. No significant changes were observed for PCB congener 153.
These data suggest that PCB concentrations may change during the periconception interval, questioning the stability of persistent compounds during this critical window.
critical windows; infertility; periconception; persistent organic pollutants; polychlorinated biphenyls (PCBs); pregnancy loss