Post-hoc analysis of vitamin D status and reduced risk of preterm birth in two vitamin D pregnancy cohorts compared with South Carolina March of Dimes 2009-2011 rates.

BACKGROUND: Two vitamin D pregnancy supplementation trials were recently undertaken in South Carolina: The NICHD (n=346) and Thrasher Research Fund (TRF, n=163) studies. The findings suggest increased dosages of supplemental vitamin D were associated with improved health outcomes of both mother and newborn, including risk of preterm birth (<37 weeks gestation). How that risk was associated with 25(OH)D serum concentration, a better indicator of vitamin D status than dosage, by race/ethnic group and the potential impact in the community was not previously explored. While a recent IOM report suggested a concentration of 20 ng/mL should be targeted, more recent work suggests optimal conversion of 25(OH)D-1,25(OH)2D takes place at 40 ng/mL in pregnant women. OBJECTIVE: Post-hoc analysis of the relationship between 25(OH)D concentration and preterm birth rates in the NICHD and TRF studies with comparison to Charleston County, South Carolina March of Dimes (CC-MOD) published rates of preterm birth to assess potential risk reduction in the community. METHODS: Using the combined cohort datasets (n=509), preterm birth rates both for the overall population and for the subpopulations achieving 25(OH)D concentrations of ≤20 ng/mL, >20 to <40 ng/mL, and ≥40 ng/mL were calculated; subpopulations broken down by race/ethnicity were also examined. Log-binomial regression was used to test if an association between 25(OH)D serum concentration and preterm birth was present when adjusted for covariates; locally weighted regression (LOESS) was used to explore the relationship between 25(OH)D concentration and gestational age (weeks) at delivery in more detail. These rates were compared with 2009-2011 CC-MOD data to assess potential risk reductions in preterm birth. RESULTS: Women with serum 25(OH)D concentrations ≥40 ng/mL (n=233) had a 57% lower risk of preterm birth compared to those with concentrations ≤20 ng/mL [n=82; RR=0.43, 95% confidence interval (CI)=0.22,0.83]; this lower risk was essentially unchanged after adjusting for covariates (RR=0.41, 95% CI=0.20,0.86). The fitted LOESS curve shows gestation week at birth initially rising steadily with increasing 25(OH)D and then plateauing at ∼40 ng/mL. Broken down by race/ethnicity, there was a 79% lower risk of preterm birth among Hispanic women with 25(OH)D concentrations ≥40 ng/mL (n=92) compared to those with 25(OH)D concentrations ≤20 ng/mL (n=29; RR=0.21, 95% CI=0.06,0.69) and a 45% lower risk among Black women (n=52 and n=50; RR=0.55, 95% CI=0.17,1.76). There were too few white women with low 25(OH)D concentrations for assessment (n=3). Differences by race/ethnicity were not statistically significant with 25(OH)D included as a covariate. Compared to the CC-MOD reference group, women with serum concentrations ≥40 ng/mL in the combined cohort had a 46% lower rate of preterm birth overall (n=233, p=0.004) with a 66% lower rate among Hispanic women (n=92, p=0.01) and a 58% lower rate among black women (n=52, p=0.04). CONCLUSIONS: In this post-hoc analysis, achieving a 25(OH)D serum concentration ≥40 ng/mL significantly decreased the risk of preterm birth compared to ≤20 ng/mL. These findings suggest the importance of raising 25(OH)D levels substantially above 20 ng/mL; reaching 40 ng/mL during pregnancy would reduce the risk of preterm birth and achieve the maximal production of the active hormone.

Evidence of a role for the novel zinc-finger transcription factor ZKSCAN3 in modulating Cyclin D2 expression in multiple myeloma.

Dysregulation of cyclin D2 contributes to the pathogenesis of multiple myeloma, and can occur through translocations that activate MAF/MAFB or MMSET/FGFR3. However, cyclin D2 induction can also be seen in the absence of such translocations, such as in patients with hyperdiploid disease, through unknown mechanisms. In UniGene cluster data-mining and ECgene analysis, we found that zinc-finger with KRAB and SCAN domains 3 (ZKSCAN3), a novel transcription factor, is overrepresented in this malignancy, and three consensus ZKSCAN3 binding sites were found in the cyclin D2 promoter. Analysis of a panel of myeloma cell lines, primary patient samples and datasets from Oncomine and the Multiple Myeloma Genomics Portal (MMGP) revealed expression of ZKSCAN3 messenger RNA (mRNA) in a majority of samples. Studies of cell lines by western blotting, and of primary tissue microarrays by immunohistochemistry, showed ZKSCAN3 protein expression in a majority, and in a manner that paralleled messenger levels in cell lines. ZKSCAN3 overexpression was associated with increased gene copy number or genomic DNA gain/amplification in a subset based on analysis of data from the MMGP, and from fluorescence in situ hybridization studies of cell lines and primary samples. Overexpression of ZKSCAN3 induced cyclin D2 promoter activity in a MAF/MAFB-independent manner, and to an extent that was influenced by the number of consensus ZKSCAN3 binding sites. Moreover, ZKSCAN3 protein expression correlated with cyclin D2 levels in cell lines and primary samples, and its overexpression induced cyclin D2. Conversely, ZKSCAN3 suppression using small hairpin RNAs (shRNAs) reduced cyclin D2 levels, and, importantly, inhibited myeloma cell line proliferation. Finally, ZKSCAN3 was noted to specifically bind to oligonucleotides representing sequences from the cyclin D2 promoter, and to the endogenous promoter itself in myeloma cells. Taken together, the data support the conclusion that ZKSCAN3 induction represents a mechanism by which myeloma cells can induce cyclin D2 dysregulation, and contribute to disease pathogenesis.

New tumor markers: CA125 and beyond.

A variety of biomarkers have been developed to monitor growth of ovarian cancer and to detect disease at an early interval. CA125 (MUC16) has provided a useful serum tumor marker for monitoring response to chemotherapy, detecting disease recurrence, distinguishing malignant from benign pelvic masses, and potentially improving clinical trial design. A rapid fall in CA125 during chemotherapy predicts a favorable prognosis and could be used to redistribute patients on multiarmed randomized clinical trials. Several studies now document that CA125 can serve as a surrogate marker for response in phase II trials. Serial measurement of CA125 might also provide a useful marker for monitoring stabilization of disease with cytostatic targeted therapeutic agents. The greatest potential for serum markers may be in detecting ovarian cancer at an early stage. A rising CA125 can be used to trigger transvaginal sonography (TVS) in a small fraction of patients. An algorithm has been developed that calculates risk of ovarian cancer based on serial CA125 values and refers patients at highest risk for TVS. Use of the algorithm is currently being evaluated in a trial with 200,000 women in the UK that will test critically the ability of a two-stage screening strategy to improve survival in ovarian cancer. Whatever the outcome, as 20% of ovarian cancers have little or no expression of CA125, additional serum markers will be required to detect all patients in an initial phase of screening. More than 30 serum markers have been evaluated alone and in combination with CA125 by different investigators. Some of the most promising include: HE4, mesothelin, M-CSF, osteopontin, kallikrein(s), and soluble EGF receptor. Two proteomic approaches have been used: one examines the pattern of peaks on mass spectroscopy and the other uses proteomic analysis to identify a limited number of critical markers that can be assayed by more conventional methods. Both approaches are promising and require further development. Several groups are placing markers on multiplex platforms to permit simultaneous assay of multiple markers with very small volumes of serum. Mathematical techniques are being developed to analyze combinations of marker levels to improve sensitivity and specificity. In the future, serum markers should improve the sensitivity of detecting recurrent disease as well as facilitate earlier detection of ovarian cancer.

Identifying differentially expressed genes in cDNA microarray experiments.

A major goal of microarray experiments is to determine which genes are differentially expressed between samples. Differential expression has been assessed by taking ratios of expression levels of different samples at a spot on the array and flagging spots (genes) where the magnitude of the fold difference exceeds some threshold. More recent work has attempted to incorporate the fact that the variability of these ratios is not constant. Most methods are variants of Student's t-test. These variants standardize the ratios by dividing by an estimate of the standard deviation of that ratio; spots with large standardized values are flagged. Estimating these standard deviations requires replication of the measurements, either within a slide or between slides, or the use of a model describing what the standard deviation should be. Starting from considerations of the kinetics driving microarray hybridization, we derive models for the intensity of a replicated spot, when replication is performed within and between arrays. Replication within slides leads to a beta-binomial model, and replication between slides leads to a gamma-Poisson model. These models predict how the variance of a log ratio changes with the total intensity of the signal at the spot, independent of the identity of the gene. Ratios for genes with a small amount of total signal are highly variable, whereas ratios for genes with a large amount of total signal are fairly stable. Log ratios are scaled by the standard deviations given by these functions, giving model-based versions of Studentization. An example is given.

Probability binning and testing agreement between multivariate immunofluorescence histograms: extending the chi-squared test.

BACKGROUND: A key problem in immunohistochemistry is assessing when two sample histograms are significantly different. One test that is commonly used for this purpose in the univariate case is the chi-squared test. Comparing multivariate distributions is qualitatively harder, as the "curse of dimensionality" means that the number of bins can grow exponentially. For the chi-squared test to be useful, data-dependent binning methods must be employed. An example of how this can be done is provided by the "probability binning" method of Roederer et al. (1,2,3). METHODS: We derive the theoretical distribution of the probability binning statistic, giving it a more rigorous foundation. We show that the null distribution is a scaled chi-square, and show how it can be related to the standard chi-squared statistic. RESULTS: A small simulation shows how the theoretical results can be used to (a) modify the probability binning statistic to make it more sensitive and (b) suggest variant statistics which, while still exploiting the data-dependent strengths of the probability binning procedure, may be easier to work with. CONCLUSIONS: The probability binning procedure effectively uses adaptive binning to locate structure in high-dimensional data. The derivation of a theoretical basis provides a more detailed interpretation of its behavior and renders the probability binning method more flexible.

Microarrays: handling the deluge of data and extracting reliable information.

Application of powerful, high-throughput genomics technologies is becoming more common and these technologies are evolving at a rapid pace. Genomics facilities are being established in major research institutions to produce inexpensive, customized cDNA microarrays that are accessible to researchers in a broad range of fields. These high-throughput platforms have generated a massive onslaught of data, which threatens to overwhelm researchers. Although microarrays show great promise, the technology has not matured to the point of consistently generating robust and reliable data when used in the average laboratory. This article addresses several aspects related to the handling of the deluge of microarray data and extracting reliable information from these data. We review the essential elements of data acquisition, data processing and data analysis, and briefly discuss issues related to the quality, validation and storage of data. Our goal is to point out some of the problems that must be overcome before this promising technology can achieve its full potential.

Gene amplification by unequal sister chromatid exchange: probabilistic modeling and analysis of drug resistance data.

Unequal sister chromatid exchange has been proposed as one of several possible mechanisms for gene amplification resulting in tandemly repeated sequences on chromosomes. Two requirements for testing this hypothesis are analytical observations and a mathematical model. Recently observations were reported for the number of tandemly repeated sequences on chromosomes of cells growing in the presence of a toxic drug and the mechanism was proposed to be unequal sister chromatid exchange. We now develop a mathematical model of this process based on the following hypotheses, (i) the extent of slippage between paired sister chromatids is a random variable with geometric distribution, (ii) the number of crossover sites is a random variable with a Poisson distribution, and (iii) cells with less than a threshold number of copies of an essential gene are eliminated when grown in selective conditions. Iterating the model at successive cell divisions results in a Markov chain with a denumerable infinity of states. The resulting distributions of gene copy number per cell at a particular population size are compared to published data on the CAD gene in BHK cells growing in the presence of the drug PALA (Smith et al., 1990, Cell, 63, 1219). The mathematical model can reproduce the observed means and standard deviations of gene copy number per cell and allows construction of confidence region estimates of parameters describing the extent of slippage, density of crossover sites, and strength of selection. An important prediction of the model is that in non-selective conditions the cells with amplified sequences gradually disappear from the population even if they are not at a growth disadvantage, though rare cells with a very large number of amplified sequences might continue to exist. The success of modeling suggests that the proposed mechanism of gene amplification by unequal sister chromatid exchange is consistent with the number of tandemly repeated sequences on chromosomes observed in some circumstances.

Measuring cell proliferation by relative movement. I. Introduction and in vitro studies.

This paper presents two new ways of analysing data which may be obtained from pulse labelling a population of cells with bromodeoxyuridine and analysing that population as a function of time with bivariate flow cytometry. The progression of cells is measured by the change in position in the cell cycle, as shown by a change in the mean DNA content of the labelled and unlabelled cells. The particular measures of the mean DNA content used are extensions of the relative movement of the labelled undivided cells, RMlu(t), which was introduced by Begg and co-workers to measure the DNA synthesis time, TS. In general, the relative movement is defined as the mean DNA fluorescence of a population of cells less the DNA fluorescence of the cells in G1 and divided by the difference in DNA fluorescence of the cells in G2 + M and G1. In this paper we examine the relative movements of all the labelled cells and all of the unlabelled cells, denoted RML(t) and RMU(t) respectively. It is found that RML(t) and RMU(t) exhibit clear cyclic behaviour and distinguishable characteristics which depend directly on the transit times (T) of the cell cycle phases, i.e. TG1, TS and TG2 + M. Furthermore, the peak heights of the RMU(t) curve are shown to depend strongly on the growth fraction of the population under consideration. A theoretical treatment of the curves so obtained is presented, and is shown to yield values in close agreement with those from other methods for measuring these transit times and a lower limit to values for the growth fraction of Chinese hamster ovary cells grown in vitro.