Cell specific patterns of methylation in the human placenta

Epigenetic processes, such as DNA methylation, are known to regulate tissue specific gene expression. We explored this concept in the placenta to define whether DNA methylation is cell-type specific. Cytotrophoblasts and fibroblasts were isolated from normal midtrimester placentas. Using immunocytochemistry, we demonstrated 95% purity for cytotrophoblasts and 60–70% for fibroblasts. We compared DNA methylation profiles from cytotrophoblasts, fibroblasts and whole placental villi using bisulfite modified genomic DNA hybridized to the Illumina Methylation27 array. Euclidean cluster analysis of the DNA methylation profiles showed two main clusters, one containing cytotrophoblasts and placenta, the other fibroblasts. Differential methylation analysis identified 442 autosomal CpG sites that differed between cytotrophoblasts and fibroblasts, 315 between placenta and fibroblasts and 61 between placenta and cytotrophoblasts. Three candidate methylation differences were validated by targeted pyrosequencing assays. Pyrosequencing assays were developed for CpG sites less methylated in cytotrophoblasts than fibroblasts mapping to the promoter region of the beta subunit of human chorionic gonadotropin 5 (CGB5), as well as two CpG sites mapping to each of two tumor suppressor genes. Our data suggest that epigenetic regulation of gene expression is likely to be a key factor in the functional specificity of cytotrophoblasts. These data are proof of principle for cell-type specific epigenetic regulation in placenta and demonstrate that the methylation profile of placenta is mainly driven by cytotrophoblasts.Key words: cytotrophoblast purification, placental fibroblast purification, DNA methylation, epigenetics, placenta, cell type-specific methylation     

Interictal Neurocognitive Processing of Visual Stimuli in Migraine: Evidence from Event-Related Potentials

Research has established decreased sensory habituation as a defining feature in migraine, while decreased cognitive habituation has only been found with regard to cognitive assessment of the relative probability of the occurrence of a stimulus event. Our study extended the investigation of interictal habituation in migraine to include cognitive processing when viewing of a series of visually-complex images, similar to those we encounter on the internet everyday. We examined interictal neurocognitive function in migraine from a habituation perspective, using a novel paradigm designed to assess how the response to a series of images changes over time. Two groups of participants--migraineurs (N = 25) and non-migraine controls (N = 25)--were asked to view a set of 232 unfamiliar logos in the context of a target identification task as their brain electrical responses were recorded via event-related potentials (ERPs). The set of logos was viewed serially in each of 10 separate trial blocks, with data analysis focusing on how the ERP responses to the logos in frontal electrodes from 200-600 ms changed across time within each group. For the controls, we found that the amplitude of the late positive potential (LPP) ERP component elicited by the logos had no significant change across trial blocks. In contrast, in migraineurs we found that the LPP significantly increased in amplitude across trial blocks, an effect consistent with a lack of habituation to visual stimuli seen in previous research. Our findings provide empirical support abnormal cognitive processing of complex visual images across time in migraineurs that goes beyond the sensory-level habituation found in previous research.     

Design and analysis issues in genome-wide somatic mutation studies of cancer

The availability of the human genome sequence and progress in sequencing and bioinformatic technologies have enabled genome-wide investigation of somatic mutations in human cancers. This article briefly reviews challenges arising in the statistical analysis of mutational data of this kind. A first challenge is that of designing studies that efficiently allocate sequencing resources. We show that this can be addressed by two-stage designs and demonstrate via simulations that even relatively small studies can produce lists of candidate cancer genes that are highly informative for future research efforts. A second challenge is to distinguish mutated genes that are selected for by cancer (drivers) from mutated genes that have no role in the development of cancer and simply happened to mutate (passengers). We suggest that this question is best approached as a classification problem and discuss some of the difficulties of more traditional testing-based approaches. A third challenge is to identify biologic processes affected by the driver genes. This can be pursued by gene set analyses. These can reliably identify functional groups and pathways that are enriched for mutated genes even when the individual genes involved in those pathways or sets are not mutated at sufficient frequencies to provide conclusive evidence as drivers.     

Proteomic profiling of the Baltic Sea cyanobacterium Nodularia spumigena strain AV1 during ammonium supplementation

The cyanobacterium Nodularia spumigena dominates the annual, toxic summer blooms in the Baltic Sea. Although Nodularia has been receiving attention due to its production of the hepatotoxin nodularin, molecular data regarding the regulation of nitrogen fixation is lacking. We have previously reported that N. spumigena strain AV1, unlike model filamentous cyanobacteria, differentiates heterocysts in the absence of detectable nitrogen fixation activity. To further analyze the uncoupling between these two linked processes, we assessed the impact of ammonium ions on the N. spumigena metabolism using a proteomic approach. Proteomic profiling was performed at three different times during ammonium supplementation using quantitative 2-dimensional gel electrophoresis followed by MS/MS analysis. Using this approach, we identified 34 proteins, 28 of which were unique proteins that changed successively in abundance during growth on ammonium. Our results indicate that N. spumigena generally exhibits lower energy production and carbon fixation in the presence of ammonium and seems to be inefficient in utilizing ammonium as an external nitrogen source. The possibility of ammonium toxicity due to PSII damage was investigated and the results are discussed. Our findings have implications in regard to the strategies considered to manage the cyanobacterial blooms in the Baltic Sea.     

Sources of Variability in Metabolite Measurements from Urinary Samples

Background

The application of metabolomics in epidemiological studies would potentially allow researchers to identify biomarkers associated with exposures and diseases. However, within-individual variability of metabolite levels caused by temporal variation of metabolites, together with technical variability introduced by laboratory procedures, may reduce the study power to detect such associations. We assessed the sources of variability of metabolites from urine samples and the implications for designing epidemiologic studies.

Methods

We measured 539 metabolites in urine samples from the Navy Colon Adenoma Study using liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectroscopy (GC-MS). The study collected 2–3 samples per person from 17 male subjects (age 38–70) over 2–10 days. We estimated between-individual, within-individual, and technical variability and calculated expected study power with a specific focus on large case-control and nested case-control studies.

Results

Overall technical reliability was high (median intraclass correlation = 0.92), and for 72% of the metabolites, the majority of total variance can be attributed to between-individual variability. Age, gender and body mass index explained only a small proportion of the total metabolite variability. For a relative risk (comparing upper and lower quartiles of “usual” levels) of 1.5, we estimated that a study with 500, 1,000, and 5,000 individuals could detect 1.0%, 4.5% and 75% of the metabolite associations.

Conclusions

The use of metabolomics in urine samples from epidemiological studies would require large sample sizes to detect associations with moderate effect sizes.     

Patient-oriented gene set analysis for cancer mutation data

Recent research has revealed complex heterogeneous genomic landscapes in human cancers. However, mutations tend to occur within a core group of pathways and biological processes that can be grouped into gene sets. To better understand the significance of these pathways, we have developed an approach that initially scores each gene set at the patient rather than the gene level. In mutation analysis, these patient-oriented methods are more transparent, interpretable, and statistically powerful than traditional gene-oriented methods.