Kimberly Bunce

Noninvasive prenatal diagnosis of a fetal microdeletion syndrome.

This proof-of-principle study shows that it is possible to detect a genetic microdeletion carried by a fetus through analysis of DNA in circulating maternal blood.

A microarray‐based approach for the identification of epigenetic biomarkers for the noninvasive diagnosis of fetal disease

We describe a novel microarray‐based approach for the high‐throughput discovery of epigenetic biomarkers for use in the noninvasive detection of fetal genetic disease.

Comprehensive Analysis of Preeclampsia-Associated DNA Methylation in the Placenta

Background A small number of recent reports have suggested that altered placental DNA methylation may be associated with early onset preeclampsia. It is important that further studies be undertaken to confirm and develop these findings. We therefore undertook a systematic analysis of DNA methylation patterns in placental tissue from 24 women with preeclampsia and 24 with uncomplicated pregnancy outcome. Methods We analyzed the DNA methylation status of approximately 27,000 CpG sites in placental tissues in a massively parallel fashion using an oligonucleotide microarray. Follow up analysis of DNA methylation at specific CpG loci was performed using the Epityper MassArray approach and high-throughput bisulfite sequencing. Results Preeclampsia-specific DNA methylation changes were identified in placental tissue samples irrespective of gestational age of delivery. In addition, we identified a group of CpG sites within specific gene sequences that were only altered in early onset-preeclampsia (EOPET) although these DNA methylation changes did not correlate with altered mRNA transcription. We found evidence that fetal gender influences DNA methylation at autosomal loci but could find no clear association between DNA methylation and gestational age. Conclusion Preeclampsia is associated with altered placental DNA methylation. Fetal gender should be carefully considered during the design of future studies in which placental DNA is analyzed at the level of DNA methylation. Further large-scale analyses of preeclampsia-associated DNA methylation are necessary.

High resolution non-invasive detection of a fetal microdeletion using the GCREM algorithm.

The non‐invasive prenatal detection of fetal microdeletions becomes increasingly challenging as the size of the mutation decreases, with current practical lower limits in the range of a few megabases. Our goals were to explore the lower limits of microdeletion size detection via non‐invasive prenatal tests using Minimally Invasive Karyotyping (MINK) and introduce/evaluate a novel statistical approach we recently developed called the GC Content Random Effect Model (GCREM).

Structural and Regulatory Characterization of the Placental Epigenome at Its Maternal Interface

Epigenetics can be loosely defined as the study of cellular “traits” that influence biological phenotype in a fashion that is not dependent on the underlying primary DNA sequence. One setting in which epigenetics is likely to have a profound influence on biological phenotype is during intrauterine development. In this context there is a defined and critical window during which balanced homeostasis is essential for normal fetal growth and development. We have carried out a detailed structural and functional analysis of the placental epigenome at its maternal interface. Specifically, we performed genome wide analysis of DNA methylation in samples of chorionic villus (CVS) and maternal blood cells (MBC) using both commercially available and custom designed microarrays. We then compared these data with genome wide transcription data for the same tissues. In addition to the discovery that CVS genomes are significantly more hypomethylated than their MBC counterparts, we identified numerous tissue-specific differentially methylated regions (T-DMRs). We further discovered that these T-DMRs are clustered spatially along the genome and are enriched for genes with tissue-specific biological functions. We identified unique patterns of DNA methylation associated with distinct genomic structures such as gene bodies, promoters and CpG islands and identified both direct and inverse relationships between DNA methylation levels and gene expression levels in gene bodies and promoters respectively. Furthermore, we found that these relationships were significantly associated with CpG content. We conclude that the early gestational placental DNA methylome is highly organized and is significantly and globally associated with transcription. These data provide a unique insight into the structural and regulatory characteristics of the placental epigenome at its maternal interface and will drive future analyses of the role of placental dysfunction in gestational disease.

Discovery of epigenetic biomarkers for the noninvasive diagnosis of fetal disease.

The primary goal of this study was to identify CpG sites in the human genome that are differentially methylated in DNA obtained from chorionic villus sampling (CVS) samples and gestational age‐matched maternal blood cell (MBC) samples.

Statistical considerations for digital approaches to non-invasive fetal genotyping

MOTIVATION A growing body of literature has demonstrated the potential for non-invasive diagnosis of a variety of human genetic diseases using cell-free DNA extracted from maternal plasma samples in early gestation. Such methods are of great significance to the obstetrics community because of their potential use as clinical standard of care. Proof of concept for such approaches has been established for aneuploidy and paternally inherited dominant traits. Although significant progress has recently been made, the non-invasive diagnosis of monogenic diseases that segregate in a recessive mendelian fashion is more problematic. Recent developments in microfluidic digital PCR and DNA sequencing have resulted in a number of recent advances in this field. These have largely, although not exclusively, been used for the development of diagnostic methods for aneuploidy. However, given their prevalence, it is likely that such methods will be utilized towards the development of non-invasive methods for diagnosing monogenetic disorders. RESULTS With this in mind, we have undertaken a statistical modeling of three contemporary (digital) analytical methods in the context of prenatal diagnosis using cell free DNA for monogenic diseases that segregate in a recessive mendelian fashion. We provide an experimental framework for the future development of diagnostic methods in this context that should be considered when designing molecular assays that seek to establish proof of concept in this field.

Comprehensive analysis of the transcriptional response of human decidual cells to lipopolysaccharide stimulation

Decidual cells are central to innate immunity at the maternal/fetal interface. We sought to characterize the response of decidual cells to stimulation and then removal of lipopolysaccharide (LPS) using a whole genome approach. Decidual cells were isolated from term unlabored cesarean sections. Cells were stimulated with LPS and RNA isolated both pre-stimulation and 2 and 24 h post-stimulation. Media were changed and RNA extracted 48 h later. Gene expression was measured using Agilent 44K whole genome microarrays. Data were visualized and interpreted using Ingenuity Pathway Analysis (IPA) software and selected (n=5) target gene expression was verified with quantitative real-time PCR. Genes related to immune function were up-regulated at 2 and 24 h after LPS exposure and then generally returned to baseline or were at least substantially reduced after LPS removal. Pathway analysis also revealed that genes involved in lipid metabolism (specifically cholesterol and steroid biosynthesis), iron metabolism, and the plasminogen system were coordinately altered following exposure to LPS. Our novel, preliminary findings provide insight into possible mechanisms via which the host inflammatory response could contribute to preterm birth and warrant further investigation in preterm samples.

DNA methylation alters transcriptional rates of differentially expressed genes and contributes to pathophysiology in mice fed a high fat diet

Objective Overnutrition can alter gene expression patterns through epigenetic mechanisms that may persist through generations. However, it is less clear if overnutrition, for example a high fat diet, modifies epigenetic control of gene expression in adults, or by what molecular mechanisms, or if such mechanisms contribute to the pathology of the metabolic syndrome. Here we test the hypothesis that a high fat diet alters hepatic DNA methylation, transcription and gene expression patterns, and explore the contribution of such changes to the pathophysiology of obesity. Methods RNA-seq and targeted high-throughput bisulfite DNA sequencing were used to undertake a systematic analysis of the hepatic response to a high fat diet. RT-PCR, chromatin immunoprecipitation and in vivo knockdown of an identified driver gene, Phlda1, were used to validate the results. Results A high fat diet resulted in the hypermethylation and decreased transcription and expression of Phlda1 and several other genes. A subnetwork of genes associated with Phlda1 was identified from an existing Bayesian gene network that contained numerous hepatic regulatory genes involved in lipid and body weight homeostasis. Hepatic-specific depletion of Phlda1 in mice decreased expression of the genes in the subnetwork, and led to increased oil droplet size in standard chow-fed mice, an early indicator of steatosis, validating the contribution of this gene to the phenotype. Conclusions We conclude that a high fat diet alters the epigenetics and transcriptional activity of key hepatic genes controlling lipid homeostasis, contributing to the pathophysiology of obesity.

Comparative evaluation of the Minimally-Invasive Karyotyping (MINK) algorithm for non-invasive prenatal testing

Minimally Invasive Karyotyping (MINK) was communicated in 2009 as a novel method for the non-invasive detection of fetal copy number anomalies in maternal plasma DNA. The original manuscript illustrated the potential of MINK using a model system in which fragmented genomic DNA obtained from a trisomy 21 male individual was mixed with that of his karyotypically normal mother at dilutions representing fetal fractions found in maternal plasma. Although it has been previously shown that MINK is able to non-invasively detect fetal microdeletions, its utility for aneuploidy detection in maternal plasma has not previously been demonstrated. The current study illustrates the ability of MINK to detect common aneuploidy in early gestation, compares its performance to other published third party methods (and related software packages) for prenatal aneuploidy detection and evaluates the performance of these methods across a range of sequencing read inputs. Plasma samples were obtained from 416 pregnant women between gestational weeks 8.1 and 34.4. Shotgun DNA sequencing was performed and data analyzed using MINK RAPIDR and WISECONDOR. MINK performed with greater accuracy than RAPIDR and WISECONDOR, correctly identifying 60 out of 61 true trisomy cases, and reporting only one false positive in 355 normal pregnancies. Significantly, MINK achieved accurate detection of trisomy 21 using just 2 million aligned input reads, whereas WISECONDOR required 6 million reads and RAPIDR did not achieve complete accuracy at any read input tested. In conclusion, we demonstrate that MINK provides an analysis pipeline for the detection of fetal aneuploidy in samples of maternal plasma DNA.