Microarray-relevant NIH Grants Awarded in FY 2009, May 13 – June 22
Abnormality in gene expression of key mediators of vitamin A action in COPD
Start date: May 11, 2009
Amount awarded to date: $73,250
Principal investigator: Salil Das
Sponsor: Meharry Medical College
This study aims to establish the relationship between the severity of emphysema and levels of expression of certain genes associated with chronic obstructive pulmonary disease and lung cancer development. The investigators have obtained formalin-fixed, paraffin-embedded and frozen lung tissues samples from COPD patients with mild, moderate, and severe emphysema. The samples will be age-matched and divided into two groups: smokers and non-smokers. After organizing the samples, the investigators plan to analyze the samples using immunohistochemistry, Western blot analysis, real-time PCR, and microarrays. If successful in establishing that there is a relationship between expression of the genes of the mediators of vitamin A action and COPD, the study could help in generating "potentially therapeutic drugs targeting some of these genes," investigators said in the abstract.
Meta-analysis of GWAS data to identify novel rheumatoid arthritis risk loci
Start date: May 12, 2009
Amount awarded to date: $279,038
Principal investigator: Robert Plenge
Sponsor: Brigham and Women's Hospital
The investigators in this study recently conducted a meta-analysis of three published genome-wide association studies of around 15,000 case-control samples of European ancestry, and found evidence for six additional rheumatoid arthritis risk loci — bringing the total number of validated loci to 11. According to the investigators, statistical modeling of the GWAS meta-analysis demonstrated that "less than half the genetic burden of RA can be explained by all known risk loci" and "dozens of additional common variants of modest effect size should be identified with more powerful GWAS." This project now aims to undertake the "largest GWAS performed to date to search for RA susceptibility loci," according to the abstract. The investigators also plan to "search for shared biological pathways implicated by our GWAS meta-analysis using novel literature mining methods developed in our laboratory." They hypothesize that "true RA risk genes share common biological pathways" and will test the hypothesis by "assessing the degree of similarity between genes in regions implicated by GWAS, where we define similarity using a text-based approach based on PubMed abstracts." Finally, the investigators plan to make all GWAS results available to the public.
Self-luminant microarrays and reader for rapid diagnostics
Start date: June 1, 2009
Amount awarded to date: $203,820
Principal investigator: Pavel Anzenbacher
Sponsor: Bowling Green State University
The aim of this project is to develop a fluorescence-based microarray diagnostic platform and a "rugged device" capable of reading DNA and protein microarrays for performing the routine array-based comprehensive DNA, protein, pathogen, and other analysis, "allowing for rapid diagnosis or ruling out a potential threat to human health early in the short period of time," according to the abstract. The investigators plan to develop disposable self- illuminated array slides with integrated backlighting and a portable microarray reader. According to the grant description, the self-illuminated microarray slides will consist of Agilent Technologies 105K microarray slides with fabricated resonant microcavity organic light-emitting diodes attached to the bottom that serve as the light source, designed to selectively excite a fluorescent label. The OLED array will be fabricated on the bottom of the sensing element array to form one thin sensor array, and the microcavity structure will be created by a distributed Bragg reflector or a semitransparent anode. Additionally, a portable array reader for the OLED-illuminated arrays will be developed that consists of simple optics and a camera. The reader will be based on "off-the-shelf components" such as a telecentric lens, CCD or CMOS camera, power source, and circuitry for data acquisition.
Heterogeneous cancer progression from microarray data.
Start date: June 1, 2009
Amount awarded to date: $298,436
Principal investigator: Russell Schwartz
Sponsor: Carnegie-Mellon University
Two classes of the phylogenetic or evolutionary tree models are currently used to subtype cancer patients based on gene expression data, according to this grant's abstract. One uses data gathered from gene-expression microarrays and another uses data gathered from cytometric studies, which assay small numbers of genes in individual cells isolated from tumors. The first, the investigators argue, allows a "far more complete picture of overall gene activity" while the second provides "valuable clues about tumor evolution by identifying which cell types co-occur in individual tumors." This project aims to develop a single approach with the advantages of both methods. First, the investigators will develop approaches to infer the existence of common cell types from bulk microarray measurements of tumors sampled across patient populations. Next, they will build on prior methods to infer evolutionary similarity between these tumor states. Finally, the investigators plan to adapt methods for cytometric tumor phylogenetics to the problem of inferring evolutionary sequences from these microarray states. The result will be a "unified approach for inferring evolution among individual cell states, as in a cytometric study, but assayed on thousands of genes, as in a microarray study." According to the abstract, the unified model will be validated on breast cancer data and applied to the discovery of common progression pathways in breast cancer populations.
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Development of a computational model for improved diagnostic accuracy of DNA microarrays
Start date: June 1, 2009
Amount awarded to date: $71,372
Principal investigator: David Stahl
Sponsor: University of Washington
The investigators plan to "improve the diagnostic accuracy of microarrays and characterize their detection limits by utilizing computational microarray modeling as a tool for design and validation of microarray data analysis methods," according to the abstract. For model validation, they will collect thermal hybridization and dissociation data from an in-house microfluidic microarray imaging platform, with the ultimate aim of developing a finite element mathematical model of microarray hybridization that captures the "essential features" of the group's platform, including competitive binding and dissociation in three-dimensional gel elements, diffusion and convective flow, effects of target length, concentration, and temperature. The investigators also plan to collect thermal hybridization and dissociation data to validate this model, and will also use the model to "generate simulated datasets, and assess the performance of selected analysis algorithms on datasets corresponding to samples of differing complexities."
Role of microRNAs in bronchopulmonary dysplasia
Start date: June 1, 2009
Awarded amount to date: $221,550
Principal investigator: Lin Liu
Sponsor: Oklahoma State University, Stillwater
Bronchopulmonary dysplasia is a chronic lung disease that develops in preterm neonates treated with oxygen and mechanical ventilation, causing arrested lung development, according to the grant abstract. The investigators hypothesize that the microRNAs in a pre-identified miRNAs pathway are "dysregulated during the progression of BPD in neonatal lungs and that these miRNAs regulate genes responsible for the development of BPD," according to the abstract. To test this hypothesis, the investigators plan to use miRNA microaroarrays to examine miRNA profiles of the normal and BPD lungs, later establishing functional roles of the selected miRNAs in BPD. They hope that the "elucidation of miRNAs' functions in the lung will provide insight into the normal mechanisms of lung development as well as aid in the design of therapies for BPD."
Computational tools to analyze SNP data from patients with mental illness
Start date: June 17, 2009
Amount awarded to date: $243,011
Principal investigator: Thomas Downey
St. Louis-based bioinformatics shop Partek plans to develop a software product that will "facilitate the analysis of genetic changes in order to elucidate chromosomal abnormalities that underlie diseases such as autism spectrum disorder, bipolar disorder, and schizophrenia," the investigators said in the grant abstract. According to the firm, there are "two main approaches to data analysis include copy number estimates, based on the intensity of hybridization of samples to SNP arrays, and genotype analysis, revealing heterozygosity and homozygosity." Partek aims to "add another dimension to the analysis of high density SNP data by incorporating information about the genetic relatedness of individuals" into its Partek Genomic Suite analysis tool as a new module. Ultimately, the developed module prototype will be used to analyze a set of 500,000 SNPs measured in 2,883 individuals from 700 families having two or more individuals affected with autism.
DNA methylation in photoreceptor-specific gene expression and retinal disease
Start date: July 1, 2009
Amount awarded to date: $246,000
Principal investigator: Shannath Merbs
Sponsor: Johns Hopkins University
Though there have been "significant advances" made in understanding the role of epigenetics in gene regulation in other fields, "little is known about the relationship between DNA methylation and tissue-specific gene expression in the developing and adult retina," according to this grant's abstract. This project aims to create a detailed molecular description of DNA methylation patterns around the transcription start site of two model PR-specific genes, Rbp3 and Rho, and answer how that methylation status changes during development. The investigators will use genome-wide array experiments to examine tissue-specific DNA methylation patterns in the adult and developing retina, and will explore the hypothesis that retinal degeneration may be associated with changing patterns of retinal DNA methylation.
Identification of microRNA biomarkers for lung cancer
Start date: July 1, 2009
Amount awarded to date: $273,456
Principal investigator: Elizabeth Mambo
Sponsor: Ambion Diagnostics
The goal of this project is to develop "biofluid-based lung cancer diagnostic markers that can be used for non-invasive, affordable detection of lung cancer at an early stage at which medical intervention can benefit the patients," according to the abstract. The investigators will use microRNA-profiling technologies to identify miRNAs that are differentially expressed between cancer-free subjects and lung cancer patients, with a focus on two subtypes of non-small-cell lung cancer, adenocarcinoma and squamous cell carcinoma. The project will use "highly-annotated clinical samples provided by academic collaborators to assemble age, gender and environment-balanced sample sets to analyze early stage cancers of both subtypes." Using this approach, the investigators hope to define generic miRNA biomarkers or biomarker classifiers for lung cancer, as well as biomarkers that are specific for each gender or cancer subtype. Their phase I goals are to demonstrate the "feasibility of identifying highly-specific and sensitive lung cancer biomarkers signatures from biofluids." Then, investigators will "establish the clinical validity of the biomarker signatures, and development of comprehensive assays to test for these signatures."
Nonparametric analysis of reverse-phase protein lysate array data
Start date: August 1, 2009
Amount awarded to date: $181,024
Principal investigator: Jianhua Hu
Sponsor: University of Texas MD Anderson Cancer Center
According to investigators, there exists a "lack of reliable statistical tools" for quantifying the information from protein-lysate arrays. The aim of this project is to quantify protein-lysate arrays by "fitting a monotone nonparametric response curve to all samples on the same array." The investigators also aim to "incorporate the modern shrinkage ideas in statistics into the nonparametric approach, leading to more stable quantification in time course experiments where the number of replicates is small at each time point." They propose the use of "wild-bootstrap for assessing uncertainty of the protein concentration estimates and for assessing the influence of such uncertainties in follow-up analyses."
Increasing the reliability of clinical microarray data analysis by systemic bias removal
Start date: Sept. 1, 2009
Amount awarded to date: $85,416
Principal investigator: Zoltan Szallasi
Sponsor: Children's Hospital Boston
Clinical microarray data sets contain a "significant level of systematic bias," according to the investigators, including technical bias, "such as the overall level of mRNA integrity in a given microarray sample." In response, the investigators are developing a method that could "correct for such technical biases in clinical microarray data that are produced on the various generally used microarray platforms." They also plan to evaluate the "overall impact of systematic bias correction in clinical microarray datasets" in this study by determining "whether clinical microarray measurements show better correlation with independent validation or during cross-validation."