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Harvard Nets $2.7M to Expand Microarray Profiling of Nursing Health Study Cohorts


The Harvard University School of Public Health will use $2.7 million in recently awarded National Institutes of Health funding to further characterize samples in its Nurses' Health Study biorepository using multiple microarray platforms.

Andrew Beck, an associate professor of pathology at Harvard Medical School who is participating in the effort, said that the researchers intend to use tissue microarrays, Affymetrix expression arrays, and, potentially, DNA methylation arrays to collect more information about the samples.

The Nurses' Health Study was established with NIH funding in 1976, and 122,000 registered nurses aged 30 to 55 were enrolled. The participants have provided information about their health and nutrition via routine questionnaires. In 1989, Harvard organized a second cohort of NHS participants, ultimately enrolling 116,000 women, aged 25 to 42. According to the project's website, blood and urine samples were collected from nearly 30,000 women in the late 1990s, and 16,000 provided blood and urine samples again between 2008 and 2011. The project has also collected tissue blocks of breast, ovarian, and melanoma samples.

According to Beck, these tissue blocks have already been used to make tissue micoarrays over the past several years, and the new funding will continue those efforts.

"You can put 250 patients on one block and do all kinds of in situ biomarker analysis," Beck told BioArray News. "We mostly do it for immunohistochemistry, for linking biomarkers with epidemiological risk factors, but also for linking markers with clinical outcome, such as survival."

Beck said that his lab has manually produced tissue microarrays in the past, but that it has recently adopted 3DHistech's TMA Master instrument to make the arrays.

Beyond tissue microarrays, Beck and colleagues are using Affymetrix's 6.9-million oligonucleotide GeneChip Human Transcriptome and Splice Junction Array to profile expression in about 750 tumor-normal pairs. Researchers from Stanford University led the development of the array, which Affy launched as a commercial product two years ago, marketing the $400-per-sample arrays as an alternative to RNA-seq (BAN 8/16/2011). It was also profiled in Proceedings of the National Academy of Sciences in March 2011.

Another application Beck and colleagues intend to adopt is DNA methylation analysis to "identify how modifiable behavior might affect the methylation of cancer and normal tissues." He said that the study currently relies on pyrosequencing assays to measure Line-1 methylation levels. The researchers would like to adopt a different assay to look at a larger number of samples, he said.

"We are looking for the right assay for genome-wide studies," said Beck. He said that Illumina's HumanMethylation450 BeadChips and next-generation sequencing-based Methyl-seq approaches were both being evaluated for future use.

Part of the reason Harvard is eager to extend its characterization of the NHSII samples is that it is now easier to obtain information from formalin-fixed, paraffin-embedded tissue than it was in the past, Beck noted.

"We've been very lucky in that in recent years there have been improvements in the extraction and analysis of FFPE," he said.

New Step

Harvard's new NIH grant was awarded June 1 and is set to expire in May 2018. The $2.7 million it received on June 1 is to support activities through mid-2014, and Beck said he was unsure of how much funding the project will net to continue its activities beyond that time. An email to principal investigator Walter Willett seeking additional information about the grant was not returned in time for this publication.

The primary purpose of the grant, according to its abstract, is to fund "cohort infrastructure," and, according to Beck, that will mean additional investments in tools to analyze the epidemiological data gained via questionnaires with the genetic data amassed from tissue, gene expression, and methylation array experiments.

"In the future, once these data sets are built, the question will be how to integrate them," said Beck. "This is a new step in the world of epidemiology," he said, noting that to date, most case-control studies have correlated single factors, such as consumption of high fat foods to increased risk of cancer. But, using microarrays, investigators will have to correlate those potential risk factors for as many different cancer expression profiles exist, which within the NHSII study could be tens of thousands.

"We will have to update our analysis methods," he said.

Fortunately, Beck said that the field of genomics has already created statistical methods that can be implemented in epidemiological studies.

"As the data expands, it will be important to expand this element of our infrastructure," he said, "but it's not like we are starting from scratch."