Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

Mathematical innovation turns blood draw into information gold mine in Stanford study

08.03.2010
Scientists at the Stanford University School of Medicine have devised a software algorithm that could enable a common laboratory device to virtually separate a whole-blood sample into its different cell types and detect medically important gene-activity changes specific to any one of those cell types.

In a study to be published online March 7 in Nature Methods, the scientists reported that they had successfully used the new technique to pinpoint changes in one cell type that flagged the likelihood of kidney-transplant recipients rejecting their new organs.

Without the software, these gene-activity flags would have gone unnoticed. The authors believe that the use of the new algorithm may have applications beyond kidney rejection, allowing doctors to better identify the onset of cancers, genetic disorders and a variety of other problems.

The lab device, called a microarray, is a standard research tool. But until the development of this algorithm, scientists and physicians have not been able to use it to derive such medically useful information from whole-blood samples. Part of the problem is that the information is obscured by the whole-blood samples' complex, multiple-component composition.

"Drawing blood is one of the most common diagnostic tests in clinical practice," said one of the investigators, Atul Butte, MD, PhD, assistant professor of pediatrics and of medical informatics. "We'd love to be able to use microarrays to find changes in the blood that indicate trouble somewhere in the body. But distinguishing one type of cell from another can be critical to doing that."

Butte is a senior author of the paper, along with Mark Davis, PhD, director of the Stanford Institute for Immunity, Transplantation and Infection. The two lead authors are postdoctoral scholar Shai Shen-Orr, PhD, and Robert Tibshirani, PhD, professor of health research and policy and of statistics.

The potential for extracting important information from a blood sample has mushroomed since the advent of the microarray about 15 years ago. A microarray is a man-made, thumbnail-sized grid of DNA on whose surface reside tens of thousands of tiny sensors that can distinguish among different short sequences of nucleic acids — the genetic material of all life. Such a chip can be immersed in an extract from living cells, such as blood; then, whenever a sensor on the chip detects a matching nucleic-acid sequence, it transmits a fluorescent signal recording the sequence's presence.

By using microarrays to measure how actively a gene is being "expressed," research scientists can detect medically important alterations in a tissue. As they get steadily cheaper and easier to work with, microarrays are also at the threshold of widespread use as clinical diagnostic devices.

Still, whole blood poses a complication when used as a sample in microarray analyses. "Any 7-year-old can look at a blood sample under a microscope and see it's a mix of a huge number of different kinds of cells," said Butte, who is also director of the Center for Pediatric Bioinformatics at Lucile Packard Children's Hospital. A single sample contains dozens of cell types, at different levels of maturity or at different stages of activation. A gene-expression change that, in one cell type, means something has gone terribly wrong may in another cell type be completely benign, or even a sign of needed activation. But a microarray has no way of knowing which kind of cell in the mix a particular nucleic-acid snippet came from.

To make things more difficult, the composition of samples drawn from two different patients — or even of two samples drawn at different times from the same patient — varies dramatically.

Imagine that a public-opinion analyst, new on the job, were to conduct two national voter-preference surveys before and after a politician's speech, to see if that speech improved or impaired the popularity of a piece of legislation. But the rookie analyst has neglected to ask those surveyed which party they lean toward or what state they come from, so doesn't realize the first survey sample had a Democrat-to-Republican ratio of 30:70, while in the second, the ratio was reversed. The analyst might mistakenly infer a huge swing in pre- and post-speech preferences, when in fact the only real change was in the samples' compositions. Meanwhile, a vehement change in support among residents of a small but election-swinging state might go undetected.

In the same way, comparing a gene-expression pattern based on one person's whole-blood sample to another person's, or even the same person's blood over time, isn't very informative with a typical microarray run. Medically significant changes in gene-expression patterns can go unnoticed in those tests, while those that reflect changes in the composition of the sample may trigger false alarms.

While ways of separating whole blood into its constituent cell types do exist, these methods are too tedious, time-consuming and costly for routine clinical diagnostics and, for similar reasons, pose a challenge for research on large groups of subjects.

So the investigators devised an algorithm — in this case, a very large number of fairly simple equations. They believed that the simultaneous solution for all these equations enabled the assigning of gene-expression changes to particular cell types in patients' blood samples.

To test their algorithm's accuracy, the researchers obtained whole blood samples from 24 pediatric kidney-transplant patients. Fifteen of the 24 patients were experiencing symptoms of acute transplant rejection, while nine were in stable condition.

Because complete blood counts had been routinely performed on these patients, the frequencies within each sample of five important blood-cell types — monocytes, lymphocytes, neutrophils, basophils and eosinophils — were known.

Analyzing patients' whole blood samples via microarrays without resorting to the new algorithm, the investigators couldn't distinguish any gene-expression pattern differences between the two patient groups. But when they used the new algorithm, they found hundreds of differences in gene expression. Those differences could be used to tell which patients were rejecting their transplants and which were not. Of equal importance, this method let the researchers see that these changes were largely confined to one particular cell type: the monocytes. Only the new virtual-separation technique made fingering this cellular culprit possible.

"It was like a giant arrow pointing to the biological source of the rejection problem," said Davis, the Burton and Marion Avery Family Professor of Immunology and a Howard Hughes Medical Institute investigator.

Other Stanford co-authors were Dale Bodian, PhD; Trevor Hastie, PhD; Purvesh Khatri, PhD; Nicholas Perry; and Minnie Sarwal, MD, PhD. None of the co-authors has any financial stake in the new software technology. They intend to distribute it to the academic and nonprofit investigator communities free of charge and, perhaps, to license it to for-profit companies in order to speed its dissemination.

The study was supported by the National Institute of Allergy and Infectious Diseases, the National Heart Lung, and Blood Institute and the National Cancer Institute, all arms of the National Institutes of Health.

The Stanford University School of Medicine consistently ranks among the nation's top 10 medical schools, integrating research, medical education, patient care and community service. For more news about the school, please visit http://mednews.stanford.edu. The medical school is part of Stanford Medicine, which includes Stanford Hospital & Clinics and Lucile Packard Children's Hospital. For information about all three, please visit http://stanfordmedicine.org/about/news.html.

BROADCAST MEDIA CONTACT: M.A. Malone at (650) 723-6912 (mamalone@stanford.edu)

Bruce Goldman | EurekAlert!
Further information:
http://www.stanford.edu

More articles from Studies and Analyses:

nachricht WAKE-UP provides new treatment option for stroke patients | International study led by UKE
17.05.2018 | Universitätsklinikum Hamburg-Eppendorf

nachricht First form of therapy for childhood dementia CLN2 developed
25.04.2018 | Universitätsklinikum Hamburg-Eppendorf

All articles from Studies and Analyses >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Powerful IT security for the car of the future – research alliance develops new approaches

The more electronics steer, accelerate and brake cars, the more important it is to protect them against cyber-attacks. That is why 15 partners from industry and academia will work together over the next three years on new approaches to IT security in self-driving cars. The joint project goes by the name Security For Connected, Autonomous Cars (SecForCARs) and has funding of €7.2 million from the German Federal Ministry of Education and Research. Infineon is leading the project.

Vehicles already offer diverse communication interfaces and more and more automated functions, such as distance and lane-keeping assist systems. At the same...

Im Focus: Molecular switch will facilitate the development of pioneering electro-optical devices

A research team led by physicists at the Technical University of Munich (TUM) has developed molecular nanoswitches that can be toggled between two structurally different states using an applied voltage. They can serve as the basis for a pioneering class of devices that could replace silicon-based components with organic molecules.

The development of new electronic technologies drives the incessant reduction of functional component sizes. In the context of an international collaborative...

Im Focus: LZH showcases laser material processing of tomorrow at the LASYS 2018

At the LASYS 2018, from June 5th to 7th, the Laser Zentrum Hannover e.V. (LZH) will be showcasing processes for the laser material processing of tomorrow in hall 4 at stand 4E75. With blown bomb shells the LZH will present first results of a research project on civil security.

At this year's LASYS, the LZH will exhibit light-based processes such as cutting, welding, ablation and structuring as well as additive manufacturing for...

Im Focus: Self-illuminating pixels for a new display generation

There are videos on the internet that can make one marvel at technology. For example, a smartphone is casually bent around the arm or a thin-film display is rolled in all directions and with almost every diameter. From the user's point of view, this looks fantastic. From a professional point of view, however, the question arises: Is that already possible?

At Display Week 2018, scientists from the Fraunhofer Institute for Applied Polymer Research IAP will be demonstrating today’s technological possibilities and...

Im Focus: Explanation for puzzling quantum oscillations has been found

So-called quantum many-body scars allow quantum systems to stay out of equilibrium much longer, explaining experiment | Study published in Nature Physics

Recently, researchers from Harvard and MIT succeeded in trapping a record 53 atoms and individually controlling their quantum state, realizing what is called a...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

VideoLinks
Industry & Economy
Event News

In focus: Climate adapted plants

25.05.2018 | Event News

Save the date: Forum European Neuroscience – 07-11 July 2018 in Berlin, Germany

02.05.2018 | Event News

Invitation to the upcoming "Current Topics in Bioinformatics: Big Data in Genomics and Medicine"

13.04.2018 | Event News

 
Latest News

In focus: Climate adapted plants

25.05.2018 | Event News

Flow probes from the 3D printer

25.05.2018 | Machine Engineering

Less is more? Gene switch for healthy aging found

25.05.2018 | Life Sciences

VideoLinks
Science & Research
Overview of more VideoLinks >>>