Personalized medical care that takes into account information derived from sequencing a patient’s entire genome came a step closer this week as US researchers revealed how they used a healthy man’s genome to assess his risk of contracting dozens of diseases and likely responses to several common medications.
You can read about the study, led by researchers from Stanford University School of Medicine in California, online in the 1 May issue of The Lancet.
Dr Jeremy Berg, director of the NIH’s National Institute of General Medical Sciences, one of the sponsors of the research, said the study shows how genomics, the science of sequencing genomes, can make medical care more personalized:
“When combined with other sources of information, genomics has the power to predict the diseases a person is most likely to develop and how he or she might respond to certain medicines.”
The researchers, who compiled an overall risk analysis from the genome sequence and more traditional clinical measurements, suggested such an approach will be within reach of the average physician within the next ten years.
However, it is not the information per se that poses a medical challenge, but how to use it.
First author Dr Euan Ashley, cardiologist and assistant professor of medicine at Stanford University School of Medicine, who headed the team of geneticists, physicians, bioinformaticians and ethicists involved in the study, told the media that:
“The $1,000 genome is coming fast,” but the challenge, he said, “lies in knowing what to do with all that information”.
Ashley and colleagues believe that this study has helped to establish the priorities that will be “most helpful when a patient and a physician are sitting together looking at the computer screen”.
For example, take medications. Clinical trials tell us what the potential harms and benefits of drugs might be for the “average” patient. But what doctors and patients really need to know, is whether an individual patient is likely to react like a typical trial participant, or is he or she likely to be one of the participants who has a bad reaction, or perhaps even, a particularly good reaction.
Another area where knowing genome data might help is where risk factors interact: for instance, to what extent might a patient’s obesity or smoking interact with a genetic factor that protects or puts them at higher risk of heart attack or diabetes?
For the study, the researchers used information from the complete genome sequence of Dr Stephen Quake, who is the Lee Otterson Professor of Bioengineering at Stanford, and who last autumn hit the headlines when he announced that use of a new technology had enabled him to sequence his own genome for under $50,000, which he also published.
Quake told the media that:
“We’re at the dawn of a new age in genomics.”
“Information like this will enable doctors to deliver personalized health care like never before,” he added, explaining for example, that it will help fine tune care so that patients at higher risk get closer, more relevant surveillance and patients at lower risk are spared unnecessary tests.
Another benefit, said Quake, is the financial savings that will accrue from improved efficiency.
However, there is a downside: what about the things that patients may not wish to know about, and how should that information be handled?
The ethical and practical challenges posed by this question are addressed by senior author Dr Hank Greely, professor and director of Stanford’s Center for Law and the Biosciences, and colleagues in a separate paper published in the same issue of the journal.
Greely commented that we need to start thinking “hard and soon” about what to do with the “tsunami” of data that a genome sequence produces.
Investigation into Quake’s genome began when the 40-year old, apparently healthy man, asked Ashley what he thought about a piece of information from his genome that showed he was at risk for hypertrophic cardiomyopathy, an inherited condition where the heart is enlarged, doesn’t beat properly, and puts the carrier at risk of sudden cardiac death.
Added to this, was a piece of family history: Quake told Ashley a distant relative had died in his sleep at age 19, presumably from a heart condition.
This rang alarm bells fro Ashley, who runs Stanford’s Hypertrophic Cardiomyopathy Center: putting the two pieces of information together, the genetic and family history, he recommended Quake be screened for the condition.
Quake agreed to the screening, but then the two men got thinking about how to take the whole thing to another level: what else might Quake’s genome reveal?
Ashley said he and others were already wondering how the information held in the billions of DNA base pairs in a person’s genome might be turned into something that is clinically useful. Where would they start?
“Then we realized,” said Ashley, ” we already have someone’s genome”.
And, another lucky break was that co-author Dr Atul Butte, assistant professor in bioinformatics at Stanford, and members of his lab had already done a lot of the information sorting because they had spent one and a half years cataloguing information about links between certain SNPs (single nucleotide polymorphisms) and particular diseases.
This was the first time anyone had compiled such a database, and as Butte explained, it involved reading thousands of articles, and making a list of every point on the genome where for instance they found that “the letter A raises the risk of a particular disease, or the letter T confers protection”.
When Quake came along with his genome, they were ready, said Butte.
For the study, the researchers compiled an algorithm that brought together what was already known, using traditional methods, about Quake’s disease risks, with that revealed by his genome sequence and the information they had in their SNP database.
For example, the traditional method, based on Quake’s age and gender (a 40-year old male), gave a risk profile for 55 conditions, ranging from obesity and diabetes to schizophrenia and gum disease, including a 16 per cent likelihood of developing prostate cancer during his lifetime.
However, when the algorithm started to factor in the information from Quake’s genome, the prostate cancer risk first went lower, and then went higher, eventually after incorporating information from 18 different SNP variants derived from 54 studies, Quake’s risk of developing prostate cancer came out at 23 per cent.
When they did the same thing for his risk of Alzheimer’s, the pattern went the other way. Traditional risk factors put his risk at 9 per cent, but after plugging in the genome information, the algorithm brought this down to 1.4 per cent, because of the protective factors indicated in his particular Alzheimer’s related SNP variants.
In terms of drug responses, the algorithm also revealed that some of Quake’s SNP variants suggested he might have unusual responses to certain heart medications, which would be important information in the light of his cardiovascular risk factors.
But the most alarming information was his obesity, type-2 diabetes and coronary artery disease risks: these came out at over 50 per cent, and we also know that there is a chance that they can affect each other.
Quake said that while he was curious to know everything that his genome could tell him about his own disease risks, it was important to recognize that:
“… not everyone will want to know the intimate details of their genome, and it’s entirely possible that this group will be the majority.”
“There are many ethical, educational and policy questions that need to be addressed going forward,” said Quake.
The researchers said this study is proof of concept that whole-genome sequencing offers clinically useful information for doctors helping individual patients.
They stressed that many challenges remain, however, including how the effect of environment interacts with genetic risk factors, which is difficult to quantify and can change during a person’s lifetime.
They concluded that as medicine moves toward greater use of genome sequencing, we will need teams of people who have not just the medical skills, but also experience and knowledge from disciplines like genetics, ethics, and health-care delivery.
“Clinical assessment incorporating a personal genome.”
Euan A Ashley, Atul J Butte, Matthew T Wheeler, Rong Chen, Teri E Klein, Frederick E Dewey, Joel T Dudley, Kelly E Ormond, Aleksandra Pavlovic, Alexander A Morgan, Dmitry Pushkarev, Norma F Neff, Louanne Hudgins, Li Gong, Laura M Hodges, et al.
DOI:10.1016/S0140-6736(10)60452-7
Sources: Stanford University Medical Center , NIH/National Institute of General Medical Sciences.
Written by: Catharine Paddock, PhD