As the director of Britain’s Wellcome Trust Center for Human Genetics, Peter Donnelly oversees research that provides vital raw material for the 23andMe Personal Genome Service™ — specifically, correlations between one-letter DNA variations, known as SNPs, and particular diseases.

Those correlations are made by research projects known as genome-wide association studies (GWAS), which scan the genomes of people with a disease and similar individuals who don’t, then look for statistically significant genetic differences between the two groups. The studies can be enormous — last year the Wellcome Trust published the results of a GWAS that analyzed data from 17,000 participants and found genetic associations with seven different diseases — coronary heart disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, Crohn’s disease, bipolar disorder and hypertension.

In a commentary published this week by Nature, Donnelly assessed what GWAS have been able to achieve so far, and argued that in most cases, people should be able to gain valuable information from having access to their own genomes.

Here’s Donnelly’s reasoning in his own words:

For a particular disease, most individuals will have inherited some sequence variants that confer risk and some variants that provide protection, and they will therefore have an overall risk around average. A small proportion of people, however, will have inherited mainly variants that confer risk of developing the disease. Using Crohn’s disease as an example … the top 5% of the UK population … have a 5—8-fold higher risk than average of developing the disease, whereas the top 1% have a 9—15-fold higher risk.

Using statistics from the US, that amounts to a risk increase from the poplation average of less than 0.5% to somewhere in the neighborhood of 4-7%. Performing the same calculations for type 2 diabetes, Donnelly concludes that 1% of the population would end up having a 4-fold risk increase, which amounts to about a 50/50 chance of developing the disease.

“Across 50 diseases,” Donnelly continues (23andMe provides complete estimates of lifetime genetic risk due to known SNPs for 10 common diseases),

making the simplifying assumption that susceptibility to each disease is independent of susceptibility to every other disease, almost everyone will be in the top 5% of risk for at least one disease, and nearly half of all people will be in the top 1% for at least one disease. … Given that it is possible to reduce the risk of developing certain diseases, I can see the value of knowing about the genetic risks now.

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The structure of DNA was first publicly described 55 years ago at Cold Spring Harbor Laboratory (CSHL) on Long Island in New York by James Watson. Thursday night, the now 80-year-old Watson opened up the 2008 Personal Genomes meeting at CSHL by telling the story of the origins of the Human Genome Project, which he headed from 1990 to 1992. In 2003 the Human Genome Project produced a (nearly) complete reference DNA sequence of a human genome that is now essential to basic and applied human genetic research.

These days, Watson pointed out, scientists are able to read the DNA letters of the double helix so quickly and inexpensively that it is becoming practical to sequence the genomes of large numbers of people. With this progress comes a flood of research questions, technological challenges, and hope that these insights from the lab will translate into advances in personalized medicine.

Watson was followed on Thursday night by Francis Collins, who also followed him as director of the Human Genome Project, and later by Mary-Claire King, the renowned breast cancer geneticist from the University of Washington. Collins pointed out that health care costs have risen steadily over the years to the current level of roughly 20% of the US GDP. How much of this is spent on treatments that might have been identified as unnecessary with the availability of genetic information? He suggested that widespread genomic sequencing and analysis could lead to the discovery of the genetic causes of common diseases, such as lung cancer and Type II diabetes, for which some genetic links are now known, but much more remains to be learned.

Mary-Claire King considered breast cancer as a case study for personalized medicine. In the case of breast cancer, she noted, there are more than a thousand known mutations in each the genes BRCA1 and BRCA2 that can predispose a woman to the disease. Many of these are unique to specific families, or specific localities — she gave the example of one BRCA mutation endemic to a Norwegian valley. King illustrated through recent breast cancer studies that linking newly-discovered mutations to disease is a formidable technical challenge, but emphasized that the rewards for succeeding in doing so would be immense: roughly 5% of new breast cancer cases in the US each year — around 10,000 — are linked to known BRCA1/2 mutations, and thus might have been prevented through such measures as prophylactic mastectomy.

Friday moved into reports from the trenches. The morning session consisted of talks by researchers from major genome sequencing centers and from the companies behind the so-called “next generation” sequencing methods that underlie this conference. The new technologies, namely Illumina’s Solexa, 454’s FLX, and ABI’s SOLiD, follow the same general plan as the venerable Sanger sequencing method: scan short fragments, or ‘reads’, of DNA letters, and then reconstruct the original sequence from the reads. They just do it much faster than before, mainly by doing the scanning of many reads in parallel. Much of the concern these days is on the reliability of these new techniques — considering that a single changed DNA letter can mean the difference, for example, between getting Alzheimer’s or not — and so the presentations tended to focus on technical topics like error rates and comparisons across platforms. Even so, there were suggestions that some exciting new scientific findings might be around the corner; Richard Gibbs of Baylor showed early data from their sequencing of a HapMap trio (a father, mother and child) suggesting that the human mutation rate might be much higher than previously thought. And Elaine Mardis from Washington University showed that her lab had been able to find mutations unique to tumor tissue in a lung cancer patient. Known as somatic mutations, they had arisen in the patient during their lifetime, and were not found in non-tumorous skin tissue from the same patient. Her study did not show that one of these mutations had actually caused the cancer, but the demonstration that such changes may even be found is intriguing.

The afternoon session moved into the imposing task of storing, processing and interpreting the flood of data these new technologies generate. Paul Flicek from the European Bioinformatics Institute produced that rarest of things, the funny bioinformatics talk, in describing the travails of dealing with the 100 terabytes (that’s 100,000 gigabytes, or 100 million megabytes) generated so far by the pilot phase of the 1000 Genomes Project , and the specter of dealing with a petabyte (1,000 terabytes) of sequence data. Carlos Bustamante of Cornell described some of the insights into human evolutionary history that have made possible by the DNA deluge, including using sequence data to infer possibly the most detailed models yet of historical human population size and migrations. He also described his lab’s and John Novembre’s recent findings on the relationships between geography and human genetics; a topic we’ve blogged on recently at the Spittoon here and here.

There’s another big day of talks to come here at CSHL. I’m glad to be here keeping up to date on the latest research, so we can incorporate it into 23andMe, and to show off the site to a bunch of people on the cutting edge of genetics.

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A new paper by Venter and colleagues at his Rockville, Maryland-based institute provides a prime example. Writing in the September issue of Clinical Phamacology & Therapeutics, Venter et al. argue that knowing how genetic differences between ethnicities affect patients’ reactions to certain medications isn’t good enough. To make sure patients get the best healthcare, they say, doctors should be looking at how each person is likely to respond to a particular drug regimen based on his or her unique genetic makeup.

“Even the term ‘Caucasian’ can be deceptive,” the authors noted. “If a self-identified Caucasian originates from a founder population in which certain disease-specific alleles occur at higher frequencies (e.g. Quebec French Canadians or Ashkenazi Jews), his or her doctor may miss an important aspect of the patient’s medical history. One’s ethnicity/race is, at best, a probabilistic guess at one’s true genetic makeup.”

To further emphasize the differences between people within the same ethnic group, the authors compare the publicly available genome sequences of Venter himself and Nobel Prize winner James Watson, focusing on six genes involved in drug metabolism.

One of those genes revealed a substantial difference between the two men. CYP2D6 is involved in the metabolism of various drugs for high blood pressure, heart arrhythmia and depression. Venter’s genotype indicates that like most Europeans he is an “extensive metabolizer” of such drugs; but Watson’s genotype puts him in the “intermediate metabolizer” category, which is more common among Asians.

Using race as a guide, the authors noted, a physician would have no reason to expect Venter and Watson to react differently to drugs that are metabolized by CYP2D6.

Venter and his colleagues conclude by emphasizing the need for personalized health care based on genomic information, adding that the cost to do so is dropping rapidly.

“Given the complex nature of drug responses, it would ultimately better serve all to dissect the relevant factors of a drug response instead of categorically stereotyping a culture with a presumed genetic background.”

Images: Venter photo by Michael Janich; Watson photo courtesy of the National Library of Medicine

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We agree that this evolving field of personal genomics is in need of proper regulatory oversight. While our mission to provide accurate and contextual information to our customers about their genetic information is aligned with the regulatory mandate to protect the public health, we also want to ensure that efforts to rein in our industry do not hamper the potential benefit of genetic knowledge to our health.

Most recipients of healthcare—those of us who are lucky enough to have health insurance or other means to pay for health-related services—recognize that it cannot remain one-size-fits-all. Whether you’ve had a bad reaction to a drug or felt that your physician’s diagnosis didn’t hit the mark, it’s clear that our healthcare system has a long way to go before we advance to a more personalized approach. Genetics could move us toward that goal by revealing the roots of common diseases, providing the basis for more accurate diagnostics and giving doctors information about how a patient may respond to a particular drug or treatment.

The blood-thinning drug warfarin (Coumadin) is a great example of how far doctors are from using genetics in their practices. Right now physicians typically prescribe a standard dose for all patients. Then they closely monitor each patient through blood tests to make sure the dose isn’t too high (which could cause excessive bleeding and other complications) or too low (allowing clots to form).

This trial-and-error process is costly and inconvenient; the hope is that it could eventually be supplemented with a molecular-based approach. Genetic studies have identified several genes that play a role in how individuals respond to warfarin. The FDA has even added language to package inserts suggesting that measurement of these genes could be used to help doctors determine dosage levels. But asking doctors to trust genetics requires a leap of faith that most are not willing to take, especially in the United States’ litigious environment.

What is needed is an on-going (prospective) study that follows thousands of patients on warfarin who are under-going blood testing AND who have been genotyped. By collecting drug response data on an on-going basis through accepted practices as well as examining the genetic profiles of these same individuals, evidence-based proof could be established that the medical community needs before they’ll trust genetic markers.

Now imagine this same scenario for pretty much every other drug on the market. Unfortunately, no existing mechanism can gather the massive amount of information needed to drive these studies.

This is the fundamental reason we founded 23andMe. Our first mission is to enable personal access to genetic information and provide a look, through the prism of an individual’s genome, at the flood of research discoveries being published. Our longer-term goal is to utilize a web-based platform that gives individuals the ability to share details related to their personal traits–including diseases they have and how they respond to therapies–uniformly layered on their genetic profiles to start building the evidence needed to drive targeted diagnoses and treatments.

It could take hundreds of thousands of people participating in these types of studies before true progress can be made in personalized healthcare. And these people need to come from a diverse population so that everyone, not just people of European ancestry, can benefit.

What better places than California and New York to engage large, diverse communities? We hope to work with the regulators in both states to demonstrate how our Personal Genome Service can become a viable means of translating genetic knowledge into the clinic. With appropriate regulatory oversight, we believe 23andMe can play a significant role.

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