How much can you help yourself by getting your genome sequenced?

A lot, a little, not at all?

Scenario 1 (big help): You discover you have a greatly elevated risk of Disease X. You do various things to reduce that risk that actually reduce it.

Scenario 2: (a little help): You discover you have a greatly elevated risk of Rare Disease X. You do various things to reduce that risk but they don’t help. At least, when Disease X starts, you will be less upset.

Scenario 3 (no help): You discover that you have a greatly elevated risk for a common easily-noticed disease (such as obesity). You already watched your weight, this changes nothing. Scenario 4 (harm): You discover that you have a greatly elevated risk of Scary Disease X (e.g., bipolar disorder). It is depressing news. Later studies show that the gene/disease association was a mistake. (Many gene/disease associations have failed to replicate.)

A recent Wired article tries to answer this question for one person: Raymond McCauley, a bioinformatics scientist who had his genome sequenced four years ago and learned he was “four or five times more likely than most people to develop age-related macular degeneration (AMD)”. The article says “of all the ailments described in the 23andme profile, AMD has one of the strongest genetic associations”. If I found this in my genetic profile, I would want to know the confidence interval of the increased risk. Is it a factor of 4.5 plus or minus 1? Or 4.5 plus or minus 8? This isn’t easy to figure out. In addition to the question of variability, there can easily be bias (= estimate is too high). Let’s say I do 100 gene/disease association studies.

Then I scan these studies to pick the one with the strongest gene/disease association. It should be obvious that this particular association is likely to be too high and, depending on the details, could plausibly be pure chance (i.e., true association is zero).  I have been unable to find out how replicable the gene/AMD association is. According to Wikipedia, “the lifetime risk of developing late-stage macular degeneration is 50% for people that have a relative with macular degeneration, versus 12% for people that do not have relatives with macular degeneration.” (Until it was eliminated via better diet, pellagra also ran in families.) The Wired article does not say whether any of McCauley’s relatives have/had AMD — a huge omission, given the uncertainty of gene/disease associations.

It wasn’t obvious what McCauley should do, according to the article:

McCauley read that there were a few preventative measures he could take to reduce the chances of AMD one day rendering him blind: don’t smoke and avoid ultraviolet light, for instance. Also, it seemed, he could try taking a special combination of vitamins, including B12 and lutein. But when he consulted the research, he could find little evidence to support the effectiveness of the regime, based on his genotype.

The article says nothing about quitting smoking but he does wear glasses that reduce ultraviolet light and takes certain vitamins. It is very hard for him to determine whether they help.

Here is a study that found greater omega-3 consumption associated with lower risk of AMD. Here is a study that found AMD associated with inflammation (too little omega-3 increases inflammation). Here is a study that found no association between vitamin and mineral intake and AMD. Based on this, if 23andme told me I had an increased risk of AMD, I would make sure to optimize my intake of flaxseed oil (or other omega-3 source) using some sort of brain test. I have documented in other posts that brain function is sensitive to omega-3 intake and (probably) most people don’t get enough. Of course, just as it is foolish to smoke (a lot) regardless of whether you have genetic risk of AMD, it is foolish to not optimize one’s omega-3 intake, whether or not you have genetic risk of AMD. In other words: everyone should optimize their omega-3 intake.  If the 23andme results cause McCauley to do something wise like this that he would otherwise not have done, they have helped him.

The omega-3 study appeared after the Wired article so I don’t know how McCauley reacted to it. A puzzle about the  story is that it isn’t even clear that the gene/AMD associations are true. Consider McCauley’s older relatives: parents, grandparents. Did/do any of them have AMD? If not, it is more plausible that all of them were at 12% risk of the disease than at 50% risk. Suppose all of them had, according to 23andme, the same increased risk as McCauley (at least some of them have the risk-bearing genes). Now it becomes more plausible that something is wrong with the 23andme risk estimate. If some of McCauley’s older relatives do have AMD, it is not clear why the 23andme results would make much difference. He should have already have known he was at increased risk of AMD.

The upshot is that in this particular case, I cannot even rule out Scenario 4 (does harm). All four scenarios strike me as plausible.  Based on this article, we are a long way from learning the value of personal genomics.

Previously I used the example of Aaron Blaisdell to make the possibly counter-intuitive point that if you have a genetic disease something is wrong with your environment. Well, I do not have any obvious genetic disease. But I discovered, via self-experimentation, that my environment was terrible — meaning it could be improved in all sorts of ways: stop eating breakfast, drink flaxseed oil, eat butter, look at faces in the morning, take Vitamin D in the morning, and so on, not to mention eat fermented foods (which I figured out via psychology, not self-experimentation). My findings about what is optimal are so different than the way anyone now lives (except people who read this blog) that I believe everyone‘s environment can be vastly improved. If so, the value of discovering you have a genetically elevated risk of this or that is not obvious — you should already be trying to improve your environment. At least that is what my data has taught me. On the other hand, maybe genetic info (even wrong genetic info!) will give you a kick in the pants. Maybe that has happened with McCauley.

Seth Roberts is a professor of psychology at Tsinghua University and an emeritus professor of psychology at the University of California Berkeley. This piece is reposted from his blog. He is looking for other stories like this one, where people use science or data collection to improve their own health. His email is twoutopias (at) gmail.com.

Share on Twitter

Leave a Reply

FROM THE VAULT

The Power of Small Why Doctors Shouldn't Be Healers Big Data in Healthcare. Good or Evil? Depends on the Dollars. California's Proposition 46 Narrow Networking
MASTHEAD STUFF

MATTHEW HOLT
Founder & Publisher

JOHN IRVINE
Executive Editor

JONATHAN HALVORSON
Editor

JOE FLOWER
Contributing Editor

MICHAEL MILLENSON
Contributing Editor

ALEX EPSTEIN
Director of Digital Media

MICHELLE NOTEBOOM Business Development

MUNIA MITRA, MD
Clinical Medicine

Vikram Khanna
Editor-At-Large, Wellness

THCB FROM A-Z

FOLLOW US ON TWITTER
@THCBStaff

WHERE IN THE WORLD WE ARE

The Health Care Blog (THCB) is based in San Francisco. We were founded in 2004 by Matthew Holt and John Irvine.

MEDIA REQUESTS

Interview Requests + Bookings. We like to talk. E-mail us.

BLOGGING
Yes. We're looking for bloggers. Send us your posts.

STORY TIPS
Breaking health care story? Drop us an e-mail.

CROSSPOSTS

We frequently accept crossposts from smaller blogs and major U.S. and International publications. You'll need syndication rights. Email a link to your submission.

WHAT WE'RE LOOKING FOR

Op-eds. Crossposts. Columns. Great ideas for improving the health care system. Pitches for healthcare-focused startups and business.Write ups of original research. Reviews of new healthcare products and startups. Data-driven analysis of health care trends. Policy proposals. E-mail us a copy of your piece in the body of your email or as a Google Doc. No phone calls please!

THCB PRESS

Healthcare focused e-books and videos for distribution via THCB and other channels like Amazon and Smashwords. Want to get involved? Send us a note telling us what you have in mind. Proposals should be no more than one page in length.

HEALTH SYSTEM $#@!!!
If you've healthcare professional or consumer and have had a recent experience with the U.S. health care system, either for good or bad, that you want the world to know about, tell us about it. Have a good health care story you think we should know about? Send story ideas and tips to editor@thehealthcareblog.com.

REPRINTS Questions on reprints, permissions and syndication to ad_sales@thehealthcareblog.com.

WHAT WE COVER

HEALTHCARE, GENERAL

Affordable Care Act
Business of Health Care
National health policy
Life on the front lines
Practice management
Hospital managment
Health plans
Prevention
Specialty practice
Oncology
Cardiology
Geriatrics
ENT
Emergency Medicine
Radiology
Nursing
Quality, Costs
Residency
Research
Medical education
Med School
CMS
CDC
HHS
FDA
Public Health
Wellness

HIT TOPICS
Apple
Analytics
athenahealth
Electronic medical records
EPIC
Design
Accountable care organizations
Meaningful use
Interoperability
Online Communities
Open Source
Privacy
Usability
Samsung
Social media
Tips and Tricks
Wearables
Workflow
Exchanges

EVENTS

TedMed
HIMSS South x South West
Health 2.0
WHCC
AHIP
AHIMA
Log in - Powered by WordPress.