Predicting whether you’ll live to 100.
Scientists are claiming a genetic test can predict whether someone will live to 100 years old.
The study…claims to be able to predict exceptional longevity with 60 to 85 percent accuracy, depending on the subject’s age.
You can read the paper, which is in the open-access journal PLoS One.
Whether the prediction really works comes down in part to what you mean by “60 to 85% accuracy”. There’s a very easy way to predict whether someone will live to 100 years old, with better than 99% accuracy. Ask them if they are over 100. If they say “Yes”, predict “Yes”; if they say “No”, predict “No”. Since almost no-one lives to be 100 you will almost always be right.
The new test is not as useless as this, but it still isn’t terribly accurate. Distinguishing people who live to 90 from those who live to 100, the test gets the correct prediction for about half of the centenarians and for about two-thirds of the non-centenarians. You could probably predict that well in 90+ year olds by asking them how their health is, and whether they can get around on their own. The ability to predict survival to 105 among 100-year-olds is slightly better, but again, probably not as accurate as you could get more easily from health information. The point of the paper isn’t really prediction. It’s to find genes that are connected with longevity, which are still not well understood, and the reason for talking about prediction is to make the point that genetic variations do matter in extreme old age. Even from this point of view the results are a bit over-sold, since the biggest component of the genetics is a well-known gene, APO E, where commercial testing has been (controversially) available for years.
This study has attracted a lot of media attention around the world. Some stories mentioned this note from the journal editors:
While we recognize that aspects of this study will attract attention owing to the history and the strong claims made in the paper, the handling editor, Greg Gibson, made the decision that publication is warranted, balancing the extensive peer review and the spirit of PLoS ONE to allow important new results and approaches to be available to the scientific community so long as scientific standards have been met. We trust that publication will facilitate full evaluation of the study.
Thomas Lumley (@tslumley) is Professor of Biostatistics at the University of Auckland. His research interests include semiparametric models, survey sampling, statistical computing, foundations of statistics, and whatever methodological problems his medical collaborators come up with. See all posts by Thomas Lumley »