But reality exists in context. And to ignore context, argues Dr. Sandro Galea, physician and Gelman professor of epidemiology at Columbia’s Mailman School of Public Health, is a cognitive mistake with real consequences for both biomedical science and public health. He recently visited NIH to argue for a re-engagement in the behavioral/social sciences in “Is It All About Me? The Role of Public Health in an Era of Personalized Medicine.” His lecture was sponsored by the Office of Behavioral and Social Sciences Research.
Galea began with a question from Mario Balotelli, the international soccer star, flaunting a T-shirt stamped “Why Always Me?”
Surely, Balotelli is a great striker, but he also plays for a great team with guys who pass him the ball so he can score. His boast is a “fundamental attribution error”—the tendency to overestimate the effect of the individual and to ignore context.
This shows Galea’s central premise: We in biomedicine are undervaluing context. Despite the promise of personalized medicine, our focus on the individually curative is crowding out our responsibility for disease and disability prevention across populations.
“I realize that coming to NIH to talk about public health is a little bit incongruous, but that’s part of my intention,” said Galea, who has a wry sense of humor. “I mean to issue a bit of a provocation to see what you all think about it. In an era when we’re thinking about a narrower approach, that approach is excluding approaches that we not only should take, but we must take if we’re going to get our science right,” he said.
He offered a caveat: “Nothing in my talk is taking on genomics. I come not to bury genomics but to elevate public health,” he said.
Galea (c) speaks with OBSSR acting deputy director Dr. Patricia Mabry and Dr. G. Stephane Philogene, OBSSR associate director for policy and planning.
Photos: Ernie Branson
In Galea’s own primary research focus, he has documented the mental health consequences of mass trauma and conflicts, including the 9/11 attacks, Hurricane Katrina, conflicts in sub-Saharan Africa and the American wars in Iraq and Afghanistan.
Our central motivation should be improving the health of all, he insisted. Yet our enthusiasm for the individual, particularly for genomics, has become “a riveting distraction” from focusing on other fundamental drivers of health.
“Here is the perhaps inevitable syllogism,” he said. “Here is where we make our mistake.”
A syllogism goes like this: A = B. And B = C. Therefore, A = C.
So: Penguins are black and white. Some old movies are black and white. Therefore, some penguins are old movies.
You can see the problem.
Galea says we’ve applied this flawed logic to our investment in personalized medicine. We know that genetic mutations cause disease (A = B). We know that we can genotype individuals (B = C). Therefore, we think we can predict disease or treatment response in individuals (A = C).
This idea is compelling, he says, but it is based on a fallacy. It is mathematically impossible to predict who is going to develop disease by looking only at genetic factors.
For example, a mega-analysis of genome-wide association studies for major depressive disorder found no “robust and replicable findings.”
Meanwhile, an analysis of life expectancy at birth for U.S. white males shows a 15-year gap according to county, 1997-2001. The gap was “not driven by heterogeneity in genes or behavior. It was something greater than that.” Where we live affects our health so much that “to put all our eggs in the individualist basket may not be the smartest thing after all.”
Galea offered several other published studies and mathematical simulation models showing that disease can be understood only if genetic and social/environmental risk factors are modeled simultaneously over time.
Galea said he meant to be somewhat provocative in urging NIH to rethink research emphases.
“The dominant research in the biomedical establishment keeps asking why one individual in the population has a systolic blood pressure of 140, rather than asking the larger question,” he said. “Why is it that London civil servants’ curve [of data showing relatively higher blood pressure values] is there, while Kenyan nomads’ curve [with lower, healthier values] is over here? Were we able to understand that, we might be able to move the whole curve.”
This applies to other risk factors as well. “There is an association between cholesterol and heart disease, but the problem is that association is true at the population level. At the individual level it tells you next to nothing as to whether I, with a serum cholesterol of 270, will develop heart disease.”
The genetic revolution has brought important triumphs such as pharmacogenomics, diagnostics for breast cancer and neonatal screening.
Yet “we keep investing more and more money in better mousetraps, in better sequencing approaches…Of course these methods are valid, but no matter how good you get at identifying individual characteristics, you are not going to be able to predict individual health.”
In a discussion after the talk, Galea was asked about the importance of disease mechanisms.
“A subset of population health is curative medicine,” he said. “I think the mechanistic knowledge is very important for the practice of curative medicine, and, from the point of view of science, of understanding nature. My worry is about that at the expense of all else.”
The videocast is archived at http://videocast.nih.gov/summary.asp?live=12723.