If you have gene variants such as BRCA or Lynch Syndrome, both of which may lead to difficult-to-treat cancers, “you’ve noticed it,” says Thomas May, an endowed professor of bioethics in Washington State University’s College of Medicine. “Noticed” is May’s measured way of saying that “multiple people in your family have died” of breast or colon cancer.

“Unless you don’t have access to family health history,” May adds.

One of the primary diagnostic tools available to doctors is family medical history. Breast cancer, cardiovascular disease, and other conditions are often genetic. Knowing that a parent had a disease is important information in preventing it in the child.

But adoptees often lack access to that history. That, says May, puts them at a disadvantage that is both systemic and unjust.

Together with an interdisciplinary team of experts, May argues that genetic testing is a way to bridge health history gap.

The adoptee community is keenly interested in filling that gap, May says, as demonstrated through surveys, focus groups, published narratives, and utilization of direct-to-consumer genetic testing services.

But there are concerns. Consider Angelina Jolie, May says. After a screening test indicated the actress had the BRCA variant that carries a very high risk of breast cancer, she had a double mastectomy. But what if someone acted on a test for a disease that had a less than one percent chance of actually manifesting?

“The prophylactic intervention may actually be more dangerous than the risk of actually manifesting the disease,” he cautions. That’s one reason why he and the genomic family history project team, which includes members of the adoptee community, argue that filling the informational gap should be limited to genetic testing of only very high-risk, highly pathological diseases.

The problem is funding. It’s hard to get traction on serving such a small segment of the population as the adoptee community, May says. There are about 120,00 adoptions per year in the U.S.

In an effort to change minds by showing where the money goes, May and a colleague have done an economic analysis which signals that, in fact, genetic testing for highly pathological, highly penetrant diseases would pay for itself.

May says that about a quarter of one percent of the population will test positive for Lynch Syndrome, a heritable genetic variant that indicates a high risk for colon cancer. For those with access to family medical history, it’s not likely to go unnoticed as, again, family members will have had the cancer. For them, there is minimal benefit in testing, only an expense.

But for those without such access, as with adoptees, the cost of genetic testing and counseling is zeroed out by the savings incurred in avoiding expensive late-stage cancer treatments.

“You have to dig deeper than the academic headlines,” May says. The few studies done to date claim there is little value added by genetic testing. That has been true, to this point, for the general population because they have access to their family health histories.

But testing for those highly pathological, highly penetrant genetic variants would be a potentially life-saving service for those who lack family histories. And, for a health care system trying to control costs, it could also be a money-saving service, inasmuch as prophylaxis is preferable to expensive treatments.

As May points out, “There are other populations” beside adoptees who may not have access to family health history. “Every kid who is born to a mother who is not sure who the father is. Every kid who is the child of a sperm or egg donor. Every child who lives in a broken family where one side of the family is estranged from the other. All could potentially benefit from this form of testing, the same as adoptees.”

The Weighted Coin Problem

May explains a problem with the current state of our genetic data that he explores with his students.

“If we flip a coin, we know that, over time, about half the time it will come up heads, the other half tails. We know that because we have a conceptual framework–probability theory–for understanding those odds.

“But what if you didn’t have a background conceptual framework and you wanted to see, purely from empirical observation, what happened when you flip a coin.

“That’s where we stand right now with genetic testing. Someday we may have a comprehensive framework that tells us the types of combinations of variants that lead to disease manifestations–but right now we don’t. We’re simply looking at variants and trying to correlate these to disease manifestation. We see a variant pop up and, purely through empirical observation, identify whether this variant tends to occur in people who manifest some disease. In brief, we’re identifying patterns. This is a very challenging project.

“With coin tosses,” May continues, “we know that if we flip a coin ten times, it’s probably not going to be a 50-50 distribution for any particular set of ten flips. It’s only over time–and many coin tosses–that it regresses to that 50-50 pattern.”

It’s the same with genetic testing: to notice the pattern of occurrence of something rare, it’s going to take a lot of people getting tested.

“But,” May adds, “there’s a potential problem. Suppose that coin is weighted and I don’t know it. I’m going to come to the conclusion that when I flip a coin it’s going to come up heads. Unless, that is, I have a variety of coins, not all of which are weighted. Then I’m going to recognize that mine is different because all the other coins regress to the 50-50 heads-tails pattern.”

And here’s the catch with genetic testing, May says.

“Right now, almost all the data we have on gene variance and diseases is based on white, European-descended individuals. That coin may be weighted. It very likely is! We don’t know if our reference genome is accurate, or if it’s a weighted coin.

“That inhibits our ability to know gene-disease associations in different [ethnic] genetic makeups but also limits our ability to know those associations even within that [particular ethnic] group, because we don’t know how the data is weighted.

“We need a lot more people to be tested and, even more important than that, we need great diversity of testing participation. It is a big problem for everyone that we have a lack of minorities represented in genetic testing. Not only for the minority communities, but for everyone.

“Getting trust” from a variety of populations, May concludes, “is what is required to flesh out that database.”