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What can SNPs tell us about breast cancer risk? Not much, researchers say

March 17, 2010 |  4:29 pm

There are certainly many genetic mutations that increase a woman’s risk of developing breast cancer. The most famous examples are variations in the genes BRCA1 and BRCA2 (whose names are short for BReast CAncer).

More common are the single-letter DNA changes called single nucleotide polymorphisms– or SNPs for short. Researchers have identified many SNPs that appear to be associated with breast cancer because they are more common in women who have the disease.

But can those SNPs be used to predict an individual woman’s risk of developing breast cancer? That was the question that a large group of researchers from the National Cancer Institute, the American Cancer Society and a host of other esteemed institutions set out to answer.

The group tested 10 SNPs that have “established associations with breast cancer,” they write in Thursday’s issue of the New England Journal of Medicine. Using data on 5,590 women with breast cancer and 5,998 healthy controls, they found that those SNPs alone did just as good a job of predicting a woman’s breast cancer risk as the government’s Breast Cancer Risk Assessment Tool, which relies on family health history, age at the time of first menstrual period and other personal information. Combining the SNPs and the traditional risk model boosted their predictive accuracy only slightly, the researchers found.

They also looked at how the addition of the SNP data changed the risk prediction for the women in the study. In 26% of cases, it moved women into a higher risk category, and in 28% of cases it moved women to a lower risk category. In the remaining 46% of cases, there was no change.

All in all, the researchers said the use of SNPs to predict breast cancer risk still isn’t ready for prime time. “Our results indicate that the recent identification of common genetic variants does not herald the arrival of personalized prevention of breast cancer in most women,” they wrote.

Perhaps researchers are getting a little more realistic about the predictive value of SNPs. A study published last month in the Journal of the American Medical Assn. found that nearly 100 SNPs linked to heart disease did almost nothing to predict the risk of heart attacks, strokes, coronary artery disease or cardiovascular death.

However, in an editorial accompanying the study, a pair of European scientists who focus on breast cancer genetics said the problem isn’t that the SNPs don’t work – it’s that we haven’t identified enough of them.

The 10 SNPs examined in the study “are no more than the tip of the iceberg,” they wrote. “A more pressing question is why … only a dozen risk alleles have been identified.”

-- Karen Kaplan

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Comments (1)

If the two predictive methods are roughly equally accurate (with accuracies substantially greater than chance, or else they would have no predictive value at all), BUT combining the two methods does not result in any increase in overall accuracy, the implication is that they somehow must overlap. Which would be a very interesting result. Because while one of the methods is purely physiological (DNA mutations), the other is purely clinical (personal & family development, as measured by the Risk Assessment Tool). The extent to which the two methods overlap would seem to imply that the measured physiology (DNA mutations) expresses itself in the form of the listed clinical manifestations, such as age of onset of menses, etc. This would be fantastic to disentangle. A beautiful example of how a "negative" result in science can still be enormously valuable.



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