Factor V Leiden testing to prevent pregnancy loss: different methods produce conflicting conclusions

see Modeling uncertain outcomes of genetic testing: factor V Leiden mutation and pregnant women and A risk–benefit analysis of factor V Leiden testing to improve pregnancy outcomes: a case study of the capabilities of decision modeling in genomics

The search for an explanation for recurrent pregnancy loss (RPL) may include testing for genetic factors. Women who test positive for factor V Leiden mutation are at higher risk for RPL. Treatment may include aspirin and/or heparin, but it is unclear whether this treatment prevents future miscarriage. In this issue, Bajaj and Veenstra report that a decision model they developed suggests that factor V Leiden testing could result in small improvements in quality of life for women with RPL. Their position contrasts with the conclusions of a recent systematic review of two randomized clinical trials published in this journal in 2012. Those authors concluded that anticoagulation treatment does not improve pregnancy outcomes in women with RPL, except in the case of antiphospholipid antibody syndrome. In their related commentary, Grosse and Caughey offer an explanation for the seemingly contradictory conclusions, namely, that the two groups used different approaches to evidence analysis. Bajaj and Veenstra used a modeling approach based on observational data that allows them to address uncertainty. In addition, although their model suggests that factor V Leiden testing could be beneficial, Bajaj and Veenstra point out that the uncertainty of the underlying data limits their ability to assess the broader impact of testing and treatment on women and their families. —Karyn Hede, News Editor

We screen newborns, don’t we?

see We screen newborns, don’t we?: realizing the promise of public health genomics

Newborn screening is a powerful example of how genetics can contribute to public health. Countless lives have been saved or dramatically improved, and vast expense to society averted, by identifying preventable diseases in newborns that would otherwise have resulted in serious morbidity or mortality. Now, because of technical advances in genomics, there exists another exciting possibility: targeted genomic screening of healthy adults to detect highly penetrant mutations for preventable conditions. For example, approximately 1 in 400 individuals in the United States carries a Lynch syndrome mutation, but we currently do not usually identify it until genetic testing is prompted by the development of cancer in the individuals or in their family members, or their death. If, instead, those at high risk were proactively identified via mutational analysis, considerable suffering could be averted. There exist effective preventive modalities for Lynch syndrome and several other genetic conditions, including predisposition to other specific cancers or to vascular catastrophe. Taking into consideration all such conditions, 0.5–1% of the US population—that is, millions of people in this country—harbor highly penetrant mutations for eminently preventable conditions.

In the commentary “We Screen Newborns, Don’t We?,” several of us, including colleagues from the world of public health, explore how we might sequence a carefully selected panel of genes in healthy individuals to identify at-risk individuals and prevent disease. We encourage a new partnership between geneticists and members of the public health community to investigate the feasibility of offering such screening to help realize the full promise of public health genomics. —James P. Evans, Editor-in-Chief