Specific genetic mutations associated with preeclampsia

Specific genetic mutations in women with autoimmune diseases are associated with preeclampsia—a common pregnancy-related problem that can threaten the health of both baby and mother. Furthermore, investigation of these specific genetic mutations has revealed an association between similar mutations and preeclampsia in women without any underlying autoimmune disease. These are the findings of a study by Jane Salmon a rheumatologist from Hospital for Special Surgery, New York, USA, and colleagues and published in this week's PLoS Medicine. Preeclampsia complicates 4%-5% of all pregnancies worldwide, causing significant maternal and neonatal mortality. Pregnancy in women with systemic lupus erythematosus (SLE) or the antiphospholipid syndrome (APS), two autoimmune diseases characterized by complement-mediated injury, is associated with an increased risk of preeclampsia.

The authors studied 250 pregnant women with SLE and/or APS. 30 patients developed preeclampsia during the study and 10 more had experienced preeclampsia during a previous pregnancy. The authors studied specific genes [complement regulatory proteins membrane cofactor protein (MCP), factor I and factor H] of these 40 women and found that 7 of the 40 had a mutation in one of these genes. The authors also found that 5 of 59 women who did not have an autoimmune disease but who developed preeclampsia, had mutations in MCP or factor I.

Although further studies are needed to confirm and extend these findings, the results of this study suggest new genetic targets for the treatment of preeclampsia and raise the possibility of developing tests to identify women at risk of developing preeclampsia.

The authors conclude: "Our findings underscore the important role of complement activation in preeclampsia, define mutations and likely mechanisms for increased risk in patients with SLE and/or APS, and suggest new targets for treatment of this important public health problem that, thus far, has defied reliable prediction and satisfactory intervention."

Source: Public Library of Science