Urinary Biomarkers Diagnose Preeclampsia

In the future, this urine-based diagnostic method will enable specialists to detect the disease in its early stages.

Scientists at the Moscow Institute of Physics and Technology (Moscow, Russia) and their colleagues compared samples of three groups of ten women, women with a normal pregnancy, and with mild and severe preeclampsia. The team was not only interested in comparing healthy women and patients with preeclampsia; they also wanted to examine how certain biomarkers are associated with the severity of the condition.

Samples were prepared using size-exclusion chromatography method, which gives more than twice peptides identities if compared with solid phase extraction. High performance liquid chromatography – mass spectrometry (HPLC-MS/MS) analysis was performed for all urinary peptides samples in fourfold on a nano-HPLC Agilent 1100 system (Agilent Technologies, Santa Clara, CA, USA) in combination with a 7-Tesla Linear Ion Trap Ultra mass spectrometer ((LTQ-FT) (Thermo Fisher Scientific, Bremen, Germany) equipped with an in-house system nanospray ion source.

Thirty urine samples from women with mild and severe preeclampsia and the control group were analyzed and a total 1,786 peptides were identified using complementary search engines. Label-free data comparison resulted in 35 peptides, which reliably distinguished a particular preeclampsia group (severe or mild) from controls. The results revealed unique identifications correlated to alpha-1-antitrypsin, collagen alpha-1(I) chain, collagen alpha-1 (III) chain, and uromodulin that can potentially serve as early indicators of preeclampsia.

Evgeny N Nikolayev, PhD, a professor and a senior author of the study said, “We were able to confirm a number of markers previously proposed by our colleagues abroad, and also identify some new ones. We will obviously need to verify and confirm their significance. What is important is that this non-invasive method has proven effective and it can be used as a basis to develop a clinical method.” The study was published on April 21, 2016, in the Journal of Proteomics.

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Moscow Institute of Physics and Technology
Agilent Technologies
Thermo Fisher Scientific