Proteome profiling of early gestational plasma reveals novel biomarkers of congenital heart disease

Plasma Proteomics Analysis of Early Biomarkers for Predicting Female Fecundability: A Nested Case-Control Study

The present study aimed to identify and verify new plasma protein markers to predict the female fecundability level. A nested case-control study was conducted involving couples who participated in the Chinese National Free Preconception Check-up Project. Women who successfully conceive within one year were defined as the high fecundability group, and those unable to conceive were defined as the low fecundability group. In the training cohort, potential protein biomarkers were identified using proteomics technology and were further tested in a validation cohort by the Western blotting assay, enzyme-linked immunosorbent assay, and biochemical tests. Meanwhile, receiver operating characteristic curve analysis were used to evaluate the predictive value. Cox proportional hazard regression analyses were conducted to calculate hazard ratios; restricted cubic spline analysis was used to assess the linear relationship between the the protein level and hazard ratios for fecundability. Pyruvate, a key product of glycolysis, was significantly increased in the high fecundability group (P < 0.01) compared to the low fecundability group, and its area under the curve value was 0.68 (P < 0.05). There was a linear positive dose-response association between the pyruvate level and fecundability possibility (hazard ratios = 1.66, 95% CI: 1.07-2.59, p for trend = 0.025, nonlinearity, p-value = 0.2927).

Unveiling the potential of SLURP1 protein as a biomarker for prostate cancer screening

Background

Prostate cancer (PCa) develops slowly and lacks obvious symptoms in the early stage, which makes early screening and diagnosis difficult. Urine collection is simple and is an ideal source of biomarkers. In this study, we performed urinary proteomic studies in PCa patients to screen proteins and apply them to the non-invasive early diagnosis of PCa.

Method

Urine samples from PCa patients, benign prostatic hyperplasia (BPH) patients and normal control group were collected. Mass spectrometry was used for proteomic analysis and screening target proteins. Western blot and enzyme-linked immunosorbent assay (ELISA) were used to verify the results. Correlations with clinical indicators were explored, and receiver operating characteristic (ROC) curves were drawn to evaluate the value of target proteins in PCa.

Result

A total of 1065 proteins were identified. Urinary SLURP1 protein was significantly elevated in patients with PCa compared with normal controls and patients with BPH patients. Western blot and ELISA further verified the expression changes of SLURP1. The immunohistochemical staining results revealed a substantial increase in positive SLURP1 expression within PCa tumor tissue. Correlation analysis showed a positive correlation between the expression level of urine SLURP1 protein and serum PSA. ROC curve analysis of the SLURP1 protein in the urine of both normal individuals and PCa patients is determined to be 0.853 (95% CI=0.754 to 0.954).

Conclusion

The concentration of SLURP1 protein in urine of PCa patients is increased, which can serve as a biomarker for screening PCa.

Looking at a baby's heart through the lens of the mother's blood

Congenital heart disease (CHD) comprises several cardiovascular abnormalities existing from birth. Cardiac defects range from minor asymptomatic lesions to potentially life-threatening situations. Early fetal echocardiography, the gold standard for the in-utero diagnosis of CHD, is inaccurate at identifying defects in pulmonary veins and atrioventricular valves or lesions that occur later or progress during pregnancy. In this issue of EMBO Molecular Medicine, Yin et al report new proteomic data on maternal blood samples and a novel bioinformatic and artificial intelligence approach for the early diagnosis and screening of CHD.