The Soluble Fms-like Tyrosine Kinase-1 Contributes to Structural and Functional Changes in Endothelial Cells in Chronic Kidney Disease

Predictive and Diagnostic Value of the Angiogenic Proteins in Patients With Chronic Kidney Disease

BACKGROUND

Our objective was to investigate the predictive and diagnostic accuracy of the angiogenic proteins sFlt-1 (soluble fms-like tyrosine kinase-1) and PlGF (placental growth factor) for preterm preeclampsia and explore the relationship between renal function and these proteins.

METHODS

We completed a blinded, prospective, longitudinal, observational study of patients with chronic kidney disease followed at a tertiary center (2018-2023). Serum samples were obtained at 3 time points along gestation (planned sampling): 12-16, 18-22, and 28-32 weeks. In addition, samples were obtained whenever preeclampsia was suspected (indicated sampling). sFlt-1 and PlGF levels remained concealed until the study ended. The primary outcome was preterm preeclampsia. The planned and indicated samples were used to estimate the predictive and diagnostic accuracy of the angiogenic proteins, respectively.

RESULTS

Of the 97 participants, 21 (21.6%) experienced preterm preeclampsia. In asymptomatic patients with chronic kidney disease, the angiogenic proteins were predictive of preterm preeclampsia only when sampled in the third trimester, in which case the sFlt-1/PlGF ratio (false positive rate of 37% for a detection rate of 80%) was more predictive than either sFlt-1 or PlGF in isolation. In patients with suspected preeclampsia, the diagnostic accuracy of the sFlt-1/PlGF ratio (false positive rate of 26% for a detection rate of 80%) was higher than that of sFlt-1 and PlGF in isolation. Diminished renal function was associated with increased levels of PlGF.

CONCLUSIONS

sFlt-1 and PlGF can effectively predict and improve the diagnostic accuracy for preterm preeclampsia among patients with chronic kidney disease. The optimal sFlt-1/PlGF ratio cutoff to rule out preeclampsia may need to be lower in patients with impaired renal function.

The importance of protein domain mutations in cancer therapy

Cancer is a complex disease that is caused by multiple genetic factors. Researchers have been studying protein domain mutations to understand how they affect the progression and treatment of cancer. These mutations can significantly impact the development and spread of cancer by changing the protein structure, function, and signalling pathways. As a result, there is a growing interest in how these mutations can be used as prognostic indicators for cancer prognosis. Recent studies have shown that protein domain mutations can provide valuable information about the severity of the disease and the patient's response to treatment. They may also be used to predict the response and resistance to targeted therapy in cancer treatment. The clinical implications of protein domain mutations in cancer are significant, and they are regarded as essential biomarkers in oncology. However, additional techniques and approaches are required to characterize changes in protein domains and predict their functional effects. Machine learning and other computational tools offer promising solutions to this challenge, enabling the prediction of the impact of mutations on protein structure and function. Such predictions can aid in the clinical interpretation of genetic information. Furthermore, the development of genome editing tools like CRISPR/Cas9 has made it possible to validate the functional significance of mutants more efficiently and accurately. In conclusion, protein domain mutations hold great promise as prognostic and predictive biomarkers in cancer. Overall, considerable research is still needed to better define genetic and molecular heterogeneity and to resolve the challenges that remain, so that their full potential can be realized.

A single-cell atlas of the aging mouse ovary

Ovarian aging leads to diminished fertility, dysregulated endocrine signaling and increased chronic disease burden. These effects begin to emerge long before follicular exhaustion. Female humans experience a sharp decline in fertility around 35 years of age, which corresponds to declines in oocyte quality. Despite a growing body of work, the field lacks a comprehensive cellular map of the transcriptomic changes in the aging mouse ovary to identify early drivers of ovarian decline. To fill this gap we performed single-cell RNA sequencing on ovarian tissue from young (3-month-old) and reproductively aged (9-month-old) mice. Our analysis revealed a doubling of immune cells in the aged ovary, with lymphocyte proportions increasing the most, which was confirmed by flow cytometry. We also found an age-related downregulation of collagenase pathways in stromal fibroblasts, which corresponds to rises in ovarian fibrosis. Follicular cells displayed stress-response, immunogenic and fibrotic signaling pathway inductions with aging. This report provides critical insights into mechanisms responsible for ovarian aging phenotypes. The data can be explored interactively via a Shiny-based web application.

A single-cell atlas of the aging murine ovary

Ovarian aging leads to diminished fertility, dysregulated endocrine signaling, and increased chronic disease burden. These effects begin to emerge long before follicular exhaustion. Around 35 years old, women experience a sharp decline in fertility, corresponding to declines in oocyte quality. Despite a growing body of work, the field lacks a comprehensive cellular map of the transcriptomic changes in the aging ovary to identify early drivers of ovarian decline. To fill this gap, we performed single-cell RNA sequencing on ovarian tissue from young (3-month-old) and reproductively aged (9-month-old) mice. Our analysis revealed a doubling of immune cells in the aged ovary, with lymphocyte proportions increasing the most, which was confirmed by flow cytometry. We also found an age-related downregulation of collagenase pathways in stromal fibroblasts, which corresponds to rises in ovarian fibrosis. Follicular cells displayed stress response, immunogenic, and fibrotic signaling pathway inductions with aging. This report raises provides critical insights into mechanisms responsible for ovarian aging phenotypes.

The Endothelial Glycocalyx as a Target of Excess Soluble Fms-like Tyrosine Kinase-1

Soluble fms-like tyrosine kinase-1 (sFlt-1) is a secreted protein that binds heparan sulfate expressed on the endothelial glycocalyx (eGC). In this paper we analyze how excess sFlt-1 causes conformational changes in the eGC, leading to monocyte adhesion, a key event triggering vascular dysfunction. In vitro exposure of primary human umbilical vein endothelial cells to excess sFlt-1 decreased eGC height and increased stiffness as determined by atomic force microscopy (AFM). Yet, structural loss of the eGC components was not observed, as indicated by Ulex europaeus agglutinin I and wheat germ agglutinin staining. Moreover, the conformation observed under excess sFlt-1, a collapsed eGC, is flat and stiff with unchanged coverage and sustained content. Functionally, this conformation increased the endothelial adhesiveness to THP-1 monocytes by about 35%. Heparin blocked all these effects, but the vascular endothelial growth factor did not. In vivo administration of sFlt-1 in mice also resulted in the collapse of the eGC in isolated aorta analyzed ex vivo by AFM. Our findings show that excess sFlt-1 causes the collapse of the eGC and favors leukocyte adhesion. This study provides an additional mechanism of action by which sFlt-1 may cause endothelial dysfunction and injury.