Biology subjects

Zaninovic, N.

Publications and source records attributed to Zaninovic, N..

4 recordsLinked to original sources

bioRxiv2025

Dysregulation of the actin cytoskeleton and FMRP causes polar body protrusion defects in human fragile X premutation and aged oocytes

Women carrying the fragile X premutation (55-200 CGG repeat expansion, PM) are at risk for developing fragile X-associated primary ovarian insufficiency (FXPOI), which is preceded by fragile X-associated diminished ovarian reserve (FXDOR). So far, the cause of FXDOR/FXPOI could not be comprehensively examined due to the scarcity of human ovarian tissue and oocytes. From studies in model systems, it was proposed that molecular abnormalities within the ovaries or a diminished primordial follicle pool cause FXDOR/FXPOI. To elucidate the defects instigating FXDOR/FXPOI, we examined human oocytes obtained from PM carriers undergoing in vitro fertilization (IVF). We found that the number of MII oocytes was reduced suggesting that the maturation of the oocytes is constrained in PM carriers. Furthermore, immature PM oocytes contained abnormal inclusions, irregular ubiquitin levels and DNA breaks. Despite these defects PM oocytes passed the DNA damage checkpoints. However, in anaphase I PM oocytes failed to initiate the protrusion of the first polar body. In addition, these oocytes amassed bundle actin structures, lacked an actin cap and had elevated profilin1 level. Profilin1 limits the formation of branched actin structures which are necessary for actin cap formation and membrane protrusions. Surprisingly, our results suggest that in PM oocytes an increase in FMRP elevates the profilin1 translation, which leads to the cytoskeleton defects and deficiencies in formation of the first polar body. We also analyzed the decline of MII oocytes in aging human ovaries. Similar, we found that the profilin1 expression and formation of the actin cytoskeleton were dysregulated due to appearance of cytoplasmatic FMRP foci in aged human oocytes. Thus, these results reveal that defects during anaphase I hinder the maturation of human oocytes resulting in FXDOR/FXPOI in PM carriers and a reduction in mature oocytes in women with advanced maternal age.

cell biology↗

bioRxiv2023

Automatic Ploidy Prediction and Quality Assessment of Human Blastocyst Using Time-Lapse Imaging

Assessing fertilized human embryos is crucial for in vitro-fertilization (IVF), a task being revolutionized by artificial intelligence and deep learning. Existing models used for embryo quality assessment and chromosomal abnormality (ploidy) detection could be significantly improved by effectively utilizing time-lapse imaging to identify critical developmental time points for maximizing prediction accuracy. Addressing this, we developed and compared various embryo ploidy status prediction models across distinct embryo development stages. We present BELA (Blastocyst Evaluation Learning Algorithm), a state-of-the-art ploidy prediction model surpassing previous image- and video-based models, without necessitating subjective input from embryologists. BELA uses multitask learning to predict quality scores that are used downstream to predict ploidy status. By achieving an AUC of 0.76 for discriminating between euploidy and aneuploidy embryos on the Weill Cornell dataset, BELA matches the performance of models trained on embryologists manual scores. While not a replacement for preimplantation genetic testing for aneuploidy (PGT-A), BELA exemplifies how such models can streamline the embryo evaluation process, reducing time and effort required by embryologists.

developmental biology↗

bioRxiv2018

Robust Automated Assessment of Human Blastocyst Quality using Deep Learning

Morphology assessment has become the standard method for evaluation of embryo quality and selecting human blastocysts for transfer in in vitro fertilization (IVF). This process is highly subjective for some embryos and thus prone to human bias. As a result, morphological assessment results may vary extensively between embryologists and in some cases may fail to accurately predict embryo implantation and live birth potential. Here we postulated that an artificial intelligence (AI) approach trained on thousands of embryos can reliably predict embryo quality without human intervention.\n\nTo test this hypothesis, we implemented an AI approach based on deep neural networks (DNNs). Our approach called STORK accurately predicts the morphological quality of blastocysts based on raw digital images of embryos with 98% accuracy. These results indicate that a DNN can automatically and accurately grade embryos based on raw images. Using clinical data for 2,182 embryos, we then created a decision tree that integrates clinical parameters such as embryo quality and patient age to identify scenarios associated with increased or decreased pregnancy chance. This IVF data-driven analysis shows that the chance of pregnancy varies from 13.8% to 66.3%.\n\nIn conclusion, our AI-driven approach provides a novel way to assess embryo quality and uncovers new, potentially personalized strategies to select embryos with an improved likelihood of pregnancy outcome.

bioinformatics↗

bioRxiv2017

Tripolar mitosis drives the association between maternal genotypes of PLK4 and aneuploidy in human preimplantation embryos

Aneuploidy is prevalent in human preimplantation embryos and is the leading cause of pregnancy loss. Many aneuploidies arise during oogenesis, increasing in frequency with maternal age. Superimposed on these meiotic aneuploidies are a range of errors occurring during early mitotic divisions of the embryo, contributing to widespread chromosomal mosaicism. Here we reanalyzed a published dataset comprising preimplantation genetic testing for aneuploidy in 24,653 blastomere biopsies from day-3 cleavage-stage embryos, as well as 17,051 trophectoderm biopsies from day-5 blastocysts. We focused on complex abnormalities that affected multiple chromosomes simultaneously, seeking to quantify their incidences and gain insight into their mechanisms of formation. In addition to well-described patterns such as triploidy and haploidy, we identified 4.7% of day-3 blastomeres possessing karyotypes suggestive of tripolar mitosis in normally-fertilized diploid zygotes or descendant diploid cells. We further supported this hypothesis using time-lapse data from an intersecting set of 77 cleavage-stage embryos. The diploid tripolar signature was rare among day-5 blastocyst biopsies (0.5%), suggesting that complex aneuploidy generated by tripolar mitosis impairs cellular and/or early embryonic survival. Strikingly, we found that the tripolar mitosis mechanism is responsible for the previously described association with common maternal genetic variants spanning PLK4. Our findings are consistent with the role of PLK4 as the master regulator of centriole duplication with a known capacity to induce tripolar mitosis when mutated or mis-expressed. Taken together, we propose that tripolar mitosis is a key mechanism generating karyotype-wide aneuploidy in cleavage-stage embryos and implicate PLK4-mediated centrosome abnormality as a factor influencing its occurrence.

genetics↗