Biology subjects

Urbanek, M.

Publications and source records attributed to Urbanek, M..

7 recordsLinked to original sources

bioRxiv2024

Ovarian disrupting effects and mechanisms of long- and short-chain per- and polyfluoroalkyl substances in mice

BackgroundThe extensive use of per- and polyfluoroalkyl substances (PFAS) has led to environmental contamination and bioaccumulation. Previous research linked PFAS exposure to female reproductive disorders, but the mechanism remains elusive. Further, most studies focused on legacy long-chain PFOA and PFOS, yet the reproductive impacts of other long-chain PFAS and short-chain alternatives are rarely explored. ObjectivesWe investigated the effects and mechanisms of long- and short-chain PFAS on the ovary and associated ovarian functions. MethodsA 3D in vitro ovarian follicle culture system and an in vivo mouse model, together with approaches of reverse transcription-quantitative polymerase chain reaction, enzyme-linked immunosorbent assay, RNA-sequencing, pharmacological treatment, in situ zymography, histology, in situ hybridization, analytical chemistry, and benchmark dose modeling (BMD), were used to test environmentally relevant exposure levels of six long- and short-chain PFAS on follicle maturation, hormone secretion, and ovulation. ResultsIn vitro exposure revealed that long-but not short-chain PFAS interfered with gonadotropin-dependent follicle maturation, ovulation, and hormone secretion. Mechanistically, long-chain perfluorononanoic acid (PFNA) acted as a peroxisome proliferator-activated receptor gamma (PPAR{gamma}) agonist in granulosa cells to disrupt follicle-stimulating hormone (FSH)-dependent follicle maturation, luteinizing hormone (LH)-stimulated ovulation, and associated gene regulatory pathways. In vivo mouse exposure confirmed the ovarian accumulation of PFNA and the mechanism of PPAR{gamma}-mediated ovarian toxicities of PFNA observed in vitro. The BMD analysis of in vitro and in vivo results suggested human relevant exposure levels of long-chain PFAS in our study pose an extra risk of ovarian defects, with follicular rupture as the most sensitive endpoint. DiscussionUsing in vitro follicle culture and in vivo mouse models, we discovered that long-chain PFAS interfere with gonadotropin-dependent follicle maturation, hormone secretion, and ovulation, posing a non-negligible risk to womens reproductive health including anovulation, irregular menstrual cycles, and sub- or infertility.

pharmacology and toxicology↗

bioRxiv2023

Imaging the microscopic viscoelastic anisotropy in living cells

Maintaining and modulating the mechanical anisotropy is essential for biological processes. How this is achieved on the microscopic scale in living soft matter is however not always clear. Here we introduce Brillouin Light Scattering Anisotropy Microscopy (BLAM) for mapping the high-frequency viscoelastic anisotropy inside living cells. Following proof-of-principle experiments on muscle myofibers, we apply this to study two fundamental biological processes. In plant cell walls we show how a phase-transition driven switch between anisotropic-isotropic wall properties may lead to asymmetric growth. In mammalian cell nuclei we uncover a spatio-temporally oscillating elastic anisotropy correlated to chromatin condensation, with long range orientational correlations that may provide a dynamic framework for coordinating intra-nuclear processes. Our results highlight the direct and indirect role the high-frequency mechanics can play in providing dynamic structure that lead to the regulation of diverse fundamental processes in biological systems, and offer a means for studying these. BLAM should find diverse biomedical and material characterization applications.

biophysics↗

bioRxiv2022

In silico transcriptomics identifies FDA-approved drugs and biological pathways for protection against cisplatin-induced hearing loss

Acquired hearing loss is a major health problem that affects 5-10% of the world population. However, there are no FDA-approved drugs for the treatment or prevention of hearing loss. Employing the Connectivity Map (CMap) that contains >54,000 compounds, we performed an unbiased in silico screen using the transcriptomic profiles of cisplatin-resistant and -sensitive cancer cell lines. Pathway enrichment analysis identified gene-drug targets for which 30 candidate drugs were selected with potential to confer protection against cisplatin-induced ototoxicity. In parallel, transcriptomic analysis of a cisplatin-treated cochlear-derived cell line identified common enriched pathway targets. We subsequently tested these top 30 candidate compounds, 15 (50%) of which are FDA-approved for other indications, and 26 (87%) of which were validated for their protective effects in either a cochlear-derived cell line or zebrafish lateral line neuromasts, thus confirming our in silico transcriptomic approach. Among these top compounds, niclosamide, a salicyanilide drug approved by the FDA for treating tapeworm infections for decades, protected from cisplatin- and noise-induced hearing loss in mice. Finally, niclosamide and ezetimibe (an Nrf2 agonist) exerted synergistic protection against cisplatin-ototoxicity in zebrafish, validating the Nrf2 pathway as part of niclosamides mechanism of action. Taken together, employing the CMap, we identified multiple pathways and drugs against cisplatin ototoxicity and confirmed that niclosamide can effectively be repurposed as an otoprotectant for future clinical trials against cisplatin- and noise-induced hearing loss. Significant StatementEmploying the Connectivity Map as our in silico transcriptomic screening strategy we identified FDA-approved drugs and biological pathways for protection against cisplatin-induced hearing loss.

neuroscience↗

bioRxiv2019

Phenotypic clustering reveals distinct subtypes of polycystic ovary syndrome with novel genetic associations

BackgroundPolycystic ovary syndrome (PCOS) is a common, complex genetic disorder affecting up to 15% of reproductive age women worldwide, depending on the diagnostic criteria applied. These diagnostic criteria are based on expert opinion and have been the subject of considerable controversy. The phenotypic variation observed in PCOS is suggestive of an underlying genetic heterogeneity, but a recent meta-analysis of European ancestry PCOS cases found that the genetic architecture of PCOS defined by different diagnostic criteria was generally similar, suggesting that the criteria do not identify biologically distinct disease subtypes. We performed this study to test the hypothesis that there are biologically relevant subtypes of PCOS.\n\nMethods and FindingsUnsupervised hierarchical cluster analysis was performed on quantitative anthropometric, reproductive, and metabolic traits in a genotyped discovery cohort of 893 PCOS cases and an ungenotyped validation cohort of 263 PCOS cases. We identified two PCOS subtypes: a \"reproductive\" group (21-23%) characterized by higher luteinizing hormone (LH) and sex hormone binding globulin (SHBG) levels with relatively low body mass index (BMI) and insulin levels; and a \"metabolic\" group (37-39%), characterized by higher BMI, glucose, and insulin levels with lower SHBG and LH levels. We performed a GWAS on the genotyped cohort, limiting the cases to either the reproductive or metabolic subtypes. We identified alleles in four novel loci that were associated with the reproductive subtype at genome-wide significance (PRDM2/KAZN1, P=2.2x10-10; IQCA1, P=2.8x10-9; BMPR1B/UNC5C, P=9.7x10-9; CDH10, P=1.2x10-8) and one locus that was significantly associated with the metabolic subtype (KCNH7/FIGN, P=1.0x10-8). We have previously reported that rare variants in DENND1A, a gene regulating androgen biosynthesis, were associated with PCOS quantitative traits in a family-based whole genome sequencing analysis. We classified the reproductive and metabolic subtypes in this family-based PCOS cohort and found that the subtypes tended to cluster in families and that carriers of rare DENND1A variants were significantly more likely to have the reproductive subtype of PCOS. Limitations of our study were that only PCOS cases of European ancestry diagnosed by NIH criteria were included, the sample sizes for the subtype GWAS were small, and the GWAS findings were not replicated.\n\nConclusionsIn conclusion, we have found stable reproductive and metabolic subtypes of PCOS. Further, these subtypes were associated with novel susceptibility loci. Our results suggest that these subtypes are biologically relevant since they have distinct genetic architectures. This study demonstrates how precise phenotypic delineation can be more powerful than increases in sample size for genetic association studies.

genomics↗

bioRxiv2019

A polygenic and phenotypic risk prediction for Polycystic Ovary Syndrome evaluated by Phenome-wide association studies

PurposeAs many as 75% of patients with Polycystic ovary syndrome (PCOS) are estimated to be unidentified in clinical practice. Utilizing polygenic risk prediction, we aim to identify the phenome-wide comorbidity patterns characteristic of PCOS to improve accurate diagnosis and preventive treatment.\n\nMethods and FindingsLeveraging the electronic health records (EHRs) of 124,852 individuals, we developed a PCOS risk prediction algorithm by combining polygenic risk scores (PRS) with PCOS component phenotypes into a polygenic and phenotypic risk score (PPRS). We evaluated its predictive capability across different ancestries and perform a PRS-based phenome-wide association study (PheWAS) to assess the phenomic expression of the heightened risk of PCOS. The integrated polygenic prediction improved the average performance (pseudo-R2) for PCOS detection by 0.228 (61.5-fold), 0.224 (58.8-fold), 0.211 (57.0-fold) over the null model across European, African, and multi-ancestry participants respectively. The subsequent PRS-powered PheWAS identified a high level of shared biology between PCOS and a range of metabolic and endocrine outcomes, especially with obesity and diabetes: morbid obesity, type 2 diabetes, hypercholesterolemia, disorders of lipid metabolism, hypertension and sleep apnea reaching phenome-wide significance.\n\nConclusionsOur study has expanded the methodological utility of PRS in patient stratification and risk prediction, especially in a multifactorial condition like PCOS, across different genetic origins. By utilizing the individual genome-phenome data available from the EHR, our approach also demonstrates that polygenic prediction by PRS can provide valuable opportunities to discover the pleiotropic phenomic network associated with PCOS pathogenesis.

bioinformatics↗

bioRxiv2018

Family-based quantitative trait meta-analysis implicates rare noncoding variants in DENND1A in pathogenesis of polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is among the most common endocrine disorders of premenopausal women, affecting 5-15% of this population depending on the diagnostic criteria applied. It is characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. PCOS is a leading risk factor for type 2 diabetes in young women. PCOS is highly heritable, but only a small proportion of this heritability can be accounted for by the common genetic susceptibility variants identified to date. To test the hypothesis that rare genetic variants contribute to PCOS pathogenesis, we performed whole-genome sequencing on DNA from 62 families with one or more daughters with PCOS. We tested for associations of rare variants with PCOS and its concomitant hormonal traits using a quantitative trait meta-analysis. We found rare variants in DENND1A (P=5.31x10-5, Padj=0.019) that were significantly associated with reproductive and metabolic traits in PCOS families. Common variants in DENND1A have previously been associated with PCOS diagnosis in genome-wide association studies. Subsequent studies indicated that DENND1A is an important regulator of human ovarian androgen biosynthesis. Our findings provide additional evidence that DENND1A plays a central role in PCOS and suggest that rare noncoding variants contribute to disease pathogenesis.

genomics↗

bioRxiv2018

Large-Scale Genome-Wide Meta Analysis of Polycystic Ovary Syndrome Suggests Shared Genetic Architecture for Different Diagnosis Criteria.

Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed with different criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease indicate shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. Only one locus differed in its association by diagnostic criteria, otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or Rotterdam criteria across common variants at 13 loci.

genetics↗