COVID-19 biomarkers for severity mapped to polycystic ovary syndrome.
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ABSTRACT:
SUBMITTER: Moin ASM
PROVIDER: S-EPMC7753500 | biostudies-literature | 2020 Dec
REPOSITORIES: biostudies-literature
Publications
COVID-19 biomarkers for severity mapped to polycystic ovary syndrome.
Moin Abu Saleh Md ASM Sathyapalan Thozhukat T Atkin Stephen L SL Butler Alexandra E AE
Journal of translational medicine 20201222 1
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Project description:Women with polycystic ovary syndrome (PCOS) are more likely to develop endometrial cancer (EC). The molecular mechanisms which increase the risk of EC in PCOS are unclear. Derangements in lipid metabolism are associated with EC, but there have been no studies, investigating if this might increase the risk of EC in PCOS. This was a cross-sectional study of 102 women in three groups of 34 (PCOS, EC and controls) at Nottingham University Hospital, UK. All participants had clinical assessments, followed by obtaining plasma and endometrial tissue samples. Lipidomic analyses were performed using liquid chromatography (LC) coupled with high resolution mass spectrometry (HRMS) and the obtained lipid datasets were screened using standard software and databases. Using multivariate data analysis, there were no common markers found for EC and PCOS. However, on univariate analyses, both PCOS and EC endometrial tissue samples showed a significant decrease in monoacylglycerol 24:0 and capric acid compared to controls. Further studies are required to validate these findings and investigate the potential role of monoacylglycerol 24:0 and capric acid in the link between PCOS with EC.
| S-EPMC7370092 | biostudies-literature
Project description: Not available
| S-EPMC10515223 | biostudies-literature
Project description:ObjectiveSeveral recent observational studies have linked metabolic comorbidities to an increased risk from COVID-19. Here we investigated whether women with PCOS are at an increased risk of COVID-19 infection.DesignPopulation-based closed cohort study between 31 January 2020 and 22 July 2020 in the setting of a UK primary care database (The Health Improvement Network, THIN).MethodsThe main outcome was the incidence of COVID-19 coded as suspected or confirmed by the primary care provider. We used Cox proportional hazards regression model with stepwise inclusion of explanatory variables (age, BMI, impaired glucose regulation, androgen excess, anovulation, vitamin D deficiency, hypertension, and cardiovascular disease) to provide unadjusted and adjusted hazard risks (HR) of COVID-19 infection among women with PCOS compared to women without PCOS.ResultsWe identified 21 292 women with a coded diagnosis of PCO/PCOS and randomly selected 78 310 aged and general practice matched control women. The crude COVID-19 incidence was 18.1 and 11.9 per 1000 person-years among women with and without PCOS, respectively. Age-adjusted Cox regression analysis suggested a 51% higher risk of COVID-19 among women with PCOS compared to women without PCOS (HR: 1.51 (95% CI: 1.27-1.80), P < 0.001). After adjusting for age and BMI, HR reduced to 1.36 (1.14-1.63)], P = 0.001. In the fully adjusted model, women with PCOS had a 28% increased risk of COVID-19 (aHR: 1.28 (1.05-1.56), P = 0.015).ConclusionWomen with PCOS are at an increased risk of COVID-19 infection and should be specifically encouraged to adhere to infection control measures during the COVID-19 pandemic.Significance statementWomen with polycystic ovary syndrome (PCOS) have an increased risk of cardio-metabolic disease, which have been identified as a risk factor for COVID-19. To investigate whether the increased metabolic risk in PCOS translates into an increased risk of COVID-19 infection, we carried out a population-based closed cohort study in the UK during its first wave of the SARS-CoV-2 pandemic (January to July 2020), including 21 292 women with PCOS and 78 310 controls matched for sex, age and general practice location. Results revealed a 52% increased risk of COVID-19 infection in women with PCOS, which remained increased at 28% above controls after adjustment for age, BMI, impaired glucose regulation and other explanatory variables.
| S-EPMC8052516 | biostudies-literature
Project description:ObjectivePolycystic ovary syndrome (PCOS) is a prevalent metabolic disorder with an increased risk for cardiovascular disease (CVD) that is enhanced by obesity. This study sought to determine whether a panel of cardiovascular risk proteins (CVRPs) would be dysregulated in overweight/obese PCOS patients, highlighting potential biomarkers for CVD in PCOS.MethodsIn this exploratory cross-sectional study, plasma levels of 54 CVRPs were analyzed in women with PCOS (n = 147) and controls (n = 97). CVRPs were measured using the SOMAscan proteomic platform (version 3.1), with significant proteins identified through linear models, regression analysis, and receiver operating characteristic (ROC) analysis. Analysis on BMI-matched subsets of the cohort were undertaken. Functional enrichment and protein-protein interaction analyses elucidated the pathways involved.ResultsEleven CVRPs were dysregulated in PCOS (whole set, without matching for body mass index (BMI) or insulin resistance (IR)): leptin, Interleukin-1 receptor antagonist protein (IL-1Ra), polymeric immunoglobulin receptor (PIGR), interleukin-18 receptor (IL-18Ra), C-C motif chemokine 3 (MIP-1a), and angiopoietin-1 (ANGPT1) were upregulated whilst advanced glycosylation end product-specific receptor, soluble (sRAGE), bone morphogenetic protein 6 (BMP6); growth/differentiation factor 2 (GDF2), superoxide dismutase [Mn] mitochondrial (MnSOD), and SLAM family member 5 (SLAF5) were downregulated versus the controls. In BMI-matched (overweight/obese, BMI ≥ 26 kg/m2) subset analysis, six CVRPs were common to the whole set: ANGPT1 and IL-1Ra were upregulated; and sRAGE, BMP6, GDF2, and Mn-SOD were downregulated. In addition, lymphotactin (XCL1) was upregulated and placenta growth factor (PIGF), alpha-L-iduronidase (IDUA), angiopoietin-1 receptor, and soluble (sTie-2) and macrophage metalloelastase (MMP12) were downregulated. A subset analysis of BMI-matched plus insulin resistance (IR)-matched women revealed only upregulation of tissue factor (TF) and renin in PCOS, potentially serving as biomarkers for cardiovascular risk in overweight/obese women with PCOS.ConclusionsA combination of upregulated obesity-related CVRPs (ANGPT1/IL/1Ra/XCL1) and downregulated cardioprotective proteins (sRAGE/BMP6/Mn-SOD/GDF2) in overweight/obese PCOS women may contribute to the increased risk for CVD. TF and renin upregulation observed in the BMI- and IR-matched limited sample PCOS subgroup indicates their potential risk of CVD.
| S-EPMC11763313 | biostudies-literature
Project description:BackgroundPolycystic ovary syndrome (PCOS) affects 10% of reproductive-aged women, and is marked by irregular menses and high androgens. PCOS is a known risk factor for imaging-confirmed steatosis, and we now aim to evaluate whether PCOS influences histologic severity of non-alcoholic fatty liver disease (NAFLD).MethodsRetrospective study of women ages 18-45 years with biopsy-confirmed NAFLD between 2008 and 2019. Metabolic comorbidities were captured within 6 months of biopsy. Histologic features of non-alcoholic steatohepatitis (NASH) were independently evaluated by two pathologists blinded to PCOS status.ResultsAmong 102 women meeting study criteria, 36% (n = 37) had PCOS; median age was 35 years; 27% were white, 6% black, 19% Asian and 47% reported Hispanic ethnicity. Women with PCOS had higher LDL (122 vs 102 mg/dL, P = .05) and body mass index(BMI) (38 vs 33 kg/cm2 , P < .01). NASH was present in 76% of women with PCOS vs 66% without PCOS (P = .3), and a higher proportion with PCOS had severe ballooning (32% vs 13%, P = .02), presence of any fibrosis (84% vs 66%, P = .06) and advanced fibrosis (16% vs 6%, P = .10). Adjusted for age and BMI, PCOS remained associated with severe hepatocyte ballooning (OR 3.4, 95% CI 1.1-10.6, P = .03) and advanced fibrosis (OR 7.1, 95% CI 1.3-39, P = .02). Among women with advanced fibrosis, median age was 5 years younger in those with as compared to those without PCOS (40 vs 45 years, P = .02).ConclusionPolycystic ovary syndrome is independently associated with more severe NASH, including advanced fibrosis. Hepatologists should routinely inquire about PCOS in reproductive-aged women with NAFLD, and evaluate for more severe liver disease in this population.
| S-EPMC6980925 | biostudies-literature
Project description:Respiratory viruses such as SARS-CoV-2 are pathogens that can reach pandemic proportions. The early human response to respiratory viruses are in the nasal cavity and nasopharyngeal regions. Defining biomarkers of disease trajectory at the time of a positive test is important for opting for treatment and monitoring decisions. We hypothesize that the nasopharyngeal tRNA profiles can be used to predict symptom severity resulting from SARS-CoV-2 infection. We carried out multiplex small RNA sequencing (MSR-seq) on nasopharyngeal swaps to measure the human tRNA response to SARS-CoV-2 infection. Our result simultaneously measured full-length tRNA abundance, tRNA modifications, and tRNA fragmentation among individuals that went on to develop no/mild or severe symptoms. We identified distinct tRNA signatures that can predict the clinical outcome of SARS-CoV-2 infected individual at the time of a positive test. These results highlight the utility of using host tRNA properties as biomarkers for clinical applications.
2022-10-01 | GSE208612 | GEO
Project description:BackgroundIn this study, we aimed to identify novel biomarkers for polycystic ovary syndrome (PCOS) and analyze their potential roles in immune infiltration during PCOS pathogenesis.MethodsFive datasets, namely GSE137684, GSE80432, GSE114419, GSE138518, and GSE155489, were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were selected from the train datasets. The least absolute shrinkage and selection operator logistic regression model and support vector machine-recursive feature elimination algorithm were combined to screen potential biomarkers. The test datasets validated the expression levels of these biomarkers, and the area under the curve (AUC) was calculated to analyze their diagnostic value. Quantitative real-time PCR was conducted to verify biomarkers' expression in clinical samples. CIBERSORT was used to assess differential immune infiltration, and the correlations of biomarkers with infiltrating immune cells were evaluated.ResultsHerein, 1265 DEGs were identified between PCOS and control groups. The gene sets related to immune response and adaptive immune response were differentially activated in PCOS. The two diagnostic biomarkers of PCOS identified by us were HD domain containing 3 (HDDC3) and syndecan 2 (SDC2; AUC, 0.918 and 0.816, respectively). The validation of hub biomarkers in clinical samples using RT-qPCR was consistent with bioinformatics results. Immune infiltration analysis indicated that decreased activated mast cells (P = 0.033) and increased eosinophils (P = 0.040) may be a part of the pathogenesis of PCOS. HDDC3 was positively correlated with T regulatory cells (P = 0.0064), activated mast cells (P = 0.014), and monocytes (P = 0.024) but negatively correlated with activated memory CD4 T cells (P = 0.016) in PCOS. In addition, SDC2 was positively correlated with activated mast cells (P = 0.0021), plasma cells (P = 0.0051), and M2 macrophages (P = 0.038) but negatively correlated with eosinophils (P = 0.01) and neutrophils (P = 0.031) in PCOS.ConclusionHDDC3 and SDC2 can serve as candidate biomarkers of PCOS and provide new insights into the molecular mechanisms of immune regulation in PCOS.
| S-EPMC9258136 | biostudies-literature
Project description:ObjectiveThe study aimed to explore the role of metabolism-related proteins and their correlation with clinical data in predicting the prognosis of polycystic ovary syndrome (PCOS).MethodsThis research involves a secondary analysis of proteomic data derived from endometrial samples collected from our study group, which includes 33 PCOS patients and 7 control subjects. A comprehensive identification and analysis of 4425 proteins were conducted to screened differentially expressed proteins (DEPs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were subsequently performed on the DEPs. To identify independent prognostic metabolism-related proteins, univariate Cox regression and LASSO regression were applied. The expression levels of these proteins were then used to develop a prognostic model, with their predictive accuracy evaluated through receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves. Furthermore, we also investigate the correlation between clinical data and prognostic proteins.ResultsThe study identified 285 DEPs between the PCOS and control groups. GO enrichment analysis revealed significant involvement in metabolic processes, while KEGG pathway analysis highlighted pathways such as glycolysis/gluconeogenesis and glucagon signaling. Ten key metabolism-related proteins (ACSL5, ANPEP, CYB5R3, ENOPH1, GLS, GLUD1, LDHB, PLCD1, PYCR2, and PYCR3) were identified as significant predictors of PCOS prognosis. Patients were separated into high and low-risk groups according to the risk score. The ROC curves for predicting outcomes at 6, 28, and 37 weeks demonstrated excellent predictive performance, with AUC values of 0.98, 1.0, and 1.0, respectively. The nomogram constructed from these proteins provided a reliable tool for predicting pregnancy outcomes. DCA indicated a net benefit of the model across various risk thresholds, and the calibration curve confirmed the model's accuracy. Additionally, we also found BMI exhibited a significant negative correlation with the expression of GLS (r =-0.44, p = 0.01) and CHO showed a significant positive correlation with the expression of LDHB (r = 0.35, p = 0.04).ConclusionThe identified metabolism-related proteins provide valuable insights into the prognosis of PCOS. The protein based prognostic model offers a robust and reliable tool for risk stratification and personalized management of PCOS patients.
| S-EPMC11660692 | biostudies-literature
Project description:Polycystic ovary syndrome (PCOS) is known as the most common metabolic/endocrine disorder among women of reproductive age. Its complicated causality assessment and diagnostic emphasized the role of non-coding regulatory RNAs as molecular biomarkers in studying, diagnosing and even as therapeutics of PCOS. This review discusses a comparative summary of research into microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) that are molecularly or statistically related to PCOS. We categorize the literature in terms of centering on either miRNAs or lncRNAs and discuss the combinatory studies and promising ideas as well. Additionally, we compare the pros and cons of the prominent research methodologies used for each of the abovementioned research themes and discuss how errors can be stopped from propagation by selecting correct methodologies for future research. Finally, it can be concluded that research into miRNAs and lncRNAs has the potential for identifying functional networks of regulation with multiple mRNAs (and hence, functional proteins). This new understanding may eventually afford clinicians to control the molecular course of the pathogenesis better. With further research, RNA (with statistical significance and present in the blood) may be used as biomarkers for the disease, and more possibilities for RNA therapy agents can be identified.
| S-EPMC8817139 | biostudies-literature
Project description:BACKGROUND:In women of reproductive age, polycystic ovary syndrome (PCOS) constitutes the most frequent endocrine disorder. Women with PCOS are considered to typically belong to an age and sex group which is at lower risk for severe COVID-19. MAIN BODY:Emerging data link the risk of severe COVID-19 with certain factors such as hyper-inflammation, ethnicity predisposition, low vitamin D levels, and hyperandrogenism, all of which have known direct associations with PCOS. Moreover, in this common female patient population, there is markedly high prevalence of multiple cardio-metabolic conditions, such as type 2 diabetes, obesity, and hypertension, which may significantly increase the risk for adverse COVID-19-related outcomes. This strong overlap of risk factors for both worse PCOS cardio-metabolic manifestations and severe COVID-19 should be highlighted for the clinical practice, particularly since women with PCOS often receive fragmented care from multiple healthcare services. Comprehensively informing women with PCOS regarding the potential risks from COVID-19 and how this may affect their management is also essential. CONCLUSION:Despite the immense challenges posed by the COVID-19 outbreak to the healthcare systems in affected countries, attention should be directed to maintain a high standard of care for complex patients such as many women with PCOS and provide relevant practical recommendations for optimal management in the setting of this fast moving pandemic.
| S-EPMC7360476 | biostudies-literature