Quantification of lipoproteins by proton nuclear magnetic resonance spectroscopy (1H-NMRS) improves the prediction of cardiac autonomic dysfunction in patients with type 1 diabetes.

AIMS: To assess if advanced characterization of serum glycoprotein and lipoprotein profile, measured by proton nuclear magnetic resonance spectroscopy (1H-NMRS) improves a predictive clinical model of cardioautonomic neuropathy (CAN) in subjects with type 1 diabetes (T1D). METHODS: Cross-sectional study (ClinicalTrials.gov Identifier: NCT04950634). CAN was diagnosed using Ewing's score. Advanced characterization of macromolecular complexes including glycoprotein and lipoprotein profiles in serum samples were measured by 1H-NMRS. We addressed the relationships between these biomarkers and CAN using correlation and regression analyses. Diagnostic performance was assessed by analyzing their areas under the receiver operating characteristic curves (AUCROC). RESULTS: Three hundred and twenty-three patients were included (46% female, mean age and duration of diabetes of 41 ± 13 years and 19 ± 11 years, respectively). The overall prevalence of CAN was 28% [95% confidence interval (95%CI): 23; 33]. Glycoproteins such as N-acetylglucosamine/galactosamine and sialic acid showed strong correlations with inflammatory markers such as high-sensitive C-reactive protein, fibrinogen, IL-10, IL-6, and TNF-α. On the contrary, we did not find any association between the former and CAN. A stepwise binary logistic regression model (R2 = 0.078; P = 0.003) retained intermediate-density lipoprotein-triglycerides (IDL-TG) [ß:0.082 (95%CI: 0.005; 0.160); P = 0.039], high-density lipoprotein-triglycerides (HDL-TGL)/HDL-Cholesterol [ß:3.633 (95%CI: 0.873; 6.394); P = 0.010], and large-HDL particle number [ß: 3.710 (95%CI: 0.677; 6.744); P = 0.001] as statistically significant determinants of CAN. Adding these lipoprotein particles to a clinical prediction model of CAN that included age, duration of diabetes, and A1c enhanced its diagnostic performance, improving AUCROC from 0.546 (95%CI: 0.404; 0.688) to 0.728 (95%CI: 0.616; 0.840). CONCLUSIONS: When added to clinical variables, 1H-NMRS-lipoprotein particle profiles may be helpful to identify those patients with T1D at risk of CAN.

Validation of circulating microRNAs miR-142-3p and miR-598-3p in women with polycystic ovary syndrome as potential diagnostic markers.

STUDY QUESTION: Circulating miRNAs previously associated with androgen excess in women might be used as diagnostic biomarkers for polycystic ovary syndrome (PCOS). SUMMARY ANSWER: Models based on circulating miR-142-3p and miR-598-3p expression show good discrimination among women with and without PCOS, particularly when coupled with easily available measurements such as waist-to-hip ratio (WHR) and circulating LH-to-FSH (LH/FSH) ratios. WHAT IS KNOWN ALREADY: The lack of standardization of the signs, methods, and threshold values used to establish the presence of the diagnostic criteria (hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology) complicates the diagnosis of PCOS. Certain biomarkers may help with such a diagnosis. We conducted a validation study to check the diagnostic accuracy for PCOS of several miRNAs that were associated with the syndrome in a small pilot study that had been previously carried out by our research group. STUDY DESIGN, SIZE, DURATION: This was a diagnostic test study involving 140 premenopausal women. PARTICIPANTS/MATERIALS, SETTING, METHODS: We included 71 women with PCOS and 69 healthy control women in the study. Both groups were selected as to be similar in terms of body mass index. We used miRCURY LNA™ Universal RT microRNA PCR to analyse the five miRNAs that had shown the strongest associations with PCOS in a much smaller pilot study previously conducted by our group. We studied diagnostic accuracy using receiver operating characteristics (ROC) curve analysis. MAIN RESULTS AND THE ROLE OF CHANCE: Only the expression of two miRNAs, miR-142-3p and miR-598-3p, of the five studied, was different between the women with PCOS and the non-hyperandrogenic controls. The diagnostic accuracy of the combination of these circulating miRNAs was good (area under the ROC curve (AUC) 0.801; 95% CI: 0.72-0.88) and was further improved when adding WHR (AUC 0.834, 95% CI: 0.756-0.912), LH/FSH ratio (AUC = 0.869, 95% CI: 0.804-0.934) or both (AUC = 0.895, 95% CI: 0.835-0.954). We developed several models by selecting different threshold values for these variables favouring either sensitivity or specificity, with positive and negative predictive values as high as 88% or 85%, respectively. LIMITATIONS, REASONS FOR CAUTION: Patients included here had the classic PCOS phenotype, consisting of hyperandrogenism and ovulatory dysfunction; hence, the present results might not apply to milder phenotypes lacking androgen excess. WIDER IMPLICATIONS OF THE FINDINGS: If confirmed in larger studies addressing different populations and PCOS phenotypes, these biomarkers may be useful to simplify the clinical diagnosis of this prevalent syndrome. STUDY FUNDING/COMPETING INTEREST(S): This research was funded by Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation (grants PI15/01686, PIE16/00050, PI18/01122 & PI21/00116) and co-funded by European Regional Development Fund 'A way to make Europe'. Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM) and Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS) are also initiatives of the Instituto de Salud Carlos III. The authors have no competing interests to disclose. TRIAL REGISTRATION NUMBER: N/A.

Application of proteomics to the study of polycystic ovary syndrome.

BACKGROUND: Clinical proteomics consists of qualitative and quantitative profiling of proteins present in clinical specimens such as body fluids or tissues, with the aim of discovering novel proteins and cellular pathways associated with the disease of interest. AIM: To review the proteomic studies conducted to date that addressed different aspects of the pathogenesis of polycystic ovary syndrome (PCOS). METHODS: Descriptive review of studies that applied proteomic techniques to the study of PCOS. Published articles were identified using the Entrez-PubMed online search facilities. RESULTS: Most studies conducted to date focused on protein variations in plasma and different target tissues. Plasma proteomics analysis revealed that PCOS associates changes in protein expression in several acute-phase response proteins. Moreover, some of these molecules play major roles in iron metabolism and low-grade chronic inflammation. Studies using omental adipose tissue from morbidly obese women with or without PCOS revealed differences in abundance of proteins that may be involved in lipid and glucose metabolism, oxidative stress processes, and adipocyte differentiation. Moreover, identification of differentially expressed proteins in ovarian tissue, granulosa cells or T lymphocites may help to characterize more clearly some aspects of this disorder. CONCLUSIONS: Although the application of proteomic techniques to the study of PCOS is in its early infancy, studies conducted to date highlight its heterogeneous nature. Aside from androgen excess, several pathways related to intermediate metabolism, oxidative stress processes, inflammation and iron metabolism appear to be involved in the pathophysiology of PCOS.