Coding and Non-Coding Transcriptomic Landscape of Aortic Complications in Marfan Syndrome

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(13), P. 7367 - 7367

Published: July 5, 2024

Marfan syndrome (MFS) is a rare congenital disorder of the connective tissue, leading to thoracic aortic aneurysms (TAA) and dissection, among other complications. Currently, most efficient strategy prevent life-threatening dissection preventive surgery. Periodic imaging applying complex techniques required monitor TAA progression guide timing surgical intervention. Thus, there an acute demand for non-invasive biomarkers diagnosis prognosis, as well innovative therapeutic targets MFS. Unraveling intricate pathomolecular mechanisms underlying vital address these needs. High-throughput platforms are particularly well-suited this purpose, they enable integration different datasets, such transcriptomic epigenetic profiles. In narrative review, we summarize relevant studies investigating changes in both coding non-coding transcriptome epigenome MFS-induced TAA. The collective findings highlight implicated pathways, TGF-β signaling, extracellular matrix structure, inflammation, mitochondrial dysfunction. Potential candidates biomarkers, miR-200c, emerged, like Tfam, associated with respiration, or miR-632, stimulating endothelial-to-mesenchymal transition. While discoveries promising, rigorous extensive validation large patient cohorts indispensable confirm their clinical relevance potential.

Language: Английский

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Integrated transcriptomic and regulatory RNA profiling reflects complex pathophysiology and uncovers a conserved gene signature in end stage heart failure

Journal of Molecular and Cellular Cardiology Plus, Journal Year: 2025, Volume and Issue: 11, P. 100282 - 100282

Published: Jan. 5, 2025

Heart failure (HF) is a complex syndrome. Despite availability of multiple treatment options, the mortality remains high and quality life poor. Better understanding underlying pathophysiological processes can lead to development novel therapies. Multiple comparative transcriptomics studies, which revealed gene level changes in key pathways failing hearts, point towards heterogeneity from interplay disease stage, etiologies ethnicity. Transcriptomic characterization HF patients different ethnicities potentially help imparted by various factors core elements heart failure. An integrated analysis bulk transcriptome microRNA sequencing cardiac tissues 30 South Asian (SA) having with reduced ejection fraction (HFrEF) 19 control subjects was conducted. Plasma miRNAs subset HFrEF were also sequenced understand their biomarker potential. The altered myocardium SA reflected muscle contraction, cellular energetics, immune signaling extracellular matrix remodelling as predominant mechanisms. showed dysregulation microRNAs tissue like miR-216, miR-217, miR-184 miR-9983. Many these miRNAs, such miR184 few others, levels both plasma suggesting diversity transcriptomes published studies led us examine genes our cohort. A signature generated using machine learning (ML) top dysregulated cohort stratified controls other cohorts. sensitivity further improved when union two cohorts used training set. Our ML analyses developed consisting 21 that stratify 98 % all tested This study reveals molecular pathophysiology coding regulatory non-coding components uncovers conserved for HF.

Language: Английский

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A protocol for microRNA extraction from gastrointestinal digesta

Food Chemistry Molecular Sciences, Journal Year: 2025, Volume and Issue: 10, P. 100245 - 100245

Published: Feb. 11, 2025

MicroRNAs (miRNAs) are non-coding RNAs that influence gene-expression via post-transcriptional regulation of target protein-coding RNAs. With literature reports indicating survival diet-derived miRNAs following their ingestion, it is important to study stability and concentration during gastrointestinal digestion. The unique combination chemicals elevated RNAse content present in the matrix may be a limiting factor for studying miRNAs. First, chemical cross-reactivity with constituents (e.g. bile salts) interfere salt bridge interactions typically RNA extraction, reducing efficiency column. Second, high not fully inhibited extraction could continue degrading miRNAs, as observed other tissues content. These combined issues result reduced yield purity extracts, further (i.e. downstream metabolism). In manuscript, we display method based on silica column purification extract quantify from bioaccessible phase digesta. proposed protocol provides simple, quick (less than 2 h), reliable, systematic miRNA optimization showcased challenges caused by activity, plant bioactive substances bile-salt within digesta have been overcome fraction body fluid so far neglected now available researchers, allowing use biomarkers intake potentially biological changes.

Language: Английский

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Non‐Invasive Diagnosis of Early Colorectal Cancerization via Amplified Sensing of MicroRNA‐21 in NIR‐II Window

Advanced Materials, Journal Year: 2025, Volume and Issue: unknown

Published: March 24, 2025

Abstract Accurate, sensitive, and in situ visualization of aberrant expression level low‐abundant biomolecules is crucial for early colorectal cancer (CRC) detection ahead tumor morphology change. However, the clinical used colonoscopy biopsy methods are invasive lack sensitivity at early‐stage cancerization. Here, an amplified sensing strategy developed second near‐infrared long‐wavelength subregion (NIR‐II‐L, 1500–1900 nm) by integrating DNAzyme‐triggered signal amplification technology lanthanide‐dye hybrid system. In CRC, overexpressed biomarker microRNA‐21 initiates NIR‐II‐L luminescence ratiometric CRCsensor. The high with a limit (LOD) 1.26 p m allows non‐invasive orthotopic cancerization via rectal administration, which achieves accurate diagnosis 2 weeks vitro histological results. This innovative approach offers promising tool long‐term monitoring carcinogenesis progression, potential applications other cancer‐related biomarkers.

Language: Английский

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A Sensitive and Fast microRNA Detection Platform Based on CRlSPR-Cas12a Coupled with Hybridization Chain Reaction and Photonic Crystal Microarray

Biosensors, Journal Year: 2025, Volume and Issue: 15(4), P. 233 - 233

Published: April 5, 2025

Changes in microRNA (miRNA) levels are closely associated with the pathological processes of many diseases. The sensitive and fast detection miRNAs is critical for diagnosis prognosis. Here, we report a platform employing CRISPR/Cas12a to recognize changes miRNA while avoiding complex multi-thermal cycling procedures. A non-enzyme-dependent hybridization chain reaction (HCR) was used convert signal into double-stranded DNA, which contained Cas12a activation sequence. target sequence amplified simply isothermally, enabling test be executed at constant temperature 37 °C. had capacity measure concentrations down picomolar level, could distinguished nanomolar level. By using photonic crystal microarrays stopband-matched emission spectrum fluorescent-quencher modified reporter, fluorescence moderately enhanced increase sensitivity. With this enhancement, analyzable results were obtained 15 min. HCR cleavage conducted single tube by separating two procedures bottom cap. We verified sensitivity specificity one-pot system, both comparable those two-step method. Overall, our study produced based on system enzyme-free amplification. This may serve as potential solution clinical practice.

Language: Английский

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Circulating Non-Coding RNAs as Indicators of Fibrosis and Heart Failure Severity

Cells, Journal Year: 2025, Volume and Issue: 14(7), P. 553 - 553

Published: April 7, 2025

Heart failure (HF) is a leading cause of morbidity and mortality worldwide, representing complex clinical syndrome in which the heart’s ability to pump blood efficiently impaired. HF can be subclassified into heart with reduced ejection fraction (HFrEF) preserved (HFpEF), each distinct pathophysiological mechanisms varying levels severity. The progression significantly driven by cardiac fibrosis, pathological process extracellular matrix undergoes abnormal uncontrolled remodelling. Cardiac fibrosis characterized excessive protein deposition activation myofibroblasts, increasing stiffness heart, thus disrupting its normal structure function promoting lethal arrythmia. MicroRNAs, long non-coding RNAs, circular collectively known as RNAs (ncRNAs), have recently gained significant attention due growing body evidence suggesting their involvement remodelling such fibrosis. ncRNAs found peripheral blood, indicating potential biomarkers for assessing In this review, we critically examine recent advancements findings related use discuss implication development.

Language: Английский

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Impact of microRNAs and long non-coding RNAs in skeletal and cardiac muscle

Current Opinion in Physiology, Journal Year: 2025, Volume and Issue: unknown, P. 100829 - 100829

Published: April 1, 2025

Language: Английский

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piRNAs as emerging biomarkers and physiological regulatory molecules in cardiovascular disease

Biochemical and Biophysical Research Communications, Journal Year: 2024, Volume and Issue: 711, P. 149906 - 149906

Published: April 7, 2024

Language: Английский

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Circulating biomarkers of myocardial remodelling: current developments and clinical applications

Heart, Journal Year: 2024, Volume and Issue: 110(19), P. 1157 - 1163

Published: Aug. 7, 2024

Myocardial remodelling, entailing cellular and molecular changes in the different components of cardiac tissue response to damage, underlies morphological structural leading which turn contributes dysfunction disease progression. Since is not available for histomolecular diagnosis, surrogate markers are needed evaluating myocardial remodelling as part clinical management patients with disease. In this setting, circulating biomarkers, a component liquid biopsy, provide promising approach fast, affordable scalable screening large numbers patients, allowing detection pathological features related aiding risk stratification therapy monitoring. However, despite advances field identification numerous potential candidates, their implementation practice beyond natriuretic peptides troponins mostly lacking. review, we will discuss some biomarkers alterations main compartments (cardiomyocytes, extracellular matrix, endothelium immune cells) have shown assessment cardiovascular risk, effects. The hurdles challenges translation into also be addressed.

Language: Английский

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Prediction of COVID‐19 severity using machine learning

Clinical and Translational Medicine, Journal Year: 2024, Volume and Issue: 14(10)

Published: Oct. 1, 2024

Dear Editor, Prediction of COVID-19 severity is a critical task in the decision-making process during initial stages disease, enabling personalised surveillance and care patients. To develop machine learning (ML) model for prediction severity, consortium 15 institutions from 12 European countries analysed expression data 2906 blood long noncoding RNAs (lncRNAs) clinical collected four independent cohorts, totalling 564 patients with COVID-19. This predictive based on age five lncRNAs predicted disease an area under receiver operating characteristic curve (AUC) .875 [.868–.881] accuracy .783 [.775–.791]. The sudden onset pandemic caught world unprepared, leading to more than 774 million confirmed cases over 7 reported deaths worldwide (over period January 2020 March 2024), according World Health Organization (WHO).1 Other having impact respiratory system, severe acute syndrome coronavirus 2 (SARS-CoV-2) can also infect nonpulmonary cells such as cardiac brain cardiovascular or neurological symptoms.2 With recent advances high throughput sequencing, large number RNA signatures have emerged promising biomarkers involved progression various diseases, including diseases.3 As response pandemic, partners EU-CardioRNA COST Action network4-6 joined forces H2020-funded COVIRNA project RNA-based diagnostic test using artificial intelligence (AI) that help predict outcomes after COVID-19.7 We chose implement targeted sequencing approach FIMICS panel cardiac-enriched heart failure-associated previously characterised by our consortium.8 In present study, we aimed apply identify will used ML conduct analysis, algorithms are suitably capable analysing complex relationships between biomedical data.9 overall workflow study illustrated Figure 1A. Briefly, cohorts were included consisting total COVID-19: PrediCOVID cohort Luxembourg (n = 162; recruitment May present), COVID19_OMICS-COVIRNA Italy 100; 2021), TOCOVID Spain 233; April June MiRCOVID Germany 69; November 2021). Patient characteristics presented Table 1. Plasma samples at baseline stored −80°C central NF S96-900-certified Biobank Firalis SA. Samples then processed following workflow: extraction, quality check, library preparation, analysis panel. Overall, 463 datasets representing each unique patient available (Figure 1B). most important predictors (lncRNAs variables) build predicting balanced 2A) imbalanced 2B) datasets. was split into training validation sets (80/20 split), feature selection performed set—for features be selected they had appear 90 out 100 iterations. which evaluated set before final highest capacity (highest AUC) chosen. Using described method, identified six best iterations 3A). Cross-validation biostatistical methods (GLMnet Stability selection; 3B). lncRNAs: SEQ0548 (LINC01088-201), SEQ0817 (FGD5-AS1), SEQ1056 (LINC01088-209), SEQ3051 (an unannotated lncRNA, henceforth referred lncCOVIRNA1) SEQ1321 (AKAP13-SI). Box/violin plots 4A–F) show significant (p < .001) differences stable groups. presents results dataset (age, LINC01088-201, FGD5-AS1, LINC01088-209, lncCOVIRNA1 AKAP13-SI) across multiple models (Naïve Bayes, Logistic Regression, Extreme gradient boosting, Support Vector Machine, Multilayer Perceptron, K-Nearest Neighbours). built performance only predictor (Table S1) S2). obtained all (age lncRNAs) Naïve Bayes allowed AUC (95% CI .868–.881) .775–.791, S1). developed integral part development molecular assay utilising routinely quantitative PCR quantify levels input prediction. Together another whole blood-based algorithm,10 use plasma could implications, instance selecting high-risk tailored treatment. An advantage method it allows faster risk stratification decision making, especially useful widely sample. LncRNAs easily quickly (2 h) measured noninvasive increasing interest community molecules treat vaccinate followed approval circulating medicine, coupled methods.7 Moreover, identification novel enhance knowledge mechanisms adverse death, pave way new therapies repurposing existing ones. Taken together, these findings value improve management All authors members who conducted study. Kanita Karaduzovic-Hadziabdic, Muhamed Adilovic, Fabio Martelli, Yvan Devaux Lu Zhang designed research acquired funding. Adilovic experiments. Pranay Shah GLMNet SS analysis. Muhammad Shoaib curated data. preprocessed Devaux, Zhang, Andrew I Lumley, Shah, Shoaib, Prashant Kumar Srivastava, Mitja Lustrek, Maciej Rosolowski, Marko Jordan Bettina Benczik staff (Joanna Michel, Gabriel Sanchez, Hüseyin Firat) responsible sample storage raw Karaduzovic-Hadziabdic wrote draft manuscript. supervised writing manuscript critically revised intellectual content. Firat Joanna Michel provided comments parts prepared figures tables. Alisia Madè, Simona Greco, Lina Badimon, Teresa Padro, Pedro Domingo, Timo Brandenburger, Guy Fagherazzi Markus Ollert participated acquiring approved version MA co-first author, together KK-H majority experiments other contributions noted above. order among cVo-first assigned contributions. thank their contribution: Claude Pelletier, Petr Nazarov, Adriana Voicu, Irina Carpusca, Eric Schordan, Rodwell Mkhwananzi, Stephanie Boutillier, Louis Chauviere, Chauviere Seval Kul, Florent Tessier, Reinhard Schneider, Belaur, Wei Gu, Enrico Petretto, Michaela Noseda, Verena Zuber, Leonardo Bottolo, Leon de Windt, Emma Robinson, George Valiotis, Tina Hadzic, Federica Margheri, Chiara Gonzi, Detlef Kindgen-Milles, Christian Vollmer, Thomas Dimski, Emin Tahirovic. thankful participants Predi-COVID acknowledge involvement interdisciplinary interinstitutional team contributed Predi-COVID. full list found here: https://sites.lih.lu/the-predi-covid-study/about-us/project-team/. would like COVID19_OMICS-COVIRNA, TOCOVID, studies. YD holds patents licensing agreements related therapeutic purposes (WO2018229046, licensed SA, protecting RNAseq paper; licenses not work). Scientific Advisory Board member PF founder CEO Pharmahungary Group, group R&D companies. LB declares acted SAB Sanofi, Ionnis, MSD NovoNordisk; received speaker fees Bayer AB-Biotics SA founded spin-off Ivastatin Therapeutics S.L. (all unrelated this TP co-founder Spin-off SL MS funding Pfizer Inc. Owkin projects research. HF owner company commercialising He targets. declare no competing interests. work supported EU Horizon awarded (grant agreement # 101016072). National Research Fund (FNR) (Predi-COVID, grant 14716273), André Losch Foundation Regional Development (FEDER, convention 2018-04-026-21). funded 101016072), (grants C14/BM/8225223, C17/BM/11613033 COVID-19/2020-1/14719577/miRCOVID), Ministry Higher Education Research, Heart Foundation-Daniel Wagner Luxembourg. FM Italian (Ricerca Corrente 2024 1.07.128, RF-2019-12368521 POS T4 CAL.HUB.RIA cod. T4-AN-09), #101016072, Next Generation PNRR M6C2 Inv. 2.1 PNRR-MAD-2022-12375790 PNRR/2022/C9/MCID/I8 FibroThera. Framework Programme 101016072, Fondation, Luxembourg, Ministero della Salute T4-AN-09, RF-2019-12368521, Ricerca Fonds la Recherche C17/BM/11613033, COVID-19/2020-1/14719577/miRCOVID, EU, FEDER, 2018-04-026-21, Ministère l'Education Nationale, l'Enseignement Superieur et code Supplementary File accessible GitHub repository link https://github.com/madilovic/COVIRNA_plasma ID: 118e2ccd07df8b10b7fc52df95ae11b52bb8216a. compliance Declaration Helsinki. comprising COVID-19-positive aged 18 years older (PrediCOVID study), (COVID19_OMICS—COVIRNA (TOCOVID (MiRCOVID study). Ethics Committee (study Number 202003/07) registered ClinicalTrials.gov (NCT04380987). COVID19_OMICS—COVIRNA Institutional San Raffaele Hospital (protocol 75/INT/2020, 20/04/2020 subsequent modification dated 16/12/2020) ID NCT04441502. Santa Creu i Sant Pau, Barcelona (Ref 21/036) (NCT04332094). Duesseldorf University (internal 2020−912) (NCT04381351). Periods enrolment biological collection PrediCOVID, 2021 2021. Informed consent signed enrolled Legal material sharing been coordinator Institute (LIH). Due legal ethical issues General Data Protection Regulation guidelines, upon request consortium. Please email corresponding author details information about access ([email protected]). note: publisher content functionality any supporting supplied authors. Any queries (other missing content) should directed article.

Language: Английский

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