Urinary and plasma metabolite differences detected by HPLC-ESI-QTOF-MS in systemic sclerosis patients

Fernández-Ochoa, Álvaro; Quirantes-Piné, Rosa; Borrás-Linares, Isabel; Gemperline, David C; Alarcón‐Riquelme, Marta E.; Beretta, Lorenzo; Segura‐Carretero, Antonio

doi:10.1016/j.jpba.2018.09.021

Cited by 31 publications

(38 citation statements)

References 24 publications

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“…Other differential metabolites in the majority of the models were acylcarnitines, unsaturated fatty acids (UFAs), and phospholipids. The dyregulation of these metabolites, mainly acylcarnitines and UFAs, are in line with previous research on a smaller number of volunteers [36], which gives consistency to the data obtained by both methodologies in this subset of samples.…”

Section: Multivariate Modelssupporting

confidence: 90%

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A Case Report of Switching from Specific Vendor-Based to R-Based Pipelines for Untargeted LC-MS Metabolomics

Fernández-Ochoa

Quirantes-Piné²,

Borrás-Linares³

et al. 2020

Metabolites

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Data pre-processing of the LC-MS data is a critical step in untargeted metabolomics studies in order to achieve correct biological interpretations. Several tools have been developed for pre-processing, and these can be classified into either commercial or open source software. This case report aims to compare two specific methodologies, Agilent Profinder vs. R pipeline, for a metabolomic study with a large number of samples. Specifically, 369 plasma samples were analyzed by HPLC-ESI-QTOF-MS. The collected data were pre-processed by both methodologies and later evaluated by several parameters (number of peaks, degree of missingness, quality of the peaks, degree of misalignments, and robustness in multivariate models). The vendor software was characterized by ease of use, friendly interface and good quality of the graphs. The open source methodology could more effectively correct the drifts due to between and within batch effects. In addition, the evaluated statistical methods achieved better classification results with higher parsimony for the open source methodology, indicating higher data quality. Although both methodologies have strengths and weaknesses, the open source methodology seems to be more appropriate for studies with a large number of samples mainly due to its higher capacity and versatility that allows combining different packages, functions, and methods in a single environment.

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Section: Multivariate Modelssupporting

confidence: 90%

“…Metabolites were separated using a reversed-phase C18 analytical column (Agilent Zorbax Eclipse Plus, 3.5 µm, 2.1 × 150 mm) and detected in positive-ion mode over a range from 50 to 1700 m/z. The analytical methodology is described in detail elsewhere [36].…”

Section: Datasetmentioning

confidence: 99%

A Case Report of Switching from Specific Vendor-Based to R-Based Pipelines for Untargeted LC-MS Metabolomics

Fernández-Ochoa

Quirantes-Piné²,

Borrás-Linares³

et al. 2020

Metabolites

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“…4 A major contribution to the study of scleroderma pathogenesis has been given by nextgeneration sequencing (NGS) techniques. [5][6][7] Gene expression profiling has long been used to understand the contribution of genes to biological functions and to discover deregulated pathways that may contribute to disease susceptibility. 5 6 8 The vast majority of gene expression studies in SSc are based on microarray technology, while NGS methods, namely RNA sequencing (RNA-seq), despite their advantages over existing approaches, have had limited applications.…”

Section: Introductionmentioning

confidence: 99%

Genome-wide whole blood transcriptome profiling in a large European cohort of systemic sclerosis patients

et al. 2020

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ObjectivesThe analysis of annotated transcripts from genome-wide expression studies may help to understand the pathogenesis of complex diseases, such as systemic sclerosis (SSc). We performed a whole blood (WB) transcriptome analysis on RNA collected in the context of the European PRECISESADS project, aiming at characterising the pathways that differentiate SSc from controls and that are reproducible in geographically diverse populations.MethodsSamples from 162 patients and 252 controls were collected in RNA stabilisers. Cases and controls were divided into a discovery (n=79+163; Southern Europe) and validation cohort (n=83+89; Central-Western Europe). RNA sequencing was performed by an Illumina assay. Functional annotations of Reactome pathways were performed with the Functional Analysis of Individual Microarray Expression (FAIME) algorithm. In parallel, immunophenotyping of 28 circulating cell populations was performed. We tested the presence of differentially expressed genes/pathways and the correlation between absolute cell counts and RNA transcripts/FAIME scores in regression models. Results significant in both populations were considered as replicated.ResultsOverall, 15 224 genes and 1277 functional pathways were available; of these, 99 and 225 were significant in both sets. Among replicated pathways, we found a deregulation in type-I interferon, Toll-like receptor cascade, tumour suppressor p53 protein function, platelet degranulation and activation. RNA transcripts or FAIME scores were jointly correlated with cell subtypes with strong geographical differences; neutrophils were the major determinant of gene expression in SSc-WB samples.ConclusionsWe discovered a set of differentially expressed genes/pathways validated in two independent sets of patients with SSc, highlighting a number of deregulated processes that have relevance for the pathogenesis of autoimmunity and SSc.

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“…Other groups, however, found no evidence of association between SSc and R620W polymorphism in Spanish, Columbian and French patients [314,315,316], and other variants (R263Q and G788A) were not identified as risk factors either [313,317]. On the other hand, comparison of plasma samples obtained from 59 Italian SSc patients and 28 age- and sex-matched healthy volunteers revealed an elevated 2-AG level in the plasma of SSc patients [318]. Although these data are definitely not more than mere indirect pointers indicating the putative involvement of eCB dysregulation in SSc, additional evidence suggests that certain cannabinoids may have therapeutic value in this disease [319,320].…”

Section: Translational Potential Of the Cutaneous Cannabinoid Signmentioning

confidence: 99%

Cannabinoid Signaling in the Skin: Therapeutic Potential of the “C(ut)annabinoid” System

et al. 2019

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The endocannabinoid system (ECS) has lately been proven to be an important, multifaceted homeostatic regulator, which influences a wide-variety of physiological processes all over the body. Its members, the endocannabinoids (eCBs; e.g., anandamide), the eCB-responsive receptors (e.g., CB1, CB2), as well as the complex enzyme and transporter apparatus involved in the metabolism of the ligands were shown to be expressed in several tissues, including the skin. Although the best studied functions over the ECS are related to the central nervous system and to immune processes, experimental efforts over the last two decades have unambiguously confirmed that cutaneous cannabinoid (“c[ut]annabinoid”) signaling is deeply involved in the maintenance of skin homeostasis, barrier formation and regeneration, and its dysregulation was implicated to contribute to several highly prevalent diseases and disorders, e.g., atopic dermatitis, psoriasis, scleroderma, acne, hair growth and pigmentation disorders, keratin diseases, various tumors, and itch. The current review aims to give an overview of the available skin-relevant endo- and phytocannabinoid literature with a special emphasis on the putative translational potential, and to highlight promising future research directions as well as existing challenges.

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Urinary and plasma metabolite differences detected by HPLC-ESI-QTOF-MS in systemic sclerosis patients

Cited by 31 publications

References 24 publications

A Case Report of Switching from Specific Vendor-Based to R-Based Pipelines for Untargeted LC-MS Metabolomics

A Case Report of Switching from Specific Vendor-Based to R-Based Pipelines for Untargeted LC-MS Metabolomics

Genome-wide whole blood transcriptome profiling in a large European cohort of systemic sclerosis patients

Cannabinoid Signaling in the Skin: Therapeutic Potential of the “C(ut)annabinoid” System

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