PLS2 in Metabolomics

Stocchero, Matteo; Locci, Emanuela; d’Aloja, Ernesto; Nioi, Matteo; Baraldi, Eugenio; Giordano, Giuseppe

doi:10.3390/metabo9030051

Cited by 26 publications

(20 citation statements)

References 39 publications

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“…Multivariate data analysis was performed using projection methods. Specifically, Principal component analysis (PCA) was applied for outlier detection, while differences in the metabolic profiles of urine or plasma samples were investigated using projection to latent structures discriminant analysis (PLS–DA) with stability selection [ 29 , 44 ]. Class membership was assessed by applying linear discriminant analysis to the scores of the PLS–DA model built autoscaling the dummy variables specifying the class of the sample.…”

Section: Methodsmentioning

confidence: 99%

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Untargeted and Targeted Metabolomic Profiling of Preterm Newborns with EarlyOnset Sepsis: A Case-Control Study

et al. 2021

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Sepsis is a major concern in neonatology, but there are no reliable biomarkers for its early diagnosis. The aim of the study was to compare the metabolic profiles of plasma and urine samples collected at birth from preterm neonates with and without earlyonset sepsis (EOS) to identify metabolic perturbations that might orient the search for new early biomarkers. All preterm newborns admitted to the neonatal intensive care unit were eligible for this proof-of-concept, prospective case-control study. Infants were enrolled as “cases” if they developed EOS, and as “controls”if they did not. Plasma samples collected at birth and urine samples collected within 24 h of birth underwent untargeted and targeted metabolomic analysis using mass spectrometry coupled with ultra-performance liquid chromatography. Univariate and multivariate statistical analyses were applied. Of 123 eligible newborns, 15 developed EOS. These 15 newborns matched controls for gestational age and weight. Metabolomic analysis revealed evident clustering of the cases versus controls, with the glutathione and tryptophan metabolic pathways markedly disrupted in the former. In conclusion, neonates with EOS had a metabolic profile at birth that clearly distinguished them from those without sepsis, and metabolites of glutathione and tryptophan pathways are promising as new biomarkers of neonatal sepsis.

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Section: Methodsmentioning

confidence: 99%

“…Samples from cases of sepsis are indicated with black circles, those from controls with light grey circles; panel ( A ) NEG data set; panel ( B ) POS data set. The PLS–DA models have been post-transformed to obtain the predictive latent variable tp and the non-predictive latent variable to [ 29 ].…”

Section: Figurementioning

confidence: 99%

Untargeted and Targeted Metabolomic Profiling of Preterm Newborns with EarlyOnset Sepsis: A Case-Control Study

et al. 2021

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“…Five-fold cross-validation and permutation test on the class (1000 random permutations) were applied to check over-fitting. PLS-DA models were post-transformed to simplify model interpretation [ 46 ].…”

Section: Methodsmentioning

confidence: 99%

Breathomics in Asthmatic Children Treated with Inhaled Corticosteroids

et al. 2020

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Background: “breathomics” enables indirect analysis of metabolic patterns underlying a respiratory disease. In this study, we analyze exhaled breath condensate (EBC) in asthmatic children before (T0) and after (T1) a three-week course of inhaled beclomethasone dipropionate (BDP). Methods: we recruited steroid-naive asthmatic children for whom inhaled steroids were indicated and healthy children, evaluating asthma control, spirometry and EBC (in asthmatics at T0 and T1). A liquid-chromatography–mass-spectrometry untargeted analysis was applied to EBC and a mass spectrometry-based target analysis to urine samples. Results: metabolomic analysis discriminated asthmatic (n = 26) from healthy children (n = 16) at T0 and T1, discovering 108 and 65 features relevant for the discrimination, respectively. Searching metabolomics databases, seven putative biomarkers with a plausible role in asthma biochemical–metabolic processes were found. After BDP treatment, asthmatic children, in the face of an improved asthma control (p < 0.001) and lung function (p = 0.01), showed neither changes in EBC metabolomic profile nor in urinary endogenous steroid profile. Conclusions: “breathomics” can discriminate asthmatic from healthy children, with prostaglandin, fatty acid and glycerophospholipid as putative markers. The three-week course of BDP—in spite of a significant clinical improvement—was not associated with changes in EBC metabolic arrangement and urinary steroid profile.

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“…PCA techniques make it possible to extract analytical information from chromatograms or spectra of samples to identify similarities and differences among highly complex datasets. PLS is one of the most popular calibration methods, which is based on determining the linear relationship between the independent dataset of measurement X (such as peak, absorbance values, fingerprint, spectra, or peak area from the detected metabolites) and the dependent set of variable Y (biological activity) in order to predict the bioactive compounds [ 13 , 14 , 15 ]. For the first time, we have performed metabolomics analysis using FTIR and UHPLC-Q-Orbitrap HRMS to identify major functional groups and metabolites in the two Curculigo spp.…”

Section: Introductionmentioning

confidence: 99%

Untargeted Metabolomics Analysis Using FTIR and UHPLC-Q-Orbitrap HRMS of Two Curculigo Species and Evaluation of Their Antioxidant and α-Glucosidase Inhibitory Activities

et al. 2021

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Curculigo orchioides and C. latifolia have been used as traditional medicines such as antidiabetic and anticancer. This study measured the total phenolics and flavonoid contents as well as analyzed the functional groups and chemical compounds using Fourier-transform infrared (FTIR) spectra and UHPLC-Q-Orbitrap-HRMS profiling for the discrimination of plant parts, geographical origin, and compounds that presumably have a significant contribution as antioxidant and α-glucosidase inhibitors on both plants. The total phenolics and flavonoids contents in Curculigo species varied from 142.09 to 452.47 mg gallic acid equivalent (GAE/g) and from 0.82 to 5.44 mg quercetin equivalent (QE/g), respectively. The lowest IC50 for antioxidant and α-glucosidase inhibitory activities is presented by C. latifolia from a higher altitude region. Principal component analysis (PCA) from FTIR and UHPLC-Q-Orbitrap-HRMS data could discriminate the plant parts and geographical origin. Partial least squares (PLS) analysis has identified several functional groups, such as O–H, C–H, C=O, C–C, C–O, and chemical compounds, unknown-185 and unknown-85, that are most likely to contribute to the antioxidant and α-glucosidase inhibitory activities.

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PLS2 in Metabolomics

Cited by 26 publications

References 39 publications

Untargeted and Targeted Metabolomic Profiling of Preterm Newborns with EarlyOnset Sepsis: A Case-Control Study

Untargeted and Targeted Metabolomic Profiling of Preterm Newborns with EarlyOnset Sepsis: A Case-Control Study

Breathomics in Asthmatic Children Treated with Inhaled Corticosteroids

Untargeted Metabolomics Analysis Using FTIR and UHPLC-Q-Orbitrap HRMS of Two Curculigo Species and Evaluation of Their Antioxidant and α-Glucosidase Inhibitory Activities

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