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Multiple biomarkers of sepsis identified by novel time-lapse proteomics of patient serum.

ABSTRACT: Serum components of sepsis patients vary with the severity of infection, the resulting inflammatory response, per individual, and even over time. Tracking these changes is crucial in properly treating sepsis. Hence, several blood-derived biomarkers have been studied for their potential in assessing sepsis severity. However, the classical approach of selecting individual biomarkers is problematic in terms of accuracy and efficiency. We therefore present a novel approach for detecting biomarkers using longitudinal proteomics data. This does not require a predetermined set of proteins and can therefore reveal previously unknown related proteins. Our approach involves examining changes over time of both protein abundance and post-translational modifications in serum, using two-dimensional gel electrophoresis (2D-PAGE). 2D-PAGE was conducted using serum from n = 20 patients, collected at five time points, starting from the onset of sepsis. Changes in protein spots were examined using 49 spots for which the signal intensity changed by at least two-fold over time. These were then screened for significant spikes or dips in intensity that occurred exclusively in patients with adverse outcome. Individual level variation was handled by a mixed effects model. Finally, for each time transition, partial correlations between spots were estimated through a Gaussian graphical model (GGM) based on the ridge penalty. Identifications of spots of interest by tandem mass spectrometry revealed that many were either known biomarkers for inflammation (complement components), or had previously been suggested as biomarkers for kidney failure (haptoglobin) or liver failure (ceruloplasmin). The latter two are common complications in severe sepsis. In the GGM, many of the tightly connected spots shared known biological functions or even belonged to the same protein; including hemoglobin chains and acute phase proteins. Altogether, these results suggest that our screening method can successfully identify biomarkers for disease states and cluster biologically related proteins using longitudinal proteomics data derived from 2D-PAGE.

SUBMITTER: Hayashi N

PROVIDER: S-EPMC6768476 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Multiple biomarkers of sepsis identified by novel time-lapse proteomics of patient serum.

Hayashi Nobuhiro N Yamaguchi Syunta S Rodenburg Frans F Ying Wong Sing S Ujimoto Kei K Miki Takahiro T Iba Toshiaki T

PloS one 20190930 9

Serum components of sepsis patients vary with the severity of infection, the resulting inflammatory response, per individual, and even over time. Tracking these changes is crucial in properly treating sepsis. Hence, several blood-derived biomarkers have been studied for their potential in assessing sepsis severity. However, the classical approach of selecting individual biomarkers is problematic in terms of accuracy and efficiency. We therefore present a novel approach for detecting biomarkers u ...[more]

PMID: 31568522

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Project description:Study questionCan time-lapse imaging systems make it possible to identify novel early non-invasive biomarkers to predict live birth?Summary answerFrom mostly high-grade embryos, out of 35 morphometric, morphologic and morphokinetic variables, only pronuclei (PN) position at time of PN juxtaposition and the absence of multinucleated blastomeres at the 2-cell stage (MNB2cell), were potentially associated with live birth.What is known alreadyPrevious studies indicate that some kinetic markers may be predictive of blastocyst development and embryonic implantation. Certain teams have suggested including some of them in decisional algorithms for embryo transfers.Study design, size, durationUsing a time-lapse incubator (EmbryoScope, Unisense FertiliTech), we retrospectively explored the associations between the morphometric, morphologic and morphokinetic parameters of oocytes, zygotes and embryos, and their associations with live birth. This study assessed 232 embryos from single embryo transfers after ICSI cycles performed between January 2014 and December 2017.Participants/materials, setting, methodsThe morphometric, morphologic and morphokinetic parameters (18, 4 and 13, respectively) of oocytes, zygotes and early embryos were studied retrospectively. The associations between these parameters were examined using a Spearman's correlation, Mann-Whitney or chi-squared test as appropriate. We examined whether these parameters were associated with outcomes in univariate and multivariate logistic regression analyses.Main results and the role of chanceCentral PN juxtaposition was associated with a 2-fold increase in the odds of live birth (OR = 2.20; 95% CI, [1.26-3.89]; P = 0.006), while the presence of MNB2cell was associated with half the odds of live birth (OR = 0.51; 95% CI, [0.27-0.95]; P = 0.035). These two parameters were independent of embryo kinetics. The 33 remaining parameters had no significant association with the capacity of transferred embryos to develop to term.Limitations, reasons for cautionEven though the population size was relatively small, our analyses were based on homogeneous cycles, i.e. young women whose transferred embryos were found to be high-grade according to conventional morphology evaluation. In addition, our conclusions were established from a specific, highly selected population, so other study populations, such as women in an older age bracket, may yield different results. Finally, because we assessed day 2/3 transfers, our findings cannot be generalized to embryos cultured up to the blastocyst stage.Wider implications of the findingsIt would be interesting to explore, prospectively, whether PN localisation is a relevant measure to predict embryo development when added into further algorithms and whether this parameter could be suitable for use in other IVF clinics. Further studies are needed, notably to explore the added value of timing evaluation in cohorts of embryos with low or intermediate morphology grade, as well as in other maternal populations (i.e. older women).Study funding/competing interest(s)No external funding was used for this study. P. Sagot received funding from the following commercial companies: Merck Serono, Finox Biotech, Ferring, MSD France SAS, Teva Sante ́ SAS, Allergan France, Gedeon Richter France, Effik S.A., Karl Storz Endoscopie France, GE Medical Systems SCS, Laboratoires Genevrier, H.A.C. Pharma and Ipsen.All the authors confirm that none of this funding was used to support the research in this study. There are no patents, products in development or marketed products to declare. This does not alter the authors' adherence to all the journal policies on sharing data and materials.

Project description:PurposeScleritis is an extremely painful and potentially blinding inflammation of the sclera with unknown pathogenesis and unpredictable course. To gain insight in its disease process and identify biomarker candidates, we performed extensive proteomics in serum and tear fluid.DesignProspective multicenter cohort study.ParticipantsA total of 121 patients with noninfectious scleritis (of which 39 active cases), 30 healthy controls, and 23 disease controls (uveitis and rheumatoid arthritis) were enrolled in the Netherlands from 2020 to 2022.MethodsSerum, tear fluid of both eyes, and clinical data were gathered. The level of 368 inflammatory proteins was measured using proximity extension assays. Results were validated in an independent cohort of 15 patients with scleritis, and using addressable laser bead immunoassay, or enzyme-linked immunoassays. In addition, we studied an extended panel of matrix metalloproteinases in tear fluid of necrotizing scleritis with addressable laser bead immunoassay.Main outcome measuresStatistically significant differences in the level of inflammatory proteins between patients with scleritis and control groups.ResultsProteomics revealed 18 significantly upregulated or downregulated serum proteins in active scleritis cases compared with all control groups in both the discovery cohort and the validation cohort. The most upregulated protein was nuclear migration protein nudC (NudC; P = 0.0032), a protein involved in neurogenesis. The other significant hits included proteins involved in T-cell activation, apoptosis, epithelial barrier maintenance, and angiogenesis. Our tear fluid analysis showed matrix metalloproteinase 9 (MMP9) to be upregulated in the tear fluid of patients with scleral necrosis.ConclusionsThe results of our proteomics analysis suggest a role for neurogenesis, T-cell activation, disruption of epithelial barrier, and angiogenesis in the pathogenesis of scleritis, and highlight MMP9 and NudC as biomarkers with potential clinical relevance.Funding disclosuresThe authors have no proprietary or commercial interest in any materials discussed in this article.

Project description:BackgroundOsteoarthritis (OA) is a slowly developing and debilitating disease, and there are no validated specific biomarkers for its early detection. To improve therapeutic approaches, identification of specific molecules/biomarkers enabling early determination of this disease is needed. This study aimed at identifying, with the use of proteomics/mass spectrometry, novel OA-specific serum biomarkers. As obesity is a major risk factor for OA, we discriminated obesity-regulated proteins to target only OA-specific proteins as biomarkers.MethodsSerum from the Osteoarthritis Initiative cohort was used and divided into 3 groups: controls (n=8), OA-obese (n=10) and OA-non-obese (n=10). Proteins were identified and quantified from the liquid chromatography-tandem mass spectrometry analyses using MaxQuant software. Statistical analysis used the Limma test followed by the Benjamini-Hochberg method. To compare the proteomic profiles, the multivariate unsupervised principal component analysis (PCA) followed by the pairwise comparison was used. To select the most predictive/discriminative features, the supervised linear classification model sparse partial least squares regression discriminant analysis (sPLS-DA) was employed. Validation of three differential proteins was performed with protein-specific assays using plasma from a cohort derived from the Newfoundland Osteoarthritis.ResultsIn total, 509 proteins were identified, and 279 proteins were quantified. PCA-pairwise differential comparisons between the 3 groups revealed that 8 proteins were differentially regulated between the OA-obese and/or OA-non-obese with controls. Further experiments using the sPLS-DA revealed two components discriminating OA from controls (component 1, 9 proteins), and OA-obese from OA-non-obese (component 2, 23 proteins). Proteins from component 2 were considered related to obesity. In component 1, compared to controls, 7 proteins were significantly upregulated by both OA groups and 2 by the OA-obese. Among upregulated proteins from both OA groups, some of them alone would not be a suitable choice as specific OA biomarkers due to their rather non-specific role or their strong link to other pathological conditions. Altogether, data revealed that the protein CRTAC1 appears to be a strong OA biomarker candidate. Other potential new biomarker candidates are the proteins FBN1, VDBP, and possibly SERPINF1. Validation experiments revealed statistical differences between controls and OA for FBN1 (p=0.044) and VDPB (p=0.022), and a trend for SERPINF1 (p=0.064).ConclusionOur study suggests that 4 proteins, CRTAC1, FBN1, VDBP, and possibly SERPINF1, warrant further investigation as potential new biomarker candidates for the whole OA population.

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Multiple biomarkers of sepsis identified by novel time-lapse proteomics of patient serum.

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Multiple biomarkers of sepsis identified by novel time-lapse proteomics of patient serum.

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