Measuring Serum Amyloid A for Infection Prediction in Aneurysmal Subarachnoid Hemorrhage

Improving prognostication of pneumonia among elderly patients: usefulness of suPAR

PURPOSE

Elderly patients with suspected pneumonia represent a significant proportion of hospital admissions, which is a prognostic challenge for physicians. Our research aimed to assess the prognosis of patients with pneumonia using soluble urokinase plasminogen activator receptor (suPAR) combined with clinical data.

METHODS

In a prospective observational study including 164 patients > 65 years (mean age 84.2 (+/-7.64) years) who were hospitalized for a suspicion of pneumonia, suPAR was assessed for each patient, as was the prognosis score (PSI, CURB65) and inflammatory biomarkers (C-reactive protein, procalcitonin, white blood cells). The prognostic value of the suPAR for 30-day mortality was assessed using receiver operating characteristic (ROC) curve analyses. Optimal cut-offs with corresponding sensitivity (SE) and specificity (SP) were determined using the Youden index.

RESULTS

A suPAR > 5.1 ng/mL was predictive of 30-day mortality with a sensitivity of 100% and a specificity of 40.4%. A combination of the following parameters exhibited an SE of 100% (95% CI, 100-100) for an SP value of 64.9% (95% CI, 57.6-72.2) when at least two of them were above or below the following cut-off threshold values: suPAR > 9.8 ng/mL, BMI < 29.3 kg/m2 and PSI > 106.5.

CONCLUSION

The suPAR seems to be a promising biomarker that can be combined with the PSI and BMI to improve the prognosis of pneumonia among elderly patients. Prospective studies with larger populations are needed to confirm whether this new approach can improve patient outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT02467192), 27th may 2015.

Kinetics of inflammatory biomarkers to predict one-year mortality in older patients hospitalized for pneumonia: a multivariable analysis

OBJECTIVES

Long-term mortality is increased in older patients with pneumonia. We aimed to test whether residual inflammation is predictive of one-year mortality after pneumonia.

METHODS

Inflammation biomarkers (C-reactive protein [CRP], interleukin [IL]-6 and IL-8, tumor necrosis factor-α, serum amyloid A, neopterin, myeloperoxidase, anti-apolipoprotein A-1, and anti-phosphorylcholine IgM) were measured at admission and discharge in older patients hospitalized for pneumonia in a prospective study. Univariate and multivariate analyses were conducted using absolute level at discharge and relative and absolute differences between admission and discharge for all biomarkers, along with usual prognostic factors.

RESULTS

In the 133 included patients (median age, 83 years [interquartile range: 78-89]), one-year mortality was 26%. In univariate analysis, the relative difference of CRP levels had the highest area under the receiver operating characteristic curve (0.70; 95% confidence interval [CI] 0.60-0.80). A decrease of CRP levels of more than 67% between admission and discharge had 68% sensitivity and 68% specificity to predict survival. In multivariate analysis, lower body mass index (hazard ratio=0.87 [CI 95% 0.79-0.96], P-value=0.01), higher IL-8 (hazard ratio=1.02 [CI 95% 1.00-1.04], P-value=0.02), and higher CRP (1.01 [95% CI 1.00-1.02], P=0.01) at discharge were independently associated with mortality.

CONCLUSION

Higher IL-8 and CRP levels at discharge were independently associated with one-year mortality. The relative CRP difference during hospitalization was the best individual biomarker for predicting one-year mortality.

High Neutrophil-to-Albumin Ratio Predicts Postoperative Pneumonia in Aneurysmal Subarachnoid Hemorrhage

Background and Aim

There is still an absence of objective and easily accessible biomarkers despite the variety of risk factors associated with postoperative pneumonia (POP) in patients with aneurysmal subarachnoid hemorrhage (aSAH). In the present study, we have thus evaluated the relationship between the neutrophil-to-albumin ratio (NAR) and POP in patients with aSAH.

Methods

Several consecutive patients (n = 395) who had undergone clipping or coiling of the aneurism were retrospectively assessed, of which we were able to analyze the existing population data and the related baseline variables. The patients were divided into POP and revealed not to occur. To identify independent predictors, we used the recipient operation feature (receiver operating characteristic, ROC) curve and a logic regression analysis.

Results

This cohort was based on POP that occurred in 78 out of the 395 patients (19.7%), and these revealed a significantly higher NAR than those without (0.31 [0.25–0.39] vs. 0.23 [0.18–0.28]; p &lt; 0.001). On the other hand, a multivariate logistic regression analysis showed that NAR (odds ratio = 1.907; 95% confidence interval, 1.232–2.953; p = 0.004) was independently associated with a POP after due adjustment for confounders. Moreover, the predictive performances of NAR for POP were also significant (area under the ROC curve [95% CI] 0.775 [0.717–0.832]; p &lt; 0.001).

Conclusion

The elevation of NAR at admission in patients with aSAH might help predict POP.

Role of Clinical Characteristics and Biomarkers at Admission to Predict One-Year Mortality in Elderly Patients with Pneumonia

BACKGROUND

A hospitalization for community-acquired pneumonia results in a decrease in long-term survival in elderly patients. We assessed biomarkers at admission to predict one-year mortality in a cohort of elderly patients with pneumonia.

METHODS

A prospective observational study included patients >65 years hospitalized with pneumonia. Assessment of PSI, CURB-65, and biomarkers (C-reactive protein (CRP), procalcitonin (PCT), NT-pro-B-type natriuretic peptide (NT-proBNP), interleukin (IL)-6 and -8, tumor necrosis factor alpha (TNF-α), serum amyloid A (SAA), neopterin (NP), myeloperoxidase (MPO), anti-apolipoprotein A-1 IgG (anti-apoA-1), and anti-phosphorylcholine IgM (anti-PC IgM)) was used to calculate prognostic values for one-year mortality using ROC curve analyses. Post hoc optimal cutoffs with corresponding sensitivity (SE) and specificity (SP) were determined using the Youden index.

RESULTS

A total of 133 patients were included (median age 83 years [IQR: 78-89]). Age, dementia, BMI, NT-proBNP (AUROC 0.65 (95% CI: 0.55-0.77)), and IL-8 (AUROC 0.66 (95% CI: 0.56-0.75)) were significantly associated with mortality, with NT-proBNP (HR 1.01 (95% CI 1.00-1.02) and BMI (HR 0.92 (95% CI 0.85-1.000) being independent of age, gender, comorbidities, and PSI with Cox regression. At the cutoff value of 2200 ng/L, NT-proBNP had 67% sensitivity and 70% specificity. PSI and CURB-65 were not associated with mortality.

CONCLUSIONS

NT-proBNP levels upon admission and BMI displayed the highest prognostic accuracy for one-year mortality and may help clinicians to identify patients with poor long-term prognosis.

A Panel Comprising Serum Amyloid A, White Blood Cells and Nihss for the Triage of Patients at Low Risk of Post-Stroke Infection

Accurate and early prediction of poststroke infections is important to improve antibiotic therapy guidance and/or to avoid unnecessary antibiotic treatment. We hypothesized that the combination of blood biomarkers with clinical parameters could help to optimize risk stratification during hospitalization. In this prospective observational study, blood samples of 283 ischemic stroke patients were collected at hospital admission within 72 h from symptom onset. Among the 283 included patients, 60 developed an infection during the first five days of hospitalization. Performance predictions of blood biomarkers (Serum Amyloid-A (SAA), C-reactive protein, procalcitonin (CRP), white blood cells (WBC), creatinine) and clinical parameters (National Institutes of Health Stroke Scale (NIHSS), age, temperature) for the detection of poststroke infection were evaluated individually using receiver operating characteristics curves. Three machine learning techniques were used for creating panels: Associative Rules Mining, Decision Trees and an internal iterative-threshold based method called PanelomiX. The PanelomiX algorithm showed stable performance when applied to two representative subgroups obtained as splits of the main subgroup. The panel including SAA, WBC and NIHSS had a sensitivity of 97% and a specificity of 45% to identify patients who did not develop an infection. Therefore, it could be used at hospital admission to avoid unnecessary antibiotic (AB) treatment in around half of the patients, and consequently, to reduce AB resistance.

Neutrophil to lymphocyte ratio is a prognosis factor for post-operative pneumonia in aneurysmal subarachnoid hemorrhage patients

Background:

Although a variety of risk factors of pneumonia after clipping or coiling of the aneurysm (post-operative pneumonia [POP]) in patients with aneurysmal subarachnoid hemorrhage (aSAH) have been studied, the predictive model of POP after aSAH has still not been well established. Thus, the aim of this study was to assess the feasibility of using admission neutrophil to lymphocyte ratio (NLR) to predict the occurrence of POP in aSAH patients.

Methods:

We evaluated 711 aSAH patients who were enrolled in a prospective observational study and collected admission blood cell counts data. We analyzed available demographics and baseline variables for these patients and analyzed the correlation of these factors with POP using Cox regression. After screening out the prognosis-related factors, the predictive value of these factors for POP was further assessed.

Results:

POP occurred in 219 patients (30.4%) in this cohort. Patients with POP had significantly higher NLR than those without (14.11 ± 8.90 vs. 8.80 ± 5.82, P < 0.001). Multivariate analysis revealed that NLR remained a significant factor independently associated with POP following aSAH after adjusting for possible confounding factors, including the age, World Federation of Neurosurgical Societies (WFNS) grade, endovascular treatment, and ventilator use. And the predictive value of NLR was significantly increased after WFNS grade was combined with NLR (NLR vs. WFNS grade × NLR, P = 0.011).

Conclusions:

Regardless of good or poor WNFS grade, patients having NLR >10 had significantly worse POP survival rate than patients having NLR ≤10. NLR at admission might be helpful as a predictor of POP in aSAH patients.

SAA (Serum Amyloid A): A Novel Predictor of Stroke-Associated Infections

BACKGROUND AND PURPOSE

The aim of this study was to evaluate and independently validate SAA (serum amyloid A)-a recently discovered blood biomarker-to predict poststroke infections.

METHODS

The derivation cohort (A) was composed of 283 acute ischemic stroke patients and the independent validation cohort (B), of 367 patients. The primary outcome measure was any stroke-associated infection, defined by the criteria of the US Centers for Disease Control and Prevention, occurring during hospitalization. To determine the association of SAA levels on admission with the development of infections, logistic regression models were calculated. The discriminatory ability of SAA was assessed, by calculating the area under the receiver operating characteristic curve.

RESULTS

After adjusting for all predictors that were significantly associated with any infection in the univariate analysis, SAA remained an independent predictor in study A (adjusted odds ratio, 1.44 [95% CI, 1.16-1.79]; P=0.001) and in study B (adjusted odds ratio, 1.52 [1.05-2.22]; P=0.028). Adding SAA to the best regression model without the biomarker, the discriminatory accuracy improved from 0.76 (0.69-0.83) to 0.79 (0.72-0.86; P<0.001; likelihood ratio test) in study A. These results were externally validated in study B with an improvement in the area under the receiver operating characteristic curve, from 0.75 (0.70-0.81) to 0.76 (0.71-0.82; P<0.038).

CONCLUSIONS

Among patients with ischemic stroke, blood SAA measured on admission is a novel independent predictor of infection after stroke. SAA improved the discrimination between patients who developed an infection compared with those who did not in both derivation and validation cohorts. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00390962.

Admission Levels of Interleukin 10 and Amyloid β 1-40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury

Background: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI).

Objective: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI.

Materials and methods: Eighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1–40 (Aβ40) and 1–42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale—Extended 5–8, n = 49) and unfavorable (Glasgow Outcome Scale—Extended 1–4, n = 33) groups. The outcome was assessed 6–12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90–100%.

Results: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9–100) and specificity of 22.4% (95% CI: 10.2–32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1–4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7–6.2) with a sensitivity of 90.9% (95% CI: 81.8–100) and specificity of 59.2% (95% CI: 40.8–69.4).

Conclusion: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI.

Accuracy of C-reactive protein, procalcitonin, serum amyloid A and neopterin for low-dose CT-scan confirmed pneumonia in elderly patients: A prospective cohort study

Objective

The diagnosis of pneumonia based on semiology and chest X-rays is frequently inaccurate, particularly in elderly patients. Older (C-reactive protein (CRP); procalcitonin (PCT)) or newer (Serum amyloid A (SAA); neopterin (NP)) biomarkers may increase the accuracy of pneumonia diagnosis, but data are scarce and conflicting. We assessed the accuracy of CRP, PCT, SAA, NP and the ratios CRP/NP and SAA/NP in a prospective observational cohort of elderly patients with suspected pneumonia.

Methods

We included consecutive patients more than 65 years old, with at least one respiratory symptom and one symptom or laboratory finding suggestive of infection, and a working diagnosis of pneumonia. Low-dose CT scan and comprehensive microbiological testing were done in all patients. The index tests, CRP, PCT, SAA and NP, were obtained within 24 hours. The reference diagnosis was assessed a posteriori by a panel of experts considering all available data, including patients’ outcome. We used area under the curve (AUROC) and Youden index to assess the accuracy and obtain optimal cut-off of the index tests.

Results

200 patients (median age 84 years) were included; 133 (67%) had pneumonia. AUROCs for the diagnosis of pneumonia was 0.64 (95% CI: 0.56–0.72) for CRP; 0.59 (95% CI: 0.51–0.68) for PCT; 0.60 (95% CI: 0.52–0.69) for SAA; 0.41 (95% CI: 0.32–0.49) for NP; 0.63 (95% CI: 0.55–0.71) for CRP/NP; and 0.61 (95% CI: 0.53–0.70) for SAA/NP. No cut-off resulted in satisfactory sensitivity or specificity.

Conclusions

Accuracy of traditional (CRP, PCT) and newly proposed biomarkers (SAA, NP) and ratios of CRP/NP and SAA/NP was too low to help diagnosing pneumonia in the elderly. CRP had the highest AUROC.

Clinical Trial Registration

NCT 02467092

Progress and pitfalls of using isobaric mass tags for proteome profiling

Introduction: Quantitative proteomics using mass spectrometry is performed via label-free or label-based approaches. Labeling strategies rely on the incorporation of stable heavy isotopes by metabolic, enzymatic, or chemical routes. Isobaric labeling uses chemical labels of identical masses but of different fragmentation behaviors to allow the relative quantitative comparison of peptide/protein abundances between biological samples.Areas covered: We have carried out a systematic review on the use of isobaric mass tags in proteomic research since their inception in 2003. We focused on their quantitative performances, their multiplexing evolution, as well as their broad use for relative quantification of proteins in pre-clinical models and clinical studies. Current limitations, primarily linked to the quantitative ratio distortion, as well as state-of-the-art and emerging solutions to improve their quantitative readouts are discussed.Expert opinion: The isobaric mass tag technology offers a unique opportunity to compare multiple protein samples simultaneously, allowing higher sample throughput and internal relative quantification for improved trueness and precision. Large studies can be performed when shared reference samples are introduced in multiple experiments. The technology is well suited for proteome profiling in the context of proteomic discovery studies.

Innate immunity activation in the early brain injury period following subarachnoid hemorrhage

Background

Aneurysmal subarachnoid hemorrhage (SAH) is a catastrophic disease with devastating consequences, including a high mortality rate and severe disabilities among survivors. Inflammation is induced following SAH, but the exact role and phenotype of innate immune cells remain poorly characterized. We investigated the inflammatory components of the early brain injury in an animal model and in SAH patients.

Method

SAH was induced through injection of blood in the subarachnoid space of C57Bl/6 J wild-type mice. Prospective blood collections were obtained at 12 h, days 1, 2, and 7 to evaluate the systemic inflammatory consequences of SAH by flow cytometry and enzyme-linked immunosorbent-assay (ELISA). Brains were collected, enzymatically digested, or fixed to characterize infiltrating inflammatory cells and neuronal death using flow cytometry and immunofluorescence. Phenotypic evaluation was performed at day 7 using the holding time and footprint tests. We then compared the identified inflammatory proteins to the profiles obtained from the plasma of 13 human SAH patients.

Results

Following SAH, systemic IL-6 levels increased rapidly, whereas IL-10 levels were reduced. Neutrophils were increased both in the brain and in the blood reflecting local and peripheral inflammation following SAH. More intracerebral pro-inflammatory monocytes were found at early time points. Astrocyte and microglia activation were also increased, and mice had severe motor deficits, which were associated with an increase in the percentage of caspase-3-positive apoptotic neurons. Similarly, we found that IL-6 levels in patients were rapidly increased following SAH. ICAM-1, bFGF, IL-7, IL-12p40, and MCP-4 variations over time were different between SAH patients with good versus bad outcomes. Moreover, high levels of Flt-1 and VEGF at admission were associated with worse outcomes.

Conclusion

SAH induces an early intracerebral infiltration and peripheral activation of innate immune cells. Furthermore, microglia and astrocytic activation are present at later time points. Our human and mouse data illustrate that SAH is a systemic inflammatory disease and that immune cells represent potential therapeutic targets to help this population of patients in need of new treatments.

Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.

Proteome and Metabolome of Subretinal Fluid in Central Serous Chorioretinopathy and Rhegmatogenous Retinal Detachment: A Pilot Case Study

PURPOSE

To investigate the molecular composition of subretinal fluid (SRF) in central serous chorioretinopathy (CSCR) and rhegmatogenous retinal detachment (RRD) using proteomics and metabolomics.

METHODS

SRF was obtained from one patient with severe nonresolving bullous CSCR requiring surgical subretinal fibrin removal, and two patients with long-standing RRD. Proteins were trypsin-digested, labeled with Tandem-Mass-Tag and fractionated according to their isoelectric point for identification and quantification by tandem mass spectrometry. Independently, metabolites were extracted on cold methanol/ethanol, and identified by untargeted ultra-high performance liquid chromatography and high-resolution mass spectrometry. Bioinformatics analyses were conducted.

RESULTS

In total, 291 proteins and 651 metabolites were identified in SRF samples. Compared with RRD, 128 proteins (77 downregulated; 51 upregulated) and 76 metabolites (43 downregulated; 33 upregulated) differed in the SRF from CSCR. Protein and metabolites notably deregulated in CSCR were related to glycolysis/gluconeogenesis, inflammation (including serum amyloid P component, versican), alternative complement pathway (complement factor H and complement factor H-related protein), cellular adhesion, biliary acid metabolism (farnesoid X receptor/retinoid X receptor), and gluco- and mineralocorticoid systems (aldosterone, angiotensin, and corticosteroid-binding globulin).

CONCLUSIONS

Proteomics and metabolomics can be performed on SRF. A unique SRF sample from CSCR exhibited a distinct molecular profile compared with RRD.

TRANSLATIONAL RELEVANCE

This first comparative multiomics analysis of SRF improved the understanding of CSCR and RRD pathophysiology. It identified pathways potentially involved in the better photoreceptor preservation in CSCR, suggesting neuroprotective targets that will require additional confirmation.

Proteomic discovery and verification of serum amyloid A as a predictor marker of patients at risk of post-stroke infection: a pilot study

Background

Post-stroke infections occur in 20–36% of stroke patients and are associated with high morbidity and mortality rates. Early identification of patients at risk of developing an infection could improve care via an earlier treatment leading to a better outcome. We used proteomic tools in order to discover biomarkers able to stratify patients at risk of post-stroke infection.

Methods

The post hoc analysis of a prospective cohort study including 40 ischemic stroke patients included 21 infected and 19 non-infected participants. A quantitative, isobaric labeling, proteomic strategy was applied to the plasma samples of 5 infected and 5 non-infected patients in order to highlight any significantly modulated proteins. A parallel reaction monitoring (PRM) assay was applied to 20 additional patients (10 infected and 10 non-infected) to verify discovery results. The most promising protein was pre-validated using an ELISA immunoassay on 40 patients and at different time points after stroke onset.

Results

Tandem mass analysis identified 266 proteins, of which only serum amyloid A (SAA1/2) was significantly (p = 0.007) regulated between the two groups of patients. This acute-phase protein appeared to be 2.2 times more abundant in infected patients than in non-infected ones. These results were verified and validated using PRM and ELISA immunoassays, which showed that infected patients had significantly higher concentrations of SAA1/2 than non-infected patients at hospital admission, but also at 1, 3, and 5 days after admission.

Conclusions

The present study demonstrated that SAA1/2 is a promising predictor, at hospital admission, of stroke patients at risk of developing an infection. Further large, multicenter validation studies are needed to confirm these results. If confirmed, SAA1/2 concentrations could be used to identify the patients most at risk of post-stroke infections and therefore implement treatments more rapidly, thus reducing mortality.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-017-9162-0) contains supplementary material, which is available to authorized users.

Principles of precision medicine in stroke

The era of precision medicine has arrived and conveys tremendous potential, particularly for stroke neurology. The diagnosis of stroke, its underlying aetiology, theranostic strategies, recurrence risk and path to recovery are populated by a series of highly individualised questions. Moreover, the phenotypic complexity of a clinical diagnosis of stroke makes a simple genetic risk assessment only partially informative on an individual basis. The guiding principles of precision medicine in stroke underscore the need to identify, value, organise and analyse the multitude of variables obtained from each individual to generate a precise approach to optimise cerebrovascular health. Existing data may be leveraged with novel technologies, informatics and practical clinical paradigms to apply these principles in stroke and realise the promise of precision medicine. Importantly, precision medicine in stroke will only be realised once efforts to collect, value and synthesise the wealth of data collected in clinical trials and routine care starts. Stroke theranostics, the ultimate vision of synchronising tailored therapeutic strategies based on specific diagnostic data, demand cerebrovascular expertise on big data approaches to clinically relevant paradigms. This review considers such challenges and delineates the principles on a roadmap for rational application of precision medicine to stroke and cerebrovascular health.

Effect of intraoral mechanical stress application on the expression of a force-responsive prognostic marker associated with system disease progression

OBJECTIVES

Malocclusion may be corrected nonsurgically by mechanical tooth movement. The plasma protein profiles of human subjects receiving the first phase of orthodontic treatment were examined to test the hypothesis that application of mechanical stresses to teeth induces systemic proteomic alterations.

METHODS

Tandem mass tag-based liquid chromatography-mass spectrometry (LC-MS/MS) was used to examine systemic proteomic alterations in subjects undergoing controlled stress application (N=10) and in volunteers not receiving treatment (N=7) at 3 time intervals within 24h. Proteins differentially expressed by the tooth movement group were functionally analyzed with "Gene Ontology" (GO) and "Search Tool to Retrieve Interacting Genes/proteins" (STRING) softwares. Enzyme-Linked Immunosorbent Assay and Western-blot were used to validate the in vivo protein alterations. An in vitro model consisting of human periodontal ligament cells (hPDLCs) under compression was used to validate the force-responsive characteristics of galectin-3 binding protein (LGALS3BP).

RESULTS

Sixteen out of the 294 proteins identified by LC-MS/MS were differentially expressed in the plasma of subjects receiving controlled mechanical stresses for moving teeth. Those proteins were clustered in biological processes related to acute inflammatory response and vesicle-related transportation. Serotransferrin, fibronectin and LGALS3BP were processed for confirmation in vivo; LGALS3BP was significantly increased in the tooth movement group. In vitro secretion of LGALS3BP in PDLCs was force-responsive.

CONCLUSIONS

Regional application of mechanical stresses stimulates systemic proteomic changes. Because serum LGALS3BP is over-expressed in different systemic diseases, including cancer, further work is needed to examine how systemic up-regulation of LGALS3BP affects the progression of those diseases.

Measuring Serum Amyloid A for Infection Prediction in Aneurysmal Subarachnoid Hemorrhage

Aneurysmal subarachnoid hemorrhage (aSAH) is associated with high rates of mortality and morbidity. Nosocomial infections, such as pneumonia or urinary tract infections, are among the main causes of worsening outcomes and death. The aim of this study was to discover a biomarker to predict infection in aSAH patients. For this purpose, the plasma of infected and noninfected patients was compared using quantitative mass spectrometry. The most interesting differentially expressed proteins were selected for validation by immunoassays on plasma samples taken from patients (n = 81) over 10 days of hospitalization. Predictive performances were established using Mann-Whitney U tests and receiver operating characteristic curves. Quantitative proteomics identified 17 significantly regulated proteins. Of these, levels of serum amyloid A (SAA) were significantly higher in infected patients (p < 0.007). ELISA confirmed that the concentrations were significantly higher (p < 0.002) already at hospital admission in patients who subsequently developed an infection during their hospitalization, (AUC of 76%) for a cutoff value of 90.9 μg/mL. Our data suggested that measuring SAA could be an efficient means of detecting patients susceptible of developing an infection during hospitalization after an aSAH. Its predictive capacity could lead to earlier antibiotherapy, improved patient management, and potentially better long-term outcomes.