The Future of Biomarkers

Plasma Connective Tissue Growth Factor as a Biomarker of Pulmonary Arterial Hypertension Associated With Congenital Heart Disease in Adults

BACKGROUND

Connective tissue growth factor (CTGF) has diagnostic value for pulmonary arterial hypertension (PAH) associated with congenital heart disease (CHD) in children; however, its value in adult patients remains unclear. This study evaluated CTGF as a biomarker in adult PAH-CHD patients.Methods and Results: Based on mean pulmonary artery pressure (mPAP), 56 CHD patients were divided into 3 groups: without PAH (W; mPAP <25 mmHg; n=28); mild PAH (M; mPAP 25-35 mmHg; n=18); and moderate and severe PAH (H; mPAP ≥35 mmHg; n=10). The control group consisted of 28 healthy adults. Plasma CTGF and B-type natriuretic peptide (BNP) concentrations were determined. Plasma CTGF concentrations were higher in the H and M groups than in the W and control groups, and were higher in the H than M group. Plasma CTGF concentrations were positively correlated with pulmonary artery systolic pressure (PASP), mPAP, and pulmonary vascular resistance, and negatively correlated with mixed venous oxygen saturation. CTGF, BNP, red blood cell distribution width, and World Health Organization Class III/IV were risk factors for PAH in CHD patients, and CTGF was an independent risk factor for PAH-CHD. The efficacy of CTGF in the diagnosis of PAH was not inferior to that of BNP.

CONCLUSIONS

CTGF is a biomarker of PAH associated with CHD. It can be used for early diagnosis and severity assessment in adult patients with CHD-PAH.

Biomarkers as Prognostic Predictors and Therapeutic Guide in Critically Ill Patients: Clinical Evidence

A biomarker is a molecule that can be measured in a biological sample in an objective, systematic, and precise way, whose levels indicate whether a process is normal or pathological. Knowing the most important biomarkers and their characteristics is the key to precision medicine in intensive and perioperative care. Biomarkers can be used to diagnose, in assessment of disease severity, to stratify risk, to predict and guide clinical decisions, and to guide treatments and response to them. In this review, we will analyze what characteristics a biomarker should have and how to ensure its usefulness, and we will review the biomarkers that in our opinion can make their knowledge more useful to the reader in their clinical practice, with a future perspective. These biomarkers, in our opinion, are lactate, C-Reactive Protein, Troponins T and I, Brain Natriuretic Peptides, Procalcitonin, MR-ProAdrenomedullin and BioAdrenomedullin, Neutrophil/lymphocyte ratio and lymphopenia, Proenkephalin, NefroCheck, Neutrophil gelatinase-associated lipocalin (NGAL), Interleukin 6, Urokinase-type soluble plasminogen activator receptor (suPAR), Presepsin, Pancreatic Stone Protein (PSP), and Dipeptidyl peptidase 3 (DPP3). Finally, we propose an approach to the perioperative evaluation of high-risk patients and critically ill patients in the Intensive Care Unit (ICU) based on biomarkers.

Diagnosis by Volatile Organic Compounds in Exhaled Breath in Exhaled Breath from Patients with Gastric and Colorectal Cancers

One in three cancer deaths worldwide are caused by gastric and colorectal cancer malignancies. Although the incidence and fatality rates differ significantly from country to country, the rates of these cancers in East Asian nations such as South Korea and Japan have been increasing each year. Above all, the biggest danger of this disease is how challenging it is to recognize in its early stages. Moreover, most patients with these cancers do not present with any disease symptoms before receiving a definitive diagnosis. Currently, volatile organic compounds (VOCs) are being used for the early prediction of several other diseases, and research has been carried out on these applications. Exhaled VOCs from patients possess remarkable potential as novel biomarkers, and their analysis could be transformative in the prevention and early diagnosis of colon and stomach cancers. VOCs have been spotlighted in recent studies due to their ease of use. Diagnosis on the basis of patient VOC analysis takes less time than methods using gas chromatography, and results in the literature demonstrate that it is possible to determine whether a patient has certain diseases by using organic compounds in their breath as indicators. This study describes how VOCs can be used to precisely detect cancers; as more data are accumulated, the accuracy of this method will increase, and it can be applied in more fields.

Synthesis of novel benzothiophene derivatives as protectors against cranial irradiation-induced neuroinflammation

Aim: Cranial irradiation results in many deleterious effects to normal tissues, including neuroinflammation. There is a need to explore radioprotective agents that could be safely used to ameliorate these effects. Method: Nine novel benzothiophene derivatives bearing pyrimidinone, pyrazolidinone, triazole and other active moieties were synthesized and evaluated as antioxidants in an in vitro screening experiment. The most potent compounds were then tested as protectors against radiation-induced neuroinflammation and oxidative stress in rat brains following cranial irradiation. Results: The most potent antioxidant compounds were compounds 3–5 and 10 . P-fluro,p- bromo and pyrido benzothiophene derivatives offered good antioxidant and anti-inflammatory effects. Conclusion: Compounds 3–5 may be introduced as nontoxic candidates for adjuvant therapeutic protocols used in head and neck tumor radiotherapeutic management.

Serum kisspeptin and proopiomelanocortin in cystic fibrosis: a single study

The determination of hormonal biomarkers is of increasing interest in many diseases, including cystic fibrosis (CF). Hormones that have not been estimated and described so far in CF include kisspeptin (KISS) and proopiomelanocortin (POMC), which are involved in the regulation of many processes, including appetite and fertility. Therefore, the aim of our study was to estimate the level of KISS and POMC in sera from CF patients and to determine the correlation between these hormones and clinical parameters. For this purpose, we estimated the levels of KISS and POMC in 38 CF patients and 16 healthy participants with enzyme-linked immunosorbent assay. We found significantly reduced levels of KISS and POMC in people with CF compared to healthy subjects (1.76 ± 0.46 vs. 2.27 ± 0.56 ng/mL, p < 0.05 and 6.25 ± 4.36 vs. 14.74 ± 6.24 ng/mL, p < 0.001, respectively). Furthermore, the level of both hormones was negatively correlated with age. The hormones studied did not correlate with the results of spirometry and each other. Thus, decreased KISS and POMC levels may be associated with lower body weight and delayed puberty in patients with CF.

Novel Applications of Biomarkers in Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is an important health problem and an increasing cause of morbidity and mortality worldwide. Currently, COPD is considered a multisystem disease. Although it primarily affects the lungs, structural and functional changes occur in other organs due to systemic inflammation. It is stated that in patients with COPD, airway and systemic inflammatory markers are increased and that these markers are high are associated with a faster decline in lung functions. In recent years, numerous articles have been published on the discovery and evaluation of biomarkers in COPD. Many markers have also been studied to accurately assess COPD exacerbations and provide effective treatment. However, based on the evidence from published studies, a single molecule has not been adequately validated for broad clinical use.

Integrative analysis of DNA methylation and gene expression data for the diagnosis and underlying mechanism of Parkinson’s disease

Background

Parkinson’s disease (PD) is the second most common progressive neurodegenerative disorder and the leading cause of disability in the daily activities. In the management of PD, accurate and specific biomarkers in blood for the early diagnosis of PD are urgently needed. DNA methylation is one of the main epigenetic mechanisms and associated with the gene expression and disease initiation of PD. We aimed to construct a methylation signature for the diagnosis of PD patients, and explore the potential value of DNA methylation in therapeutic options.

Materials and methods

Whole blood DNA methylation and gene expression data of PD patients as well as healthy controls were extracted from Gene Expression Omnibus database. Next, differentially expressed genes (DEGs) and differentially methylated genes (DMGs) between PD patients and healthy controls were identified. Least absolute shrinkage and selection operator cox regression analysis was carried out to construct a diagnostic signature based on the overlapped genes. And, the receiver operating characteristic (ROC) curves were drawn and the area under the curve (AUC) was used to assess the diagnostic performance of the signature in both the training and testing datasets. Finally, gene ontology and gene set enrichment analysis were subsequently carried out to explore the underlying mechanisms.

Results

We obtained a total of 9,596 DMGs, 1,058 DEGs, and 237 overlapped genes in the whole blood between PD patients and healthy controls. Eight methylation-driven genes (HIST1H4L, CDC42EP3, KIT, GNLY, SLC22A1, GCM1, INO80B, and ARHGAP26) were identified to construct the gene expression signature. The AUCs in predicting PD patients were 0.84 and 0.76 in training dataset and testing dataset, respectively. Additionally, eight methylation-altered CpGs were also identified to construct the CpGs signature which showed a similarly robust diagnostic capability, with AUCs of 0.8 and 0.73 in training dataset and testing dataset, respectively.

Conclusion

We conducted an integrated analysis of the gene expression and DNA methylation data, and constructed a methylation-driven genes signature and a methylation-altered CpGs signature to distinguish the patients with PD from healthy controls. Both of them had a robust prediction power and provide a new insight into personalized diagnostic and therapeutic strategies for PD.

Integrated Bioinformatics Analysis for Identifying the Significant Genes as Poor Prognostic Markers in Gastric Adenocarcinoma

Gastric adenocarcinoma (GAC) is the most common histological type of gastric cancer and imposes a considerable health burden globally. The purpose of this study was to identify significant genes and key pathways participated in the initiation and progression of GAC. Four datasets (GSE13911, GSE19826, GSE54129, and GSE79973) including 171 GAC and 77 normal tissues from Gene Expression Omnibus (GEO) database were collected and analyzed. Through integrated bioinformatics analysis, we obtained 69 commonly differentially expressed genes (DEGs) among the four datasets, including 20 upregulated and 49 downregulated genes. The prime module in protein-protein interaction network of DEGs, including ADAMTS2, COL10A1, COL1A1, COL1A2, COL8A1, BGN, and SPP1, was enriched in protein digestion and absorption, ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and amoebiasis. Furthermore, expression and survival analysis found that all seven hub genes were highly expressed in GAC tissues and 6 of them (except for SPP1) were able to predict poor prognosis of GAC. Finally, we verified the 6 high-expressed hub genes in GAC tissues via immunohistochemistry, Western blot, and RNA quantification analysis. Altogether, we identified six significantly upregulated DEGs as poor prognostic markers in GAC based on integrated bioinformatical methods, which could be potential molecular markers and therapeutic targets for GAC patients.

[Prognostic power of soluble urokinase plasminogen activator receptor (suPAR) for short-term mortality in patients seen in Emergency Departments due to infections]

OBJECTIVE

To analyse and compare 30-day mortality prognostic power of several biomarkers (C-reactive protein, procalcitonin, lactate and suPAR) in patients seen in emergency departments (ED) due to infections. Secondly, if these could improve the accuracy of systemic inflammatory response syndrome (SIRS) and quick Sepsis-related Organ Failure Assessment (qSOFA).

METHODS

A prospective, observational and analytical study was carried out on patients who were treated in an ED of one of the eight participating hospitals. An assessment was made of 32 independent variables that could influence mortality at 30 days. They covered epidemiological, comorbidity, functional, clinical and analytical factors.

RESULTS

The study included 347 consecutive patients, 54 (15.6%) of whom died within 30 days of visiting the ED. SUPAR has got the best biomarker area under the curve (AUC)-ROC to predict mortality at 30 days of 0.836 (95% CI: 0.765-0.907; P <.001) with a cut-off > 10 ng/mL who had a sensitivity of 70% and a specificity of 86%. The score qSOFA ≥ 2 had AUC-ROC of 0.707 (95% CI: 0.621-0.793; P < .001) with sensitivity of 53% and a specificity of 89%. The mixed model (suPAR > 10 ng/mL plus qSOFA ≥ 2) has improved the AUC-ROC to 0.853 [95% CI: 0.790-0.916; P < .001] with the best prognostic performance: sensitivity of 39% and a specificity of 97% with a negative predictive value of 90%.

CONCLUSIONS

suPAR showed better performance for 30-day mortality prognostic power from several biomarkers in the patients seen in ED due to infections. Score qSOFA has better performance that SRIS and the mixed model (qSOFA ≥ 2 plus suPAR > 10 ng/mL) increased the ability of qSOFA.

Inflammatory markers assessment in an animal model of intracranial hypertension: a randomized trial

Background

Intracranial hypertension (ICH) is a common final pathway of most neurosurgical pathologies and leads to poor prognosis if not detected and treated properly. Inflammatory markers have been assessed in clinical scenarios of neurological injuries, in which systemic and brain tissue aggressions may introduce bias. There is a lack of studies under controlled settings to isolate the ICH effect on inflammation. This study aims to evaluate the effects of ICH on the serum concentration of cytokines as biomarkers of neuroinflammation in an experimental model which isolates ICH from potential confounding variables.

Methods

An established model of ICH using an intracerebral pediatric bladder catheter and a multisensor intraparenchymal catheter was used in adult pigs (Sus domesticus). The animals were randomly allocated to 2 groups based on the catheter balloon volume used to simulate the ICP increase (4 ml or 7 ml). Cytokines were measured in 4 timepoints during the experiment: (1) 15 min before balloon insufflation; (2) 5 min after insufflation; (3) 125 min after insufflation; (4) 60 min after deflation. The following cytokines were measured IL-1α; IL-1β; IL–1ra; IL-2; IL-4; IL-6; IL-8; IL-10; IL-12; IL-18; TNFα. Generalized estimating equations were modeled to compare the ICP and cytokines values between the groups along the experiment. The study sample size was powered to detect interactions between the groups and the study moments with an effect size (f) of at least 0.3. The ARRIVE checklist was followed.

Results

A total of 20 animals were studied (10 in each group, 4 ml or 7 ml balloon volume insufflation). The animal model was successful in increasing the ICP along the moments of the experiment (p < 0,001) and in creating an ICP gradient between the groups (p = 0,004). The interaction term (moment × group) was also significant (p < 0,001). There was a significant association between ICP elevation and most cytokines variation. The cytokines IL-1α, IL-1β, IL1-ra, IL-6, IL-12, and IL-18 increased, whereas IL-2, IL-4, and TNF-α decreased. IL-10 did not vary significantly in response to the ICP elevation.

Conclusion

The serum concentration of cytokines varied in response to intracranial hypertension. The study demonstrated the specific changes in each cytokine after intracranial hypertension and provides key information to guide neuroinflammation clinical research. The proposed experiment was successful as an animal model to the study of neuroinflammation biomarkers

Supplementary Information

The online version contains supplementary material available at 10.1186/s40635-021-00408-5.

The potential impact of salivary peptides in periodontitis

Periodontitis is a complex immune-inflammatory condition characterized by the disruption of the periodontal ligament and subsequent formation of periodontal pockets, and by alveolar bone loss, often resulting in tooth loss. A myriad of factors, namely, genetic, metabolic, immunological, and inflammatory, is associated with progression of periodontitis. Periodontitis is also associated with systemic conditions such as neoplastic disorders, obesity, and diabetes. The current diagnosis of this disease relies on clinical measurements such as clinical attachment loss and probing depth, which have poor precision due to patient, operator and probe-related factors. Thus, there is a need to develop reliable, objective, and reproducible biomarkers for early diagnosis of periodontitis. In this regard, saliva, with contributions from the gingival crevicular fluid, holds great potential. However, most of the information on biomarkers of periodontium-related salivary proteins has come from studies on the molecular pathogenesis of periodontitis. In periodontitis, a more holistic approach, such as the use of -omics technologies, for biomarker discovery, is needed. Herein, we review the biomarkers proposed to date for the assessment of periodontitis, with emphasis on the role of salivary peptides in periodontitis and their assessment by high-throughput saliva proteomics. We also discuss the challenges pertaining to the identification of new periodontitis biomarkers in saliva.

Comparison of Pteridine Normalization Methods in Urine for Detection of Bladder Cancer

Pterin compounds belong to the group of biomarkers for which an increase in interest has been observed in recent years. Available literature data point to this group of compounds as potential biomarkers for cancer detection, although the biochemical justification for this claim is not yet fully understood. The aim of this study was to evaluate the usefulness of pterin compounds in the diagnosis of bladder cancer, with particular emphasis on the role of creatinine and the specific gravity of urine as factors for normalizing the concentration of pterin compounds in urine. The standardization of the concentration of pterin compounds to urine specific gravity allows the building of better classification models for screening patients with potential cancer of the bladder. Of the compounds that make up the pterin profile, isoxanthopterin appears to be a compound that can potentially be described as a biomarker of bladder cancer.

Development of an ultrasound-enhanced smartphone colorimetric biosensor for ultrasensitive hydrogen peroxide detection and its applications

In this work, we developed the first ultrasound technique enhanced smartphone application for highly sensitive determination of hydrogen peroxide (H₂O₂). The measurement technique is based on the change in color intensity due to the transformation of tetramethylbenzidine (TMB) to oxidized tetramethylbenzidine (oxTMB) by the oxidation process with hydroxyl radical (OH˙) from the oxidation etching of silver nanoparticles (AgNPs) and its ultrasound usability. The oxTMB product occurs without peroxidase and can be detected with a saturation channel using HSV methodology via the application of a smartphone. To prove the peroxidase mimic property, our proposed method was also validated by determination of certain biomolecules, including glucose, uric acid, acetylcholine and total cholesterol, of which the known amounts are a valuable diagnostic tool. The proposed method provided the lowest limits of detection (LOD) of 2.0, 5.0, 12.50, 7.50, and 10.0 nmol L⁻¹ for H₂O₂, glucose, uric acid, acetylcholine, and cholesterol, respectively, when compared with LODs obtained from other smartphone colorimetric methods. Reproducibility was calculated from the detection of H₂O₂ at 25.0 and 50.0 nmol L⁻¹ with the highest standard deviations of 3.47 and 4.58%, respectively. Additionally, the determination of all analytes in human urine samples indicated recoveries in the range of 96–104% with the highest relative standard deviation of 3.98%, offering high accuracy and precision. Our research shows the novel compatibility of basic technology and chemical methodology with green chemistry principles by reducing a high-power process and organic solvent as well as exhibiting good colorimetric performance and effective sensitivity and selectivity. Thus, our developed method can be applied for point-of-care medical diagnosis.

In this work, we developed the first ultrasound technique enhanced smartphone application for highly sensitive determination of hydrogen peroxide (H₂O₂).