Biomarkers For Human Diseases Research Articles

DynProfiler: A Python package for comprehensive analysis and interpretation of signaling dynamics leveraged by deep learning techniques

Abstract Signaling dynamics encode important features and regulatory mechanisms of biological systems, and recent studies have reported the use of simulated signaling dynamics with mechanistic modeling as biomarkers for human diseases. Given the success of deep learning techniques, it is expected that they can extract informative patterns from simulation results more effectively than traditional approaches involving manual feature selection, which can be used for subsequent analyses, such as patient stratification and survival prediction. Here, we propose DynProfiler, which utilizes the entire signaling dynamics, including intermediate variables, as input and leverages deep learning techniques to extract informative features without requiring any labels. Furthermore, DynProfiler incorporates a modern explainable AI solution to provide quantitative time-dependent importance scores for each dynamics. Using simulated dynamics of patients with breast cancer as an example, we demonstrate DynProfiler’s ability to extract high-quality features that can predict mortality risk and identify important dynamics, highlighting upregulated phosphorylated GSK3β as a biomarker for poor prognosis. Overall, this tool can be useful for clinical application, as well as for elucidating biological system dynamics. Availability The DynProfiler Python library is available in GitHub at https://github.com/okadalabipr/DynProfiler. Supplementary information Supplementary data are available at Bioinformatics Advances online.

Postmortem-Derived Exosomal MicroRNA 486-5p as Potential Biomarkers for Ischemic Heart Disease Diagnosis.

Exosomes are nanovesicles 30-150 nm in diameter released extracellularly. Those isolated from human body fluids reflect the characteristics of their cells or tissues of origin. Exosomes carry extensive biological information from their parent cells and have significant potential as biomarkers for disease diagnosis and prognosis. However, there are limited studies utilizing exosomes in postmortem diagnostics. In this study, we extended our initial research which identified the presence and established detection methodologies for exosomes in postmortem fluids. We analyzed exosomal miRNA extracted from plasma and pericardial fluid samples of a control group (n = 13) and subjects with acute myocardial infarction (AMI; n = 24). We employed next-generation sequencing (NGS) to investigate whether this miRNA could serve as biomarkers for coronary atherosclerosis leading to acute myocardial infarction. Our analysis revealed 29 miRNAs that were differentially expressed in the AMI group compared to the control group. Among these, five miRNAs exhibited more than a twofold increase in expression across all samples from the AMI group. Specifically, miR-486-5p levels were significantly elevated in patients with high-grade (type VI or above) atherosclerotic plaques, as per the American Heart Association criteria, highlighting its potential as a predictive biomarker for coronary atherosclerosis progression. Our results indicate that postmortem-derived exosomal microRNAs can serve as potential biomarkers for various human diseases, including cardiovascular disorders. This finding has profound implications for forensic diagnostics, a field critically lacking diagnostic markers.

Fluorescent cyclopropyl ester probes are efficiently cleaved by endogenous carboxylesterase in mouse blood: implications for preclinical fluorescence imaging

ABSTRACT Prior studies have shown that fluorescent molecular probes based on cyclopropyl esters are good substrates for butyrylcholine esterase (BChE), which is a biomarker of several human diseases. We tested two fluorescent cyclopropyl ester derivatives as BChE-activated fluorogenic probes. One was a known fluorescein probe, and the other was a newly designed near-infrared probe based on a heptamethine cyanine dye. As expected, both probes were good substrates for BChE, but they were also good substrates for carboxylesterase (CE). The probes were efficiently cleaved in mouse blood and serum which contains high levels of CE, but they were not cleaved in human serum which contains negligible CE. There are two major implications of these results. One is a cautionary note that esterase levels in different organisms can vary substantially. Researchers developing fluorescent cyclopropyl ester probes for BChE imaging should anticipate high levels of background signal in preclinical mouse models due to ester cleavage by the abundant CE in mouse blood. However, there is very little cleavage of fluorescent cyclopropyl ester probes in human blood, which contains low levels of CE. Therefore, fluorescent cyclopropyl ester probes should be viable in humans as imaging agents that identify disease sites with overexpressed levels of CE or BChE.

High Sensitivity and Specificity Platform to Validate MicroRNA Biomarkers in Cancer and Human Diseases.

We developed a technology for detecting and quantifying trace nucleic acids using a bracketing protocol designed to yield a copy number with approximately ± 20% accuracy across all concentrations. The microRNAs (miRNAs) let-7b, miR-15b, miR-21, miR-375 and miR-141 were measured in serum and urine samples from healthy subjects and patients with breast, prostate or pancreatic cancer. Detection and quantification were amplification-free and enabled using osmium-tagged probes and MinION, a nanopore array detection device. Combined serum from healthy men (Sigma-Aldrich, St. Louis, MO, USA #H6914) was used as a reference. Total RNA isolated from biospecimens using commercial kits was used as the miRNA source. The unprecedented ± 20% accuracy led to the conclusion that miRNA copy numbers must be normalized to the same RNA content, which in turn illustrates (i) independence from age, sex and ethnicity, as well as (ii) equivalence between serum and urine. miR-21, miR-375 and miR-141 copies in cancers were 1.8-fold overexpressed, exhibited zero overlap with healthy samples and had a p-value of 1.6 × 10-22, tentatively validating each miRNA as a multi-cancer biomarker. miR-15b was confirmed to be cancer-independent, whereas let-7b appeared to be a cancer biomarker for prostate and breast cancer, but not for pancreatic cancer.

Harnessing myelin water fraction as an imaging biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination: A review.

Myelin water fraction (MWF) imaging has emerged as a promising magnetic resonance imaging (MRI) biomarker for investigating brain function and composition. This comprehensive review synthesizes the current state of knowledge on MWF as a biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination. The databases used include Web of Science, Scopus, Science Direct, and PubMed. We begin with a brief discussion of the theoretical foundations of MWF imaging, including its basis in MR physics and the mathematical modeling underlying its calculation, with an overview of the most adopted MRI methods of MWF imaging. Next, we delve into the clinical and research applications that have been explored to date, highlighting its advantages and limitations. Finally, we explore the potential of MWF to serve as a predictive biomarker for neurological disorders and identify future research directions for optimizing MWF imaging protocols and interpreting MWF in various contexts. By harnessing the power of MWF imaging, we may gain new insights into brain health and disease across the human lifespan, ultimately informing novel diagnostic and therapeutic strategies.

Urinary miRNAs: Technical Updates.

Due to its non-invasive nature and easy accessibility, urine serves as a convenient biological fluid for research purposes. Furthermore, urine samples are uncomplicated to preserve and relatively inexpensive. MicroRNAs (miRNAs), small molecules that regulate gene expression post-transcriptionally, play vital roles in numerous cellular processes, including apoptosis, cell differentiation, development, and proliferation. Their dysregulated expression in urine has been proposed as a potential biomarker for various human diseases, including bladder cancer. To draw reliable conclusions about the roles of urinary miRNAs in human diseases, it is essential to have dependable and reproducible methods for miRNA extraction and profiling. In this review, we address the technical challenges associated with studying urinary miRNAs and provide an update on the current technologies used for urinary miRNA isolation, quality control assessment, and miRNA profiling, highlighting both their advantages and limitations.

Quantitative and equipment-free paper-based agglutination assay of bacterial cells.

Background: point-of-care (POC) tests are useful for bedside/home applications, emergencies, frequent follow-ups, and resource-limited areas. Limited quantitative and equipment-free POC assays have been reported. This study aims to develop, validate, and apply a simple, quantitative, paper-based POC assay. Methods: wax-channeled paper treated with specific anti-Brucella and anti-Salmonella antibodies was used for distance-based chromatographic elution of stained bacterial cell agglutinations. Results: a qualitative paper-based agglutination POC test was developed using color intensity, tail appearance, and "+/-" signs that clearly distinguish the positive and negative results. The optimization of the test for paper type, microfluidic channel design, antibody and bacterial cell concentrations, and elution methods was carried out. Quantitative assay transformation was successfully developed using the color intensity of the original reaction zone, intensity of elution tail, and distance-based migration that correspond to bacterial agglutination size. The migration distance of eluted bacterial agglutination bands corresponds to the target concentration with good linearity and minimal variability. Reporting of colored band migration with numbers using microfluidic patterns was used to enhance non-technical end-user applications. A distance-based POC assay prototype was then successfully used for the accurate detection of known and unknown samples in comparison with standard assays. Conclusions: the migration distance of an eluted stained bacterial agglutination correlated with anti-bacterial antibody concentrations. A simple, cheap, quantitative, and equipment-free paper-based POC assay of bacterial cell agglutination was developed. This test can be used for simple "+/-" results, thermometer-like quantification, or text reporting with numbers corresponding to target concentrations. The assay has extended applications to different human disease biomarkers.

Investigating and Annotating the Human Peptidome Profile from Urine under Normal Physiological Conditions.

Examining the composition of the typical urinary peptidome and identifying the enzymes responsible for its formation holds significant importance, as it mirrors the normal physiological state of the human body. Any deviation from this normal profile could serve as an indicator of pathological processes occurring in vivo. Consequently, this study focuses on characterizing the normal urinary peptidome and investigating the various catalytic enzymes that are involved in generating these native peptides in urine. Our findings reveal that 1503 endogenous peptides, corresponding to 436 precursor proteins, were consistently identified robustly in at least 10 samples out of a total of 19 samples. Notably, the liver and kidneys exhibited the highest number of tissue-enriched or enhanced genes in the analyzed urinary peptidome. Furthermore, among the catalytic types, CTSD (cathepsin D) and MMP2 (matrix metalloproteinase-2) emerged as the most prominent peptidases in the aspartic and metallopeptidases categories, respectively. A comparison of our dataset with two of the most comprehensive urine peptidome datasets to date indicates a consistent relative abundance of core endogenous peptides for different proteins across all three datasets. These findings can serve as a foundational reference for the discovery of biomarkers in various human diseases.

Preanalytical, analytical and postanalytical considerations in circulating microRNAs measurement.

Microribonucleic acids (miRNAs) have emerged as a new category of biomarkers for many human diseases like cancer, cardiovascular and neurodegenerative disorders. MicroRNAs can be detected in various body fluids including blood, urine and cerebrospinal fluid. However, the literature contains conflicting results for circulating miRNAs, which is the main barrier to using miRNAs as non-invasive biomarkers. This variability in results is largely due to differences between studies in sample processing methodology, miRNA quantification and result normalization. The purpose of this review is to describe the various preanalytical, analytical and postanalytical factors that can impact miRNA detection accuracy and to propose recommendations for the standardization of circulating miRNAs measurement.

Circ_0003945: an emerging biomarker and therapeutic target for human diseases.

Due to the rapid development of RNA sequencing techniques, a circular non-coding RNA (ncRNA) known as circular RNAs (circRNAs) has gradually come into focus. As a distinguished member of the circRNA family, circ_0003945 has garnered attention for its aberrant expression and biochemical functions in human diseases. Subsequent studies have revealed that circ_0003945 could regulate tumor cells proliferation, migration, invasion, apoptosis, autophagy, angiogenesis, drug resistance, and radio resistance through the molecular mechanism of competitive endogenous RNA (ceRNA) during tumorigenesis. The expression of circ_0003945 is frequently associated with some clinical parameters and implies a poorer prognosis in the majority of cancers. In non-malignant conditions, circ_0003945 also holds considerable importance in diseases pathogenesis. This review aims to recapitulate molecular mechanism of circ_0003945 and elucidates its potential as a diagnostic and therapeutic target in neoplasms and other diseases.

Comparative analysis of human tear fluid and aqueous humor proteomes

PurposeTechnological advancements allowing for the analysis of low-volume samples have led to the investigation of human tear fluid and aqueous humor (AH) as potential biomarker sources. However, acquiring AH samples poses significant challenges, making human tear fluid a more accessible alternative. This study aims to compare the protein compositions of these two biofluids to evaluate their suitability for biomarker discovery. MethodsPaired tear and AH samples were collected from 20 patients undergoing cataract surgery. Tear samples were collected using Schirmer strips prior to surgery, and AH samples were collected from the anterior chamber immediately after corneal incision. Proteins were extracted and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). ResultsA total of 481 proteins were identified in greater than 50% of the tear samples, and 191 proteins were detected in greater than 50% of the AH samples. Of these proteins, 82 were found to be common between the two biofluids, with ALB, LTF, TF, LCN1, and IGKC being the most abundant. ConclusionAlthough tear fluid and the AH are functionally independent and physically separated, many of the proteins detected in AH were also detected in tears. This direct comparison of the proteomic content of tear fluid and AH may aid in further investigation of tear fluid as a source of readily accessible biomarkers for various human diseases.

Unraveling the microbiome-metabolome nexus: a comprehensive study protocol for personalized management of Behçet's disease using explainable artificial intelligence.

The presented study protocol outlines a comprehensive investigation into the interplay among the human microbiota, volatilome, and disease biomarkers, with a specific focus on Behçet's disease (BD) using methods based on explainable artificial intelligence. The protocol is structured in three phases. During the initial three-month clinical study, participants will be divided into control and experimental groups. The experimental groups will receive a soluble fiber-based dietary supplement alongside standard therapy. Data collection will encompass oral and fecal microbiota, breath samples, clinical characteristics, laboratory parameters, and dietary habits. The subsequent biological data analysis will involve gas chromatography, mass spectrometry, and metagenetic analysis to examine the volatilome and microbiota composition of salivary and fecal samples. Additionally, chemical characterization of breath samples will be performed. The third phase introduces Explainable Artificial Intelligence (XAI) for the analysis of the collected data. This novel approach aims to evaluate eubiosis and dysbiosis conditions, identify markers associated with BD, dietary habits, and the supplement. Primary objectives include establishing correlations between microbiota, volatilome, phenotypic BD characteristics, and identifying patient groups with shared features. The study aims to identify taxonomic units and metabolic markers predicting clinical outcomes, assess the supplement's impact, and investigate the relationship between dietary habits and patient outcomes. This protocol contributes to understanding the microbiome's role in health and disease and pioneers an XAI-driven approach for personalized BD management. With 70 recruited BD patients, XAI algorithms will analyze multi-modal clinical data, potentially revolutionizing BD management and paving the way for improved patient outcomes.

Method of Localization of Spatiotemporal Patterns on the Time Sequence of Biomedical Images

A method has been developed for localizing spatiotemporal patterns observed in sequentially recorded biomedical images of laser scanning microscopy and reflecting the dynamics of the biological structures under study. By means of interpolation by radial basis functions of each individual image, a compact mathematical model of the space-time dynamics of the brightness function on a sequence of images is obtained. The subsequent localization of the structures of the sought-for dynamic patterns is carried out by means of the mathematical apparatus of singular spectral analysis. The results of experiments on optical visualization of the activity patterns of the olfactory bulb of a macrosmatic (rat) confirmed the efficiency of the developed method for localizing the reaction to biomarkers of human oncological diseases.

Transcriptome-based biomarker prediction for Parkinson’s disease using genome-scale metabolic modeling

Parkinson's disease (PD) is the second most common neurodegenerative disease in the world. Identification of PD biomarkers is crucial for early diagnosis and to develop target-based therapeutic agents. Integrative analysis of genome-scale metabolic models (GEMs) and omics data provides a computational approach for the prediction of metabolite biomarkers. Here, we applied the TIMBR (Transcriptionally Inferred Metabolic Biomarker Response) algorithm and two modified versions of TIMBR to investigate potential metabolite biomarkers for PD. To this end, we mapped thirteen post-mortem PD transcriptome datasets from the substantia nigra region onto Human-GEM. We considered a metabolite as a candidate biomarker if its production was predicted to be more efficient by a TIMBR-family algorithm in control or PD case for the majority of the datasets. Different metrics based on well-known PD-related metabolite alterations, PD-associated pathways, and a list of 25 high-confidence PD metabolite biomarkers compiled from the literature were used to compare the prediction performance of the three algorithms tested. The modified algorithm with the highest prediction power based on the metrics was called TAMBOOR, TrAnscriptome-based Metabolite Biomarkers by On–Off Reactions, which was introduced for the first time in this study. TAMBOOR performed better in terms of capturing well-known pathway alterations and metabolite secretion changes in PD. Therefore, our tool has a strong potential to be used for the prediction of novel diagnostic biomarkers for human diseases.

CD177 is a novel IgG Fc receptor and CD177 genetic variants affect IgG-mediated function.

CD177 plays an important role in the proliferation and differentiation of myeloid lineage cells including neutrophils, myelocytes, promyelocytes, megakaryocytes, and early erythroblasts in bone marrow. CD177 deficiency is a common phenotype in humans. Our previous studies revealed genetic mechanisms of human CD177 deficiency and expression variations. Up to now, immune functions of CD177 remain undefined. In the current study, we revealed human IgG as a ligand for CD177 by using flow cytometry, bead-rosette formation, and surface plasmon resonance (SPR) assays. In addition, we show that CD177 variants affect the binding capacity of CD177 for human IgG. Furthermore, we show that the CD177 genetic variants significantly affect antibody-dependent cell-mediated cytotoxicity (ADCC) function. The demonstration of CD177 as a functional IgG Fc-receptor may provide new insights into CD177 immune function and genetic mechanism underlying CD177 as biomarkers for human diseases.

Two-dimensional oxygen-deficient ZnO1-x nanosheet as a highly selective and sensitive fluorescence probe for ferritin detection: the electron transfer biosensor (ETBS).

Iron proteins are of great scientific interest due to their importance as an excellent biomarker for human diseases. Ferritin (Fe3+), being an iron-rich blood protein, is related to various diseases like anemia and cancer. For the first time, we have developed a highly sensitive and selective ferritin biosensor based on fluorescent oxygen-deficient zinc oxide nanosheets through hydrothermal and probe-ultrasonication combined methods. The fluorescence study showed an intense bluish-green fluorescence at λex = 370 nm, after optimization at different excitation wavelengths. In addition, the fluorescence of ZnO1-x nanosheets can be efficiently quenched due to electron transfer reactions in order to achieve quantification analysis. The limit of detection (LOD) was calculated to be 0.015 nM (7.2 ng mL-1) with high linearity (R2 = 0.9930). In addition, the real-world application of the proposed biosensor has been performed on human blood serum samples in the presence of various interfering analytes showing high selectivity and sensitivity with a regression value R2 = 0.9980 indicating the current approach is an excellent biosensor platform.

Design and Discovery of Novel NLRP3 Inhibitors and PET Imaging Radiotracers Based on a 1,2,3-Triazole-Bearing Scaffold.

The NOD-like receptor (NLR) family pyrin-domain-containing 3 (NLRP3) inflammasome, an essential component of the innate immune system, has been emerging as a viable drug target and a potential biomarker for human diseases. In our efforts to develop novel small molecule NLRP3 inhibitors, a 1-(5-chloro-2-methoxybenzyl)-4-phenyl-1H-1,2,3-triazole scaffold was designed via a rational approach based on our previous leads. Structure-activity relationship studies and biophysical studies identified a new lead compound 8 as a potent (IC50: 0.55 ± 0.16 μM), selective, and direct NLRP3 inhibitor. Positron emission tomography (PET) imaging studies of [11C]8 demonstrated its rapid and high brain uptake as well as fast washout in mice and rhesus macaque. Notably, plasma kinetic analysis of this radiotracer from the PET/magnetic resonance imaging studies in rhesus macaque suggested radiometabolic stability. Collectively, our data not only encourage further studies of this lead compound but also warrant further optimization to generate additional novel NLRP3 inhibitors and suitable central nervous system PET radioligands with translational promise.

Oxy- and Phytosterols as Biomarkers: Current Status and Future Perspectives.

Oxysterols and phytosterols are sterol compounds present at markedly low levels in tissues and serum of healthy individuals. A wealth of evidence suggests that they could be employed as biomarkers for human diseases or for cholesterol absorption.An increasing number of reports suggest circulating or tissue oxysterols as putative biomarkers for cardiovascular and neurodegenerative diseases or cancers. Thus far most of the studies have been carried out on small study populations. To achieve routine biomarker use, large prospective cohort studies are absolutely required. This, again, would necessitate thorough standardization of the oxysterol analytical methodology across the different laboratories, which now employ different technologies resulting in inconsistencies in the measured oxysterol levels. Routine use of oxysterol biomarkers would also necessitate the development of a new targeted analytical methodology suitable for high-throughput platforms.The most important use of phytosterols as biomarkers involves their use as markers for cholesterol absorption. For this to be achieved, (1) their quantitative analyses should be available in routine lipid laboratories, (2) it should be generally acknowledgment that the profile of cholesterol metabolism can reveal the risk of the development of atherosclerotic cardiovascular diseases (ASCVD), and (3) screening of the profile of cholesterol metabolism should be included in the ASCVD risk surveys. This should be done e.g. in families with a history of early onset or frequent ASCVD and in young adults aged 18-20years, to exclude the presence of high cholesterol absorption. Individuals in high cholesterol absorption families need preventive measures from young adulthood to inhibit the possibledevelopment and progression of atherosclerosis.

Orbitrap Mass Spectrometry and High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Enable the in-Depth Analysis of Human Serum Proteoforms.

Blood serum and plasma are arguably the most commonly analyzed clinical samples, with dozens of proteins serving as validated biomarkers for various human diseases. Top-down proteomics may provide additional insights into disease etiopathogenesis since this approach focuses on protein forms, or proteoforms, originally circulating in blood, potentially providing access to information about relevant post-translational modifications, truncations, single amino acid substitutions, and many other sources of protein variation. However, the vast majority of proteomic studies on serum and plasma are carried out using peptide-centric, bottom-up approaches that cannot recapitulate the original proteoform content of samples. Clinical laboratories have been slow to adopt top-down analysis, also due to higher sample handling requirements. In this study, we describe a straightforward protocol for intact proteoform sample preparation based on the depletion of albumin and immunoglobulins, followed by simplified protein fractionation via polyacrylamide gel electrophoresis. After molecular weight-based fractionation, we supplemented the traditional liquid chromatography-tandem mass spectrometry (LC-MS2) data acquisition with high-field asymmetric waveform ion mobility spectrometry (FAIMS) to further simplify serum proteoform mixtures. This LC-FAIMS-MS2 method led to the identification of over 1000 serum proteoforms < 30 kDa, outperforming traditional LC-MS2 data acquisition and more than doubling the number of proteoforms identified in previous studies.

Iron links endogenous and exogenous nanoparticles

Current progress in biology and medical science is based on the observation at the level of nanometers via electron microscopy and computation. Of note, the size of most cells in higher species exists in a limited range from 5 to 50 μm. Recently, it was demonstrated that endogenous extracellular nanoparticles play a role in communication among various cellular types in a variety of contexts. Among them, exosomes in serum have been established as biomarkers for human diseases by analyzing the cargo molecules. No life on the earth can survive without iron. However, excess iron can be a risk for carcinogenesis in rodents and humans. Nano-sized molecules may cause unexpected bioeffects, including carcinogenesis, which is a process to establish cellular iron addiction with ferroptosis-resistance. Asbestos and carbon nanotubes are the typical examples, leading to carcinogenesis by the alteration of iron metabolism. Recently, we found that CD63, one of the representative markers of exosomes, is under the regulation of iron-responsive element/iron-regulatory protein system. This is a safe strategy to share excess iron in the form of holo-ferritin between iron-sufficient and -deficient cells. On the other hand, damaged cells may secrete holo-ferritin-loaded exosomes as in the case of macrophages in ferroptosis after asbestos exposure. These holo-ferritin-loaded exosomes can cause mutagenic DNA damage in the recipient mesothelial cells. Thus, there is an iron link between exogenous and endogenous nanoparticles, which requires further investigation for better understanding and the future applications.