Common Biomarkers Research Articles

Simultaneous multiple target detection platform based on vertical flow immunoassay

In general, vertical flow assay (VFA) has a disadvantage of requiring a complex analysis process that involves manually injecting various reagents (target analyte, washing buffer, detection conjugate, etc.) sequentially. However, in this study, we have developed an innovative paper-based VFA device that replaces the complex analysis process with one-step and enables the detection of multiple targets. The fabrication process of the multi-target detection VFA device is as follows: preparation and pre-treatment of the strip materials, design of strip cartridge, design of the multiple detection VFA device, optimization experiments for strip sample flow rates, determination of device analysis time, determination of device limit of detection (LOD), multiple target signal uniformity experiment, immunoglobulin G (IgG) and C-reactive protein (CRP) antigen-antibody multiple detection experiment, and data extraction and analysis method. The use of paper-based materials enables the device to be produced at cost-effective, and cartridge production allowed for uniform array formation. IgG and CRP are used to evaluate the performance of the device as common biomarkers. The device proposed in this study is currently under research. To validate multiple target detection capability of the VFA device proposed in this study, two types of antigens-antibodies (Human IgG and Human CRP) were employed. The detection limit is 0.15 μg/mL for IgG and 0.19 μg/mL for CRP in naked eye. Furthermore, it was confirmed that there is no cross-reactivity caused by the device structure through IgG and CRP antigens. In conclusion, the VFA device proposed in this study consists of a one-step analysis process, and it has been confirmed that it can detect multiple targets simultaneously.

Examining a Preclinical Alzheimer's Cognitive Composite for Telehealth Administration for Reliability Between In-Person and Remote Cognitive Testing with Neuroimaging Biomarkers.

The preclinical Alzheimer's cognitive composite (PACC) was developed for in-person administration to capture subtle cognitive decline. At the outset of the COVID-19 pandemic, cognitive testing was increasingly performed remotely by telephone or video administration. It is desirable to have a harmonized composite measurement derived from both in-person and remote assessments for identifying cognitive changes and to examine its relationship with common neuroimaging biomarkers. We defined a telehealth compatible PACC (tPACC) and examined its relationship with neuroimaging biomarkers related to neurodegeneration, brain function and perfusion, white matter integrity, and amyloid-β. We examined 648 participants' neuroimaging and in-person and remote cognitive testing data from the Wake Forest Alzheimer's Disease Research Center's Clinical Core cohort (observational study) to calculate a modified PACC (PACC5-RAVLT) score and tPACC scores (in-person and remote). We performed Spearman/intraclass correlation coefficient (ICC) analyses for reliability of tPACC scores and linear regression models to evaluate associations between tPACC and neuroimaging. Bland-Altman plots for agreement were constructed across cognitively normal and impaired (mild cognitive impairment and dementia) participants. There was a significant positive relationship between tPACCin-person and PACC5-RAVLT (Overall group: r2 = 0.94, N = 648), and tPACCin-person and tPACCremote (validation subgroup: ICC = 0.82, n = 53). Overall, tPACC showed significant associations with brain thickness/volume, gray matter perfusion, white matter free water, and amyloid-β deposition. There is a good agreement between tPACCand PACC5-RAVLTfor cognitively normal and impaired individuals. The tPACC is associated with common neuroimaging markers of Alzheimer's disease.

Progressive substitution of fish oil with Schizochytrium-derived algal oil in the diet of Atlantic salmon (Salmo salar) parr subjected to winter signal period

The aim of this study was to investigate the impact of progressive replacement of fish oil with Schizochytrium-derived oil from Veramaris® (VMO) in the diets of Atlantic salmon, focusing on its effect during the pre-adaptation to smoltification phase of parr, with an emphasis on the winter signal period. Substitution of fish oil with VMO during this critical developmental phase of salmon (pre-adaptation to smoltification phase) can contribute to the goal of reducing dependence on wild fisheries as a primary source of essential fatty acids in aquafeeds. Three isoproteic, isolipidic and isoenergetic diets were formulated; a control diet containing 5% fish oil and 12% plant oil (0VMO) and two other diets, in which 50% and 100% of the EPA+DHA from fish oil were replaced with VMO, henceforth referred to as 50VMO and 100VMO, respectively. The fish were exposed to a 12 L:12D photoperiod over a 49-day window with samples collected at five time points, including a 48-h salt water challenge to evaluate the effects on common smoltification-related biomarkers including the expression of two genes coding for the two protein isoforms of the NKA alpha catalytic subunit (nkaa1a, nkaa1b), the gene coding for NA+/K+Cl⁻ co-transporter (nkcc1) in the gills as well as osmolality, Cl-, Mg2+, Ca2+, cortisol, growth hormone, and insulin-like growth factor-1 in plasma. The results showed non-significant differences in growth performance and only minor differences in smoltification-related parameters between the dietary treatment groups. Overall, the unconventional source of EPA+DHA was not detrimental to growth, hypoosmoregulatory ability or general welfare, suggesting that the progressive substitution of fish oil with Schizochytrium-derived oil in diets for Atlantic salmon parr is a viable option for adoption by the aquaculture industry.

C-reactive protein is more suitable than Serum Amyloid A to monitor crises and attack-free periods in Systemic Auto-Inflammatory Diseases.

BackgroundWith their broad presentations and no global biomarker to discriminate crises and attack-free periods, Systemic Auto-Inflammatory Diseases (SAID) are difficult to manage. This study assessed Serum Amyloid A (SAA), C-reactive protein (CRP) and serum calprotectin as potential biomarkers to monitor patients with SAID. MethodSAA (already studied in Familial Mediterranean Fever (FMF)), CRP and serum calprotectin were measured on SAID adult patients from Juvenile Inflammatory Rheumatism (JIR) cohort during their follow-up visits between 2020 and 2022. Crises and attack-free periods were clinically determined. Results96 measures, mainly from FMF (43 %) and Unclassified SAID (USAID) (37 %) patients were included. Using ROC curves, a threshold with sensitivity and specificity of/over 75 % was determined for SAA (9 mg/L) and CRP (9 mg/L) but not for serum calprotectin, not investigated further. With this threshold, the results were similar in FMF and USAID patients’ subgroups. SAA and CRP showed a positive correlation with crises and attack-free periods in SAID patients (r = 0.4796, p < 0.001 and r = 0.5525, p < 0.001, respectively) as in FMF and USAID patients, with no significant difference between both markers in diagnosis value and ROC curves Area Under Curve (AUC) (p = 0.32). Only the CRP results were not influenced by obesity. ConclusionSAA and CRP can discriminate crisis and attack-free periods in our cohort of SAID patients mainly composed of FMF and USAID patients. However, only CRP can be used regardless of body mass index. It is the first report of common biomarkers for all SAID, including USAID patients, with CRP widely accessible in routine worldwide.

Autoimmune diseases (AIDs) in Côte d’Ivoire West Africa

Abstract Introduction Autoimmune diseases (AIDs) are until now very well unknown in Africa and particularly in subsaharien countries. They were even considered non-existent . The objective of this work is to estimate the prevalence, describe the epidemiological, clinical and biological aspects of AID in our country. Methods This was a descriptive retrospective study conducted from January 1, 2010 to December 31, 2020, on the files of patients hospitalized in the rheumatology department of the University Hospital of Cocody in Abidjan, Côte d’Ivoire. Results We studied 116 patients including 104 female patients (90%) and 12 male patients (10%). Most systemic autoimmune diseases have been observed in patients aged from 31 to 45 years. The average age was 40.02 +/- 15.07 years (extreme 12 and 72 years). The main diagnoses retained were systemic lupus erythematosus (34%), rheumatoid arthritis (22%), mixed connectivites (27%), sclerodermia(13%) . Of the 116 patients, 82% were not tested, 4% were negative and 14% were found positive for antinuclear antibodies, the most common biomarker in autoimmunity. Conclusion AIDs are prevalent in our countries with various presentation in our patients and they occur in young adults. Autoimmune disease are prevalent in our country and increasing. Further studies and a national regsitry of autoimmune disease need to be established to understand the disease and its increase in african environnement.

Specific biomarkers and neurons distribution of different brain regions in largemouth bass (Micropterus salmoides).

The brain regulates multiple physiological processes in fish. Despite this, knowledge about the basic structure and function of distinct brain regions in non-model fish species remains limited due to their diversity and the scarcity of common biomarkers. In the present study, four major brain parts, the telencephalon, diencephalon, mesencephalon and rhombencephalon, were isolated in largemouth bass, Micropterus salmoides. Within these parts, nine brain regions and 74 nuclei were further identified through morphological and cytoarchitectonic analysis. Transcriptome analysis revealed a total of 7153 region-highly expressed genes and 176 region-specifically expressed genes. Genes related to growth, reproduction, emotion, learning, and memory were significantly overexpressed in the olfactory bulb and telencephalon (OBT). Feeding and stress-related genes were in the hypothalamus (Hy). Visual system-related genes were predominantly enriched in the optic tectum (OT), while vision and hearing-related genes were widely expressed in the cerebellum (Ce) region. Sensory input and motor output-related genes were in the medulla oblongata (Mo). Osmoregulation, stress response, sleep/wake cycles, and reproduction-related genes were highly expressed in the remaining brain (RB). Three candidate marker genes were further identified for each brain regions, such as neuropeptide FF (npff) for OBT, pro-melanin-concentrating hormone (pmch) for Hy, vesicular inhibitory amino acid transporter (viaat) for OT, excitatory amino acid transporter 1 (eaat1) for Ce, peripherin (prph) for Mo, and isotocin neurophysin (itnp) for RB. Additionally, the distribution of seven neurotransmitter-type neurons and five types of non-neuronal cells across different brain regions were analyzed by examining the expression of their marker genes. Notably, marker genes for glutamatergic and GABAergic neurons showed the highest expression levels across all brain regions. Similarly, the marker gene for radial astrocytes exhibited high expression compared to other markers, while those for microglia were the least expressed. Overall, our results provide a comprehensive overview of the structural and functional characteristics of distinct brain regions in the largemouth bass, which offers a valuable resource for understanding the role of central nervous system in regulating physiological processes in teleost.

Time-encoded electrical detection of trace RNA biomarker by integrating programmable molecular amplifier on chip

One of the serious challenges facing modern point-of-care (PoC) molecular diagnostic platforms relate to reliable detection of low concentration biomarkers such as nucleic acids or proteins in biological samples. Non-specific analyte-receptor interactions due to competitive binding in the presence of abundant molecules, inefficient mass transport and very low number of analyte molecules in sample volume, in general pose critical hurdles for successful implementation of such PoC platforms for clinical use. Focusing on these specific challenges, this work reports a unique PoC biosensor that combines the advantages of nanoscale biologically-sensitive field-effect transistor arrays (BioFET-arrays) realized in a wafer-scale top-down nanofabrication as high sensitivity electrical transducers with that of sophisticated molecular programs (MPs) customized for selective recognition of analyte miRNAs and amplification resulting in an overall augmentation of signal transduction strategy. The MPs realize a programmable universal molecular amplifier (PUMA) in fluidic matrix on chip and provide a biomarker-triggered exponential release of small nucleic acid sequences easily detected by receptor-modified BioFETs. A common miRNA biomarker LET7a was selected for successful demonstration of this novel biosensor, achieving limit of detection (LoD) down to 10 fM and wide dynamic ranges (10 pM–10 nM) in complex physiological solutions. As the determination of biomarker concentration is implemented by following the electrical signal related to analyte-triggered PUMA in time-domain instead of measuring the threshold shifts of BioFETs, and circumvents direct hybridization of biomarkers at transducer surface, this new strategy also allows for multiple usage (>3 times) of the biosensor platform suggesting exceptional cost-effectiveness for practical use.

Identification of common mechanisms and biomarkers of atrial fibrillation and heart failure based on machine learning.

Atrial fibrillation (AF) is the most common arrhythmia. Heart failure (HF) is a disease caused by heart dysfunction. The prevalence of AF and HF were progressively increasing over time. The co-existence of AF and HF presents a significant therapeutic challenge. In order to provide new ideas for the diagnosis of AF and HF, it is necessary to carry out biomarker related studies. The training set and validation set data of AF and HF patient samples were downloaded from the GEO database, 'limma' was used to compare the differences in gene expression levels between the disease group and the normal group to screen for differentially expressed genes (DEGs). Weighted correlation network analysis (WGCNA) identified the modules with the highest positive correlation with AF and HF. Functional enrichment and PPI network construction of key genes were carried out. Biomarkers were screened by machine learning. The infiltration of immune cells in AF and HF groups was evaluated by R-packet 'CIBERSORT'. The miRNA network was constructed and potential therapeutic agents for biomarker genes were predicted through the drugbank database. Through WGCNA analysis, it was found that the modules most positively correlated with AF and HF were MEturquoise (r=0.21, P value=0.09) and MEbrown (r=0.62, P value=8e-12), respectively. We screened 25 genes that were highly correlated with both AF and HF. Lasso regression analysis results showed 7 and 20 core genes in AF and HF groups, respectively. The top 20 important genes in AF and HF groups were obtained as core genes by RF model analysis. Four biomarkers were obtained after the intersection of core genes in four groups, namely, GLUL, NCF2, S100A12, and SRGN. The diagnostic efficacy of four genes in AF validation sets was good (AUC: GLUL 0.76, NCF2 0.64, S100A12 0.68, and SRGN 0.76), as well as in the HF validation set (AUC: GLUL 0.76, NCF2 0.84, S100A12 0.92, and SRGN 0.68). The highest correlation with neutrophils was observed for GLUL, NCF2, and S100A12, while SRGN exhibited the strongest correlation with T cells CD4 memory resting in the AF group. GLUL, NCF2, S100A12, and SRGN were most associated with neutrophils in the HF group. A total of 101 miRNAs were predicted by four genes, and GLUL, NCF2, and S100A12 predicted a total of 10 potential therapeutic agents. We identified four biological markers that are highly correlated with AF and HF, namely, GLUL, NCF2, S100A12, and SRGN. Our findings provide theoretical basis for the clinical diagnosis and treatment of AF and HF.

Post-COVID syndrome in patients with type 2 diabetes: definition, epidemiology, pathophysiology, biomarkers and genetic associations

The article presents the modern ideas about post-COVID syndrome, indicates various types and classifications of post-COVID syndrome, provides epidemiological data, including the patients with type 2 diabetes, also the definition of post-COVID syndrome is given. The group of patients defined as patients with post-COVID syndrome is very heterogeneous. Post-COVID syndrome is more common in the elderly, with comorbid pathology, severe disease. The pathophysiology of this syndrome in patients with type 2 diabetes mellitus is analyzed, and risk factors are indicated. The main biomarkers of disorders were determined: monocytes and their coefficients, acute phase proteins, some biochemical indicators, including analysis of genetic associations with the severity of post-COVID disorders (interferon gamma gene, methylenetetrahydrofolate reductase gene, ACE2 inhibitor). Genotyping of a sample of 26 single nucleotide polymorphisms in genes implicated in viral entry, immune response, and inflammation were significantly associated not only with the risk of long-term COVID-19 symptoms, but also with the cumulative incidence of post-COVID syndrome. Elevated levels of interleukin 6, C-reactive protein and tumor necrosis factor alpha may serve as potential diagnostic biomarkers in long-term COVID biomarkers of blood vascular transformation have great potential for diagnosis, and angiogenesis modulators may have therapeutic efficacy It has been shown that the vast majority of patients, in particular those suffering from type 2 diabetes, develop post-COVID-19 syndrome, and taking into account pre-existing diseases, post-COVID syndrome is not so harmless. By identifying common biomarkers and genetic associations, it is possible to identify the common molecular mechanism of post-COVID syndrome COVID-19 and diabetes mellitus. The novelty of disease association studies in the context of COVID-19 provides new insights into the management of rapidly evolving long-term COVID and post-COVID syndromes that have significant global implications.

Wetland technology for the treatment of HCH-contaminated water – Case study at Hajek site

Hexachlorocyclohexanes (HCH) isomers and their transformation products, such as chlorobenzenes (ClB), generate severe and persistent environmental problems at many sites worldwide. The Wetland technology employing oxidation-reduction, biosorption, biodegradation and phytoremediation methods can sufficiently treat HCH-contaminated water. The treatment process is inherently natural and requires no supplementary chemicals or energy. The prototype with a capacity of 3 L/s was installed at Hajek quarry spoil heap (CZ), to optimize the technology on a full scale. The system is fed by drainage water with an average concentration of HCH 129 μg/L, ClB 640 μg/L and chlorophenols (ClPh) of 16 μg/L. The system was tested in two years of operation, regularly monitored for HCH, ClB and ClPh, and maintained to improve its efficiency. The assessment was not only for environmental effects but also for socio and economic indicators. During the operation, the removal efficiency of HCH ranged from 53.5 % to 96.9 % (83.9 % on average) depending on the flow rate. Removal efficiency was not uniform for individual HCH isomers but exhibited the trend: α = γ = δ > β = ε. The improved water quality was reflected in a biodiversity increase expressed by a number of phytobenthos (diatoms) species, a common biomarker of aquatic environment quality. The Wetland outranked the conventional WWTP in 10 out of the 15 general categories, and it is the most relevant scenario from the socio, environmental, and economic aspects.

Clinical Utility of the Tokyo Guidelines 2018 for Acute Cholangitis in the Emergency Department and Comparison with Novel Markers (Neutrophil-to-Lymphocyte and Blood Nitrogen Urea-to-Albumin Ratios).

Introduction: The Tokyo Guidelines 2018 (TG2018) is a scoring system used to recommend the clinical management of AC. However, such a scoring system must incorporate a variety of clinical outcomes of acute cholangitis (AC). In an emergency department (ED)-based setting, where efficiency and practicality are highly desired, clinicians may find the application of various parameters challenging. The neutrophil-to-lymphocyte ratio (NLR) and blood urea nitrogen-to-albumin ratio (BAR) are relatively common biomarkers used to assess disease severity. This study evaluated the potential value of TG2018 scores measured in an ED to predict a variety of clinical outcomes. Furthermore, the study also compared TG2018 scores with NLR and BAR scores to demonstrate their usefulness. Methods: This retrospective observational study was performed in an ED. In total, 502 patients with AC visited the ED between January 2016 and December 2021. The primary endpoint was to evaluate whether the TG2018 scoring system measured in the ED was a predictor of intensive care, long-term hospital stays (≥14 days), percutaneous transhepatic biliary drainage (PTBD) during admission care, and endotracheal intubation (ETI). Results: The analysis included 81 patients requiring intensive care, 111 requiring long-term hospital stays (≥14 days), 49 requiring PTBD during hospitalization, and 14 requiring ETI during hospitalization. For the TG2018 score, the adjusted OR (aOR) using (1) as a reference was 23.169 (95% CI: 9.788-54.844) for (3) compared to (1). The AUC of the TG2018 for the need for intensive care was 0.850 (95% CI: 0.815-0.881) with a cutoff of >2. The AUC for long-term hospital stays did not exceed 0.7 for any of the markers. the AUC for PTBD also did not exceed 0.7 for any of the markers. The AUC for ETI was the highest for BAR at 0.870 (95% CI: 0.837-0.899) with a cutoff value of >5.2. Conclusions: The TG2018 score measured in the ED helps predict various clinical outcomes of AC. Other novel markers such as BAR and NLR are also associated, but their explanatory power is weak.

Photodynamic therapy upregulates expression of HIF-1α and PD-L1 in related pathways and its clinical relevance in non-small-cell lung cancer

BackgroundPhotodynamic therapy (PDT) is a promising interventional treatment approach that contributes to antitumor immunity. It has been reported that PDT can enhance the effectiveness of immune checkpoint inhibitors (ICIs), but its mechanism is yet unclear. Herein, we implemented bioinformatics analysis to detect common pathways and potential biomarkers in non-small cell lung cancer (NSCLC), PDT, and NSCLC immunotherapy to investigate potential links between PDT, immunotherapy and NSCLC, and their clinical impact.MethodsDifferentially expressed genes in NSCLC- and NSCLC immunotherapy-related data in the GEO database were intersected with PDT-related genes in the GeneCards database to obtain candidate genes and shared pathways. Enrichment analysis and protein–protein interaction were established to identify key genes in functionally enriched pathways. The expression profiles and the prognostic significance of key genes were depicted.ResultsBioinformatics analysis showed that HIF-1α was screened as a prognostic gene in hypoxia, HIF-1, and PD-L1-related signaling pathways, which was associated with clinical response in NSCLC patients after PDT and immunotherapy. In vivo experiments showed that PDT could inhibit tumor growth and upregulate HIF-1α and PD-L1 expressions in NSCLC tissues with a positive correlation, which might influence the blocking activity of ICIs on the HIF-1, and PD-L1-related signaling pathways.ConclusionsPDT might improve the clinical response of ICIs by upregulating tumor HIF-1α and PD-L1 expressions in NSCLC.

Pick a PACC: Comparing domain-specific and general cognitive composites in Alzheimer disease research.

We aimed to illustrate how complex cognitive data can be used to create domain-specific and general cognitive composites relevant to Alzheimer disease research. Using equipercentile equating, we combined data from the Charles F. and Joanne Knight Alzheimer Disease Research Center that spanned multiple iterations of the Uniform Data Set. Exploratory factor analyses revealed four domain-specific composites representing episodic memory, semantic memory, working memory, and attention/processing speed. The previously defined preclinical Alzheimer disease cognitive composite (PACC) and a novel alternative, the Knight-PACC, were also computed alongside a global composite comprising all available tests. These three composites allowed us to compare the usefulness of domain and general composites in the context of predicting common Alzheimer disease biomarkers. General composites slightly outperformed domain-specific metrics in predicting imaging-derived amyloid, tau, and neurodegeneration burden. Power analyses revealed that the global, Knight-PACC, and attention and processing speed composites would require the smallest sample sizes to detect cognitive change in a clinical trial, while the Alzheimer Disease Cooperative Study-PACC required two to three times as many participants. Analyses of cognition with the Knight-PACC and our domain-specific composites offer researchers flexibility by providing validated outcome assessments that can equate across test versions to answer a wide range of questions regarding cognitive decline in normal aging and neurodegenerative disease. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Identification of shared potential diagnostic markers in asthma and depression through bioinformatics analysis and machine learning

BackgroundThere is mounting evidence that asthma might exacerbate depression. We sought to examine candidates for diagnostic genes in patients suffering from asthma and depression. MethodsMicroarray data were downloaded from the Gene Expression Omnibus(GEO) database and used to screen for differential expressed genes(DEGs) in the SA and MDD datasets. A weighted gene co-expression network analysis(WGCNA) was used to identify the co-expression modules of SA and MDD. The least absolute shrinkage and selection operatoes(LASSO) and support vector machine(SVM) were used to determine critical biomarkers. Immune cell infiltration analysis was used to investigate the correlation between immune cell infiltration and common biomarkers of SA and MDD. Finally, validation of these analytical results was accomplished via the use of both in vivo and in vitro studies. ResultsThe number of DEGs that were included in the MDD dataset was 5177, whereas the asthma dataset had 1634 DEGs. The intersection of DEGs for SA and MDD included 351 genes, the strongest positive modules of SA and MDD was 119 genes, which played a function in immunity. The intersection of DEGs and modular hub genes was 54, following the analysis using machine learning algorithms,three hub genes were identified and employed to formulate a nomogram and for the evaluation of diagnostic effectiveness, which demonstrated a significant diagnostic value (area under the curve from 0.646 to 0.979). Additionally, immunocyte disorder was identified by immune infiltration. In vitro studies have revealed that STK11IP deficiency aggravated the LPS/IFN-γinduced up-regulation in M1 macrophage activation. ConclusionAsthma and MDD pathophysiology may be associated with alterations in inflammatory processes and immune pathways. Additionally, STK11IP may serve as a diagnostic marker for individuals with the two conditions.

Atrial Fibrillation and Clonal Hematopoiesis in TET2 and ASXL1

Clonal hematopoiesis of indeterminate potential (CHIP) may contribute to the risk of atrial fibrillation (AF) through its association with inflammation and cardiac remodeling. To determine whether CHIP was associated with AF, inflammatory and cardiac biomarkers, and cardiac structural changes. This was a population-based, prospective cohort study in participants of the Atherosclerosis Risk in Communities (ARIC) study and UK Biobank (UKB) cohort. Samples were collected and echocardiography was performed from 2011 to 2013 in the ARIC cohort, and samples were collected from 2006 to 2010 in the UKB cohort. Included in this study were adults without hematologic malignancies, mitral valve stenosis, or previous mitral valve procedure from both the ARIC and UKB cohorts; additionally, participants without hypertrophic cardiomyopathy and congenital heart disease from the UKB cohort were also included. Data analysis was completed in 2023. CHIP (variant allele frequency [VAF] ≥2%), common gene-specific CHIP subtypes (DNMT3A, TET2, ASXL1), large CHIP (VAF ≥10%), inflammatory and cardiac biomarkers (high-sensitivity C-reactive protein, interleukin 6 [IL-6], IL-18, high-sensitivity troponin T [hs-TnT] and hs-TnI, N-terminal pro-B-type natriuretic peptide), and echocardiographic indices. Incident AF. A total of 199 982 adults were included in this study. In ARIC participants (4131 [2.1%]; mean [SD] age, 76 [5] years; 2449 female [59%]; 1682 male [41%]; 935 Black [23%] and 3196 White [77%]), 1019 had any CHIP (24.7%), and 478 had large CHIP (11.6%). In UKB participants (195 851 [97.9%]; mean [SD] age, 56 [8] years; 108 370 female [55%]; 87 481 male [45%]; 3154 Black [2%], 183 747 White [94%], and 7971 other race [4%]), 11 328 had any CHIP (5.8%), and 5189 had large CHIP (2.6%). ARIC participants were followed up for a median (IQR) period of 7.0 (5.3-7.7) years, and UKB participants were followed up for a median (IQR) period of 12.2 (11.3-13.0) years. Meta-analyzed hazard ratios for AF were 1.12 (95% CI, 1.01-1.25; P = .04) for participants with vs without large CHIP, 1.29 (95% CI, 1.05-1.59; P = .02) for those with vs without large TET2 CHIP (seen in 1340 of 197 209 [0.67%]), and 1.45 (95% CI, 1.02-2.07; P = .04) for those with vs without large ASXL1 CHIP (seen in 314 of 197 209 [0.16%]). Large TET2 CHIP was associated with higher IL-6 levels. Additionally, large ASXL1 was associated with higher hs-TnT level and increased left ventricular mass index. Large TET2 and ASXL1, but not DNMT3A, CHIP was associated with higher IL-6 level, indices of cardiac remodeling, and increased risk for AF. Future research is needed to elaborate on the mechanisms driving the associations and to investigate potential interventions to reduce the risk.

Methylation patterns associated with C-reactive protein in racially and ethnically diverse populations

ABSTRACT Systemic low-grade inflammation is a feature of chronic disease. C-reactive protein (CRP) is a common biomarker of inflammation and used as an indicator of disease risk; however, the role of inflammation in disease is not completely understood. Methylation is an epigenetic modification in the DNA which plays a pivotal role in gene expression. In this study we evaluated differential DNA methylation patterns associated with blood CRP level to elucidate biological pathways and genetic regulatory mechanisms to improve the understanding of chronic inflammation. The racially and ethnically diverse participants in this study were included as 50% White, 41% Black or African American, 7% Hispanic or Latino/a, and 2% Native Hawaiian, Asian American, American Indian, or Alaska Native (total n = 13,433) individuals. We replicated 113 CpG sites from 87 unique loci, of which five were novel (CADM3, NALCN, NLRC5, ZNF792, and cg03282312), across a discovery set of 1,150 CpG sites associated with CRP level (p < 1.2E–7). The downstream pathways affected by DNA methylation included the identification of IFI16 and IRF7 CpG-gene transcript pairs which contributed to the innate immune response gene enrichment pathway along with NLRC5, NOD2, and AIM2. Gene enrichment analysis also identified the nuclear factor-kappaB transcription pathway. Using two-sample Mendelian randomization (MR) we inferred methylation at three CpG sites as causal for CRP levels using both White and Black or African American MR instrument variables. Overall, we identified novel CpG sites and gene transcripts that could be valuable in understanding the specific cellular processes and pathogenic mechanisms involved in inflammation.

Temporal Ordering of Biomarkers in Dutch-Type Hereditary Cerebral Amyloid Angiopathy.

The temporal ordering of biomarkers for cerebral amyloid angiopathy (CAA) is important for their use in trials and for the understanding of the pathological cascade of CAA. We investigated the presence and abnormality of the most common biomarkers in the largest (pre)symptomatic Dutch-type hereditary CAA (D-CAA) cohort to date. We included cross-sectional data from participants with (pre)symptomatic D-CAA and controls without CAA. We investigated CAA-related cerebral small vessel disease markers on 3T-MRI, cerebrovascular reactivity with functional 7T-MRI (fMRI) and amyloid-β40 and amyloid-β42 levels in cerebrospinal fluid. We calculated frequencies and plotted biomarker abnormality according to age to form scatterplots. We included 68 participants with D-CAA (59% presymptomatic, mean age, 50 [range, 26-75] years; 53% women), 53 controls (mean age, 51 years; 42% women) for cerebrospinal fluid analysis and 36 controls (mean age, 53 years; 100% women) for fMRI analysis. Decreased cerebrospinal fluid amyloid-β40 and amyloid-β42 levels were the earliest biomarkers present: all D-CAA participants had lower levels of amyloid-β40 and amyloid-β42 compared with controls (youngest participant 30 years). Markers of nonhemorrhagic injury (>20 enlarged perivascular spaces in the centrum semiovale and white matter hyperintensities Fazekas score, ≥2, present in 83% [n=54]) and markers of impaired cerebrovascular reactivity (abnormal BOLD amplitude, time to peak and time to baseline, present in 56% [n=38]) were present from the age of 30 years. Finally, markers of hemorrhagic injury were present in 64% (n=41) and only appeared after the age of 41 years (first microbleeds and macrobleeds followed by cortical superficial siderosis). Our results suggest that amyloid biomarkers in cerebrospinal fluid are the first to become abnormal in CAA, followed by MRI biomarkers for cerebrovascular reactivity and nonhemorrhagic injury and lastly hemorrhagic injury. This temporal ordering probably reflects the pathological stages of CAA and should be taken into account when future therapeutic trials targeting specific stages are designed.

Investigation of Common Pathways and Putative Biomarker Candidates of Colorectal Cancer and Insomnia by Using Integrative In-Silico Approaches.

Colorectal cancer (CRC) is one of the leading causes of cancer-related mortalities across the globe. Accumulating evidence shows that individuals having sleep disorders such as insomnia are at high risk of developing CRC, yet the association of sleep disorders with CRC risk is still unclear. Here, we investigated the potential molecular connections between CRC and insomnia using integrative in silico approaches. This study aims to explore the potential molecular connections between CRC and insomnia utilizing integrative in-silico methodologies. Gene expression microarray datasets for CRC and insomnia samples were retrieved from the NCBI-GEO database and analyzed using R. Functional enrichment analysis of common differentially expressed genes (DEGs) was performed by the g: Profiler tool. Cytoscape software was used to construct a protein-protein interaction network and hub gene identification. Expression profiles of hub genes in TCGA datasets were also determined, and predicted miRNAs targeting hub genes were analyzed by miRNA target prediction tools. Our results revealed a total of 113 shared DEGs between the CRC and insomnia datasets. Six genes (HSP8A, GAPDH, HSP90AA1, EEF1G, RPS6, and RPLP0), which were also differently expressed in TCGA datasets, were prioritized as hub genes and were found to be enriched in pathways related to protein synthesis. hsa-miR-324-3p, hsa-miR-769-3p, and hsa-miR-16-5p were identified as promising miRNA biomarkers for two diseases. Our in-silico analysis provides promising evidence of the molecular link between CRC and insomnia and highlights multiple potential molecular biomarkers and pathways. Validation of the results by wet lab work can be utilized for novel translational and precision medicine applications to alleviate the public health burden of CRC.

Neutrophil to Hemoglobin Lymphocyte Ratio (NHLR) as a Novel Biomarker is Superior to Neutrophil Lymphocyte Ratio (NLR) and Platelet Lymphocyte Ratio (PLR) as Predictors of Advanced Colorectal Cancer

Background: Neutrophils, Hemoglobin, and Lymphocytes are biological markers that may be related to the colorectal cancer stage. Neutrophils to Hemoglobin-Lymphocytes Ratio (NHLR) is a new biomarker that will be tested with Neutrophil Lymphocyte Ratio (NLR) and Platelet Lymphocyte Ratio (PLR) as common biomarkers that have been shown to have predictive value with colorectal cancer stage. This study aims to prove NHLR as a new biomarker that can predict advanced colorectal cancer in terms of staging and site of cancer compared to NLR and PLR. Methods: This is a retrospective cross-sectional study. Data obtained from the medical records of colorectal cancer patients undergoing surgery at Dr Sardjito Hospital from 2020 until 2022. Results: 386 patients enrolled in the study, and 62 patients met the inclusion criteria. Twentyeight patients (45.16 %) were male, and 34 (54.84 %) were female. The mean age is 58.82 years. Bivariate analysis showed a significant relationship between NHLR, NLR, and PLR with colorectal cancer stage and significant differences between NHLR and NLR with early and advanced colorectal cancer, but not with PLR. There are also significant differences between NHLR, NLR, and PLR with colorectal cancer sites in the colon and rectum. Still, in locally advanced stages of colorectal cancer, there is no significant association between NLR and cancer sites. On the contrary, there are significant differences between colon and rectal cancer sites with NHLR and PLR. Conclusions: NHLR is superior to NLR and PLR in predicting the stage and site of advanced colorectal cancer.

Study on the Neuroprotective Effects of Eight Iridoid Components Using Cell Metabolomics.

Iridoid components have been reported to have significant neuroprotective effects. However, it is not yet clear whether the efficacy and mechanisms of iridoid components with similar structures are also similar. This study aimed to compare the neuroprotective effects and mechanisms of eight iridoid components (catalpol (CAT), genipin (GE), geniposide (GEN), geniposidic acid (GPA), aucubin (AU), ajugol (AJU), rehmannioside C (RC), and rehmannioside D (RD)) based on corticosterone (CORT)-induced injury in PC12 cells. PC12 cells were randomly divided into a normal control group (NC), model group (M), positive drug group (FLX), and eight iridoid administration groups. Firstly, PC12 cells were induced with CORT to simulate neuronal injury. Then, the MTT method and flow cytometry were applied to evaluate the protective effects of eight iridoid components on PC12 cell damage. Thirdly, a cell metabolomics study based on ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UPLC-Q/TOF-MS) was performed to explore changes in relevant biomarkers and metabolic pathways following the intervention of administration. The MTT assay and flow cytometry analysis showed that the eight iridoid components can improve cell viability, inhibit cell apoptosis, reduce intracellular ROS levels, and elevate MMP levels. In the PCA score plots, the sample points of the treatment groups showed a trend towards approaching the NC group. Among them, AU, AJU, and RC had a weaker effect. There were 38 metabolites (19 metabolites each in positive and negative ion modes, respectively) identified as potential biomarkers during the experiment, among which 23 metabolites were common biomarkers of the eight iridoid groups. Pathway enrichment analysis revealed that the eight iridoid components regulated the metabolism mainly in relation to D-glutamine and D-glutamate metabolism, arginine biosynthesis, the TCA cycle, purine metabolism, and glutathione metabolism. In conclusion, the eight iridoid components could reverse an imbalanced metabolic state by regulating amino acid neurotransmitters, interfering with amino acid metabolism and energy metabolism, and harmonizing the level of oxidized substances to exhibit neuroprotective effects.