Biomarker Profiles Research Articles

Highly specific amyloid and tau PET ligands for ATN classification in suspected Alzheimer's disease patients.

This study aims to accurately classify ATN profiles using highly specific amyloid and tau PET ligands and MRI in patients with cognitive impairment and suspected Alzheimer's disease (AD). It also aims to explore the relationship between quantified amyloid and tau deposition and cognitive function. Twenty-seven patients (15 women and 12 men; age range: 64-81years) were included in this study. Amyloid and tau PET scans were performed using 18F-NAV4694 and 18F-MK6240, respectively. For each patient, amyloid and tau PET images were visually assessed and classified as either amyloid-positive or amyloid-negative, and as 18F-MK6240 Braak stage 0 (tau-negative) or Braak stages I-VI (tau-positive). Voxel-based morphometry of three-dimensional T1-weighted MRI was used to evaluate neurodegeneration. Amyloid and tau depositions were quantified using the Centiloid scale and standardized uptake value ratio (SUVR), respectively. Global cognitive function was assessed with the Mini-Mental State Examination (MMSE). Patients were categorized into seven ATN profiles. Six patients (22%) exhibited a normal AD biomarker profile, 15 patients (56%) fell within the Alzheimer's continuum, and 14 patients (52%) were diagnosed with AD. Additionally, six patients (22%) displayed non-AD pathological changes. Positive and negative findings of amyloid and tau PET were concordant in 24 patients (89%). Among the 14 patients diagnosed with AD, the Centiloid scale for amyloid deposition did not show a significant negative correlation with MMSE scores (r = 0.269, p = 0.451). In contrast, the SUVR for tau deposition in the neocortex exhibited a significant negative correlation (r = -0.689, p = 0.014), while tau deposition in the mesial temporal region did not show a significant correlation (r = 0.158, p = 0.763). Highly specific amyloid and tau PET scans, along with MRI, can be utilized to accurately classify ATN profiles in patients with cognitive impairment and suspected AD. The discordance in amyloid and tau PET findings in three patients allowed for a more precise AD diagnosis. Furthermore, tau PET imaging provided insight into the propagation of tau deposition in the neocortex beyond the mesial temporal region, which is associated with cognitive decline.

CSF cytokine, chemokine and injury biomarker profile of glial fibrillary acidic protein (GFAP) autoimmunity.

Defining the CSF cytokine/chemokine and injury biomarker signature of glial fibrillary acidic protein (GFAP) autoimmunity can inform immunopathogenesis. CSF GFAP-IgG-positive samples (N = 98) were tested for 17 cytokines/chemokines, neurofilament light chain (NfL), and GFAP (ELLA, Bio-Techne). Controls included non-inflammatory (N = 42), AQP4-IgG-positive (N = 83), CNS infections (N = 13), and neurosarcoidosis (N = 32). IL5, IL6, IL10, IL8/CXCL8, CXCL9, CXCL10, CXCL13, BAFF, GM-CSF, IFN-gamma, and TNF-alpha concentrations were higher compared to non-inflammatory controls (P < 0.01). GFAP concentrations were similar to those of AQP4-IgG-positive patients; NfL was higher (P < 0.001) and correlated with MRI changes and outcomes. CSF cytokine/chemokine findings in GFAP autoimmunity correlate with histopathology; GFAP and NfL hold promise as disease biomarkers.

A multidimensional fecal microbial and inflammatory biomarker profiling in preterm and full-term neonates.

Preterm birth affects approximately one in every ten neonates. The clinical outcomes depend on care and management factors, including the birth delivery method and the use of antibiotics. This observational cohort study determined antimicrobial peptides, proteases, metabolomic, and microbiome profiles in fecal samples collected from 20 preterm and nine full-term neonates 48 h after birth. The results show that preterm neonates have increased levels of α-defensins, serine proteases, and matrix metalloproteinases. They also have distinct metabolic signatures characterized by decreased kynurenic acid and increased mevalonate levels. These neonates also exhibit reduced microbial diversity. This study highlights that heightened immune response and proteolytic activity, marked dysbiosis, and reduced short-chain fatty acids within the preterm gastrointestinal tract immediately after birth might predispose neonates to exacerbated gut inflammation. Some of the findings, including the elevated fecal mevalonate levels, are potential biomarkers in neonatology for early identification of metabolic disturbances linked to gut inflammation, emphasizing further studies to explore its association with inflammatory conditions in preterm infants. Inflammatory markers that can predict intestinal disorders are insufficiently characterized in preterm neonates. This study identified antimicrobial peptide responses, proteolytic activity, marked dysbiosis, and reduced short-chain fatty acid production in feces from preterm neonates. These critical differences in inflammatory, metabolomic, and microbial signatures may predispose to exacerbated gut inflammation in preterm neonates. Some inflammatory effectors in feces are potential biomarkers for the early detection of intestinal inflammatory conditions in preterm neonates. This study contributes to understanding the inflammatory conditions in the guts of preterm babies and identifies novel targets for timely diagnosis, interventions, and management practices in neonatal care.

Digital Profiling of Immune Biomarkers in Breast Cancer: Relation to Anthracycline Benefit.

Assessment of the tumor immune microenvironment can be used as a prognostic tool for improved survival and as a predictive biomarker for treatment benefit, particularly from immune modulating treatments including cytotoxic chemotherapy. Using Digital Spatial Profiling (DSP), we studied the tumor immune microenvironment of 522 breast cancer cases by quantifying 35 immune biomarkers on tissue microarrays from the MA.5 phase III clinical trial. In this trial, node-positive breast cancer patients were randomized to receive either a non-anthracycline chemotherapy (CMF) or anthracycline-containing cytotoxic chemotherapy (CEF). Donor block hematoxylin and eosin (H&E)-stained sections were scored for the level of stromal tumor infiltrating lymphocytes (sTILs), according to the international guidelines. We hypothesized that patients with higher levels of tumor immune infiltration, assessed by either DSP or H&E staining, would benefit from CEF (relative to CMF) more than patients with lower immune infiltration. Unsupervised hierarchical clustering of digitally scored biomarkers revealed two patient clusters: immune infiltrated vs. ignored. Following a pre-specified statistical plan crafted to meet ReMARK guidelines, we found that the DSP-derived Immune Cluster assignment did not predict an improved 10-year relapse-free survival for patients receiving CEF compared to CMF. However, a secondary hypothesis revealed a significant predictive value for H&E-sTILs assessed on full-faced sections for CEF benefit over CMF in the entire cohort and the HER2-enriched subset. As exploratory analyses, supervised clustering of DSP scored biomarkers suggested that low levels of TIM-3 and high levels of HLA-DR and PD-L1 are associated with sensitivity to CEF. Although novel high-plex techniques provide a detailed insight into the tumor microenvironment, conventional H&E staining remains a powerful tool that can be applied onto full-faced sections to assess the value of immune microenvironment, particularly sTILs, in predicting benefits from immunogenic chemotherapies.

OP19 Pre- and Post-diagnostic Metabolomic Biomarker Profiling of Over 700,000 Individuals in Three National Biobanks Enables Prediction of Inflammatory Bowel Disease Onset and Complications

Abstract Background We currently lack sensitive and specific prognostic biomarkers of inflammatory bowel disease (IBD) onset and severity. In three large, population-scale cohorts, we investigated metabolomic biomarkers for predicting disease onset and course. Methods We measured 250 metabolomic biomarkers using nuclear magnetic resonance (NMR) in ~500,000 individuals from the UK Biobank [1]. 2036 individuals had prevalent Crohn’s disease (CD) and 4029 had ulcerative colitis (UC) at recruitment. 1242 participants developed incident CD and 2283 incident UC during 10-year follow-up, allowing us to study the pre-diagnostic metabolic profile of IBD. We investigated associations between individual metabolomic biomarkers with prevalent and incident IBD using logistic and proportional hazards regressions. Among the incident IBD cohort we used LASSO with five-fold cross-validation on 50% of the cohort to build predictive models of future IBD onset. The resulting predictive model was validated in the Estonian Biobank and the Finnish THL Biobank (N ~218,000), confirming its robustness in multiple cohorts. Finally, in the UK Biobank we identified individuals with prevalent IBD who had IBD-related emergency admission, surgery or death and used these to develop a disease course score. Results GlycA, a biomarker of systemic inflammation, was the strongest association for both incident and prevalent UC and CD. We also identified associations between non-inflammatory metabolomic markers and IBD, such as albumin, branched-chain amino acids, cardiovascular lipid factors, fatty acids and creatinine. Notably, the perturbation in metabolites was markedly greater in CD versus UC, showing that CD is a more systemic illness (Fig. 1). Metabolomics scores were predictive of CD (AUC=0.69) and UC (0.62) onset up to 10 years prior to diagnosis, with performance for CD improving closer to diagnosis (2y follow-up AUC: CD 0.76, UC 0.62). Patients in the highest decile of incident metabolomic score were substantially more likely to develop the disease, with this observation being consistent in other two biobanks (Fig. 2). Metabolite profiles were predictive of IBD complications in prevalent patients (AUC 0.68 for CD; 0.62 for UC), outperforming both genetic and blood biomarker scores. Conclusion Leveraging cohort-wide profiling of population-scale biobanks, we present the largest metabolomics study and the largest pre-diagnostic study of IBD to date. Pre-diagnostic metabolomic scores are predictive of disease onset. These results warrant further investigation of multi-omic prediction of the onset, comorbidities and disease course of IBD. References * A.S, K.S. contributed equally. # T.J., J.C.B., C.L. contributed equally. [1] Nightingale Health Biobank Collaborative Group, Barrett, J. C., Esko, T., Fischer, K., Jostins-Dean, L., Jousilahti, P., ... &amp; Estonian Biobank Research Team. (2023). Metabolomic and genomic prediction of common diseases in 477,706 participants in three national biobanks. medRxiv, 2023-06. Figure 1: Associations between clinically validated biomarkers and prevalent IBD Figure 2: UK Biobank-derived score consistency across the three biobanks

Exploring the ability of plasma pTau217, pTau181 and beta-amyloid in mirroring cerebrospinal fluid biomarker profile of Mild Cognitive Impairment by the fully automated Lumipulse® platform

BackgroundThe approval of new disease-modifying therapies by the U.S. Food and Drug Administration and the European Medicine Agency makes it necessary to optimize non-invasive and cost-effective tools for the identification of subjects at-risk of developing Alzheimer’s Disease (AD). Plasma biomarkers are excellent candidates. However, their ability to reflect the cerebrospinal fluid (CSF) profile - that remains to date the gold standard for the biochemical diagnosis of AD - needs to be confirmed and validated before their implementation in clinical practice. The aims of this study are to analyse the correlation between CSF and plasma Aβ40, Aβ42, Aβ42/Aβ40 and pTau181, and to assess the diagnostic performance of plasma biomarkers in a cohort of subjects affected by Mild Cognitive Impairment (MCI).MethodsThe study was performed on 306 subjects affected by MCI, enrolled in the context of the Italian Interceptor Project. Aβ40, Aβ42 and pTau181 were analysed in plasma and CSF, and pTau217 was measured in plasma. The fully automated chemiluminescence enzyme immunoassay and the Lumipulse® G600II (Fujirebio) instrument were used for all measurements. We analysed the correlations between CSF and plasma biomarkers and the differences of plasma biomarker concentrations after grouping MCI cases according to AT classification of CSF AD biomarker profiles.ResultsWe found statistically significant positive correlations between CSF and plasma Aβ42, Aβ42/Aβ40 ratio and pTau181. All the biomarkers, except Aβ40, showed differences in A+ vs. A-, A+T+ vs. A-T- and A+T- vs. A-T- patients. Moreover, Aβ42 and Aβ42/Aβ40 plasma levels were lower in A+T- compared to A-T- and A-T+ groups, and pTau181 and pTau217 plasma levels were higher in A+T+ compared to A+T-. Aβ42/Aβ40 and pTau217 showed a robust performance in distinguishing A+ from A- (AUC = 0.857 and 0.862, respectively) and A+T+ from A-T- (AUC = 0.866 and 0.911) subjects.ConclusionsOur results suggest that plasma biomarkers, and especially Aβ42/Aβ40 ratio and pTau217, are promising candidates for the early detection of AD pathology.

Proinflammatory cytokine genes and their polymorphic variants: clinical and laboratory profiles in the Federal Firefighting Service employees of the EMERCOM of Russia

Relevance. Genetic determinants of multifactorial diseases are critical for assessing the risk of genetic diseases and their prevention, especially among the workforce exposed to industry-related dangerous and aggressive occupational factors. Firefighters perform combat service duties in extremely unfavorable industrial environments associated with occupational diseases. Respiratory diseases are among the pathologies with highest incidence rates in firefighters. In addition to environmental factors, the development of these diseases (especially bronchial asthma and chronic obstructive pulmonary disease) is largely driven by impaired immune system – one of the three critical regulatory systems involved in pathogenetic mechanisms of various diseases, including inflammatory diseases. Polymorphic gene variants of inflammatory mediators – in particular cytokine genes and their receptors – mediate the immune system activity and can impact its functionality, susceptibility, or resistance to disease development.The objective is to analyze how interleukin 1β, 4, 6, 13, TNF and interleukin 6 receptor genes, as well as their polymorphic variants are associated with respiratory diseases and changes in the biomarker profiles showing immune response intensity in the employees of the Federal Firefighting Service of the EMERCOM of Russia. Methodology. Molecular genetic profiling and immunology tests were performed in 70 employees of the Federal Firefighting Service of the EMERCOM of Russia to analyze proinflammatory cytokine genes and their polymorphic variants. Real-timePCR was used to analyze the interleukin 1β, 4, 6, 13, TNF and interleukin-6 receptor genes and their polymorphic variants. Immunological examination evaluated the blood monocyte subpopulations and relative count of type 2 T-helper cells; flowcytometry and immunochemiluminescence assays were used to evaluate immune response biomarkers in peripheral blood and total immunoglobulin E (IgE) respectively.Results and discussion. The analysis provides evidence that minor alleles of most polymorphic cytokine genes are associated with a proinflammatory phenotype, which is especially apparent for genotypes comprising several minor alleles. Allele A at rs1 800 629 polymorphic TNF gene exposed a direct correlation with respiratory diseases, as well as with increased monocyte differentiation. Allele T of IL4 rs2243250 gene and allele A of IL1β rs16944 gene were associated with increased proinflammatory monocyte count. Elevated count of type 2 T-helper mediators of humoral response, especially of allergicorigin, was observed in individuals with C/C IL6 rs1 800 795 and G/G IL1β rs16944 genotype.Conclusion. The obtained results suggest that evaluation of cytokine gene polymorphic variants is a promising strategy to predict the risk of respiratory diseases in firefighters. Prompt assessment of genetic predisposition to a proinflammatory phenotype paves the way towards prevention and early detection of inflammatory diseases in this cohort of workers.

Characterizing biomarkers of ageing in Singaporeans: the ABIOS observational study protocol.

Ageing is the primary driver of age-associated chronic diseases and conditions. Asian populations have traditionally been underrepresented in studies understanding age-related diseases. Thus, the Ageing BIOmarker Study in Singaporeans (ABIOS) aims to characterise biomarkers of ageing in Singaporeans, exploring associations between molecular, physiological, and digital biomarkers of ageing. This is a single-centre, cross-sectional study that recruits healthy community-dwelling adults (≥ 21 years) from three different ethnic groups (Chinese, Malay, and Indian). Molecular biomarkers of ageing include multi-omics approaches, such as DNA methylation analysis and metabolic and inflammatory proteomic profiling in blood, saliva, and stool. Physiological biomarkers of ageing include bone density, body composition, skin autofluorescence, arterial stiffness, physical performance (e.g., muscle strength and flexibility), cognition, and nutritional status. Digital biomarkers of ageing include three-dimensional facial morphology and objectively measured physical activity. Additional measures, such as habitual physical activity, dietary patterns, and medical history, are also examined. The associations between the molecular, physiological, and digital phenotypes will be explored. This study is expected to generate a comprehensive profile of molecular, physiological, and digital biomarkers of ageing in Chinese, Malay, and Indian populations in Singapore. By integrating diverse age-related biomarkers, clinical indicators, and lifestyle factors, ABIOS will offer unique insights into the ageing process specific to Southeast Asian populations. These findings can help identify markers of biological ageing, uncover ethnic-specific patterns, and reveal modifiable lifestyle factors for healthier ageing. The results could inform evidence-based health policies, personalized interventions, and future cross-ethnic comparative studies to enhance understanding of ageing biology across diverse populations.

Immunohistochemical Profiling of Histone Modification Biomarkers Identifies Subtype-Specific Epigenetic Signatures and Potential Drug Targets in Breast Cancer.

Breast cancer (BC) subtypes exhibit distinct epigenetic landscapes, with triple-negative breast cancer (TNBC) lacking effective targeted therapies. This study investigates histone biomarkers and therapeutic vulnerabilities across BC subtypes. The immunohistochemical profiling of >20 histone biomarkers, including histone modifications, modifiers, and oncohistone mutations, was conducted on a discovery cohort and a validation cohort of BC tissues, healthy controls, and cell line models. Transcriptomic and cell growth analyses were conducted to evaluate the effects of the small-molecule G9a inhibitor in diverse BC models. Key histone biomarkers, including H3K9me2, H3K36me2, and H3K79me, were differentially expressed across BC subtypes. H3K9me2 emerged as an independent predictor for distinguishing TNBC from other less-aggressive BC subtypes, with elevated expression correlating with higher tumor grade and stage. G9a inhibition impaired cell proliferation and modulated epithelial-mesenchymal transition pathways, with the strongest impact in basal-like TNBC. The disruption of the oncogene and tumor suppressor regulation (e.g., TP53, SATB1) was observed in TNBC. This study highlights G9a's context-dependent roles in BC, supporting its potential as a therapeutic target. The findings provide a foundation for subtype-specific epigenetic therapies to improve outcomes in aggressive BC subtypes.

Blood biomarker profiles in young-onset neurocognitive disorders: A cohort study.

Young-onset neurocognitive symptoms result from a heterogeneous group of neurological and psychiatric disorders which present a diagnostic challenge. To identify such factors, we analysed the Biomarkers in Younger-Onset Neurocognitive Disorders cohort, a study of individuals <65 years old presenting with neurocognitive symptoms for a diagnosis and who have undergone cognitive and biomarker analyses. Sixty-five participants (median age at assessment of 56 years, 45% female) were recruited during their index presentation to the Royal Melbourne Hospital Neuropsychiatry Centre, a tertiary specialist service in Melbourne, Australia, and categorized as either early-onset Alzheimer's disease (n = 18), non-Alzheimer's disease neurodegeneration (n = 23) or primary psychiatric disorders (n = 24). Levels of neurofilament light chain, glial fibrillary acidic protein and phosphorylated-tau 181, apolipoprotein E genotype and late-onset Alzheimer's disease polygenic risk scores were determined. Information-theoretic model selection identified discriminatory factors. Neurofilament light chain, glial fibrillary acidic protein and phosphorylated-tau 181 levels were elevated in early-onset Alzheimer's disease compared with other diagnostic categories. A multi-omic model selection identified that a combination of cognitive and blood biomarkers, but not the polygenic risk score, discriminated between early-onset Alzheimer's disease and primary psychiatric disorders (area under the curve ⩾ 0.975, 95% confidence interval: 0.825-1.000). Phosphorylated-tau 181 alone significantly discriminated between early-onset Alzheimer's disease and non-Alzheimer's disease neurodegeneration causes (area under the curve = 0.950, 95% confidence interval: 0.877-1.00). Discriminating between early-onset Alzheimer's disease, non-Alzheimer's disease neurodegeneration and primary psychiatric disorders causes of young-onset neurocognitive symptoms is possible by combining cognitive profiles with blood biomarkers. These results support utilizing blood biomarkers for the work-up of young-onset neurocognitive symptoms and highlight the need for the development of a young-onset Alzheimer's disease-specific polygenic risk score.

Inflammatory biomarkers profiles and cognition among older adults

Inflammation plays a major role in cognitive aging. Most studies on peripheral inflammation and cognitive aging focused on selected major inflammatory biomarkers. However, inflammatory markers are regulated and influenced by each other, and it is therefore important to consider a more comprehensive panel of markers to better capture diverse immune pathways and characterize the overall inflammatory profile of individuals. We explored 23 circulating inflammatory biomarkers using data from 1,743 participants without dementia (≥ 65 years-old) from the community-based, multiethnic Washington Heights Inwood Columbia Aging Project. Using principal component analysis (PCA), we developed six inflammatory profiles (PC-1 to PC-6) based on these 23 biomarkers and tested the association of resulting inflammatory profile with cognitive decline, over up to 12 years of follow-up. PC-1 described a pro-inflammatory profile characterized by high positive loadings for pro-inflammatory biomarkers. A higher PC-1 score was associated with lower baseline cognitive performances. No association of this profile with cognitive decline was observed in longitudinal analysis. However, PC-5 characterized by high PDGF-AA and RANTES was associated with a faster cognitive decline. Among older adults, a circulating pro-inflammatory immune profile is associated with lower baseline cognitive performance, and some specific pro-inflammatory cytokines might be associated with faster cognitive decline.

Detecting early cognitive deficits in preclinical Alzheimer’s disease using a remote digital multi-day learning paradigm

Remote, digital cognitive testing on an individual’s own device provides the opportunity to deploy previously understudied but promising cognitive paradigms in preclinical Alzheimer’s disease (AD). The Boston Remote Assessment for NeuroCognitive Health (BRANCH) captures a personalized learning curve for the same information presented over seven consecutive days. Here, we examined BRANCH multi-day learning curves (MDLCs) in 167 cognitively unimpaired older adults (age = 74.3 ± 7.5, 63% female) with different amyloid-β (A) and tau (T) biomarker profiles on positron emission tomography. MDLC scores decreased across ascending biomarker groups, with the A + T- group performing numerically worse (β = –0.24, 95%CI[–0.55,0.07], p = 0.128) and the A + T+ group performing significantly worse (β = –0.58, 95%CI[–1.06,–0.10], p = 0.018) than the A-T- group. Further, lower MDLC scores were associated with greater cortical thinning (β = 0.18, 95%CI[0.04,0.34], p = 0.013). Our results suggest that diminished MDLCs track with advanced AD pathophysiology, and demonstrate how a digital multi-day learning paradigm can provide novel insights about cognitive decline during preclinical AD.

Microbiome and Inflammatory Biomarkers Associated With Palatal Wound Healing.

The clinical outcomes of a variety of surgical procedures highly depend on tissue repair and show high variability among patients. There is a gap in the literature on how the host inflammatory response, the microbiome, and the interplay between them can influence oral mucosa healing. In this pilot study, we aimed to evaluate the microbiome and biomarkers profiles in patients who had desired versus undesired wound healing in the palatal mucosa. Seventeen patients underwent a free gingival graft (FGG) for socket preservation. Palatal wound closure (WC) and epithelization (EPT) were assessed clinically. Biofilm from the palatal wound was collected before the surgical procedure and 3, 7, 14, and 30 days postoperatively. The inflammatory exudate was sampled on Days 3 and 7. At 14 days posttreatment, patients were classified into two groups based on EPT rates: (1) undesired healing (UH) and (2) desired healing (DH). No difference was observed in alfa diversity over time or between groups. In beta diversity, both UH and DH showed microbiome changes on Days 3-7 and 7, respectively, compared with the baseline (p = 0.01), returning to its initial condition 30 days later. There was a trend toward a different microbiome profile between groups on Day 7 (p = 0.08). Bacterium composition in DH showed a balance between healthy species and oral pathogens over time, whereas UH composition was characterized by microorganisms correlated with epithelium invasion/cytotoxicity; virulence factor upregulation; and oral diseases, such as periodontitis and aphthous stomatitis, until Day 30. UH showed an increase in IL-6, MCP-1, and MIP-1α over time, and DH showed a decrease in TIMP-1, IL-1β, and MIP-1α. On Days 3 and 7, MIP-1α and MMP-2 showed greater concentrations of DH in the intergroup assessment, and MCP-1 increased on Day 7 in UH. Specific microbiome/inflammatory profiles are associated with DH and UH. NCT05171400.

SBB-Chi2-A2: stacking of bagging-boosting with the blend Chi-square for effective prediction of aortic aneurysm using biomarker profiling

SBB-Chi2-A2: stacking of bagging-boosting with the blend Chi-square for effective prediction of aortic aneurysm using biomarker profiling

The Proteomic Landscape of the Coronary Accessible Heart Cell Surfaceome.

Cell surface proteins (surfaceome) represent key signalling and interaction molecules for therapeutic targeting, biomarker profiling and cellular phenotyping in physiological and pathological states. Here, we employed coronary artery perfusion with membrane-impermeant biotin to label and capture the surface-accessible proteome in the neo-native (intact) heart. Using quantitative proteomics, we identified 701 heart cell surfaceome accessible by the coronary artery, including receptors, cell surface enzymes, adhesion and junctional molecules. This surfaceome comprises to 216 cardiac cell-specific surface proteins, including 29 proteins reported in cardiomyocytes (CXADR, CACNA1C), 12 in cardiac fibroblasts (ITGA8, COL3A1) and 63 in multiple cardiac cell types (ICAM1, SLC3A2, CDH2). Further, this surfaceome comprises to 53 proteins enriched in heart tissue compared to other tissues in humans and implicated in cardiac cell signalling networks involving cardiomyopathy (CDH2, DTNA, PTKP2, SNTA1, CAM, K2D/B), cardiac muscle contraction and development (ENG, SNTA1, SGCG, MYPN), calcium ion binding (SGCA, MASP1, THBS4, FBLN2, GSN) and cell metabolism (SDHA, NUDFS1, GYS1, ACO2, IDH2). This method offers a powerful tool for dissecting the molecular landscape of the coronary artery accessible heart cell surfaceome, its role in maintaining cardiac and vascular function, and potential molecular leads for studying cardiac cell interactions and systemic delivery to the neo-native heart.

Early Use of Liraglutide for the Treatment of Acute COVID-19 Infection: An Open-Label Single-Center Phase II Safety Study with Biomarker Profiling.

Glucagon-like peptide-1 (GLP-1) agonists are an existing treatment option for patients with insulin-resistant states, which elicit further pleiotropic effects related to immune cell recruitment and vascular inflammation. GLP-1 agonists downregulate the cluster of differentiation 147 (CD147) receptor, one of several receptors for the SARS-CoV-2 spike protein that mediate viral infection of host cells. We conducted an open-label prospective safety and tolerability study including biomarker responses of the GLP-1 agonist Liraglutide, administered for 5 days as an add-on therapy to the standard of care within 48 h of presentation in a cohort of 13 patients hospitalized with COVID-19 pneumonia. Biomarker responses were compared in patients admitted to critical care and those not requiring critical care admission (non-critical group). Liraglutide (0.6 mg, subcutaneously) was well tolerated by all patients and all patients were alive 30 days after diagnosis. Plasma soluble CD147 levels were reduced in the non-critical patient group at day 5 in contrast to critical care-treated patients, who demonstrated an increase in soluble CD147 levels between day 0 and day 5. Patients with milder COVID-19 pneumonia severity also demonstrated improvement in echocardiographic parameters of right and left ventricular function, reduction in plasma Troponin levels, increased CD147 expression on T lymphocytes, and reduction in plasma IL-8. This first-in-disease use of the GLP-1 agonist Liraglutide demonstrates its safety and tolerability in an unselected cohort of patients hospitalized with COVID-19 pneumonia across a range of clinical severities.

LUNG CANCER IN THE NORTHEAST MICROREGION OF RIO GRANDE DO SUL: EPIDEMIOLOGICAL ASPECTS, MOLECULAR AND IMMUNOHISTOCHEMICAL PROFILE

Objective: To analyze the epidemiological profile of patients affected by lung cancer between 2005 and 2021 in the northeastern microregion of Rio Grande do Sul and to describe the molecular and immunohistochemical profile through the EGFR, PD-L1 and ALK biomarkers. Methods: This was a cross-sectional, retrospective study with quantitative and qualitative analysis carried out by the access to the Hospital Cancer Registry (RHC) database of a High Complexity Oncology Unit located in the northeast microregion of RS. Epidemiological parameters were histological type, age, gender, stage at diagnosis, family history, smoking and alcohol consumption, as well as data on PD-L1, ALK and EGFR biomarkers. Results: For the epidemiological profile, 1139 records were analyzed. Adenocarcinoma was the most frequent histological type (43.9%), the median age of patients was 65 years and men were more affected than women, corresponding to 66.4%. The most prevalent staging was IV (metastatic) and most patients were smokers, non-alcoholics and had a family history of cancer. Regarding the biomarkers, only 49 requests were made during the period. PD-L1 positivity, EGFR alterations and ALK gene rearrangements were observed in 43.8%, 20% and 7.5% of the cases, respectively. Conclusion: The epidemiological data cover 17 years of cases and corroborate previous studies evaluating lung cancer profile. Some variations of the analyzed biomarkers were verified in comparison to other national and international studies; however, more investigation is necessary to better assess the profile of biomarkers in the region.

Distinct clinical phenotypes in gastric pathologies: a cluster analysis of demographic and biomarker profiles in a diverse patient population.

Understanding the heterogeneity of a population at risk is an important step in the early detection of gastric cancer. We aimed to cluster demographic, hematological, and biochemical markers of gastric cancer in a heterogeneous sample of patients. Data of 695 adult patients (50.0% women) who were diagnosed with histologically confirmed gastric cancer, benign gastric disease, or identified as healthy individuals (December 2018 to August 2019, Hangzhou, China) were analyzed. We conducted hierarchical clustering using a factorial analysis of mixed data. To assess the clustering scheme, we also developed a machine-learning classification model using the Extreme Gradient Boosting algorithm and subsequently ranked the variables for differentiating patient phenotypes. Three clusters were identified using patient characteristics. The classification model showed high performance (multi-class AUC = 0.921) for recognizing the clusters. The top five important variables in differentiating the clusters were sex, hemoglobin, albumin, creatinine, and high-density lipoprotein (all ANOVA P <0.001) in decreasing order of importance. The prevalence of gastric cancer in clusters I, II, and III was 95.8%, 53.8%, and 34%, respectively [χ2(2) = 164.050, P <0.001]. Cluster I (N = 167) predominantly had an inflammatory profile, Cluster II (N = 240) showed metabolic disturbances, and Cluster III (N = 288) presented a relatively favorable metabolic and inflammatory profile. There were distinct clinical phenotypes in the population, each with varying prevalence of gastric cancer. A combination of routine clinical data outperformed carbohydrate or carcinoembryonic antigens in capturing the heterogeneity of the population regarding gastric pathologies.

Skin Tape Stripping Reveals Distinct Biomarker Profiles in Chronic Hand Eczema of Patients With and Without Comorbid Atopic Dermatitis.

Chronic hand eczema (CHE) is a highly prevalent inflammatory skin condition which is often resistant to conventional treatments. Molecular insights of CHE remain limited. Tape stripping combined with high-throughput RNA sequencing can now provide a better insight into CHE pathogenesis in a minimally invasive fashion. We collected tape strip samples from lesional and non-lesional skin of 66 patients with moderate-to-severe CHE, comprising 33 with and 33 without comorbid atopic dermatitis (AD), and performed bulk RNA sequencing. Results were compared to tape strips from palmar skin of age/race/sex-matched healthy controls (HC). Differentially expressed genes (DEGs) (fold change/FCH > 1.5 and false discovery rate/FDR < 0.05) were calculated and correlated with clinical severity scores including hand eczema severity index (HECSI) and modified total lesion symptoms score (mTLSS). Tape strip isolates detected a common phenotype in CHE lesions regardless of AD status, including upregulated type-1 (IL12RB2, IFNGR1, IFNGR2, MX1) and type-2-associated inflammatory mediators (CCL22, CCL24, OX40/TNFRSF4, TSLPR/CRLF2, GATA3), paralleled by downregulated epidermal barrier markers (i.e., FLG or LORICRIN). Non-lesional skin demonstrated a similar, albeit milder, dysregulation pattern, with additional reduction in type-17 pathways. Lesional skin of CHE patients without AD showed greater skewing towards type-1 immunity (IL15RA, CXCL9), while CHE from AD patients showed a more pronounced type-2 inflammatory pattern (IL13, CCL17) and their gene expression biomarkers had greater and more significant correlations with clinical severity markers. Tape stripping can capture detailed immune and skin barrier abnormalities in CHE and identify potential novel subtype-specific treatment targets. Stronger correlations in patients with AD suggest a more homogenous disease phenotype than in CHE non-AD patients. NCT03728504.

Clinical characteristics and biomarker profile in early- and late-onset Alzheimer's disease: the Shanghai Memory Study.

Early-onset Alzheimer's disease constitutes ∼5-10% of Alzheimer's disease. Its clinical characteristics and biomarker profiles are not well documented. To compare the characteristics covering clinical, neuropsychological and biomarker profiles between patients with early- and late-onset Alzheimer's disease, we enrolled 203 patients (late-onset Alzheimer's disease = 99; early-onset Alzheimer's disease = 104) from a Chinese hospital-based cohort, the Shanghai Memory Study. A full panel of plasma biomarkers under the amyloid/tau/neurodegeneration framework including plasma amyloid beta 40, amyloid beta 42, total-tau, neurofilament light chain and phosphorylated tau 181 were assayed using ultra-sensitive Simoa technology. Seventy-five patients underwent an amyloid molecular positron emission tomography scan whereas 43 received comprehensive amyloid, Tau deposition and hypometabolism analysis. Clinical features, plasma and imaging biomarkers were compared cross-sectionally. Compared to those with late-onset Alzheimer's disease, patients with early-onset Alzheimer's disease presented more severe impairment in language function, lower frequency of APOE ɛ4 and lower levels of plasma neurofilament light chain (all P < 0.05). The plasma phosphorylated tau 181 concentration and phosphorylated tau 181/amyloid beta 42 ratios were higher in early-onset Alzheimer's disease than in late-onset Alzheimer's disease (all P < 0.05). More severe Tau deposition as indicated by 18F-florzolotau binding in the precuneus, posterior cingulate cortex and angular gyrus was observed in the early-onset Alzheimer's disease group. Plasma phosphorylated tau 181 was associated with earlier age at onset and domain-specific cognitive impairment, especially in patients with early-onset Alzheimer's disease. We concluded that patients with early-onset Alzheimer's disease differed from late-onset Alzheimer's disease in cognitive performance and biomarker profile. A higher burden of pathological tau was observed in early-onset Alzheimer's disease and was associated with earlier age at onset and more profound cognitive impairment.