Combination Of Biomarkers Research Articles

Towards cascading genetic risk in Alzheimer's disease.

Alzheimer's disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: amyloid (A), tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, in which each of the biomarkers can be either positive (+) or negative (-). Over the past decades, genome-wide association studies have implicated ∼90 different loci involved with the development of late-onset Alzheimer's disease. Here, we investigate whether genetic risk for Alzheimer's disease contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect. Amyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort. In 312 participants with biomarker-confirmed A-T- status, we used Cox proportional hazards models to estimate the contribution of APOE and polygenic risk scores (beyond APOE) to convert to A+T- status (65 conversions). Furthermore, we repeated the analysis in 290 participants with A+T- status and investigated the genetic contribution to conversion to A+T+ (45 conversions). Both survival analyses were adjusted for age, sex and years of education. For progression from A-T- to A+T-, APOE-e4 burden showed a significant effect [hazard ratio (HR) = 2.88; 95% confidence interval (CI): 1.70-4.89; P < 0.001], whereas polygenic risk did not (HR = 1.09; 95% CI: 0.84-1.42; P = 0.53). Conversely, for the transition from A+T- to A+T+, the contribution of APOE-e4 burden was reduced (HR = 1.62; 95% CI: 1.05-2.51; P = 0.031), whereas the polygenic risk showed an increased contribution (HR = 1.73; 95% CI: 1.27-2.36; P < 0.001). The marginal APOE effect was driven by e4 homozygotes (HR = 2.58; 95% CI: 1.05-6.35; P = 0.039) as opposed to e4 heterozygotes (HR = 1.74; 95% CI: 0.87-3.49; P = 0.12). The genetic risk for late-onset Alzheimer's disease unfolds in a disease stage-dependent fashion. A better understanding of the interplay between disease stage and genetic risk can lead to a more mechanistic understanding of the transition between ATN stages and a better understanding of the molecular processes leading to Alzheimer's disease, in addition to opening therapeutic windows for targeted interventions.

Assessing the impact of imidacloprid, glyphosate, and their mixtures on multiple biomarkers in Corbicula largillierti

Pesticide mixtures are frequently utilized in agriculture, yet their cumulative effects on aquatic organisms remain poorly understood. Aquatic animals can be effective bioindicators and invasive bivalves, owing to their widespread distribution, provide an opportunity to assess these impacts. Glyphosate and imidacloprid, among the most prevalent pesticides globally, are frequently detected in freshwater systems in South America. This study aims to understand the cumulative effects of pesticide mixtures on aquatic organisms, using invasive Corbicula largillierti clams from a natural stream in northwestern Argentina. We conducted 48-hour exposure experiments using two concentrations of imidacloprid (20 and 200 μg L−1 a.i), two concentrations of glyphosate (0.3 and 3 mg L−1 a.i), and two combinations of these pesticides (both at low and high concentrations, respectively), simulating the direct contamination of both pesticides based on their agronomic recipe and observed values in Argentine aquatic environments. Clam metabolism was assessed through the examination of multiple oxidative stress parameters and measuring oxygen consumption rate as a proxy for standard metabolic rate (SMR). Our findings revealed that imidacloprid has a more pronounced effect compared to glyphosate. Imidacloprid significantly decreased clam SMR and cellular levels of reduced glutathione (GSH). However, when both pesticides were present, also cellular glycogen and thiobarbituric acid-reactive substances (TBARS) were affected. Proteins and glutathione S-Transferase (GST) activity were unaffected by either pesticide or their mixture at the assayed concentrations, highlighting the need to test several stress parameters to detect toxicological impacts. Our results indicated additive effects of imidacloprid and glyphosate across all measured parameters. The combination of multiple physiological and cytological biomarkers in invasive bivalves offers significant potential to enhance biomonitoring sensitivity and obtain insights into the origins and cellular mechanisms of chemical impacts. These studies can improve pollution regulatory policies and pesticide management.

Deep Learning–Based Clustering of OCT Images for Biomarker Discovery in Age-Related Macular Degeneration (PINNACLE Study Report 4)

PurposeWe introduce a deep-learning-based biomarker proposal system for the purpose of accelerating biomarker discovery in age-related macular degeneration (AMD). DesignRetrospective analysis of a large dataset of retinal optical coherence tomography (OCT) images. ParticipantsA total of 3,456 adults aged between 51 and 102 years of whom OCT images were collected under the PINNACLE project. MethodsOur system proposes candidates for novel AMD imaging biomarkers in OCT. It works by first training a neural network using self-supervised contrastive learning to discover, without any clinical annotations, features relating to both known and unknown AMD biomarkers present in 46,496 retinal OCT images. To interpret the learned biomarkers, we partition the images into 30 subsets, termed clusters, that contain similar features. We conduct two parallel 1.5-hour semi-structured interviews with two independent teams of retinal specialists to assign descriptions in clinical language to each cluster. Descriptions of clusters achieving consensus can potentially inform new biomarker candidates. Main Outcome MeasuresWe checked if each cluster showed clear features comprehensible to retinal specialists, if they related to AMD and how many described established biomarkers used in grading systems as opposed to recently proposed or potentially new biomarkers. We also compared their prognostic value for late stage wet and dry AMD against an established clinical grading system and a demographic baseline model. ResultsOverall, both teams independently identified clearly distinct characteristics in 27 of 30 clusters, of which 23 were related to AMD. Seven were recognised as known biomarkers used in established grading systems and 16 depicted biomarker combinations or subtypes that are either not yet used in grading systems, were only recently proposed, or were unknown. Clusters separated incomplete from complete retinal atrophy, intraretinal from subretinal fluid and thick from thin choroids, and in simulation outperformed clinically-used grading systems in prognostic value. ConclusionsUsing self-supervised deep learning we were able to automatically propose AMD biomarkers going beyond the set used in clinically established grading systems. Without any clinical annotations, contrastive learning discovered subtle differences between fine-grained biomarkers. Ultimately, we envision that equipping clinicians with discovery-oriented deep-learning tools can accelerate discovery of novel prognostic biomarkers.

Hospital Acquired Sepsis, Disease Prevalence, and Recent Advances in Sepsis Mitigation.

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, commonly associated with nosocomial transmission. Gram-negative bacterial species are particularly problematic due to the release of the lipopolysaccharide toxins upon cell death. The lipopolysaccharide toxin of E. coli has a greater immunogenic potential than that of other Gram-negative bacteria. The resultant dysregulation of the immune system is associated with organ failure and mortality, with pregnant women, ICU patients, and neonates being particularly vulnerable. Additionally, sepsis recovery patients have an increased risk of re-hospitalisation, chronic illness, co-morbidities, organ damage/failure, and a reduced life expectancy. The emergence and increasing prevalence of antimicrobial resistance in bacterial and fungal species has impacted the treatment of sepsis patients, leading to increasing mortality rates. Multidrug resistant pathogens including vancomycin-resistant Enterococcus, beta lactam-resistant Klebsiella, and carbapenem-resistant Acinetobacter species are associated with an increased risk of mortality. To improve the prognosis of sepsis patients, predominantly high-risk neonates, advances must be made in the early diagnosis, triage, and control of sepsis. The identification of suitable biomarkers and biomarker combinations, coupled with machine learning and artificial intelligence, show promise in early detection protocols. Rapid diagnosis of sepsis in patients is essential to inform on clinical treatment, especially with resistant infectious agents. This timely review aims to discuss sepsis prevalence, aetiology, and recent advances towards disease mitigation and control.

Navigating the landscape of theranostics in nuclear medicine: current practice and future prospects.

Theranostics refers to the combination of diagnostic biomarkers with therapeutic agents that share a specific target expressed by diseased cells and tissues. Nuclear medicine is an exciting component explored for itsapplicability in theranostic concepts in clinical and research investigations. Nuclear theranostics is based on the employment of radioactive compounds delivering ionizing radiation to diagnose and manage certain diseases employing binding with specifically expressed targets. In the realm of personalized medicine, nuclear theranostics stands as a beacon of potential, potentially revolutionizing disease management. Studies exploring the theranostic profile of radioactive compounds have been presented in this review along with a detailed explanation of radioactive compounds and their theranostic applicability in several diseases. It furnishes insights into their applicability across diverse diseases, elucidating the intricate interplay between these compounds and disease pathologies. Light is shed on the important milestones of nuclear theranostics beginning with radioiodine therapy in thyroid carcinomas, MIBG labelled with iodine in neuroblastoma, and several others. Our perspectives have been put forth regarding the most important theranostic agents along with emerging trends and prospects.

#668 Combined biomarker testing for the assessment of acute kidney injury among myocardial infarction patients

Abstract Background and aims The utility of different biomarkers for the prediction of acute kidney injury following ST-elevation myocardial infarction (STEMI) has been evaluated in several studies however, very few data exist on the prognostic value of combining biomarkers. Among numerous biomarkers examined, C-reactive protein (CRP) and Neutrophil gelatinase associated Lipocalin (NGAL) stand high in their utility to assess AKI risk. The aim of this study was to assess the prognostic value of combined CRP and NGAL measurement for the assessment of the risk of AKI in reperfused STEMI patients Methods Blood samples for plasma NGAL and CRP were drawn 24 hours after admission. High NGAL and CRP were defined as values within the 4th quartile (&amp;gt;75percentile). Patients were stratified into 4 study groups: Low NGAL/Low CRP, LOW NGAL/high CRO, High NGAL /low CRP and high NGAL/high CRP. Patients were assessed for the occurrence of in-AKI based on the KDIGO criteria. Results A total of 311 patients were included (mean age 66 ± 14 years, 81% males). According to the 4 study groups, there was a stepwise increase in the proportion of AKI (9% vs. 21% vs. 40% vs. 68%; p 0.001; Fig. 1). In a multivariate regression model, compared to patients having low NGAL/low CRP we observed a graded, independent increase in the risk for AKI for low NGAL/high CRP, high NGAL/low CRP and high NGAL/high CRP(OR 2.89, p = 0.02 vs. OR 3.29, p &amp;lt; 0.001 vs. OR 17.6, p &amp;lt; 0.001 respectively, Table 1). Peak concentrations showed significant areas under the curves (AUCs) for the prediction of AKI for both CRP AUC (0.692, 95% CI 0.62-0.76) and NGAL (AUC 0.778, 95% CI 0.72-0.84). The combination of NGAL and CRP yielded a significant increase in AUC to 0.822 (95% CI 0.77 to 0.88) (combined biomarkers vs CRP: p &amp;lt; 0.001 and combined vs. NGAL: p = 0.02; Fig. 2). Conclusions In patients with reperfused STEMI, the combined assessment of NGAL and CRP provided incremental prognostic information for the prediction AKI when compared with single-biomarker measurement.

#1298 Combination of clinical frailty score and biomarkers as mortality predictor in hemodialysis patients

Abstract Background and Aims Frailty is common among hemodialysis (HD) patients. Its assessment is usually based on clinical criteria. In the present work, we evaluated the interest of combining clinical frailty score and biomarkers to predict mortality of chronic HD patients. Three biomarkers were assessed: myostatin, insulin-like growth factor-1 (IGF-1) and dehydroepiandrosterone sulfate (DHEA-S) Method Prevalent HD patients were enrolled from September 2016 to October 2017 in two centers in Liège, Belgium in this observational prospective study and followed up for 5 years. Myostatin, IGF-1 and DHEA-S levels were measured at baseline. Frailty was assessed using Fried's five points frailty score (≥3 indicates frailty). The ability to predict mortality was assessed by calculating areas under the curve (AUC). AUCs were compared by Hanley &amp; McNeil test. Results We included 125 HD patients with the following characteristics: median age was 67 [53; 78] years; 60% of men; 41% of diabetic and median dialysis vintage of 30 [16; 54] months. Among them, 46% were classified as “Frail” according to Fried. The median follow up was 49 [19; 60] months (Table 1). The ability (AUC) of Fried score, myostatin, IGF-1 and DHEA-S to predict mortality was significant and comparable: 0.72 (95% CI: 0.63 to 0.80), 0.72 (95% CI: 0.64 to 0.80), 0.68 (95% CI: 0.59 to 0.76) and 0.73 (95% CI: 0.64 to 0.80), respectively (Fig. 1). Combining (by logistic regression) one biomarker with Fried score improved significantly the AUC with myostatin (AUC = 0.79, 95% CI: 0.71 to 0.86, p = 0.0049), IGF-1 (AUC = 0.78, 95% CI: 0.70 to 0.85, p = 0.0099) and DHEA-S (AUC = 0.79, 95% CI: 0.71 to 0.86, p = 0.0018) compared to Fried score alone. Compared to biomarker alone, the combination also improved significantly AUC for myostatin and IGF-1 (p = 0.035 and p = 0.011 respectively) but not for DHEA-S. The combination of several biomarkers with Fried score did not significantly improve mortality prediction compared to the combination of a single biomarker with Fried score. Conclusion The study suggests that combining Fried frailty score with either myostatin, IGF-1 or DHEA-S concentration improves the prediction of five-year mortality in chronic HD patients.

The long noncoding RNA SUMO1P3 as urinary biomarker for monitoring bladder cancer progression

IntroductionUrothelial Bladder Cancer (BC) is the ninth most common cancer worldwide. It is classified into Non Muscle Invasive (NMIBC) and Muscle Invasive Bladder Cancer (MIBC), which are characterized by frequent recurrences and progression rate, respectively. The diagnosis and monitoring are obtained through invasive methods as cystoscopy and post-surgery biopsies. Thus, a panel of biomarkers able to discriminate BC based on grading or staging represents a significant step forward in the patients’ workup. In this perspective, long non-coding RNAs (lncRNAs) are emerged as reliable candidates as potential biomarker given their specific and regulated expression. In the present work we propose two lncRNAs, the Small Ubiquitin Modifier 1 pseudogene 3 (SUMO1P3), a poorly characterized pseudogene, and the Urothelial Carcinoma Associated 1 (UCA1) as candidates to monitor the BC progression.MethodsThis study was a retrospective trial enrolling NMIBC and MIBC patients undergoing surgical intervention: the expression of the lncRNA SUMO1P3 and UCA1 was evaluated in urine from 113 subjects (cases and controls). The receiver operating characteristic curve analysis was used to evaluate the performance of single or combined biomarkers in discriminating cases from controls.ResultsSUMO1P3 and UCA1 expression in urine was able to significantly discriminate low grade NMIBC, healthy control and benign prostatic hyperplasia subjects versus high grade NMIBC and MIBC patients. We also demonstrated that miR-320a, which binds SUMO1P3, was reduced in high grade NMIBC and MIBC patients and the SUMO1P3/miR-320a ratio was used to differentiate cases versus controls, showing a statistically significant power. Finally, we provided an automated method of RNA extraction coupled to ddPCR analysis in a perspective of clinical application.DiscussionWe have shown that the lncRNA SUMO1P3 is increased in urine from patients with high grade NMIBC and MIBC and that it is likely to be good candidate to predict bladder cancer progression if used alone or in combination with UCA1 or with miRNA320a.

Combining plasma Aβ and p-tau217 improves detection of brain amyloid in non-demented elderly

BackgroundMaximizing the efficiency to screen amyloid-positive individuals in asymptomatic and non-demented aged population using blood-based biomarkers is essential for future success of clinical trials in the early stage of Alzheimer’s disease (AD). In this study, we elucidate the utility of combination of plasma amyloid-β (Aβ)-related biomarkers and tau phosphorylated at threonine 217 (p-tau217) to predict abnormal Aβ-positron emission tomography (PET) in the preclinical and prodromal AD.MethodsWe designed the cross-sectional study including two ethnically distinct cohorts, the Japanese trial-ready cohort for preclinica and prodromal AD (J-TRC) and the Swedish BioFINDER study. J-TRC included 474 non-demented individuals (CDR 0: 331, CDR 0.5: 143). Participants underwent plasma Aβ and p-tau217 assessments, and Aβ-PET imaging. Findings in J-TRC were replicated in the BioFINDER cohort including 177 participants (cognitively unimpaired: 114, mild cognitive impairment: 63). In both cohorts, plasma Aβ(1-42) (Aβ42) and Aβ(1-40) (Aβ40) were measured using immunoprecipitation-MALDI TOF mass spectrometry (Shimadzu), and p-tau217 was measured with an immunoassay on the Meso Scale Discovery platform (Eli Lilly).ResultsAβ-PET was abnormal in 81 participants from J-TRC and 71 participants from BioFINDER. Plasma Aβ42/Aβ40 ratio and p-tau217 individually showed moderate to high accuracies when detecting abnormal Aβ-PET scans, which were improved by combining plasma biomarkers and by including age, sex and APOE genotype in the models. In J-TRC, the highest AUCs were observed for the models combining p-tau217/Aβ42 ratio, APOE, age, sex in the whole cohort (AUC = 0.936), combining p-tau217, Aβ42/Aβ40 ratio, APOE, age, sex in the CDR 0 group (AUC = 0.948), and combining p-tau217/Aβ42 ratio, APOE, age, sex in the CDR 0.5 group (AUC = 0.955), respectively. Each subgroup results were replicated in BioFINDER, where the highest AUCs were seen for models combining p-tau217, Aβ42/40 ratio, APOE, age, sex in cognitively unimpaired (AUC = 0.938), and p-tau217/Aβ42 ratio, APOE, age, sex in mild cognitive impairment (AUC = 0.914).ConclusionsCombination of plasma Aβ-related biomarkers and p-tau217 exhibits high performance when predicting Aβ-PET positivity. Adding basic clinical information (i.e., age, sex, APOE ε genotype) improved the prediction in preclinical AD, but not in prodromal AD. Combination of Aβ-related biomarkers and p-tau217 could be highly useful for pre-screening of participants in clinical trials of preclinical and prodromal AD.

Identifying potential breath biomarkers for early diagnosis of papillary thyroid cancer based on solid-phase microextraction gas chromatography-high resolution mass spectrometry with metabolomics.

Thyroid cancer incidence rate has increased substantially worldwide in recent years. Fine needle aspiration biopsy (FNAB) is currently the golden standard of thyroid cancer diagnosis, which however, is invasive and costly. In contrast, breath analysis is a non-invasive, safe and simple sampling method combined with a promising metabolomics approach, which is suitable for early cancer diagnosis in high volume population. This study aims to achieve a more comprehensive and definitive exhaled breath metabolism profile in papillary thyroid cancer patients (PTCs). We studied both end-tidal and mixed expiratory breath, solid-phase microextraction gas chromatography coupled with high resolution mass spectrometry (SPME-GC-HRMS) was used to analyze the breath samples. Multivariate combined univariate analysis was applied to identify potential breath biomarkers. The biomarkers identified in end-tidal and mixed expiratory breath mainly included alkanes, olefins, enols, enones, esters, aromatic compounds, and fluorine and chlorine containing organic compounds. The area under the curve (AUC) values of combined biomarkers were 0.974 (sensitivity: 96.1%, specificity: 90.2%) and 0.909 (sensitivity: 98.0%, specificity: 74.5%), respectively, for the end-tidal and mixed expiratory breath, indicating of reliability of the sampling and analysis method CONCLUSION: This work not only successfully established a standard metabolomic approach for early diagnosis of PTC, but also revealed the necessity of using both the two breath types for comprehensive analysis of the biomarkers.

The role of preoperative FPR and FAR in prognostic evaluation of stages II and III radical colorectal cancer: A single-center retrospective study.

The inflammatory and nutritional states of body are 2 important causes associated with the initiation and progression of colorectal cancer (CRC). The aim of this study is to investigate the prognostic evaluation value of preoperative fibrinogen-to-prealbumin ratio (FPR) and preoperative fibrinogen-to-albumin ratio (FAR) in CRC. The clinical data of 350 stages II and III patients with CRC who received radical resection were retrospectively analyzed. All patients were followed up for 5 years to observe the overall survival and disease-free survival of 5 years and analyze the relationship between preoperative FPR and FAR and prognosis of all enrolled patients. In addition, we analyzed the diagnostic and application value of combined biomarkers. This study showed high-level preoperative FPR and FAR were significantly associated with poor overall survival and disease-free survival of stages II and III patients with CRC. The elevated preoperative FPR and FAR level was significantly related to age, tumor differentiation level, TNM stage, vascular infiltration, carcinoembryonic antigen, carbohydrate antigen199, etc. The combination of FPR, FAR, neutrophil-to-lymphocyte ratio, and carbohydrate antigen199 had the maximum area under curve (AUC = 0.856, 95% CI: 0.814-0.897, Sen = 78.20%, Spe = 82.49%, P < .05) under the receiver-operating characteristics curve. The preoperative FPR and FAR have important prognostic value and they can be used as independent prognostic marker for patients with stages II and III CRC undergoing radical resection. Moreover, the combination of biomarkers could further enhance the diagnostic and prognostic efficacy of CRC.

Altered Serum Proteins Suggest Inflammation, Fibrogenesis and Angiogenesis in Adult Patients with a Fontan Circulation.

Previous omics research in patients with complex congenital heart disease and single-ventricle circulation (irrespective of the stage of palliative repair) revealed alterations in cardiac and systemic metabolism, inter alia abnormalities in energy metabolism, and inflammation, oxidative stress or endothelial dysfunction. We employed an affinity-proteomics approach focused on cell surface markers, cytokines, and chemokines in the serum of 20 adult Fontan patients with a good functioning systemic left ventricle, and we 20 matched controls to reveal any specific processes on a cellular level. Analysis of 349 proteins revealed 4 altered protein levels related to chronic inflammation, with elevated levels of syndecan-1 and glycophorin-A, as well as decreased levels of leukemia inhibitory factor and nerve growth factor-ß in Fontan patients compared to controls. All in all, this means that Fontan circulation carries specific physiological and metabolic instabilities, including chronic inflammation, oxidative stress imbalance, and consequently, possible damage to cell structure and alterations in translational pathways. A combination of proteomics-based biomarkers and the traditional biomarkers (uric acid, γGT, and cholesterol) performed best in classification (patient vs. control). A metabolism- and signaling-based approach may be helpful for a better understanding of Fontan (patho-)physiology. Syndecan-1, glycophorin-A, leukemia inhibitory factor, and nerve growth factor-ß, especially in combination with uric acid, γGT, and cholesterol, might be interesting candidate parameters to complement traditional diagnostic imaging tools and the determination of traditional biomarkers, yielding a better understanding of the development of comorbidities in Fontan patients, and they may play a future role in the identification of targets to mitigate inflammation and comorbidities in Fontan patients.

Determinants of serious health outcome-free status in middle-aged and older people with dysglycaemia: Exploratory analysis of the ORIGIN trial.

To assess clinical and biochemical measurements that can identify people with dysglycaemia (i.e. diabetes or pre-diabetes) who remain free of serious outcomes during follow-up. We conducted exploratory analyses using data from the Outcomes Reduction with an Initial Glargine Intervention (ORIGIN) study to identify independent determinants of outcome-free status in 12 537 middle-aged and older adults with prediabetes and early type 2 diabetes from 40 countries. Serious outcome-free status was defined as the absence of major cardiovascular outcomes, kidney or retinal outcomes, peripheral artery disease, dementia, cancer, any hospitalization, or death during follow-up. In total, 3328 (26.6%) participants remained free of serious outcomes during a median follow-up of 6.2 years (IQR 5.8, 6.7). Independent clinical determinants of outcome-free status included younger age, female sex, non-White ethnicity, shorter diabetes duration, absence of previous cardiovascular disease, current or former smokers, higher grip strength, Mini-Mental State Examination score, and ankle-brachial index, lower body mass index and kidney disease index, and non-use of renin-angiotensin system drugs and beta-blockers. In a subset of 8401 people with baseline measurements of 238 biomarkers, growth differentiation factor 15, kidney injury molecule-1, N-terminal pro-brain natriuretic peptide, uromodulin, C-reactive protein, factor VII and ferritin were independent determinants. The combination of clinical determinants and biomarkers best identified participants who remained outcome-free (C-statistics 0.71, 95% confidence interval 0.70-0.73; net reclassification improvement 0.55, 95% confidence interval 0.48-0.58). A set of routinely measured clinical characteristics and seven protein biomarkers identify middle-aged and older people with prediabetes or early type 2 diabetes as least likely to experience serious outcomes during follow-up.

MASLD and MASH at the crossroads of hepatology trials and cardiorenal metabolic trials.

Steatotic liver disease (SLD) is a worldwide public health problem, causing considerable morbidity and mortality. Patients with SLD are at increased risk for major adverse cardiovascular (CV) events, type 2 diabetes mellitus and chronic kidney disease. Conversely, patients with cardiometabolic conditions have a high prevalence of SLD. In addition to epidemiological evidence linking many of these conditions, there is evidence of shared pathophysiological processes. In December 2022, a unique multi-stakeholder, multi-specialty meeting, called MOSAIC (Metabolic multi Organ Science Accelerating Innovation in Clinical Trials) was convened to foster collaboration across metabolic, hepatology, nephrology and CV disorders. One of the goals of the meeting was to consider approaches to drug development that would speed regulatory approval of treatments for multiple disorders by combining liver and cardiorenal endpoints within a single study. Non-invasive tests, including biomarkers and imaging, are needed in hepatic and cardiorenal trials. They can be used as trial endpoints, to enrich trial populations, to diagnose and risk stratify patients and to assess treatment efficacy and safety. Although they are used in proof of concept and phase 2 trials, they are often not acceptable for regulatory approval of therapies. The challenge is defining the optimal combination of biomarkers, imaging and morbidity/mortality outcomes and ensuring that they are included in future trials while minimizing the burden on patients, trialists and trial sponsors. This paper provides an overview of some of the wide array of CV, liver and kidney measurements that were discussed at the MOSAIC meeting.

Biomarker signatures associated with ageing free of major chronic diseases: results from a population-based sample of the EPIC-Potsdam cohort.

A number of biomarkers denoting various pathophysiological pathways have been implicated in the aetiology and risk of age-related diseases. Hence, the combined impact of multiple biomarkers in relation to ageing free of major chronic diseases, such as cancer, cardiovascular disease and type 2 diabetes, has not been sufficiently explored. We measured concentrations of 13 biomarkers in a random subcohort of 2,500 participants in the European Prospective Investigation into Cancer and Nutrition Potsdam study. Chronic disease-free ageing was defined as reaching the age of 70years within study follow-up without major chronic diseases, including cardiovascular disease, type 2 diabetes or cancer. Using a novel machine-learning technique, we aimed to identify biomarker clusters and explore their association with chronic disease-free ageing in multivariable-adjusted logistic regression analysis taking socio-demographic, lifestyle and anthropometric factors into account. Of the participants who reached the age of 70years, 321 met our criteria for chronic-disease free ageing. Machine learning analysis identified three distinct biomarker clusters, among which a signature characterised by high concentrations of high-density lipoprotein cholesterol, adiponectin and insulin-like growth factor-binding protein 2 and low concentrations of triglycerides was associated with highest odds for ageing free of major chronic diseases. After multivariable adjustment, the association was attenuated by socio-demographic, lifestyle and adiposity indicators, pointing to the relative importance of these factors as determinants of healthy ageing. These data underline the importance of exploring combinations of biomarkers rather than single molecules in understanding complex biological pathways underpinning healthy ageing.

Combined biomarker testing for the assessment of cardio-renal interactions among myocardial infarction patients

Abstract Funding Acknowledgements None. Background The utility of different biomarkers for the prediction of either renal or cardiovascular outcomes following ST-elevation myocardial infarction (STEMI) has been evaluated in several studies however, very few data exist on the prognostic value of combining biomarkers. Among numerous biomarkers examined, C-reactive protein (CRP) and Neutrophil gelatinase associated Lipocalin (NGAL) stand high in their utility to assess the cardiorenal crosstalk. The aim of this study was to assess the prognostic value of combined CRP and NGAL measurement for the assessment of renal and cardiovascular outcomes in reperfused STEMI patients. Methods Blood samples for plasma NGAL and CRP were drawn 24 hours after admission. High NGAL and CRP were defined as values within the 4th quartile (&amp;gt;75percentile). Patients were stratified into 4 study groups: Low NGAL/Low CRP, LOW NGAL/high CRO, High NGAL /low CRP and high NGAL/high CRP. Patients were assessed for the occurrence of in-hospital adverse clinical events (MACE). These included occurrence of acute kidney injury , 30-day mortality and their combination. Results A total of 311 patients were included (mean age 66 ± 14 years, 81% males). According to the 4 study groups, there was a stepwise increase in the proportion of in hospital MACE ( 9% vs. 21% vs. 40% vs. 68% ;p,0.001,figure 1). In a multivariate regression model , compared to patients having low NGAL/low CRP we observed a graded, independent increase in the risk for MACE for low NGAL/high CRP , high NGAL/low CRP and high NGAL/high CRP levels( OR 2.89, p=0.02 vs. OR 3.29,p&amp;lt;0.001 vs. OR 17.6,p&amp;lt;0.001 respectively). Peak concentrations showed significant areas under the curves (AUCs) for the prediction of MACE for both CRP AUC (0.692,95% CI 0.62-0.76) and NGAL ( AUC 0.778,95% CI 0.72-0.84). The combination of NGAL and CRP yielded a significant increase in AUC to 0.822 (95% CI 0.77 to 0.88) (combined biomarkers vs CRP: p&amp;lt;0.001 and combined vs. NGAL :p=0.02,figure 2). Conclusions In patients with reperfused STEMI, the combined assessment of NGAL and CRP provided incremental prognostic information for the prediction of in hospital MACE when compared with single-biomarker measurement.Proportion of in-hospital MACEAUC CR NGAL

On the relationship between viscoelasticity and water diffusion in soft biological tissues

Magnetic resonance elastography (MRE) and diffusion-weighted imaging (DWI) are complementary imaging techniques that detect disease based on viscoelasticity and water mobility, respectively. However, the relationship between viscoelasticity and water diffusion is still poorly understood, hindering the clinical translation of combined DWI-MRE markers.We used DWI-MRE to study 129 biomaterial samples including native and cross-linked collagen, glycosaminoglycans (GAGs) with different sulfation levels, and decellularized specimens of pancreas and liver, all with different proportions of solid tissue, or solid fractions. We developed a theoretical framework of the relationship between mechanical loss and tissue-water mobility based on two parameters, solid and fluid viscosity. These parameters revealed distinct DWI-MRE property clusters characterizing weak, moderate, and strong water-network interactions. Sparse networks interacting weakly with water, such as collagen or diluted decellularized tissue, resulted in marginal changes in water diffusion over increasing solid viscosity. In contrast, dense networks with larger solid fractions exhibited both free and hindered water diffusion depending on the polarity of the solid components. For example, polar and highly sulfated GAGs as well as native soft tissues hindered water diffusion despite relatively low solid viscosity.Our results suggest that two fundamental properties of tissue networks, solid fraction and network polarity, critically influence solid and fluid viscosity in biological tissues. Since clinical DWI and MRE are sensitive to these viscosity parameters, the framework we present here can be used to detect tissue remodeling and architectural changes in the setting of diagnostic imaging. Statement of significanceThe viscoelastic properties of biological tissues provide a wealth of information on the vital state of cells and host matrix. Combined measurement of viscoelasticity and water diffusion by medical imaging is sensitive to tissue microarchitecture. However, the relationship between viscoelasticity and water diffusion is still poorly understood, hindering full exploitation of these properties as a combined clinical biomarker. Therefore, we analyzed the parameter space accessible by diffusion-weighted imaging (DWI) and magnetic resonance elastography (MRE) and developed a theoretical framework for the relationship between water mobility and mechanical parameters in biomaterials. Our theory of solid material properties related to particle motion can be translated to clinical radiology using clinically established MRE and DWI.

The Association between Urine N-Glycome and Prognosis after Initial Therapy for Primary Prostate Cancer.

Next to prostate-specific antigen, no biochemical biomarkers have been implemented to guide patient follow-up after primary therapy for localized prostate cancer (PCa). We evaluated the prognostic potential of urine N-glycome in terms of event-free survival (EFS) in patients undergoing primary therapy for PCa. The prognostic features of the urine N-glycosylation profile at diagnosis, assessed in 77 PCa patients, were determined in terms of EFS next to standard clinical parameters. The majority of patients were diagnosed with International Society of Urological Pathology grade ≤ 3 (82%) T1-2 tumors (79%) and without pelvic lymph node invasion (96%). The patients underwent active surveillance (14%), robot-assisted laparoscopic prostatectomy (48%), or external beam radiotherapy (37%). Decreased ratios of biantennary core-fucosylation were noted in patients who developed an event, which was linked to a shorter EFS in both the intention-to-treat cohort and all subcohort analyses. Combining the urine N-glycan biomarker with the D'Amico Risk Classification for PCa resulted in an improved nomogram for patient classification after primary therapy. The rate of urine N-glycan biantennary core-fucosylation, typically linked to more aggressive disease status, is lower in patients who eventually developed an event following primary therapy and subsequently in patients with a worse EFS. The combination of urine N-glycan biomarkers together with clinical parameters could, therefore, improve the post-therapy follow-up of patients with PCa.

Greatly isolated heterogeneous circulating tumor cells using hybrid engineered cell membrane-camouflaged magnetic nanoparticles

BackgroundCirculating tumor cells (CTCs) are considered as a useful biomarker for early cancer diagnosis, which play a crucial role in metastatic process. Unfortunately, the tumor heterogeneity and extremely rare occurrence rate of CTCs among billions of interfering leukocytes seriously hamper the sensitivity and purity of CTCs isolation.MethodsTo address these, we firstly used microfluidic chips to detect the broad-spectrum of triple target combination biomarkers in CTCs of 10 types of cancer patients, including EpCAM, EGFR and Her2. Then, we constructed hybrid engineered cell membrane-camouflaged magnetic nanoparticles (HE-CM-MNs) for efficient capture of heterogeneous CTCs with high-purity, which was enabled by inheriting the recognition ability of HE-CM for various CTCs and reducing homologous cell interaction with leukocytes. Compared with single E-CM-MNs, HE-CM-MNs showed a significant improvement in the capture efficiency for a cell mixture, with an efficiency of 90%. And the capture efficiency of HE-CM-MNs toward 12 subpopulations of tumor cells was ranged from 70 to 85%. Furthermore, by using HE-CM-MNs, we successfully isolated heterogeneous CTCs with high purity from clinical blood samples. Finally, the captured CTCs by HE-CM-MNs could be used for gene mutation analysis.ConclusionsThis study demonstrated the promising potential of HE-CM-MNs for heterogeneous CTCs detection and downstream analysis.Graphical abstract

Multidimensional biomarker approach integrating tumor markers, inflammatory indicators, and disease activity indicators may improve prediction of rheumatoid arthritis-associated interstitial lung disease.

Rheumatoid arthritis (RA) often leads to interstitial lung disease (ILD), significantly affecting patient outcomes. This study explored the diagnostic accuracy of a multi-biomarker approach to offer a more efficient and accessible diagnostic strategy for RA-associated ILD (RA-ILD). Patients diagnosed with RA, with or without ILD, at Beijing Tiantan Hospital from October 2019 to October 2023 were analyzed. A total of 125 RA patients were included, with 76 diagnosed with RA-ILD. The study focused on three categories of indicators: tumor markers, inflammatory indicators, and disease activity measures. The heatmap correlation analysis was employed to analyze the correlation among these indicators. Logistic regression was used to determine odds ratios (OR) for indicators linked to RA-ILD risk. Receiver-operating characteristic (ROC) curve analysis was employed to evaluate the diagnostic potential of these indicators for RA-ILD. The results of logistic regression analysis showed that tumor markers (carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), and cytokeratin 19 fragment (CYFRA21-1)), as well as inflammatory indicators (neutrophil, neutrophil-to-lymphocyte ratio (NLR), platelet, C-reactive protein (CRP)) and disease activity measures (disease activity score-28-CRP (DAS28-CRP), rheumatoid factor (RF), and anti-cyclic peptide containing citrulline (anti-CCP)), were significantly associated with RA-ILD. The correlation coefficients among these indicators were relatively low. Notably, the combination indicator 4, which integrated the aforementioned three categories of biomarkers, demonstrated improved diagnostic accuracy with an AUC of 0.857. The study demonstrated that combining tumor markers, inflammatory indicators, and disease activity measures significantly enhanced the prediction of RA-ILD. Key Points • Multidimensional strategy: Integrated tumor markers, inflammatory indicators, and disease activity measures to enhance early detection of rheumatoid arthritis-associated interstitial lung disease (RA-ILD). • Diagnostic accuracy: Employed heatmap correlation and logistic regression, identifying significant associations and improving diagnostic accuracy with a multidimensional biomarker combination. • Superior performance: The combined multidimensional biomarker strategy demonstrated higher diagnostic precision compared to individual or dual-category indicators. • Clinical relevance: Offers a promising, accessible approach for early detection of RA-ILD in clinical settings, potentially improving patient outcomes.