Biomarker Patterns Research Articles

Different Proteins as Biomarkers for Sac Shrinkage After Endovascular Aortic Repair of Abdominal Aortic Aneurysms.

This study aims to identify circulating biomarkers by using proteomic analysis associated with sac shrinkage or expansion in patients undergoing endovascular aneurysm repair (EVAR) for abdominal aortic aneurysms (AAAs). Plasma samples were analysed from 32 patients treated with EVAR between 10/2009 and 10/2020. Patients were divided into two groups based on postoperative sac behaviour: sac shrinkage (≥5 mm reduction) and no shrinkage (stabilisation or expansion). Proteomic analysis was performed using high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS), with abundant protein depletion to enhance the detection of low-abundant proteins. Of the 32 patients, 20 exhibited sac shrinkage, and 12 showed no shrinkage. Proteomic analysis identified 632 proteins, with significant differential abundance observed after adjusting for relevant clinical parameters. Notably, neurogranin (NRGN) levels were significantly associated with hypertension and smoking, while casein alpha S1 (CSN1S1) levels varied with statin use. Differentially abundant proteins related to aortic diameter included calpastatin, SCUBE3, and ubiquitin-conjugating enzyme E2, among others. Proteomic profiling revealed distinct biomarker patterns associated with sac behaviour in EVAR-treated AAA patients. These findings suggest potential therapeutic targets for enhancing EVAR outcomes and underscore the need for further investigation into the biological mechanisms underlying aneurysm sac shrinkage and stability.

INNV-15. A PIVOTAL, MULTICENTER TRIAL OF FOCUSED ULTRASOUND FOR BLOOD-BRAIN BARRIER DISRUPTION FOR PLASMA-BASED LIQUID BIOPSY IN PATIENTS WITH GLIOBLASTOMA (LIBERATE)

Abstract BACKGROUND Liquid biopsy in glioblastoma (GBM) is hindered by insufficient requisite circulating-tumor (ct) and cell-free (cf) DNA in blood due to blood-brain barrier (BBB). This limits the identification of blood-based tumor biomarkers along with biomarker-driven systemic therapies. Real-time image-guided low-intensity focused ultrasound (LIFU) plus IV microbubble oscillators, leads to non-invasive BBB disruption. METHODS LIBERATE is an ongoing, prospective, multi-center, self-controlled, pivotal trial investigating safety and technical efficacy of LIFU-based BBB disruption for increasing blood ctDNA and cfDNA levels in adult GBM patients (aged 18-80 years). Patients with suspected GBM planned for biopsy/resection at ten US centers are being enrolled. Patients with multifocal tumors or tumors arising from deep midline, thalamus, cerebellum, or brainstem are excluded. Patients are administered IV microbubbles for enhanced sonication effects, after which MR-guided BBB disruption using 220kHz LIFU device is performed with real-time acoustic-feedback-control for effective microbubble activation. Pre- and post-LIFU, phlebotomy and MRI brain are performed. Primary study endpoint is defined, per subject, as ratio between their blood cfDNA level 1-hour post-LIFU procedure compared to blood cfDNA pre-procedure. Primary study hypothesis is that BBB disruption leads to ≥2-fold rise in blood cfDNA. Secondary hypothesis is that there exists ≥75% agreement between biomarker pattern in blood cfDNA sample obtained 1-hour post-LIFU and biomarker pattern in tumor tissue obtained later. Trial is powered to evaluate both primary and secondary hypotheses. Based on assumed true agreement rate of 91% and one-sided alpha=0.025, an exact test for binomial proportions provides N=50 with 84% power for secondary hypothesis. Exploratory endpoints include (1) sensitivity of detection of specific somatic mutations in ctDNA from blood collected pre- and post-LIFU, (2) ctDNA estimation in samples collected at 30-minutes, 1-hour, 2-hour, and 3-hour post-LIFU to determine time of greatest yield, (3) correlation of MRI parameters related to grading of BBB disruption and ctDNA-based biomarkers from post-LIFU blood samples. Patient enrollment commenced in 2022 and remains ongoing (NCT05383872).

Integrating Enzyme-Based Kinetics in Reactive Transport Models to Simulate Spatiotemporal Dynamics of Biomarkers during Chlorinated Ethene Degradation.

Biomarkers such as functional gene mRNA (transcripts) and proteins (enzymes) provide direct proof of metabolic regulation during the reductive dechlorination (RD) of chlorinated ethenes (CEs). Yet, current models to simulate their spatiotemporal variability are not flexible enough to mimic the homologous behavior of RDase functional genes. To this end, we developed new enzyme-based kinetics to model the concentrations of CEs together with the transcript and enzyme levels during RD. First, the model was calibrated to existing microcosm data on RD of cis-DCE. The model mirrored the tceA and vcrA gene expression and the production of their enzymes in Dehalococcoides spp. Considering tceA and vcrA as homologous instead of nonhomologous improved fitting of the mRNA time series. Second, CEs and biomarker patterns were explored as a proof of concept under groundwater flow conditions, considering degraders occurring in immobile and mobile states. Under both microcosm and flow conditions, biomarker-rate relationships were nonlinear hysteretic because tceA and vcrA acted as homologous genes. The mobile biomarkers additionally undergo advective-dispersive transport, which increases the nonlinearity and makes the observed patterns even more challenging to interpret. The model offers a thorough mechanistic description of RD while also allowing simulation of spatiotemporal dynamic patterns of various key biomarkers in aquifers.

Fluid biomarkers of chronic traumatic brain injury.

Traumatic brain injury (TBI) is a leading cause of long-term disability across the world. Evidence for the usefulness of imaging and fluid biomarkers to predict outcomes and screen for the need to monitor complications in the acute stage is steadily increasing. Still, many people experience symptoms such as fatigue and cognitive and motor dysfunction in the chronic phase of TBI, where objective assessments for brain injury are lacking. Consensus criteria for traumatic encephalopathy syndrome, a clinical syndrome possibly associated with the neurodegenerative disease chronic traumatic encephalopathy, which iscommonly associated with sports concussion, have been defined only recently. However, these criteria do not fit all individuals living with chronic consequences of TBI. The pathophysiology of chronic TBI shares many similarities with other neurodegenerative and neuroinflammatory conditions, such as Alzheimer disease. As with Alzheimer disease, advancements in fluid biomarkers represent one of the most promising paths for unravelling the chain of pathophysiological events to enable discrimination between these conditions and, with time, provide prediction modelling and therapeutic end points. This Review summarizes fluid biomarker findings in the chronic phase of TBI (≥6 months after injury) that demonstrate the involvement of inflammation, glial biology and neurodegeneration in the long-term complications of TBI. We explore how the biomarkers associate with outcome and imaging findings and aim to establish mechanistic differences in biomarker patterns between types of chronic TBI and other neurodegenerative conditions. Finally, current limitations and areas of priority for future fluid biomarker research are highlighted.

Disentangling Anemia in Frailty: Exploring the Role of Inflammation.

In older patients, frailty and anemia frequently coexist. However, only few studies have been conducted in older patients with multimorbidity and several overlapping causes of anemia, such as inflammation, inadequate nutrition, or certain pathologies. This analysis aims to decipher potential factors associated with anemia in older hospital patients with frailty. Patients (n = 208, age: 62-98 years) were categorized as prefrail (n = 68) and frail (n = 140) using the Fried frailty phenotype. We quantified serum concentrations of markers of iron metabolism (iron, ferritin, transferrin, soluble transferrin receptor, and hepcidin), inflammation (interleukin [IL]-6 and IL-10 C-reactive protein), and hematology (hemoglobin). Principal component analysis was conducted to evaluate biomarker patterns and associations with frailty were assessed with logistic regression analysis. Anemia prevalence was higher in patients with frailty (84.3% vs 70.6%, p = .021). Three principal components (PC1-3) were identified. PC1 was characterized by high factor loadings representing inflammation and factor scores differed between patients with prefrailty and frailty (-0.04 (interquartile range [IQR]: 1.45) vs -0.51 (IQR: 0.87), p < .001]. PC2 represents macrocytic anemia and thus vitamin B12 or folate deficiency, whereas PC3 indicates hematological pathologies. Only PC1 was associated with frailty status when controlled for age, sex, number of drugs, and comorbidities (OR: 2.018, 95% CI: 1.316; 3.094, p = .001). PC2 and PC3 were not associated with frailty. Our results suggest that anemia in patients with frailty is driven by inflammation rather than being disease-related or solely the result of micronutrient deficiencies.

Shifting feed delivery time: effects on feeding behavior, milk production, and blood biomarkers in late-lactating dairy cows

Improving the synchronization between the pattern of milk synthesis and nutrient availability throughout the day could enhance production efficiency. In this study, we evaluated the effects of changing feed delivery time on milk production, feeding behavior, and the daily rhythms of blood biomarkers. Eight multiparous Holstein cows housed in a tie-stall barn with controlled environmental conditions were enrolled in a crossover experimental design with three periods of 14 days and three treatments each. Cows were milked twice daily (0530 and 1730 h) and were individually fed with two equal meals of forage and eight equal meals of concentrate during the day. Forage meals were provided at 12-hour intervals either: (i) 5 h before each milking (0030 and 1230 h; BM), (ii) at the end of each milking (0530 and 1730 h; ME), (iii) or 2 h after (0730 and 1930 h; AM). Feed intake and feeding behavior were monitored, and milk production and composition were measured. Blood samples were collected every 4 days at 0700 h and, during the last day of each period, 15 times daily to determine metabolic profiles, hormones, and their daily rhythmicity by the cosinor analysis. Changing forage delivery time did not affect milk yield and dry matter intake. No difference was observed in feeding behavior when expressed relative to the first meal. There were no significant differences in milk component contents and yields. In samples collected at 0700 h, ME had reduced plasma calcium (Ca), magnesium (Mg), and potassium (K) and increased sodium (Na). AM had increased inflammation, as suggested by the greater blood globulin and ceruloplasmin. The patterns of metabolic biomarkers had limited variations when expressed relative to the first forage meal. Nevertheless, the daily rhythms of these biomarkers were remarkably different. Under our conditions, feeding forage meals to cows at different times of the day did not influence productive performance but highlighted the importance of considering the sampling time when interpreting metabolic profiles.

NLRP3 Inflammasome Inhibition After Pilocarpine-Induced Status Epilepticus Attenuates Chronic Inflammation in Epileptic Mice.

To investigate the effects of inhibiting the NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome on neuronal damage and chronic pro-inflammatory responses during epileptogenesis in a mouse model of pilocarpine-induced status epilepticus (SE). Mice were randomly allocated into three groups: control, SE, and SE + MCC 950. The expression patterns of M1 and M2 microglial biomarkers in the hippocampus were quantified using Western blotting, quantitative real-time polymerase chain reaction, enzyme-linked immunosorbent assay, and immunofluorescence staining. Additionally, seizure susceptibility, video-electroencephalography recording, Morris water maze test, and brain immunofluorescence staining were performed to evaluate the epileptic brain 4 weeks post-SE. Within 72 hours post-SE, hippocampal microglia demonstrated a preferential polarization towards the M1 phenotype, a trend that was mitigated by NLRP3 inflammasome inhibition. During epileptogenesis, SE mice treated with NLRP3 inflammasome inhibition exhibited reduced neuronal damage, improved cognitive function, decreased seizure susceptibility, and attenuated chronic pro-inflammatory responses. Inhibition of NLRP3 inflammasome post-SE effectively ameliorates neuronal loss, seizure susceptibility, and cognitive dysfunction during epileptogenesis. This neuroprotective effect may be mediated through the mitigation of chronic pro-inflammatory responses within the epileptic brain.

Biomarker patterns and mechanistic insights into hypothermia from a postmortem metabolomics investigation

Postmortem metabolomics holds promise for identifying crucial biological markers relevant to death investigations and clinical scenarios. We aimed to assess its applicability in diagnosing hypothermia, a condition lacking definitive biomarkers. Our retrospective analysis involved 1095 postmortem femoral blood samples, including 150 hypothermia cases, 278 matched controls, and 667 randomly selected test cases, analyzed using UHPLC-QTOF mass spectrometry. The model demonstrated robustness with an R2 and Q2 value of 0.73 and 0.68, achieving 94% classification accuracy, 92% sensitivity, and 96% specificity. Discriminative metabolite patterns, including acylcarnitines, stress hormones, and NAD metabolites, along with identified pathways, suggest that metabolomics analysis can be helpful to diagnose fatal hypothermia. Exposure to cold seems to trigger a stress response in the body, increasing cortisol production to maintain core temperature, possibly explaining the observed upregulation of cortisol levels and alterations in metabolic markers related to renal function. In addition, thermogenesis seems to increase metabolism in brown adipose tissue, contributing to changes in nicotinamide metabolism and elevated levels of ketone bodies and acylcarnitines, these findings highlight the effectiveness of UHPLC-QTOF mass spectrometry, multivariate analysis, and pathway identification of postmortem samples in identifying metabolite markers with forensic and clinical significance. The discovered patterns may offer valuable clinical insights and diagnostic markers, emphasizing the broader potential of postmortem metabolomics in understanding critical states or diseases.

Revealing static and dynamic biomarkers from postprandial metabolomics data through coupled matrix and tensor factorizations.

Longitudinal metabolomics data from a meal challenge test contains both fasting and dynamic signals, that may be related to metabolic health and diseases. Recent work has explored the multiway structure of time-resolved metabolomics data by arranging it as a three-way array with modes: subjects, metabolites, and time. The analysis of such dynamic data (where the fasting data is subtracted from postprandial states) reveals dynamic markers of various phenotypes, and differences between fasting and dynamic states. However, there is still limited success in terms of extracting static and dynamic biomarkers for the same subject stratifications. Through joint analysis of fasting and dynamic metabolomics data, our goal is to capture static and dynamic biomarkers of a phenotype for the same subject stratifications providing a complete picture, that will be more effective for precision health. We jointly analyze fasting and dynamic metabolomics data collected during a meal challenge test from the COPSAC cohort using coupled matrix and tensor factorizations (CMTF), where the dynamic data (subjects by metabolites by time) is coupled with the fasting data (subjects by metabolites) in the subjects mode. The proposed data fusion approach extracts shared subject stratifications in terms of BMI (body mass index) from fasting and dynamic signals as well as the static and dynamic metabolic biomarker patterns corresponding to those stratifications. Specifically, we observe a subject stratification showing the positive association with all fasting VLDLs and higher BMI. For the same subject stratification, a subset of dynamic VLDLs (mainly the smaller sizes) correlates negatively with higher BMI. Higher correlations of the subject quantifications with the phenotype of interest are observed using such a data fusion approach compared to individual analyses of the fasting and postprandial state. The CMTF-based approach provides a complete picture of static and dynamic biomarkers for the same subject stratifications-when markers are present in both fasting and dynamic states.

Simultaneous determination of total homocysteine, methionine, methylmalonic acid and 2-methylcitric acid in dried blood spots by ultra-performance liquid chromatography–tandem mass spectrometry

Homocysteine, methionine, methylmalonic acid and 2-methylcitric acid are clinically relevant markers in the methionine, propionate, and cobalamin metabolism. This study aimed to develop and validate an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for simultaneously determining total homocysteine, methionine, methylmalonic acid and 2-methylcitric acid in dried blood spots. Three 3.2 mm discs were punched from each calibrator, quality control, and sample dried blood spot into a 96-well U-plate. Each sample was spiked with internal standards and extracted. Then the supernatant was transferred to another 96-well U-plate. After nitrogen drying, the dried residues were reconstituted, centrifuged, and the resulting supernatant was transferred to another 96-well plate for analysis. The method was performed using UPLC-MS/MS within 3 min, validated according to guidance documents, and applied to 72 samples from confirmed patients with methionine, propionate, and cobalamin metabolism disorders. The UPLC-MS/MS method provided satisfactory separation of the four analytes. The R2 values were ≥ 0.9937 for all analytes. The recoveries ranged from 94.17 to 114.29 %, and the coefficients of variation for intraday and interday precision were 0.19 % to 5.23 % and 1.02 % to 6.89 %, respectively. No significant carry-over was detected for the four analytes, and most of confirmed samples exhibited biomarker patterns characteristic of the relevant disorders. A simple and fast UPLC-MS/MS method was successfully developed, validated, and applied to clinical samples for the simultaneous determination of total homocysteine, methionine, methylmalonic acid, and 2-methylcitric acid in dried blood spots.

Cluster analysis of blood biomarkers to identify molecular patterns in pulmonary fibrosis: assessment of a multicentre, prospective, observational cohort with independent validation

Pulmonary fibrosis results from alveolar injury, leading to extracellular matrix remodelling and impaired lung function. This study aimed to classify patients with pulmonary fibrosis according to blood biomarkers to differentiate distinct disease patterns, known as endotypes. In this cluster analysis, we first classified patients from the PROFILE study, a multicentre, prospective, observational cohort of individuals with incident idiopathic pulmonary fibrosis or non-specific interstitial pneumonia in the UK (Nottingham University Hospitals, Nottingham; and Royal Brompton Hospital, London). 13 blood biomarkers representing extracellular matrix remodelling, epithelial stress, and thrombosis were measured by ELISA in the PROFILE study. We classified patients by unsupervised consensus clustering. To evaluate generalisability, a machine learning classifier trained on biomarker signatures derived from consensus clustering was applied to a replication dataset from the Australian Idiopathic Pulmonary Fibrosis Registry (AIPFR). Biomarker associations with mortality and change in percentage of predicted forced vital capacity (FVC%) were assessed, adjusting for age, gender, baseline FVC%, and antifibrotic treatment and steroid treatment before and after baseline. Mortality risk associated with the clusters in the PROFILE cohort was evaluated with Cox proportional hazards models, and mixed-effects models were used to analyse how clustering was associated with longitudinal FVC% in the PROFILE and AIPFR cohorts. 455 of 580 participants from the PROFILE study (348 [76%] men and 107 [24%] women; mean age 72·4 years [SD 8·3]) were included in the analysis. Within this group, three clusters were identified based on blood biomarkers. A basement membrane collagen (BM) cluster (n=248 [55%]) showed high concentrations of PRO-C4, PRO-C28, C3M, and C6M, whereas an epithelial injury (EI) cluster (n=109 [24%]) showed high concentrations of MMP-7, SP-D, CYFRA211, CA19-9, and CA-125. The third cluster (crosslinked fibrin [XF] cluster; n=98 [22%]) had high concentrations of X-FIB. In the replication dataset (117 of 833 patients from AIPFR; 87 [74%] men and 30 [26%] women; mean age 72·9 years [SD 7·9]), we identified the same three clusters (BM cluster, n=93 [79%]; EI cluster, n=8 [7%]; XF cluster, n=16 [14%]). These clusters showed similarities with clusters in the PROFILE dataset regarding blood biomarkers and phenotypic signatures. In the PROFILE dataset, the EI and XF clusters were associated with increased mortality risk compared with the BM cluster (EI vs BM: adjusted hazard ratio [HR] 1·88 [95% CI 1·42-2·49], p<0·0001; XF vs BM: adjusted HR 1·53 [1·13-2·06], p=0·0058). The EI cluster showed the greatest annual FVC% decline, followed by the BM and XF clusters. A similar FVC% decline pattern was observed in these clusters in the AIPFR replication dataset. Blood biomarker clustering in pulmonary fibrosis identified three distinct blood biomarker signatures associated with lung function and prognosis, suggesting unique pulmonary fibrosis biomarker patterns. These findings support the presence of pulmonary fibrosis endotypes with the potential to guide targeted therapy development. None.

Plasma biomarkers of amyloid, tau, axonal, and neuroinflammation pathologies in dementia with Lewy bodies

BackgroundIncreasing evidence supports the use of plasma biomarkers of amyloid, tau, neurodegeneration, and neuroinflammation for diagnosis of dementia. However, their performance for positive and differential diagnosis of dementia with Lewy bodies (DLB) in clinical settings is still uncertain.MethodsWe conducted a retrospective biomarker study in two tertiary memory centers, Paris Lariboisière and CM2RR Strasbourg, France, enrolling patients with DLB (n = 104), Alzheimer’s disease (AD, n = 76), and neurological controls (NC, n = 27). Measured biomarkers included plasma Aβ40/Aβ42 ratio, p-tau181, NfL, and GFAP using SIMOA and plasma YKL-40 and sTREM2 using ELISA. DLB patients with available CSF analysis (n = 90) were stratified according to their CSF Aβ profile.ResultsDLB patients displayed modified plasma Aβ ratio, p-tau181, and GFAP levels compared with NC and modified plasma Aβ ratio, p-tau181, GFAP, NfL, and sTREM2 levels compared with AD patients. Plasma p-tau181 best differentiated DLB from AD patients (ROC analysis, area under the curve [AUC] = 0.80) and NC (AUC = 0.78), and combining biomarkers did not improve diagnosis performance. Plasma p-tau181 was the best standalone biomarker to differentiate amyloid-positive from amyloid-negative DLB cases (AUC = 0.75) and was associated with cognitive status in the DLB group. Combining plasma Aβ ratio, p-tau181 and NfL increased performance to identify amyloid copathology (AUC = 0.79). Principal component analysis identified different segregation patterns of biomarkers in the DLB and AD groups.ConclusionsAmyloid, tau, neurodegeneration and neuroinflammation plasma biomarkers are modified in DLB, albeit with moderate diagnosis performance. Plasma p-tau181 can contribute to identify Aβ copathology in DLB.

Urinary Kidney Injury Molecule 1 and Urinary Monocyte Chemotactic Protein 1 as Novelbiomarkers for Early Detection of Sickle Cell Nephropathy

Abstract Background Sickle cell disease (SCD) is one of the most common genetic disorders, it not onlyhas hematological pathophysiological consequences, but also has systemic pathologicalmanifestations such as Sickle cell nephopathy(SN). There are no randomized control trials thatexamined the utility of screening test for renal disease in individuals with SCD. Aim of the Work To evaluate urinary monocyte chemoattractant protein-1 (MCP-1) and urinarykidney injury molecule 1 (KIM-1) as biomarkers for early detection of sickle cell nephropathy and correlate them with proteinuria and decline in estimate glomerular filtration rate ( eGFR). Patient and Methods This study was a cross sectional study, conducted at Pediatrics Hematology-Oncology Unit at Ain Shams University Children’s Hospital, where 45 children with sickle cell disease were enrolled aged 6 months - 16 years. Urine samples were collected to measure MCP-1and KIM-1 levels and compared to age and sex matched control. Results There was a statistically significant difference found between control group and patients’group regarding the level of MCP-1 in urine as it was found higher in patients than control group with median(IQR) values of 600 pg/ml (300–780) vs. 47.5 pg/ml (30–80, p &amp;lt; 0.001). Regarding the level of KIIM-1 in urine, it was found higher in patients than control group with median (IQR)values of 2.8 ng/ml (1.6–5.6) vs. 0.4 ng/ml (0.4–0.55, p&amp;lt;0.001) respectively. Conclusion Our data shows a distinct biomarker pattern in children with SCD, identifying KIM-1and MCP-1 as two potential biomarkers of early SN and its progression.

Integrated assessment of trace elements in a marine ranching area based on multi-species and multi-level biomarkers: a case study in China’s national-level marine ranching demonstration area

The goal of this study was to evaluate the trace element pollution in a marine ranching area in China based on molecular responses (expression of metallothionein and antioxidant enzyme genes), and biochemical biomarkers (metallothionein content, antioxidant enzyme activities, and malonaldehyde level) in four indicator species. We collected samples of two fish (Lateolabrax maculatus and Sebastes schlegelii), one crustacean (Charybdis japonica), and one gastropod (Rapana venosa) from the western Furong Island marine ranching area and from an adjacent area in March 2022 and measured the trace element content in these indicator species as well as in the seawater and sediment. We found that the bioaccumulation characteristics of trace elements and the response patterns of biomarkers were species specific. Moreover, not every biomarker was significantly correlated with environmental trace element content. We then established two biomarker combinations indicative of trace element pollution in seawater and sediment, respectively, based on the correlation between biomarkers and trace element contents. The selected biomarkers were integrated using integrated biomarker response version 2 (IBRv2). IBRv2 values in the studied marine ranching area were lower than those in the adjacent area. Additionally, these values were consistent with the bioaccumulation of trace elements in the indicator species, the integrated trace element pollution index for seawater, and the potential risk index for sediment. These results show that this multi-biomarker and multi-species IBRv2 approach provided a comprehensive diagnosis of trace element pollution in the marine ranching area. Therefore, its application may be beneficial for marine environmental monitoring and management in view of the ecotoxicological impact of pollutants on organisms.

Characterizing Common and Rare Variations in Nontraditional Glycemic Biomarkers Using Multivariate Approaches on Multiancestry ARIC Study.

Genetic studies of non-traditional glycemic biomarkers, glycated albumin and fructosamine, can shed light on unknown aspects of type 2 diabetes genetics and biology. We performed a multi-phenotype GWAS of glycated albumin and fructosamine from 7,395 White and 2,016 Black participants in the Atherosclerosis Risk in Communities (ARIC) study on common variants from genotyped/imputed data. We discovered 2 genome-wide significant loci, one mapping to known type 2 diabetes gene (ARAP1/STARD10) and another mapping to a novel region (UGT1A complex of genes) using multi-omics gene-mapping strategies in diabetes-relevant tissues. We identified additional loci that were ancestry- and sex-specific (e.g., PRKCA in African ancestry, FCGRT in European ancestry, TEX29 in males). Further, we implemented multi-phenotype gene-burden tests on whole-exome sequence data from 6,590 White and 2,309 Black ARIC participants. Ten variant sets annotated to genes across different variant aggregation strategies were exome-wide significant only in multi-ancestry analysis, of which CD1D, EGFL7/AGPAT2 and MIR126 had notable enrichment of rare predicted loss of function variants in African ancestry despite smaller sample sizes. Overall, 8 out of 14 discovered loci and genes were implicated to influence these biomarkers via glycemic pathways, and most of them were not previously implicated in studies of type 2 diabetes. This study illustrates improved locus discovery and potential effector gene discovery by leveraging joint patterns of related biomarkers across the entire allele frequency spectrum in multi-ancestry analysis. Future investigation of the loci and genes potentially acting through glycemic pathways may help us better understand risk of developing type 2 diabetes.

CSF and plasma biomarkers in cerebral amyloid angiopathy: A single-center study and a systematic review/meta-analysis.

There are limited data regarding cerebrospinal fluid (CSF) and plasma biomarkers among patients with Cerebral Amyloid Angiopathy (CAA). We sought to investigate the levels of four biomarkers [β-amyloids (Aβ42 and Aβ40), total tau (tau) and phosphorylated tau (p-tau)] in CAA patients compared to healthy controls (HC) and patients with Alzheimer Disease (AD). A systematic review and meta-analysis of published studies, including also a 5 year single-center cohort study, with available data on CSF and plasma biomarkers in symptomatic sporadic CAA versus HC and AD was conducted. Biomarkers' comparisons were investigated using random-effects models based on the ratio of mean (RoM) biomarker concentrations. RoM < 1 and RoM > 1 indicate lower and higher biomarker concentration in CAA compared to another population, respectively. We identified nine cohorts, comprising 327 CAA patients (mean age: 71 ± 5 years; women: 45%) versus 336 HC (mean age: 65 ± 5 years; women: 45%) and 384 AD patients (mean age: 68 ± 3 years; women: 53%) with available data on CSF biomarkers. CSF Aβ42 levels [RoM: 0.47; 95% CI: 0.36-0.62; p < 0.0001], Aβ40 levels [RoM: 0.70; 95% CI: 0.63-0.79; p < 0.0001] and the ratio Aβ42/Aβ40 [RoM: 0.62; 95% CI: 0.39-0.98; p = 0.0438] differentiated CAA from HC. CSF Aβ40 levels [RoM: 0.73; 95% CI: 0.64-0.83; p = 0.0003] differentiated CAA from AD. CSF tau and p-tau levels differentiated CAA from HC [RoM: 1.71; 95% CI: 1.41-2.09; p = 0.0002 and RoM: 1.44; 95% CI: 1.20-1.73; p = 0.0014, respectively] and from AD [RoM: 0.65; 95% CI: 0.58-0.72; p < 0.0001 and RoM: 0.64; 95% CI: 0.57-0.71; p < 0.0001, respectively]. Plasma Aβ42 [RoM: 1.14; 95% CI: 0.89-1.45; p = 0.2079] and Aβ40 [RoM: 1.07; 95% CI: 0.91-1.25; p = 0.3306] levels were comparable between CAA and HC. CAA is characterized by a distinct CSF biomarker pattern compared to HC and AD. CSF Aβ40 levels are lower in CAA compared to HC and AD, while tau and p-tau levels are higher in CAA compared to HC, but lower in comparison to AD patients.

Neurofilaments and progranulin are related to atrophy in frontotemporal lobar degeneration - A transdiagnostic study cross-validating atrophy and fluid biomarkers.

Frontotemporal lobar degeneration (FTLD) encompasses behavioral variant frontotemporal dementia (bvFTD), progressive supranuclear palsy, corticobasal syndrome/degeneration, and primary progressive aphasias (PPAs). We cross-validated fluid biomarkers and neuroimaging. Seven fluid biomarkers from cerebrospinal fluid and serum were related to atrophy in 428 participants including these FTLD subtypes, logopenic variant PPA (lvPPA), Alzheimer's disease (AD), and healthy subjects. Atrophy was assessed by structural magnetic resonance imaging and atlas-based volumetry. FTLD subtypes, lvPPA, and AD showed specific profiles for neurofilament light chain, phosphorylated heavy chain, tau, phospho-tau, amyloid beta1-42 from serum/cerebrospinal fluid, and brain atrophy. Neurofilaments related to regional atrophy in bvFTD, whereas progranulin was associated with atrophy in semantic variant PPA. Ubiquitin showed no effects. Results specify biomarker and atrophy patterns in FTLD and AD supporting differential diagnosis. They identify neurofilaments and progranulin in interaction with structural imaging as promising candidates for monitoring disease progression and therapy. Study cross-validated neuroimaging and fluid biomarkers in dementia. Five kinds of frontotemporal lobar degeneration and two variants of Alzheimer's disease. Study identifies disease-specific fluid biomarker and atrophy profiles. Fluid biomarkers and atrophy interact in a disease-specific way. Neurofilaments and progranulin are proposed as biomarkers for diagnosis and therapy.

Serial cardiac biomarkers, pulmonary artery pressures and traditional parameters of fluid status in relation to prognosis in patients with chronic heart failure: Design and rationale of the BioMEMS study.

Heart failure (HF), a global pandemic affecting millions of individuals, calls for adequate predictive guidance for improved therapy. Congestion, a key factor in HF-related hospitalizations, further underscores the need for timely interventions. Proactive monitoring of intracardiac pressures, guided by pulmonary artery (PA) pressure, offers opportunities for efficient early-stage intervention, since haemodynamic congestion precedes clinical symptoms. The BioMEMS study, a substudy of the MONITOR-HF trial, proposes a multifaceted approach integrating blood biobank data with traditional and novel HF parameters. Two additional blood samples from 340 active participants in the MONITOR-HF trial were collected at baseline, 3-, 6-, and 12-month visits and stored for the BioMEMS biobank. The main aims are to identify the relationship between temporal biomarker patterns and PA pressures derived from the CardioMEMS-HF system, and to identify the biomarker profile(s) associated with the risk of HF events and cardiovascular death. Since the prognostic value of single baseline measurements of biomarkers like N-terminal pro-B-type natriuretic peptide is limited, with the BioMEMS study we advocate a dynamic, serial approach to better capture HF progression. We will substantiate this by relating repeated biomarker measurements to PA pressures. This design rationale presents a comprehensive review on cardiac biomarkers in HF, and aims to contribute valuable insights into personalized HF therapy and patient risk assessment, advancing our ability to address the evolving nature of HF effectively.

Comprehensive analysis of TROP2, PD-L1, stromal (s)TILs, and HER2 expression patterns in patients (pts) with metastatic HR+HER2- breast cancer.

1062 Background: Immune checkpoint inhibitors (ICI) have shown limited efficacy in hormone receptor positive (HR+) metastatic breast cancer (mBC) and the optimal ICI-based combination is unknown. The TROP2 antibody-drug conjugate sacituzumab govitecan (SG) demonstrated antitumor activity with a 5.5-month median PFS in endocrine refractory HR+ mBC. Given SG's potential for anticancer immunity, we sought to evaluate expression patterns of biomarkers of interest in HR+ mBC. Methods: This retrospective study included pts with HR+HER2- mBC identified at DFCI between 10/2020 and 12/2021 who received 0-1 prior lines of chemotherapy in the metastatic setting and consented to analysis of archival FFPE tissue samples. We aimed to 1) characterize expression patterns of TROP2 (SP295 H-score), PD-L1 (22C3 CPS), sTILs and HER2 (per central pathology review) in the most recent available sample; 2) assess the prognostic value of selected biomarker combinations for overall survival (OS) defined as the time from consent to either death due to any cause or last follow-up (Cox proportional hazard models; p-value &lt;0.05 considered significant). Results: Among 142 pts included, median age at diagnosis was 46 yrs (IQR: 40–56). Baseline characteristics are shown (Table). At least one biomarker was available for 123 subjects (86.6%). TROP2 expression (n=61) was Medium/High (M-H: 101-300) in 43 pts (70.5%) and Low (L: 0-100) in 18 (29.5%). PD-L1 central assessment (n=120) revealed CPS ≥1 (PD-L1+) in 32 pts (26.7%) and &lt;1 (PD-L1-) in 88 (73.3%); only 7 (5.8%) pts had CPS ≥10. sTILs (n=87) were ≥10% in 14 pts (16.1%) and &lt;10% in 73 (83.9%). When analyzing TROP2 and PD-L1 (n=61), 15 pts (24.6%) were TROP2-M-H/PD-L1+, 28 (45.9%) were TROP2-M-H/PD-L1-, 5 (8.2%) were TROP2-L/PD-L1+, and 13 (21.3%) were TROP2-L/PD-L1-. When analyzing TROP2 and sTILs (n=54), 6 pts (11.1%) were TROP2-M-H/sTILs ≥10%, 32 (59.3%) were TROP2-M-H/sTILs &lt;10%, 2 (3.7%) were TROP2-L/sTILs ≥10% and 14 (25.9%) were TROP2-L/sTILs &lt;10%. For TROP2 and HER2 (n=46), 26 pts (56.5%) had TROP2-M-H/HER2-low tumors, 7 (15.2%) TROP2-M-H/HER2-0, 3 (6.5%) TROP2-L/HER2-low, and 10 (21.7%) TROP2-Low/HER2-0. Median OS (n=138) was 43.8 months; stratification for selected biomarker combinations will be presented although no statistical significance was found. Correlations with NGS data and HER2DX are ongoing and will be presented. Conclusions: Analyzing biomarkers of interest in pts with HR+ mBC unveiled diverse patterns, without associations with OS. Patient characteristics. [Table: see text]

Immunological biomarkers in patients with radiographic axial spondyloarthritis, an exploratory longitudinal Swedish study.

Objectives There is a need for more specific biomarkers to diagnose and predict disease course in patients with axial spondyloarthritis (axSpA). This study aimed to study immunological plasma biomarkers, at different time-points in radiographic (r)-axSpA patients overall and stratified by sex and compare these biomarker pattern in r-axSpA patients concerning disease phenotypes and disease activity. Methods Plasma samples were analysed from r-axSpA patients at and prior (Pre-Backbone) inclusion in the Backbone study. Interferon gamma, interleukin-10, -17A, -17F, -22, -23, -6, MCP-1, TNF-α, VEGF-A, MIF, IgA anti-CD74, zonulin, ESR, hsCRP, white blood cell count, and blood lipids were measured. Results Biomarker pattern discriminated significantly between r-axSpA patients in Backbone and Pre-Backbone compared with controls. When stratifying by sex, it was possible to discriminate between male and female r-axSpA patients in Backbone vs controls and between male r-axSpA patients in pre-Backbone and controls. In Backbone, markers with high discriminative capacity were MIF, IgA anti-CD74, and MCP-1. In Pre-Backbone, IL-6, TNF-α, MIF, triglycerides, cholesterol, IL-10, and zonulin displayed high discriminative capacity. Conclusion Based on their temporal pattern and mutual relationship, we suggest studying MIF, IgA anti-CD74, and MCP-1 in depth, at more time points, to further elucidate disease-driving mechanisms in this complex disease.