Plasma Proteomic Profiling Research Articles

Systemic changes induced by autologous stem cell ovarian transplant in plasma proteome of women with impaired ovarian reserves.

Patients with poor ovarian response (POR) and premature ovarian insufficiency (POI) are challenging to treat, with oocyte donation remaining as the only feasible option to achieve pregnancy in some cases. The Autologous stem cell ovarian transplantation (ASCOT) technique allows follicle development, enabling pregnancies and births of healthy babies in these patients. Previous results suggest that growth factors and cytokines secreted by stem cells are partially responsible for their regenerative properties. Indeed, ASCOT beneficial effects associate with the presence of different bone marrow derived stem cell- secreted factors in plasma. Therefore, the aim of this study was to assess whether ASCOT induce any modifications in the plasma proteomic profile of patients with impaired ovarian reserves. Discriminant analysis highlighted clear distinctions between the plasma proteome before (PRE), during stem cell mobilization and collection (APHERESIS) and three months after ASCOT (POST) in patients with POR and POI. Both the stem cell mobilization and ASCOT technique induced statistically significant modifications in the plasma composition, reversing some age-related protein expression changes. In the POR group, functional analysis revealed an enrichment in processes related to the complement cascade, immune system, and platelet degranulation, while in the POI group, enriched processes were also associated with responses to oxygen-containing compounds and growth hormones, and blood vessel maturation. In conclusion, our findings highlight the potential proteins and biological processes that may promote the follicle activation and growth observed after ASCOT. Identifying plasma proteins that regenerate aged or damaged ovaries could lead to more effective, targeted and/or preventive therapies for patients.

Protein profiling and assessment of amyloid beta levels in plasma in canine refractory epilepsy.

The relationship between epilepsy and cognitive dysfunction has been investigated in canines, and memory impairment was prevalent in dogs with epilepsy. Additionally, canines with epilepsy have greater amyloid-β (Aβ) accumulation and neuronal degeneration than healthy controls. The present study investigated plasma Aβ42 levels and performed proteomic profiling in dogs with refractory epilepsy and healthy dogs. In total, eight dogs, including four healthy dogs and four dogs with epilepsy, were included in the study. Blood samples were collected to analyze Aβ42 levels and perform proteomic profiling. Changes in the plasma proteomic profiles of dogs were determined by nano liquid chromatography tandem mass spectrometry. The plasma Aβ42 level was significantly higher in dogs with epilepsy (99 pg/mL) than in healthy dogs (5.9 pg/mL). In total, 155 proteins were identified, and of these, the expression of 40 proteins was altered in epilepsy. Among these proteins, which are linked to neurodegenerative diseases, 10 (25%) were downregulated in dogs with epilepsy, whereas 12 (30%) were upregulated. The expression of the acute phase proteins haptoglobin and α2-macroglobulin significantly differed between the groups. Complement factor H and ceruloplasmin were only detected in epilepsy dogs, suggesting that neuroinflammation plays a role in epileptic seizures. Gelsolin, which is involved in cellular processes and cytoskeletal organization, was only detected in healthy dogs. Gene Ontology annotation revealed that epilepsy can potentially interfere with biological processes, including cellular processes, localization, and responses to stimuli. Seizures compromised key molecular functions, including catalytic activity, molecular function regulation, and binding. Defense/immunity proteins were most significantly modified during the development of epilepsy. In Kyoto Encyclopedia of Genes and Genomes pathway analysis, complement and coagulation cascades were the most relevant signaling pathways affected by seizures. The findings suggested that haptoglobin, ceruloplasmin, α2-macroglobulin, complement factor H, and gelsolin play roles in canine epilepsy and Aβ levels based on proteomic profiling. These proteins could represent diagnostic biomarkers that, after clinical validation, could be used in veterinary practice as well as proteins relevant to disease response pathways. To determine the precise mechanisms underlying these relationships and their implications in canine epilepsy, additional research is required.

Molecular Pathogenesis of Central and Peripheral Nervous System Complications in Anderson-Fabry Disease.

Fabry disease (FD) is a recessive monogenic disease linked to chromosome X due to more than two hundred mutations in the alfa-galactosidase A (GLA) gene. Modifications of the GLA gene may cause the progressive accumulation of globotriaosylceramide (Gb3) and its deacylated form, globotriasylsphingosine (lyso-Gb3), in lysosomes of several types of cells of the heart, kidneys, skin, eyes, peripheral and central nervous system (not clearly and fully demonstrated), and gut with different and pleiotropic clinical symptoms. Among the main symptoms are acroparesthesias and pain crisis (involving the peripheral nervous system), hypohidrosis, abdominal pain, gut motility abnormalities (involving the autonomic system), and finally, cerebrovascular ischemic events due to macrovascular involvement (TIA and stroke) and lacunar strokes and white matter abnormalities due to a small vessel disease (SVS). Gb3 lysosomal accumulation causes cytoplasmatic disruption and subsequent cell death. Additional consequences of Gb3 deposits are inflammatory processes, abnormalities of leukocyte function, and impaired trafficking of some types of immune cells, including lymphocytes, monocytes, CD8+ cells, B cells, and dendritic cells. The involvement of inflammation in AFD pathogenesis conflicts with the reported poor correlation between CRP levels as an inflammation marker and clinical scores such as the Mainz Severity Score Index (MSSI). Also, some authors have suggested an autoimmune reaction is involved in the disease's pathogenetic mechanism after the α-galactosidase A deficiency. Some studies have reported a high degree of neuronal apoptosis inhibiting protein as a critical anti-apoptotic mediator in children with Fabry disease compared to healthy controls. Notably, this apoptotic upregulation did not change after treatment with enzymatic replacement therapy (ERT), with a further upregulation of the apoptosis-inducing factor after ERT started. Gb3-accumulation has been reported to increase the degree of oxidative stress indexes and the production of reactive oxygen species (ROS). Lipids and proteins have been reported as oxidized and not functioning. Thus, neurological complications are linked to different pathogenetic molecular mechanisms. Progressive accumulation of Gb3 represents a possible pathogenetic event of peripheral nerve involvement. In contrast, central nervous system participation in the clinical setting of cerebrovascular ischemic events seems to be due to the epitheliopathy of Anderson-Fabry disease with lacunar lesions and white matter hyperintensities (WMHs). In this review manuscript, we revised molecular mechanisms of peripheral and central neurological complications of Anderson-Fabry Disease. The management of Fabry disease may be improved by the identification of biomarkers that reflect the clinical course, severity, and progression of the disease. Intensive research on biomarkers has been conducted over the years to detect novel markers that may potentially be used in clinical practice as a screening tool, in the context of the diagnostic process and as an indicator of response to treatment. Recent proteomic or metabolomic studies are in progress, investigating plasma proteome profiles in Fabry patients: these assessments may be useful to characterize the molecular pathology of the disease, improve the diagnostic process, and monitor the response to treatment.

Plasma proteome profiling reveals metabolic and immunologic differences between Anorexia Nervosa subtypes

Aims/hypothesisAnorexia Nervosa (AN) is a severe psychiatric disorder of an unknown etiology with a crude mortality rate of about 5 % per decade, making it one of the deadliest of all psychiatric illnesses. AN is broadly classified into two main subtypes, restricting and binge/purging disorder. Despite extensive research efforts during several decades, the underlying pathophysiology of AN remains poorly understood. In this study, we aimed to identify novel protein biomarkers for AN by performing a proteomics analysis of fasting plasma samples from 78 females with AN (57 restrictive and 21 binge/purge type) and 70 healthy controls. MethodsUsing state-of-the-art mass spectrometry-based proteomics technology in conjunction with an advanced bioinformatics pipeline, we quantify >500 plasma proteins. ResultsDifferential expression analysis and correlation of proteomics data with clinical variables led to identification of a panel of novel protein biomarkers with potential pathophysiological significance for AN. Our findings demonstrate evidence of a humoral immune system response, altered lipid metabolism and potential alteration of plasma cells in AN patients. Additionally, we stratified AN patients based on the quantified proteins and suggest a potential autoimmune nature in the restrictive subtype of AN. Conclusions/interpretationIn summary, on top of biomarkers of AN subtypes, this study provides a comprehensive map of plasma proteins that constitute a resource for further studies of the pathophysiology of AN.

Plasma proteomics-based biomarkers for predicting response to mesenchymal stem cell therapy in severe COVID-19

BackgroundThe objective of this study was to identify potential biomarkers for predicting response to MSC therapy by pre-MSC treatment plasma proteomic profile in severe COVID-19 in order to optimize treatment choice.MethodsA total of 58 patients selected from our previous RCT cohort were enrolled in this study. MSC responders (n = 35) were defined as whose resolution of lung consolidation ≥ 51.99% (the median value for resolution of lung consolidation) from pre-MSC to 28 days post-MSC treatment, while non-responders (n = 23) were defined as whose resolution of lung consolidation < 51.99%. Plasma before MSC treatment was detected using data-independent acquisition (DIA) proteomics. Multivariate logistic regression analysis was used to identify pre-MSC treatment plasma proteomic biomarkers that might distinguish between responders and non-responders to MSC therapy.ResultsIn total, 1101 proteins were identified in plasma. Compared with the non-responders, the responders had three upregulated proteins (CSPG2, CTRB1, and OSCAR) and 10 downregulated proteins (ANXA1, AGRG6, CAPG, DDX55, KV133, LEG10, OXSR1, PICAL, PTGDS, and S100A8) in plasma before MSC treatment. Using logistic regression model, lower levels of DDX55, AGRG6, PICAL, and ANXA1 and higher levels of CTRB1 pre-MSC treatment were predictors of responders to MSC therapy, with AUC of the ROC at 0.910 (95% CI 0.818–1.000) in the training set. In the validation set, AUC of the ROC was 0.767 (95% CI 0.459–1.000).ConclusionsThe responsiveness to MSC therapy appears to depend on baseline level of DDX55, AGRG6, PICAL, CTRB1, and ANXA1. Clinicians should take these factors into consideration when making decision to initiate MSC therapy in patients with severe COVID-19.

TROP2 Is Associated with Primary Resistance to Immune Checkpoint Inhibition in Patients with Advanced Non-Small Cell Lung Cancer.

Mechanisms of primary resistance to inhibitors of the programmed cell death-1 (PD-1)/programmed death-ligand 1 (PD-L1) signaling axis in non-small cell lung cancer (NSCLC) are still poorly understood. While some studies suggest the involvement of trophoblast cell surface antigen 2 (TROP2) in modulating tumor cell resistance to therapeutic drugs, its specific role in the context of PD-1/PD-L1 axis blockade is not definitively established. We performed high-throughput analysis of transcriptomic data from 891 NSCLC tumors from patients treated with either the PD-L1 inhibitor atezolizumab or chemotherapy in two large randomized clinical trials. To confirm our results at the protein level, we complemented this transcriptional approach by performing a multiplex immunofluorescence analysis of tumor tissue samples as well as a proteomic profiling of plasma. We observed a significant association of TROP2 overexpression with worse progression-free survival and overall survival on PD-L1 blockade, independent of other prognostic factors. Importantly, we found increased TROP2 expression to be predictive of survival in patients treated with atezolizumab but not chemotherapy. TROP2 overexpression was associated with decreased T-cell infiltration. We confirmed these results at the proteomic level both on tumor tissue and in plasma. Our results suggest an important contribution of TROP2 expression to the primary resistance to PD-L1 blockade in NSCLC. TROP2-biomarker-based strategy may be relevant in selecting patients with NSCLC who are more likely to benefit from a combination of immunotherapy and an anti-TROP2 agent.

Discovery‐based proteomics identifies plasma proteins that predict longitudinal cognitive decline in older adults over a 7‐year follow‐up period

AbstractBackgroundRecent technological advances have enabled large‐scale proteomic profiling of plasma and especially in studies of Alzheimer’s disease. However, studies that have comprehensively examined longitudinal cognitive decline as an outcome from plasma protein levels prior to the onset of clinical dementia are limited. This project aimed to identify plasma proteins predictive of cognitive decline across a robust neuropsychological protocol over a 7‐year follow‐up period.MethodsVanderbilt Memory and Aging Project participants (n = 333, 73±7 years, 41% female) free of clinical dementia at study entry underwent fasting blood draw and comprehensive serial neuropsychological assessment over a 7‐year period (mean follow‐up = 5.8 years). Plasma samples were subjected to multiplex liquid chromatography tandem mass spectrometry analysis to quantify cross‐sectional protein abundances for each participant at study entry. Normalization of proteomic data adjusted for batch effects, high levels of missingness, and log2 transformation. Linear mixed‐effects regressions related protein levels to longitudinal neuropsychological outcomes, adjusting for age, sex, race/ethnicity, education, baseline cognitive status, apolipoprotein E ε4 status, and follow‐up time. False discovery rate correction was applied to the a priori significance threshold.ResultsInitial proteomics analyses yielded 3,784 proteins, of which 686 were used as analytical predictors following quality control, post‐acquisition filtering, and data normalization. Regression analyses resulted in 86 proteins which predicted longitudinal decline in global cognition, as assessed by the Montreal Cognitive Assessment. In analyses with individual neuropsychological domains as outcomes, 144 proteins predicted longitudinal decline in at least one neuropsychological domain [episodic memory (40 proteins), language (72 proteins), information processing speed (99 proteins), executive function (22 proteins), visuospatial skills (55 proteins)]. There was a smaller number of proteins (i.e., five) that were predictive of longitudinal cognitive decline across all domains.ConclusionWe conducted large‐scale proteomics analyses and identified 144 plasma proteins at study entry among a cohort of older adults free of clinical dementia that predict subsequent decline in cognition over a 7‐year follow‐up period. Five of these proteins were predictive of decline across all domains suggesting these proteins may represent biological pathways that adversely affect brain health with increasing age. Replication is needed to validate identified proteins as potential biomarkers of cognitive decline.

Nowhere to run, nowhere to hide ‐ targeting the immune system in AD with multimodal plasma therapeutics

AbstractBackgroundAge‐related diseases, especially Alzheimer’s Disease (AD), have multifaceted nature because of the different factors and pathways contributing to these diseases. Multi‐modal plasma therapies have the potential to impact multiple pathways and modulate different mechanisms of diseases in a safe and versatile way. Here we discuss insights from deep plasma proteomics profiling in patients from the GRF6019 and AMBAR clinical trials in which multi‐modal plasma therapeutics were used and limited cognitive decline was observed.MethodThe GRF6019 phase 2 trials were based on the infusion of a complex plasma fraction while the AMBAR phase 2b/3 trial used plasma exchange and albumin replacement (PE‐Alb). Patients in these trials were mild‐to‐moderate AD and 1143 plasma samples were analyzed using the SomaScan platform. The trajectories of 7k proteins were analyzed using classic and new machine learning techniques.ResultGRF6019 infusion resulted in an acute and broad impact on the plasma proteome but the detectable long‐term effects on molecular level were minimal. Pathways analysis of protein trajectories pointed out to the immune system, ECM remodeling but also brain specific biological processes linked to neurons and axon guidance, suggesting that various biological pathways were significantly modulated (q&lt;0.05). PE‐Alb treatment also induced an acute effect on several hundreds of proteins (461 proteins with log2FC←1 &amp; q&lt;0.05) but some proteomics changes lasted for weeks after the end of the intensive period (25 proteins with q&lt;0.05). A significant part of these changes (19% of acute and 56% of lasting response proteins) were related to immune and inflammatory‐related pathways. In addition, several individual proteins from the immune pathway were associated with improvement of CDR‐SB or ADCS‐CGIC at the end of the AMBAR trial suggesting that multiple parts of the immune system might need to be targeted to slow‐down AD progression.ConclusionAD has multifaceted nature and plasma therapeutics have proven safety, efficacy, and versatility. The proteomics results from these trials shed the light on the underlying mode of action of multi‐modal plasma‐derived therapies and demonstrate that they can modulate multiple pathways relevant to AD, with a strong effect on the immune and inflammatory responses which may contribute to slowing down AD progression.

Plasma Proteomic Signature Predicts Risk of Myeloid Neoplasm

Introduction The presence of clonally expanded mutant hematopoietic stem cells, clonal hematopoiesis (CH) is known to predispose to hematologic malignancy, particularly myeloid neoplasms (MN). However, the overall risk of developing MNs among individuals with CH is low (&amp;lt;1% per year). Limitations in our ability to predict who with CH will progress to MN is a barrier to prevention strategies. The human proteome reflects the downstream impact of complex interactions between genetic and epigenetic regulation of biologic systems. We hypothesized that plasma proteomic markers might be associated with MN risk and if so could inform our understanding of the mechanisms promoting the progression of CH to MN. Methods Among 46,237 individuals in the UK Biobank (UKB) with whole exome sequencing data and single nucleotide polymorphism (SNP) array profiling of the blood and plasma proteomic profiling using the Olink Explore platform (1,463 unique proteins), we jointly characterized CH and plasma proteomic profile. Cox proportional hazard models were used to assess the association between the level of each plasma protein and risk of MN; while controlling for age, sex, genetic ancestry, smoking status, blood counts, and sample collection year. The relative contribution of clinical, CH, and proteomics features in prediction of incident MN was assessed using lasso regression with 100-fold cross validation. We performed protein quantitative trait loci (pQTL) mapping to identify independent germline autosomal genetic loci that significantly regulate plasma proteomic levels (p &amp;lt;5x10 -8). We calculated genetically predicted risk scores for plasma protein levels as the as the sum of the effect estimates from linear regression analysis with additive genetic effect, multiplied by the number of risk alleles for each locus. As a validation cohort, we used an independent set of 427,614 individuals in the UKB to test for an association between genetically predicted levels of proteomic markers and MN risk. Results A total of 115 participants developed MN at least 3 months after study entry (median 83 months). As expected, participants who developed MN (cases) had a higher frequency of CH at the time of study entry compared to those free of hematologic malignancy (controls); 42 versus 6% for SNV/Indels and 23 versus 3% for mosaic copy number events in cases compared to controls respectively. We identified 115 proteins significantly associated (qFDR &amp;lt;0.05) with incident MN (Figure 1). These include known regulators of the adaptive immune system, innate immune system, leukocyte trafficking, hematopoietic stem cell self-renewal, and platelet activation. Given that CH is a genetic precursor to MN, we assessed the relationship between plasma proteomic markers of MN and CH. Among the 115 plasma proteins that were significantly associated with MN, 35 were significantly (qFDR &amp;lt;0.05) and 59 nominally (p &amp;lt;0.05) associated with CH. After adjusting for CH, the strength of the association between plasma protein markers and MN risk was generally reduced (mean 7%), but remained significant for many (N=44). We identified a total of 79 plasma proteins that were associated with the presence of CH at the time of study entry, 34 of which overlapped with MN risk proteins. Inclusion of proteomics features in a lasso regression model (AUC = 0.85) improved prediction of incident MN beyond clinical factors and CH (AUC = 0.80; Figure 2). There were 1,282 independent genetic loci that were significantly associated with 115 proteomic markers of MN risk. On average, genetic risk scores captured 12% of the total variance of plasma protein levels (range 0.1-64%). In an independent cohort of 427,614 UKB participants (1,099 of whom developed MN), we found that of the 110 plasma protein markers with a genetic risk score R 2 &amp;gt;1%, 12 were significantly associated with MN (p &amp;lt;0.05). Of the remaining, 63 were directionally consistent. Conclusions We show that plasma proteomic markers predict risk of MN. Some, but not all of the impact of plasma proteomic profile on MN risk is mediated by baseline CH. Inclusion of proteomic markers improves MN risk prediction beyond clinical and CH features. Genetic risk score analysis provides orthogonal validation of the plasma proteomic signature for MN risk. These data highlight the promise of protein and genetic biomarker integration for early diagnosis of MN and further support the role of immune cell regulation in early leukemogenesis.

Plasma Proteome Profiling of Sickle Cell Patients Reveals Activation of Inflammatory Pathways during Steady State and Vaso-Occlusive Crisis

Background The pathophysiology of Sickle Cell Disease (SCD) is characterized by chronic intravascular hemolysis and ischemia-reperfusion, resulting in oxidative stress and chronic inflammation. Although inflammation seems to play an important role in the development of tissue damage in SCD, little is known about the various cellular and cytokine pathways involved in the pathophysiology of SCD. This study aims to further elucidate the inflammatory pathways in SCD using targeted plasma protein profiling both in steady state and during vaso-occlusive crisis (VOC). Methods In this prospective study, SCD patients with the genotypes HbSS and HbSβ 0-thalassemia and healthy ethnicity matched controls were included. Plasma levels of 92 proteins involved in various inflammatory pathways were measured in EDTA plasma using Olink Proximity Extension Assay (PEA) technology. In brief, pairs of oligonucleotide-labeled antibody probes were added to 20 μL of plasma, resulting in the binding of these antibody probes to their targeted protein. Subsequently DNA polymerase was added, leading to a proximity-dependent DNA polymerization event, generating a unique PCR target sequence. The final assay read-out is presented in Normalized Protein eXpression (NPX) values, which is an arbitrary unit on a log2-scale with an NPX difference (estimate) of 1 meaning a doubling of protein concentration. RStudio version 4.2.1 was used for data analysis and visualization. Differences between subgroups were tested using an unpaired or paired t-test as appropriate. Results were corrected for multiple testing using the Benjamini-Hochberg method. Results with p &amp;lt; 0.05 were considered significant. Furthermore Over-representation Analysis (ORA) was performed to investigate the association of the differentially expressed proteins with specific biological processes. Results Plasma samples were collected from 43 SCD patients in steady state (median age: 25 years (IQR: 20 - 32)) and 13 healthy ethnicity matched controls (median age: 29 (IQR: 28-39)). From 15 SCD patients plasma samples were collected during both steady state and VOC (median age: 27 (IQR: 19 - 34)). Comparison of protein levels between healthy controls and SCD patients in steady state identified 38 proteins (IL-18, ANGPT2, Gal-9, CD4, HGF, HO-1, CCL4, ARG1, ADA, GZMA, PD-L1, CCL23, LAG3, TNFRSF4, CCL3, CXCL11, CRTAM, IL-10, GZMB, CD27, FGF2, IL-8, IL-6, TNF, PGF, NCR1, TNFSF14, CASP-8, IL-7, FASLG, TNFRSF9, LAP TGF-beta-1, PD-L2, CCL19, CD83, GZMH, MCP-4, CD244, TIE2) that were significantly higher in SCD patients as shown in Figure 1. Furthermore soluble CD70 was significantly lower in SCD patients in steady state compared to healthy controls (estimate: -0.34, p &amp;lt; 0.05). Over-representation Analysis revealed a significant upregulation of proteins involved in the regulation of hematopoiesis, the IL-18 signaling pathway, T-cell activation, leukocyte differentiation and leukocyte adhesion (Figure 2). Pairwise comparison of protein levels between steady state and VOC in SCD patients revealed 6 proteins (TWEAK, VEGFR-2, CD244, PDCD1, GZMA, TNFRSF4) which were significantly lower and 12 proteins (IL-6, TNFSF14, ADA, IL-15, HGF, IL-10, IL-8, Gal-9, CSF-1, CCL20, MMP7, VEGFA) which were significantly higher during VOC as compared to steady state. During VOC, pathways involved in the regulation of cell death (IL-6, TNFSF14, ADA, HGF, IL-10, PDCD1, VEGFA) and tissue development (IL-6, ADA, HGF, IL-10, VEGFA) were significantly enriched. Summary/conclusion The results of these proteomic analyses provide new insights into the pathways that regulate inflammation in SCD, both during steady state and VOC. These findings might contribute to a better understanding of SCD pathophysiology and identifying potential new targets for therapeutic interventions in SCD patients. Our results warrant further in-depth investigation of the different activated pathways.

An enhanced label-free proteomics approach for deep-diving into equine plasma proteome, including the discovery of protein biomarkers for strenuous exercise.

Plasma proteins have been a valuable source of biomarkers for clinical uses and for monitoring of the illicit use of prohibited substances or practices in equine sports. We have previously reported the first use of label-free proteomics in profiling equine plasma proteome. This study aimed to refine the method by systematically evaluating various plasma fractionation methods and the use of narrower precursor mass ranges in data-independent acquisition (DIA) mass spectrometry (MS). Tandem fractionations of equine plasma with octanoic acid precipitation followed by solid-phase extraction (SPE) with C4 cartridges provided the largest increase in the number of new proteins identified. The use of two narrow precursor mass ranges of m/z 400-600 and 600-800 in DIA not only identified most proteins detectable by using a single mass range of m/z 350-1500 but also identified ~27% more proteins. The improved method was applied to analyse the plasma proteome of 'postrace' samples which, unlike other samples, had been collected from racehorses soon after racing. Multivariate data analysis has identified upregulation of 14 proteins and downregulation of six proteins in postrace plasma compared with the non-postrace plasma samples. Literature review of these proteins has provided evidence of exercise-induced haemolysis and changes in antioxidant enzyme activities, kinin system, insulin signalling and energy metabolism after strenuous exercise. The improved method has enabled a deeper profiling of the equine plasma proteome and identified the proteins associated with normal physiological changes after racing which are potential confounding factors in the development of a biomarker approach for doping control.

Clinical characterization and proteomic profiling of lean nonalcoholic fatty liver disease.

Obesity has been historically associated with nonalcoholic fatty liver disease (NAFLD), but it can also occur in lean individuals. However, limited data is available on this special group. To investigate the clinical and proteomic characteristics of lean subjects with NAFLD, and to identify potential clinical variables and plasma proteins for diagnosing NAFLD in lean individuals, we collected clinical data from a large cohort of 2,236 subjects. Diagnosis of NAFLD relied on detecting pronounced hepatic steatosis through abdominal ultrasonography. Participants were categorized into four groups based on body mass index: overweight NAFLD, overweight control, lean NAFLD, and lean control. Plasma proteomic profiling was performed on samples from 20 subjects in each group. The lean NAFLD group was compared to both lean healthy and obese NAFLD groups across all data. The results indicated that the lean NAFLD group exhibited intermediate metabolic profiles, falling between those of the lean healthy and overweight NAFLD groups. Proteomic profiling of plasma in lean subjects with or without NAFLD revealed 45 statistically significant changes in proteins, of which 37 showed high diagnostic value (AUC > 0.7) for lean NAFLD. These potential biomarkers primarily involved lipid metabolism, the immune and complement systems, and platelet degranulation. Furthermore, AFM, GSN, CFH, HGFAC, MMP2, and MMP9 have been previously associated with NAFLD or NAFLD-related factors such as liver damage, insulin resistance, metabolic syndromes, and extracellular homeostasis. Overall, lean individuals with NAFLD exhibit distinct clinical profiles compared to overweight individuals with NAFLD. Despite having worse metabolic profiles than their healthy counterparts, lean NAFLD patients generally experience milder systemic metabolic disturbances compared to obese NAFLD patients. Additionally, the plasma proteomic profile is significantly altered in lean NAFLD, highlighting the potential of differentially expressed proteins as valuable biomarkers or therapeutic targets for diagnosing and treating NAFLD in this population.

Abstract 11317: Comprehensive Plasma Proteomics Profiling Identifies Signaling Pathways Dysregulated in Genotype-Positive versus Genotype-Negative Patients With Hypertrophic Cardiomyopathy

Introduction: Only a subset of patients with hypertrophic cardiomyopathy (HCM) have positive genotype. Although genotype-positive patients with HCM are known to have worse prognosis than genotype-negative patients, the underlying mechanism is unclear. Hypothesis/Aims: To test the hypothesis that plasma proteomics profiling identifies signaling pathways that are dysregulated in genotype-positive patients with HCM compared with those with negative genotype. Methods: In this multi-center study, we conducted plasma proteomics profiling of 4986 proteins in patients with HCM who underwent genetic testing. The outcome measure was positive genotype, defined as having a mutation that is pathogenic or likely pathogenic for HCM. We identified plasma proteins with significant (univariable P&lt;0.05) differences in concentration between patients with positive and negative genotype in HCM using the Mann-Whitney-Wilcoxon test. Using these proteins, we performed pathway analysis to determine dysregulated pathways with false discovery rate &lt;0.05. Results: A total of 340 patients with HCM underwent genotyping and 103 patients (30%) had positive genotype for HCM. Among the 4986 proteins, 844 (17%) had significant differences between patients with positive and negative genotypes - a larger percentage than what is expected by chance. Pathway analysis exhibited that both pathways known to be associated with poor prognosis (e.g., TGF-β, metabolic, and inflammation) and novel pathways (e.g., Ras-MAPK and associated pathways such as Pl3K-Akt and JAK-STAT) were dysregulated in genotype-positive patients with HCM compared to those who were genotype-negative ( Figure ). Conclusions: This study serves as the first to apply comprehensive proteomics profiling to identify signaling pathways that are differentially regulated in patients with positive genotype in the HCM population, elucidating dysregulation of both known (e.g., TGF-β) and novel (e.g., Ras-MAPK) pathways.

Abstract 15726: Large-Scale Plasma Proteomics and Mendelian Randomization of Cardiovascular Performance and Peak Arterio-Venous Oxygen Difference Identify Novel Biology Related to VO 2 max

Introduction: VO 2 max is the product of maximal cardiac output (Q) (maximal stroke volume (SVmax) x heart rate) and peak arterio-venous oxygen content difference (a-vO 2 diff). SVmax and peak a-vO 2 diff have important implications across the spectrum of human health and performance. However, the molecular mechanisms underlying SVmax and peak a-vO 2 diff remain largely unknown. We characterize SVmax and peak a-vO 2 diff using large-scale plasma proteomics and genotyping to identify circulating proteins and putative mediators of these traits. Methods: 763 physically inactive adults without overt cardiovascular disease underwent cardiopulmonary exercise testing with rigorous measurements of Q. High-throughput plasma proteomic profiling was performed to identify proteins associated with SVmax, a-vO 2 diff, and VO 2 max. cis-Mendelian Randomization (MR) analysis was conducted to assess causal relationships between protein markers and cardiovascular performance traits. Results: Proteomic profiling revealed associations between SVmax and several adiposity-related proteins, as well as secretory muscle factors (cathepsin B, α-actinin 2, and troponin I) (Figure). Proteins associated with peak a-vO2diff reflected oxygen-carrying capacity, muscle biology, and glucose metabolism (erythropoietin, myoglobin, fructose-1,6-bisphosphatase). Significant overlap was observed between proteins associated with SVmax, a-vO 2 diff, and VO 2 max. Cis-MR identified myocilin (MYOC) and caspase recruitment domain family member 9 (CARD9) as potential mediators of cardiovascular performance and VO 2 max. Conclusions: This study provides novel insights into the molecular influences of cardiovascular performance and VO 2 max. The identified protein markers associated with SVmax and a-vO 2 diff, along with the possible mediators MYOC and CARD9, merit further investigation into their role in endurance exercise capacity and cardiometabolic health.

Abstract 15735: Antibody-Based Plasma Proteomics Profiling Reveals New Markers of Cardiorespiratory Fitness

Background: Plasma proteins can be biomarkers of cardiovascular health status but also physiologic effectors that mediate health benefits. Cardiorespiratory fitness (CRF) is an integrative measure of cardiovascular and metabolic health and independent predictor of future cardiovascular disease (CVD) and mortality risk, however limited knowledge exists regarding its molecular transducers. We sought to expand upon prior proteomic studies of CRF using an antibody-based technology (Olink TM ). Hypothesis: Olink proteomic profiling will identify new markers and potential mediators of CRF. Methods: We measured plasma proteins (N=1,472) using Olink’s platform in a pilot study within the HERITAGE Family Study (N=209 participants, mean age=34 years, 56% female, 36% Black) before and after 20 weeks of endurance exercise training (ET). We performed multivariable linear regression to measure the association between protein levels and CRF measured by CPET (VO 2 max in ml*kg -1 *min -1 ) adjusting for age and sex. Lean body mass was measured by hydrostatic weighing. Protein changes after ET were assessed using paired Student’s t-tests. Results: We identified 70 proteins significantly associated (FDR q &lt;0.05) with VO 2 max. Among these, 14 have not previously been measured in the context of CRF, including perilipin-1, a modulator of lipid homeostasis in adipocytes (beta=-3.8, q=2.4x10 -4 ); latent-transforming growth factor beta-binding protein 3 (beta=-2.6, q=1.3x10 -3 ), a key regulator of TGF-beta activation; and hydroxysteroid 11-beta dehydrogenase 1 (beta=3.2, q=1.2x10 -3 ), which regulates cortisol metabolism. Carbonic anhydrase (CA) XIV (CA14; beta=5.4, q=1.3x10 -8 ), a member of the CA family with extracellular activity, had the strongest positive association with VO 2 max in our primary model as well as after further adjusting VO 2 max for lean body mass. Further, CA14 levels increased significantly after ET (log2 fold change: 0.14, q=0.007). Conclusions: Antibody-based plasma proteomics profiling identified new markers of CRF, including a CA isoform that increases after ET. These findings motivate further study of CA14’s mechanistic role in CA14 and expanded proteomics profiling to investigate molecular transducers of CRF.

Abstract 17527: Plasma Proteomic Representations of Central Hemodynamics Over Time in Heart Failure

Introduction: Perturbation of central hemodynamic parameters are defining features in heart failure (HF) and strong prognostic factors, including increased filling pressures, reduced cardiac output (CI), extended blood circulation times and increased peripheral oxygen extraction (ΔAVO2). Invasive catheterization is used for precise assessment of central hemodynamics. Hypothesis: We postulated that plasma proteins may serve as non-invasive representations of central hemodynamics in HF patients. Methods: Affinity-based plasma proteomic profiling of 1305 proteins was applied to a cohort of patients with advanced HF undergoing invasive cardiac catheterization before and 6 months after heart transplantation. A total of 30 central hemodynamic parameters were measured and calculated. Protein profiles associated with central hemodynamics over time were identified from repeated-measures models. Results: We identified 1304 associations for 201 unique proteins meeting our Bonferroni-adjusted significance threshold (p&lt;1x10-6) for at least one hemodynamic parameter. Most of the 201 proteins were associated with more than one parameter. Most proteins (70%) associated with parameters in more than one of five domains (filling pressures, left ventricular (LV) function, right ventricular (RV) function, systemic arterial function, pulmonary arterial function). No proteins were associated with 6 of the 30 hemodynamic parameters, which changed little after transplantation and related to arterial function or RV function. The largest number of protein associations were observed for RAP, cardiac power index, left ventricular stroke work index, and ΔAVO2 followed by systolic blood pressure, CI, and PAWP (&gt;80). These include expected associations of natriuretic peptides, ST2 with LV function, filling pressures and of angiotensinogen with vascular function parameters. We further describe the discriminatory ability of identified proteins for clinically relevant differences in key hemodynamic parameters. Conclusions: We have identified circulating biomarkers to non-invasively monitor central hemodynamics in HF over time. Our findings may also inform understanding of pathways involved in HF pathophysiology and circulatory regulation.

Detection of early prognostic biomarkers for metastasis of Ewing's sarcoma in pediatric patients

AimsEwing's Sarcoma is an extremely aggressive tumor in children. The disease is associated with highly metastatic rate, especially at the time of diagnosis, contributing to a lower survival rate and poor prognosis. The study aimed to identify predictive biomarkers for metastatic Ewing's sarcoma through in-depth analysis of the plasma proteome profile of pediatric Ewing's sarcoma patients. Main methodsPlasma samples from Ewing's sarcoma patients and control individuals were profiled using both shotgun and dimethyl-labeled proteomics analysis. Subsequently, Ewing's sarcoma patients were further stratified according to their metastatic state and chemotherapy response. Western blot was used for validation. Univariate and multivariate analyses were performed to determine proteome metastasis predictors. Receiver operating characteristic (ROC) analysis was done to assess the diagnostic significance of the potential plasma Ewing's sarcoma biomarkers. Key findingsOur results revealed a set of proteins significantly associated with the metastatic Ewing's sarcoma disease profile. These proteins include ceruloplasmin and several immunoglobulins. Additionally, our study disclosed significant differentially expressed proteins in pediatric Ewing's sarcoma, including CD5 antigen-like, clusterin, and dermcidin. Stable isotope dimethyl labeling and western blot further confirmed our results, strengthening the impact of such proteins in disease development. Furthermore, an unbiased ROC curve evaluated and confirmed the predictive power of these biomarker candidates. SignificanceThis study presented potential empirical predictive circulating biomarkers for determining the disease status of pediatric Ewing's sarcoma, which is vital for early prediction.

High-Throughput Plasma Proteomics to Define the Precursor Multiple Myeloma Proteome and Identify Candidate High-Risk Disease Biomarkers of Progression

Introduction Multiple Myeloma (MM) develops from well-defined precursors Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering Multiple Myeloma (SMM), where patients remain stable or may unknowingly rapidly progress. Bone marrow (BM) biopsies are not routine for precursor disease management, and precursor patients are limited to monitoring few proteins within peripheral blood (PB) for signs of progressive disease. Deep proteome profiling of PB circulating proteins may help track disease; however, the dynamic range of the plasma proteome has limited the depth of detection for MS-based proteomics without first depleting abundant proteins and fractionating the samples after digestion to peptides. Technological advancements in multiplex immunoassays with low cross-reactivity and off-target events have enabled plasma profiling for disease stage classification, defining high-risk disease features, and novel therapeutic target discovery. Here, we perform the first comprehensive plasma proteomic profiling study on patients across the MM disease continuum and longitudinal sequential samples from progressive and stable disease. Methods We carried out high-throughput plasma proteomic profiling for approximately 3000 proteins simultaneously using the Olink® Explore 3072 library and Proximity Extension Assay (PEA) technology. Targeted proteins are recognized by multiplexed, matched pairs of antibodies labelled with unique DNA oligonucleotides that upon binding come into proximity, hybridize, and are extended to generate a unique sequence for protein identification with NextGen DNA sequencing. We profiled 423 PB plasma samples from 348 individuals, including MGUS (n=67), SMM (n=179), MM (n=44), and healthy controls (n=58). Sequential samples from patients with progressive disease (n=27) and patients with stable disease with matched clinical follow-up time were also profiled. Precursor defined samples from progressors ranged 1.03-5.88 yrs prior to diagnosis and were untreated in the precursor setting, while MM disease samples were also collected prior to any active disease therapy. Patients had a median clinical follow-up time of 7.05 years. T-tests, ANOVAs, and a linear mixed effect (LME) model were used to identify proteins that change across disease stages, progression status, and time. Results were adjusted for multiple testing using the Benjamini-Hochberg Method. Results We identified 751 significantly dysregulated proteins with the majority upregulated in progressive disease. We captured circulating levels of proteins highly expressed on the surface of plasma cells, including CD38, SDC1, BCMA and SLAMF7, highlighting the utility of PEA technology to monitor clinically-relevant targets for which monoclonal antibodies, antibody-drug conjugates, CAR-T and BiTE therapies are being developed. We identified proteins that significantly distinguished MGUS, SMM, and NDMM from healthy donors (n=222, 423 and 494), where increasing B-cell maturation antigen (BCMA) was a significant classifier and positive control. Consistent with previous findings, baseline BCMA levels were also significantly elevated in SMM-MM progressors vs. SMM non-progressors, further supporting the potential utility of BCMA measurements during routine blood tests of precursor MM patients. Proinflammatory cytokines were also identified, including IL1, IL5, IL6, IL16, and IL18, known to create a BM environment that promotes malignant cell development by suppressing the microenvironment, promoting cellular adhesion, or increasing angiogenesis. Four novel proteins that are vital for calcium homeostasis and integrin-mediated cell adhesion significantly increased from healthy to MM and were also significantly elevated in SMM progressors vs. SMM non-progressors, nominating these proteins as candidate biomarkers of high-risk disease. Conclusion We performed the most comprehensive plasma proteomics study to date, which characterized disease stage proteomes and identified candidate high-risk disease biomarkers in longitudinal progressor samples. Further advancements are underway to validate the accuracy levels of the novel candidates, test the performance of a classification model that recognizes disease stage-specific proteins, and determine how best to integrate proteins into current MM risk stratification models.

CAR T-Related Toxicities Based on Dynamic Proteomic Profiles Identifies Risk Factors for Cytokine Release Syndrome (CRS) and Immune Effector Cell -Associated Neurotoxicity Syndrome (ICANS)

TK and SM are Co-first authors INTRODUCTION Treatment with chimeric antigen receptor (CAR) T-cells significantly improved outcomes in relapsed/refractory non-Hodgkin lymphoma (NHL) and multiple myeloma (MM). CAR-T activation and anti-tumor cytotoxicity are associated with bystander inflammatory reactions resulting in CRS and/or ICANS. Due to complex cytokine profiles, disease heterogeneity, and variability between commercial CAR-T products, identification of risk factors associated with CRS and/or ICANS has been challenging. In this study, we used plasma proteomic profiling at different timepoints to identify possible inflammatory mediators associated with CRS and ICANS METHODS We prospectively collected plasma samples from patients who received CAR-T cells therapy between 9/2021 to 12/2022 at several time points - before lymphodepletion chemotherapy on day -5 (relative to CAR-T cell infusion), prior to CAR T-cell infusion on day 0, and post CAR T-cell therapy on days 1, 2, 3, and 7. Protein profiling analyses were conducted at Eve Technologies (Calgary, Alberta, Canada) using an assay measuring 71 total cytokines and chemokines. Proteins levels were compared across different time points used Wilcoxon rank test, while features associated with CRS/ICANS were identified using logistic regression. Receiver operating characteristic (ROC) analysis used to identify variables predictive for CRS. Area under the curve (AUC) of at least 0.8 was used and best cutoffs were determined according to Youden index. P-values &amp;lt;0.05 were considered statistically significant. This study was supported in part by The Frederick A. Deluca Foundation. RESULTS Overall, 56 patients with available cytokine assays at all time points were included. The median age was 65 years (IQR: 57-74) and 70% were men. Of all patients, 26 (46%) had diffuse large B-cell lymphoma (DLBCL), 23 (41%) MM, 4 (7%) mantle cell lymphoma, and 3 (6) follicular lymphoma. Ide-cel (39%), liso-cel (36%), and axi-cel (17%) were the most used CAR-T cell products. All patients received lymphodepleting chemotherapy with fludarabine/cyclophosphamide. In total, 35 (63%) patients developed CRS (grade 1, 89%; grade 2, 8%; grade 3, 3%) and 18 (32%) patients developed ICANS (grade 1, 72%; grade 2, 22%; grade 3, 6%). Compared to patients who did not develop CRS, patients with CRS had lower median absolute lymphocyte counts at day -5 (0.02 x10 9/L vs. 0.05, p=0.0146), higher baseline CRP (13 vs. 4 mg/L, p=0.0005), and higher ferritin (914 vs. 442 mg/L, p=0.048). No differences in the type of CAR-T products (p=0.090), percentages of DLBCL or MM (p=0.270) were observed between CRS and no CRS cohorts ( Panel-A). First, we investigated the proteomic profiles at baseline for CRS odds. Hemoglobin (odd ratio [OR]: 0.6, 95%CI: 0.4-0.8) was associated with lower odds for CRS while IL6 (2.0, 1.2-3.3) and stem cell factor (scf 2.2, 1.2-4.2) were associated with higher odds of CRS. We then analyzed the differences in cytokine levels between day 0 and day 3 to select cytokines with significant changes for further analysis ( Panel-B). At day 3, groa (1.9, 1.1-3.3), IL3 (1.6, 1.2-2.1), IL5 (1.5, 1.2-1.9), IL6 (1.7, 1.3-2.3), IL10 (2.0, 1.3-3.0), TNFα (2.0, 1.1-3.6), and mcp2 (2.5, 1.2-5.3) were all associated with higher odds for CRS. Based on ROC analysis at day 3, best cutoff points to estimate CRS (value, sensitivity/specificity) for IL3 (3, 80%/90%), IL5 (197, 74%/85%), IL6 (11, 70%/85%), and IL10 (53, 74%/85%) were identified. Based on that, elevated IL3 (OR:24, 95%CI: 6-105), IL5 (11, 3-40), IL6 (21, 5-95), and IL10 (12, 3-46) were associated with higher odds for CRS. For ICANS, day 3 IL3 (1.5, 1.2-1.9), IL6 (1.2, 1.1-1.5), IL8 (2.1, 1.4-3.3), and IL10 (1.7, 1.3-2.4) were associated with higher odds for ICANS. Best cutoff points to estimate ICANS at day 3 (value, sensitivity/specificity) for IL3 (5, 78%/76%), IL6 (115, 78%/78%), IL10 (130, 81%/80%), and IL8 (21, 83%/81%) were identified. Based on that, elevated IL3 (OR:10, 95%CI: 3-37), IL6 (11, 3-43), IL10 (13, 3-51), and IL8 (19, 4-81) were associated with higher odds for ICANS. CONCLUSIONS In our comprehensive plasma proteomic profiles analysis, we identified cutoffs for IL3, IL6, IL5 and IL10 that may be predictive for CRS and ICANS regardless of CAR-T cell product. Our results are clinically applicable and may be used to recognize patients at risk for CRS and/or ICANS who may be eligible for prophylactic therapies.

Ruxolitinib Promotes Clinical Responses in Large Granular Lymphocytic Leukemia Via Suppression of JAK/STAT-Dependent Inflammatory Cascades

Background: Large granular lymphocytic leukemias (LGL) are T or NK-cell lymphoproliferative disorders that are characterized by myelosuppression and frequent mutations in STAT3. Commonly used agents include low doses of methotrexate or cyclophosphamide. Among 5 patients (pts) with LGL treated on our phase II study of ruxolitinib in T-cell lymphoma (Moskowitz, et al. Blood 2021), 2 achieved partial response (PR) and 2 achieved stable disease, suggesting oncogenic dependence on JAK/STAT pathway activity in LGL. Methods: To further explore the efficacy and mechanism of JAK1/2 blockade in LGL, we expanded our phase II study to include 23 pts with relapsed/refractory LGL. This sample size was chosen to allow for narrowing of the 95% confidence interval to 54-87% (Wilson score method) if similar efficacy was observed. Pts received ruxolitinib 20mg PO BID continuously. Responses were assessed after cycles 2, 5, and every 3 cycles thereafter using the response assessment from the ECOG-5998 study for LGL. Furthermore, stable disease (SD) was defined as improvement in cytopenia(s) by 1 grade (without meeting criteria for PR) for a minimum of 6 months. Overall response rate (ORR) included complete response (CR) plus PR; clinical benefit rate (CBR) included ORR plus SD. In parallel, we performed single-cell RNA sequencing (scRNA-seq) on paired C1D1 and C1D8 peripheral blood mononuclear cells (PBMCs) from 7 patients (5 PR, 1 SD, and 1 non-responder) and plasma proteomic profiling on 5 patients (3 PR, 1 SD, and 1 POD). Results: Among 23 pts, median age was 58 (31-86), 13 (57%) were male, 19 (83%) were white, 1 (4%) was black. Median number of prior therapies was 2 (range 0-5). 12/22 (54%) had STAT3 mutations (of whom 1 also had a JAK1 mutation); 1 had a JAK2 mutation, 1 pt was missing sequencing. Baseline cytopenias included anemia (n=14, 61%), thrombocytopenia (n=12, 52%), and/or neutropenia (n=16, 70%). Among 20 pts evaluable for response (3 too early), there were 5 (25%) CRs, 6 (30%) PRs, and 4 (20%) SD. ORR and CBR were 55% and 75% respectively. Median event free survival (EFS) was not reached and was 68% (95% CI: 50-93) at 14 months ( Fig. 1A). STAT3 mutation status predicted for improved EFS (14-month EFS 100% vs 40%, p=0.007). After a median duration of treatment of 13.1 months, there were no unexpected toxicities. Severe adverse events included febrile neutropenia (n=3, 13%) and herpes zoster (n=1, 4%). To understand the mechanism by which ruxolitinib improved hematologic parameters in LGL, we performed unbiased proteomic analysis of peripheral blood plasma samples using the OLink 96 Inflammation and Immune Response Platforms. Ruxolitinib led to a decrease in several soluble mediators known to be driven by interferon-driven JAK/STAT activation, including CXCL9, CXCL10, and PD-L1, as well as TNF ( Fig. 1B). Several of these factors have been shown to suppress hematopoietic stem cell function, suggesting a JAK/STAT-dependent paracrine mechanism by which LGL leads to myelosuppression. ScRNA-seq of PBMCs identified LGL cells based on expression of cytotoxic genes, including NKG7, CST7, CCL5, GZMB and PRF1. Analysis of cell type proportions within the peripheral blood showed that patients achieving a PR to Ruxolitinib showed a decrease in the proportion of circulating myeloid cells. Gene set enrichment analysis (GSEA) of LGL cells revealed substantial downregulation of both JAK/STAT signaling and TNF signaling in LGL cells in PR but not SD patients, whereas persistently elevated TNF signaling was seen not only in LGL cells but also circulating myeloid and naïve T-cells in SD patients, suggesting that LGL cells might promote bone marrow suppression via paracrine effects on the bystander host immune system. Network analysis of LGL cells and non-malignant peripheral blood immune cells is ongoing. Conclusions: Ruxolitinib induced durable responses in pts with LGL and therefore may represent an option for pts requiring treatment. STAT3 mutation status was predictive of EFS and responses were associated with JAK/STAT pathway down-regulation, demonstrating on-target effects. Integrated immune profiling suggests that ruxolitinib may interrupt JAK/STAT-dependent paracrine inflammatory signals that promote bone marrow suppression. An ongoing phase II study of ruxolitinib in LGL will aid in clarifying optimal dosing and confirming both efficacy and mechanism of action (NCT05592015).