Serum Proteomic Variability Associated with Clinical Phenotype in

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Serum Proteomic Variability Associated with Clinical Phenotype in Familial Transthyretin Amyloidosis (ATTRm) Gloria G. Chan, Clarissa M. Koch, and Lawreen H. Connors J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.7b00479 • Publication Date (Web): 18 Sep 2017 Downloaded from http://pubs.acs.org on September 19, 2017

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Journal of Proteome Research

Serum Proteomic Variability Associated with Clinical Phenotype in Familial Transthyretin Amyloidosis (ATTRm)

Gloria G. Chan1#, Clarissa M. Koch1,2+, Lawreen H. Connors1,2* 1

Amyloidosis Center and 2Department of Pathology and Laboratory Medicine, Boston University School

of Medicine, Boston, MA 02118

Correspondence: Lawreen H. Connors, PhD Amyloidosis Center Boston University School of Medicine 72 East Concord Street, K-507 Boston, MA 02118 Tel: 617-638-4313 Fax: 617-638-4493 Email: [email protected]

Present address: #Bing Center for Waldenström's Macroglobulinemia, Dana-Farber Cancer Institute, Boston, MA 02215 +Department of Medicine, Division of Pulmonary and Critical Care, Northwestern University, Chicago, IL 60611

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ABSTRACT: Transthyretin (TTR), normally a plasma circulating protein, can become misfolded and aggregated, ultimately leading to extracellular deposition of amyloid fibrils usually targeted to heart or nerve tissues. Referred to as TTR-associated amyloidoses (ATTR), this group of diseases is frequently life threatening and fatal if untreated. ATTR, caused by amyloid-forming variant TTR proteins (ATTRm) which arise from point mutations in the TTR gene, were classically referred to as familial amyloid cardiomyopathy (FAC) or familial amyloid polyneuropathy (FAP) reflecting the clinical phenotype. FAC and FAP are pathologies that can be challenging to diagnose as there are no definitive biomarkers of disease; moreover, disease-specific measures of progression are lacking and treatment options are limited. Thus, the discovery of sensitive and specific indicators of disease has the potential to improve recognition, enable accurate measurement of amyloid progression and response to treatment, and reveal key information regarding FAC and FAP pathobiological mechanisms. In this study, the goal was to investigate serum proteomic features unique to FAC and FAP types of ATTRm. Multiple-reaction monitoring mass spectrometry (MRM-MS), a powerful technique in profiling proteomes, was used to measure the serum concentrations of 160 proteins in samples from FAC and FAP patients. Results were compared to data from healthy control sera obtained from individuals matched to age (≥ 60 years), gender (male), and race (Caucasian). Proteomic analyses of ATTRm (FAC and FAP) and control samples showed significant concentration differences in 107 of 192 (56%) of the serum proteins that were studied. In comparing FAC to FAP, differences in concentrations, and interactions and functions of several proteins were identified as unique to each disease; significantly lower levels of TTR were specific to FAC, but not to FAP. Annotated functional clustering identified extracellular region, signal and signal peptide as terms common to FAC and FAP. Conversely, disulfide bond was unique to FAC; secreted, glycosylation site:N-linked, glycosylation, glycoprotein, polymorphism, and sequence variant were associated solely with FAP. Predicted protein-protein associations in FAC were seen for reaction, binding, and activation processes; no associations were found in FAP. This study demonstrates significant proteomic differences between ATTRm patient and control sera, as well as ATTRm phenotype-associated variations in the circulating levels of several proteins including TTR. The 2 ACS Paragon Plus Environment

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identification of serum proteins unique to FAC and FAP may have diagnostic and prognostic utility, and could possibly provide important clues about disease mechanisms. KEYWORDS: familial amyloidosis, transthyretin, biomarker, cardiomyopathy, neuropathy, MRM-MS, DAVID, STRING, PANTHER, UniprotKB



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INTRODUCTION Amyloidosis is a term used to describe a diverse group of progressive and fatal protein folding disorders featuring the aggregation and tissue deposition of one of more than 40 different precursor proteins.1 Soluble amyloidogenic oligomers and aggregates are believed to have cytotoxic effects and the unabated formation of amyloid deposits causes disruption of normal cellular function and worsening organ status, usually with catastrophic consequences.2–4 One group of amyloid diseases is associated with transthyretin (TTR), normally an extremely stable and soluble protein present in plasma and cerebral spinal fluid.5,6 TTR-related amyloidosis (ATTR) can be inherited or acquired and both mutant and wild-type forms of TTR are components of the extracellularly deposited amyloid fibrils responsible for organ impairment and failure.7,8 In familial or mutant-associated TTR amyloidosis (ATTRm), a coding region missense mutation in the TTR gene leads to the expression of a variant protein which is aggregation-prone and amyloid-forming. Alternatively, wild-type TTR amyloidosis (ATTRwt) is an amyloid disease that features destabilization and fibril formation of a ‘normal’ protein, i.e. TTR in the absence of protein sequence variation. ATTRm is an autosomal dominant genetic disease for which >100 mutations have been reported; located throughout exons 2 – 4 in the TTR gene, the pathologic mutants almost exclusively result from single nucleotide base alterations.9 The phenotypes of ATTRm are varied, but common clinical features and ethnic origins have been noted among kinships afflicted with identical TTR mutations.10–13 Patients with ATTRm can display a spectrum of debilitating and life threatening symptoms dependent on the sites of amyloid infiltration; the heart and/or nerves are predominantly affected and such cases were classically referred to as familial amyloid cardiomyopathy (FAC)14,15 or familial amyloid polyneuropathy (FAP),16–18 respectively. While inheritance of a pathologic mutation is a strong risk factor, an unequivocal diagnosis of FAC or FAP can be challenging as disease penetrance is variable and onset is usually delayed until the fourth decade or beyond; furthermore, there are no definitive biomarkers of disease and demonstration of amyloid generally relies on biopsy evidence from the affected organ. The absence of disease-specific measures of progression and in particular, indicators of nerve function status, is problematic in disease 4 ACS Paragon Plus Environment

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management and a limitation in clinical studies of new treatments. Currently, therapeutic options for ATTRm are limited; organ (liver and/or heart) transplantation is the only treatment approved world-wide and major disadvantages include significant mortality, morbidity risk, early disease status requirement, and donor availability. The recent emergence of investigational therapies such as TTR stabilizers, amyloid fibril disruptors, and inhibitors of TTR expression offers hope, but also highlights the need for sensitive and specific indicators of disease to aide in the analysis of data from interventional clinical trials. Over the past decade, a number of proteomic studies utilizing biochemical and immunologic assays have yielded important discovery and validation of unique, disease-specific indicators. Investigations detailing patient serum proteomes have led to the identification and utilization of biomarkers in prostate cancer, liver disease, and muscular dystrophy.19–21 One proteomic-based approach is the use of multiple-reaction monitoring mass spectrometry (MRM-MS), a quantification method that measures targeted protein to peptide abundances within a given sample.22 MRM-MS has gained recognition as a useful multiplexing method for sensitive and selective quantification of large collections of proteins in complex solutions.23 In this technique, targeted protein sequences are combined with stable isotope-labeled internal standards (SIS) bound to specific peptides and measured using mass spectrometry to determine absolute peptide concentration while filtering out unwanted peptides. Several advantages of MRM-MS include minimal sample requirement, avoidance of epitope-driven specificity of antibodybased methods, reproducible results, and multiplexing capability. The present study was undertaken to generate accurate proteomic profiles in sera from patients with ATTRm, and to investigate the presence of phenotype-specific biomarkers unique to FAC and FAP. Using the same strategy as detailed in our previous report,24 we performed targeted proteomic analysis of 330 peptides representing 160 distinct proteins to identify differences in FAC, FAP, and healthy control sera. Proteins that were FAC or FAP disease-specific were further analyzed using bioinformatics tools to link protein characteristics and associations within amyloid disease type. In this report, we present data demonstrating the unique association of several proteins with FAC or FAP and evidence suggesting the 5 ACS Paragon Plus Environment


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possible utility of these proteins as candidate biomarkers in the separate ATTRm phenotypes. Further, the results indicating distinctive proteomes in FAC and FAP provide a rationale for further mechanistic studies to understand the pathobiological differences between TTR-associated amyloid disease featuring cardiomyopathy and neuropathy. EXPERIMENTAL PROCEDURES Study Groups Informed consent for data and sample collection was obtained from all patients under a repository protocol approved by the Boston University Medical Campus Institutional Review Board. Patient serum samples were chosen from cases with biopsy proven ATTRm amyloidosis and cardiac or neurological involvement as a major clinical feature. The diagnosis of amyloid disease was based on histological demonstration of amyloid deposits by Congo red staining of a cardiac, nerve, or other tissue biopsy using Congo red. Identification of TTR as the major fibril constituent in the congophillic deposits established amyloid disease type and was accomplished by immunohistochemistry, immunogold electron microscopy or mass spectral analysis. Pathologic mutations were identified by genomic DNA sequencing25 of amplified products from exons 1 – 4 of the TTR gene and the presence of a variant TTR was confirmed by isoelectric focusing of serum.26 Cardiac involvement was defined by an interventricular septal wall thickness > 12 mm in the absence of other causes of cardiomyopathy and serum BNP ˃ 100 pg/mL. Neurological involvement was determined by the presence of peripheral neuropathy on neurological examination or autonomic neuropathy assessed by orthostasis. Orthostasis was defined as a drop in systolic blood pressure of ≥ 20 mm Hg after a positional change from supine to standing in patients without significant dehydration. The demographic, clinical, and serological data were collected in a database maintained by the Boston University Amyloidosis Center. Human sera from healthy, control subjects were commercially purchased from Bioreclamation (Westbury, NY). Gene sequencing of all four TTR coding regions was also performed on DNA extracted from the control samples. Patient and control sera were from individuals matched for age ≥ 60 years, male gender, and Caucasian race. 6 ACS Paragon Plus Environment

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Serum Sample Preparation and Total Protein Quantification Whole blood from individual patients were clotted and spun for 10 minutes at 1500 rpm (269 x g) and 25°C to obtain serum. Sample processing was performed within 24 hours of blood collection. All patient and commercially obtained control sera were stored at -80°C until required for analysis. Three separate pooled serum samples were prepared for the proteomic studies by mixing equal amounts (50 µL) of sera from individuals with FAC (n=8) or FAP (n=8), or control (n=10) cases. Using the Pierce™ bicinchoninic acid assay (BCA) protein kit (Thermo Scientific, Waltham, MA), the total amount of protein in each pooled serum sample was measured; bovine serum albumin, in a working concentration range of 0 – 2000 µg/mL, was used to generate protein standard solutions. Multiple-Reaction Monitoring Mass Spectrometry (MRM-MS) The PeptiQuant™ Human Discovery Assay (MRM-MS, MRM Proteomics, Victoria, BC, Canada) was utilized to determine the presence and relative concentrations of 330 tryptic peptides representing 160 human serum proteins. Specifically, pooled serum samples were treated with 9 M urea/20 mM dithiothreitol for 30 minutes at 37°C to denature the proteins and reduce disulfide bonds. Alkylation of the denatured proteins was accomplished in a reaction with 40 mM iodoacetamide, performed for 30 minutes at room temperature; samples were subsequently diluted to a final urea concentration of 0.55 mM prior to protein digestion with TPCK-treated trypsin (Worthington Biochemical). The digestion reaction was performed for 18 hours at 37ºC using a 20:1 ratio of substrate:enzyme. Samples from the digestion were acidified with a solution containing 1% formic acid, combined with chilled stable isotope-labeled peptide standards, concentrated with solid phase extraction (10 mg Oasis HLB cartridges; Waters, Milford, MA), and lyophilized. The lyophilized samples were rehydrated in 0.1% formic acid to a concentration of 1 µg/uL and evaluated by LC-MRM/MS. Triplicate analyses were performed on all peptides. Statistical, Biological Function, and Interaction Network Analyses Statistical tests were written and implemented as an R script. MRM-MS quantified protein data for FAC, FAP, and control pooled serum samples were compared using Welch’s t-test for unequal variance. P7 ACS Paragon Plus Environment


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values were adjusted using the false discovery rate (FDR, Benajmini & Hochberg) test for multiple comparison testing.27,28 Statistical significance was defined as q < 0.05. Several readily available online databases were used to obtain information regarding the diseasespecific ATTRm proteins. The UniprotKB database yielded generalized protein descriptions, as well as data detailing functionality and binding domains.29 Information from UniprotKB was mainly derived from genome sequencing projects and literature reference sources. Further exploration of individual protein classification, biological context, and molecular pathway involvement was achieved by utilizing PANTHER30 version 11.0, DAVID31 version 6.7, and STRING32 version 10.0. Briefly, the gene names of unique proteins from each ATTRm group were uploaded to PANTHER and mapped to obtain classifications, assignments of biological processes, and predictions of molecular functions. Results from PANTHER were further compared using DAVID to designate formal identity and definition of types, properties, and associations linked to enriched gene/protein clusters. With information collected from multiple annotation sources including UniprotKB, Ensembl33, EntrezGene34 and RefSeq35, each database was used to identify previously reported knowledge and information about genes/proteins. Lastly, protein-protein interaction network analyses were performed with STRING, a database containing recognized and predicted molecular associations. RESULTS Serum Proteomes in FAC and FAP ATTRm sera were obtained from patients at initial (baseline) amyloid clinic evaluation; control sera were available commercially. Serum samples for this study were selected from patients and healthy donors based on age, gender, and race. All individuals were ≥ 60 years, male, and Caucasian (Table 1). Mean ages for the FAC and FAP groups were 68.2 and 66.7 years, respectively; while individual ages for the controls were not available, all donors were reported to be 60 years of age or older. In ATTRm featuring a cardiac phenotype (FAC), the amyloidogenic TTR mutants included T60A, A19D, T59K, I68L, A81V, and E89Q. The ATTRm group with mainly neurologic clinical characteristics (FAP) was comprised of individuals with TTR-L58H, -V30M, and -K70N. No pathological mutations were detected in the control 8 ACS Paragon Plus Environment

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group. BMI in the patient groups was similar and total protein amounts were comparable in patient and control sera. However, serum TTR levels were lower in both FAC and FAP compared to controls as previously reported.36–38 In the FAC group with cardiac involvement as the major clinical feature, an elevated BNP of 308 pg/mL and increased IVST of 16 mm were consistent with the phenotype. By comparison, BNP and IVST values were normal in FAP. Proteomic data from MRM-MS analyses revealed significant concentration differences (q < 0.05) between ATTRm (FAC and FAP) and control sera in the majority of proteins that were measured. As illustrated by the Venn diagram (Figure 1), there were protein level variations exclusive to each ATTRm group when compared to control; 18 were unique to FAC and 12 distinct to FAP. Serum measurements of 77 proteins common to both FAC and FAP were significantly different (q < 0.05) from control. Of note, this ATTRm shared set included serum amyloid P-component, serum amyloid A-4 protein and apolipoprotein C-II, proteins strongly related to amyloid disease.39–41 In the protein set unique to FAC, 12/18 (66.67%) proteins showed significantly lower serum levels with fold changes ranging from 0.55 – 0.84 of control (Table 2). Interestingly, the cardiac diseasespecific group of proteins with lower concentrations included TTR which was decreased by 0.67-fold (q = 0.003) compared to control. Carbonic anhydrase 1 (CA1) was the lowest of the disease-specific protein set with a 0.55-fold change from control. Conversely, six proteins in the FAC set had higher levels than control with increasing fold changes ranging from 1.12 for fibronectin (FN1) to 1.68 for von Willebrand factor (VWF); others in the group included mannose-binding protein C (MBL2), complement component C9 (C9), leucine-rich alpha-2-glycoprotein (LRG1), and sex hormone-binding globulin (SHBG). Furthermore, levels of 11/18 proteins were significantly different (q < 0.05) between FAC and FAP, including TTR which was 0.75-fold lower in FAC (q = 0.02); these results were consistent with the clinical laboratory measurements (Table 1) showing that TTR in FAC serum was the lowest of all study groups. Sera from patients with FAP demonstrated concentrations lower than control in 11/12 (91.67%) of the neurologic phenotype-specific proteins; fold changes ranged from 0.71 – 0.92 of control (Table 3). 9 ACS Paragon Plus Environment


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Complement C2 (C2) was the most reduced at about 70% of control level (fold change, 0.71; q = 0.046); levels of galectin-3-binding protein (LGALS3BP) and inter-alpha-trypsin inhibitor heavy chain H2 (ITIH2) were also < 80% of control with 0.75- (q = 0.007) and 0.79-fold changes (q = 0.043), respectively. Of the 12 FAP-unique proteins, only IgGFc-binding protein (FCGBP) showed elevated serum levels, measuring 135% of control (q = 0.001). A comparative analysis of FAP vs. FAC by Welch's t-test showed significant differences in the concentrations of all 12 proteins between the patient groups, with fold changes ranges from 0.75 – 1.32. In the majority (10/12) of proteins, the fold changes between FAP and FAC, while significant (q-values ranging from 0.002 – 0.033), were either less varied than (higher fold change value) or near equal to (< 0.05-fold change) results in FAP vs. control; larger decreases in the concentrations of complement component C6 (C6) and lipopolysaccharide-binding protein (LBP) were noted in FAP vs. FAC compared to FAP vs. control. ATTRm Phenotype Variation in Functional Annotations and Predicted Associations The serum proteins identified as specific to FAC and FAP were further analyzed using PANTHER and DAVID to define molecular functions and biological processes, and determine potential relationships within the protein sets. A search using the GO Molecular Function of PANTHER yielded 3 categorical results common to both FAC and FAP; the classifications were binding (GO:0005488), catalytic activity (GO:0003824), and receptor activity (GO:0004872) (Figure 2). A fourth category, transporter activity (GO:0005215), was uniquely represented in 7.1% of the FAC disease-specific protein group. In FAC, the greatest number of observations were assigned to catalytic activity (42.9%) and binding (35.7%); receptor activity was attributed to a smaller portion (14.3%) of the group. By comparison, the differentially measured proteins unique to FAP were equally distributed among binding, catalytic activity, and receptor activity classification groups. Proteins in both FAC and FAP groups showed 8 common categories for GO Biological Function including biological adhesion (GO:0022610; 6.3% vs. 18.5%), biological regulation (GO: 0065007; 9.4% vs. 3.7%), cellular process (GO: 0009987; 21.9% vs. 25.9%), immune system process (GO: 0002376; 12.5% vs. 14.8%), localization (GO: 0051179; 12.5% vs. 3.7%), metabolic process (GO: 0008152; 18.8% vs. 7.4%), multicellular organismal process (GO: 0032501; 10 ACS Paragon Plus Environment

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9.4% vs. 7.4%), and response to stimulus (GO: 0050896; 9.4% vs. 14.8%); categorical values in the patient sets were variable. Reproduction (GO:0000003) was a biological process only represented in the FAP protein set. Analysis of the 18 differentially measured proteins in FAC by DAVID showed a clustered predicted gene count of > 76.47% (Figure 3A). CA1, hemoglobin subunit alpha (HBA2), and Ig mu heavy chain disease protein were not found to be clustered or enriched; the lack of published reports or available data on these genes excluded them from the cluster as seen in the DAVID results. The most enriched functional annotation terms included extracellular region, disulfide bond, signal, and signal peptide. In the FAP group, a higher (> 91.67%) clustered predicted gene count for the 12 proteins was obtained (Figure 3B) and nine annotated terms were most enriched in the group. Categories unique to FAP were secreted, glycosylation site:N-linked, glycosylation, glycoprotein, polymorphism, and sequence variant; DAVID enriched terms common to FAP and FAC included extracellular region, signal, and signal peptide. FAC and FAP disease-specific proteins were further analyzed using STRING to explore functional interactions and predict relationships among each protein set. Among 17/18 proteins identified as unique to FAC, interactions defined as reaction (black line) associations were predicted between several pairs including coagulation factor XIII A chain (F13A1) and von Willebrand Factor (VWF), VWF and fibronectin (FN1), FN1 and F13A1, and lastly, cystatin-C (CST3) and TTR (Figure 4A). Other links classified as binding (blue line) associations were noted between F13A1 and FN1, FN1 and VWF, FN1 and CD44 antigen (CD44), as well as compliment C4-A (C4A) and CST3. Moreover, activation (green line) interactions were predicted between FN1 and CD44 (Figure 4A). Conversely, no associations were predicted to be present among any of the 12 proteins in FAP with levels significantly different from control (Figure 4B). DISCUSSION Using a proteomic approach, this study examined the concentrations of 160 proteins in sera from patients with ATTRm featuring cardiomyopathy (FAC) or polyneuropathy (FAP), and compared the patient 11 ACS Paragon Plus Environment


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results to data obtained on serum from age-, gender- and race-matched healthy control donors. Key and novel findings of this investigation include: 1) discovery of proteomic profile variations in ATTRm patient and control sera; 2) identification of significantly different serum protein levels unique to ATTRm-FAC and ATTRm-FAP; 3) classification and assessment of functional and annotation term descriptions for disease-specific clusters of proteins; and 4) prediction of protein behavior, interactions, and relationships in each ATTRm protein group. Previously published reports have demonstrated the scientific importance and clinical utility of proteomic analysis in studies aimed at the identification of disease biomarkers.42,43 A proteomic-based investigative approach provides an alternative to conventional studies not designed for discovery, but instead focused on the restrictive and potentially biased examination of a set of proteins based on prior knowledge. Studying the proteomic profiles of clinical samples offers the opportunity to globally characterize a multitude of proteins simultaneously and produce data in extremely high yield. The generation of an expanded dataset engenders novel perspectives on disease-related differences in protein abundance and behavior, and provides information which can be used to identify pathologically-related protein functions and networks with the support of statistical and bioinformatics tools. The present study was aimed at profiling the serum proteomes in ATTRm and healthy controls. Our results provide evidence that the circulating levels of > 100 serum proteins are significantly different in patient and control samples. Concentrations were mainly (93/107, 86.9%) decreased in the patient sera compared to control and marked variations in the ATTRm levels of several amyloid-related proteins (serum amyloid P-component, serum amyloid A-4 protein and apolipoprotein C-II) were observed. Moreover, in a comparative study of ATTRm featuring differing clinical phenotypes, i.e. cardiomyopathy (FAC) vs. neuropathy (FAP), significant dissimilarities in the proteomes of the two patient groups were demonstrated. The levels of several proteins were found to be disease-specific, 18 in FAC and 12 in FAP; in the unique sets, the majority of proteins have been linked to amyloid pathologies, including Alzheimer’s disease (AD).44–50 It is interesting to note that TTR, the amyloid fibril precursor protein in ATTRm, was included only in the FAC-specific set; serum TTR concentrations were significantly lower 12 ACS Paragon Plus Environment

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in FAC compared to FAP (q = 0.02) and controls (q = 0.003). While lower levels of serum TTR are known to be a feature of ATTRm36–38, this is the first report, to our knowledge, describing phenotyperelated concentration differences. In examining the serum proteins specific to FAC and FAP, we used PANTHER and DAVID to define molecular functions and biological processes, and determine potential relationships within the protein sets. From PANTHER, molecular functions and biological processes attributed to both FAC and FAP were similar; however, transporter activity was unique to FAC and reproduction to FAP suggesting disease-specific variations. DAVID enriched terms common to both ATTRm phenotypes included signal and signal peptide; these annotations were not unexpected and feature the commonly shared characteristics of serum proteins which are exported and circulated through the secretory pathway. In addition, the term, extracellular region, was shared by both groups and possibly reflects the disease process characterized by misfolding and aggregation of circulating TTR, the extracellular accumulation of TTR fibrils and associated proteins, and remodeling of the extracellular matrix. Conversely, the disease phenotype comparison highlighted several interesting differences in functional and biological terms associated with the unique protein sets in each group. Glycosylation, glycosylation site: N-linked (GlcNAc...), and glycoprotein were terms solely ascribed to FAP; these data suggest a possible role for glycosylated proteins and/or glycosylation in the pathobiology of ATTRm featuring neurological involvement. This is consistent with recent reports indicating a link between N-glycosylated TTR and FAP51,52 and a previous study demonstrating glycosylation defects in the intracellular sorting, processing and export of amyloid precursor proteins, tau, and other proteins in AD.53 Protein-protein relationships within the protein sets unique to the two ATTRm patient groups were examined using STRING. In FAC, two separate associations involving 7/18 of the disease-specific proteins were predicted; these included interactions among 1) a multimetric glycoprotein involved with the blood coagulation system (VWF, q = 0.01), a zymogen activated in the final step of the blood coagulation cascade (F13A1, q = 0.03), a protein with a role in adhesive and migratory processes of cells (FN1, q = 0.05), and a cell membrane glycoprotein involved in matrix adhesion, lymphocyte activation, 13 ACS Paragon Plus Environment


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and lymph node homing (CD44, q = 0.002); and 2) a protein that facilitates interaction between antigenantibody complexes and other complement components (C4A, q = 0.03), a potent inhibitor of lysosomal proteinases (CST3, q = 0.03), and a plasma transport protein for thyroxine and retinol (TTR, q = 0.003). These associations may provide clues leading to a more precise understanding of disease onset and progression in FAC, most especially with respect to the amyloid-causing protein, TTR. Interestingly, no interactions were predicted when STRING analysis was performed on the protein set unique to FAP. This may be related to the small size of the protein group which lacks the statistical power needed to achieve significance. Limitations of this study were the use of pooled sera and the comparative analysis of groups with small sample sizes. In such a study, it is challenging to assess whether distribution of the statistical data is normal or skewed; furthermore, statistical power is restricted, as the small samplings decrease the probability that the data being analyzed accurately represent the study groups. However, in our analyses, we utilized the Welch's t-test and performed multiple corrections with FDR to address this drawback. By adjusting the p-values with FDR and indicated as q-values, our statistical study revealed significant concentration differences between ATTRm patient and control in analyses of 107/160 (66.9%) serum proteins. In summary, data from the present study provide evidence that the serum proteomes of patients with ATTRm and healthy age, gender- and race-matched controls are dissimilar. Our discovery of unique and significant variations in the levels of multiple serum proteins related to ATTRm disease phenotype offers important information, potentially useful as diagnostic indicators and measures of progression in FAC and FAP. Moreover, these findings suggest differing pathobiologies in FAC and FAP, and provide data for future mechanistic studies aimed at uncovering new therapeutic targets. ACKNOWLEDGMENTS This work was supported by the E. Rhodes and Leona B. Carpenter Foundation, National Institutes of Health grant RO1AG031804, and the Young Family Amyloid Research Fund. All authors of this manuscript declare no competing financial interest. 14 ACS Paragon Plus Environment

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REFERENCES 1.

Sipe, J. D. et al. Nomenclature 2014: Amyloid fibril proteins and clinical classification of the amyloidosis. Amyloid 21, 221–4 (2014).

2.

Reixach, N., Deechongkit, S., Jiang, X., Kelly, J. W. & Buxbaum, J. N. Tissue damage in the amyloidoses: Transthyretin monomers and nonnative oligomers are the major cytotoxic species in tissue culture. Proc. Natl. Acad. Sci. U. S. A. 101, 2817–22 (2004).

3.

Merlini, G. & Westermark, P. The systemic amyloidoses: clearer understanding of the molecular mechanisms offers hope for more effective therapies. J. Intern. Med. 255, 159–78 (2004).

4.

Wechalekar, A. D., Gillmore, J. D. & Hawkins, P. N. Systemic amyloidosis. Lancet (London, England) 387, 2641–54 (2016).

5.

Goodman, D. S. Plasma retinol-binding protein. Ann. N. Y. Acad. Sci. 348, 378–90 (1980).

6.

Cornwell, G. G., Sletten, K., Olofsson, B. O., Johansson, B. & Westermark, P. Prealbumin: its association with amyloid. J. Clin. Pathol. 40, 226–31 (1987).

7.

Benson, M. D., Breall, J., Cummings, O. W. & Liepnieks, J. J. Biochemical characterisation of amyloid by endomyocardial biopsy. Amyloid 16, 9–14 (2009).

8.

Gertz, M. A. et al. Diagnosis, Prognosis, and Therapy of Transthyretin Amyloidosis. J. Am. Coll. Cardiol. 66, 2451–66 (2015).

9.

Rowczenio, D. M. et al. Online registry for mutations in hereditary amyloidosis including nomenclature recommendations. Hum. Mutat. 35, E2403-12 (2014).

10.

Lobato, L. Portuguese-type amyloidosis (transthyretin amyloidosis, ATTR V30M). J. Nephrol. 16, 438–42

11.

Oide, T., Arima, K., Yamazaki, M., Hanyu, N. & Ikeda, S.-I. Coexistence of familial transthyretin amyloidosis ATTR Val30Met and spinocerebellar ataxia type 1 in a Japanese family--a follow-up autopsy report. Amyloid 11, 191–9 (2004).

12.

Hellman, U. et al. Heterogeneity of penetrance in familial amyloid polyneuropathy, ATTR Val30Met, in the Swedish population. Amyloid 15, 181–186 (2008). 15 ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

13.

Adams, D. et al. First European consensus for diagnosis, management, and treatment of transthyretin familial amyloid polyneuropathy. Curr. Opin. Neurol. 29, S14–S26 (2016).

14.

Westermark, P., Johnson, K. H. & Pitkänen, P. Systemic amyloidosis: a review with emphasis on pathogenesis. Appl. Pathol. 3, 55–68 (1985).

15.

Ruberg, F. L. & Berk, J. L. Transthyretin (TTR) Cardiac Amyloidosis. Circulation 126, 1286– 1300 (2012).

16.

ANDRADE, C. A peculiar form of peripheral neuropathy; familiar atypical generalized amyloidosis with special involvement of the peripheral nerves. Brain 75, 408–27 (1952).

17.

Benson, M. D. & Kincaid, J. C. The molecular biology and clinical features of amyloid neuropathy. Muscle Nerve 36, 411–23 (2007).

18.

Shin, S. C. & Robinson-Papp, J. Amyloid Neuropathies. Mt. Sinai J. Med. A J. Transl. Pers. Med. 79, 733–748 (2012).

19.

Rosenzweig, C. N. et al. Predicting Prostate Cancer Biochemical Recurrence Using a Panel of Serum Proteomic Biomarkers. J. Urol. 181, 1407–1414 (2009).

20.

Bell, L. N. et al. Serum proteomics and biomarker discovery across the spectrum of nonalcoholic fatty liver disease. Hepatology 51, 111–20 (2010).

21.

Hathout, Y. et al. Large-scale serum protein biomarker discovery in Duchenne muscular dystrophy. Proc. Natl. Acad. Sci. 112, 7153–7158 (2015).

22.

Lange, V., Picotti, P., Domon, B. & Aebersold, R. Selected reaction monitoring for quantitative proteomics: a tutorial. Mol. Syst. Biol. 4, (2008).

23.

Hoofnagle, A. N. et al. Multiple-reaction monitoring-mass spectrometric assays can accurately measure the relative protein abundance in complex mixtures. Clin. Chem. 58, 777–81 (2012).

24.

Chan, G. G., Koch, C. M. & Connors, L. H. Blood Proteomic Profiling in Inherited (ATTRm) and Acquired (ATTRwt) Forms of Transthyretin-Associated Cardiac Amyloidosis. J. Proteome Res. 16, 1659–1668 (2017).

25.

Lim, A. et al. Characterization of transthyretin variants in familial transthyretin amyloidosis by 16 ACS Paragon Plus Environment

Page 16 of 31

Page 17 of 31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


mass spectrometric peptide mapping and DNA sequence analysis. Anal. Chem. 74, 741–51 (2002). 26.

Connors, L. H. et al. A simple screening test for variant transthyretins associated with familial transthyretin amyloidosis using isoelectric focusing. Biochim. Biophys. Acta 1407, 185–92 (1998).

27.

Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995).

28.

Yekutieli, D. & Benjamini, Y. Resampling-based false discovery rate controlling multiple test procedures for correlated test statistics. J. Stat. Plan. Inference 82, 171–196 (1999).

29.

Magrane, M. & Consortium, U. P. UniProt Knowledgebase: A hub of integrated protein data. Database 2011, 1–13 (2011).

30.

Mi, H., Muruganujan, A. & Thomas, P. D. PANTHER in 2013: modeling the evolution of gene function, and other gene attributes, in the context of phylogenetic trees. Nucleic Acids Res. 41, D377–D386 (2013).

31.

Huang, D. W. et al. DAVID Bioinformatics Resources: Expanded annotation database and novel algorithms to better extract biology from large gene lists. Nucleic Acids Res. 35, 169–175 (2007).

32.

Franceschini, A. et al. STRING v9.1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res. 41, D808-15 (2013).

33.

Birney, E. An Overview of Ensembl. Genome Res. 14, 925–928 (2004).

34.

Maglott, D., Ostell, J., Pruitt, K. D. & Tatusova, T. Entrez Gene: gene-centered information at NCBI. Nucleic Acids Res. 39, D52–D57 (2011).

35.

Pruitt, K. D., Tatusova, T. & Maglott, D. R. NCBI Reference Sequence (RefSeq): a curated nonredundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 33, D501-4 (2005).

36.

Connors, L. H., Gertz, M. A., Skinner, M. & Cohen, A. S. Nephelometric measurement of human serum prealbumin and correlation with acute-phase proteins CRP and SAA: results in familial amyloid polyneuropathy. J. Lab. Clin. Med. 104, 538–45 (1984).

37.

Skinner, M. et al. Lowered prealbumin levels in patients with familial amyloid polyneuropathy 17 ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(FAP) and their non-affected but at risk relatives. Am. J. Med. Sci. 289, 17–21 (1985). 38.

Buxbaum, J., Anan, I. & Suhr, O. Serum transthyretin levels in Swedish TTR V30M carriers. Amyloid 17, 83–5 (2010).

39.

Hawkins, P. N. Serum amyloid P component scintigraphy for diagnosis and monitoring amyloidosis. Curr. Opin. Nephrol. Hypertens. 11, 649–55 (2002).

40.

Murphy, C. L. et al. AA amyloidosis associated with a mutated serum amyloid A4 protein. Amyloid 16, 84–8 (2009).

41.

Nasr, S. H. et al. Novel Type of Renal Amyloidosis Derived from Apolipoprotein-CII. J. Am. Soc. Nephrol. 28, 439–445 (2017).

42.

Hu, S., Loo, J. A. & Wong, D. T. Human saliva proteome analysis and disease biomarker discovery. Expert Rev. Proteomics 4, 531–8 (2007).

43.

Schiess, R., Wollscheid, B. & Aebersold, R. Targeted proteomic strategy for clinical biomarker discovery. Mol. Oncol. 3, 33–44 (2009).

44.

Kolev, M., Ruseva, M., Harris, C., Morgan, B. & Donev, R. Implication of Complement System and its Regulators in Alzheimers Disease. Curr. Neuropharmacol. 7, 1–8 (2009).

45.

Uberti, D. et al. Increased CD44 gene expression in lymphocytes derived from alzheimer disease patients. Neurodegener. Dis. 7, 143–147 (2010).

46.

Hagnelius, N.-O., Boman, K. & Nilsson, T. K. Fibrinolysis and von Willebrand factor in Alzheimer’s disease and vascular dementia – a case-referent study. Thromb. Res. 126, 35–38 (2010).

47.

Muller, M., Schupf, N., Manly, J. J., Mayeux, R. & Luchsinger, J. A. Sex hormone binding globulin and incident Alzheimer’s disease in elderly men and women. Neurobiol. Aging 31, 1758– 65 (2010).

48.

Padurariu, M., Ciobica, A., Mavroudis, I., Fotiou, D. & Baloyannis, S. Hippocampal neuronal loss in the CA1 and CA3 areas of Alzheimer’s disease patients. Psychiatr. Danub. 24, 152–8 (2012).

49.

Noguchi, M. et al. Roles of serum fibrinogen α chain-derived peptides in Alzheimer’s disease. Int. 18 ACS Paragon Plus Environment

Page 18 of 31

Page 19 of 31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


J. Geriatr. Psychiatry 29, 808–18 (2014). 50.

Hu, Y.-S., Xin, J., Hu, Y., Zhang, L. & Wang, J. Analyzing the genes related to Alzheimer?s disease via a network and pathway-based approach. Alzheimers. Res. Ther. 9, 29 (2017).

51.

Teixeira, A. C. & Saraiva, M. J. Presence of N-glycosylated transthyretin in plasma of V30M carriers in familial amyloidotic polyneuropathy: an escape from ERAD. J. Cell. Mol. Med. 17, 429–435 (2013).

52.

Batista, A. R., Sena-Esteves, M. & Saraiva, M. J. Hepatic production of transthyretin L12P leads to intracellular lysosomal aggregates in a new somatic transgenic mouse model. Biochim. Biophys. Acta 1832, 1183–93 (2013).

53.

Schedin-Weiss, S., Winblad, B. & Tjernberg, L. O. The role of protein glycosylation in Alzheimer disease. FEBS J. 281, 46–62 (2014).



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Table 1. Demographic, Clinical, and Serological Characteristics of Study Groups Study Group

ATTRm-FAC

ATTRm-FAP

Controls

8

8

10

cardiac

neurological

---

TTR Mutant (Case No.)

T60A (3) A19D (1)* T59K (1) I68L (1) A81V (1) E89Q (1)

L58H (5) V30M (2) K70N (1)

---

Age, y (Mean ± SD)

68.2 ± 7.3

66.7 ± 2.9

≥ 60

Male Sex

8/8

8/8

10/10

White Race

8/8

8/8

10/10

BMI (Mean ± SD)

29.97 ± 2.56

28.53 ± 4.93

---

Total Protein, g/dL (Mean ± SD)

8.5 ± 1.12

8.4 ± 0.86

8.3 ± 0.73

TTR, ug/mL (Mean ± SD)

184 ± 48

204 ± 32

239 ± 35

BNP, pg/mL (Mean ± SD)

308 ± 117

52 ± 27

< 72#

IVST, mm (Mean ± SD)

16 ± 2

11 ± 2

< 11#

N ATTRm Phenotype

ATTRm, mutant transthyretin (TTR)-associated amyloidosis; FAC, familial amyloid cardiomyopathy; FAP, familial amyloid polyneuropathy; BMI, body mass index; BNP, B-type natriuretic peptide; and IVST, echocardiographic measure for inter-ventricular septal thickness. *also heterozygous for non-pathologic TTR-G6S


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Table 2. Proteins differentially expressed in ATTRm-FAC (n = 18) FAC vs. Control

FAC vs. FAP

PANTHER GO

PANTHER GO

Gene Name CA1

Fold Change 0.55

q-value 0.05

Fold Change 0.75

q-value 0.07

Molecular Function Catalytic Activity

Biological Function ---

F13A1

0.57

0.03

0.71

0.01

Catalytic Activity

---

HBA2

0.63

0.002

0.60

0.0002

---

Localization

Transthyretin

TTR

0.67

0.003

0.75

0.02

---

Localization

Proteoglycan 4

PRG4

0.68

0.02

0.93

0.62

Binding, Catalytic Activity

Biological Regulation, Cellular Process

-

0.71

0.0000005

0.69

0.0002

---

---

Protein Name Carbonic anhydrase 1 Coagulation factor XIII A chain Hemoglobin subunit alpha

Ig mu heavy chain disease protein

CD5 antigen-like

CD5L

0.76

0.01

0.68

0.01

Catalytic Activity, Receptor Activity

Biological Adhesion, Biological Regulation, Cellular Process, Immune System Response. Localization

Cystatin-C

CST3

0.78

0.03

0.83

0.08


---

Complement C4-A

C4A

0.79

0.03

0.91

0.19

Binding

Cellular Process, Immune System Response

L-selectin

SELL

0.80

0.03

0.87

0.20

---

---

CD44 antigen

CD44

0.81

0.002

0.83

0.01

---

---

Angiogenin

ANG

0.84

0.02

0.94

0.54

---

---



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Fibronectin

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FN1

1.12

0.05

1.13

0.02

Binding

Mannose-binding protein C

MBL2

1.15

0.01

1.21

0.005


Complement component C9

C9

1.16

0.02

1.20

0.07

---

--Biological Regulation, Immune System Response Biological Adhesion, Cellular Process, Immune System Response

Leucine-rich alpha-2glycoprotein Sex hormone-binding globulin

LRG1

1.20

0.002

1.15

0.002

Receptor Activity

---

SHBG

1.41

0.03

1.23

0.05

---

---

Von Willebrand Factor

VWF

1.68

0.01

1.38

0.02

---

Cellular Process


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Table 3. Proteins differentially expressed in ATTRm-FAP (n = 12)

Gene Name

Fold Change

q-value

Fold Change

q-value

PANTHER GO Molecular Function

C2

0.71

0.046

0.83

0.024

---

LGALS3BP

0.75

0.007

0.78

0.005

---

---

Inter-alpha-trypsin inhibitor heavy chain H2

ITIH2

0.79

0.043

0.90

0.002


---

Fibrinogen alpha chain

FGA

0.80

0.012

0.78

0.002

Binding

Complement factor H

CFH

0.82

0.006

0.88

0.009

---

Alpha-1B-glycoprotein

A1BG

0.82

0.006

0.84

0.004

Receptor Activity

Carboxypeptidase N subunit 2

CPN2

0.83

0.0005

0.97

0.002

Receptor Activity

Vitamin K-dependent protein S

PROS1

0.85

0.046

0.91

0.028

---

FAP vs. Control Protein Name Complement C2 Galectin-3-binding protein

Complement component C6 Lipopolysaccharidebinding protein

FAP vs. FAC

C6

0.85

0.013

0.76

0.033

---

LBP

0.85

0.042

0.75

0.017

---


PANTHER GO Biological Function Biological Adhesion, Cellular Process, Immune System Process, Response to Stimulus

Biological Adhesion, Cellular Process Multicellular Organismal Process Biological Adhesion, Cellular Process, Immune System Process Cellular Process, Response to Stimulus Cellular Process, Multicellular Organismal Process --Biological Adhesion, Cellular Process, Immune System Process, Response to Stimulus Immune System Process, Localization, Response to


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Stimulus Alpha-1-antichymotrypsin IgGFc-binding protein

SERPINA3

0.92

0.040

0.88

0.012

Catalytic Activity

Biological Regulation

FCGBP

1.35

0.001

1.32

0.015

---

Biological Adhesion, Cellular Process, Reproduction


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Figure Legends Figure 1. Venn diagram showing the distribution of proteins in ATTRm significantly different (p < 0.05) from control. Disease-specific proteins totaled 18 in FAC (blue) and 12 in FAP (salmon); overlap of the circles represents the 77 serum proteins that were differentially expressed in both ATTRm groups compared to control. Figure 2. PANTHER-derived distributions of GO molecular functions and biological processes associated with the proteins differentially expressed in ATTRm-FAC and ATTRm-FAP are shown. Percentage of proteins in each category for each disease is also reported. Figure 3. Cluster terms identified with DAVID are presented for (A) ATTRm-FAC and (B) ATTRmFAP. Previously reported terms are indicated in green; previously unreported terms are shown as novel associated designations are shown in black. Figure 4. Recognized and predicted protein-protein associations are shown with STRING connections among the 18 proteins unique to ATTRm-FAC (A). A similar analysis of the 12 proteins specific to ATTRm-FAP showed no associations (B). Networks are presented in evidence view, where line color represents the type of interaction between functional associations. Associations feature nodes with connection lines such as activation (green), binding (blue), catalysis (purple), and reaction (black).



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Figure 1.


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Figure 2.

GO Molecular Function

GO Biological Process Response to Stimulus (9.4%)

Transporter Activity (7.1%)

Biological Adhesion (6.3%)

Multicellular Process (9.4%) Receptor Activity (14.3%)

Biological Regulation (9.4%)

Binding (35.7%) Cellular Process (21.9%)

Metabolic Process (18.8%) Catalytic Activity (42.9%)

Immune Localization System (12.5%) Process (12.5%)

ATTRm-FAC

Reproduction (3.7%) Receptor Activity (33.3%)

Binding (33.3%)

Catalytic Activity (33.3%)

Multicellular Organismal Process (7.4%) Metabolic Process (7.4%) Localization (3.7%)

ATTRm-FAP 27 ACS Paragon Plus Environment

Response to Stimulus (14.8%)


Cellular Process (25.9%) Immune System Process (14.8%)



Figure 3. A.

Signal peptide

Signal

Disulfide bond

Carbonic anyhydrase 1 (CA1) Coagulation factor XIII A chain (F13A1) Hemoglobin subunit alpha (HBA2) Transthyretin (TTR) Proteoglycan 4 (PRG4) Ig mu heavy chain disease protein CD5 antigen-like (CD5L) Cystatin-C (CST3) Complement C4-A (C4A) L-selectin (SELL) CD44 antigen (CD44) Angiogenin (ANG) Fibronectin (FN1) Mannose-binding protein C (MBL2) Complement component 9 (C9) Leucine-rich alpha-2-glycoprotein (LRG1) Sex hormone-binding globulin (SHBG) von Willebrand Factor (VWF) GO:0005576~extracellular region

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B.

Sequence variant

Polymorphism

Glycoprotein

Glycosylation

Glycosylation site:N-linked (GlcNAc...)

Signal peptide

Signal

GO:0005576~extracellular region

Complement C2 (C2) Galectin-3-binding protein (LGALS3BP) Inter-alpha -trypsin inhibitor heavy chain H2 (ITIH2) Fibrinogen alpha chain (FGA) Complement factor H (CFH) Alpha-1-antichymotrypsin (SERPINA3) Carboxypeptidase N subunit 2 (CPN2) Vitamin K-dependent protein S (PROS1) Complement component C6 (C6) Lipopolysaccharide-binding protein (LBP) Alpha-1-antichymotrypsin (SERPINA3) IgGFc-binding protein (FCGBP) Secreted

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60




1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figure 4. A.

B.


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For TOC only:

GO Molecular Function

GO Biological Process Response to Stimulus (9.4%)

Transporter Activity (7.1%)


Multicellular Process (9.4%) Receptor Activity (14.3%)


Binding (35.7%) Cellular Process (21.9%)

Metabolic Process (18.8%) Catalytic Activity (42.9%)

Immune Localization System (12.5%) Process (12.5%)

ATTRm-FAC

Reproduction (3.7%) Receptor Activity (33.3%)

Binding (33.3%)

Catalytic Activity (33.3%)

Multicellular Organismal Process (7.4%)

Response to Stimulus (14.8%)

Metabolic Process (7.4%) Localization (3.7%)

ATTRm-FAP 31 ACS Paragon Plus Environment


Cellular Process (25.9%) Immune System Process (14.8%)


Serum Proteomic Variability Associated with Clinical Phenotype in

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