Forms of Transthyretin-Associated Cardiac ... - ACS Publications

Subscriber access provided by UNIVERSITY OF SOUTH CAROLINA LIBRARIES

Article

Blood proteomic profiling in inherited (ATTRm) and acquired (ATTRwt) forms of transthyretin-associated cardiac amyloidosis Gloria G. Chan, Clarissa M. Koch, and Lawreen H. Connors J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.6b00998 • Publication Date (Web): 14 Feb 2017 Downloaded from http://pubs.acs.org on February 16, 2017

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Journal of Proteome Research is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 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

Journal of Proteome Research

Blood proteomic profiling in inherited (ATTRm) and acquired (ATTRwt) forms of transthyretinassociated cardiac amyloidosis

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

Running title: Proteomic profiling in ATTR cardiac amyloidosis

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

1 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

Abstract Transthyretin-associated forms of cardiac amyloidosis are fatal protein misfolding diseases that can be inherited (ATTRm) or acquired (ATTRwt). An accurate diagnosis of ATTR amyloidosis can be challenging as biopsy evidence, usually from the affected organ, is required. Precise biomarkers for ATTR disease identification and monitoring are undiscovered, disease-specific therapeutic options are needed, and the current understanding of ATTR molecular pathogenesis is limited. The aim of this study was to investigate and compare the serum proteomes in ATTRm and ATTRwt cardiac amyloidosis to identify differentially expressed blood proteins that were disease-specific. Using multiple-reaction monitoring mass spectrometry (MRM-MS), the concentrations of 160 proteins were analyzed in serum samples from ATTRm and ATTRwt patients, and a healthy control group. Patient and control sera were matched to age (≥ 60 years), gender (male), and race (Caucasian). The circulating concentrations of 123/160 proteins were significantly different in patient vs. control sera; TTR and retinol-binding protein (RBP4) levels were significantly decreased (p < 0.03) in ATTRm compared to controls. In ATTRm, 14/123 proteins were identified as unique to that group and found generally to be lower than controls; moreover, the concentrations of RBP4 and 6 other proteins in this group were significantly different (p < 0.04) compared to ATTRwt. Predicted interactions among the 14 proteins unique to ATTRm were categorized as reaction and binding associations. Alternatively, twenty-seven proteins were found to be unique to ATTRwt with associated interactions defined as activation, catalysis, and inhibition, in addition to reaction and binding. This study demonstrates significant proteomic differences between ATTR patient and control sera, and disease-associated variations in circulating levels of several proteins including TTR and RBP4. The identification of serum proteins unique to ATTRm and ATTRwt cardiac amyloidosis may have diagnostic and prognostic utility, and may provide important clues about disease mechanisms. Keywords: Amyloidosis, cardiomyopathy, biomarker, serum, familial ATTR, wild-type ATTR, MRMMS, DAVID, STRING, PANTHER, UniprotKB 2 ACS Paragon Plus Environment

Page 2 of 31

Page 3 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


Introduction The systemic amyloidoses are a collection of fatal diseases characterized by the extracellular deposition of misfolded and aggregated proteins in tissues and organs throughout the body. One group of these diseases is associated with the normally circulating plasma protein, transthyretin (TTR). Collectively referred to as ATTR amyloidoses, these pathologies feature continuous progression from disease onset and lead to life-threatening symptoms as a consequence of organ-accumulating TTR amyloid fibril deposits. Both mutant and wild-type TTR proteins can be amyloidogenic and as such, are responsible for organ dysfunction and tissue damage featured in ATTRm and ATTRwt amyloidosis, respectively. ATTRm, an inherited amyloidosis, arises from point mutations in the TTR gene and is frequently characterized by manifestations of cardiac amyloid deposits; previously, ATTRm featuring cardiac involvement was referred to as familial amyloid cardiomyopathy, FAC.1 Alternatively, ATTRwt is a non-hereditary or acquired cardiac amyloidosis of unknown etiology caused by the deposition of amyloid fibrils derived from wild-type TTR; this is a syndrome described mainly in elderly Caucasian men who commonly exhibit poor functional capacity, atrial arrhythmias, and heart failure.2,3,4 Establishing a diagnosis of ATTR amyloidosis can be challenging as biopsy proof, usually from the affected tissue, is required; this can be particularly problematic in older patients with signs and symptoms of congestive heart failure. Moreover, in ATTRwt, there are no definitive biomarkers of disease and the clinical characteristics frequently overlap with other forms of amyloidosis featuring cardiac involvement. Treatment options in TTR-associated cardiac amyloidosis are limited and disease management is often focused on control of heart failure symptoms. While several promising therapies are currently in development, organ transplantation remains the major accepted treatment for ATTR cardiac amyloidosis at present. Thus, there is an important need for improvements in ATTR disease diagnosis, monitoring, and treatment; the discovery of ATTRm- and/or ATTRwt-specific indicators would offer advancement in each of these areas and potentially reveal key information regarding ATTR disease mechanisms.



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

Various immunologic and biochemical methodologies employing a proteomic-based approach have been used for discovery and validation of disease biomarkers.5,6 Many of these strategies have included the use of microarray technologies which rely on monoclonal antibodies and enzyme-linked immunosorbent assay (ELISA) analyses to detect and quantitate proteins in complex solutions. ELISAbased data have been used to identify serum protein profiles for the diagnosis of bladder cancer and nonsmall cell lung cancer.7,8 An alternative approach to immunochemical techniques is the use of multiplereaction monitoring mass spectrometry (MRM-MS), a targeted quantification method that measures protein to peptide abundances.9 MRM-MS is recognized as a sensitive and selective proteomic method which offers several advantages over immunodetection or ELISA-based techniques. The analytical restrictions associated with reliance on available antibodies and the specificity of these immunologic reagents is avoided in mass spectral proteomic measurements. In addition, the multiplexing capability, reproducibility, and small volume requirement make MRM-MS a versatile and efficient platform for profiling and comparing serum protein levels in ATTRm and ATTRwt amyloidosis. The aim of this study was to investigate the presence of serum proteomic identifiers in ATTR cardiac amyloidosis to uncover indicators with utility in disease detection and monitoring. We performed targeted proteomic analysis of 271 peptides representing 160 distinct proteins to identify differences in ATTRm, ATTRwt, and healthy control sera. Disease-specific proteins were further analyzed with several online bioinformatics tools developed to understand protein characteristics and associations. These data provide initial evidence for several candidate markers uniquely associated with ATTRm or ATTRwt cardiomyopathy, and highlight the need for further mechanistic studies to understand the pathobiological differences between inherited and acquired TTR-associated cardiac amyloid disease. Experimental Procedures Study groups Patient sera were obtained from the clinical specimens repository in the Boston University Amyloidosis Center with approval from the Institutional Review Board at the Boston University Medical Campus. Samples were chosen from cases with an unequivocal diagnosis of ATTRm or ATTRwt 4 ACS Paragon Plus Environment

Page 4 of 31

Page 5 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


amyloidosis featuring cardiac involvement. The diagnosis of amyloidosis was based on Congo red staining of a cardiac or other tissue biopsy; cardiac amyloid disease type was established by immunohistochemical, immunogold electron microscopic, or mass spectral identification of TTR in the congophillic deposits. For ATTRm, the amyloidogenic mutation was determined by genomic DNA sequencing10 and the presence of a variant TTR confirmed by isoelectric focusing of serum.11 No pathologic mutants were detected in the ATTRwt or healthy control cases. Cardiac involvement was defined by an interventricular septal wall thickness ≥ 12 mm and serum BNP ˃ 100 pg/mL. Sera from healthy, control subjects were available commercially and purchased from Bioreclamation (Westbury, NY). Patient and control sera were from age-, gender-, and race-matched individual donors. Sample preparation and total protein quantification Patient sera were separated from whole blood by centrifugation at 1500 rpm and 25°C for 10 minutes performed within 24 hours from collection. Patient and control sera were stored at -80°C until required for analyses. For proteomic studies, pooled samples were prepared by mixing equivalent amounts (50 µL) of sera from individuals with ATTRm (n=8), ATTRwt (n=10), or control (n=10) cases. Total protein concentrations in each of the pooled serum samples were measured using Pierce™ bicinchoninic acid assay (BCA) protein kit (Thermo Scientific, Waltham, MA). Bovine serum albumin was serially diluted with PBS, pH 7.4 to a working concentration range of 0 – 2000 µg/mL for use as protein standard solutions. Multiple-reaction monitoring mass spectrometry (MRM-MS) The presence and relative concentrations of 330 tryptic peptides representing 160 human serum proteins was determined using the PeptiQuant™ Human Discovery Assay (MRM-MS, MRM Proteomics, Victoria, BC, Canada). Pooled serum samples were denatured and reduced with 9 M urea/20 mM dithiothreitol for 30 minutes at 37 °C. Denatured proteins were alkylated with 40 mM iodoacetamide for 30 minutes at room temperature then diluted to a final urea concentration of 0.55 mM prior to trypsin digestion. A substrate:enzyme ratio digestion of 20:1 was carried out using TPCK-treated trypsin (Worthington Biochemical) for 18 hours at 37 ºC. Digestion samples were acidified with a 1% solution 5 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

of formic acid and chilled stable isotope-labeled standards (SIS) peptide mixture. Samples were concentrated via solid phase extraction (10 mg Oasis HLB cartridges; Waters, Milford, MA) and lyophilized. Dried samples were rehydrated in 0.1% formic acid to a concentration of 1 µg/uL for LCMRM/MS analysis. Peptide analyses were performed in triplicate. Statistical, biological function, and interaction network analyses Quantified protein data obtained from MRM-MS analyses of ATTRm, ATTRwt, and control sera were compared using Welch’s t-test for unequal variance. P-values were adjusted using the false discovery rate (FDR, Benajmini & Hochberg) test for multiple comparison testing.12,13 Statistical significance was defined as p < 0.05. Initial information about ATTR differentially expressed proteins was obtained from UniprotKB database (Universal Protein Resource Knowledgebase, http://www.uniprot.org/)14,15; results included descriptions of protein sequences and functional data derived from genome sequencing projects and literature reference sources. For further classification, biological context, and involvement in molecular pathways, proteins were subjected to PANTHER version 11.0 (Protein ANalysis THrough Evolutionary Relationships, http://pantherdb.org/)16, DAVID version 6.7 (Database for Annotation, Visualization, and Integrated Discovery, https://david.ncifcrf.gov/)17,18 and STRING version 10.0 (Search Tool for the Retrieval of Interacting Genes/Proteins, http://string-db.org/)19 analyses. Specifically, gene names of the differentially expressed protein sets, obtained from UniprotKB, were uploaded to PANTHER and mapped to obtain predictions of molecular functions, biological processes, and classifications. Results from PANTHER were further studied using DAVID, a web-based resource that provides specific information from the Gene Ontology (GO, http://geneontology.org/)20 database describing the formal naming and definition of types, properties, and associations relating to enriched gene/protein clusters. Both PANTHER and DAVID take annotation resources from UniprotKB, Ensembl (http://www.ensembl.org/)21, EntrezGene (http://www.ncbi.nlm.nih.gov/gene/)22, and RefSeq (http://www.ncbi.nlm.nih.gov/refseq/).23 Protein-protein interaction network analyses were examined with STRING, a database of recognized and predicted molecular associations. 6 ACS Paragon Plus Environment

Page 6 of 31

Page 7 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


Results Serum concentration profiles in ATTR All ATTR and control study sera were matched to age, gender, and race; patients and donors were individuals aged ≥ 60 years, male, and Caucasian (Table 1). ATTR sera were obtained at time of baseline evaluation at our center. Mean ages at sample collection for the ATTRm and ATTRwt groups were 68.2 ± 7.3 and 73.6 ± 5.3 years, respectively; individual ages for controls were not available. In ATTRm, amyloidogenic TTR mutants included A81V, I68L, A19D, T60A, E89Q, and T59K. Both ATTR groups were comprised of patients with cardiac amyloid as a major feature of disease; measures of cardiac involvement included BNP of 308 and 585 pg/mL, cTnI of 0.116 and 0.310 ng/mL, IVST of 15.9 and 16.3 mm, and LVEF 49.6 and 45.8 % for ATTRm and ATTRwt, respectively. Total protein concentrations in the pooled sera samples ranged from 8.0 to 8.5 g/dL in patient and control groups. By MRM-MS analyses, 159/330 (48.2%) of peptides were differentially expressed in ATTR (ATTRm or ATTRwt) vs. control; these data corresponded to variations between patient and control sera in the majority (123/160, 76.9%) of proteins that were measured (Figure 1). As demonstrated by the Venn diagram, the serum concentrations of 82 proteins in both ATTRm and ATTRwt were significantly different from control; interestingly, this group included TTR and 2 other amyloidogenic proteins, serum amyloid A-1 and apolipoprotein C-II. Conversely, there were protein level variations that were exclusive to each ATTR group when compared to control; 14 were unique to ATTRm and 27 distinct to ATTRwt. In the protein set unique to ATTRm sera (Table 2), the majority of concentration levels (11/14) were significantly decreased with fold changes ranging from 0.57 – 0.96 of control. Notably, retinolbinding protein 4 (RBP4), a normal circulating partner of TTR, was found to be significantly lower in ATTRm vs. control sera by a 0.76-fold difference. Coagulation factor XIII A chain (F13A1) was the lowest differentially expressed protein with a 0.57-fold change from control. Three proteins in the ATTRm set were shown to have higher levels than control and included inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), fibronectin (FN1) and sex hormone-binding globulin (SHBG), the latter



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

increased by 1.4-fold. Moreover, levels of 7/14 proteins were significantly different between ATTRm and ATTRwt including RBP4 which was 0.67-fold lower in ATTRm (p = 0.00005). For the ATTRwt-specific group, 17/27 proteins exhibited decreased levels (0.52 – 0.89-fold change) when compared to control data (Table 3). Apolipoprotein E (APOE) was the most dramatically reduced at about 50% of control level (fold change, 0.52; p = 0.00001). Conversely, elevated concentrations, ranging from 1.19 – 2.25 fold change from control, were observed in 10/27 proteins differentially expressed in the ATTRwt sera. Complement component C7 (C7) was more than twice the control level in the patient pooled sera. In addition, a comparative analysis of the 27 proteins in ATTRwt vs. ATTRm by Welch’s t-test showed significant differences in a majority (16/27) of the set. In the set that was significantly different between the patient groups, more than one-half (9/16) were lower in ATTRwt and included APOE24 and FGA25, two proteins associated with other amyloid diseases. In ATTRwt, fold changes in APOE and FGA levels were 0.66 (p = 0.0003) and 0.85 (p = 0.006), respectively. Elevated concentrations in ATTRwt vs. ATTRm were similar to those noted in the comparison to control and included C7 with a 1.65-fold change (p = 0.003). Functional annotations and predicted associations among ATTR disease-specific proteins The proteins differentially expressed and specific to ATTRm and ATTRwt cardiac patient sera were further studied using PANTHER and DAVID to determine molecular and biological functions, and potential relationships. PANTHER's classification system revealed 3 categories of GO molecular functions that were common to proteins in both ATTRm and ATTRwt; these included binding, catalytic activity, and receptor activity (Figure 2). In ATTRm, proteins were equally distributed between binding (44.4%) and catalytic activity (44.4%), while receptor activity was attributed to only a portion (11.1%) of the group. However, in ATTRwt, binding was less frequent (28.6%) than catalytic activity (35.7%), and receptor activity (21.4%) was more frequently occurring. In addition, transporter activity (14.3%) was identified only in ATTRwt. The majority of the proteins for the ATTR groups belonged to 4 major GO biological processes; localization (15.4 vs.7.7 %), cellular process (30.8 vs. 21.8%), metabolic process (23.1 vs. 11.5%), and response to stimulus (23.1 vs. 14.1%) showed varied results in ATTRm and 8 ACS Paragon Plus Environment

Page 8 of 31

Page 9 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


ATTRwt, respectively. Major classifications unique to ATTRwt featured developmental process (7.7%), biological adhesion (11.5%), immune system process (11.5%), and response to stimulus (14.1%). Analysis of the 14 proteins differentially expressed in ATTRm yielded a gene count coverage of > 85.71 % (Figure 3A). The most enriched functional annotation terms included disulfide bond, secreted, polymorphism, signal, signal peptide, sequence variant, and GO:0005576~extracellular region. Alternatively, in the ATTRwt set (Figure 3B), a higher (> 92.59 %) gene count coverage for 25/27 proteins was obtained. The most enriched functional annotation terms for the ATTRwt-specific group included glycoprotein, in addition to signal, signal peptide, and GO:0005576~extracellular region. Proteins that were unique to ATTRm or ATTRwt were further analyzed using STRING, an open-access database that provides information on functional interactions among proteins based on both experimental results and predictive algorithms. Among the 14 proteins, found to be unique to ATTRm in their variation from control, a single cluster of 4 interacting proteins was observed (Figure 4A). Interactions of coagulation factor XIII A chain (F13A1), secreted protein acidic and rich in cysteine (SPARC), and fibrinogen (FN1) were defined as reaction (black line) associations, while links among F13A1, FN1, and inter-alpha trypsin inhibitor heavy chain H4 (ITIH4) were classified as binding (blue line) associations. In the 7 proteins that were significantly different from ATTRwt, no associations were predicted (Supplemental Figure 1). Predicted interactions among the 27 ATTRwt-specific proteins are shown in Figure 4B. Two distinct clusters indicating separately associated protein groups were noted. The first cluster set featured 8 proteins interacting in a variety of categorized associations. Multiple links between vitamin-Kdependent protein S (PROS1) and coagulation factor V (F5) were defined as binding and reaction associations. PROS1 and F2 were noted to have an inhibition association (red line). Interactions among F5, prothrombin (F2), coagulation factor XIII B chain (F13B), and fibrinogen alpha chain (FGA) were designated as binding, activation (green line), and catalysis (purple line) associations. FGA, beta-2microglobulin (B2M), and vascular cell adhesion protein 1 (VCAM1) were predicted to form a reaction



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

link. The second cluster featured 2 proteins, complement component C8 alpha chain (C8A) and complement component C7 (C7), with activation and binding associations. Discussion In the present study, we used a proteomic approach to study differentially expressed proteins in sera from patients with ATTRm or ATTRwt cardiac amyloidosis, and healthy control donors. Important and novel aspects of this study include 1) demonstration of proteomic profile differences between serum from patients with ATTR cardiac amyloidosis and age-, gender-, and race-matched healthy controls; 2) identification of differentially expressed serum protein levels unique to ATTRm and ATTRwt cardiac amyloidoses; 3) assessment of functional and annotation term descriptions for clusters of disease-specific proteins; and 4) predictions of protein interactions and relationships in the ATTR protein groups. Previously published reports have demonstrated the utility of proteomic analysis and protein profiling in identifying disease biomarkers. An advantage of these studies lies in the discovery approach of examining global protein content rather than a limited strategy studying a restricted set of proteins based solely on prior knowledge. An expanded dataset from proteomic analyses presents an opportunity to ascertain disease-related differences, and in combination with statistical and bioinformatics tools, can be utilized to potentially ascertain pathologically-related protein functions and networks. The data from our proteomic analyses provide evidence that significant differences in the circulating levels of > 100 serum protein exist in patients with ATTR cardiac amyloidosis (inherited or sporadic) compared to healthy donors. Interestingly, circulating concentrations of TTR, the putative amyloid fibril precursor, were significantly varied in both ATTR groups vs. controls (Supplemental Table 1). Furthermore, in the study of ATTRm vs. ATTRwt, there were protein levels unique to each disease. For instance, RBP4 was found to be significantly decreased in ATTRm compared to controls, but not in ATTRwt. This is in agreement with our measurements in ELISA studies of patient sera where we have found significantly lower levels of RBP4 in ATTRm, particularly in ATTR-V122I, and near normal concentrations in ATTRwt.


Page 10 of 31

Page 11 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


To gain a further understanding of functionality and relationships between the disease-specific differentially expressed proteins, we performed cluster analysis predictions. Results for the ATTRm group revealed differences in 11/14 proteins known to be linked to amyloid proteins or associated with other amyloid pathologies, including Alzheimer’s disease (AD). The protein set, which included RBP426, ANG27,28, SHBG29, LYZ30, APOD31, SPARC32, PON333, FN134, HPX35, C436, and PRG437, was classified by PANTHER into catalytic activity, binding, and receptor activity molecular functions and cellular process, metabolic process, and response to stimulus biological functions. These predictions suggest that this cluster of proteins may share common pathways and processing at the cellular level. Further analyses of the GO categorizations were investigated using DAVID to extend our results from PANTHER and provide an interpretation of GO annotations. Common DAVID terms for the ATTRm group were secreted, GO:0005576~extracellular region, signal, signal peptide, sequence variant, and polymorphism. These annotations appear to be consistent with the study of serum, containing proteins exported to the circulation through a secretory pathway, from individuals with an inherited type of amyloidosis caused by mutant forms of TTR. In addition, disulfide bond was also a predicted term which may be linked to the protein misfolding nature of amyloid diseases. Of the 27 proteins differentially expressed and unique to ATTRwt, 20 proteins have been shown to be amyloidogenic or linked to amyloidosis and/or AD. The group included APOH 38, CFH 39, PROS12, SERPINA342,43, F544, FBLN145, APOE46, B2M47,48, FGA49, FCGBP50, C736,51, CP52, C8A53, IGFALS54, APMAP55, VCAM127, F244, CPN257, C1S36, and LBP58. Several studies in APOE protein levels found in biological fluids (i.e. cerebrospinal fluid, plasma, serum) has been studied to identify the patheogensis of AD59,60. The presence of APOE is known to cause the formation of beta-amyloid plaques in the brain61. Because this study featured patients in the ATTR groups with cardiac primary involvement, it is difficult to conclude whether or not APOE concentration has a true effect; a future study to include ATTRm patients with polyneuropathy is needed. Analysis using PANTHER yielded molecular functions similar to those described for ATTRm, but with the additional categorical term, transporter activity. Similarly, there was overlap in the 11 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

biological process classifications for ATTRwt and ATTRm, notwithstanding 2 additional annotations, biological adhesion and localization, identified in ATTRwt. Transporter activity (GO:0005215) refers to the movement of substances (such as macromolecules, small molecules, ions) into, out of, or within a cell or between cells. Biological adhesion (GO:0022610) suggests that intracellular attachments at specific membrane regions may be relevant, while localization (GO:0051179) refers to cells or protein complexes either transported or remaining at a specific location. Results from DAVID included the terms signal, signal peptide, glycoprotein, and GO:0005576~extracellular region which were consistent with our proteomic profiling of serum. Interestingly, the 3 terms common to both ATTRm and ATTRwt, signal, signal peptide, and GO:0005576~extracellular region, suggest that the unique proteins have a similar production cascade and may be important in ATTR cardiac amyloidosis pathogenesis. The examination of protein-protein relationships within the ATTR sets was accomplished with STRING. In ATTRm, an association among 4 of 14 proteins was predicted. The relationship included a type II acute-phase protein involved in inflammatory responses (ITIH4, p = 0.023), a protein involved in cell shape, adhesion and motility (FN1, p = 0.047), an enzyme that catalyzes the formation of gammaglutamyl-epsilon-lysine cross-links between fibrin chains (F13A1, p = 0.026), and a cell growth regulator which functions through interactions with the extracellular matrix and cytokines (SPARC, p = 0.01). While these proteins are related in terms of cell formation and processes, their role in ATTRm is unknown. Of note, there was no predicted relationship between RBP4 and any of the other 13 proteins found statistically significant in the STRING analyses despite significantly lower concentrations compared to control (p = 0.03) and ATTRwt (p = 0.00005) sera. RBP4 is thought to have antiamyloidogenic properties as it binds to and stabilizes native state TTR62,63; thus, data from this study provides further evidence in support of RBP4 as a potential biomarker of ATTRm. Alternatively, in 10 of 27 differentially expressed proteins specific to ATTRwt, multiple proteinprotein interactions were predicted. Common trends among this group were relationships to hemostasis and the immune response system. Inter-related associations were found among PROS1 (p = 0.003) – an anti-coagulant plasma protein, F5 (p = 0.017) – a cofactor that drives activation of prothrombin to 12 ACS Paragon Plus Environment

Page 12 of 31

Page 13 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


thrombin, B2M (p = 0.001) – a protein involved in the presentation of peptide antigens to the immune system, FGA (p = 0.005) – a primary component of blood clots, IGFALS (p = 0.008) – a facilitator of receptor-ligand binding or cell adhesion, F13B (p = 0.038) – a regulator of transglutaminase formation by thrombin, VCAM1 (p = 0.029) – a factor important in cell-cell recognition, and F2 (p = 0.037) – a protein functioning in blood homeostasis, inflammation and wound healing. A separate interaction was predicted between C7 (p = 0.002), a protein that serves as a membrane anchor and helps with the process of innate immune response by forming pores in cellular plasma membrane, and C8A (p = 0.004) which inserts itself into target membrane and does not form pores by itself. One drawback in the present study is the use of pooled sera. In the comparative analysis of a small number of samples, it is difficult to verify whether distributions of measurements violate the normality assumption and statistical power is limited. However, we utilized the Welch’s t-test and performed multiple corrections with FDR to address this limitation. By adjusting the p-values with FDR, this study has shown significant concentration differences between ATTR and control in 76.9% (123/160) of the serum proteins that were studied. In summary, data from the present study suggest that the serum proteomes in ATTR and healthy age-matched controls are dissimilar. Our findings of unique differences between ATTRm and ATTRwt suggest multiple serum candidates that may be useful in identification of ATTR and differentiating between inherited and acquired TTR-associated cardiac amyloidosis. Differentially expressed proteins, including RBP4, may have diagnostic and prognostic utility in ATTR amyloidosis. Supporting Information The following files are available free of charge at ACS website http://pubs.acs.org: SI Figure 1: No STRING associations are seen in 7 out of the 14 proteins unique to ATTRm. SI Figure 2: ATTRwt STRING associations are seen for 16 out of 27 proteins that are significantly different than controls. SI Table 1: Proteins differentially expressed in both ATTRm and ATTRwt. Acknowledgements 13 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

Page 14 of 31

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. References 1.

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

2.

Ng, B., Connors, L. H., Davidoff, R., Skinner, M. & Falk, R. H. Senile systemic amyloidosis presenting with heart failure: a comparison with light chain-associated amyloidosis. Arch. Intern. Med. 165, 1425–9 (2005).

3.

Pinney, J. H. et al. Senile Systemic Amyloidosis: Clinical Features at Presentation and Outcome. J. Am. Heart Assoc. 2, e000098–e000098 (2013).

4.

Connors, L. H. et al. Heart Failure Resulting From Age-Related Cardiac Amyloid Disease Associated With Wild-Type Transthyretin: A Prospective, Observational Cohort Study. Circulation 133, 282–90 (2016).

5.

Caron, M., Choquet-Kastylevsky, G. & Joubert-Caron, R. Cancer immunomics using autoantibody signatures for biomarker discovery. Mol. Cell. Proteomics 6, 1115–22 (2007).

6.

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

7.

Sanchez-Carbayo, M., Socci, N. D., Lozano, J. J., Haab, B. B. & Cordon-Cardo, C. Profiling Bladder Cancer Using Targeted Antibody Arrays. Am. J. Pathol. 168, 93–103 (2006).

8.

Zhong, L. et al. Using Protein Microarray as a Diagnostic Assay for Non–Small Cell Lung Cancer. Am. J. Respir. Crit. Care Med. 172, 1308–1314 (2005).

9.

Picotti, P. & Aebersold, R. Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions. Nat. Methods 9, 555–66 (2012).

10.

Lim, A. et al. Characterization of transthyretin variants in familial transthyretin amyloidosis by mass spectrometric peptide mapping and DNA sequence analysis. Anal. Chem. 74, 741–51 (2002).

11.

Connors, L. H. et al. A simple screening test for variant transthyretins associated with familial 14 ACS Paragon Plus Environment

Page 15 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


transthyretin amyloidosis using isoelectric focusing. Biochim. Biophys. Acta 1407, 185–92 (1998). 12.

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).

13.

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).

14.

Apweiler, R. et al. UniProt: the Universal Protein knowledgebase. Nucleic Acids Res. 32, D115– D119 (2004).

15.

Leinonen, R., Nardone, F., Zhu, W. & Apweiler, R. UniSave: The UniProtKB Sequence/Annotation version database. Bioinformatics 22, 1284–1285 (2006).

16.

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).

17.

Dennis, G. et al. DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol. 4, P3 (2003).

18.

Huang, D. W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2009).

19.

von Mering, C. et al. STRING: known and predicted protein-protein associations, integrated and transferred across organisms. Nucleic Acids Res. 33, D433-7 (2005).

20.

Gene Ontology Consortium. The Gene Ontology (GO) database and informatics resource. Nucleic Acids Res. 32, 258D–261 (2004).

21.

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

22.

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

23.

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). 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

24.

Carter, D. B. The interaction of amyloid-beta with ApoE. Subcell. Biochem. 38, 255–72 (2005).

25.

Eriksson, M. et al. Three German fibrinogen Aα-chain amyloidosis patients with the p.Glu526Val mutation. Virchows Arch. 453, 25–31 (2008).

26.

Benson, M. D. & Dwulet, F. E. Prealbumin and retinol binding protein serum concentrations in the Indiana type hereditary amyloidosis. Arthritis Rheum. 26, 1493–8 (1983).

27.

Del Giudice, R. et al. Amyloidogenic variant of apolipoprotein A-I elicits cellular stress by attenuating the protective activity of angiogenin. Cell Death Dis. 5, e1097 (2014).

28.

Del, R. et al. Does Angiogenin Play a Role in Amyloid Diseases ? Chinese Journal of Biochem and Mol Biol. 31, 1276-83 (2015).

29.

Gillett, M. J. et al. Relationship between testosterone, sex hormone binding globulin and plasma amyloid beta peptide 40 in older men with subjective memory loss or dementia. J. Alzheimers. Dis. 5, 267–9 (2003).

30.

Helmfors, L. et al. Protective properties of lysozyme on β-amyloid pathology: implications for Alzheimer disease. Neurobiol. Dis. 83, 122–133 (2015).

31.

Li, H. et al. Apolipoprotein D modulates amyloid pathology in APP/PS1 Alzheimer’s disease mice. Neurobiol. Aging 36, 1820–33 (2015).

32.

Vafadar-Isfahani, B. et al. Identification of SPARC-like 1 protein as part of a biomarker panel for Alzheimer’s disease in cerebrospinal fluid. J. Alzheimers. Dis. 28, 625–36 (2012).

33.

Erlich, P. M. et al. Serum paraoxonase activity is associated with variants in the PON gene cluster and risk of Alzheimer disease. Neurobiol. Aging 33, 1015.e7-1015.e23 (2012).

34.

Kawahara, E., Shiroo, M., Nakanishi, I. & Migita, S. The role of fibronectin in the development of experimental amyloidosis. Evidence of immunohistochemical codistribution and binding property with serum amyloid protein A. Am J Pathol 134, 1305–1314 (1989).

35.

Hahl, P., Davis, T., Washburn, C., Rogers, J. T. & Smith, A. Mechanisms of neuroprotection by hemopexin: modeling the control of heme and iron homeostasis in brain neurons in inflammatory states. J. Neurochem. 125, 89–101 (2013). 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


36.

Veerhuis, R. et al. Complement activation in amyloid plaques in Alzheimer’s disease brains does not proceed further than C3. Virchows Arch. 426, 603–10 (1995).

37.

Shioi, J. et al. The Alzheimer amyloid precursor proteoglycan (appican) is present in brain and is produced by astrocytes but not by neurons in primary neural cultures. J. Biol. Chem. 270, 11839– 44 (1995).

38.

Song, F. et al. Plasma Apolipoprotein Levels Are Associated with Cognitive Status and Decline in a Community Cohort of Older Individuals. PLoS One 7, e34078 (2012).

39.

Alexandrov, P. N., Pogue, A., Bhattacharjee, S. & Lukiw, W. J. Retinal amyloid peptides and complement factor H in transgenic models of Alzheimer’s disease. Neuroreport 22, 623–7 (2011).

40.

Ferland, G. Vitamin K, an emerging nutrient in brain function. Biofactors 38, 151–7 (2012).

41.

Ferland, G. Vitamin K and the Nervous System: An Overview of its Actions. Adv. Nutr. An Int. Rev. J. 3, 204–212 (2012).

42.

Nilsson, L. N. et al. Alpha-1-antichymotrypsin promotes beta-sheet amyloid plaque deposition in a transgenic mouse model of Alzheimer’s disease. J. Neurosci. 21, 1444–51 (2001).

43.

Padmanabhan, J., Levy, M., Dickson, D. W. & Potter, H. Alpha1-antichymotrypsin, an inflammatory protein overexpressed in Alzheimer’s disease brain, induces tau phosphorylation in neurons. Brain 129, 3020–34 (2006).

44.

Emori, Y. et al. Life-threatening bleeding and acquired factor V deficiency associated with primary systemic amyloidosis. Blood Coagul. Fibrinolysis 13, 555–9 (2002).

45.

Ohsawa, I., Takamura, C. & Kohsaka, S. Fibulin-1 binds the amino-terminal head of beta-amyloid precursor protein and modulates its physiological function. J. Neurochem. 76, 1411–20 (2001).

46.

Poirier, J. Apolipoprotein E and Alzheimer’s disease. A role in amyloid catabolism. Ann. N. Y. Acad. Sci. 924, 81–90 (2000).

47.

Drüeke, T. B. Beta2-microglobulin and amyloidosis. Nephrol. Dial. Transplant 15 Suppl 1, 17–24 (2000).

48.

Jaradat, M. I., Schnizlein-Bick, C. T., Singh, G. K. & Moe, S. M. beta(2)-Microglobulin increases 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

the expression of vascular cell adhesion molecule on human synovial fibroblasts. Kidney Int. 59, 1951–9 (2001). 49.

Stangou, A. J. et al. Hereditary fibrinogen A alpha-chain amyloidosis: phenotypic characterization of a systemic disease and the role of liver transplantation. Blood 115, 2998–3007 (2010).

50.

Kochunov, P. et al. Transcriptomics of cortical gray matter thickness decline during normal aging. Neuroimage 82, 273–283 (2013).

51.

Shen, Y., Yang, L. & Li, R. What does complement do in Alzheimer’s disease? Old molecules with new insights. Transl. Neurodegener. 2, 21 (2013).

52.

Ayton, S. et al. Ceruloplasmin and β-amyloid precursor protein confer neuroprotection in traumatic brain injury and lower neuronal iron. Free Radic. Biol. Med. 69, 331–7 (2014).

53.

Ikonen, M. et al. Interaction between the Alzheimer’s survival peptide humanin and insulin-like growth factor-binding protein 3 regulates cell survival and apoptosis. Proc. Natl. Acad. Sci. 100, 13042–13047 (2003).

54.

Sung, H. Y., Choi, E. N., Lyu, D., Mook-Jung, I. & Ahn, J.-H. Amyloid beta-mediated epigenetic alteration of insulin-like growth factor binding protein 3 controls cell survival in Alzheimer’s disease. PLoS One 9, e99047 (2014).

55.

Mosser, S. et al. The adipocyte differentiation protein APMAP is an endogenous suppressor of A production in the brain. Hum. Mol. Genet. 24, 371–382 (2015).

56.

Simao, T. et al. Development of an Anti-Vascular Cell Adhesion Protein-1 Aptamer for Molecular Imaging and Inflammation Detection in Transgenic Mouse Model of Alzheimer’s Disease. J. Biomed. Nanotechnol. 11, 2264–74 (2015).

57.

Song, F. et al. Plasma protein profiling of Mild Cognitive Impairment and Alzheimer’s disease using iTRAQ quantitative proteomics. Proteome Sci. 12, 5 (2014).

58.

de Haas, C. New insights into the role of serum amyloid P component, a novel lipopolysaccharidebinding protein. FEMS Immunol. Med. Microbiol. 26, 197–202 (1999).

59.

Merched, A. et al. Apolipoprotein E, transthyretin and actin in the CSF of Alzheimer’s patients: 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


relation with the senile plaques and cytoskeleton biochemistry. FEBS Lett. 425, 225–8 (1998). 60.

Bekris, L. M. et al. Multiple SNPs within and surrounding the apolipoprotein E gene influence cerebrospinal fluid apolipoprotein E protein levels. J. Alzheimers. Dis. 13, 255–66 (2008).

61.

Kline, A. Apolipoprotein E, amyloid-ß clearance and therapeutic opportunities in Alzheimer’s disease. Alzheimers. Res. Ther. 4, 32 (2012).

62.

White, J. T. & Kelly, J. W. Support for the multigenic hypothesis of amyloidosis: the binding stoichiometry of retinol-binding protein, vitamin A, and thyroid hormone influences transthyretin amyloidogenicity in vitro. Proc. Natl. Acad. Sci. U. S. A. 98, 13019–24 (2001).

63.

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



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

Page 20 of 31

Table 1. Demographic and clinical characteristics for sample groups, including serum levels for total protein, B-type natriuretic peptide (BNP), cardiac troponin-I (cTn-I), echocardiographic measure for inter-ventricular septal thickness (IVST), and left-ventricular ejection fraction (LVEF).

Group

Cardiac Amyloidosis Type

Age (years), Mean (SD)

Gender

Race

Dominant Organ Involved

Total Protein (g/dL)

BNP (pg/mL)

cTn-I (ng/mL)

IVST (mm)

LVEF (%)

ATTRm N=8

Inherited*

68.2 (7.3)

Male

White

Cardiac

8.5

308

0.116

15.9

49.6

ATTRwt N = 10

Acquired

73.6 (5.3)

Male

White

Cardiac

8.0

585

0.310

16.3

45.8

Controls N = 10

---

≥ 60

Male

White

Normal

8.3

< 72#

Forms of Transthyretin-Associated Cardiac ... - ACS Publications

Recommend Documents