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Article

Characterization of New Proteomic Biomarker Candidates in Mucopolysaccharidosis Type IVA

by
Víctor J. Álvarez
1,2,
Susana B. Bravo
3,
Maria Pilar Chantada-Vazquez
3,
Cristóbal Colón
1,
María J. De Castro
1,
Montserrat Morales
4,
Isidro Vitoria
5,
Shunji Tomatsu
2,
Francisco J. Otero-Espinar
6,7 and
María L. Couce
1,*
1
Department of Forensic Sciences, Pathology, Gynecology and Obstetrics, Pediatrics, Neonatology Service, Department of Paediatrics, Hospital Clínico Universitario de Santiago de Compostela, Health Research Institute of Santiago de Compostela (IDIS), CIBERER, MetabERN, 15706 Santiago de Compostela, Spain
2
Skeletal Dysplasia Lab Nemours Biomedical Research Nemours/Alfred I. du Pont Hospital for Children, 1600 Rockland Road., Wilmington, DE 19803, USA
3
Proteomic Platform, Health Research Institute of Santiago de Compostela (IDIS), Hospital Clínico Universitario de Santiago de Compostela, 15706 Santiago de Compostela, Spain
4
Minority Diseases Unit Hospital Universitario12 de Octubre, 28041 Madrid, Spain
5
Nutrition and Metabolophaties Unit, Hospital Universitario La Fe, 46026 Valencia, Spain
6
Paraquasil Platform, Health Research Institute of Santiago de Compostela (IDIS), Hospital Clínico Universitario de Santiago de Compostela, 15706 Santiago de Compostela, Spain
7
Department of Pharmacology, Pharmacy and Pharmaceutical Technology, School of Pharmacy, Campus Vida, University of Santiago de Compostela, 15872 Santiago de Compostela, Spain
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2021, 22(1), 226; https://doi.org/10.3390/ijms22010226
Submission received: 26 November 2020 / Revised: 21 December 2020 / Accepted: 24 December 2020 / Published: 28 December 2020
(This article belongs to the Special Issue Omics Technologies in Rare Diseases)
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Abstract

:
Mucopolysaccharidosis type IVA (MPS IVA) is a lysosomal storage disease caused by mutations in the N-acetylgalactosamine-6-sulfatase (GALNS) gene. Skeletal dysplasia and the related clinical features of MPS IVA are caused by disruption of the cartilage and its extracellular matrix, leading to a growth imbalance. Enzyme replacement therapy (ERT) with recombinant human GALNS has yielded positive results in activity of daily living and endurance tests. However, no data have demonstrated improvements in bone lesions and bone grow thin MPS IVA after ERT, and there is no correlation between therapeutic efficacy and urine levels of keratan sulfate, which accumulates in MPS IVA patients. Using qualitative and quantitative proteomics approaches, we analyzed leukocyte samples from healthy controls (n = 6) and from untreated (n = 5) and ERT-treated (n = 8, sampled before and after treatment) MPS IVA patients to identify potential biomarkers of disease. Out of 690 proteins identified in leukocytes, we selected a group of proteins that were dysregulated in MPS IVA patients with ERT. From these, we identified four potential protein biomarkers, all of which may influence bone and cartilage metabolism: lactotransferrin, coronin 1A, neutral alpha-glucosidase AB, and vitronectin. Further studies of cartilage and bone alterations in MPS IVA will be required to verify the validity of these proteins as potential biomarkers of MPS IVA.

1. Introduction

Morquio A syndrome, or mucopolysaccharidosis type IVA (MPS IVA, OMIM #253000), is an autosomal recessive disease caused by mutations in the GALNS gene. A deficiency of N-acetylgalactosamine-6-sulfatase (GALNS, E.C.3.1.6.4) [1,2,3] leads to the accumulation of keratan sulfate (KS) and chondroitin-6-sulfate (C6S) in multiple tissues, mainly bone, cartilage, heart valves, and cornea. The classical phenotype is characterized by systemic skeletal dysplasia with incomplete ossification and successive imbalance of growth [4], including short stature and neck, cervical instability, spinal cord compression, tracheal obstruction, prominent chest, kyphoscoliosis, laxity of joints, hip dysplasia, and knock knees [5,6]. Respiratory failure is the primary cause of death during the second and third decades of life in untreated patients [7,8].
Currently, two therapies are available for MPS IVA in clinical practice, namely enzyme replacement therapy (ERT) and hematopoietic stem cell transplantation (HSCT) [1,9,10]. ERT and HSCT are based on the principle of cross-correction, whereby lysosomal enzymes are taken up by deficient recipients’ cells and their lysosomes via the mannose-6-phosphate receptor. ERT with recombinant enzyme GALNS (elosulfase alfa) is an established treatment for MPS IVA. However, like other forms of ERT for lysosomal storage diseases (LSDs), elosulfase alfa has several limitations. It requires weekly 4–6 h infusions; is cleared rapidly due to its short half-life (35 min in human, 2 min in mouse) [11,12,13], it is expensive [13,14], penetration of the avascular cartilage is limited; and patients can develop an immune response against the infused enzyme [11,14,15]. In addition, clinical trials of elosulfase alfa have shown little improvement in bone growth and pathology [16,17,18,19]. Recent studies have demonstrated that the presence of KS, KS sulfation level, chondroitin-6-sulfate levels, and the presence of collagen type II in blood are potential biomarkers [20] associated with bone and cartilage disease in MPS IVA. Although urinary KS levels have been measured as a potential biomarker in clinical trials, there is no proof that decreases in urinary KS reduction correlate with clinical improvement. Urinary KS originates in the kidneys and does not reflect the degree of impairment of bone and other relevant tissues in MPS IVA. Therefore, urinary KS is considered a pharmacokinetic marker but not a surrogate biomarker [20].
Proteomics allows the large-scale identification and quantification of proteins in biological fluids (serum, urine, saliva, tears, etc.), cells, tissues, or organisms in continuous change. Among the first proteomic approaches developed are one and two-dimensional polyacrylamide gel systems (1D SDS-PAGE and 2D SDS-PAGE). These methods provide a means of monitoring protein purification, protein expression, and post-transcriptional modifications [20]. Although 1D and 2D SDS-PAGE are commonly used to screen for putative biomarkers in several disorders, particularly in animal studies [21,22], they have not been applied to LSDs. Mass spectrometry (MS) is a more recent and accurate proteomics technology, and allows high-through put protein identification [23,24]. This approach also enables the characterization of post-transcriptional modifications, such as phosphorylation and glycosylation, similar to the 2D-PAGE approach [25]. In the last decade, MS has led to significant advances by increasing the number of potential protein biomarkers of different diseases [26]. Liquid chromatography (LC) coupled with MS is widely used to search for disease biomarkers [24] in different biological sample types [26,27,28].
Most quantitative methods using liquid chromatography-tandem mass spectrometry (LC-MS/MS) involve labeling of proteins/peptides with heavy and light stable-isotope pairs (SILAC, iTRAQ). More recently developed label-free quantification techniques rely on advanced software analysis. One of these techniques is SWATH-MS (sequential window acquisition of all theoretical mass spectra) analysis [29,30]. This method measures the concentrations of peptide analytes (10 peptides per protein in SWATH analysis) in two or more samples, using certain peptides in the samples as an internal standard. By contrast, other absolute quantification techniques use external peptides as standards to create a calibration curve. These external peptides are identified by searching using monitoring methods (monitoring of selected reactions or multiple reactions) [23].
Given that MPS IVA is a dynamic entity that involves alterations in the expression of multiple proteins, proteomics techniques can provide important biological information that can help advance our understanding of the underlying pathophysiological mechanisms. Moreover, proteomics could aid the identification of novel disease biomarkers [28,30,31], which can facilitate disease diagnosis, prognosis, and monitoring [32,33,34,35,36,37,38,39,40,41,42].
To address the lack of disease-specific protein biomarkers in MPS IVA, we applied quantitative and qualitative proteomics approaches to peripheral blood cell specimens from treated and untreated patients with MPS IVA to systematically identify and biochemically characterize new biomarker candidates.

2. Results

Leukocytesamplesfrom13 patients with MPS IVA and 6 control subjects were classified in the three following groups: healthy controls; untreated MPS IVA patients; and ERT-treated MPS IVA patients, from whom samples were acquired before (ERT-a group) and 24 h after (ERT-b group) treatment. The demographic features of participating MPS IVA patients are shown in Table 1.
We first performed a qualitative analysis to identify the entire set of proteins expressed in leukocyte samples using LC-MS/MS technology in data-dependent acquisition (DDA) mode. Proteins were identified with only 1% error (false discovery rate (FDR) 1%). To characterize the most significant proteins, we selected those commonly found in all or all but one sample (n − 1) per group. Subsequently, quantitative analysis was performed using the SWATH method.

2.1. Qualitative Analysis of Proteins

Table 2 shows the number of proteins identified by LC-MS/MS in individual samples and the number of proteins commonly found in all or all but one samples. We identified 235 proteins in untreated patients, 164 proteins in health controls, 301 proteins in the ERT-a group, and 222 proteins in the ERT-b group.
To analyze the distribution of proteins expressed in leukocytes across the different groups, a Venn diagram was generated (Figure 1). Supplementary Table S1 shows this same list with the corresponding UniProt codes and names of the identified proteins.
These proteins were subjected to functional analysis using the FunRich program. In this analysis, we evaluated proteins implicated in the endosome, lysosomal lumen, lysosomal membrane, lysosome, mitochondria, and vesicles, since these organelles are affected in patients with MPS IVA [42,43,44] (Figure 2). The percentage of proteins involved in endosome function was lower in untreated versus control samples, and was higher in ERT-a and ERT-b samples than in untreated samples, although still lower than that of control samples. A similar pattern was observed in proteins expressed in the lysosomal membrane, mitochondrion, and vesicles. By contrast, the percentage of proteins expressed in the lysosome and lysosomal lumen was lower in ERT-a and ERT-b.
Further functional analyses performed using the Reactome program allowed us to identify the metabolic pathways in which these proteins participate. In samples from ERT treated patients we observed significant differences with respect to untreated patients in the expression of proteins involved in inflammation pathways, including of leukotrienes, eoxins, and thromboxane. Expression of proteins involved in the gluconeogenesis pathway was also partially normalized in MPS IVA patients that received ERT compared to untreated patients.

2.2. Quantitative Analysis of Proteins by SWATH

To identify dysregulated proteins in leukocyte samples, we performed a quantitative analysis using SWATH. To this end, we generated a protein library consisting of 690 potential biomarker proteins expressed by leukocytes in all groups analyzed. Next, we performed large-scale targeted protein analysis to quantify the levels of each protein in each group. In this analysis, we only considered dysregulated proteins with a p-value < 0.05 and a fold change (FC) > 1.4. Table 3 shows the number of dysregulated proteins found for each SWATH comparison. Also, see Supplementary Table S2.

2.2.1. Proteins Down Regulated in MPS IVA Patients Relative to Healthy Controls

We next assessed the distribution of proteins that were downregulated in the untreated, ERT-a, and ERT-b groups relative to controls (Figure 3).
Table 4 shows the 91proteins that were down regulated in untreated patients relative to healthy controls, and indicates the changes observed in these proteins in the ERT-a and ERT-b groups. These proteins corresponded to the 36 proteins exclusively downregulated in the untreated group, the 15 downregulated proteins common to the untreated and ERT-a groups, the 6 proteins common to the untreated and ERT-b groups, and the 34 proteins common to the untreated, ERT-a, and ERT-b groups (Figure 3). We observed partial normalization (i.e., proteins remained dysregulated, p > 0.05) of the expression of proteins involved in the pyruvate metabolic pathway (KPYM, G3P, LDHA, PGK1, LDHB, ODPB and ALDOA; Table 4, gray rows) and complete normalization (protein expression was fully restored with treatment; p < 0.05) in some proteins involved in glucose metabolism (G6PI, PGM1 and G6PD; Table 4, green rows). Expression of most proteins involved in cytoskeletal organization (MOES, DEST, ARPC3, CORO1A, ANXA1, TPM1, K1C9, K22E, ARC1B, K2C1, K2C6A, TPM4, and K1C14) was normalized after ERT (Table 4, clear gray rows), although some remained downregulated (ARP2, ARPC5, ACTB). The following proteins are also involved in cytoskeletal organization: ADDB, a membrane-cytoskeleton-associated protein that promotes the assembly of spectrin-actin in a network of actin filaments (F-actin) and binds to actin monomers (G-actin); CNN2, which is involved in the regulation and modulation of smooth muscle contraction (Table 4, clear gray rows); SPTN1, which interacts with calmodulin in a calcium-dependent manner and regulates the movement of the cytoskeleton in the calcium-dependent membrane; VASP, which is involved in the remodeling of the cytoskeleton and all of them were normalized after ERT; and SEPT7, which is required for the normal organization of the actin cytoskeleton, and WDR1, which is involved in chemotactic cell migration by restricting the protrusions of the lamellipodial membrane, were further downregulated after ERT (Table 4, clear gray rows). Our findings reveal dysregulation of proteins involved in the lysosome/endosome system in untreated MPS IVA patients. Proteins involved in lysosomal membrane repair (LEG3 and VPS35) were normalized after ERT (Table 4, blue rows). Expression of STXB2 (Table 4, dark blue rows), which promotes vesicle trafficking and vesicle fusion with membranes in the SNARE position, was partially normalized in treated leukocytes (FC values decreased from 2.4 in untreated patients to 1.8 and 1. 6 in ERT-a or ERT-b groups, respectively). Expression of ubiquitin protein, UB2L3 (Table 4, clear blue rows), which is involved in vesicle trafficking from the endoplasmic reticulum to the lysosome, it was partially normalized. Expression of other proteins involved in membrane trafficking (ERP29 and PICAL; Table 4, dark blue rows) was also normalized after ERT.
We observed post-treatment normalization of the expression of several proteins involved in mitochondrial energy activity, assembly, or function (Table 4, pink rows) (ATPD, ATPA, CISY, PRDX5, ATPB), although others remained downregulated after ERT (ETFA, CH60, CH10, AATM, MDHM). TERA, which is involved in the formation of the transitional endoplasmic reticulum (tER), it was partially normalized only in the ERT-b group. GANAB, a catalytic subunit of glucosidase II of Glc2Man9GlcNAc2 oligosaccharide, acts as an immature precursor of glycoproteins involved in the N-glycan metabolism pathway, and was down regulated relative to healthy controls in all MPS IVA patient groups (Table 4, yellow rows). We also observed normalization after ERT of the expression of cytoplasmic and extracellular proteins (HBA, HBB) involved in oxygen transport and of proteins implicated in DNA binding (H13, H15). Proteins involved in the interconversion of metabolites, including hydrolases, dehydrogenases, transketolases, and isomerases (6PGD, ARGI1, TKT, THTR, PUR8, EM55, TTHY, IPYR2, DET1) were normalized after ERT (Table 4, dark gray rows). Among proteins involved in metabolic and cellular processes we observed normalization of PDIA3 and PSA; partial normalization of APT, PSME1, CD14, APOA2, PEBP1, and KAPCA; and no change in the expression of IGHG3 and EF1A3 (Table 4, dark pink rows). Several proteins with catalytic activity or transport-related functions showed partial normalization of expression after ERT (OLA1, RAN, CLIC1), although one such protein (VATA) showed no changes in expression (Table 4, orange rows). Proteins with DNA-binding functions (STIP1, PCBP2, HNRPK, ROA1, HMGB2) were partially or fully normalization after ERT (Table 4, clear red rows). Similarly, partial normalization of expression was observed for CEAM6, which belongs to the carcinoembryonic antigen-related cell adhesion molecule family, and OSTF1, which participates in bone resorption, interacts with secretion factors during bone formation, and participates in osteoclast development (Table 4, white rows).
Dysregulated proteins for which partial or complete normalization was observed after ERT are shown in the interaction diagrams in Figure 4. Figure 4A depicts the string network analysis of all 91 proteins that were downregulated in untreated MPS IVA patients relative to healthy controls. The results of the same analysis performed after treatment reveal a less complex network, given that many proteins were normalized by ERT.
Coronin 1A (CORO1A) is a crucial component of the cytoskeleton of highly mobile cells. This protein is involved in the invagination of large pieces of the plasma membrane and in the formation of protrusions of the plasma membrane, thereby contributing to cell locomotion. We carried out an interactome study using STING. As shown in Figure 5, we observed that CORO1A interacts with other specific proteins such as OSTF1, which participates in bone resorption and enhances osteoclast formation. In bone, CORO1A also regulates cathepsin K, which promotes degradation of collagen I and II.
Figure 6 shows the mean values of the area obtained for each individual sample in each group for CORO1A and GANAB proteins. GANAB is a catalytic subunit of glucosidase II that sequentially cleaves the two innermost alpha-1,3-linked glucose residues from the Glc(2)Man(9)GlcNAc(2) oligosaccharide precursor of immature glycoproteins. This protein is associated with the N-glycan metabolism pathway, which in turn is involved in glycan metabolism.

2.2.2. Proteins Upregulated in Untreated MPS IVA Patients Relative to Untreated Patients and Controls

We next identified proteins that were upregulated in the healthy control, ERT-a, and ERT-b groups relative to the untreated MPS IVA group (Figure 7).
Table 5 lists the 73 proteins that were upregulated in MPS IVA patients relative to healthy controls. We quantified the FC in the expression of these proteins relative to healthy controls to determine whether their expression was normalized with treatment. Expression of proteins involved in the organization of cellular components (Table 5, light blue rows) was normalized after treatment (except for ARAP1). Similar effects were observed for proteins involved in the cellular response to stimulus (Table 5, light green rows) and proteins expressed in components of the lysosome (Table 5, light pink rows). Other proteins that showed normalization of expression after ERT included those involved in extracellular matrix (ECM) binding and cellular adhesion (Table 5, light orange rows), and in the function of organelles such as the endoplasmic reticulum, Golgi apparatus, and mitochondria (Table 5, purple rows). Similarly, ERT resulted in normalization of the expression of proteins expressed in secretory granules and in small subcellular vesicles formed in Golgi apparatus (Table 5, dark blue rows), and partial or complete normalization of proteins involved in transport (Table 5, dark green rows).
Normalization of the expression of proteins involved in the transit of vesicles to lysosomes was also observed (Table 5, purple rows), including RAB4A, which modulates the remodeling of the actin cytoskeleton; ARAP1, which mediates cholesterol biosynthesis and drug metabolism; NB5R3, which is normally found in lysosomes; and DEF3 and TRFL, which may be implicated in oxidative stress.
Figure 8 shows the mean values obtained in each group for TRLF (lactotransferrin) and VTNC (vitronectin) proteins, which are implicated in bone reabsorption and mineralization.

2.2.3. Proteins Not Detected in Healthy Controls but Are Detected in MPSIV Patients

Table 6 shows proteins that were not detected in healthy controls and were downregulated in ERT-treated MPS IVA patients (ERT-a and/or ERT-b groups) relative to untreated patients. RNAS2 was common to the ERT-a and ERT-b groups. This protein is a non-secretory ribonuclease, which exerts selective chemotactic effects on dendritic cells. It is secreted by a range of innate immune cells, from blood cells to epithelial cells. Levels of this protein correlate with infection and inflammation processes. Recent studies have demonstrated that RNases in the extracellular space can exert immuno-modulatory effects.

3. Discussion

Variation in GALNS enzymatic activity has been proposed as a biomarker of MPS IVA: low levels are observed in more severe phenotypes and higher levels in attenuated forms [45,46]. However, enzymatic activity cannot be used as a biomarker to evaluate the therapeutic efficacy of ERT.
Other classical biomarkers in MPS IVA include levels of glycosaminoglycan (GAG). One such example is KS, which can be easily measured in blood and urine samples [3,45]. However, KS levels decrease with age and can be normalized in older patients with MPS IVA, especially after 12 years of age when the growth plate is entirely closed or destroyed [47,48]. C6S is another GAG that accumulates in MPS IVA, but is not widely used as a biomarker as it can be masked by other GAGs that appear in the same position in the MS/MS analysis spectrum [47]. The identification of definitive biomarkers of bone and cartilage disease in MPS IVA remains an unmet challenge, and is essential to monitor disease progression and treatment response.
Until now, no biomarker has been identified that can adequately reflect bone and cartilage pathology MPS IVA patients of all ages and at all disease stages. Detection of proteins that are dysregulated in MPS IVA constitutes a significant advance in our understanding of the mechanism underlying the disease. Using a proteomics-based approach, we have identified biomarkers with potential diagnostic and prognostic utility that are expressed in leukocytes in MPS IVA patients.
Previous reports have described the relationship between lysosomes with other organelles such as the transGolgi reticulum, mitochondrion, vesicles, and cytoskeleton [49,50,51,52,53]. Lysosomal activity is regulated by the activation of mTORC1 and CLEAR promotors [49]. The lysosome requires the cellular cytoskeleton in order to move and maintain its membrane structure. The main cellular impairment found in lysosomal disorders is the storage of undegraded substrates. This abnormal accumulation leads to alterations in proteins that participate in the interconnection between organelles. Ubiquitin proteins [54] and cholesterol [55] play important roles in this process; their principal function is the degradation or elimination of components and the biosynthesis of new ones [56]. Undegraded substrates can also modulate the function and location of cell receptors such as Toll-like receptors [57], activation of this receptor by ligands as AMP-activated protein kinase [58], It can reduce activity mTOR affection (this effect reduced the activation CLEAR promotors) [59] and insulin signaling [60], leading to cellular damage.
Using qualitative and quantitative proteomic methods to analyze proteins in leukocytes from MPS IV patients, we identified proteins that show altered expression relative to healthy controls, and then examined changes in their expression MPS IV patients that received ERT. Qualitative studies revealed that ERT resulted in normalization of dysregulated proteins in all parts of the cell. However, quantitative analyses showed only partial restoration of the expression of proteins involved in pyruvate metabolism, the cytoskeleton, vesicle trafficking, the mitochondrion, the Golgi-lysosome interaction, and repair of the lysosomal membrane, and no restorative effect on proteins involved in iron transport. Analysis of proteins involved in DNA binding showed that ERT resulted in partial normalization or had no effect. Interestingly, the inflammation pathway was activated only in samples from untreated MPS IV patients. In a previous study, we demonstrated qualitative and quantitative changes in proteins expressed by fibroblasts from MPS IVA patients following ERT and encapsulated ERT in nanoparticles [61].
The protein biomarker candidates identified in our quantitative analysis were TRFL, CORO1A, GANAB, and VTNC. In MPS IVA cellular inflammatory processes are affected. We demonstrated activation of inflammation factors in samples from untreated MPS IVA patients. Oxidative stress is caused by the accumulation of substrates in lysosomes. Therefore, the combination of anti-oxidants with ERT treatment can improve therapeutic efficacy [62]. We found that TRFL was upregulated in untreated MPS IVA patients compared with healthy controls, and that this effect was corrected after ERT. However, TRFL is easily dysregulated, possibly due to a lack of enzyme before the next dose of ERT is weekly administered. TRFL is transferred during lactation from mothers to infants, helping to improve the infant’s immune system, and exerts immune regulatory functions, decreasing the release of interleukin-1 (IL-1), IL-2, IL-6, IL-12, and tumor necrosis factor-α (TNF-α), and enhancing the cytotoxicity of natural killer cells and monocytes [63]. This protein is also implicated in iron metabolism [64] and bone regeneration [65]. In MPS IVA, the constant activation of this protein may be linked to more severe disease [66].
CORO1A is another protein that was downregulated in untreated MPS IVA patients compared with healthy controls, and was partially normalized after ERT. CORO1A regulates actin cytoskeleton-dependent processes (cytokinesis), cell polarization, migration, and phagocytosis, and plays an important role in Ca2+ signaling in macrophages [67]. These effects could correct the pro-inflammatory processes that occur in MPS IVA. In bone, CORO1A regulates cathepsin k [66,67,68,69] and exerts significant effects on bone resorption through degradation of bone-matrix proteins and type I and type II collagen [70]. The third protein identified that may serve as a biomarker in MPSIVA was GANAB. Although not well described, GANAB has one catalytic subunit of glucosidase II that sequentially cleaves 2 alpha-1,3-linked glucose residues from the Glc2Man9GlcNAc2 oligosaccharide, which in turn is a precursor of immature glycoproteins and participates in the N-glycan metabolic pathway [71]. VTNC is a glycoprotein predominantly produced by the liver, and expressed in the blood and ECM. VTNC, which binds to GAGs, collagen, plasminogen, and the urokinase-receptor, participates in stabilization of the inhibitory conformation of plasminogen activation inhibitor-1, and in the ECM can potentially regulate proteolytic degradation of this matrix. VTNC also participates in homeostatic processes, binding to complement, heparin, and thrombin–antithrombin III complexes, and exerts effects on the immune response. This protein can modulate multiple biological functions, influencing proteolytic enzyme activity and modulating protein kinases. In addition, the presence of the sequence RGD (Arg-Gly-Asp) in VTNC allows it to bind to the integrin receptor VnR (αvβ3) and modulate cell attachment [72]. αvβ3 is found in many cell types, including endothelial cells, chondrocytes, fibroblasts, monocytes, and activated blymphocytes [73]. In bone, VTNC is present in the bone matrix at low levels and at higher levels in the unmineralized osteoid, and participates in bone regeneration and mineralization. VTNC is degraded by the matrix metalloproteinases (MMP) collagenase-1 (MMP-1), gelatinase A (MMP-2), matrilysin (MMP-7), metalloelastase (MMP-12), and MT1-MMP (MMP-14) [74].
Given their involvement in bone metabolism, we consider TRFL, CORO1A, GANAB and VTNC to be candidate biomarkers of bone impairment in MPS IVA. We postulate that these proteins expressed in leukocytes may also be expressed in bone cells, given that macrophages and osteoclasts originate from the same cell line and may share similar proteins [65]. In a previous proteomic analysis of fibroblasts, we observed upregulation of TRFL in untreated MPS IVA patients and upregulation of GANAB in ERT-treated versus untreated MPS IVA patients [61].
One protein that was downregulated in MPS IVA patients that received ERT was RNAS2. This specific pyrimidine nuclease shows a slight preference for cytotoxin and helminthotoxin, is located in the lysosome, and is described as a chemotactic factor for dendritic cells. Several other proteins showed partial or complete normalization of expression after ERT, including proteins implicated in the pyruvate metabolic pathway (LDHA, LDHB) and in cytoskeletal organization (MOES) [61]. Inflammation-associated proteins that were dysregulated in untreated patients included OLFM4, TGFB1, THAS, PGH1, CAP7, andCHIT1 [70,75]. PRTN3, which is involved in collagen I and II degradation, was also dysregulated in untreated patients, in line with the well described impairment of collagen I and II biosynthesis and catabolism in MPS IVA [76,77].
A qualitative study conducted using the Funrich program produced similar results to our quantitative analysis in terms of ERT-mediated normalization of dysregulated protein expression. While the quantitative study allowed precise quantification of proteins whose expression was normalized after ERT, the qualitative study gives us only an identification of proteins expressed in all conditions combining these two approaches allowed us to confirm the effect of ERT on the expression of dysregulated proteins in MPS IVA [76,77].

3.1. Limitations of the Study

In our cohort we identified and analyzed 690 proteins with 99% reliability. The SWATH method is a specific, reproducible, and sensitive approach, allowing relative or absolute protein quantification. However, some limitations of this approach should be noted. First, the number of proteins identified/quantified is largely limited by the composition of the spectral library. In this study, the library was generated with a pool of proteins for each condition, and consisted of a total of 690 proteins, all with a FDR < 1%. In contrast to the selected reaction monitoring (SRM) technique, in which only three transitions are quantified, in the SWATH technique, seven transitions are quantified for each peptide. Therefore, 10 peptides per protein must be identified in order to extract the peak areas necessary for quantification. Despite the precision of this technique, this also constitutes a limitation, as proteins in the library for which less than 10 peptides are identified will not be quantified. Due to this limitation, the SWATH method may be unable to detect collagens, pro-inflammatory factors and lysosomal enzymes that degrade substrates in the lysosome. Interestingly, our analysis detected TRFL, which modulates interleukins, and PRTN3, which degrades collagen, but failed to detect any collagens, interleukins, or lysosomal enzymes.
Another limitation of our study is that normalization of protein expression in leukocytes does not necessarily correlate with normalization in chondrocytes in the avascular region. The enzyme is easily taken up by the leukocytes, restoring the function of dysregulated metabolic pathways in these cells while the infused enzyme circulates in the blood. It is critical to understand whether these proteins are dysregulated in bone and cartilage in MPS IVA patients in order to identify potential diagnostic biomarkers of disease severity. When a bone-penetrating drug becomes available, surrogate biomarkers will be essential.

3.2. Conclusions

Lysosomal disorders are characterized by significant alterations in proteins caused by the accumulation of undegraded substrate. We have identified a large set of proteins that are dysregulated in leukocytes from untreated MPS IVA patients, and many of which are fully or partially normalized following ERT. Several of these proteins are implicated in bone metabolism and are therefore potential biomarkers of the severity of bone disease in MPS IVA. These candidate proteins should be investigated in bone and cartilage specimens in MPS IVA patients to determine the extent to which they truly reflect bone pathology.

4. Materials and Methods

4.1. Study Work Flow

The graphic below outlines the workflow used to identify dysregulated proteins in leukocytes. Analyses consisted of both qualitative (LC-MS/MS) and quantitative (SWATH-MS) proteomic methods (Figure 9).
Blood samples were collected from 3 groups of participants: untreated MPS IVA patients; ERT-treated MPS IVA patients (sampled before ERT and 1day after), and healthy controls. Blood samples were separated into plasma and leukocytes. The leukocytes were lysed, and proteomic analyses performed. The workflow in Figure 9 depicts the qualitative analysis (left), which identified proteins expressed in leukocytes, and the quantitative analysis (right), which determined the number of specific proteins expressed in leukocytes. After these two distinct proteomics approaches, bioinformatics analyses were performed to obtain more information about the identified/quantified proteins.

4.2. Samples

Cell samples for proteomic analyses were obtained from MPS IVA patients in 3 hospitals in Spain after receiving informed consent: 8 untreated patients and 5 patients who underwent weekly ERT. In the ERT group, blood samples were obtained before (ERT-a) and 24 h after (ERT-b) treatment. All patients presented the classical MPS IVA phenotype. For the control group, blood samples were obtained from 6 healthy donors.

4.3. Protein Extraction

Leukocytes were sonicated to rupture the membrane and release proteins, and then centrifuged for 10 min at 10,000× rpm and 4 °C. Protein extracts were recovered from the supernatant and subsequently frozen at −20 °C.

4.4. Enzyme Activity Test

An enzyme activity test was used to analyze GALNS enzymatic activity in samples [78]. Results are shown in Table 7 (physiologicalrange, 1.8–20.0 nM/h/mg).

4.5. Proteomic Analysis

Protein identification and quantification were performed as described in bibliography [61,79,80,81,82]. For protein identification, digested peptides from each sample were separated using reverse phase chromatography. The gradient was developed using a micro liquid chromatography system (Eksigent Technologies nanoLC 400, Sciex, Redwood City, CA, USA) coupled to a high-speed Triple TOF 6600 mass spectrometer (Sciex, Redwood City, CA, USA) with a microflow source. The analytical column used was a Chrom XP C18 silica-based reversed-phase column (150 × 0.30 mm) with a 3mm particle size and 120Å pore size (Eksigent, Sciex Redwood City, CA, USA). The trap column was a YMC-TRIART C18 (YMC Technologies Teknokroma Analítica, Barcelona, Spain), with a 3mm particle size and 120Å pore size, that was switched on-line with the analytical column. Data were acquired with a TripleTOF 6600 System (Sciex, Redwood City, CA, USA) using a data-dependent workflow (DDA).
For the SWATH analysis a spectral library was created using pooled samples from each group (healthy controls, untreated patients, and the ERT-a and ERT-b groups) using a DDA. Next, peak extraction was performed using the MS/MSALL add-in for PeakView Software (v. 2.2., Sciex, Redwood City, CA, USA) with the SWATH Acquisition MicroApp (v. 2.0., Sciex, Redwood City, CA, USA). Only peptides with a confidence score > 99% (as obtained from a Protein Pilot database search) were included in the spectral library.
SWATH–MS acquisition was performed on a TripleTOF® 6600 LC-MS/MS system (Sciex, Redwood City, CA, USA). Samples from each group were analyzed using the data-independent acquisition (DIA) method. Targeted data extraction of the fragment ion chromatogram traces from the SWATH runs was performed in PeakView (v. 2.2) using the SWATH Acquisition MicroApp (v. 2.0). The integrated peak areas (processed mrkvw files from PeakView) were directly exported to MarkerView software (Sciex, Redwood City, CA, USA) for relative quantitative analysis.
Unsupervised multivariate statistical analysis using principal component analysis (PCA) was performed to compare data across the samples using a range scale. The average MS peak area for each protein was derived from the biological replicates of the SWATH-MS of each sample, followed by analysis using a Student’s t-test (MarkerView software, sciex, Redwood City, CA, USA) to compare between samples based on the averaged total area of all transitions for each protein. The t-test result (p-value) indicates how well each variable distinguishes the two groups. Candidate proteins were selected for each library based on t-test results (p-value < 0.05 and FC (increase or decrease) > 1.4).
Functional analysis was performed by FunRich (Functional Enrichment analysis tool) open-access software for functional enrichment and interaction network analysis (http://funrich.org/index.html).Reactome (https://reactome.org). STRING (https://string-db.org).PANTHER (http://pantherdb.org).

Supplementary Materials

The following are available online at https://www.mdpi.com/1422-0067/22/1/226/s1.

Author Contributions

Contributions were provided by the authors in the statements: conceptualization, V.J.Á., S.B.B. and M.L.C.; methodology, S.B.B., V.J.Á., M.P.C.-V. and C.C.; validation, V.J.Á. and S.B.B.; sample collection. I.V., M.J.D.C. and M.M.; formal analysis, V.J.Á., S.B.B. and C.C.; writing—original draft preparation, V.J.Á., S.B.B.; writing—review and editing, M.L.C., S.T.; visualization, S.B.B.; supervision, M.L.C., F.J.O.-E. and S.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was approved by the local Ethics Committee of Santiago-Lugo (data approval 22 May 2017 Reference number 2017/298).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available in this article and this Supplementary Material.

Acknowledgments

We acknowledge to the patients and controls for allowing us to collect and analyze the samples.

Conflicts of Interest

The authors have no conflicts of interest to declare.

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Figure 1. Venn diagram showing the distribution of proteins in the 4 study groups. Abbreviations: CG: control group; ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion; UG: untreated group.
Figure 1. Venn diagram showing the distribution of proteins in the 4 study groups. Abbreviations: CG: control group; ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion; UG: untreated group.
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Figure 2. Functional analysis using the FunRich program. This figure shows the changes in the relative percentages of leukocyte proteins expressed in the endosome, different parts of the lysosome, the mitochondria, and the vesicles in each of the 4 groups. Abbreviations: CG: control group; ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion; UG: untreated group.
Figure 2. Functional analysis using the FunRich program. This figure shows the changes in the relative percentages of leukocyte proteins expressed in the endosome, different parts of the lysosome, the mitochondria, and the vesicles in each of the 4 groups. Abbreviations: CG: control group; ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion; UG: untreated group.
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Figure 3. Venn diagram showing the distribution of leukocyte proteins that were downregulated the untreated, ERT-a, and ERT-b groups relative to healthy controls. Abbreviations: CG, control group; UG, untreated group; ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion.
Figure 3. Venn diagram showing the distribution of leukocyte proteins that were downregulated the untreated, ERT-a, and ERT-b groups relative to healthy controls. Abbreviations: CG, control group; UG, untreated group; ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion.
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Figure 4. String network analysis. (A) Proteins downregulated in untreated MPS IVA patients. (B) Proteins (n = 32) that remain dysregulated or partially dysregulated in ERT-treated MPS IVA patients. Abbreviations: MPS IVA, Mucopolysaccharidosis type IVA; ERT, enzyme replacement therapy.
Figure 4. String network analysis. (A) Proteins downregulated in untreated MPS IVA patients. (B) Proteins (n = 32) that remain dysregulated or partially dysregulated in ERT-treated MPS IVA patients. Abbreviations: MPS IVA, Mucopolysaccharidosis type IVA; ERT, enzyme replacement therapy.
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Figure 5. STRING analysis of the CORO1A interactome. Interactions among proteins found CORO1A and OSTF1, where participated ARP family proteins.
Figure 5. STRING analysis of the CORO1A interactome. Interactions among proteins found CORO1A and OSTF1, where participated ARP family proteins.
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Figure 6. Changes in the levels of CORO1A and GANAB proteins in the different groups analyzed. Each point represents the mean value of the protein area for an individual sample in each group. The bottom and top of each box represent the first and third quartiles, respectively. The whiskers represent the minimum and maximum values within 1.5 times the interquartile range. Any data points not included between the whiskers are considered outliers. * p < 0.05; ** p < 0.01. Abbreviations: CG, control group; ERT-a: ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion; UG: untreated group.
Figure 6. Changes in the levels of CORO1A and GANAB proteins in the different groups analyzed. Each point represents the mean value of the protein area for an individual sample in each group. The bottom and top of each box represent the first and third quartiles, respectively. The whiskers represent the minimum and maximum values within 1.5 times the interquartile range. Any data points not included between the whiskers are considered outliers. * p < 0.05; ** p < 0.01. Abbreviations: CG, control group; ERT-a: ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion; UG: untreated group.
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Figure 7. Venn diagram showing the distribution of leukocyte proteins that were the healthy control. Abbreviations: CG, control group; UG, untreated group; ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion.
Figure 7. Venn diagram showing the distribution of leukocyte proteins that were the healthy control. Abbreviations: CG, control group; UG, untreated group; ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion.
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Figure 8. Variations in the levels of TRFL and VTNC proteins in the different groups analyzed. Each point represents the mean value of the protein area for an individual sample in each group. The bottom and top of each box represent the first and third quartiles, respectively. The whiskers represent the minimum and maximum values within 1.5 times the interquartile range. Any data points not included between the whiskers are considered outliers. * p < 0.05; *** p < 0.001. Abbreviations: CG, control group; ERT-a: ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion; TRFL, lactotransferrin; UG: untreated group; VTNC, vitronectin.
Figure 8. Variations in the levels of TRFL and VTNC proteins in the different groups analyzed. Each point represents the mean value of the protein area for an individual sample in each group. The bottom and top of each box represent the first and third quartiles, respectively. The whiskers represent the minimum and maximum values within 1.5 times the interquartile range. Any data points not included between the whiskers are considered outliers. * p < 0.05; *** p < 0.001. Abbreviations: CG, control group; ERT-a: ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion; TRFL, lactotransferrin; UG: untreated group; VTNC, vitronectin.
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Figure 9. Schematic illustrating the study workflow showing both qualitative (LC-MS/MS, left) and quantitative (SWATH-MS, right) proteomic methods.
Figure 9. Schematic illustrating the study workflow showing both qualitative (LC-MS/MS, left) and quantitative (SWATH-MS, right) proteomic methods.
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Table
Table 1. Demographics of MPS IVA patients.
Table 1. Demographics of MPS IVA patients.
Patient
ID		SexAge at Diagnosis
(y)		ERTAge at Start of Treatment
(y)		Current Characteristics
Age
(y)		Height
(cm)		6 Minute Walk Test (m)FVC
(mL)		FEV1
(mL)
1F1No-3198250600500
2M2No-31113305870700
3M2No-2195ND *380260
4M2No 4099ND *480360
5F4No-15103341920820
6F3No-2999ND *ND **ND **
7F1No-18119272110900
8MunknownNo-21103ND *920700
9M1Yes1216100105690450
10M2Yes26104450770720
11M3Yes1318113.547213901330
12M3Yes111911323413501160
13M5Yes1822110344870730
Patients 1 and 2 are twin brothers; patients 6 and 7 are brothers * patient cannot walk; ** patient undergoing ventilation with tracheostomy. Abbreviations: ERT, enzyme replacement therapy; F, female; FEV1, forced expiratory volume in 1 s; FVC, forced vital capacity; ID, identification, M, male; ND, not determined.
Table
Table 2. Number of proteins per sample and number of common proteins per group. Only proteins with FDR < 1% were selected.
Table 2. Number of proteins per sample and number of common proteins per group. Only proteins with FDR < 1% were selected.
Patients and Control Groups-Sample IDProteins Identified Per Sample (n)Proteins Identified in All or All but One Samples (n)
Untreated GroupUG 1460235
UG 2330
UG 3367
UG 4612
UG 5NA
UG 6NA
UG 7341
UG 8304
ERT-a GroupERT-a 1480301
ERT-a 2338
ERT-a 3369
ERT-a 4406
ERT-a 5400
ERT-b GroupERT-b 1492222
ERT-b 2190
ERT-b 3437
ERT-b 4252
ERT-b 5557
Healthy Control GroupCG 1144164
CG 2470
CG 3238
CG 4286
CG 5315
CG6261
Abbreviations: ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion; NA, not analyzed (due to very low quantity of leukocytes).
Table
Table 3. Dysregulated proteins in leukocyte samples from MPSIVA patients. Proteins considered dysregulated are those with a p-value < 0.05 and a fold change (FC) > 1.4.
Table 3. Dysregulated proteins in leukocyte samples from MPSIVA patients. Proteins considered dysregulated are those with a p-value < 0.05 and a fold change (FC) > 1.4.
ComparisonProteins Downregulated Compared with ControlsProteins Upregulated Compared with Controls
Control vs. Untreated9173
Control vs. ERT-a6455
Control vs. ERT-b4956
Comparison Proteins down regulated compared with untreated groupProteins upregulated compared with untreated group
Untreated vs. ERT-a2210
Untreated vs. ERT-b1023
Comparison Proteins down regulated compared with ERT-a groupProteins upregulated compared with ERT-b group
ERT-a vs. ERT-b412
Abbreviations: ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion.
Table
Table 4. Downregulated proteins in untreated and ERT-treated MPS IVA patients (ERT-a, ERT-b) with respect to healthy controls. Proteins considered dysregulated are those with a p-value < 0.05 and a fold change (FC) > 1.4.
Table 4. Downregulated proteins in untreated and ERT-treated MPS IVA patients (ERT-a, ERT-b) with respect to healthy controls. Proteins considered dysregulated are those with a p-value < 0.05 and a fold change (FC) > 1.4.
UniProt CodeUniProt NameProtein NameFold Change Relative to Healthy Controls
UntreatedERT-aERT-b
P14618KPYMPyruvate kinase PKM0.05370.07700.1210
P04406G3PGlyceraldehyde-3-phosphate dehydrogenase0.05390.07290.0632
P00338LDHAl-lactate dehydrogenase A chain0.06290.10390.1176
P00558PGK1Phosphoglycerate kinase 10.09020.11240.1742
P07195LDHBl-lactate dehydrogenase B chain0.22610.20490.2358
P11177ODPBPyruvate dehydrogenase E1 component subunit beta. mitochondrial0.30050.25200.3246
P04075ALDOAFructose-bisphosphatealdolase A0.40120.59570.6128
P06744G6PIGlucose-6-phosphate isomerase0.16450.34010.3358
P36871PGM1Phosphoglucomutase-10.32840.25240.5816
P11413G6PDGlucose-6-phosphate 1-dehydrogenase0.39510.45850.5714
P26038MOESMoesin0.12820.12840.2848
P60981DESTDestrin0.36040.27560.4310
O15145ARPC3Actin-related protein 2/3 complex subunit 30.50940.44800.5276
P31146CORO1ACoronin-1A0.12830.14180.2020
P09493TPM1Tropomyosin alpha-1 chain0.29970.65170.7882
P35527K1C9Keratin. type I cytoskeletal 90.30190.59490.6857
P35908K22EKeratin. type II cytoskeletal 2 epidermal0.29400.61490.8652
O15143ARC1BActin-related protein 2/3 complex subunit 1B0.31320.44720.4072
P04264K2C1Keratin. type II cytoskeletal 10.33010.60550.7358
P02538K2C6AKeratin. type II cytoskeletal 6A0.43521.09182.2909
P67936TPM4Tropomyosin alpha-4 chain0.46020.87770.5522
P02533K1C14Keratin. type I cytoskeletal 140.51860.83160.7752
P61160ARP2Actin-related protein 20.36080.33150.3566
O15511ARPC5Actin-related protein 2/3 complex subunit 50.40500.52060.4899
P60709ACTBActin. cytoplasmic 10.30100.21640.2500
Q99439CNN2Calponin-20.56531.21210.9130
P35612ADDBBeta-adducin0.45050.53560.7874
Q13813SPTN1Spectrin alpha chain. non-erythrocytic 10.62230.95010.9308
P50552VASPVasodilator-stimulated phosphoprotein0.48090.72580.6589
O75083WDR1WD repeat-containing protein 10.60810.50590.4914
Q16181SEPT7Septin-70.39980.25070.3119
P17931LEG3Galectin-30.39030.49690.6100
Q96QK1VPS35Vacuolar protein sorting-associated protein 350.40530.34530.7819
Q15833STXB2Syntaxin-binding protein 20.40430.53820.6145
P68036UB2L3Ubiquitin-conjugating enzyme E2 L30.36960.63360.5254
P30040ERP29Endoplasmic reticulum resident protein 290.57510.82060.6180
Q13492PICALPhosphatidylinositol-binding clathrin assembly protein0.62980.64270.6980
P30049ATPDATP synthasesubunit delta. mitochondrial0.59060.86450.9240
P25705ATPAATP synthasesubunit alpha. mitochondrial0.30600.27760.5251
O75390CISYCitrate synthase. mitochondrial0.67940.58430.6636
P30044PRDX5Peroxiredoxin-5. mitochondrial0.44860.60430.5455
P06576ATPBATP synthase subunit beta. mitochondrial0.48900.74800.7076
Q99798ACONAconitatehydratase. mitochondrial0.51000.41290.6735
P13804ETFAElectron transfer flavoprotein subunit alpha. mitochondrial0.24720.15650.1542
P10809CH6060 kDa heat shock protein. mitochondrial0.19050.47080.3593
P61604CH1010 kDa heat shock protein. mitochondrial0.37790.35370.3176
P00505AATMAspartate aminotransferase. mitochondrial0.56930.42550.3930
P40926MDHMMalate dehydrogenase. mitochondrial0.66690.53970.6540
P69905HBAHemoglobin subunit alpha0.27720.63110.4201
P68871HBBHemoglobin subunit beta0.20630.66780.3896
P55072TERATransitional endoplasmic reticulum ATPase0.23470.19770.3911
Q14697GANABNeutral alpha-glucosidase AB0.54540.43640.4613
P08133ANXA6Annexin A60.48990.70860.9723
P09525ANXA4Annexin A40.46460.68250.7587
P04083ANXA1Annexin A10.20100.56500.6752
P522096PGD6-phosphogluconate dehydrogenase decarboxylating0.11360.15700.2218
P05089ARGI1Arginase-10.28340.40690.4421
P29401TKTTransketolase0.34320.33580.2993
Q16762THTRThiosulfate sulfurtransferase0.49240.78560.8081
P30566PUR8Adenylosuccinatelyase0.23640.13610.7371
Q00013EM5555 kDa erythrocyte membrane protein0.44140.42750.6262
P02766TTHYTransthyretin0.48080.41670.5573
Q9H2U2IPYR2Inorganic pyrophosphatase2.mitochondrial0.55330.66670.7373
Q7L5Y6DET1DET1 homolog0.35180.56130.6315
P19971TYPHThymidine phosphorylase0.25210.27060.4983
P00488F13ACoagulation factor XIII A chain0.29920.30870.3043
P06737PYGLGlycogen phosphorylase. liver form0.11670.14410.2094
P62136PP1ASerine/threonine-protein phosphatase PP1-alpha catalytic subunit0.56900.45780.5951
P30101PDIA3Protein disulfide-isomerase A30.55981.00881.1788
P55786PSAPuromycin-sensitive aminopeptidase0.43890.62560.6560
P07741APTAdenine phosphoribosyltransferase0.26590.25160.3201
Q06323PSME1Proteasome activator complexsubunit 10.30350.47440.4342
P08571CD14Monocyte differentiation antigen CD140.44340.35941.0551
P02652APOA2Apolipoprotein A-II0.36960.29740.8084
P30086PEBP1Phosphatidylethanolamine-binding protein 10.53240.63530.8049
P17612KAPCAcAMP-dependent protein kinase catalytic subunit alpha0.29210.28310.4253
P01860IGHG3Immunoglobulin heavy constant gamma 30.51320.49990.4892
Q5VTE0EF1A3Putative elongation factor 1-alpha-like 30.34660.36860.4249
Q9NTK5OLA1Obg-like ATPase 10.10990.34310.2186
P62826RANGTP-binding nuclear protein Ran0.12770.11780.3363
O00299CLIC1Chloride intracellular channel protein 10.25410.48000.6103
P38606VATAV-type proton ATPase catalytic subunit A0.33860.40630.3411
P31948STIP1Stress-induced-phosphoprotein 10.30710.59920.5741
Q15366PCBP2Poly(rC)-binding protein 20.45840.32820.4541
P61978HNRPKHeterogeneous nuclear ribonucleoprotein K0.50870.58070.6304
P09651ROA1Heterogeneous nuclear ribonucleoprotein A10.57980.61740.6532
P26583HMGB2High mobility group protein B20.18730.41590.6264
P16402H13Histone H1.30.07610.28830.2277
P16401H15Histone H1.50.08960.73841.0462
P40199CEAM6Carcinoembryonic antigen-related cell adhesion molecule 60.25370.49840.7378
Q92882OSTF1Osteoclast-stimulating factor 10.29630.62960.9094
Fold-change values in red indicate proteins that were not significantly dysregulated compared with healthy controls (p > 0.05). For more details, Supplementary Table S3. Protein related to metabolic pathway of pyruvate is shown in grey, glucose metabolism in green, cytoskeleton organization in clear gray, lysosome membranes reparation in blue, vesicle traffic and vesicle fusion in dark blue, oxygen transport in dark pink, mitochondrial organelle in pink, N-glycan metabolism pathway in yellow, DNA binding in clear orange, metabolite interconversion activity in dark green, metabolic and cellular process in dark orange, catalytic activity or proteins related to transport in purple and other proteins in white.
Table
Table 5. Proteins upregulated in untreated and ERT-treated MPS IVA patients relative to healthy controls. Proteins considered dysregulated are those with a p-value < 0.05 and a fold change (FC) > 1.4.
Table 5. Proteins upregulated in untreated and ERT-treated MPS IVA patients relative to healthy controls. Proteins considered dysregulated are those with a p-value < 0.05 and a fold change (FC) > 1.4.
UniProt CodeUniProt NameProtein NameFold change Relative to Healthy Controls
Untreated ERT-a ERT-b
P30405PPIFPeptidyl-prolylcis-transisomerase F. mitochondrial1.86560.97641.2728
P62318SMD3Small nuclear ribonucleoproteinSm D32.11121.82271.5860
Q9H4B7TBB1Tubulin beta-1 chain2.67651.44121.5400
P61224RAP1BRas-related protein Rap-1b2.80331.21821.1940
P14780MMP9Matrix metalloproteinase-93.10511.77321.5370
P08567PLEKPleckstrin1.46691.04821.0934
Q6DRA6H2B2DPutative histone H2B type 2-D8.32082.31691.3557
Q9BTM1H2AJHistone H2A.J8.82932.31971.3487
Q99879H2B1MHistone H2B type 1-M9.98912.11371.4663
P62805H4Histone H412.00443.08222.1018
Q6UX71PXDC2Plexin domain-containing protein 22.09051.02931.0988
Q8WWA1TMM40Transmembrane protein 404.95071.57211.2002
P62314SMD1Small nuclear ribonucleo protein Sm D12.35891.94951.7400
P20338RAB4ARas -related protein Rab-4A1.53222.14341.0633
Q96P48ARAP1Arf-GAP with Rho-GAP domain. ANK repeat and PH domain-containing protein 12.0361.85591.3848
P01137TGFB1Transforming growth factor beta-1 proprotein2.3361.02451.2298
P05106ITB3Integrin beta-31.67771.06760.9028
P02775CXCL7Platelet basic protein3.16691.09471.0450
P41218MNDAMyeloid cell nuclear differentiation antigen3.26561.71160.7412
P02776PLF4Platelet factor 43.95961.36541.3027
P11234RALBRas-related protein Ral-B2.0041.11841.0789
P12838DEF4Neutrophil defensin 42.46082.37111.2386
P59666DEF3Neutrophil defensin 38.94843.72531.5188
O14773TPP1Tripeptidyl-peptidase 11.44411.14611.0245
Q8NBS9TXND5Thioredoxin domain-containing protein 51.57221.02671.2345
P24158PRTN3Myeloblastin2.01151.84801.4986
P50990TCPQT-complexprotein 1 subunittheta2.04161.21481.2408
P12724ECPEosinophil cationic protein2.41911.02590.5594
P17213BPIBactericidal permeability-increasing protein3.39661.56351.2036
P05164PERMMyeloperoxidase5.5112.01221.2871
P20160CAP7Azurocidin7.21032.04811.1568
Q13231CHIT1Chitotriosidase-12.14112.03081.7411
P00387NB5R3NADH-cytochrome b5 reductase 32.44631.79331.2666
P23229ITA6Integrin alpha-61.88541.09130.6926
P21926CD9CD9 antigen1.98641.00810.9969
Q9Y6C2EMIL1EMILIN-12.47651.15401.2063
P04004VTNCVitronectin4.03583.13894.1505
P07996TSP1Thrombospondin-12.03311.04551.0711
Q6UX06OLFM4Olfactomedin-42.81322.47172.1722
Q15084PDIA6Protein disulfide-isomerase A61.46351.03871.1286
P04839CY24BCytochrome b-245 heavy chain1.59461.64271.2274
Q9HDC9APMAPAdipocyte plasma membrane-associated protein1.6151.39201.3258
P61769B2MGBeta-2-microglobulin1.62241.10670.8221
P24557THASThromboxane-A synthase1.74771.63201.4601
P04844RPN2Dolichyl-diphospho-oligosaccharide—proteinglycosyltransferasesubunit 21.86421.36341.2661
Q9NQC3RTN4Reticulon-41.98671.53871.0570
Q14165MLECMalectin2.15861.08980.9708
Q9BSJ8ESYT1Extended synaptotagmin-12.46491.29701.2265
Q8TC12RDH11Retinol dehydrogenase 113.0611.34000.8831
P23219PGH1Prostaglandin G/H synthase 13.69291.56691.3489
P02774VTDBVitamin D-binding protein2.43271.48551.6653
P41240CSKTyrosine-protein kinase CSK3.42881.87393.5935
P02749APOHBeta-2-glycoprotein 15.3742.44363.0788
Q00325MPCPPhosphate carrier protein. mitochondrial2.27582.52521.3470
Q9UFN0NPS3AProteinNip Snap homolog 3ª1.64091.34361.3143
Q96P48ARAP1Arf-GAP with Rho-GAP domain. ANK repeat and PH domain-containing protein 12.0361.85591.3848
P20061TCO1Transcobalamin-11.78941.24421.2795
P80188NGALNeutrophil gelatinase-associated lipocalin1.9831.57981.2060
P08246ELNENeutrophil elastase2.94742.02150.9159
P00747PLMNPlasminogen3.33821.27311.4806
Q8NBM8PCYXLPrenylcysteine oxidase-like3.85141.06751.1120
P02788TRFLLactotransferrin7.67762.28621.4302
Q5SQ64LY66FLymphocyte antigen 6 complex locus protein G6f2.11071.37051.0059
P54108CRIS3Cysteine-rich secretory protein 31.71241.77091.2384
P54578UBP14Ubiquitin carboxyl-terminal hydrolase 141.69280.88511.3075
Q7L5Y6DET1DET1 homolog2.84290.62660.5570
P19971TYPHThymidine phosphorylase3.96743.69550.5058
P00488F13ACoagulation factor XIII A chain3.34213.23960.9832
P06737PYGLGlycogen phosphorylase. liver form8.57216.93740.5571
P62136PP1ASerine/threonine-protein phosphatase PP1-alpha catalytic subunit1.75762.18430.9561
P30101PDIA3Protein disulfide-isomerase A31.78640.55490.4749
P55786PSAPuromycin-sensitive aminopeptidase2.27830.70160.6691
P07741APTAdenine phosphoribosyltransferase3.76143.97420.8305
Q99623PHB2Prohibitin-21.76282.17711.6235
Fold-change values in red indicate proteins that were not significantly dysregulated compared with healthy controls (p > 0.05). Proteins involved in cellular components organization are shown in clear blue, proteins involved in the cellular response to the stimulus in clear green, components of lysosome in clear pink, extracellular matrix binding and cellular adhesion in orange, proteins involved in constitution and organelles function in purple, secretory granules in dark blue and other proteins involved in transport in dark green.
Table
Table 6. Proteins downregulated in ERT-treated versus untreated MPS IVA patients. Proteins considered dysregulated are those with a p-value < 0.05 and a fold change (FC) > 1.4.
Table 6. Proteins downregulated in ERT-treated versus untreated MPS IVA patients. Proteins considered dysregulated are those with a p-value < 0.05 and a fold change (FC) > 1.4.
UniProtCodeUniProt NameProtein NameCGFold Change Relative to Untreated Group
ERT-aERT-b
Q96AG4LRC59Leucine-rich repeat-containing protein 59ND0.56900.6684
Q12913PTPRJReceptor-type tyrosine-protein phosphatase etaND0.44560.5427
P10153RNAS2Non-secretory ribonucleaseND0.40250.1628
Q06323PSME1Proteasome activator complex subunit 1ND0.63980.6990
P27695APEX1DNA-(apurinic or apyrimidinic site) endonucleaseND0.79120.5368
P02042HBDHemoglobin subunit deltaND0.30310.5340
O43684BUB3Mitotic check point protein BUB3ND0.59460.4602
Q9Y2Y8PRG3Proteoglycan 3ND0.54160.3759
Fold-change values in red indicate proteins that were not significantly dysregulated because the p value was >0.05 (p > 0.05). Abbreviations: CG, control group; ERT-a: ERT-a, patients sampled before enzyme infusion; ERT-b, patients sampled 24 h after enzyme infusion; MPS IVA, Mucopolysaccharidosis type IVA; ND, not detected.
Table
Table 7. Enzymatic activity of GALNS.
Table 7. Enzymatic activity of GALNS.
UGEA
nM/h/mg		Before ERTEA
nM/h/mg		After ERTEA
nM/h/mg		Healthy ControlsEA
nM/h/mg
10.2ERT-a 10.7ERT-b 11.8CG 14.8
20.2ERT-a 20.6ERT-b 22.1CG 214.2
30.2ERT-a 30.7ERT-b 32.2CG 32.7
40.0ERT-a 41.0ERT-b 42.8CG 43.6
50.1ERT-a 51.6ERT-b 56.7CG 53.1
60.2----CG 64.8
70.1------
80.2------
EA, enzymatic activity; ERT, enzyme replacement therapy; ERT-a, MPS IVA patients sampled before ERT; ERT-b, MPS IVA patients sampled 24 h after ERT; UG, untreated group.
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Álvarez, V.J.; Bravo, S.B.; Chantada-Vazquez, M.P.; Colón, C.; De Castro, M.J.; Morales, M.; Vitoria, I.; Tomatsu, S.; Otero-Espinar, F.J.; Couce, M.L. Characterization of New Proteomic Biomarker Candidates in Mucopolysaccharidosis Type IVA. Int. J. Mol. Sci. 2021, 22, 226. https://doi.org/10.3390/ijms22010226

AMA Style

Álvarez VJ, Bravo SB, Chantada-Vazquez MP, Colón C, De Castro MJ, Morales M, Vitoria I, Tomatsu S, Otero-Espinar FJ, Couce ML. Characterization of New Proteomic Biomarker Candidates in Mucopolysaccharidosis Type IVA. International Journal of Molecular Sciences. 2021; 22(1):226. https://doi.org/10.3390/ijms22010226

Chicago/Turabian Style

Álvarez, Víctor J., Susana B. Bravo, Maria Pilar Chantada-Vazquez, Cristóbal Colón, María J. De Castro, Montserrat Morales, Isidro Vitoria, Shunji Tomatsu, Francisco J. Otero-Espinar, and María L. Couce. 2021. "Characterization of New Proteomic Biomarker Candidates in Mucopolysaccharidosis Type IVA" International Journal of Molecular Sciences 22, no. 1: 226. https://doi.org/10.3390/ijms22010226

APA Style

Álvarez, V. J., Bravo, S. B., Chantada-Vazquez, M. P., Colón, C., De Castro, M. J., Morales, M., Vitoria, I., Tomatsu, S., Otero-Espinar, F. J., & Couce, M. L. (2021). Characterization of New Proteomic Biomarker Candidates in Mucopolysaccharidosis Type IVA. International Journal of Molecular Sciences, 22(1), 226. https://doi.org/10.3390/ijms22010226

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