Abstract

   Extracorporeal shock wave lithotripsy (ESWL), although a highly
   effective method for the treatment of kidney stones, can cause
   significant kidney damage. Since urinary protein composition directly
   reflects kidney function, proteomic analysis of this fluid may be
   useful to identify changes in protein levels induced by patient
   exposure to ESWL as a sign of kidney damage. To this end, we collected
   urine samples from 80 patients with nephrolithiasis 2 h before and 24 h
   after exposure to ESWL, which were concentrated and subsequently
   processed with a commercially available enrichment method to extract
   low-abundance urinary proteins. These were then separated by 2D
   electrophoresis and subsequently analyzed by a proteomic approach. A
   large number of proteins were identified as being related to
   inflammatory, fibrotic, and antioxidant processes and changes in the
   levels of some of them were confirmed by Western blot analysis.
   Therefore, although further experimental confirmation is needed, our
   results demonstrate that ESWL significantly influences the low urinary
   protein profile of patients with nephrolithiasis. Notably, among the
   identified proteins, matrix metalloproteinase 7, alpha1-antitrypsin,
   and clusterin, as well as dimethyl arginine dimethyl amino hydrolase 2
   and ab-hydrolase, may play an important role as putative biomarkers in
   the monitoring and management of ESWL-induced renal damage.

1. Introduction

   Extracorporeal shock wave lithotripsy (ESWL) is the preferred and
   relatively non-invasive method for removing renal stones smaller than
   2–2.5 cm. Although it is well tolerated by patients and has a high
   success rate, concerns about its safety have arisen since its
   introduction in 1980. Indeed, several reports indicate morphological
   and functional changes in the kidney after ESWL [[46]1,[47]2,[48]3]. In
   particular, traumatic injury can be induced by the wave physical force,
   while ischemic/hypoxic renal damage is caused by renal vasoconstriction
   associated with tissue bleeding. Accordingly, this series of events can
   lead to acute kidney injury (AKI) [[49]4,[50]5]. For a long time, AKI
   has been diagnosed by measuring serum creatinine levels and more
   recently also by serum levels of plasma cystatin C and C-reactive
   protein [[51]6]. However, there is an increasing need to search for
   more sensitive biomarkers to detect post-ESWL renal injury [[52]7].

   Since the protein composition in urine directly reflects kidney
   functions, the use of urinary proteome may represent a powerful tool to
   identify possible biomarkers expressed during pathophysiological
   processes affecting the kidneys [[53]8,[54]9,[55]10]. Therefore,
   potential urinary biomarkers for the sensitive and specific detection
   of human AKI [[56]11] or the diagnosis of calcium-oxalate
   nephrolithiasis have been investigated [[57]12]. Urine proteome studies
   in former stone patients and stone-free controls have also been
   performed, leading to the identification of a number of proteins in the
   stone group that may serve as potential useful candidates for the
   diagnosis and treatment of urolithiasis [[58]13]. Unfortunately,
   reports regarding the pattern of human urinary proteins after ESWL
   exposure in nephrolithiasis patients are still modest. For example,
   some studies have reported that urinary levels of N-acetyl
   beta-glucosaminidase (NAG) and beta-galactosidase, as well as alpha1-
   and alpha2-macroglobulin, increase significantly after lithotripsy,
   suggesting that these proteins may be indicative of renal damage
   occurring after treatment, as reviewed in [[59]14]. However, the
   presence of highly abundant proteins in some biological fluids,
   including urine, may make it difficult to detect disease-associated
   markers, as they are frequently present in low amounts and most of them
   have a molecular weight <30 kDa. To overcome this obstacle, the removal
   of high-abundance urinary proteins (e.g., uromodulin, albumin, and
   immunoglobulin G) and different depletion strategies (e.g., various
   sorbents for the removal of unwanted proteins) have been proposed in
   recent years to improve the visibility of rarer species, followed by
   subsequent protein identification by two-dimensional electrophoresis
   (2DE) and mass spectrometry (MS) analysis [[60]15,[61]16]. Since, to
   the best of our knowledge, this type of investigation has not yet been
   performed with urine from patients exposed to ESWL, with the aim of
   identifying changes in the protein pattern induced by lithotripsy and,
   thereby, revealing promising biomarkers useful in the early detection
   of ESWL-induced renal damage, in this study, we examined the
   composition of low-abundance urinary proteins from patients with
   nephrolithiasis before (baseline) and 24 h after exposure to ESWL,
   taking a proteomic approach. Protein profile analysis clearly
   demonstrated that the ESWL technique caused significant differences in
   the urinary protein composition of these patients.

2. Materials and Methods

2.1. Patients

   Eighty patients with a proteinuria value less than 20 mg/mL were
   recruited for the present study. The validity of the sample number was
   verified using PASS 2005 software (Kaysville, UT, USA) with an
   alpha-type error of 5% and a beta-type error of 20%. We studied
   normotensive male patients (diastolic pressure less than 90 mm Hg), 41
   ± 4 years old, with renal stone/s less of than 2 cm. All patients were
   hospitalized during the study. Patients with a serum creatinine value
   greater than 120 µmol or exposed to anesthesia and/or antioxidant
   therapy, as well as those with diabetic nephropathy, obesity (BMI
   higher than 30 kg/m^2), coagulopathies, cancer, autoimmunity diseases,
   and uncompensated hypertension, were excluded from the study. The study
   protocol was approved by the Joint Ethic Committee of the G. D’Annunzio
   University of Chieti-Pescara-Local Health Authorithy 2 (ASL2) (No
   9_10072014). Informed consent was obtained from all patients during
   enrollment. Before starting treatment, patients underwent standard
   assessments of hematological and biochemical blood parameters, as well
   as abdominal computed tomography (CT) without a contrast medium.
   Routine laboratory analyses were performed using established
   techniques.

2.2. ESWL Procedure

   The ESWL procedure was performed as an outpatient procedure with the
   application of standard analgesia. All patients received a number of
   2000 shock waves in a single session for an average energy of 350 kJ,
   at 60 strokes/minute, using the Sonolith 4000 plus extracorporeal
   lithotripter (EDAP Technomed Italia, Rome, Italy).

2.3. Sample Preparation

   For each patient, 70–120 mL of urine was collected 2 h before and 24 h
   after ESWL treatment. After collection, each urine sample was adjusted
   to pH 7 with 1 M NaOH, then 1.5 mM NaN[3] and a protease inhibitor
   cocktail (GE Healthcare, Munich, Germany) were added to prevent
   bacterial growth and inhibit endogenous protease activity,
   respectively. Subsequently, samples were centrifuged at 4 °C for 30 min
   at 3000× g to remove cellular debris, salts, and contaminants.
   Supernatants were collected and desalted with the Amicon device with a
   cut off of 3 kDa (Merck Life Science, Milan, Italy), concentrated up to
   ten-fold, and then stored at -80 °C until use.

   To extract low-abundance proteins, an equalization protocol was applied
   to each sample using a commercially available enrichment method
   (ProteoMiner kit, Bio-Rad Laboratories, Segrate (MI), Italy) [[62]17].
   Proteins bound to the beads of the Proteominer kit were eluted using 9M
   urea followed by a chaotropic reagent mixture composed of 1.5M Trizma,
   2M urea, 7M thiourea, and 4%
   3-[(3-cholamidopropyl)dimethylammonium]-1-propanesulfonate (CHAPS,
   Sigma Italia, Opera, MI, Italy). Total protein concentration was
   estimated using a BCA protein assay (Pierce, ThermoFisher Scientific,
   Milan, Italy) according to the Bradford method [[63]18].

2.4. Two-Dimensional Analysis

   For the 2DE run, urine samples obtained from all 80 patients and
   enriched as described above were distributed into eight cohorts, each
   consisting of ten different samples, which were pooled to optimize the
   results. From each of the latter samples, 150 µg (for analytical gels)
   and 500 µg (for preparative gels) were used to perform the 2DE analysis
   according to the procedures described previously [[64]19]. For each
   cohort, 3 independent runs were performed. A reference gel was created
   for each cohort by matching the 2D maps of the 3 individual
   electrophoretic runs while a master gel was then prepared by matching
   all reference gels for both pre- and post-ESWL treatment (see
   [65]Supplementary Figure S1).

   A comparative proteomic analysis was performed on the latter using
   Image Master 2D platinum software (6.0 version) to determine the
   quantitative changes in protein expression after ESWL treatment.
   Briefly, after background subtraction, the intensity volume of each
   spot was normalized to the total intensity volume. Additionally,
   synthetic gels were created using Image Master 2D platinum software
   that included all common spots in the 2D map of each cohort (see Figure
   3). Changes in proteome expression resulting from the ESWL treatment of
   patients were more clearly revealed when comparing synthetic gels
   obtained from the urine of patients pre- and post-ESWL (as reported in
   Figure 4).

2.5. Protein Digestion and MALDI-TOF/TOF-MS Analysis

   All protein spots chosen for their significantly different intensity
   levels between the studied groups were excised from 2D gels and
   analyzed by the peptide mass finger printing (PMF) approach with an
   MALDI-TOF/TOF spectrometer. Protein spots were picked from the gel, and
   each of them was first washed with 100% ethanol and 100 mM ammonium
   bicarbonate (NH[4]HCO[3]) and then incubated at 56 °C in 100 µL of 50
   mM NH[4]HCO[3] supplemented with 10 mM dithiothreitol (DTT, 60 min) and
   immediately after at room temperature in 100 µL of 50 mM NH[4]HCO[3]
   plus iodoacetamide (30 min in the dark). Finally, the gel was incubated
   in 50 mM NH[4]HCO[3] containing trypsin at 37 °C overnight [[66]20].
   This peptide extract was applied to a C18ZipTip (Millipore, Bedford,
   MA, USA), rinsed (0.1% trifluoroacetic acid, TFA), and eluted directly
   onto the MALDI target in 0.5 μL of a saturated solution composed of
   1:1: α-cyano-4-hydroxycinnamic acid/0.1% TFA. MS analysis was performed
   using an Autoflex Speed mass spectrometer (Bruker Daltonics, Bremen,
   Germany), as previously described [[67]21]. A mixture of reference
   peptide fragments (i.e., bradykinin fragment 1–7, 757.39 m/z;
   angiotensin II 1046.54 m/z; ACTH fragment 18–39, 2465.19 m/z;
   GluFibrinopeptide B 1571.57 m/z; and porcine renin tetradecapeptide
   substrate 1760.02 m/z) was used for external high-precision calibration
   (HPC), while trypsin autodigestion products (843,50 m/z, 1.046,56 m/z,
   2.212,11 m/z, and 2.284,19 m/z) were used for internal mass
   calibration. Samples were also analyzed using LIFT MS/MS from the same
   target. The most abundant ions per sample were chosen for MS/MS
   analysis. Analyses were performed in positive LIFT reflectron mode
   [[68]22].

2.6. Database MS/MS Searching

   After MS acquisition, each spectrum obtained from PMF was searched in
   the NCBIn protein database by the Mascot search engine. Multiple
   parameters (e.g., PMF enzyme, trypsin; fixed modification,
   carbamidomethylation (Cys); variable modification, methionine
   oxidation; mass values, monoisotopic; ion charge state set to +1;
   maximum miscleavage set to 1; mass tolerance of 100 ppm for PMF and
   0.6–0.8 Da for MS/MS) were used in this search to compare the
   experimentally determined tryptic peptide masses with the theoretical
   peptide masses calculated for proteins from the database. Additionally,
   after the automated assessment of the search results, the samples were
   automatically submitted for LIFT TOF/TOF acquisition for the validation
   of the PMF data analysis. A maximum of four precursor ions per sample
   were chosen for MS/MS analysis. An additional protein database search,
   using combined PMF and MS/MS datasets, was performed using SwissProt
   database (SwissProt_2012_03.fasta) via BioTools 3.2 (Bruker Daltonik
   GmbH, Billerica, MA, USA) connected to the Mascot search engine. The
   Mowse probability score (the observed match between the experimental
   dataset and each sequence database entry is a chance event, p < 0.05)
   was used as a criterion for correct identification. Scores are reported
   as −10 Log[10](p), where p is the probability. The lowest probability
   corresponds to the highest score and is reported as the best match.
   Typically, this is a score of around 70 for PMF and 30–40 for MS/MS
   search.

2.7. Protein Validation by Western Blot Analysis

   Urine samples obtained as described in paragraph 2.2 were used. Protein
   samples (usually 50 μg), after dilution in sodium dodecyl sulfate
   (SDS)-bromophenol blue buffer, were boiled (5 min), run on 12% SDS
   polyacrylamide gels, and subsequently transferred on polyvinylidene
   fluoride (PVF) membranes, where they were blocked by a mixture
   containing PBS, 0.1%, Tween20, and 5% nonfat milk (Bio-Rad
   Laboratories) for 2 h at 4 °C. Then, these membranes were incubated
   (overnight, 4 °C) with primary polyclonal antibodies (rabbit
   anti-matrilysin, dilution 1:1000; rabbit anti-alpha1-antitrypsin,
   dilution 1:500; and goat anti-clusterin, dilution 1:1000, all purchased
   from Abcam, Cambridge, UK), and subsequently (1 h, room temperature)
   with goat anti-rabbit or rabbit anti-goat HPR-conjugated secondary
   antibody (final dilution 1:5000, Bethyl Laboratories Inc.; Montgomery,
   TX, USA). Immunocomplexes were visualized by chemiluminescence (ECL)
   detection system (GE Healthcare Life Sciences, Milan, Italy) and
   quantified by densitometric analysis (ImageJ software, 1.54k 15
   September 2024; U.S. National Institutes of Health, Bethesda, MD, USA).

2.8. Bioinformatic Analysis of Proteomic Data

   Protein ontology classification was performed by importing proteins for
   analysis via the Gene Ontology (GO) classification system
   ([69]http://www.expasy.org/). The identified proteins were analyzed and
   grouped based on their associated molecular functions and related
   pathways using the PANTHER database ([70]https://www.pantherdb.org).
   Furthermore, using the STRING software ([71]http://string-db.org/),
   chosen as the source for protein–protein interactions, the
   interconnections existing between most of them were highlighted by
   creating networks and forming clusters based on known direct and
   indirect interactions described in the literature. We also applied a
   pathway enrichment analysis to determine the different pathways of the
   proteins with statistical significance included in the networks
   identified by STRING analysis according to the KEGG (Kyoto Encyclopedia
   of Genes and Genomes) database. Data analysis was performed using the
   ShynyGO 0.82 workbench ([72]http://bioinformatics.sdstate.edu, accessed
   on 15 April 2025).

2.9. Statistical Analysis

   Reference gels and synthetic gels were used to assess the presence of,
   and difference in, protein levels. Background subtraction was
   performed, and the intensity volume of each spot was normalized by the
   total intensity volume (by adding the intensity volumes obtained from
   all spots within the same 2D gel). All quantitative data are reported
   as means ± SEM values. The intensity volumes of individual spots were
   matched between different gels and then compared between groups by
   multiple comparisons using one-way analysis of variance (ANOVA). A p <
   0.001 was considered statistically significant. Significantly different
   protein spots were subjected to in-gel tryptic digestion and MS
   identification. Additionally, statistical comparisons between values
   from different treatments in the same model were calculated using
   Student’s t-test for unpaired data by GraphPad Prism software (version
   6.0). p-values were corrected for multiple comparisons where
   appropriate.

3. Results

3.1. Urine Sample Collection and Removal of High-Abundance Proteins

   Urine was obtained from enrolled patients 2 h before and 24 h after
   their exposure to ESWL. Before starting the proteomic analyses,
   collected samples were concentrated up to ten-fold, since protein
   concentration is usually low in normal urine, and then subjected to the
   Proteominer protein enrichment kit to optimize the samples, thus
   excluding the interference with those proteins that are normally
   present in abundance in urine [[73]23]. The fractions eluted by
   Proteominer were distributed in eight different cohorts, each formed by
   pooling the urine of ten patients. This passage was crucial to obtain a
   higher protein concentration and to reduce the heterogeneity of urinary
   samples.

3.2. Urine Proteomic Analyses

   As anticipated in the Methods section, representative urinary master
   gels were obtained for each examined condition, pre- and post-ESWL, by
   combining the 2D gel electrophoresis maps of each cohort ([74]Figure
   S1). Representative 2D master gels resolved 945 ± 65 spots and 1106 ±
   130 spots for pre- and post-ESWL, respectively, allocated in the pH
   range 4–7 and a molecular mass ranging from 10 to 180 kDa.

   The comparison of these representative master gels and MS analysis
   ([75]Figure 1 and [76]Figure 2) allowed us to identify one protein
   exclusively present in pre-ESWL urine, namely,
   abhydrolase domain-containing 14B (ABHEB, also known as putative
   protein-lysine deacylase ABHD14B), while twenty-four proteins were
   detected in both pre- and post-ESWL urine samples, although they were
   differentially regulated, as reported in [77]Table 1 (see below).
   Indeed, in post-ESWL samples, most of the identified proteins were
   upregulated, while six were downregulated (DDAH2, ACTG1, UBQL4, C3,
   DC1L1, and FIBG) compared to the protein levels found in pre-ESWL urine
   (for example only, see [78]Figure 1b). Among the upregulated proteins,
   three were present as isoforms of the same protein, namely, A1AT, APOE,
   and APOA4.

Figure 1.

   [79]Figure 1
   [80]Open in a new tab

   Reference map of the urinary proteome annotating 24 proteins identified
   by mass spectrometry, whose levels were increased in urine samples from
   patients 2 h before ((a) left panel) and 24 h after their exposure to
   ESWL ((b) right panel).

Figure 2.

   [81]Figure 2
   [82]Open in a new tab

   Examples of some proteins whose content was modified by the exposure of
   patients to ESWL (post-ESWL) compared to the pre-exposure condition
   (pre-ESWL), as identified by 2DE electrophoresis and subsequent MS
   analysis. Black arrows indicate the spots of the same protein in pre-
   and post-ESWL urine. On the left of each panel, the peaks of each
   protein measured in MS are reported, while, on the right, the
   magnification of the relative spot obtained from 2D gel and histograms
   with the corresponding intensity volume values (p < 0.0005) are given.
   ABHEB, putative protein-lysine deacylase ABHD14B Ab-hydrolase; DDAH2,
   N(G),N(G)-Dimethylargine dimethylaminohydrolase 2; MMP7, Matrix
   metalloproteinase 7, also known as matrilysin; CLU, clusterin; A1AT,
   alpha1-antitrypsin.

Table 1.

   Urinary proteins significantly changed after ESWL treatment as
   identified by spots on reference gels.
   Protein
   Name Abbreviation Swiss-
   Prot/NCBInr
   AC ^a SCORE ^b
   _SC ^c Matching
   Peptides
   # Theoretical
   Mr_pI n-Fold
   Variation ^d
   (p < 0.001)
   Alpha-1 antitrypsin variant A1AT [83]P01009 61_19 7 46,751-5.43 +3.42
   Actin, cytoplasmic 1 ACTB gi|501885 155_46 20 42,058_5.29 +2.50
   Apolipoprotein A-IV precursor APOA4 gi|178757 126_35 18 45,353_5.33
   +1.32
   Ficolin-3 FCN3 [84]O00602 47_18 5 33,404_6.20 +2.13
   Apolipoprotein E APOE [85]P02649 54_30 9 36,248_5.65 +1.69
   Serpin peptidase inhibitor A1AT gi|15080499 62_23 8 46,864_5.36 +0.91
   N(G),N(G)-dimethylarginine
   dimethylaminohydrolase 2 DDAH2 [86]O95865 80_22 7 29,915_5.66 −2.40
   Actin, cytoplasmic 1 G ACTG1 gi|40226101 67_7 21 29,878_5.5 −2.12
   Matrix metalloproteinase 7 MMP7 gi|348021 82_26 9 29,810_6.56 +4.18
   Delta-aminolevulinic acid dehydratase Hem2 [87]P13716 40_19 6
   36,728_6.32 +2.76
   Ubiquilin-4 UBQL4 [88]Q9NRR5 67_24 9 53,205_5.67 −1.88
   Complement C3 C3 gi|78101268 88_15 8 187,148_6.02 −2.02
   Hemoglobin subunit beta HBB [89]P68871 59_40 5 16,102_6.75 +3.01
   Alpha-1 antitrypsin A1AT gi|50363217 112_37 14 46,790_5.42 +1.66
   Ataxin 3 variant ATX3 gi|28951768 54_26 6 38,978_4.81 +1.27
   Clusterin CLU gi|338305 110_41 12 37,002_5.74 +2.69
   Apolipoprotein E APOE gi|178853 61_29 9 36,243_5.81 +1.78
   Cytoplasmic dynein DC1L1 [90]Q9Y6G9 55_13 5 56,834_6.01 −1.93
   Fibrinogen gamma FIBG gi|70906437 75_41 8 50,103_5.70 −1.18
   Apolipoprotein A-IV APOA4 [91]P06727 66_12 23 45,371_5.28 +1.39
   Lactate Dehydrogenase A like 6B LDHAL6B [92]Q9BYZ2 131_36 14
   41,943_5.86 +3.01
   Tripeptidyl Peptidase-I TPP1 gi|215261288 51_11 5 62,797_6.26 +1.19
   Transthyretin TTR gi|212374952 66_56 5 13,799_5.35 +1.65
   Apolipoprotein A4 APOA4 gi|93163358 123_37 17 45,371_5.28 +2.77
   [93]Open in a new tab

   (a) AC represents accession numbers from the Swiss-Prot database. (b)
   Score is −10*Log(p), where p is the probability that the observed match
   is a random event; it is based on the Swiss-Prot database using the
   MASCOT searching program as MALDI-TOF MS data. (c) SC, sequence
   coverage. (d) n-fold variation indicates the changes in mean,
   normalized spot abundance value between pre- and post-ESWL conditions.
   The mean abundance value and its SEM were calculated from the
   normalized spot intensities from n = 8 replicate gels for each pre- and
   post-ESWL condition.

   Furthermore, since we noticed some intervariability between patient
   samples, to minimize this drawback and to further characterize the
   urinary proteome, we constructed two synthetic gels representing the
   spots common to the condition under examination, one for the PRE-ESWL
   condition and the other for the POST-ESWL condition ([94]Figure 3A,B).
   The first showed 955 common spots while the second showed 916 common
   spots. Furthermore, the comparison of the matched post-ESWL synthetic
   gel with the 2D map of each pretreated cohort reveals 134 spots
   ([95]Figure 3C), 50 of which can be unambiguously assigned to unique
   proteins that can be considered secondary to the lithotripsy treatment
   ([96]Table 2).

Figure 3.

   [97]Figure 3
   [98]Open in a new tab

   Comparative analysis of synthetic gels obtained for pre-ESWL (A) versus
   post-ESWL (B) conditions, which allowed the resolution of 134 unique
   spots in the post-ESWL condition (C).

Table 2.

   Additional urinary proteins showing increased content in urine samples
   after ESWL treatment in patients, as revealed by MS analysis of
   peptides in post-ESWL synthetic gels compared to pre-ESWL gels.
   Protein
   Name Abbreviation Swiss-
   Prot/NCBInr
   AC ^a SCORE ^b
   _SC ^c Matching
   Peptides
   # Theoretical
   Mr_pI
   Actin, cytoplasmic 1 ACTB [99]P60709 109_37 11 42,052/5.28
   Alpha-1-antitrypsin A1AT [100]P01009 190_5555 23 46,878/5.37
   S Variant of Human Alpha1-Antitrypsin A1AT gi|231240 200_57 22
   39,099/5.27
   Alpha1-Antitrypsin A1AT gi|253723069 115_67 27 44,273/5.43
   Cleaved Antitrypsin Polymer A1AT gi|7546268 200_55 19 37,622/5.43
   Antitrypsin alpha-1 mutant A1AT gi|224224 229_45 22 46,873/5.35
   Serpin-Proteinase Complex A1AT gi|83754916 132_36 14 40,041/5.20
   Cleaved Antitrypsin P10 Pro A1AT gi|301598706 201_53 19 38,558/5.11
   Cleaved Antitrypsin Polymer A1AT gi|7245932 98_54 17 36,612/5.44
   A1AT Alpha-1-antitrypsin A1AT gi|28637 54_29 8 22,871/6.11
   Cleaved Antitrypsin P10 Pro, P9-P6 Asp A1AT gi|301598708 76_27 9
   38,474/5.16
   Inhibitor BrCN fragment lI, alpha1 protein A1AT gi|223039 104_63 7
   11,785/5.76
   Alpha-1B-glycoprotein A1BG [101]P04217 90_23 10 54,790/5.56
   Alpha- 1- microglobulin AMBP [102]P02760 59_23 7 38,999/5.95
   Antithrombin-III ANT3 [103]P01008 226_46 25 53,025/6.32
   Apolipoprotein A-I APOA1 [104]P02647 280_73 30 23,00/5.22
   Chain A Human Apolipoprotein A-I APOA1 gi|2914175 219_88 25 23,389/5.55
   Truncated Human Apolipoprotein A-I APOA1 gi|347447518 271_84 25
   21,611/5.02
   Apolipoprotein A-IV APOA4 [105]P06727 254_56 28 45,371/5.28
   Apolipoprotein A-IV APOA4 gi|563320 291_33 62 28,141/5.39
   Apolipoprotein E APOE [106]P02649 53_28 10 36,246/5.46
   Apolipoprotein E precursor APOE gi|4557325 195_62 24 36,246/5.56
   Alpha-enolase OS ENOA [107]P03733 53_16 7 47,481/7.01
   Crystal Structure of Human Enolase 1 ENOA gi|203282367 89_23 10
   47,350/6.99
   Ceruloplasmin CERU [108]P00450 245_28 28 122,983/5.44
   Complement protein 9 C9 gi|179726 175_24 18 64,399/5.49
   Complement component C9 CO9 [109]P02748 98_13 10 64,615/5.43
   Complement factor B CB gi|57209925 55_14 10 86,648/6.44
   Complement factor B preproprotein GB gi|67782358 55_11 9 86,847/6.67
   Human Complement Component C3 C3 gi|78101268 153_22 22 11,4238/5.55
   Complement factor H CFAH [110]P08603 267_25 35 14,3680/6.21
   FicoIin-3 FCN3 [111]O75636 82_36 11 33,395/6.20
   Fibulin-1 FBLN1 [112]P23142 56_16 10 81,268/5.07
   Glutaminyl-peptide cyclotransferase QPGT [113]Q16769 191_44 18
   40,965/6.12
   Glutaminyl Cyclase Mutant E201 QPCT gi|185177689 195_54 19 37,590/5.78
   Glutaminyl-peptide cyclotransferase QPCT gi|75766183 150_48 18
   37,606/5.69
   Glycosytated Human Glutaminyl Cyclase QPCT gi|345101018 127_40 15
   37,916/5.96
   Glutaminyl-peptide cyclotransferase QPCT [114]Q16769 171_45 15
   40,965/5.69
   Glutaminyl CycIase Mutant QPCT gi|185177695 175_48 17 37,619/5.78
   Glutaminyl CycIase with Glutamine QPCT gi|75766189 162_53 19
   37,605/5.78
   Heat shock protein beta-1 HSPB1 [115]P04792 150_11 50 22,826/5.98
   Keratin C 19 K1C19 [116]P08727 61_19 8 44,079/5.04
   Human MbI-Associated Protein 19 Map19 gi|50513645 103_44 8 19,531/5.44
   Paraneoplastic antigen-like protein 6C PNM6C [117]P0CW26 46_10 5
   44,304/5,24
   Pigment epithelial-differentiating factor PEDF gi|189778 131_18 9
   46,471/5.84
   Crystal Structure of PEDF PEDF gi|15988024 164_37 15 44,306/5.77
   Serum amyloid P-component SAMP [118]P02743 135_31 10 25,485/6.10
   Serpin-Proteinase Complex A1AT gi|83764916 131_36 14 40,041/5.20
   Serotransferrin TF [119]P02787 390_50 40 79,294/6.81
   Transthyretin TTR [120]P02766 89_53 8 15,991/5.52
   [121]Open in a new tab

   (a) AC represents accession numbers from the Swiss-Prot database. (b)
   Score is −10*Log(p), where p is the probability that the observed match
   is a random event; it is based on the Swiss-Prot database using the
   MASCOT searching program as MALDI-TOF MS data. (c) SC, sequence
   coverage.

   Again, many of these proteins were isoforms, cleaved polymers, or
   precursors of the same protein as in the case of alpha–1-antitrypsin
   (A1AT), apoliprotein A I (APOA1), apolipoprotein IV (APOA4),
   apolipoprotein E (APOE), alpha enolase (ENOA), complement protein 9
   (C9), complement factor B (CB), and glutamyl-peptide cyclotransferase
   (QPCT). However, the isoforms of A1AT, APOE, and APOA4 and the sequence
   of other proteins such as transthyretin (TTR) or complement 3 (C3)
   reported in [122]Table 2 are different from those previously identified
   in the reference gels obtained from the different patient cohorts and
   reported in [123]Table 1, while the sequence of ACTB and that of
   canonical proteins such as A1AT ([124]P01009), APOA4 ([125]P06727), and
   APOE ([126]P02649) are the same in both tables.

   In summary, through the procedures and analyses described above, we
   resolved a total of 75 (25 plus 50) proteins from the urine of patients
   with nephrolithiasis. Of these, 50 were found only in urine from
   patients after their exposure to ESWL, while 24 were present in urine
   samples obtained from patients after exposure to ESWL and were
   significantly up- or downregulated in post-ESWL urine compared to
   pre-ESWL urine ([127]Figure 4). However, as noted above, many of the
   identified proteins were isoforms of the same protein.

Figure 4.

   [128]Figure 4
   [129]Open in a new tab

   Post-ESWL synthetic gel urinary proteome map annotating 50 unique
   proteins identified by mass spectrometry. Protein names with their
   abbreviations are those reported in [130]Table 2.

3.3. Validation of the Protein Sequence and Urinary Content, Respectively, by
LIFT-MALDI TOF (MS/MS) and Western Blot Analyses of Some Peculiar Proteins
Identified by MS and Selected Among the Others in Post-ESWL Urine Samples

   Using LIFT technology (as described in the Methods section), we
   analyzed a number of proteins identified by MS and reported in
   [131]Table 1 and [132]Table 2. With this method, we obtained parental
   ion masses from PMF spectra and the high Tof-Tof Score values
   unequivocally confirmed the unique peptide sequences (reported in red)
   for each protein ([133]Table 3). For example, here, we report the
   analysis of three proteins that were shown to be highly upregulated in
   post-ESWL urine samples.

Table 3.

   Sequence validation of selected proteins previously identified in
   post-ESWL urine samples by MS using LIFT technology.
   ABBR. Name Mw/
   pI
   Theor. PMF
   Score ^a Peptide Matched/
   Peptide Searched SC ^b
   % Lift (MS[2])
   Ion Parent
   Masses
   (m/z) Score ^c
   Tof-Tof Peptide Sequence
   MMP7 29810/
   6.56 82 9/18 50 1784.9653
   1492.8482
   1139.6207 125 IVSYTRDLPHITVDR
   DLPHITVDRLVSK
   WTSKVVTYR
   DDAH2 29915/
   5.66 89 7/19 36 2497.2438
   459.7863 200 DFAVSTVPVSGPSHLRGLCGMGGI
   TVVAGSSDAAQKAVR
   CLU 37002/
   5.74 110 12/28 42 2551.2517
   1714.8468 167 FFTREPQDTYHYLPFSLPHR
   FMETVAEKALQEYR
   [134]Open in a new tab

   ^a PMF Score: Values are reported as Log[10] (p), where p is the
   probability that the observed match is a random event, as calculated by
   the Swiss Prot database using the MASCOT search program; ^b SC,
   sequence coverage, is the ratio between the part of the sequence
   covered by the matched peptide and the full length of the protein
   sequence. ^c Score Tof-Tof: This value results from the combination of
   PMF and MS/MS of the matched peptide from ion parent fragments.

   To further validate the results of the proteomic analysis in relation
   to the changes in the expression levels of urinary proteins after ESWL
   treatment in patients, Western blot analysis was performed on the
   selected proteins reported above. This technique also confirmed the
   identification of these proteins obtained by MS ([135]Figure 5A,B).
   Therefore, with these two methods, we are confident that the indicated
   proteins have an intact amino acid sequence and could be used as
   putative biomarkers of ESWL-induced changes.

Figure 5.

   [136]Figure 5
   [137]Open in a new tab

   (A) Representative Western blots showing changes in alpha-1-antitrypsin
   (A1AT) (where the white arrow indicates the appropriate immune band
   while the lower one is likely an isoform of the same protein),
   clusterin (CLU), and matrix metalloproteinase 7 (MMP7) content induced
   by ESWL treatment in patients with nephrolithiasis as previously
   identified by MS and reported in [138]Table 1 together with other
   proteins. Protein lysates (30 µg) were loaded for each electrophoretic
   lane. The original blots are reported in [139]Figure S2 in the
   Supplemental Material. (B) Bands in the immunoblots were quantified by
   densitometric analysis, performed as reported in the Methods section,
   and their values are reported as optical density (OD) on the y axis of
   the histograms. ** p < 0.01, *** p < 0.001: statistical significance
   vs. post-ESWL samples (Student’s t test). N. of examined urine samples
   = 3 for each condition (pre- and post-ESWL), each of which is a pooled
   sample of urine specimens collected from 10 patients before and after
   their exposure to ESWL.

3.4. Computer Analysis of the Biological Functions and Related Pathways, as
Well as Possible Networks, Between the Urinary Proteins Whose Levels Were
Modified by Exposure of Patients to Lithotripsy

   The composition of the assigned proteome was characterized based on
   biological functions and related molecular pathways, annotated in the
   Gene Ontology database (GO: wwe.expasy.org _UNIPROT) ([140]Figure 6).

Figure 6.

   [141]Figure 6
   [142]Open in a new tab

   Biological processes and pathways of differentially expressed proteins
   in post-ESWL urine samples, as revealed by MS analysis, were obtained
   using the PANTHER database. The percentage of proteins grouped
   according to the biological processes and pathways in which they are
   mainly involved, which are identifiable by the colored squares below
   the pies, are reported inside the pies in the left panel and only some
   in the right panel, where other percentages are reported above the
   square brackets, meaning that each colored triangle has the same
   percentage.

   With this analysis, it was possible to highlight the biological
   processes of dysregulated proteins in urine samples from the exposure
   of patients to ESWL. Most of them usually play a role in metabolic
   (21%) or cellular (21%) processes, the regulation of biological
   functions (13%), responses to stimuli (about 11%), and immune system
   processes (7.5%). The activities of all these proteins are implicated
   in a variety of pathways that modulate inflammation and related signals
   (chemokines, cytokines, and Wnt and p38 MAPK pathways), angiogenesis
   and the VEGF pathway, blood coagulation, cell cytoskeletal modeling,
   and cell–cell interactions. Unexpectedly, some of them are related to
   pathways implicated in neurodegenerative disorders such as Alzheimer’s
   or Huntington’s diseases, as emphasized in the Discussion Section.
   Finally, a large portion of the assigned proteins appear to be
   cytoplasmic, some from the endoplasmic reticulum, but there are no
   nuclear proteins, mainly due to the absence of intact cells in the
   urine.

   Using the STRING database ([143]http://string-db.org, accessed on 25
   February 2025), the interconnections existing between all proteins,
   identified by MS, that were dysregulated in urine due to patient
   exposure to ESWL were constructed ([144]Figure 7A).

Figure 7.

   [145]Figure 7
   [146]Open in a new tab

   Computer analysis performed using the STRING database to evaluate the
   mutual interactions between the proteins identified by MS analysis and
   reported in [147]Table 1 and [148]Table 2. (A) This analysis
   highlighted a close interaction between the proteins identified by MS
   in the urine of patients after ESWL and dysregulated by this treatment.
   The colors of the circles in this panel were randomly selected by the
   STRING database. (B) STRING analysis divided these proteins into three
   different clusters, where the genes corresponding to the identified
   proteins are reported inside circles labeled with different colors and
   whose composition is reported in the Table below the graph. The name of
   the proteins encoded by the genes is reported in [149]Table S1, in the
   Supplementary Material.

   Interestingly, this analysis revealed a p-value for protein–protein
   interaction (PPI) enrichment <10^−16, meaning that the proteins have
   more interactions with each other than would be expected from a random
   set of proteins of the same size and degree distribution extracted from
   the genome. Such enrichment indicates that the proteins are at least
   partially biologically connected as a group. Furthermore, by continuing
   the analysis in the STRING database, we highlighted the formation of
   three main clusters recognizable by the different colors of the spheres
   (red, green, and blue) in which the genes encoding the selected
   proteins (reported in [150]Table S1 of the Supplemental Material) are
   indicated ([151]Figure 7B). These represent the nodes, which are
   associated with each other by edges to indicate their interaction,
   while thicker lines represent stronger associations. The main clusters
   with the related color are reported in the table above the figure, as
   derived from the STRING analysis. Cluster n. 1 is the largest,
   comprising most of the identified proteins in the post-ESWL urine,
   which can be found in blood microparticles, participating in the
   complement and coagulation pathways, or in the protein–lipid complex.
   In contrast, cluster n. 2 contains structural proteins of cytoskeleton.
   STRING analysis revealed a significant enrichment in the RHO GTPases
   activating the WASP and WAVE pathway, which is known to play a key role
   in cell migration and invasion, while cluster n. 3 includes only one
   protein, tripeptidyl-peptidase-1 (TTP1), a serine protease. Most of
   these aspects are analyzed in more detail in the Discussion Section.

   Finally, an additional pathway enrichment analysis of the proteins
   forming the two main clusters was performed using the KEGG database
   ([152]Figure 8).

Figure 8.

   [153]Figure 8
   [154]Open in a new tab

   KEGG pathway enrichment analysis of proteins in clusters n.1 (upper
   histograms) and n. 2 (lower histograms). The abscissa represents the
   fold of enrichment of the genes under each pathway classification while
   the ordinate represents the enrichment pathway. On the right in each
   panel, the colored bar ranging from blue to red represents the
   enrichment expressed as –log10 from decrease to increase in proteins in
   the groups.

   This analysis highlights that the proteins included in cluster n. 1 are
   involved not only in complement-and-coagulation-related or
   lipid-turnover-related pathways but also in vitamin metabolism and
   ferroptosis, a cell death pathway involving iron accumulation and lipid
   peroxidation. The same analysis showed that the proteins of cluster n.
   2 are also implicated in cellular metabolism, mainly in carbohydrate
   and protein turnover, or in pathways such as HIF-1 signaling, related
   to the regulation of the cellular response to oxygen levels, or the Wnt
   signaling pathway, involved in the control of cell fate and tissue
   homeostasis. However, the same protein, MMP7, which regulates Wnt
   signaling, could also be involved in human T-cell leukemia virus type 1
   infection.

4. Discussion

   The aim of this investigation was to analyze urinary protein
   composition in order to determine changes in the protein profile caused
   by ESWL and, possibly, putative biomarkers of renal damage. To achieve
   this goal, the first step was to enroll an adequate number of patients
   with nephrolithiasis to be treated with ESWL by performing a careful
   selection based on their health condition. They were all male, since in
   a preliminary series of experiments, female urine showed higher
   variability. Furthermore, it should be noted that 2DE separated a
   relatively low number of spots from urine samples obtained from those
   patients, and MS identification of proteins occurred with poor
   resolution, likely due to the presence of high levels of proteins, most
   of which were of plasma origin. Therefore, the whole analytical phase
   was preceded by a methodological setup phase during which all urine
   samples, collected from subjects with nephrolithiasis treated with ESWL
   in the pre-treatment (2 h) and post-treatment (24 h) conditions, were
   subjected to the Proteominer enrichment procedure to deplete them of
   highly abundant proteins. With this technique, we obtained a good
   resolution of the less abundant proteins by electrophoretic runs, which
   should better reflect the changes in urinary protein pattern caused by
   patients’ exposure to ESWL. Indeed, when we adopted this technique for
   sample preparation, it proved to be an optimal method with a high
   degree of reproducibility and efficiency in terms of overall protein
   yield [[155]24]. Furthermore, since there was a large heterogeneity
   between the two-dimensional maps obtained for each sample and
   condition, it was necessary to create two pools of samples, consisting
   of control urine samples (pre-ESWL) and post-ESWL treatment urine
   samples, respectively, for which the image analysis and identification
   of each protein change were repeated, referring to synthetic gels built
   on specific proteomic data of the two conditions under examination and,
   above all, free of interindividual variables. This procedure allowed us
   to determine, with a certain statistical rigor, a greater number of
   changes in the protein level in the urine in the post-ESWL condition.
   Overall, with the above strategy, we were able to demonstrate that
   lithotripsy significantly modified the urinary protein profile with
   regard to the low-abundance protein composition, corroborating, at the
   biochemical level, the notion that significant morphological and
   functional changes can occur in the kidney with ESWL treatment
   [[156]4,[157]14,[158]25,[159]26,[160]27,[161]28,[162]29].

   First, it is noteworthy that only one protein, namely, putative
   ab-hydrolase domain-containing protein 14 (ABHEB), was present in
   pre-ESWL samples and no longer detectable in patient samples after
   ESWL. Since this enzyme is a papillary signaling protein associated
   with immunity and defense, which has been found to be significantly
   upregulated during osmotic stress [[163]30], our finding suggests that
   the renal osmotic stress defense capacity is strongly reduced after
   lithotripsy.

   In contrast, our MS analysis identified a large number of de novo
   expressed or upregulated proteins in post-ESWL samples compared to the
   levels detected in pre-ESWL urine. STRING analysis applied to these
   proteins showed a close relationship among them, allowing the formation
   of three main clusters.

   Cluster n. 1 is the richest, comprising 22 proteins of those reported
   in [164]Table 1 and [165]Table 2. One of the most interesting is A1AT,
   a protease that protects tissues from enzymes released from
   inflammatory cells, which was identified in our experiments with a
   large number of isoforms that are post-translation modifications of the
   same protein encoded by the SERPINA1 gene. The identification of A1AT
   was not surprising since many previous urinary proteomic studies have
   indicated this protein as one of the major biomarkers for the
   diagnostic and prognostic evaluation of different renal diseases
   [[166]31]. Note that A1AT occupies a central position in cluster n.1
   ([167]Figure 5), where it is linked to several other proteins
   dysregulated by ESWL treatment. Among them, clusterin (CLU) is usually
   related to lipid utilization, cell aggregation, and adhesion. Its
   increased expression has been found in several types of nephropathy
   [[168]32] and has been identified as one of the possible novel
   biomarkers of “subclinical AKI” [[169]33]. In cluster n.1, A1AT and CLU
   are also interconnected with complement-related and
   protein–lipid-complex-related proteins. One of these is APOE. It can
   activate several proteins in the classic or alternative pathways of the
   complement cascade, which participate in the innate immunity required
   for host defense but are also mediators of inflammation and, therefore,
   various forms of disease and injury [[170]34]. Accordingly, the
   presence of increased levels of different complement factors (H, C3,
   C9, CB) in post-ESWL urine, possibly activated by APOE, is not
   surprising, confirming that the complement cascade is involved in renal
   injury [[171]35]. C3, in particular, is a key molecule of this system
   that can be produced locally and activated in the kidney, where its
   increased levels are usually seen as being related to nephropathies;
   however, even lower levels suggest intra-renal inflammation and have
   been related to poor renal outcomes [[172]36,[173]37]. Since we found,
   in post-ESWL urine samples, several C3 isoforms, which were both down-
   and upregulated, it is reasonable to suspect that they may all
   contribute to renal damage. Furthermore, C3 and other complement
   factors can also be activated by leptin pathways, which in turn are
   stimulated by MAP19 (human MBL-associated protein 19), the short
   isoform and the alternative splice variant of MBL-associated serine
   protease 2 (MASP-2) that we found induced de novo by the ESWL
   procedure. Notably, in urine and uEVs, MAp19 is the dominant form and
   the renal tubule damaged due to ischemia represents an example of local
   complement activation following the presence of damaged renal cells
   [[174]38,[175]39]. Interconnected with the complement system in cluster
   n.1 is antithrombin III (ANT3 codified by the SERPINC1 gene), which, in
   addition to its known anticoagulant activity, exhibits
   anti-inflammatory properties, showing a slight increase in urinary
   levels in the acute phase of glomerulonephritis, but a large increase
   during the relapse phase of nephrotic syndrome, as reviewed in
   [[176]40].

   Additional apolipoproteins in the same cluster include apolipoprotein
   A-I (APOA1) and apolipoprotein A-IV (APOA4). APOA1 is the major protein
   component of HDL particles, which are crucial in reverse cholesterol
   transport, while APOA4 may play a role in the secretion and catabolism
   of chylomicrons and VLDL. Both exhibit antioxidant and
   anti-inflammatory activity, preventing thrombotic phenomena and
   protecting organs such as the heart, brain, and kidneys. However,
   proteomic analysis has previously found that increased levels of APOA1
   may represent a promising biomarker for the early diagnosis of AKI
   after percutaneous coronary intervention in elderly patients [[177]41].
   In contrast, APOA4 concentrations are markedly increased in chronic
   kidney disease (CKD), mainly in dialysis patients, resulting in a
   potential early marker of renal impairment that can predict CKD
   progression [[178]42].

   Other well-interconnected proteins in cluster n. 1 are ceruplasmin
   (CERU, encoded by the CP gene) and serum amyloid P-component (SAMP
   encoded by the APCS gene). CERU has previously been identified by MS
   analysis among the upregulated glycoproteins in the urine of CDK
   patients, together with antitrombin III, glutamyl-peptide
   cyclotrasferase (QPCT), and tripeptidyl peptidase-I (TPP1) [[179]43],
   as we also detected in post-ESWL urine samples, although these proteins
   are not included in the same cluster of CERU. These results are
   intriguing since TPP1, which forms cluster n. 3 of our network, and the
   ataxin 3 variant (ATX3) and the various QPCT isoforms, are mainly
   involved in the pathophysiology of debilitating neurodegenerative
   conditions or cancer; for example, see
   [[180]44,[181]45,[182]46,[183]47,[184]48]. Doubts are also raised by
   the increased presence of the paraneoplastic antigenic protein 6C (now
   recognized as PNMA6A), included in the paraneoplastic Ma family, since
   no function or involvement in renal pathologies has been identified for
   this protein and its physiological function is still unclear [[185]49].
   On the contrary, SAMP/APCS belonging to the pentatraxin family is able
   to regulate many aspects of the innate immune system and has been
   recognized as the most predictive marker of experimentally induced or
   lupus nephritis [[186]50].

   Finally, some upregulated/de novo induced proteins in urine samples
   from ESWL-treated patients are located in the external part of cluster
   n.1, although they are connected to the main proteins mentioned above.
   Among these is alpha-1B glycoprotein (A1BG), a recognized marker for
   autoimmunity and cancer, whose induction in post-ESWL samples may be
   due to early and specific alterations in urinary glycoprotein
   excretion, as found in diabetic nephropathy [[187]43]. As for alpha
   1-microglobulin (AMBP), a low-molecular-weight heme-binding antioxidant
   plasma protein, once readily filtered through the glomerulus, it is
   reabsorbed and catabolized by the proximal tubular cells
   [[188]51,[189]52]. Accordingly, its increased presence in post-ESWL
   urine could indicate proximal tubular dysfunction and thus impaired
   tubular functions. Furthermore, AMBP, together with pigment
   epithelium-derived factor (PEDF, also known as SERPINF1) and hemoglobin
   subunit beta (HBB), has also been found in the plasma of patients with
   reduced glomerular filtration due to CKD [[190]53]. In turn, many
   hemoglobin fragments have been found to be increased in patients with
   vasculitis or IgA nepfropathy (IgAN), which likely reflects an
   important glomerular inflammation [[191]54]. As for the other proteins,
   serotransferrin (TF) has been correlated in rat and human urine samples
   with a risk of renal damage induced by subclinical tubular alterations
   [[192]55], while Fibulin 1 (FBLN1) could be another possible biomarker
   of kidney injury, as demonstrated by proteomic studies performed both
   on sera of patients with different renal diseases [[193]56] and on
   urinary extracellular vesicles isolated from the urine of patients with
   medullary sponge kidney disease [[194]57]. Furthermore, Ficolin-3
   (FCN3) is an important member of the fibrinogen family and an activator
   of the complement lectin pathway that, by causing pro-inflammatory
   effects, contributes to the onset/progression of inflammatory diseases,
   including nephritis. Very recently, elevated levels of FCN3, together
   with galectin-3, have also been found in sera of patients with AKI,
   following complicated sepsis and correlated with the severity of renal
   damage [[195]58]. Finally, increased levels of transthyretin (TTR),
   also known as prealbumin, are relevant since elevated serum levels of
   TTR have been found in CKD, and, in the presence of tubular damage,
   there may be a leakage of TTR in the urine [[196]59,[197]60].
   Therefore, all these proteins may also act in an
   acute-phase/immune-stress response in CDK subjects and are probably
   able to play a similar role after patient lithotripsy.

   Further data that deserve to be discussed concern the upregulation of
   the proteins grouped in a second smaller cluster of seven proteins
   labeled by green circles that is, however, interconnected with cluster
   n.1. Among these is cytoplasmic actin 1 (ACTB), although the increased
   expression levels of this protein are counterbalanced by the observed
   downregulation of cytoplasmic actin 2, also known as ACTG1. Both
   proteins are components of the cytoskeleton but are localized on
   different chromosomes, and their protein chain differs by four residues
   at the N-terminus. These features likely account for differences in
   their location into actin structures within the same cell, as well as
   in their functions, with ACTB filaments being mainly involved in cell
   contraction processes while ACTG1 (or γ-actin) is enriched in stress
   fibers and plays a key role in endothelial cell motility, chemotaxis,
   and angiogenesis [[198]61]. Notably, the Wiskott–Aldrich syndrome
   (WASP)/WAVE family of proteins also controls actin arrangement and
   function in the kidney, where it plays a key role in Na^+ reabsorption
   by the aldosterone-sensitive distal nephron [[199]62]. Consequently,
   when the dysregulation of actin cytoskeleton occurs (as may be the case
   in our study) in renal epithelial cells or in renal podocytes, which
   are fundamental in preventing the filtration of large
   proteins/micromolecules and whose function is largely dependent on
   actin cytoskeleton, this can lead to ionic imbalance and/or foot
   process retraction and proteinuria [[200]63,[201]64]. Other proteins of
   the same cluster electrophoretically resolved from post-ESWL urine
   samples belong to acute-phase response proteins and/or mediators of the
   fibrotic reaction, as previously found, reinforcing the idea that ESWL
   may induce renal inflammation and acute trauma. They include
   δ-aminolevulinic acid dehydratase (δ-ALA-D or Heme-2) [[202]65], heat
   shock protein beta-1 (HSPB1) [[203]66], and enolase A (ENOA), with the
   latter implicated in calcium oxalate stone formation [[204]67].
   Additionally, keratin C 19 (KTC19), a member of the keratin family that
   was induced de novo in urine by the exposure of patients to ESWL, is a
   common finding in progressive renal diseases, even if early after
   disease onset [[205]68]. Notably, this cluster incudes the fibrogenic
   matrix metalloproteinase-7 (MMP7), also known as matrilysin, which
   belongs to a superfamily of Zn-dependent metalloproteinases responsible
   for maintaining cellular matrix homeostasis [[206]69]. It has been
   found to be elevated in renal allograft inflammation/injury, also
   acquiring moderate discriminatory significance for subclinical
   rejection [[207]70]. Thus, its upregulation in our post-ESWL samples
   supports the idea that this protein may be indicative of renal tubular
   epithelial cells damage and that these tubular cell types, under the
   action of MMP7, are undergoing epithelial–mesenchymal transition
   [[208]71,[209]72]. Of note, the presence of lactate dehydrogenase A
   like 6B (LDHAL6B) found in post-ESWL urine also strengthens the belief
   that this binding protein may be related to human glomerulus damage, as
   found in the urine from mouse diclorofenac-injured kidney glomerulus
   [[210]73] or in models of AKI and CKD [[211]74]. In summary, all these
   data support the hypothesis that lithotripsy may damage renal function,
   although often only temporarily.

   Before concluding, it should be emphasized that exposure of patients to
   ESWL also caused a significant downregulation of six proteins, which
   are mostly ubiquitous and important for normal renal function. Indeed,
   in addition to the ACTG1 and C3 proteins already mentioned, there are
   reduced levels of dimethyl arginine dimethyl amino hydrolase 2 (DDAH
   2), which is usually present in large amounts in several intra-renal
   sites, including the glomerular vasculature [[212]75]. This enzyme
   degrades asymmetric dimethyl arginine (ADMA), an inhibitor of nitric
   oxide (NO) synthase [[213]76]. As a consequence of the decreased level
   of DDAH2 produced by ESWL exposure, ADMA may increase and in turn
   predispose patients to the progression of vascular disease and renal
   damage [[214]77]. Less clear is the significance of another protein
   downregulated in post-ESWL urine, namely, ubiquilin-like protein or
   ubiquilin-4 (UBQL4). It belongs to the ubiquilin family, consisting of
   four members, and regulates protein degradation, mediating the
   transport of misfolded, mislocalized, or accumulated proteins to the
   proteasome and is also a key regulator of DNA. So far, members of this
   family and, in particular, UBQL4 have been associated with the most
   common cancers [[215]78], while another member, namely, UBQLN1, has
   been shown to be critical in combating neurological disorders caused by
   protein aggregation, such as amyotrophic lateral sclerosis (ALS),
   Alzheimer’s disease, and Huntington’s disease, while its loss has so
   far been found in lung cancer patients and human cancer cell lines
   [[216]79]. Finally, two other downregulated proteins were cytoplasmic
   dynein (DC1L1) and fibrinogen gamma (FIBG). DC1L1 is a key member of
   the dynein complex containing, in addition to light intermediate and
   light chains, dinein heavy chains that exhibit ATPase activity
   responsible for the cargo transport necessary for cellular function. It
   is also found in the intracellular vesicles of renal collecting ducts,
   where it colocalizes with aquaporin 2 (AQP2) water channels, which are
   critical for the control of renal water permeability via vasopressin.
   Therefore, the downregulation of DC1L1 could alter the filtering
   function of the kidneys [[217]80]. On the other hand, FGG is a primary
   component of fibrinogen, which comprises several chains including two
   α-chains, two β-chains, and two γ-chains (FGG) interconnected with
   disulfide bonds. In addition to its important role in blood
   coagulation, fibrinolysis, and cellular and matrix interactions,
   fibrinogen is also involved in the inflammatory response and wound
   healing. Soresensen et al. used a unilateral ureteral obstruction model
   in fibrinogen knockout mice and found that compared to fibrinogen
   deficient homozygous mice (Fib−/−), heterozygous mice (Fib+/−) showed
   more severe interstitial fibrosis damage, with massive fibrinogen
   deposition in the renal interstitium [[218]81]. However, the results
   are contradictory, as fibrinogen deficiency has been associated with
   higher mortality in renal ischemia/reperfusion injury in rats
   [[219]82]. Thus, the role of fibrinogen in AKI remains controversial.

5. Conclusions

   In conclusion, this is the first study to report the proteomic profile
   of low-abundance proteins in urine from patients with nephrolithiasis
   treated with ESWL. The results show that inflammatory, fibrotic, and
   antioxidative proteins are the major constituents confirming, at the
   biochemical level, that ESWL can produce inflammation and fibrotic
   processes. Indeed, most of those identified in post-ESWL urine samples
   have been previously proposed as possible biomarkers for renal tissue
   damage in both AKI and CKD. Therefore, most of them could also play a
   putative role as biomarkers of renal tubular and glomerular damage
   induced by patients’ exposure to lithotripsy, such as matrix
   metalloproteinase 7, alpha1-antitrypsin, and clusterin, which were
   remarkably increased in post-ESWL urine samples, as well as dimethyl
   arginine dimethyl amino hydrolase 2 and abhydrolase domain-containing
   protein 14, which were downregulated in the same urine samples. We are
   aware that further studies with a larger series and repeated
   measurements should be performed to clarify whether these proteins can
   be used to demonstrate renal damage and as urine biomarkers for the
   diagnosis and treatment of renal injury after ESWL. Nevertheless, we
   believe that the use of urine represents a non-invasive method that
   allows the early identification (24 h) of urine proteins that could
   serve as potential biomarkers to predict the severity or otherwise of
   the damage caused by lithotripsy and accelerate the application of the
   most appropriate clinical investigations and treatments.

Acknowledgments