- Open Access
Splicosomal and serine and arginine-rich splicing factors as targets for TGF-β
© Hallgren et al.; licensee BioMed Central Ltd. 2012
- Received: 18 April 2011
- Accepted: 28 April 2012
- Published: 28 April 2012
Transforming growth factor-β1 (TGF-β1) is a potent regulator of cell growth and differentiation. TGF-β1 has been shown to be a key player in tissue remodeling processes in a number of disease states by inducing expression of extracellular matrix proteins. In this study a quantitative proteomic analysis was undertaken to investigate if TGF-β1 contributes to tissue remodeling by mediating mRNA splicing and production of alternative isoforms of proteins.
The expression of proteins involved in mRNA splicing from TGF-β1-stimulated lung fibroblasts was compared to non-stimulated cells by employing isotope coded affinity tag (ICATTM) reagent labeling and tandem mass spectrometry. A total of 1733 proteins were identified and quantified with a relative standard deviation of 11% +/− 8 from enriched nuclear fractions. Seventy-six of these proteins were associated with mRNA splicing, including 22 proteins involved in splice site selection. In addition, TGF-β1 was observed to alter the relative expression of splicing proteins that may be important for alternative splicing of fibronectin. Specifically, TGF-β1 significantly induced expression of SRp20, and reduced the expression of SRp30C, which has been suggested to be a prerequisite for generation of alternatively spliced fibronectin. The induction of SRp20 was further confirmed by western blot and immunofluorescence.
The results show that TGF-β1 induces the expression of proteins involved in mRNA splicing and RNA processing in human lung fibroblasts. This may have an impact on the production of alternative isoforms of matrix proteins and can therefore be an important factor in tissue remodeling and disease progression.
- Alternative Splice
- Splice Factor
- mRNA Splice
- Myofibroblast Differentiation
- Alternative Isoforms
Remodeling of the airway wall, which involves altered extracellular matrix deposition, is an important feature in airway diseases such as asthma and chronic obstructive pulmonary disease (COPD) . This process has been suggested to be associated with aberrant wound healing, dependent on the presence of myofibroblasts [2, 3]. Differentiated myofibroblasts can be distinguished from fibroblasts by de novo synthesis of α-smooth muscle actin (α-SMA), increased expression of alternatively spliced fibronectin (EDA) and assembly of stress fibers . The growth factor TGF-β1 has been shown to play an important role in the differentiation process inducing the expression of alternatively spliced fibronectin, which leads to a subsequent increased expression of α-SMA  and other cytoskeletal proteins . In addition, TGF-β1 is a potent inducer of various extracellular matrix components such as collagen , fibronectin , and the proteoglycans: biglycan [9, 10] and versican [11–13].
During constitutive and alternative splicing of gene products, splice site selection is regulated by altering initial binding of serine-arginine-rich splicing factors (SR proteins) to pre-mRNA. These factors contain an N-terminal RNA recognition motif that allows binding to pre-mRNA and a C-terminal serine-arginine-rich domain that mediates protein-protein interactions. Different exon-splicing enhancers and silencers are recognized by specific subsets of SR proteins , which include SRp20, SRp30a (ASF/SF2) SRp30c, 9 G8, SRp40, SRp55, SRp70, SRp75, and SC35 [15–18]. The ratio of different SR proteins and the presence of exon-splicing enhancers and silencers are factors that influence further assembly of splicosomal proteins. SR proteins generally have nuclear localization but some members such as ASF/SF2, 9 G8, and SRp20 also function as mRNA transporters between nucleus and the cytoplasm . The activity of SR proteins is tightly regulated via dynamic events of phosphorylations and dephosphorylations in different domains of the proteins . The phosphorylation pattern of SR proteins not only influence their activity and function but also play a role in sorting SR proteins within the nucleus . Moreover, hypo-phosphorylation of one domain of SR proteins serves as a nuclear export signal .
One important aspect of TGF-β1-driven myofibroblast differentiation is the exon inclusion of EDA in fibronectin , a process that is not fully understood. However, induced expressions of the splicing factors SRp40, SRp20, or ASF/SF2 have been suggested to stimulate inclusion of EDA suggesting that splice site selection is regulated by quantitative changes in multiple factors [24, 25]. Several other matrix molecules have been shown to have different splice variants such as biglycan , versican , decorin , and collagen . The exact role of these splice forms has not yet been established.
To investigate the mechanism of TGF-β1-induced alternative splicing, we employed isotope coded affinity tag (ICATTM) reagent labeling and tandem mass spectrometry  to identify nuclear proteins and characterize the changes in their expression upon TGF-β1 stimulation and focus on proteins involved in the splicing process. We were able to provide a detailed quantitative expression pattern of 76 proteins involved in mRNA splicing and RNA processing. The results showed that TGF-β1 altered the relative expression of serine and arginine-rich splicing factors that control splice site selection and promote alternative splicing.
TGF-β1 induces myofibroblast-like characteristics in fibroblasts
Strategy for identification and relative quantification of nuclear proteins
Additional file 1: Table S1 show the relative expression levels (defined as TGF-β1 stimulated/control) of the individual splicing related proteins calculated from four unique experiments from independent cell cultures and ICAT workflow runs.
Western blot analysis of individual SR protein expression
Comparison of TGF-β 1 -induced fold change from ICAT and western blot
Cellular localization of SR proteins and SRp20 following TGF-β1 stimulation
In the present study the role of TGF-β1 on the expression levels of proteins involved in mRNA splicing and RNA processing was examined with a quantitative proteomic approach. We observed that TGF-β1 altered the relative ratio of splicing factors that may be important for alternative splicing of proteins. One such example was that TGF-β1 affected the levels of splicing factors possibly of importance in EDA fibronectin production, suggesting a regulatory role in myofibroblast differentiation. These results indicate that TGF-β1 may contribute to tissue remodeling and disease progression by meditating mRNA splicing and the production of alternative isoforms of proteins.
TGF-β1 plays an important role in normal wound healing but is also a central player in the development of fibrosis and tissue remodeling. TGF-β1 has been shown to induce the production of various extracellular matrix components, such as collagen , fibronectin , and proteoglycans [11–13, 36], that are elevated during disease. In the present study we verified that TGF-β1 triggered a cellular phenotypic switch of lung fibroblasts resulting in a myofibroblast-like phenotype that express α-SMA, as previously described . In addition, TGF-β1 induced production of alternative splicing variants of fibronectin. These events were accompanied by alterations in the relative ratios of proteins involved in mRNA splicing and RNA processing. Alternative splicing is an important aspect of gene regulation and results in dramatic biological consequences. It has been estimated that as much as 60% of genes undergo alternative splicing  and 15% of human genetic diseases are caused by mutations that destroy functional splice sites or generate new sites . Splicing of mRNA is carried out by the spliceosome, a large nuclear macromolecular complex of five small nuclear ribonucleic particles (snRNPs) and 50–100 polypeptides . In the current study TGF-β1 stimulation altered the relative expression of 76 proteins involved in RNA splicing and processing which indicate that TGF-β1 may be an important regulator for this process.
The ICAT results were verified by western blots that showed a general increase of phosphorylated SR proteins following TGF-β1 stimulation. The increased levels of SRp20, SRp40, and SRp75 from the ICAT experiments were consistent with the western blots (Table 1 and Additional file 1: Table S1). SRp20 was found to be induced by both ICAT and western blot using the antibody detecting the absolute protein level. However, when using the antibody that recognized phospho-epitopes of SRp20 then it was further induced. These data may suggest that TGF-β1 may influence the level of phosphorylation of SR proteins which is important for their function and localization. These results were further confirmed with immunofluorescence that indicated an increase of SRp20 accompanied by extra-nuclear localization. Some SR proteins, including SRp20, have in addition to their nuclear functions also been shown to be involved in shuttling mRNA to extra-nuclear localizations , which explains the staining pattern. Moreover, when using the antibody that detect phosphorylated SR proteins then the staining was strictly nuclear which may seem contradictory as SRp20 is one of the protein targets for the antibody. However, it has been shown that hypo-phosphorylation is a signal for nuclear export which may explain the difference in staining pattern.
There was a discrepancy in the expression levels of SRp55 as it was induced in the western blots and repressed in the ICAT dataset. A possible explanation for this is that the used antibody is directed against a conserved phospho-epitope and does not coincide with absolute protein levels. In addition, TGF-β1 changed the expression of several other proteins such as U5 associated proteins, U5 small nuclear ribonucleoprotein 200 kDa, U5 snRNP 100 kDa protein, and helicases, RNA-dependent helicase p72 and the RNA helicase II/Gu protein, all which have been shown to induce conformational changes in the spliceosome [41–43]. This suggests that TGF-β1 also can affect the splicing process via conformational changes of the spliceosome. In addition, we found one member of the hnRNPs family to be repressed, which is of interest since members of the hnRNPs competitively inhibits binding of the splicing factors to the immature mRNA . Splicing of mRNA is a complex operation which involves the activity of multiple proteins. It has been suggested that the relative ratios of proteins involved in selection of splice-sites and splicing factors may be determinants of splice site selection and alternative splicing [45, 46]. The experimental setup in this study enabled direct comparison of relative expression levels within these groups of protein (Figure 5). Our data support the idea that relatively small up- and down-regulation of different splicing factors may regulate splicing of a specific mRNA.
The ICAT experiments were chosen at a time-point where the initial changes in fibronectin splicing pattern was observed (t = 24 h) and thus, the quantification of the splicing factors and hnRNPs was made at a time point where alternative spliced sites were selected. We found that the expression of SRp20 was induced and that the expression of SRp30c was repressed. The role of SRp30c in alternative splicing of fibronectin is unclear. However, SRp20 has previously been shown to promote alternative splicing of EDB in fibronectin when induced and to inhibit EDA splicing in chondrocytes [26, 47]. In HeLa cells both the levels of EDA + and EDA- fibronectin mRNA were suppressed when over expressing SRp20, . It has been reported in other studies that SRp30a (ASF/SF2) [48, 49], 9 G8 , and SRp40 [25, 47] have positive effects on EDA inclusion. We propose that TGF-β1 mediates differential splicing of fibronectin by altering the relative expression and/or phosphorylation pattern of several of these splicing factors, which interact to promote alternative splicing. During the remodeling processes, EDA and EDB are included into the mature mRNA to generate splice isoforms . These alternative splice isoforms promote cell attachment and facilitates cell migration  and have been found to be elevated in fibrotic tissue  and malignant human tumors . TGF-β1 is known to induce an increase of EDA and EDB fibronectin in both fetal and adult fibroblasts . Collectively, these data indicate that TGF-β1 not only stimulates myofibroblast differentiation and the expression of ECM proteins, but also may contribute to alternative splicing.
In summary, we have shown that TGF-β1 may alter the expression levels of the splicing factors that regulate alternative splicing of matrix proteins. This may have an impact on the production of alternative isoforms of matrix proteins and suggests a novel mechanism of how TGF-β1 mediates tissue remodeling and disease progression.
Cell culturing and TGF-β1 stimulation
Human embryonic lung fibroblasts (HFL-1) (ATCC, Manassas, VA, USA) were sub-cultured in Eagles minimum essential medium (EMEM) supplemented with 1% glutamine and 10% fetal calf serum (FCS) and PEST. Before experiments cells were grown to confluency and were starved overnight in Dulbecco’s modified Eagle medium (DMEM) with 0.4% FCS. Cells were washed in PBS and were then incubated with or without TGF-β1 (10 ng/mL) (R&D Systems Abingdon, UK) for the time-points indicated in the figures. Experiments were performed in passage 17–22.
Cells were grown under standardized conditions with or without TGF-β1 (10 ng/mL) for 6, 24, or 48 h and whole cell lysates were prepared using lysis buffer (50 mM Tris–HCl, 500 mM NaCl, 1% NP-40, 10% glycerol, 10 mM MgCl2, pH 7.4) containing the protein inhibitor cocktail complete mini (1 mM PMSF, 1 μg/mL Aprotinin, 1 μg/mL Pepstatin, 1 μg/mL Leopeptin, Roche, Manheim, Germany). Samples were solubilized in Laemmli’s buffer and equal amounts of total protein (10 μg) were loaded and separated by electrophoresis on 4–12% Bis-Tris Gels (Invitrogen, Gibro, Carlsbad, CA, USA). The proteins were blotted to PVDF membranes (Immobilon-P Transfer Membrane, Millipore Corporation, Billerica, MA, USA). Membranes were incubated with antibodies against: a-SMA (Abcam, Cambridge, UK), prolyl 4-hydroxylase (Acris antibodies, Hiddenhausen, Germany), fibronectin (Dako, Glostrup, Denmark), EDA-fibronectin (Abcam, Cambridge, UK), GAPDH (Santa Cruz Biotechnology, Inc. Santa Cruz, CA, USA), Phospho-SR proteins (Zymed Laboratories, San Francisco, CA, USA), and SRp20 (Zymed Laboratories, San Francisco, CA, USA). Bound antibodies were visualized by peroxidase-conjugated secondary antibodies and enhanced luminescence (AmershamTM western blotting Detection Reagents, GE Healthcare, Uppsala, Sweden) with exception for the blot against phospho-SR proteins where Dy-light 800 nm conjugated secondary antibodies (Cell Signaling Technology Inc., Boston, MA, USA) was used. The luminescence/fluorescence signal was detected on Odyssey® FC imaging system (LI-COR Biosciences, Lincoln, NE, USA). Exposure times were standardized so that all samples were treated the same way for each antibody. Individual bands were quantified with densitometry using the Quantity One software version 4.6.1 (BIORAD Laboratories, Hercules, CA, USA). Data are based on four individual sets of experiments.
Fibroblasts (7000/well) were grown overnight on chamber slides and were then incubated with or without TGF-β1 24 and 48 h. Cells were then fixed in 4% formaldehyde for 15 min and permeabilized with 0.1% Triton X for 30 min. After blocking in 2% BSA-TBS containing 5% goat serum (Vector laboratories, Burlingame, CA, USA) for 30 min, cells were incubated with primary antibodies against: a-SMA (Abcam, Cambridge, UK), prolyl 4-hydroxylase (Acris antibodies, Hiddenhausen, Germany), Phospho-SR proteins (Zymed Laboratories, San Francisco, CA, USA), and SRp20 (Zymed Laboratories, San Francisco, CA, USA) and with secondary antibodies: Alexafluor 555-conjugated goat anti-mouse antibody and Alexafluor 555-conjugated goat anti-rabbit antibody (both from Molecular Probes Invitrogen, Eugene, OR, USA). To stain nuclei, cells were incubated with DAPI (Molecular Probes Invitrogen, Eugene, OR, USA). Glasses were mounted with mounting media (Dako, Glostrup, Denmark) and photographed using a TE2000-E fluorescence microscope (Nikon, Tokyo, Japan) equipped with a DXM1200C camera (Nikon).
RNA extraction and cDNA synthesis
Cells were grown under standardized conditions with or without TGF-β1 (10 ng/mL) for 6, 24, or 48 h. Total RNA was isolated from cells using RNeasy (Qiagen, GmBH, Hilden, Germany) according to the manufacturer´s instructions. The quantity of RNA was measured by spectrophotometry using a NanoDrop ND-100 (Nano Drop Technologies, Delaware, MD, USA). Total RNA (1 μg) was reverse-transcribed using superscript II according to the manufacturer’s manual (Invitrogen, Carlsbad, CA, USA) and stored at −70°C.
Five μL of cDNA (diluted 1:250) was mixed with 15 μL SYBR-green mixture (PE Biosystems, Foster City, CA, USA) and amplified by real-time RT-PCR using Stratagene MX3005P QPCR system (Agilent Technologies, Santa Clara, CA, USA). Initially the samples were held for 2 min at 50°C then for 10 min at 95°C; they were then cycled for 40 cycles of 30 s at 95°C, 1 min at 58°C, and 1 min at 72°C. Each sample was analyzed in triplicate. Reactions were performed using MX3000P 96-well plates (Agilent Technologies, Santa Clara, CA, USA). All primers were constructed using the online Primer 3 program (http://frodo.wi.mit.edu/primer3/) and they were ordered from A/S DNA Technology (Risskov, Denmark). The following primers were used. Fibronectin forward: CGA TCA CTG GCT TCC AAG TT, and reverse: TCC GAG CAT TGT CAT TCA AG. Fibronectin-EDA forward: AAT CCA AGC GGA GAG AGT CA, and reverse: CGT AAA GGG CTC AGC TCA AG. S18 forward: CGA ACG TCT GCC CTA TCA AC, and reverse: TGC CTT CCT TGG ATG TGG TA. All primers were tested for specificity by sequence alignment in the PubMed nucleic acid database (http://blast.ncbi.nlm.nih.gov/Blast.cgi). Data are based on three individual sets of experiments.
Purification of nuclei
The nuclei were purified according from a protocol previously described . Briefly, the cells were harvested in 60 mM KCl, 15 mM NaCl, 0.15 mM Spermine, 0.5 mM Spermidine, 15 mM Hepes, and 14 mM Mercaptoethanol supplemented with 0.2% (v/v) Nonidet p40, aprotinin (1 μg/mL), leupeptin (1 μg/mL), pepstatin A (1 μg/mL), PMSF (10 μg/mL) and 0.3 M sucrose. The cell suspension was then homogenized with 60 strokes at 2,000 rpm (Labortechnik, Berlin, Germany) and the homogenate was filtered with 100 μm filter paper (Schleicher&Schuell, Dassel, Germany). The nuclei were counted in a Bürker chamber and the purity was assessed and protein content was determined by Bradford protein reagent kit (Pierce, Rockford, IL, USA).
Labeling with the acid-cleavable ICATTM reagent and isolation of cysteine containing peptides
Fibroblast nuclei were lysed in a buffer containing 6 M Guanidium-HCl (pH 8.5), 1% Triton X-100, and 50 mM Tris HCl, followed by sonication. Starting with 500 μg for control and TGF-β1 stimulated, each sample was reduced by adding 10 μl of 50 mM TCEP (Tris(2-carboxyethyl)phosphine) and boiled for 10 min. The samples were allowed to cool and the acid cleavable ICATTM reagent (all the materials in this section are from the ICATTM reagent kit Applied Biosystems, Framingham, MA, USA) was added: the light reagent to the control and heavy reagent containing nine 13 C to the TGF-β1-treated sample. Alkylation was allowed to complete for 2 h, at 37°C. The two samples are combined and acetone precipitated in order to remove the guanidium-HCl and the unreacted ICATTM reagent. The pellet was dissolved in a buffer consisting of 50 mM Tris (pH 8.5), 5 mM CaCl2, and 10% acetonitrile. Trypsin was added at a 1:40 enzyme/substrate ratio in two additions once at the start of the digestion and once more, 2 h later. Digestion was completed at 37°C overnight.
Following digestion the sample was diluted into 25% acetonitrile, pH 3.0 in order to reduce the buffer concentration below 10 mM. The resulting peptide mixture was injected to a PolyLC (4.6 × 100 mm Polysulfoethyl A) SCX column on Vision workstation (Applied Biosystems, Framingham, MA, USA) at a flow rate of 1 mL/min using a binding buffer (buffer A) 10 mM KH2PO4, 25% acetonitrile, pH 3 and an elution buffer (buffer B) of 350 mM KCL, 10 mM KH2PO4, 25% acetonitrile, pH 3. The gradient was 0% B to 10% B in 2 min, 20% B in 15 min, 45% B in 3 min, 100% B in 10 min, and an additional 8 min hold at 100% B. Twenty-three SCX fractions of 1.5 mL volume were collected.
The pH was adjusted for each SCX fraction to 7.2 with 10× PBS buffer (pH 10) and injected to the avidin affinity column as prescribed by the manufacturer (Applied Biosystems, Framingham, MA, USA). Cysteine-containing peptides bound to the avidin column were washed three times: 1 mL of Wash 1, 1 mL of Wash 2, and 1 mL of de-ionized water. Elution of the cysteine-containing peptides was performed with 800 μL of avidin elution buffer. The samples were then concentrated by a speed-vac to dry, cleaved with the ICAT tm cleaving reagent containing 95% TFA and concentrated again to remove the cleaving reagent. The samples were then taken up in 2% acetonitrile, 0.1% TFA for re-injection for a nanoHPLC MS and MS/MS analysis.
Protein identification and quantification by LC-MS and -MS/MS
Avidin purified SCX fractions were subjected to MALDI and ESI HPLC-MS and MS/MS analysis in a 50:50 split. For the MALDI based workflow, these fractions were injected in the HPLC loading buffer onto a 100 μm × 15 mm C18 Magic column (Auburn, Michrom Bioresources, CA, USA) using a CapTrap pre-column (Auburn, Michrom Bioresources, CA, USA). Mobile phase A was 2% acetonitrile, 0.1% TFA, mobile phase B was 85% acetonitrile, 5% n-PrOH, 10% water, 0.1% TFA. HPLC elution was carried out at a 1-μL/min flow rate on an Ultimate nanoHPLC workstation (Dionex-LC Packings, Hercules, CA, USA). The HPLC elution from the column was collected at 20-s intervals on the MALDI plate using a Probot fraction collector (Dionex-LC Packings). Forty-eight-min HPLC elution was collected to the MALDI plates as an array of 12 × 12 sample spots. The HPLC eluent was mixed with the MALDI matrix (7.5 mg/mL α-cyano-4-hydroxycinnamic acid dissolved in 60:40 acetonitrile-water containing 0.15 mg/mL dibasic ammonium-citrate) through a mixing tee (Upchurch, WA, USA) at a flow rate of 2-μL/min. The most abundant, middle-fractions of the SCX separation were spotted onto two plates using a 90-min HPLC gradient.
MALDI plates were analyzed in automated mode on the AB4700 Proteomics Analyzer (Applied Biosystems, Framingham, MA, USA). First the MS spectra were collected from the entire HPLC run. Then, using an in-house developed program, MS/MS precursors were selected by applying an exclusion algorithm to eliminate: (a) redundant precursors carrying over multiple HPLC fractions; and (b) using only the more abundant members of peptide pairs for MS/MS analysis. MS/MS spectra were acquired using up to 2,500 laser shots/precursor unless the predefined signal-to-noise level in the MS/MS acquisitions was achieved sooner. The MS/MS data were submitted for database searching as a batch to Mascot (http://www.matrixscience.com) through its automation interface of Mascot (Mascot Daemon). The non-redundant NCBI protein database was used. A detailed description of the acceptance criteria for the database searching results will be described elsewhere. In brief, tryptic peptides containing arginine residues were accepted at a Mascot score >20, peptides not containing arginine at a Mascot score >25. Peptides with less-than-significant Mascot score were thoroughly inspected, considering the correlation of peptide basicity with SCX fraction numbers, presence of characteristic high-energy CID fragments, and accurate mass measurements through internal calibration of the MS spectra using the masses of confidently identified peptides as internal mass references.
ESI based LC-MS/MS analyses were carried out using an Ultimate nanoHPLC system (Dionex-LC Packings, CA, USA) on a 75 μM × 150 mm Picofrit C18 column at a 300-nl/min flow rate with a gradient of 5% B to 30% B over 60 min. Mobile phase A was 2% acetonitrile, 0.1% formic acid, mobile phase was 85% acetonitrile, 5% n-PrOH, 10% water, 0.1% formic. A CapTrap (Michrom Bioresources, CA, USA) precolumn was used to preconcentrate the sample.
A platinum electrode was placed behind the HPLC column using a microtee (Upchurch, WA, USA) in order to apply the electrospray voltage (3 kV) for LC-MS/MS analysis. LC-MS/MS was performed using a QSTAR quadrupole time-of-flight instrument (Applied Biosystems, CA, USA). The instrument was set up to perform a 1-s MS scan (300–1500 Da) followed by three most abundant components (two to four charges were allowed) exceeding an intensity threshold of 35 counts. To improve the protein coverage the samples were halved and the analysis was replicated. LC-MS and MS/MS analyses were processed by the ProICAT software (Applied Biosystems, Foster City, CA, USA). Database search results were accepted at >95% confidence interval. Database searching and quantification results from multiple MS platforms were consolidated by parsing all the qualitative and quantitative peptide results into an Oracle database. The set of all the identified peptides were assigned to a minimum set of proteins that could explain all the confidently identified peptide sequences. The abundance ratios of peptide pairs labeled with the heavy (9 × 13 C) and light (0 × 13 C) ICATTM reagents were normalized to the median of all peptide ratios in order to generate normalized expression ratios. Expression ratios of peptides matching to the same protein were averaged to generate expression ratios at the protein level.
Data are expressed as mean ± SEM. Student’s t-test was used to evaluate the differences of the means between groups. Differences were considered significant at P < 0.05. All analyses were performed using GraphPad Prism software version 4.00 (GraphPad Software, San Diego, CA, USA).
This work was supported by grants from the Swedish Medical Research Council (11550), the Swedish Cancer Fund, the Swedish Society for Medical Research, the Swedish Heart-Lung foundation the JA Persson, G Nilsson, Greta and John Kock, A Österlund and Anna-Greta Crafoord Foundations, Lars Hiertas Minne foundation, the Konsul Bergh Foundation, Riksföreningen mot Rheumatism, the Royal Physiographic Society in Lund Gustaf V.s 80 Årsfond and the Medical Faculty, University of Lund. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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