Quantitative Proteomics of Human Heart Samples Collected In Vivo Reveal the Remodeled Protein Landscape of Dilated Left Atrium Without Atrial Fibrillation
2020; Elsevier BV; Volume: 19; Issue: 7 Linguagem: Inglês
10.1074/mcp.ra119.001878
ISSN1535-9484
AutoresNora Linscheid, Pi Camilla Poulsen, Ida Dalgaard Pedersen, Emilie Gregers, Jesper Hastrup Svendsen, Morten S. Olesen, Jesper V. Olsen, Mario Delmar, Alicia Lundby,
Tópico(s)Protease and Inhibitor Mechanisms
ResumoGenetic and genomic research has greatly advanced our understanding of heart disease. Yet, comprehensive, in-depth, quantitative maps of protein expression in hearts of living humans are still lacking. Using samples obtained during valve replacement surgery in patients with mitral valve prolapse (MVP), we set out to define inter-chamber differences, the intersect of proteomic data with genetic or genomic datasets, and the impact of left atrial dilation on the proteome of patients with no history of atrial fibrillation (AF).We collected biopsies from right atria (RA), left atria (LA) and left ventricle (LV) of seven male patients with mitral valve regurgitation with dilated LA but no history of AF. Biopsy samples were analyzed by high-resolution mass spectrometry (MS), where peptides were pre-fractionated by reverse phase high-pressure liquid chromatography prior to MS measurement on a Q-Exactive-HF Orbitrap instrument. We identified 7,314 proteins based on 130,728 peptides. Results were confirmed in an independent set of biopsies collected from three additional individuals. Comparative analysis against data from post-mortem samples showed enhanced quantitative power and confidence level in samples collected from living hearts. Our analysis, combined with data from genome wide association studies suggested candidate gene associations to MVP, identified higher abundance in ventricle for proteins associated with cardiomyopathies and revealed the dilated LA proteome, demonstrating differential representation of molecules previously associated with AF, in non-AF hearts.This is the largest dataset of cardiac protein expression from human samples collected in vivo. It provides a comprehensive resource that allows insight into molecular fingerprints of MVP and facilitates novel inferences between genomic data and disease mechanisms. We propose that over-representation of proteins in ventricle is consequent not to redundancy but to functional need, and conclude that changes in abundance of proteins known to associate with AF are not sufficient for arrhythmogenesis. Genetic and genomic research has greatly advanced our understanding of heart disease. Yet, comprehensive, in-depth, quantitative maps of protein expression in hearts of living humans are still lacking. Using samples obtained during valve replacement surgery in patients with mitral valve prolapse (MVP), we set out to define inter-chamber differences, the intersect of proteomic data with genetic or genomic datasets, and the impact of left atrial dilation on the proteome of patients with no history of atrial fibrillation (AF). We collected biopsies from right atria (RA), left atria (LA) and left ventricle (LV) of seven male patients with mitral valve regurgitation with dilated LA but no history of AF. Biopsy samples were analyzed by high-resolution mass spectrometry (MS), where peptides were pre-fractionated by reverse phase high-pressure liquid chromatography prior to MS measurement on a Q-Exactive-HF Orbitrap instrument. We identified 7,314 proteins based on 130,728 peptides. Results were confirmed in an independent set of biopsies collected from three additional individuals. Comparative analysis against data from post-mortem samples showed enhanced quantitative power and confidence level in samples collected from living hearts. Our analysis, combined with data from genome wide association studies suggested candidate gene associations to MVP, identified higher abundance in ventricle for proteins associated with cardiomyopathies and revealed the dilated LA proteome, demonstrating differential representation of molecules previously associated with AF, in non-AF hearts. This is the largest dataset of cardiac protein expression from human samples collected in vivo. It provides a comprehensive resource that allows insight into molecular fingerprints of MVP and facilitates novel inferences between genomic data and disease mechanisms. We propose that over-representation of proteins in ventricle is consequent not to redundancy but to functional need, and conclude that changes in abundance of proteins known to associate with AF are not sufficient for arrhythmogenesis. For centuries, anatomists and physiologists have recognized that structural and functional differences exist between cardiac chambers and that cardiac diseases can affect specific regions of the heart. Yet, our knowledge of the molecular profile of the different cardiac chambers and how it relates to the causes, manifestations or treatment of disease remains limited. Advances in biochemistry and molecular biology, and more recently the availability of high throughput transcriptomics, have improved our understanding of the molecular composition of the heart (1Lindskog C. Linné J. Fagerberg L. Hallström B.M. Sundberg C.J. Lindholm M. Huss M. Kampf C. Choi H. Liem D.A. Ping P. Väremo L. Mardinoglu A. Nielsen J. Larsson E. Pontén F. Uhlén M. The human cardiac and skeletal muscle proteomes defined by transcriptomics and antibody-based profiling.BMC Genomics. 2015; 16: 475Crossref PubMed Scopus (41) Google Scholar) and its chambers (2Kääb S. Barth A.S. Margerie D. Dugas M. Gebauer M. Zwermann L. Merk S. Pfeufer A. Steinmeyer K. Bleich M. Kreuzer E. Steinbeck G. Näbauer M. Global gene expression in human myocardium—oligonucleotide microarray analysis of regional diversity and transcriptional regulation in heart failure.J. Mol. Med. 2004; 82: 308-316Crossref PubMed Scopus (71) Google Scholar). However, interpretation of transcriptomic data is limited by the fact that transcript abundance is an imperfect proxy for abundance and dynamics of the encoded protein. Quantitative high-resolution proteomics offers an unbiased approach to the identification of chamber-specific protein expression patterns and their relation to cardiac function. Recent large-scale proteomic studies have focused on mapping the human proteome across all major organs (3Wilhelm M. Schlegl J. Hahne H. Moghaddas Gholami A. Lieberenz M. Savitski M.M. Ziegler E. Butzmann L. Gessulat S. Marx H. Mathieson T. Lemeer S. Schnatbaum K. Reimer U. Wenschuh H. Mollenhauer M. Slotta-Huspenina J. Boese J.-H. Bantscheff M. Gerstmair A. Faerber F. Kuster B. Mass-spectrometry-based draft of the human proteome.Nature. 2014; 509: 582-587Crossref PubMed Scopus (1318) Google Scholar, 4Kim M.-S. Pinto S.M. Getnet D. Nirujogi R.S. Manda S.S. Chaerkady R. Madugundu A.K. Kelkar D.S. Isserlin R. Jain S. Thomas J.K. Muthusamy B. Leal-Rojas P. Kumar P. Sahasrabuddhe N.A. Balakrishnan L. Advani J. George B. Renuse S. Selvan L.D.N. Patil A.H. Nanjappa V. Radhakrishnan A. Prasad S. Subbannayya T. Raju R. Kumar M. Sreenivasamurthy S.K. Marimuthu A. Sathe G.J. Chavan S. Datta K.K. Subbannayya Y. Sahu A. Yelamanchi S.D. Jayaram S. Rajagopalan P. Sharma J. Murthy K.R. Syed N. Goel R. Khan A.A. Ahmad S. Dey G. Mudgal K. Chatterjee A. Huang T.-C. Zhong J. Wu X. Shaw P.G. Freed D. Zahari M.S. Mukherjee K.K. Shankar S. Mahadevan A. Lam H. Mitchell C.J. Shankar S.K. Satishchandra P. Schroeder J.T. Sirdeshmukh R. Maitra A. Leach S.D. Drake C.G. Halushka M.K. Prasad T.S.K. Hruban R.H. Kerr C.L. Bader G.D. Iacobuzio-Donahue C.A. Gowda H. Pandey A. A draft map of the human proteome.Nature. 2014; 509: 575-581Crossref PubMed Scopus (1507) Google Scholar), but do not provide the necessary resolution for understanding chamber-specific function and pathophysiology. Prior studies have reported unique protein expression patterns in the human heart (5Aye T.T. Scholten A. Taouatas N. Varro A. Van Veen T.a. B. Vos M.a. Heck A.J.R. Proteome-wide protein concentrations in the human heart.Mol. BioSystems. 2010; 6: 1917Crossref PubMed Scopus (59) Google Scholar, 6Lu Z.Q. Sinha A. Sharma P. Kislinger T. Gramolini A.O. Proteomic analysis of human fetal atria and ventricle.J. Proteome Res. 2014; 13: 5869-5878Crossref PubMed Scopus (20) Google Scholar, 7Doll S. Dreβen M. Geyer P.E. Itzhak D.N. Braun C. Doppler S.A. Meier F. Deutsch M.-A. Lahm H. Lange R. Krane M. Mann M. Region and cell-type resolved quantitative proteomic map of the human heart.Nat. Communications. 2017; 8Crossref Scopus (146) Google Scholar). However, those studies relied mainly on necropsy material collected hours after time of death. We therefore set out to obtain an in-depth quantitative study of the protein expression landscape in heart samples collected from living individuals (i.e. collected in vivo) and its relation to disease states. Cardiac tissue acquisition in live humans is limited by obvious ethical considerations. On the other hand, mitral valve replacement consequent to mitral valve prolapse (MVP) is a surgical procedure that permits access to tissue from right (RA) and left atria (LA) and from the left ventricle (LV) without added risk. Furthermore, MVP is not a primary cardiac muscle disease and as such, the state of the atrial and ventricular tissue is only deviated from normal to an extent secondary to the valve dysfunction. Here, we report data obtained from samples collected during mitral valve replacement surgery in seven males. For all patients, chamber dilation was limited to the LA, allowing a comparison of a dilated (LA) versus non-dilated (RA) atrial proteome. None of our patients presented persistent atrial fibrillation (AF), thus giving us the opportunity to investigate the proteome of the dilated LA in a non-AF stage. We confirmed our findings on protein changes in the dilated LA in an independent replication experiment analyzing proteomes of three additional individuals undergoing mitral valve replacement surgery. Moreover, we studied tissue from the LA and RA of a patient with persistent atrial fibrillation to assess the abundance of proteins that were separately found to be differentially expressed in the pre-AF stage. The LV of the ten patients undergoing mitral valve surgery included in this study was electrically and structurally within normal boundaries (no arrhythmias; normal chamber dimensions and normal left ventricular ejection fraction). Taking advantage of the latter, we generated for the first time a comprehensive catalogue and comparative proteome of the LV from living hearts. Finally, given that we collected tissue from living humans, we were able to compare our data to those previously published (7Doll S. Dreβen M. Geyer P.E. Itzhak D.N. Braun C. Doppler S.A. Meier F. Deutsch M.-A. Lahm H. Lange R. Krane M. Mann M. Region and cell-type resolved quantitative proteomic map of the human heart.Nat. Communications. 2017; 8Crossref Scopus (146) Google Scholar), obtained from material collected several hours post-mortem. This comparison allowed us to define the limits of the use of necropsy material to draw conclusions about the proteome of living hearts. For full description of materials and methods, please see the Supplementary Materials. Our study is based on seven biological replicates of biopsy samples from three cardiac chambers (LA, RA, LV). Based on 21 samples fractionated into 12 fractions before MS analysis, a total of 252 MS measurements were performed. No technical replicates were performed. MS measurements of each fraction were performed back-to-back in order to minimize technical variability within each measured fraction, and at the same time distribute technical variability evenly across biological replicates. Our results were validated against an independent cohort of three biological replicates from each cardiac chamber where sample acquisition, laboratory workflow and MS measurements were performed completely independently form the original cohort. The number of biological replicates was chosen based on sample availability from the clinic. Statistical significance of differential protein expression across chambers was determined by volcano plot analysis based on a permutation-based false-discovery rate (FDR) cutoff (8Tyanova S. Temu T. Sinitcyn P. Carlson A. Hein M.Y. Geiger T. Mann M. Cox J. The Perseus computational platform for comprehensive analysis of (prote)omics data.Nat. Methods. 2016; 13: 731-740Crossref PubMed Scopus (3583) Google Scholar, 9Tusher V.G. Tibshirani R. Chu G. Significance analysis of microarrays applied to the ionizing radiation response.Proc. Natl. Acad. Sci. U.S.A. 2001; 98: 5116-5121Crossref PubMed Scopus (9771) Google Scholar). This FDR approach employs a combination of Student's t test p value and fold-change enrichment to determine whether a protein is deemed significant, because both low p values and high fold changes are indicative of a biologically important finding. Tissue biopsies were collected from LA, RA and LV of patients undergoing mitral valve surgery. Tissue samples were snap-frozen in a container with liquid nitrogen while still in the operating room. All patients gave informed consent to the procedure prior to operation and the procedure conform with the principles outlined in the Declaration of Helsinki. Frozen tissue biopsies were homogenized on a Precellys24 homogenizer (Bertin Technologies, France) in tissue incubation buffer (50 mm Tris-HCl pH 8.5, 5 mm EDTA, 150 mm NaCl, 10 mm KCl, 1% Triton X-100, 5 mm NaF, 5 mm beta-glycerophosphate, 1 mm Na-orthovanadate, containing 1× Roche complete protease inhibitor) with ceramic beads (2.8 and 1.4 mm zirconium oxide beads, Precellys). Homogenates were incubated for 2 h at 4 °C (20rpm), centrifuged (15,000 × g, 20 min, 4 °C) and soluble fractions transferred to chilled 1.5 ml tubes. Protein was precipitated and resuspended in Guanidine-HCl buffer (Gnd-HCl; 6MGnd-HCl, 50 mm Tris HCl pH 8.5, 5 mm NaF, 5 mm beta-glycerophosphate, 1 mm Na-orthovanadate, containing 1× Roche complete protease inhibitor). Disulfide bridges were reduced and cysteine moieties alkylated by addition of 5 mm Tris(2-carboxyethyl)phosphine (TCEP) and 10 mm chloroacetamide (CAA) and incubation in the dark at room temperature for 15 min. Up to 1 mg protein was digested in-solution by addition of endoproteinase Lys-C (Trichem ApS, Denmark; 1:100 enzyme/protein ratio) for 1.5 h at 30 °C, 750 rpm in the dark, followed by dilution (1:12 with 50 mm Tris-HCl pH8) and digestion with trypsin overnight (14h) at 37 °C, 750rpm (Life technologies, 1:100 enzyme/protein ratio). Reactions were quenched by trifluoroacetic acid. Soluble fractions were desalted and concentrated on C18 SepPak columns (Waters, MA). Of each sample, 50–100 μg peptide (in 10 μl injection volume) was fractionated by micro-flow reverse-phase ultrahigh pressure liquid chromatograpy (UPLC) on an Dionex UltiMate 3000 UPLC system (Thermo Scientific) equipped with an ACQUITY UPLC CSH C18 Column (130Å, 1.7 μm, 1 mm × 150 mm) at 30 μl/min flow rate, essentially as previously described (10Bekker-Jensen D.B. Kelstrup C.D. Batth T.S. Larsen S.C. Haldrup C. Bramsen J.B. Sørensen K.D. Høyer S. Ørntoft T.F. Andersen C.L. Nielsen M.L. Olsen J.V. An optimized shotgun strategy for the rapid generation of comprehensive human proteomes.Cell Systems. 2017; 4: 587-599.e584Abstract Full Text Full Text PDF PubMed Scopus (260) Google Scholar). Outflow was collected in 1-min intervals into 12 concatenated fractions in the autosampler. Fractionated peptide samples were analyzed by online reversed-phase liquid chromatography coupled to a Q-Exactive HF quadrupole Orbitrap tandem mass spectrometer (LC-MS/MS, Thermo Electron, Bremen, Germany). Peptide samples were brought to concentration of 0.2 μg/μl (diluted in 5% ACN, 0.1% TFA) in 96-well microtiter plates and autosampled (5 μl injection volume) into a nanoflow Easy-nLC system (Proxeon Biosystems, Odense, Denmark). Peptide samples were separated on 15 cm fused-silica emitter columns pulled and packed in-house with reversed-phase ReproSil-Pur C18-AQ 1.9 μm resin (Dr. Maisch GmbH, Ammerbuch-Entringen, Germany) in a 1 h multi-step linear gradient (0.1% formic acid constant; 2–25% ACN in 45 min, 25–45% ACN in 8min, 45–80% ACN in 3 min) followed by short column re-equilibration (80–5% ACN in 5 min, 5% ACN for 2 min). Column effluent was directly ionized in a nano-electrospray ionization source operated in positive ionization mode and electrosprayed into the mass spectrometer. Full-MS spectra (375–1500 m/z) were acquired after accumulation of 3,000,000 ions in the Orbitrap (maximum fill time of 25 ms) at 120,000 resolution. A data-dependent Top12 method then sequentially isolated the most intense precursor ions (up to 12 per full scan) for higher-energy collisional dissociation (HCD) in an octopole collision cell. MS/MS spectra of fragment ions were recorded at resolution of 30,000 after accumulation of 100,000 ions in the Orbitrap (maximum fill time of 45 ms). Raw MS data was processed using the MaxQuant software (11Tyanova S. Temu T. Cox J. The MaxQuant computational platform for mass spectrometry-based shotgun proteomics.Nat. Protocols. 2016; 11: 2301-2319Crossref PubMed Scopus (1904) Google Scholar) version 1.5.3.30 (Max-Planck Institute of Biochemistry, Department of Proteomics and Signal Transduction, Munich) and proteins identified with the built-in Andromeda search engine. All peptides were used for protein quantification, and label-free quantification (LFQ) was performed in MaxQuant with fast LFQ option enabled. Protein identification results were further processed using the Perseus software suite (8Tyanova S. Temu T. Sinitcyn P. Carlson A. Hein M.Y. Geiger T. Mann M. Cox J. The Perseus computational platform for comprehensive analysis of (prote)omics data.Nat. Methods. 2016; 13: 731-740Crossref PubMed Scopus (3583) Google Scholar). To remove minor technical variation between samples, quantile normalization of raw intensities was performed based on the Bioconductor R package LIMMA (12Bolstad B.M. Irizarry R.A. Astrand M. Speed T.P. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias.Bioinformatics. 2003; 19: 185-193Crossref PubMed Scopus (6420) Google Scholar). All seven patients were male, middle aged (average 50 years), normal weight (average BMI 23.6), and had mitral valve regurgitation with dilated left atria and a normal left ventricular ejection fraction. Details are provided in supplemental Table S1. Details related to patients in the replication cohort as well as related to a patient with atrial fibrillation are included in the same table. Electrocardiographic recordings from the ten patients undergoing mitral valve surgery detected only normal sinus rhythm and patients did not report palpitations or other symptoms suggestive of atrial fibrillation. Cardiac biopsies were collected from the RA, LA, and LV during mitral valve surgery. The tissue was snap-frozen immediately after collection. Right ventricular samples were not accessible because of the surgical approach. Cardiac samples were homogenized and proteins extracted by detergent-based solubilization followed by enzymatic cleavage by endoproteinase Lys-C and trypsin. The generated peptides were pre-fractionated into 12 fractions (10Bekker-Jensen D.B. Kelstrup C.D. Batth T.S. Larsen S.C. Haldrup C. Bramsen J.B. Sørensen K.D. Høyer S. Ørntoft T.F. Andersen C.L. Nielsen M.L. Olsen J.V. An optimized shotgun strategy for the rapid generation of comprehensive human proteomes.Cell Systems. 2017; 4: 587-599.e584Abstract Full Text Full Text PDF PubMed Scopus (260) Google Scholar, 14Batth T.S. Francavilla C. Olsen J.V. Off-line high-pH reversed-phase fractionation for in-depth phosphoproteomics.J. Proteome Res. 2014; 13: 6176-6186Crossref PubMed Scopus (205) Google Scholar) followed by high-resolution mass spectrometry measurement of each fraction on a Q-Exactive HF Orbitrap instrument (Fig. 1A). Proteome analysis resulted in 130,728 peptides covering 7314 protein groups (Fig. 1B). Of these, 6999 proteins were identified by at least 2 peptides (supplemental Table S2). The mass spectrometry (MS) based intensity measurements of protein abundance spanned seven orders of magnitude, highlighting a high dynamic range of the dataset (supplemental Fig. S1A). As expected for a comprehensive dataset, the majority of cardiac proteins (6766 or 93%) were identified in all chambers, whereas less than 200 proteins were identified in only one chamber (Fig. 1B). Proteins were on average identified based on 23 peptides, 14 of which were unique, resulting in a mean sequence coverage of 37% and mean unique sequence coverage of 30%. The present study provides the largest dataset of cardiac protein expression evaluated from human samples collected in vivo. To perform a quantitative analysis of protein expression across cardiac chambers, we quantile normalized measured protein intensities (12Bolstad B.M. Irizarry R.A. Astrand M. Speed T.P. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias.Bioinformatics. 2003; 19: 185-193Crossref PubMed Scopus (6420) Google Scholar) and assessed data quality. Our data showed minimal technical variation, as evidenced by only minor differences in intensity distributions prior to normalization and by Pearson correlation coefficients of ≥0.87 for protein intensities across samples (supplemental Fig. S1A–S1B). Furthermore, most proteins (≥90%) in each cardiac chamber were identified in at least three patient samples, ensuring that comparative analyses across chambers were performed on replicate measurements (supplemental Fig. S1C). To evaluate main protein abundance differences between chambers, we performed principal component analysis (PCA). This revealed that biological variation between atria and ventricle was greater than any other difference in the dataset, including disease status, medication or age (i.e. 19% of variance in the dataset explained along component 1, Fig. 1C). Main drivers of this segregation included well-known marker proteins of the ventricle and the atria (supplemental Fig. S1D), such as the atrial natriuretic peptide (NPPA) and Connexin-40 (GJA5) in atrial tissues, and ventricular myosin light chain in the ventricles (MYL3) (Fig. 1D). Unsupervised hierarchical clustering of protein intensity profiles across chambers yielded two main clusters separating ventricular and atrial samples, as well as partial separation among right and left atrial samples (Fig. 1D). When analyzed independently from the ventricular samples, PCA of left and right atria clustered into two distinct groups (supplemental Fig. S1E), thus allowing for differential LA versus RA proteome characterization. We assessed the impact of blood protein contamination in the individual chambers and found that blood proteins were present, as expected for tissue samples, but at similar amounts across all chambers (supplemental Fig. S2). Taken together, these results support that our data are of sufficient quality to perform in-depth analyses of global protein expression differences between chambers. A key feature of the cardiac biopsies studied here is that they were collected from living individuals and immediately frozen in the operating room. This contrasts with previous datasets acquired at a similar measurement depth, which were obtained from dead individuals and collected at time of necropsy (7Doll S. Dreβen M. Geyer P.E. Itzhak D.N. Braun C. Doppler S.A. Meier F. Deutsch M.-A. Lahm H. Lange R. Krane M. Mann M. Region and cell-type resolved quantitative proteomic map of the human heart.Nat. Communications. 2017; 8Crossref Scopus (146) Google Scholar). We found that necropsy material presented increased unspecific proteolysis compared with samples collected in vivo. Specifically, analysis of freshly isolated biopsy material leads to less unspecific protein degradation (Fig. 1E): 18% of all peptides from necropsy material were semi-tryptic, whereas the same was the case for 8% of the peptides from freshly isolated biopsies. The greater proportion of semi-tryptic peptides in necropsy samples indicate increased unspecific proteolysis because of post-mortem protein degradation. Presence of substantial amounts of degraded peptides, and thus MS precursor peaks, raises concern whether peptides matched on MS1 level through match-between-runs represent degradation products, thereby affecting protein quantifications (supplemental Fig. S3A–S3B). Quantification of protein abundances based on necropsy biopsies is further challenged by heterogeneous proteolysis across chambers. Overall, our analyses suggest that unspecific protein degradation in necropsy samples can lead to a skewed impact on protein quantification (supplemental Fig. S3C–S3F) and analysis of proteome data acquired from of post-mortem samples needs to consider unspecific protein degradation. Our analysis suggests that, for studying quantitative differences in protein abundance, analysis of freshly collected tissue biopsies is preferential. Our data revealed the proteome of the hearts of MVP patients, offering insights into protein expression to complement genomic studies. An existing GWAS data set previously identified six MVP susceptibility loci (Dina et al. (15Dina C. Bouatia-Naji N. Tucker N. Delling F.N. Toomer K. Durst R. Perrocheau M. Fernandez-Friera L. Solis J. Investigators P. Le Tourneau T. Chen M.-H. Probst V. Bosse Y. Pibarot P. Zelenika D. Lathrop M. Hercberg S. Roussel R. Benjamin E.J. Bonnet F. Lo S.H. Dolmatova E. Simonet F. Lecointe S. Kyndt F. Redon R. Le Marec H. Froguel P. Ellinor P.T. Vasan R.S. Bruneval P. Markwald R.R. Norris R.A. Milan D.J. Slaugenhaupt S.A. Levine R.A. Schott J.-J. Hagege A.A. MVP-France Jeunemaitre X. Network L.T.M. Genetic association analyses highlight biological pathways underlying mitral valve prolapse.Nat. Genet. 2015; 47: 1206Crossref PubMed Scopus (68) Google Scholar)), yet GWAS cannot directly pinpoint which genes in such genomic loci are causal to a disease. In order to identify which proteins in each of the MVP loci were actually expressed in the heart, we queried our data for their protein expression level in the LA (Fig. 2). Protein abundances across the different proteins were estimated by intensity based absolute quantification (IBAQ) (16Schwanhäusser B. Busse D. Li N. Dittmar G. Schuchhardt J. Wolf J. Chen W. Selbach M. Global quantification of mammalian gene expression control.Nature. 2011; 473: 337-342Crossref PubMed Scopus (4095) Google Scholar). iBAQ is an estimation that allows for abundance comparison across different proteins by correcting for protein size in order to remove MS identification bias of large versus small proteins. For four of the loci, we found several orders of magnitude difference between the most abundant and the second-most abundant protein encoded by a gene in the locus. Involvement of a gene in a cardiac phenotype is considered most likely if the gene is transcribed and translated; from that rationale, we suggest that our data offers an alternative way to prioritize genes in GWAS loci. That is, for four of the loci, one protein was considerably more abundant in the LA than any other protein encoded by a gene in the same locus. Thus, for these four loci, our heart proteome data point to a prioritization of the genes LMCD1, TNS1, PITPNB, and CBR1. Notably, functional evidence in support of the involvement of LMCD1 and TNS1 in MVP has been reported (15Dina C. Bouatia-Naji N. Tucker N. Delling F.N. Toomer K. Durst R. Perrocheau M. Fernandez-Friera L. Solis J. Investigators P. Le Tourneau T. Chen M.-H. Probst V. Bosse Y. Pibarot P. Zelenika D. Lathrop M. Hercberg S. Roussel R. Benjamin E.J. Bonnet F. Lo S.H. Dolmatova E. Simonet F. Lecointe S. Kyndt F. Redon R. Le Marec H. Froguel P. Ellinor P.T. Vasan R.S. Bruneval P. Markwald R.R. Norris R.A. Milan D.J. Slaugenhaupt S.A. Levine R.A. Schott J.-J. Hagege A.A. MVP-France Jeunemaitre X. Network L.T.M. Genetic association analyses highlight biological pathways underlying mitral valve prolapse.Nat. Genet. 2015; 47: 1206Crossref PubMed Scopus (68) Google Scholar). For a fifth locus, several proteins were found at similar levels in the left atria, PAFAH1B1, SRR, TSR1, and SMG6. After querying the PheWAS database (17Bycroft C. Freeman C. Petkova D. Band G. Elliott L.T. Sharp K. Motyer A. Vukcevic D. Delaneau O. O'Connell J. Cortes A. Welsh S. McVean G. Leslie S. Donnelly P. Marchini J. Genome-wide genetic data on ∼500,000 UK Biobank participants.bioRxiv. 2017; Google Scholar) we consider SMG6 as the most likely of these candidates (supplemental Fig. S4). Taken together, we suggest that genes LMCD1, TNS1, PITPNB, CBR1, and SMG6 are likely candidates underlying the identification of specific loci in the MVP GWAS. The greatest biological signal in our dataset was found when comparing the atrial proteome to that of the left ventricle, allowing detailed insights into their functional specialization at the protein level. As will be discussed in a separate section, the vast majority (>98%) of the atrial proteome was not different between RA and LA. We thus analyzed major differences in the atrial versus ventricular proteome combining all atrial samples. Global statistical analysis identified a total of 741 proteins significantly over-represented in atria or ventricle (Fig. 3, supplemental Fig. S5, supplemental Table S3). Approximately half of these proteins (366 of them) have previously been reported as differentially expressed ((supplemental Fig. S3C), including MYL7 (the atrial isoform of the myosin regulatory chain 2 (18Small E.M. Krieg P.A. Molecular Regulation of Cardiac Chamber-Specific Gene Expression.Trends Cardiovascular Med. 2004; 14: 13-18Crossref PubMed Scopus (55) Google Scholar, 19Hailstones D. Barton P. Thomas P. Sasse S. Sutherland C. Hardeman E. Gunning P. Differential regulation of the atrial isoforms of the myosin light chains during striated muscle development.J. Biol. Chem. 1992; 267: 23295-23300Abstract Full Text PDF PubMed Google Scholar)), DKK3 (expressed in adult atrial myocytes but absent in ventricles (20Krupnik V.E. Sharp J.D. Jiang C. Robison K. Chickering T.W. Amaravadi L. Brown D.E. Guyot
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