Study design with cohorts in discovery and follow

Supplementary Figure 1
Study design with cohorts in discovery and follow-up and filtration strategy of SNPs.
Nature Genetics: doi:10.1038/ng.3383
Supplementary Figure 2
Igfbp5 expression in mouse developing heart.
Cardiac expression of Igfbp5 (red) was analyzed at embryonic (E13.5), fetal (E17.5) and adult time points. At the time
points investigated, very little Igfbp5 protein was detected in the valves. Expression was observed in the myocardium of
the left and right atria and the primary atrial septum (PAS) at E13.5 and E17.5 (arrows) as well as the coronary
endothelium in the adult (arrow heads). AL, PL, IVS, LV = anterior and posterior mitral leaflets, interventricular septum,
and left ventricle, respectively. Green = MF20 (sarcomeric myosin-myocytes), Blue = Hoescht (nuclei).
Nature Genetics: doi:10.1038/ng.3383
Supplementary Figure 3
In vivo assessment of mitral valve phenotypes in Tns1 total knockout mice using echocardiographs.
Tensin1+/+, wildtype; Tensin1-/-, Tns1 knockout mice. Images were obtained in a four-chamber view of the heart.
Nature Genetics: doi:10.1038/ng.3383
Supplementary Figure 4
In situ hybridizations of tns1 and lmcd1 mRNA distribution in zebrafish embryos.
Top panel shows tns1 expression pattern at 96 hours post fertilization. Expression is found throughout the myocardium,
with highest levels in the outflow tract (right). Lower panel shows lmcd1 expression at 72 hours post fertilization (hpf).
Expression is found in the entire myocardium, with enhanced expression in the ventricular chamber.
Nature Genetics: doi:10.1038/ng.3383
Supplementary Figure 5
In situ hybridizations for developmental markers of valvulogenesis in lmcd1 and tns1 knockdown embryos.
Top panel shows anti-notch1b probe labeling the developing valve in 72-hpf embryos. Lower panel shows anti-bmp4
probe labeling the valve and surrounding myocardium in control (CN) and lmcd1 knockdown embryos. Arrows in both
panels point to the approximate location of the AV valve.
Nature Genetics: doi:10.1038/ng.3383
Supplementary Figure 6
Pitpnb expression in mouse developing heart.
Cardiac expression of Pitpnb (red) was analyzed at embryonic (E13.5), fetal (E17.5) and adult time points. Pitpnb was
detected in valve endothelial and interstitial cells within the mitral leaflets at each of the time points investigated.
Expression was also observed in the epicardium (arrow head) and coronary endothelium (arrow) at E17.5. AL, PL, IVS, LV
= anterior and posterior mitral leaflets, interventricular septum, and left ventricle, respectively. Green = MF20
(sarcomeric myosin-myocytes), Blue = Hoescht (nuclei).
Nature Genetics: doi:10.1038/ng.3383
Supplementary Figure 7
Assessment of cardiac regurgitation in zebrafish morpholino knockdown for genes on Chr17p13.
(a) Genomic context of the association signal observed in the GWAS meta-analysis. (b) Morpholino-mediated
knockdown efficacy. Efficacy for smg6 and sgsm2 in embryonic zebrafish was measured by RT-PCR. (c) Fold change in
observed mitral regurgitation in 72-hpf zebrafish embryos after morpholino-mediated knockdown. All results are
relative to clutchmate controls. n = number of biological replicates per morpholino. (d) Brightfield micrographs
displaying gross morphology of 72-hpf embryos following smg6 or sgsm2 knockdown. Scale bar represents 1 mm. CN =
control morpholino-injected embryos.
Nature Genetics: doi:10.1038/ng.3383
Supplementary Figure 8
Multidimensional scale–based principal-component analysis.
Cases and controls positions on first and second components axis are presented for the two discovery samples (GWAS 1
and GWAS 2). C1, first principal component. C2, second principal component. All individuals plotted are those included
in the discovery GWAS who are all French with European ancestry origin. Cases and controls with non-European
ancestry based on the principal component analyses were excluded before association tests.
Nature Genetics: doi:10.1038/ng.3383
Supplementary Figure 9
Representative gel images from analysis of morpholino efficacy.
rsID indicates the sentinel SNP at the analyzed locus. CN indicates samples amplified from control-injected embryos,
whereas MO indicates amplicons from samples obtained following microinjection of gene-specific morpholino. All
samples were obtained from 72-hpf embryos.
Nature Genetics: doi:10.1038/ng.3383
Supplementary Note Genetic association analyses highlight biological pathways underlying mitral valve prolapse Christian DINA, Nabila BOUATIA-­‐NAJI, Nathan TUCKER, Francesca N. DELLING, Katelynn TOOMER , Ronen DURST, Maelle PERROCHEAU, Leticia FERNANDEZ-­‐FRIERA, Jorge SOLIS for the PROMESA investigators, Thierry LE TOURNEAU, Ming-­‐Huei CHEN, Vincent PROBST, Yohan BOSSE, Philippe PIBAROT, Diana ZELENIKA, Mark LATHROP, Serge HERCBERG, Ronan ROUSSEL, Emelia J. BENJAMIN, Fabrice BONNET, Sun Hao LO, Elena DOLMATOVA, Floriane SIMONET, Simon LECOINTE, Florence KYNDT, Richard REDON, Hervé LE MAREC, Philippe FROGUEL, Patrick T. ELLINOR, Ramachandran S. VASAN, Patrick BRUNEVAL, Russell A. NORRIS, David J. MILAN, Susan A. SLAUGENHAUPT, Robert A. LEVINE, Jean-­‐Jacques SCHOTT, Albert A. HAGEGE for the MVP-­‐France investigators, Xavier JEUNEMAITRE, for the Leducq Transatlantic MITRAL Network Nature Genetics: doi:10.1038/ng.3383
1 Additional Methods Recruitment criteria per centre MVP-­‐France The MVP-­‐France study (Genetic polymorphisms in idiopathic mitral valve prolapse: A French prospective study) is a prospective multicenter nation-­‐wide study promoted by the French Society of Cardiology and aimed at identifying susceptibility genes in MVP using genome wide approaches. Between December 2008 and July 2011, a total of 1094 patients (786 male, mean age 63.2+12.7 years, range 18-­‐90 years) were included from 20 centers. There were 793 (72.5%) surgical patients (surgical repair in 723 patients, valve replacement in 79 patients) and 301 (27.5%) non-­‐operated patients. Clinical data were collected on electronic case report forms. All echography recordings were validated by an echocardiographic core laboratory headed by AH, as were the operative reports. Genetic core laboratory (XJ) centralized the collection of blood samples. Genomic DNA was successfully extracted from peripheral blood lymphocytes of 1082 patients using a commercial isolation kit and following the provider’s procedure (Qiagen®). Approvals were obtained from CPP Ile-­‐de-­‐France VI, (approval n° 60-­‐08, June 25th, 2008), the “Commission Informatique et Libertés” (CNIL) (approval n° 908359, October 14th, 2008) and the French Ministry of Health (ID-­‐RCB: 2008-­‐
A00568-­‐47) and was registered on the ClinicalTrial.Gov website (protocol ID: 2008–01). MVP-­‐Nantes The MVP-­‐Nantes study is a prospective regional study conducted in the western part of France as a companion study of MVP-­‐France. In MVP-­‐Nantes patients referred for a degenerative mitral valve prolapse (MVP) were included from 2 medico-­‐surgical centres (Nantes, Angers) between January 2000 and December 2010. A core laboratory headed by TLT validated echography recordings. Most patients had moderate to severe mitral regurgitation. Surgery was performed in 86% of patients. Clinical and echocardiographic data were recorded at the time of enrolment and a blood sample was withdrawn for genetic purposes. MVP-­‐USA Nature Genetics: doi:10.1038/ng.3383
2 The MVP-­‐USA study is a prospective multicenter nation-­‐wide study that aims to search for susceptibility genes in MVP using genome-­‐wide approaches. Most patients were recruited from the Massachusetts General Hospital Outpatient Cardiac Ultrasound Laboratory and outpatient practices, with contributions from Beth Israel Deaconess Medical Center, Albert Einstein Medical Center in Philadelphia, the University of Wisconsin, and the University of Connecticut Medical Centers; a smaller number of surgical patients were included (MGH, BIDMC). An additional 75 subjects were kindly provided by Simon Ray and Delvac Oceandy from the University of Manchester, UK. Between March 2003 and August 2012 a total of 569 patients (43% female, mean age 61±14 years, range 20-­‐99 years) were recruited. RAL validated all echography recording of patients. Genetic core laboratory (SAS) centralized the collection of blood samples. Genomic DNA was successfully extracted from peripheral blood lymphocytes of patients using a commercial isolation kit (Qiagen®) following the procedure detailed in the kit. PROMESA-­‐CNIC (PROlapso Mitral en cEntros eSpAñoles-­‐Centro Nacional de Investigaciones Carduiovasculares) is a prospective study that has recruited MVP patients referred to Echocardiography Departments from 12 Spanish hospitals between October 2007 and December 2012. Clinical, 2D and 3D echocardiographic data all validated by LF-­‐F and/or JS, and blood samples for genetic studies have been gathered. Withdraw of 10 ml of blood was obtained from each patient and immediately sent to the IFIMAV BIOBANK (Santander, Spain) to subsequently extract DNA. All DNA samples were shipped to Boston (MGH) to perform specific genetic analysis. Additionally, controls defined as volunteers without MVP criteria on 2D echo, were recruited from CNIC (Centro Nacional de Investigaciones Cardiovasculares) for blood sample collection. The study protocol was approved by the Instituto de Salud Carlos III Ethics Committee. Hôpital Européen Georges Pompidou Surgery Cases Patients were enrolled retrospectively from the surgery register of the Cardiovascular Department of HEGP between 2001 and 2013 using computer extraction with the combined diagnostic codes “mitral valve incompetence + degenerative changes”. We included European descent patients referred for mitral valve surgery. In all cases, severe mitral Nature Genetics: doi:10.1038/ng.3383
3 regurgitation due to degenerative MVP was diagnosed preoperatively and confirmed by the operative surgical report and the histologic examination. Mitral valve tissue from mitral valve repair or replacement of the patients was fixed in formalin, paraffin-­‐embedded, and used for diagnosis and research purposes. Informed consent for the possible use of surgical specimen excised during surgery for anonymous research purposes was obtained from the patients, through a general procedure in place at the Hopital Européen Georges Pompidou and according to the principles of the Declaration of Helsinki. DNA was extracted from paraffin slices using QIAamp DNA FFPE Tissue Kit according to the provider’s protocol (Qiagen®). Framingham Heart Study (FHS) The FHS was established as a prospective epidemiologic investigation of a large cohort of men and women of European descent. Beginning in 1948, 5209 participants were enrolled into the Original cohort 1with biennial examination cycles (clinical examinations and echocardiograms at examination cycle 20). Their offspring and their spouses (5124) were enrolled in the Offspring cohort starting in 19712 (clinical examinations and echocardiograms at examination cycles 2,4,5,6,8). Children of the Offspring were enlisted in the Generation 3 cohort (Gen 3, 4095) 3 beginning in 2002 (clinical examination and echocardiograms at examination cycle 1). At each clinic visit, all attendees underwent a routine medical history, targeted physical examination for cardiovascular disease, anthropometry and laboratory assessment of cardiovascular disease risk factors. MVP cases were identified as previously described 4,5 and confirmed by two cardiologists (Emelia J. Benjamin and FND). The total number of participants with MVP and available genotype were 169 (64% women; mean age 56±14 years). Of these 169, 21 participants were from the Original cohort examination cycle 20 (1996-­‐1990), 92 from the Offspring cohort examination cycle 6 (1995-­‐1998), and 56 from the Generation 3 cohort examination cycle 1 (2002-­‐2005). The group of controls consisted of 5575 individuals (54% women; mean age 49±14 years; 516 Original cohort, 1983 Offspring cohort, 3076 Generation 3) without evidence of MVP or non-­‐diagnostic minimal systolic displacement by echocardiography. The Quebec City Case-­‐Control MR Cohort (QCCMRC) Nature Genetics: doi:10.1038/ng.3383
4 One hundred asymptomatic patients with moderate to severe organic mitral regurgitation (defined as an effective regurgitant orifice area ≥20mm² and/or a regurgitant volume ≥30ml), preserved LV ejection fraction (>60%) and normal LV end-­‐systolic diameter (<45mm) were prospectively recruited at the Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ), Quebec, Canada. Patients with the following criteria were excluded: (1) MR due to ischemic heart disease or cardiomyopathy; (2) > mild mitral stenosis, aortic regurgitation, aortic stenosis, or pulmonary stenosis; (3) previous valve operation; (4) history of myocardial infarction or angiographically documented coronary artery stenosis; (5) congenital or pericardial heart disease; (6) endocarditis. Controls were also collected at the IUCPQ and matched in a 1:1 ratio with MR patients for age and gender. All controls underwent cardiac surgery for isolated coronary artery bypass without MR. Control patients having a history of valvular heart disease (at any of the 4 valves) or with significant aortic valve or mitral regurgitation were excluded. Control patients with renal insufficiency (defined with creatinine levels > 150 µmol/l) were also excluded. The study was approved by the ethics committee of the IUCPQ (20758 & 20341). SU.VI.MAX SU.VI.MAX is a national sample of healthy volunteers living in France and enrolled between 1996 and 2001 in a randomized, placebo-­‐controlled trial testing the benefit of anti-­‐oxydants nutrients on the incidence of cancers and cardiovascular diseases6. This population has already been used as a French control population in several GWAS (The International Consortium for Blood Pressure Genome-­‐Wide Association 2011). We included 1,673 individuals, aged 35-­‐65 years at baseline who had genome-­‐wide genotyping available. Cardiac echography was not performed in this population and the MVP status is unknown for all participants. D.E.S.I.R Two sub-­‐populations from D.E.S.I.R. (The Data from the Epidemiological Study on the Insulin Resistance Syndrome 7 were used as controls for the MVP-­‐Nantes and HEGP-­‐Surgery cohorts. D.E.S.I.R 1 are 873 unselected participants from this general population 8 and D.E.S.I.R. 2 are 820 controls identified as nondiabetics and nonobese and were described Nature Genetics: doi:10.1038/ng.3383
5 elsewhere9. MVP status was not available in D.E.S.I.R because of the lack of cardiac echo data in this cohort. GWAS genotyping and quality control Genotyping of the discovery cohorts was independently performed by different genetic platforms that included standard quality control measures of genotyping and data acquisition from diverse high-­‐density genotyping arrays (See Supplementary Table1). We excluded SNPs with a minor allele frequency (MAF) <5%, call rate <95%, monomorphic, and with an exact Hardy Weinberg Equilibrium (HWE) p < 0.0001 in controls and p < 10-­‐7 in demographically homogenous cases to exclude SNPs that show very large deviations. Individuals from the MVP-­‐Nantes and D.E.S.I.R. 1 dataset were genotyped on Axiom Genome-­‐Wide CEU-­‐1 array (Affymetrix, Inc). A final list of 373222 SNPs were used for imputation (188655 SNPs were removed for low MAF or HWE deviation, 5108 SNPs were not found in 1000 genomes panel). Cases from MVP-­‐France study were genotyped on Illumina (Human 660W-­‐Quad) chip while controls from SU.VI.MAX were genotyped on Illumina (Human Hap300). We found a total of 293144 SNPs common between both arrays. After quality control, 243531 SNPs were used for imputation (59012 SNPs were removed for low MAF or HWE deviation, 795 SNPs were not found in the imputation panel). We excluded participants with individual heterozygosity (IHe) level < 10,000, determined as outlier limit after visual inspection (n=26). Direct genotyping in the replication sets MGH cases from the replication Set1 and all cases and controls of Set2 were genotyped at the Massachusetts General Hospital PNGU Core Lab using the Sequenom iPLEX Gold® application and MassARRAY® system. A total of 1107 samples (including 12 duplicate pairs) were genotyped on 4 assay groups comprising custom designed assays (including ancestry informative markers for the demographic analyses, see below). The major steps in this process are the following: primer and multiplex assay design using Sequenom’s MassARRAY® Designer software, DNA amplification by PCR, post-­‐PCR nucleotide deactivation using shrimp Nature Genetics: doi:10.1038/ng.3383
6 alkaline phosphatase (SAP) to remove phosphate groups from unincorporated dNTPs, single-­‐
base extension reaction for allele differentiation, salt removal using ion-­‐exchange resin, and mass correlated genotype calling using SpectroCHIP® array and MALDI-­‐TOF mass spectrometry. Quality control to determine sample and genotyping quality and to remove poorly performing assays and/or samples was performed in PLINK. SNP genotype assays were excluded based on at least one of the following: pass rate < 0.9, minor allele frequency < 0.01, Hardy-­‐Weinberg equilibrium p-­‐value < 0.0001 (N=8). Duplicate pairs (N=12) included in this genotyping showed high concordance rate (r2=0.999). Poorly performing samples were identified using a two-­‐tiered approach in order to control for batch effects during genotyping. If overall sample pass rate (i.e. pass rate across all 4 assay groups) was > 0.9, the sample’s data were included in the final data set. If overall pass rate was < 0.9, we examined the sample pass rate at the assay group level. If the sample had a pass rate> 0.9 for any assay group, the data for that assay group were included. If the pass rate for an assay group was < 0.9, the data for that assay group were zeroed out. Using these thresholds, 34 samples were excluded completely and 40 samples were kept with data from 1 to 3 assay groups zeroed. Imputation To complement directly genotyped SNPs we performed standard large-­‐scale imputation in the four discovery cohorts. First, genotyped SNPs in cases and controls were pre-­‐phased 10 using SHAPE-­‐IT (v1) program 11. Then, the imputation of 4.8 million common SNPs (MAF>0.05 in Europeans, proper-­‐info > 0.4) was carried out using IMPUTE v2 12 in ∼7 Mb chunks of chromosomes. The reference panel used was 1000 Genomes Phase I integrated variant set release (v3), in NCBI build 37 (hg19). For each chromosomal chunk, a set of genetically matched panel of individuals was selected, as recommended by the last strategy used by IMPUTE12. Replication SNPs genotypes in FHS were extracted from a large-­‐scale imputation process performed for previous studies. Haplotypes from genotyped SNPs were pre-­‐phased 10 using MACH13 , and imputation was carried out using minimac software13. Nature Genetics: doi:10.1038/ng.3383
7 Demographic analyses The ancestry of participants was assessed using a multi-­‐dimensional scaling technique implemented in PLINK14. SNPs were selected for short-­‐range linkage disequilibrium (LD) independence. Pruning was performed using a two-­‐step procedure to accommodate the longer range LD. Pruning was done using a two-­‐step procedure to accommodate the longer range LD (this is particularly important as the Axiom Human Array is enriched in SNPs within the HLA region). In a first step we used the threshold r2 < 0.2 within a LD block of 20 kb and 50 SNPs and at a distance of 10 Mb for 100 SNPs on the pruned dataset. Multi-­‐dimensional scaling method was applied on the Identity-­‐By-­‐State matrix. Three matrices were estimated using our cases and controls together with all 1000G populations (IC) and all European (except Finnish) populations (E). Multi-­‐dimensional scaling method was applied on the Identity-­‐By-­‐State matrix using our cases and controls together with all 1000G populations (IC) and all non-­‐Finnish European populations (E). We excluded outliers on the first two components using an expectation-­‐maximization (EM)-­‐fitted Gaussian mixture clustering method implemented in the R package M-­‐CLUST15, assuming one cluster and noise. Outlier position was initialized using a nearest-­‐neighbour-­‐based 16 classification (NNclust in R package PrabClus). Outliers were excluded from the analysis, as previously recommended in GWAS17. Multidimensional scaling (MDS) on the combined cases and controls together with the reference populations from the 1000 Genomes study (www.1000genomes.org) excluded 26 samples of non-­‐European descent in the discovery samples and 15 participants in the replication samples. Statistical Analyses Genome-­‐wide and replication association with MVP status We applied a logistic regression (additive model) as implemented in SNPTEST 12 (options -­‐
frequentist 1 and -­‐score) to test the association with MVP in the GWAS discovery adjusted for the five first principal components as covariates. We also used SNPTEST and/or logistic regression on allele dosage in replication sets when cases and/or controls were imputed for genotypes (FHS in Set 1 and D.E.S.I.R. 2 in Set 4, Supplementary Figure1). In the FHS-­‐MGH analysis, we applied generalized estimation equations18 as implemented in the GWAF R Nature Genetics: doi:10.1038/ng.3383
8 package19, in order to properly account for familial relatedness. For directly genotyped cohorts (Set 2 and Set 3) we used logistic regression as implemented in PLINK. For the GWAS meta-­‐analysis, we applied the inverse normal strategy 20 whereby the summary p-­‐value of each test – and effect direction – are combined into a signed Z-­‐score which, properly weighed, yield a N(m=0, s2=1). Because the number of controls exceeds the number of cases in all studies by far, we used the effective sample size as advised in 21, using METAL software 21. The weight was selected in order to account for effect size difference: W= 4/(1/Ncases+1/Ncontrols). Heterogeneity between individual studies was tested using Cochran Q statistics. Gene prioritization strategy Gene prioritization for functional evaluation was conducted according to: proximity to sentinel SNP, expression level in the heart, presence of eQTL signal in publically available databases, location in previous GWAS signals of cardiovascular diseases or traits and plausible biological relationship with the formation of the mitral valve or an established role in general cardiac development. At the rs12465515 locus, we identified candidate genes IGFBP2, IGFBP5, DIRC3, and TNS1. IGFBP2, IGFBP5, and DIRC3 which were chosen due to proximity to the sentinel SNP and biological candidacy (IGFBP2 and IGFBP5). TNS1 was chosen based upon a moderate eQTL (p=0.01) with rs12465515 in whole blood, as well as an established role in epithelial to mesenchymal transition, a critical pathway in valvulogenesis. There is no clear zebrafish ortholog for DIRC3, and thus we proceeded with knockdown of the remaining genes. There are two zebrafish genes for each of the igfbp candidates (igfbp2a, igfbp2b, igfbp5a, igfbp5b) and a single functional isoform of TNS1 (tns1a), all of which were targeted in the functional studies. At the rs62229266 locus, there are seven target genes within 500kb of the sentinel SNP, however, eQTL datasets strongly link rs62229266 to altered expression of a non-­‐coding RNA (LINC AP000688.8). As lincRNA interspecies conservation is currently poorly understood, we did not pursue functional studies for candidate genes at this locus. Nature Genetics: doi:10.1038/ng.3383
9 At the rs11705555 locus, there are three target genes, MN1, PITPNB, and TTC28, chosen based upon proximity to the sentinel SNP. There is incomplete gene information for MN1 in the zebrafish and given the lack of any eQTL signals we did not pursue functional studies at this locus. At rs171408, the sentinel SNP is intronic to LMCD1 for which there is a single zebrafish ortholog. Additionally, there is a moderate eQTL linking rs171408 genotype to LMCD1 expression in whole blood(p=0.04). As such, we prioritized knockdown of LMCD1 in the zebrafish. At rs216205, although the association locus is intronic to SMG6, there is a moderate eQTL signal to SGSM2 in lower leg skin (p=3e-­‐05). As both of these genes have a single zebrafish ortholog, we pursued them as candidate genes in the functional studies. At rs17767392, none of the three genes (PCNX, SIPA1L1, MAP3K9) within 500kbp of the sentinel SNP had an eQTL, strong cardiac expression, or a clear relationship with cardiac development. As such, we decided not to pursue candidate genes at this locus. Zebrafish experiments At the single-­‐cell stage, fertilized oocytes were injected with 1–10 ng of antisense Morpholino oligonucleotides dissolved in Danieau’s solution (58 mM NaCl, 0.7 mM KCl, 0.4 mM MgSO4, 0.6 mM Ca(NO3)2, 5.0 mM HEPES, pH 7.6). Controls were injected with a non-­‐
targeting morpholino of equal concentration and oligo length, but differing base composition. At 72 hours post-­‐fertilization (hpf), color brightfield images of embryos were acquired on an Olympus SZX16 microscope. High speed videography was performed (FASTEC IN250M512) at 125 frames/second followed by offline analysis and scoring for the presence of AV regurgitation. For proof of morpholino efficacy, embryos were collected at 72 hpf and RNA collected using Tri reagent (Trizol, Invitrogen) according to the manufacturer’s instructions, cDNA was generated using iScript (Biorad), and efficient knockdown was calculated based upon semi-­‐quantitative RT-­‐PCR. Amplification of ef-­‐1a was utilized as a loading control. Nature Genetics: doi:10.1038/ng.3383
10 REFERENCES 1. Dawber, T.R., Meadors, G.F. & Moore, F.E., Jr. Epidemiological approaches to heart disease: the Framingham Study. Am J Public Health Nations Health 41, 279-­‐81 (1951). 2. Kannel, W.B., Feinleib, M., McNamara, P.M., Garrison, R.J. & Castelli, W.P. An investigation of coronary heart disease in families. The Framingham offspring study. Am J Epidemiol 110, 281-­‐90 (1979). 3. Splansky, G.L. et al. The Third Generation Cohort of the National Heart, Lung, and Blood Institute's Framingham Heart Study: design, recruitment, and initial examination. Am J Epidemiol 165, 1328-­‐35 (2007). 4. Delling, F.N. et al. Mild expression of mitral valve prolapse in the Framingham offspring: expanding the phenotypic spectrum. J Am Soc Echocardiogr 27, 17-­‐23 (2014). 5. Freed, L.A. et al. Mitral valve prolapse in the general population: the benign nature of echocardiographic features in the Framingham Heart Study. J Am Coll Cardiol 40, 1298-­‐304 (2002). 6. Hercberg, S. et al. A primary prevention trial using nutritional doses of antioxidant vitamins and minerals in cardiovascular diseases and cancers in a general population: the SU.VI.MAX study-­‐-­‐design, methods, and participant characteristics. SUpplementation en VItamines et Mineraux AntioXydants. Control Clin Trials 19, 336-­‐51 (1998). 7. Balkau, B. [An epidemiologic survey from a network of French Health Examination Centres, (D.E.S.I.R.): epidemiologic data on the insulin resistance syndrome]. Rev Epidemiol Sante Publique 44, 373-­‐5 (1996). 8. Bezzina, C.R. et al. Common variants at SCN5A-­‐SCN10A and HEY2 are associated with Brugada syndrome, a rare disease with high risk of sudden cardiac death. Nat Genet 45, 1044-­‐9 (2013). 9. Sladek, R. et al. A genome-­‐wide association study identifies novel risk loci for type 2 diabetes. Nature 445, 881-­‐5 (2007). 10. Howie, B., Fuchsberger, C., Stephens, M., Marchini, J. & Abecasis, G.R. Fast and accurate genotype imputation in genome-­‐wide association studies through pre-­‐
phasing. Nat Genet 44, 955-­‐9 (2012). 11. Delaneau, O., Marchini, J. & Zagury, J.F. A linear complexity phasing method for thousands of genomes. Nat Methods 9, 179-­‐81 (2012). 12. Marchini, J., Howie, B., Myers, S., McVean, G. & Donnelly, P. A new multipoint method for genome-­‐wide association studies by imputation of genotypes. Nat Genet 39, 906-­‐13 (2007). 13. Li, Y., Willer, C.J., Ding, J., Scheet, P. & Abecasis, G.R. MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet Epidemiol 34, 816-­‐34 (2010). 14. Purcell, S. et al. PLINK: a tool set for whole-­‐genome association and population-­‐
based linkage analyses. Am J Hum Genet 81, 559-­‐75 (2007). 15. Frayley, C. & Raftery, A. MCLUST version 3 for R: normal mixture modeling and model-­‐based clustering. Washington: Department of Statistics, University of Washington Technical report 504.(2006). 16. Byers, S. & Raftery, A. Nearest-­‐Neighbor Clutter Removal for Estimating Features in Spatial Point Processes. Journal of the American Statistical Association 93 (1998). Nature Genetics: doi:10.1038/ng.3383
11 17. 18. 19. 20. 21. Postel-­‐Vinay, S. et al. Common variants near TARDBP and EGR2 are associated with susceptibility to Ewing sarcoma. Nat Genet 44, 323-­‐7 (2012). Liang, K. & Zegger, S. Longitudinal Data Analysis Using Generalized Linear Models. Biometrika 73(1986). Chen, M.H. & Yang, Q. GWAF: an R package for genome-­‐wide association analyses with family data. Bioinformatics 26, 580-­‐1 (2010). Stouffer, S.A., Suchman, E.A., Devinney, L.C., Star, S.A. & R.M., W. The American soldier: adjustment during army life. . 1(1949). Willer, C.J., Li, Y. & Abecasis, G.R. METAL: fast and efficient meta-­‐analysis of genomewide association scans. Bioinformatics 26, 2190-­‐1 (2010). Nature Genetics: doi:10.1038/ng.3383
12 REFERENCES in Supplementary Table4. 1 2 3 4 5 6 7 8 9 10 11 12 Bian, Z. Y. et al. LIM and cysteine-­‐rich domains 1 regulates cardiac hypertrophy by targeting calcineurin/nuclear factor of activated T cells signaling. Hypertension 55, 257-­‐263, doi:10.1161/HYPERTENSIONAHA.109.135665 (2010). Rath, N., Wang, Z., Lu, M. M. & Morrisey, E. E. LMCD1/Dyxin is a novel transcriptional cofactor that restricts GATA6 function by inhibiting DNA binding. Molecular and cellular biology 25, 8864-­‐8873, doi:10.1128/MCB.25.20.8864-­‐8873.2005 (2005). Sureshbabu, A. et al. IGFBP5 induces cell adhesion, increases cell survival and inhibits cell migration in MCF-­‐7 human breast cancer cells. Journal of cell science 125, 1693-­‐
1705, doi:10.1242/jcs.092882 (2012). Lo, S. H., Yu, Q. C., Degenstein, L., Chen, L. B. & Fuchs, E. Progressive kidney degeneration in mice lacking tensin. The Journal of cell biology 136, 1349-­‐1361 (1997). Timio, M. et al. The spectrum of cardiovascular abnormalities in autosomal dominant polycystic kidney disease: a 10-­‐year follow-­‐up in a five-­‐generation kindred. Clinical nephrology 37, 245-­‐251 (1992). Fayet, C., Bendeck, M. P. & Gotlieb, A. I. Cardiac valve interstitial cells secrete fibronectin and form fibrillar adhesions in response to injury. Cardiovascular pathology : the official journal of the Society for Cardiovascular Pathology 16, 203-­‐
211, doi:10.1016/j.carpath.2007.02.008 (2007). Olson, L. E. et al. Protection from doxorubicin-­‐induced cardiac toxicity in mice with a null allele of carbonyl reductase 1. Cancer research 63, 6602-­‐6606 (2003). Derbali, H. et al. Increased biglycan in aortic valve stenosis leads to the overexpression of phospholipid transfer protein via Toll-­‐like receptor 2. The American journal of pathology 176, 2638-­‐2645, doi:10.2353/ajpath.2010.090541 (2010). Aouizerat, B. E. et al. GWAS for discovery and replication of genetic loci associated with sudden cardiac arrest in patients with coronary artery disease. BMC cardiovascular disorders 11, 29, doi:10.1186/1471-­‐2261-­‐11-­‐29 (2011). Schunkert, H. et al. Large-­‐scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nature genetics 43, 333-­‐338, doi:10.1038/ng.784 (2011). Vasan, R. S. et al. Genetic variants associated with cardiac structure and function: a meta-­‐analysis and replication of genome-­‐wide association data. JAMA : the journal of the American Medical Association 302, 168-­‐178, doi:10.1001/jama.2009.978-­‐a (2009). Sotoodehnia, N. et al. Common variants in 22 loci are associated with QRS duration and cardiac ventricular conduction. Nature genetics 42, 1068-­‐1076, doi:10.1038/ng.716 (2010). Nature Genetics: doi:10.1038/ng.3383
13 Additional acknowledgments MVP-­‐France The MVP-­‐France study was supported by the French Society of Cardiology and the French Federation of Cardiology for the financial support. MVP-­‐France was promoted by the French Society of Cardiology help to the “Commission Promotion et Recherche Clinique” (Anissa Bouzamondo and Sophie Thevenin). We also aknowledge the participating centers and investigators of MVP-­‐France (classified by the number of inclusions): >100 patients: Centre Hospitalo-­‐Universitaire Pitié Salpêtrière, Paris (Christophe Acar) ; Groupement Hospitalier Est, Bron (Geneviève Derumeaux, Jean-­‐François Obadia) ; Centre Hospitalo-­‐Universitaire Pontchaillou, Rennes (Erwan Donal, Christophe Leclercq, Alain Leguerrier) ; Hôpital Européen Georges Pompidou, Paris (Jean-­‐Noël Fabiani, Paul Achouh) ; Clinique Saint Augustin, Bordeaux (Eric Abergel, Christophe Chauvel, Patrick Dehant) ; >50 patients: Hôpital du Bocage, Dijon (Jean-­‐Christophe Eicher, Jean-­‐Eric Wolf) ; Hôpital Gabriel-­‐Montpied, Clermont-­‐
Ferrand (Lionel Camilleri, Jean-­‐René Lusson) ; >15 patients: Hôpital Sud, Amiens (Dan Rusinaru, Christophe Tribouilloy) ; Hôpital Charles Nicolle, Rouen (Fabrice Bauer) ; Hôpital Cardiologique du Haut Lévêque, Pessac (Stéphane Lafitte, Patricia Reant, Raymond Roudaut) ; Hôpital de la Cavale Blanche, Brest (Jean-­‐Jacques Blanc, Yves Etienne, Yannick Jobic) ; Hôpital Dupuytren, Limoges (Caroline Etchecopar) ; Centre Hospitalo-­‐Universitaire Arnaud de Villeneuve, Montpellier (Catherine Sportouch-­‐Dukhan) ; < 15 patients: Hôpital Lariboisière, Paris (Damien Logeart) ; Hôpital Saint Antoine, Paris (Ariel Cohen, Stéphane Ederhy) ; Centre Hospitalo-­‐Universitaire Ambroise Paré, Boulogne-­‐Billancourt (Nacera Abbou, Nicolas Mansencal) ; Hôpital de la Timone, Marseille (Jean-­‐François Avierinos, Gilbert Habib) ; Centre Hospitalo-­‐Universitaire Henri Mondor, Créteil (Thibaud Damy, Jean-­‐Luc Monin) ; Institut Cardiologique Paris Sud, Massy (Bertrand Cormier, Marie-­‐Christine Malergue) ; Centre Hospitalo-­‐Universitaire Bichat, Paris (Eric Brochet, Bernard Iung). Nature Genetics: doi:10.1038/ng.3383
14 MVP-­‐Nantes The MVP-­‐Nantes collection was supported by two grants from the Clinical Research Hospital Program (PHRC) from the French Ministry of Health: PHRC-­‐N BRD/07/12-­‐C in 2007 and PHRC-­‐I RC12-­‐0143 in 2012, a grant of the French Cardiology Federation (n° R11065NN -­‐ RAK11093NNA) and by the French Cardio-­‐Vascular Research Foundation – Institut de France through the Danièle Hermann Prize awarded to Pr. Hervé Le Marec. We thank the Genomic Platform of Nantes (Biogenouest Genomics) for technical support. MVP-­‐USA MVP-­‐USA would like to acknowledge the following collaborators for their support in patient recruitment: >75 patients: Drs. Ray Simon, Delvac Oceandy, and Ludwig Neyses from the University of Manchester, UK ; additional contributions : Drs. Erick Avelar and David Ingenyator from the University of CT, Hartford, CT, USA ; Dr. Gregg Pressman from Albert Einstein Medical Center, Philadelphia, PA, USA ; Drs. Feroze Mahmood and Yuchi Han from the Beth Israel-­‐Deaconess Medical Center, Boston, MA, USA ; and Dr. Timothy D. Woods and Leanne Harmann, RDCS, from Medical College of Wisconsin, Milwaukee, WI, USA. PROMESA-­‐CNIC The PROMESA-­‐CNIC study has been supported by the Spanish Society of Cardiology. Special thanks are extended to Jesus Pelaez and Santiago Ruiz de Aguiar (HM Hospitales, Madrid) for their continuous support. Laboratory data was available thanks to the notable work of Ana Berja, Carolina Sanudo and Maria Jose Vidalled from Instituto de Investigacion Marques de Valdecilla (Santander). We also thank Borja Ibañez and Valentin Fuster (CNIC, Madrid) for their unconditional support and all the CNIC investigators, in special to Jose Luis de la Pompa and Maite Dubraska, for their collaboration in this project. D.E.S.I.R The D.E.S.I.R. study has been supported by INSERM contracts with CNAMTS, Lilly, Novartis Pharma and Sanofi-­‐Aventis; by INSERM (Réseaux en Santé Publique, Interactions entre les Nature Genetics: doi:10.1038/ng.3383
15 déterminants de la santé), Cohortes Santé TGIR, the Association Diabète Risque Vasculaire, the Fédération Française de Cardiologie, La Fondation de France, ALFEDIAM, Société francophone du diabète, ONIVINS, Abbott, Ardix Medical, Bayer Diagnostics, Becton Dickinson, Cardionics, Merck Santé, Novo Nordisk, Pierre Fabre, Roche, Topcon. The D.E.S.I.R. Study Group. INSERM U1018: B. Balkau, P. Ducimetière, E. Eschwège; INSERM U367: F. Alhenc-­‐Gelas; CHU D’Angers: A. Girault; INSERM U1138: F. Fumeron, M. Marre, R Roussel; CHU de Rennes: F. Bonnet; CNRS UMR8090, Lille: S. Cauchi, P. Froguel; Centres d’Examens de Santé: Alençon, Angers, Blois, Caen, Chateauroux, Chartres, Cholet, Le Mans, Orléans, Tours; Institute de Recherche Médecine Générale: J. Cogneau; General practitioners of the region; Institute inter-­‐Regional pour la Santé: C. Born, E. Caces, M. Cailleau, O Lantieri, J.G. Moreau, F. Rakotozafy, J. Tichet, S. Vol. Nature Genetics: doi:10.1038/ng.3383
16 PROMESA-­‐CNIC authors Angel Gonzalez Pinto(1), Jose Antonio Garcia-­‐Robles(1), Alicia Barrio(1), Jose Antonio Vazquez de Prada(2), Jose Maria Cuesta(3), Maria Martin(4), Pablo Pazos(5), Marta Sitges(6), Luis Rodriguez Padial(7), Julio Casares(7), Ana Martín (8), Miguel Angel Cavero(9) Gonzalo Pizarro(10), Ana Pastor (10), David Alonso (11) Victoria Piro (12), Laura Fernandez (12), Jorge Solis (13,14), Leticia Fernandez-­‐
Friera (13,14) 1. Hospital Universitario Gregorio Marañon, Madrid, Spain 2. from Hospital Universitario Marques de Valdecilla, Santander), Spain. 3. Hospital Sierralllana, Cantabria, Spain. 4. Hospital Universitario Central de Asturias, Spain. 5. Complejo Hospitalario Universitario A Coruña, Galicia, Spain. 6. Hospital Clinic, Barcelona, Spain. 7. Hospital Virden de la Salud, Toledo, Spain. 8. Hospital Universitario de Salamanca, Spain. 9. Hospital Puerta de Hierro, Madrid, Spain. 10. from Hospital Universitario Quirón, Madrid, Spain 11. Hospital Universitario de Leon, Spain. 12. Hospital Universitario Negrin Gran Canaria, Spain. 13. Hospital Universitario Montepríncipe. Universidad CEU San Pablo, Madrid, Spain 14. Centro Nacional de Investigaciones Cardiovasculares, Carlos III (CNIC), Madrid, Spain. Nature Genetics: doi:10.1038/ng.3383
17 MVP-­‐France authors Christophe Acar (1), Geneviève Derumeaux (2), Jean-­‐François Obadia (2) Erwan Donal (3), Christophe Leclercq(3), Alain Leguerrier(3) Jean-­‐Noël Fabiani(4), Paul Achouh (4), Eric Abergel(5), Christophe Chauvel(5), Patrick Dehant(5), Jean-­‐Christophe Eicher (6), Jean-­‐Eric Wolf (6), Lionel Camilleri (7), Jean-­‐René Lusson(7), Dan Rusinaru (8), Christophe Tribouilloy(8), Fabrice Bauer (9), Stéphane Lafitte (10), Patricia Reant (10), Raymond Roudaut (10), Jean-­‐Jacques Blanc (11), Yves Etienne (11), Yannick Jobic (11), Caroline Etchecopar (12), Catherine Sportouch-­‐Dukhan (13), Damien Logeart (14) Ariel Cohen, Stéphane Ederhy (15) Nacera Abbou (16), Nicolas Mansencal(16), Jean-­‐François Avierinos (17), Gilbert Habib (17), Thibaud Damy (18), Jean-­‐Luc Monin (18), Bertrand Cormier (19), Marie-­‐
Christine Malergue (19), Eric Brochet (20), Bernard Iung (20), Albert A. Hagège (4) 1. Centre Hospitalo-­‐Universitaire Pitié Salpêtrière, Paris, France. 2. Groupement Hospitalier Est, Bron, France. 3. Centre Hospitalo-­‐Universitaire Pontchaillou, Rennes, France. 4. Hôpital Européen Georges Pompidou, Paris, France. 5. Clinique Saint Augustin, Bordeaux, France. 6. Hôpital du Bocage, Dijon, France. 7. Hôpital Gabriel-­‐Montpied, Clermont-­‐Ferrand, France. 8. Hôpital Sud, Amiens, France. 9. Hôpital Charles Nicolle, Rouen, France. 10. Hôpital Cardiologique du Haut Lévêque, Pessac, France. 11. Hôpital de la Cavale Blanche, Brest 12. Hôpital Dupuytren, Limoges 13. Centre Hospitalo-­‐Universitaire Arnaud de Villeneuve, Montpellier 14. Hôpital Lariboisière, Paris 15. Hôpital Saint Antoine, Paris 16. Centre Hospitalo-­‐Universitaire Ambroise Paré, Boulogne-­‐Billancourt 17. Hôpital de la Timone, Marseille 18. Centre Hospitalo-­‐Universitaire Henri Mondor, Créteil 19. Institut Cardiologique Paris Sud, Massy 20. Centre Hospitalo-­‐Universitaire Bichat, Paris
Nature Genetics: doi:10.1038/ng.3383
18 Leducq Transatlantic MITRAL Network authors Albert A. Hagege1,2,3, Christian Dina4,5, Nabila Bouatia-­‐Naji1,2, Nathan Tucker6, Francesca N. Delling7,8, Katelynn Toomer9, Ronen Durst10, Maelle Perrocheau1,2, Leticia Fernandez-­‐Friera11,12, Jorge Solis11,12, Thierry Le Tourneau4,5, Hervé Le Marec4,5, Patrick Bruneval1,2,13, Russell A. Norris9, David J. Milan6, Susan A. Slaugenhaupt14, Jean-­‐Jacques Schott4,5, Xavier Jeunemaitre1,2,15, Robert A. Levine16 1. Inserm UMR970 Paris Cardiovascular Research Center, Paris, France. 2. Paris Descartes University, Paris Sorbonne Cité, Paris, France. 3. AP-­‐HP, Department of Cardiology, Hôpital Européen Georges Pompidou, Paris, France 4. Inserm UMR1087, CNRS UMR 6291, Institut du Thorax, Nantes, France. 5. Centre Hospitalier Universitaire (CHU) Nantes, Université de Nantes, France. 6. Cardiovascular Research Center, Massachusetts General Hospital, Charlestown MA, USA. 7. Framingham Heart Study, Framingham, MA, USA. 8. Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA. 9. Department of Regenerative Medicine and Cell Biology, Cardiovascular Developmental Biology Center, Children's Research Institute, Medical University of South Carolina, Charleston, SC, USA. 10. Cardiology Department, Hadassah Hebrew University Medical Center, Jerusalem, Israel. 11. Hospital Universitario Montepríncipe. Universidad CEU San Pablo, Madrid, Spain 12. Centro Nacional de Investigaciones Cardiovasculares, Carlos III (CNIC), Madrid, Spain. 13. AP-­‐HP, Department of Pathology Hôpital Européen Georges Pompidou, Paris, France. 14. Center for Human Genetic Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA 15. AP-­‐HP, Department of genetics, Hôpital Européen Georges Pompidou, Paris, France. 16. Cardiac Ultrasound Laboratory, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. Nature Genetics: doi:10.1038/ng.3383
19 Supplementary Table1. Clinical and genotyping features of the study populations. Population
Sample Size (F%)
Age at examination Mean (SD)
Country of Origin
Study Design
MVP-­‐France
953 (28)
63.2 (12.7)
France
Clinical recrutment of MVP cases
SU.VI.MAX
1566 (60)
49.8 (6.2)
France
Population-­‐based NA
MVP-­‐Nantes
489 (31)
63.0(12.6)
France
Clinical recrutment of MVP cases
D.E.S.I.R 1
873 (52)
France
MGH Cases
530 (43)
61 (14)
FHS Cases
169 (64)
FHS cohort
Diagnosis method
Genotyping Platform (array if applicable)
Imputation Software
SNPs in Analysis
IMPUTE
4.8 × 106
Illumina (Human Hap300)
IMPUTE
4.8 × 106
Echo and Surgery (90%)
Affymetrix Axiom Genome-­‐
Wide CEU-­‐1
IMPUTE
4.8 × 106
Population-­‐based NA
Affymetrix Axiom Genome-­‐
Wide CEU-­‐1
IMPUTE
4.8 × 106
USA / UK
Multi-­‐center clinical recrutment
Echo
Sequanom
-­‐
47(23 loci)
55.6 (14.2)
USA
Ascertainment of cases from population-­‐based cohort
Echo
Affymetrix 500K + 50K gene-­‐
focused MIP array
minimac
47(23 loci)
5575 (54)
49.0 (14.4)
USA
Ascertainment of controls from population-­‐based cohort
Echo
Affymetrix 500K + 50K gene-­‐
focused MIP array
minimac
47(23 loci)
CNIC Cases
171 (41)
59.1 (16.21)
Spain
Multi-­‐center clinical recrutment Echo
Sequenom
-­‐
47(23 loci)
CNIC Controls
282 (60)
37.3 (10.9)
Spain
Clinical recrutment as controls
Echo
Sequenom
-­‐
47(23 loci)
Canada Cases
102 (47)
62.7 (14.6)
Canada
Clinical recruitment of MVP cases
Echo
KASPTM
-­‐
25
Canada Controls
102 (47)
63.5 (9.8)
Canada
Clinical recruitment as controls Echo
KASPTM
-­‐
25
Surgery (100%)
KASPTM
-­‐
25
NA
Affymetrix Axiom Genome-­‐
Wide CEU-­‐1
IMPUTE
25
Discovery
Echo and Surgery (67.6%) Illumina (Human 660W-­‐Quad)
GWAS 1
GWAS 2
46.7 (10.4)
Follow-­‐up 1
Set 1
Set 2
Follow-­‐up 2
Set 3
Surgery Cases
450 (33)
63.1(13.95)
France
Clinical recrutment from surgery register
D.E.S.I.R 2
810 (67)
55.6 (5.31)
France
Population-­‐based
Set 4
Nature Genetics: doi:10.1038/ng.3383
Supplementary Table2. Association with MVP of loci carried for follow-­‐up and genotyped in all the study populations. One best associated SNP is indicated per locus. Discovery Meta-­‐analysis
Chr
Position
SNP
Locus
rs171408
LMCD1
Risk Global Meta-­‐analysis
Hetereogeneity Freq.
OR [95%CI]
P-­‐valueb
OR [95%CI]
P-­‐valueb
G
0.24
1.30 [1.16-­‐1.47]
5.36E-­‐06
1.32 [1.22-­‐1.43]
1.29E-­‐11
1.08E-­‐01
a
allele
P-­‐valuec
3
8608920
2
217894403
rs12465515
IGFBP5/TNS1
C
0.36
1.33 [1.20-­‐1.47]
1.08E-­‐08
1.25 [1.18-­‐1.33]
3.11E-­‐11
1.45E-­‐01
21
37460271
rs62229266
SETD4/CBR1
T
0.66
1.25 [1.13-­‐1.38]
8.16E-­‐06
1.22 [1.14-­‐1.30]
1.18E-­‐08
6.61E-­‐02
22
28206912
rs11705555
MN1/PITPNB
C
0.73
1.34 [1.21-­‐1.49]
4.47E-­‐08
1.23 [1.15-­‐1.33]
1.39E-­‐08
3.13E-­‐01
17
2196150
rs216205
SMG6
T
0.71
1.35 [1.22-­‐1.50]
3.02E-­‐08
1.24 [1.15-­‐1.33]
1.46E-­‐08
2.75E-­‐01
14
71752344
rs34911660*
PCNX/SIPA1L1
T
0.75
1.26 [1.13-­‐1.40]
3.19E-­‐06
1.23 [1.15-­‐1.32]
2.27E-­‐08
5.22E-­‐01
1
54138854
rs1879734
GLIS1
T
0.28
1.30 [1.15-­‐1.45]
7.10E-­‐06
1.23 [1.14-­‐1.33]
1.22E-­‐07
4.10E-­‐01
6
132397902
rs11962845
CTGF/LOC100507254
A
0.16
1.35 [1.19-­‐1.54]
6.92E-­‐06
1.23 [1.12-­‐1.34]
8.00E-­‐06
6.62E-­‐02
15
77830306
rs869310
HMG20A/LINGO1
T
0.34
1.27 [1.14-­‐1.41]
6.68E-­‐06
1.14 [1.07-­‐1.23]
2.63E-­‐04
6.02E-­‐02
3
14306607
rs9826155*
LSM3/SLC6A6
G
0.53
1.19 [1.08-­‐1.31]
2.36E-­‐07
1.13 [1.06-­‐1.21]
4.29E-­‐04
3.99E-­‐01
16
14013666
rs6498486
ERCC4/MKL2
C
0.70
1.28 [1.15-­‐1.42]
5.95E-­‐06
1.12 [1.04-­‐1.20]
2.08E-­‐03
4.07E-­‐02
4
139173327
rs10002145*
SLC7A11
T
0.59
1.24 [1.13-­‐1.37]
2.96E-­‐06
1.10 [1.03-­‐1.18]
3.53E-­‐03
3.21E-­‐02
3
12815306
rs67177961*
TMEM40/CAND2
G
0.48
1.19 [1.08-­‐1.31]
5.94E-­‐06
1.10 [1.03-­‐1.17]
5.16E-­‐03
1.27E-­‐02
1
164328322
rs1289720
PBX1
G
0.35
1.25 [1.14-­‐1.39]
7.23E-­‐06
1.10[1.03-­‐1.18]
8.97E-­‐03
1.91E-­‐02
1
172788745
rs6686744
FASLG
A
0.53
1.25 [1.14-­‐1.38]
3.20E-­‐06
1.06 [1.00-­‐1.14]
7.51E-­‐02
3.93E-­‐04
a. Alleles are indexed to the forward strand of NCBI Build 37
b. P-­‐values reported are two-­‐sided and based on an inverse-­‐variance weighted meta-­‐analysis model (fixed-­‐effects)
c. P-­‐values are for heterogeneity test between all individual studies (Cochran Q statistics). Nature Genetics: doi:10.1038/ng.3383
Supplementary Table3. Associations with MVP among surgery patients
PVM-­‐France vs SU.VI.MAX
Chr
SNP
Locusa
Risk alleleb
3
rs171408
LMCD1
G
MVP-­‐Nantes vs. D.E.S.I.R 1
OR (95%CI) OR (95%CI) P-­‐
P-­‐value
value
Surgery Cases vs. D.E.S.I.R 2
Combined 1,680 cases vs. 3,259 Controls
OR (95%CI) P-­‐value
OR (95%CI) P-­‐valuec
1.35 [1.15-­‐1.59]
1.14 [0.94-­‐1.39]
1.52 [1.25-­‐1.85]
1.87E-­‐04
0.184
3.62E-­‐05
1.33 [1.20-­‐1.47]
8.23E-­‐08
1.22 [1.03-­‐1.45]
1.12 [0.95-­‐1.33]
1.25 [1.14-­‐1.35]
2
rs12465515
IGFBP5 / TNS1
C
1.33 [1.18-­‐1.54]
1.86E-­‐05
0.0197
0.158
1.15E-­‐06
21
rs62229266
SETD4 / CBR1
T
1.15 [1-­‐1.32]
1.39 [1.18-­‐1.65]
1.05 [0.88-­‐1.24]
1.18 [1.08-­‐1.29]
0.047
0.000116
0.605
2.88E-­‐04
1.36 [1.17-­‐1.57]
1.37 [1.15-­‐1.64]
1.19 [0.99-­‐1.41]
1.31 [1.19-­‐1.44]
3.39E-­‐05
0.000465
0.059
1.88E-­‐08
1.26 [1.05-­‐1.51]
1.15 [0.95-­‐1.38]
1.26 [1.15-­‐1.39]
22
rs11705555
PITPNB / MN1
C
17
rs216205
SMG6
T
1.34 [1.16-­‐1.55]
7.53E-­‐05
0.0151
0.141
2.31E-­‐06
14
rs17767392
PCNX / SIPA1L1
T
1.27 [1.09-­‐1.47]
1.12 [0.93-­‐1.35]
1.31 [1.09-­‐1.57]
1.24 [1.12-­‐1.36]
0.002
0.224
0.004
2.07E-­‐05
OR: odds ratio; 95%CI: 95% confidence interval
a
Locus designed for nearest or the best candidate gene.
Alleles are indexed to the forward strand of NCBI Build 37.
c
P-­‐values reported are two-­‐sided and based on an inverse-­‐variance weighted meta-­‐analysis model (fixed effects).
b
Nature Genetics: doi:10.1038/ng.3383
Supp. Table4. Short literature descriptive of candidate genes near MVP confirmed loci. References are listed in online supplementary note. Locus
LMCD1
Sentinel SNP, Chr and position in the gene
rs171408, Chr3p13, intronic Best candidate gene name
LIM and cysteine-­‐rich domains 1
Comment
LIM domain proteins are important regulators in cell growth, cell fate determination, cell differentiation, and remodeling of the cell cytoskeleton. The LIM and cystein-­‐rich domains 1 (LMCD1) protein plays a critical role in the development of cardiac hypertrophy and fibrosis via activation of calcineurin/nuclear factor of activated T cells signaling pathway 1. LMCD1/dyxin is a sarcomeric Z-­‐disc LIM domain protein able to repress GATA6 activation of lung, vascular smooth-­‐muscle, and cardiac tissue-­‐specific promoters 2, and induce cardiac myocyte hypertrophy in vitro and in vivo 1.
IGFBP5 encodes the most conserved protein of the IGFBP family containing three structural domains with important redundancy among IGFBPs with a common property of modulation of IGF actions. IGFBP5 specifically modulates muscle differentiation and was shown to mediate high glucose induced profibrotic effects IGFBP5 / TNS1
rs12465515, Chr2q35, intergenic
SETD4 / CBR1
rs62229266, Chr21q22, intronic to a ncRNA overlapping CBR1
PITPNB / MN1
rs11705555, Chr22q12, intergenic
in cardian fibroblasts 3. IGFBP5 was also demonstrated to modulate migration and adhesion of cancer cells . TNS1 localizes to focal adhesions, regions of the plasma membrane where the cell attaches to the extracellular matrix. It crosslinks actin filaments and contains a Src homology 2 (SH2) domain, which is often Insulin-­‐like growth factor found in molecules involved in signal transduction. Mice homozygous for a knock-­‐out allele exhibit reduced female fertility, and develop kidney cysts and binding protein 5 / Tensin1 progressive kidney degeneration that may lead to to death from renal failure 4. Polycystic kidney disease (PKD) has been linked to mitral valve prolapse in humans 5. Tensin has also been shown to have a role in the cellular mechanisms of heart valve repair. As demonstrated in an in vitro model of valve injury 6, fibronectin is formed and secreted by valvular interstitial cells (VICs) and is associated with the formation of prominent fibrillar adhesions composed of tensin and integrin. Finally, previous GWAS identified SNPs near TNS1 associated with breast cancer, height, tooth development and thyroid cancer (http://www.genome.gov/gwastudies/). Carbonyl reductase 1
The protein encoded by carbonyl reductase 1 (cbr1) belongs the the short-­‐chain deydrogenases/reductases (SDR) family, which function as NADPH-­‐dependent oxidoreductases having wide specificity for carbonyl compunds. Echocardiography and histological analysis showed that mice with one functional copy of the cbr 1 gene were protected from gross and cellular level doxorubicin-­‐ induced cardiotoxicity 7.
phosphatidylinositol transfer protein, beta Phosphatidylinositol transfer protein, beta (PLTPbeta) is a member of the phospholipid transfer proteins (PLTP). PLTP is an enzyme that catalyzes the exchange of phospholipids between membrane compartments, and has been shown to have a role in the pathophysiology of aortic stenosis. Both biglycan, a proteoglycan 8
that promotes lipid retention within the atherosclerotic plaque, and PLTP were overexpressed in AS valves in a gene expression microarray experiment , suggesting a link between valve matrix and lipid retention in AS. Based on prior GWAS studies, single nucleotide polymorphism (SNP) rs5762311 in the PLTPbeta gene is located in the same locus associated with sudden cardiac arrest in CAD 9.
SMG6
rs216205, Chr17p13, intronic
SMG6 encodes a protein which is part of the telomerase ribonucleoprotein complex responsible for the replication of chroosome termini. The product of this SMG6 nonsense mediated gene also participates in the nonsense-­‐mediated mRNA decay pathway. Based on prior GWAS studies, SNPs rs1231206/rs216172 and rs10852932 in SMG6 are mRNA decay factor
located in the same locus associated with CAD 10 and aortic root size 11, respectively. Small G Protein signalling modulator (SGSM2) is a related gene involved in 11
G protein signalling, and associated with type 2 diabetes, obesity, and cardiac structure and function . PCNX / SIPA1L1
Signal-­‐induced proliferation-­‐associated 1 like 1 (SIPA1L1) protein appears to play a role in non-­‐canonical Wnt signalling and contributes to development. SIPA1L1 rs17767392, Chr14q24, Signal-­‐induced proliferation-­‐
was among the 22 loci associated with QRS duration and cardiac ventricular conduction 12. Rs17767392 is in high LD with the lead SNP associated with QRS intergenic
associated 1 like 1
duration and located in the intron of SIPA1L1 (r2=0.81 in CEU HapMap population). Nature Genetics: doi:10.1038/ng.3383
Supplementary Table 5. Initial list of genes for candidates prioritization for zebrafish knockdown Chromosome 2 rs12465515 IGFBP2 IGFBP5 tnp1 DIRC3 TNS1 eQTL (GTEX) ZF Ortholog(s) ZF Location NCBI Reference no igfbp2a igfbp2b igfbp5a igfbp5b None None tns1a 6: 22,605,873 9: 47,794,282 6:22,594,819 9:47,869,570 6:22450413 GenBank:BX321894 GenBank:BX005007 GenBank:BX321894 GenBank:BX005007 tns1b ZF Ortholog(s) 9:48509924 ZF Location GenBank:AL929460 NCBI Reference None N/A N/A N/A N/A N/A N/A N/A ZF Ortholog(s) ZF Location NCBI Reference mn1a mn1b pitpnb pitpnbl ttc28 ZF Ortholog(s) 10:4,103,592 5:69,672,068 10:4,054,078 3:14,936,862 10:3,737,423 ZF Location GenBank:CABZ01068912 GenBank:CU012044 GenBank:CABZ01068911 GenBank:BX784026 GenBank:CABZ01068908 NCBI Reference lmcd1 22:42,142,822 GenBank:FP102519 N/A
N/A
N/A
N/A
no no no p = 0.01 in whole blood Chromosome 21 eQTL (GTEX) rs62229266 LINC AP000688.8 yes, various tissues (p<3.2x10-­‐7) CBR1 no setd4 no dopey2 no cbr3 no morc3 no chaf1b no cldn14 no Chromosome 22 eQTL (GTEX) rs11705555 MN1 no PITPNB no TTC28 no Chromosome 3 rs171408 LMCD1 eQTL (GTEX) C3orf32 CAV3 OXTR RAD18 p =0.04 in blood, also intronic No No No No Nature Genetics: doi:10.1038/ng.3383
GenBank:BX321894 Chromosome 17 rs216205 SMG6 SGSM2 SRR TSR1 MNT PAFAH1B1 METT10D HIC1 OVCA2 DPH1 RTN4RL1 RPA1 SMYD4 Chromosome 14 rs17767392 PCNX SIPA1L1 MAP3K9 eQTL (GTEX) No, intronic p=3e-­‐05 exposed skin No No No No No No No No No No No eQTL (GTEX) no no no Nature Genetics: doi:10.1038/ng.3383
ZF Ortholog(s) ZF Location NCBI Reference smg6 sgsm2 10:36,608,814 GenBank:BX663516 15:17,062,107 GenBank:CR853297 N/A N/A
N/A N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
ZF Ortholog(s) ZF Location NCBI Reference pcnx pcnxl2 pcnxl3 pcnxl4 sipa1l1 map3k9 13:36,455,584 13:23,893,551 21:26,966,616 13:31,744,139 20:28,675,798 13:36,561,633 GenBank:CR354599 GenBank:BX957342 GenBank:CR405687 GenBank:BX072537 GenBank:BX255891 GenBank:CR354599 Supplementary Table 6. Nucleotide sequences used for morpholinos and morpholino efficacy 72 hours post fertilization (hpf). * E(X)I(X) indicates the exon and intron border which the morpholino targets. Control MO igfbp2a E1I1* igfbp2b E2I2 ifgbp5a I2E3 igfbp5b E1I1 tns1 E17I17 tns1 E18I18 lmcd1 E4E4 lmcd1 E3I3 smg6 E4I4 sgsm2 E4I4 Nature Genetics: doi:10.1038/ng.3383
Sequence ATCCTCTTGAGGCGAACAAAGAGTC CCATCCATTAAAACACATACCGCTG TATAGATGCACACTCACCTGTTTGG TGGACCCTACAGTTAGCAAACATGC TGCTTCCCAGTCAACTTACCAATGG TTTCGAGGTTGATCTTACCAGCTAC GGGATAATTGATGTGTACCTCCTTG TTCTCCACTGCACTCACATATTCAG CTTTCGAATGGTTCTCTTACCAGTT TGTTAGAAAGTGTGTACCGTCTTGC CAGAACAGTGGCCAGTTACCTTGCA Morpholino efficacy (72hpf) 86.3 + 7.1 71.3 + 20.5 46.3 + 9.3 45.7 + 12.5 54.7 + 11.2 85.0 + 3.5 53.3 + 24.9 57.7 + 11.2 54.3 + 10.1 73.0 + 12.5