Genetic investigation of fibromuscular dysplasia identifies risk loci and shared genetics with common cardiovascular diseases.
Adult
Arteries
Cardiovascular Diseases
/ complications
Cytoskeletal Proteins
/ genetics
Female
Fibroblasts
Fibromuscular Dysplasia
/ complications
Gene Expression Regulation
Genome-Wide Association Study
Humans
Intracranial Aneurysm
Low Density Lipoprotein Receptor-Related Protein-1
/ genetics
Male
Microfilament Proteins
/ genetics
Middle Aged
Plasma Membrane Calcium-Transporting ATPases
/ genetics
Sodium-Calcium Exchanger
/ genetics
Transcriptome
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
15 10 2021
15 10 2021
Historique:
received:
10
11
2020
accepted:
17
09
2021
entrez:
16
10
2021
pubmed:
17
10
2021
medline:
16
11
2021
Statut:
epublish
Résumé
Fibromuscular dysplasia (FMD) is an arteriopathy associated with hypertension, stroke and myocardial infarction, affecting mostly women. We report results from the first genome-wide association meta-analysis of six studies including 1556 FMD cases and 7100 controls. We find an estimate of SNP-based heritability compatible with FMD having a polygenic basis, and report four robustly associated loci (PHACTR1, LRP1, ATP2B1, and LIMA1). Transcriptome-wide association analysis in arteries identifies one additional locus (SLC24A3). We characterize open chromatin in arterial primary cells and find that FMD associated variants are located in arterial-specific regulatory elements. Target genes are broadly involved in mechanisms related to actin cytoskeleton and intracellular calcium homeostasis, central to vascular contraction. We find significant genetic overlap between FMD and more common cardiovascular diseases and traits including blood pressure, migraine, intracranial aneurysm, and coronary artery disease.
Identifiants
pubmed: 34654805
doi: 10.1038/s41467-021-26174-2
pii: 10.1038/s41467-021-26174-2
pmc: PMC8521585
doi:
Substances chimiques
ATP2B1 protein, human
0
Cytoskeletal Proteins
0
LIMA1 protein, human
0
LRP1 protein, human
0
Low Density Lipoprotein Receptor-Related Protein-1
0
Microfilament Proteins
0
PHACTR1 protein, human
0
SLC24A3 protein, human
0
Sodium-Calcium Exchanger
0
Plasma Membrane Calcium-Transporting ATPases
EC 3.6.3.8
Types de publication
Journal Article
Meta-Analysis
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
6031Subventions
Organisme : NCRR NIH HHS
ID : UL1 RR024989
Pays : United States
Organisme : NHLBI NIH HHS
ID : K24 HL137010
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR002548
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL122684
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL086694
Pays : United States
Organisme : NHLBI NIH HHS
ID : R35 HL161016
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL139672
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL148167
Pays : United States
Investigateurs
Peter de Leeuw
(P)
Commentaires et corrections
Type : ErratumIn
Informations de copyright
© 2021. The Author(s).
Références
World Health, O. World Health Statistics 2020: Monitoring Health for the SDGs, Sustainable Development Goals (World Health Organization, Geneva, 2020).
Plouin, P. F. et al. Fibromuscular dysplasia. Orphanet J. Rare Dis. 2, 28 (2007).
doi: 10.1186/1750-1172-2-28
pubmed: 17555581
pmcid: 1899482
Kiando, S. R. et al. PHACTR1 is a genetic susceptibility locus for fibromuscular dysplasia supporting its complex genetic pattern of inheritance. PLoS Genet. 12, e1006367 (2016).
doi: 10.1371/journal.pgen.1006367
pubmed: 27792790
pmcid: 5085032
Gornik, H. L. et al. First International Consensus on the diagnosis and management of fibromuscular dysplasia. Vasc. Med. 24, 164–189 (2019).
doi: 10.1177/1358863X18821816
pubmed: 30648921
Cordonnier, C. et al. Stroke in women - from evidence to inequalities. Nat. Rev. Neurol. 13, 521–532 (2017).
doi: 10.1038/nrneurol.2017.95
pubmed: 28731036
Haider, A. et al. Sex and gender in cardiovascular medicine: presentation and outcomes of acute coronary syndrome. Eur. Heart J. 41, 1328–1336 (2020).
doi: 10.1093/eurheartj/ehz898
pubmed: 31876924
Pappaccogli, M. et al. The european/international fibromuscular dysplasia registry and initiative (feiri)- clinical phenotypes and their predictors based on a cohort of one thousand patients. Cardiovasc. Res. 117, 950–959 (2021).
doi: 10.1093/cvr/cvaa102
pubmed: 32282921
Plouin, P. F. et al. High prevalence of multiple arterial bed lesions in patients with fibromuscular dysplasia: The ARCADIA Registry (Assessment of Renal and Cervical Artery Dysplasia). Hypertension 70, 652–658 (2017).
doi: 10.1161/HYPERTENSIONAHA.117.09539
pubmed: 28716989
Olin, J. W. et al. The United States Registry for fibromuscular dysplasia: results in the first 447 patients. Circulation 125, 3182–3190 (2012).
doi: 10.1161/CIRCULATIONAHA.112.091223
pubmed: 22615343
Hayes, S. N. et al. Spontaneous coronary artery dissection: current state of the science: a scientific statement from the American Heart Association. Circulation 137, e523–e557 (2018).
doi: 10.1161/CIR.0000000000000564
pubmed: 29472380
pmcid: 5957087
Shivapour, D. M., Erwin, P. & Kim, E. Epidemiology of fibromuscular dysplasia: a review of the literature. Vasc. Med. 21, 376–381 (2016).
doi: 10.1177/1358863X16637913
pubmed: 27067138
Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).
doi: 10.1038/ng.3211
pubmed: 25642630
pmcid: 4495769
de Leeuw, C. A., Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput Biol. 11, e1004219 (2015).
doi: 10.1371/journal.pcbi.1004219
pubmed: 25885710
pmcid: 4401657
Watanabe, K., Taskesen, E., van Bochoven, A. & Posthuma, D. Functional mapping and annotation of genetic associations with FUMA. Nat. Commun. 8, 1826 (2017).
doi: 10.1038/s41467-017-01261-5
pubmed: 29184056
pmcid: 5705698
GTEx Consortium. The genotype-tissue expression (GTEx) project. Nat. Genet. 45, 580–585 (2013).
Olin, J. W. et al. A plasma proteogenomic signature for fibromuscular dysplasia. Cardiovasc. Res. 116, 63–77 (2020).
doi: 10.1093/cvr/cvz219
pubmed: 31424497
Gusev, A. et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat. Genet 48, 245–252 (2016).
doi: 10.1038/ng.3506
pubmed: 26854917
pmcid: 4767558
Miller, C. L. et al. Integrative functional genomics identifies regulatory mechanisms at coronary artery disease loci. Nat. Commun. 7, 12092 (2016).
doi: 10.1038/ncomms12092
pubmed: 27386823
pmcid: 4941121
Schmidt, E. M. et al. GREGOR: evaluating global enrichment of trait-associated variants in epigenomic features using a systematic, data-driven approach. Bioinformatics 31, 2601–2606 (2015).
doi: 10.1093/bioinformatics/btv201
pubmed: 25886982
pmcid: 4612390
Kalluri, A. S. et al. Single-cell analysis of the normal mouse aorta reveals functionally distinct endothelial cell populations. Circulation 140, 147–163 (2019).
doi: 10.1161/CIRCULATIONAHA.118.038362
pubmed: 31146585
pmcid: 6693656
Evangelou, E. et al. Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nat. Genet. 50, 1412–1425 (2018).
doi: 10.1038/s41588-018-0205-x
pubmed: 30224653
pmcid: 6284793
Gormley, P. et al. Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine. Nat. Genet. 48, 856–866 (2016).
doi: 10.1038/ng.3598
pubmed: 27322543
pmcid: 5331903
Debette, S. et al. Common variation in PHACTR1 is associated with susceptibility to cervical artery dissection. Nat. Genet. 47, 78–83 (2015).
doi: 10.1038/ng.3154
pubmed: 25420145
Turley, T. N. et al. Identification of susceptibility loci for spontaneous coronary artery dissection. JAMA Cardiol. 5, 1–10 (2020).
doi: 10.1001/jamacardio.2020.0872
pmcid: 7203673
Jones, G. T. et al. Meta-analysis of genome-wide association studies for abdominal aortic aneurysm identifies four new disease-specific risk loci. Circ. Res. 120, 341–353 (2017).
doi: 10.1161/CIRCRESAHA.116.308765
pubmed: 27899403
pmcid: 5253231
van der Harst, P. & Verweij, N. Identification of 64 novel genetic loci provides an expanded view on the genetic architecture of coronary artery disease. Circ. Res. 122, 433–443 (2018).
doi: 10.1161/CIRCRESAHA.117.312086
pubmed: 29212778
pmcid: 5805277
Ni, G., Moser, G., Wray, N. R. & Lee, S. H. Estimation of genetic correlation via linkage disequilibrium score regression and genomic restricted maximum likelihood. Am. J. Hum. Genet. 102, 1185–1194 (2018).
doi: 10.1016/j.ajhg.2018.03.021
pubmed: 29754766
pmcid: 5993419
Hendricks, N. J. et al. Is fibromuscular dysplasia underdiagnosed? A comparison of the prevalence of FMD seen in CORAL trial participants versus a single institution population of renal donor candidates. Vasc. Med. 19, 363–367 (2014).
doi: 10.1177/1358863X14544715
pubmed: 25082538
Giri, A. et al. Trans-ethnic association study of blood pressure determinants in over 750,000 individuals. Nat. Genet. 51, 51–62 (2019).
doi: 10.1038/s41588-018-0303-9
pubmed: 30578418
Bown, M. J. et al. Abdominal aortic aneurysm is associated with a variant in low-density lipoprotein receptor-related protein 1. Am. J. Hum. Genet. 89, 619–627 (2011).
doi: 10.1016/j.ajhg.2011.10.002
pubmed: 22055160
pmcid: 3213391
Saw, J. et al. Chromosome 1q21.2 and additional loci influence risk of spontaneous coronary artery dissection and myocardial infarction. Nat. Commun. 11, 4432 (2020).
doi: 10.1038/s41467-020-17558-x
pubmed: 32887874
pmcid: 7474092
Duan, L. et al. Novel susceptibility loci for moyamoya disease revealed by a genome-wide association study. Stroke 49, 11–18 (2018).
doi: 10.1161/STROKEAHA.117.017430
pubmed: 29273593
Bres, E. E. & Faissner, A. Low density receptor-related protein 1 interactions with the extracellular matrix: more than meets the eye. Front Cell Dev. Biol. 7, 31 (2019).
doi: 10.3389/fcell.2019.00031
pubmed: 30931303
pmcid: 6428713
Au, D. T. et al. LRP1 (Low-Density Lipoprotein Receptor-Related Protein 1) regulates smooth muscle contractility by modulating Ca(2+) signaling and expression of cytoskeleton-related proteins. Arterioscler Thromb. Vasc. Biol. 38, 2651–2664 (2018).
doi: 10.1161/ATVBAHA.118.311197
pubmed: 30354243
pmcid: 6214382
Kobayashi, Y. et al. Mice lacking hypertension candidate gene ATP2B1 in vascular smooth muscle cells show significant blood pressure elevation. Hypertension 59, 854–860 (2012).
doi: 10.1161/HYPERTENSIONAHA.110.165068
pubmed: 22311909
Okuyama, Y. et al. The effects of anti-hypertensive drugs and the mechanism of hypertension in vascular smooth muscle cell-specific ATP2B1 knockout mice. Hypertens. Res. 41, 80–87 (2018).
doi: 10.1038/hr.2017.92
pubmed: 29046519
Yang, H. et al. NCKX3 was compensated by calcium transporting genes and bone resorption in a NCKX3 KO mouse model. Mol. Cell Endocrinol. 454, 93–102 (2017).
doi: 10.1016/j.mce.2017.06.006
pubmed: 28602864
Georges, A. et al. Rare Loss-of-function Mutations of PTGIR are enriched in fibromuscular dysplasia. Cardiovasc. Res. 117, 1154–1165 (2021).
doi: 10.1093/cvr/cvaa161
pubmed: 32531060
Bruno, R. M. et al. Deep vascular phenotyping in patients with renal multifocal fibromuscular dysplasia. Hypertension 73, 371–378 (2019).
doi: 10.1161/HYPERTENSIONAHA.118.12189
pubmed: 30624987
Stanley, J. C., Gewertz, B. L., Bove, E. L., Sottiurai, V. & Fry, W. J. Arterial fibrodysplasia. Histopathologic character and current etiologic concepts. Arch. Surg. 110, 561–566 (1975).
doi: 10.1001/archsurg.1975.01360110107018
pubmed: 1131001
Zhang, Y. Y. et al. A LIMA1 variant promotes low plasma LDL cholesterol and decreases intestinal cholesterol absorption. Science 360, 1087–1092 (2018).
doi: 10.1126/science.aao6575
pubmed: 29880681
Morgado, M., Cairrão, E., Santos-Silva, A. J. & Verde, I. Cyclic nucleotide-dependent relaxation pathways in vascular smooth muscle. Cell Mol. Life Sci. 69, 247–266 (2012).
doi: 10.1007/s00018-011-0815-2
pubmed: 21947498
Gupta, R. M. et al. A genetic variant associated with five vascular diseases is a distal regulator of endothelin-1 gene expression. Cell 170, 522–533.e15 (2017).
doi: 10.1016/j.cell.2017.06.049
pubmed: 28753427
pmcid: 5785707
Adlam, D. et al. Association of the PHACTR1/EDN1 genetic locus with spontaneous coronary artery dissection. J. Am. Coll. Cardiol. 73, 58–66 (2019).
doi: 10.1016/j.jacc.2018.09.085
pubmed: 30621952
Wang, X. & Musunuru, K. Confirmation of causal rs9349379- PHACTR1 expression quantitative trait locus in human-induced pluripotent stem cell endothelial. Cells Circ. Genom. Precis. Med. 11, e002327 (2018).
doi: 10.1161/CIRCGEN.118.002327
pubmed: 30354304
Wiezlak, M. et al. G-actin regulates the shuttling and PP1 binding of the RPEL protein Phactr1 to control actomyosin assembly. J. Cell Sci. 125, 5860–5872 (2012).
doi: 10.1242/jcs.112078
pubmed: 22976292
Trinquart, L., Mounier-Vehier, C., Sapoval, M., Gagnon, N. & Plouin, P. F. Efficacy of revascularization for renal artery stenosis caused by fibromuscular dysplasia: a systematic review and meta-analysis. Hypertension 56, 525–532 (2010).
doi: 10.1161/HYPERTENSIONAHA.110.152918
pubmed: 20625080
Etminan, N. et al. Worldwide incidence of aneurysmal subarachnoid hemorrhage according to region, time period, blood pressure, and smoking prevalence in the population: a systematic review and meta-analysis. JAMA Neurol. 76, 588–597 (2019).
doi: 10.1001/jamaneurol.2019.0006
pubmed: 30659573
pmcid: 6515606
Perez-Lopez, F. R., Larrad-Mur, L., Kallen, A., Chedraui, P. & Taylor, H. S. Gender differences in cardiovascular disease: hormonal and biochemical influences. Reprod. Sci. 17, 511–531 (2010).
doi: 10.1177/1933719110367829
pubmed: 20460551
Yang, H., Yoo, Y. M., Jung, E. M., Choi, K. C. & Jeung, E. B. Uterine expression of sodium/potassium/calcium exchanger 3 and its regulation by sex-steroid hormones during the estrous cycle of rats. Mol. Reprod. Dev. 77, 971–977 (2010).
doi: 10.1002/mrd.21245
pubmed: 21104767
3C Study Group. Vascular factors and risk of dementia: design of the Three-City Study and baseline characteristics of the study population. Neuroepidemiology 22, 316–325 (2003).
Ye, Z., Kalloo, F. S., Dalenberg, A. K. & Kullo, I. J. An electronic medical record-linked biorepository to identify novel biomarkers for atherosclerotic cardiovascular disease. Glob. Cardiol. Sci. Pract. 2013, 82–90 (2013).
pubmed: 24689004
pmcid: 3963733
Dobrowolski, P. et al. Echocardiographic assessment of left ventricular morphology and function in patients with fibromuscular dysplasia: the ARCADIA-POL study. J. Hypertens. 36, 1318–1325 (2018).
doi: 10.1097/HJH.0000000000001706
pubmed: 29528871
Drygas, W. et al. Multi-centre National Population Health Examination Survey (WOBASZ II study): assumptions, methods, and implementation. Kardiol. Pol. 74, 681–690 (2016).
doi: 10.5603/KP.a2015.0235
pubmed: 26620680
Fritsche, L. G. et al. Association of polygenic risk scores for multiple cancers in a phenome-wide study: results from the Michigan Genomics Initiative. Am. J. Hum. Genet. 102, 1048–1061 (2018).
doi: 10.1016/j.ajhg.2018.04.001
pubmed: 29779563
pmcid: 5992124
Rietzschel, E. R. et al. Rationale, design, methods and baseline characteristics of the Asklepios Study. Eur. J. Cardiovasc. Prev. Rehabil. 14, 179–191 (2007).
doi: 10.1097/HJR.0b013e328012c380
pubmed: 17446795
Loh, P. R. et al. Reference-based phasing using the Haplotype Reference Consortium panel. Nat. Genet. 48, 1443–1448 (2016).
doi: 10.1038/ng.3679
pubmed: 27694958
pmcid: 5096458
Das, S. et al. Next-generation genotype imputation service and methods. Nat. Genet. 48, 1284–1287 (2016).
doi: 10.1038/ng.3656
pubmed: 27571263
pmcid: 5157836
Chang, C. C. et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7 (2015).
doi: 10.1186/s13742-015-0047-8
pubmed: 25722852
pmcid: 4342193
Willer, C. J., Li, Y. & Abecasis, G. R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).
doi: 10.1093/bioinformatics/btq340
pubmed: 20616382
pmcid: 2922887
Battle, A., Brown, C. D., Engelhardt, B. E. & Montgomery, S. B. Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).
doi: 10.1038/nature24277
pubmed: 29022597
Liu, B., Gloudemans, M. J., Rao, A. S., Ingelsson, E. & Montgomery, S. B. Abundant associations with gene expression complicate GWAS follow-up. Nat. Genet. 51, 768–769 (2019).
doi: 10.1038/s41588-019-0404-0
pubmed: 31043754
pmcid: 6904208
Giambartolomei, C. et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet. 10, e1004383 (2014).
doi: 10.1371/journal.pgen.1004383
pubmed: 24830394
pmcid: 4022491
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
pubmed: 23104886
doi: 10.1093/bioinformatics/bts635
Shabalin, A. A. Matrix eQTL: ultra fast eQTL analysis via large matrix operations. Bioinformatics 28, 1353–1358 (2012).
doi: 10.1093/bioinformatics/bts163
pubmed: 22492648
pmcid: 3348564
Corces, M. R. et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat. Methods 14, 959–962 (2017).
doi: 10.1038/nmeth.4396
pubmed: 28846090
pmcid: 5623106
Buenrostro, J. D., Wu, B., Chang, H. Y. & Greenleaf, W. J. ATAC-seq: a method for assaying chromatin accessibility genome-wide. Curr. Protoc. Mol. Biol. 109, 21.29.1–21.29.9 (2015).
doi: 10.1002/0471142727.mb2129s109
Afgan, E. et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update. Nucleic Acids Res. 46, W537–W544 (2018).
doi: 10.1093/nar/gky379
pubmed: 29790989
pmcid: 6030816
Amemiya, H. M., Kundaje, A. & Boyle, A. P. The ENCODE blacklist: identification of problematic regions of the genome. Sci. Rep. 9, 9354 (2019).
doi: 10.1038/s41598-019-45839-z
pubmed: 31249361
pmcid: 6597582
Yu, G., Wang, L. G. & He, Q. Y. ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics 31, 2382–2383 (2015).
doi: 10.1093/bioinformatics/btv145
pubmed: 25765347
Ross-Innes, C. S. et al. Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature 481, 389–393 (2012).
doi: 10.1038/nature10730
pubmed: 22217937
pmcid: 3272464
Yu, G., Wang, L. G., Han, Y. & He, Q. Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16, 284–287 (2012).
doi: 10.1089/omi.2011.0118
pubmed: 22455463
pmcid: 3339379
Supek, F., Bosnjak, M., Skunca, N. & Smuc, T. REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS One 6, e21800 (2011).
doi: 10.1371/journal.pone.0021800
pubmed: 21789182
pmcid: 3138752
Freese, N. H., Norris, D. C. & Loraine, A. E. Integrated genome browser: visual analytics platform for genomics. Bioinformatics 32, 2089–2095 (2016).
doi: 10.1093/bioinformatics/btw069
pubmed: 27153568
pmcid: 4937187
Buniello, A. et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 47, D1005–d1012 (2019).
doi: 10.1093/nar/gky1120
pubmed: 30445434
Bakker, M. K. et al. Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors. Nat. Genet. 52, 1303–1313 (2020).
doi: 10.1038/s41588-020-00725-7
pubmed: 33199917
pmcid: 7116530
Malik, R. et al. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat. Genet. 50, 524–537 (2018).
doi: 10.1038/s41588-018-0058-3
pubmed: 29531354
pmcid: 5968830
Zhu, Z. et al. Causal associations between risk factors and common diseases inferred from GWAS summary data. Nat. Commun. 9, 224 (2018).
doi: 10.1038/s41467-017-02317-2
pubmed: 29335400
pmcid: 5768719