. 2023 Dec;2(12):1159-1172.

doi: 10.1038/s44161-023-00375-y. Epub 2023 Dec 4.

Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification

Paul S de Vries¹, Matthew P Conomos², Kuldeep Singh³, Christopher J Nicholson³, Deepti Jain², Natalie R Hasbani¹, Wanlin Jiang³, Sujin Lee³, Christian L Lino Cardenas³, Sharon M Lutz^{4

5}, Doris Wong⁶, Xiuqing Guo⁷, Jie Yao⁷, Erica P Young⁸, Catherine Tcheandjieu^{9

10}, Austin T Hilliard^{9

11}, Joshua C Bis¹², Lawrence F Bielak¹³, Michael R Brown¹, Shaila Musharoff^{9

14}, Shoa L Clarke^{9

10}, James G Terry¹⁵, Nicholette D Palmer¹⁶, Lisa R Yanek¹⁷, Huichun Xu¹⁸, Nancy Heard-Costa^{19

20}, Jennifer Wessel^{21

22}, Margaret Sunitha Selvaraj^{23

24

25}, Rebecca H Li³, Xiao Sun^{26

27}, Adam W Turner⁶, Adrienne M Stilp², Alyna Khan², Anne B Newman²⁸, Asif Rasheed²⁹, Barry I Freedman³⁰, Brian G Kral³¹, Caitlin P McHugh², Chani Hodonsky⁶, Danish Saleheen^{29

32

33}, David M Herrington³⁴, David R Jacobs Jr³⁵, Deborah A Nickerson^{36

37}, Eric Boerwinkle^{1

38}, Fei Fei Wang², Gerardo Heiss³⁹, Goo Jun¹, Greg L Kinney⁴⁰, Haakon H Sigurslid³, HarshaVardhan Doddapaneni³⁸, Ira M Hall⁴¹, Isabela M Bensenor⁴², Jai Broome², James D Crapo⁴³, James G Wilson⁴⁴, Jennifer A Smith^{13

45}, John Blangero^{46

47}, Jose D Vargas⁴⁸, Jose Verdezoto Mosquera⁶, Joshua D Smith^{36

37}, Karine A Viaud-Martinez⁴⁹, Kathleen A Ryan¹⁸, Kendra A Young⁴⁰, Kent D Taylor⁷, Leslie A Lange⁵⁰, Leslie S Emery², Marcio S Bittencourt⁴², Matthew J Budoff⁵¹, May E Montasser¹⁸, Miao Yu¹³, Michael C Mahaney^{46

47}, Mohammed S Mahamdeh³, Myriam Fornage^{1

52}, Nora Franceschini⁵³, Paulo A Lotufo⁴², Pradeep Natarajan^{23

24

25}, Quenna Wong², Rasika A Mathias^{17

54}, Richard A Gibbs^{38

55}, Ron Do^{56

57}, Roxana Mehran⁵⁸, Russell P Tracy⁵⁹, Ryan W Kim⁶⁰, Sarah C Nelson², Scott M Damrauer^{61

62}, Sharon L R Kardia¹³, Stephen S Rich⁶, Valentin Fuster^{63

64}, Valerio Napolioni⁶⁵, Wei Zhao¹³, Wenjie Tian³, Xianyong Yin⁶⁶, Yuan-I Min⁶⁷, Alisa K Manning^{68

69}, Gina Peloso⁷⁰, Tanika N Kelly²⁷, Christopher J O'Donnell^{71

72}, Alanna C Morrison¹, Joanne E Curran^{46

47}, Warren M Zapol⁷³, Donald W Bowden¹⁶, Lewis C Becker³¹, Adolfo Correa^{67

74}, Braxton D Mitchell^{18

75}, Bruce M Psaty^{12

76

77}, John Jeffrey Carr¹⁵, Alexandre C Pereira^{78

79}, Themistocles L Assimes^{9

10}, Nathan O Stitziel^{8

80

81}, John E Hokanson⁴⁰, Cecelia A Laurie², Jerome I Rotter⁷, Ramachandran S Vasan^{20

82

83}, Wendy S Post³¹, Patricia A Peyser¹³, Clint L Miller⁶, Rajeev Malhotra³

Affiliations

¹ Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
² Genetic Analysis Center, Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA.
³ Cardiovascular Research Center, Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
⁴ PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
⁵ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁶ Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA.
⁷ The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
⁸ Cardiovascular Division, Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO, USA.
⁹ VA Palo Alto Healthcare System, Palo Alto, CA, USA.
¹⁰ Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
¹¹ Palo Alto Veterans Institute for Research, Palo Alto, CA, USA.
¹² Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA.
¹³ School of Public Health, Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA.
¹⁴ Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
¹⁵ Department of Radiology, Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, TN, USA.
¹⁶ Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA.
¹⁷ Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
¹⁸ Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
¹⁹ Boston University School of Medicine, Boston, MA, USA.
²⁰ Boston University and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA.
²¹ Department of Epidemiology, Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA.
²² Diabetes Translational Research Center, Indiana University, Indianapolis, IN, USA.
²³ Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
²⁴ Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
²⁵ Department of Medicine, Harvard Medical School, Boston, MA, USA.
²⁶ School of Public Health and Tropical Medicine, Department of Epidemiology, Tulane University, New Orleans, LA, USA.
²⁷ College of Medicine, Department of Medicine, Division of Nephrology, University of Illinois Chicago, Chicago, IL, USA.
²⁸ Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
²⁹ Center For Non-Communicable Diseases, Karachi, Pakistan.
³⁰ Section on Nephrology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA.
³¹ Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
³² Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA.
³³ Department of Cardiology, Columbia University Irving Medical Center, New York, NY, USA.
³⁴ Department of Internal Medicine, Section of Cardiovascular Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA.
³⁵ Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA.
³⁶ Department of Genome Sciences, University of Washington, Seattle, WA, USA.
³⁷ Northwest Genomics Center, University of Washington, Seattle, WA, USA.
³⁸ Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
³⁹ Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
⁴⁰ Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
⁴¹ Yale Center for Genomic Health, Yale School of Medicine, New Haven, CT, USA.
⁴² Center for Clinical and Epidemiological Research, University Hospital, University of Sao Paulo Medical School, São Paulo, Brazil.
⁴³ Department of Medicine, National Jewish Health, Denver, CO, USA.
⁴⁴ Division of Cardiology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
⁴⁵ Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA.
⁴⁶ Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA.
⁴⁷ South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA.
⁴⁸ Medstar Heart and Vascular Institute, Medstar Georgetown University Hospital, Washington, DC, USA.
⁴⁹ Illumina Laboratory Services, Illumina Inc., San Diego, CA, USA.
⁵⁰ Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA.
⁵¹ Department of Medicine, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
⁵² Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA.
⁵³ Department of Epidemiology, Gillings School of Global Public health, University of North Carolina, Chapel Hill, NC, USA.
⁵⁴ Division of Allergy and Clinical Immunology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
⁵⁵ Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
⁵⁶ The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁵⁷ Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁵⁸ Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁵⁹ Department of Pathology and Laboratory Medicine, Robert Larner, M.D. College of Medicine, University of Vermont, Burlington, VT, USA.
⁶⁰ Psomagen Inc., Rockville, MD, USA.
⁶¹ Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
⁶² Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
⁶³ Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid, Spain.
⁶⁴ Mount Sinai Heart Center, New York, NY, USA.
⁶⁵ Genomic And Molecular Epidemiology (GAME) Lab, School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy.
⁶⁶ Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.
⁶⁷ Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
⁶⁸ Clinical and Translation Epidemiology Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
⁶⁹ Programs in Metabolism and Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
⁷⁰ Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
⁷¹ VA Boston Healthcare System, Boston, MA, USA.
⁷² Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
⁷³ Department of Anesthesia, Critical Care and Pain Medicine at Massachusetts General Hospital, Boston, MA, USA.
⁷⁴ Department of Population Health Science, University of Mississippi Medical Center, Jackson, MS, USA.
⁷⁵ Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA.
⁷⁶ Department of Epidemiology, University of Washington, Seattle, WA, USA.
⁷⁷ Department of Health Services, University of Washington, Seattle, WA, USA.
⁷⁸ Department of Genetics, Harvard Medical School, Boston, MA, USA.
⁷⁹ Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo, Brazil.
⁸⁰ Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA.
⁸¹ McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.
⁸² Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
⁸³ Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.

PMID: 38817323
PMCID: PMC11138106
DOI: 10.1038/s44161-023-00375-y

Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification

Paul S de Vries et al. Nat Cardiovasc Res. 2023 Dec.

. 2023 Dec;2(12):1159-1172.

doi: 10.1038/s44161-023-00375-y. Epub 2023 Dec 4.

Authors

Affiliations

¹ Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
² Genetic Analysis Center, Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA.
³ Cardiovascular Research Center, Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
⁴ PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
⁵ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁶ Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA.
⁷ The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
⁸ Cardiovascular Division, Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO, USA.
⁹ VA Palo Alto Healthcare System, Palo Alto, CA, USA.
¹⁰ Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
¹¹ Palo Alto Veterans Institute for Research, Palo Alto, CA, USA.
¹² Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA.
¹³ School of Public Health, Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA.
¹⁴ Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
¹⁵ Department of Radiology, Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, TN, USA.
¹⁶ Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA.
¹⁷ Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
¹⁸ Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
¹⁹ Boston University School of Medicine, Boston, MA, USA.
²⁰ Boston University and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA.
²¹ Department of Epidemiology, Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA.
²² Diabetes Translational Research Center, Indiana University, Indianapolis, IN, USA.
²³ Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
²⁴ Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
²⁵ Department of Medicine, Harvard Medical School, Boston, MA, USA.
²⁶ School of Public Health and Tropical Medicine, Department of Epidemiology, Tulane University, New Orleans, LA, USA.
²⁷ College of Medicine, Department of Medicine, Division of Nephrology, University of Illinois Chicago, Chicago, IL, USA.
²⁸ Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
²⁹ Center For Non-Communicable Diseases, Karachi, Pakistan.
³⁰ Section on Nephrology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA.
³¹ Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
³² Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA.
³³ Department of Cardiology, Columbia University Irving Medical Center, New York, NY, USA.
³⁴ Department of Internal Medicine, Section of Cardiovascular Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA.
³⁵ Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA.
³⁶ Department of Genome Sciences, University of Washington, Seattle, WA, USA.
³⁷ Northwest Genomics Center, University of Washington, Seattle, WA, USA.
³⁸ Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
³⁹ Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
⁴⁰ Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
⁴¹ Yale Center for Genomic Health, Yale School of Medicine, New Haven, CT, USA.
⁴² Center for Clinical and Epidemiological Research, University Hospital, University of Sao Paulo Medical School, São Paulo, Brazil.
⁴³ Department of Medicine, National Jewish Health, Denver, CO, USA.
⁴⁴ Division of Cardiology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
⁴⁵ Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA.
⁴⁶ Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA.
⁴⁷ South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA.
⁴⁸ Medstar Heart and Vascular Institute, Medstar Georgetown University Hospital, Washington, DC, USA.
⁴⁹ Illumina Laboratory Services, Illumina Inc., San Diego, CA, USA.
⁵⁰ Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA.
⁵¹ Department of Medicine, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
⁵² Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA.
⁵³ Department of Epidemiology, Gillings School of Global Public health, University of North Carolina, Chapel Hill, NC, USA.
⁵⁴ Division of Allergy and Clinical Immunology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
⁵⁵ Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
⁵⁶ The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁵⁷ Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁵⁸ Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁵⁹ Department of Pathology and Laboratory Medicine, Robert Larner, M.D. College of Medicine, University of Vermont, Burlington, VT, USA.
⁶⁰ Psomagen Inc., Rockville, MD, USA.
⁶¹ Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
⁶² Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
⁶³ Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid, Spain.
⁶⁴ Mount Sinai Heart Center, New York, NY, USA.
⁶⁵ Genomic And Molecular Epidemiology (GAME) Lab, School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy.
⁶⁶ Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.
⁶⁷ Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
⁶⁸ Clinical and Translation Epidemiology Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
⁶⁹ Programs in Metabolism and Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
⁷⁰ Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
⁷¹ VA Boston Healthcare System, Boston, MA, USA.
⁷² Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
⁷³ Department of Anesthesia, Critical Care and Pain Medicine at Massachusetts General Hospital, Boston, MA, USA.
⁷⁴ Department of Population Health Science, University of Mississippi Medical Center, Jackson, MS, USA.
⁷⁵ Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA.
⁷⁶ Department of Epidemiology, University of Washington, Seattle, WA, USA.
⁷⁷ Department of Health Services, University of Washington, Seattle, WA, USA.
⁷⁸ Department of Genetics, Harvard Medical School, Boston, MA, USA.
⁷⁹ Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo, Brazil.
⁸⁰ Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA.
⁸¹ McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.
⁸² Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
⁸³ Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.

PMID: 38817323
PMCID: PMC11138106
DOI: 10.1038/s44161-023-00375-y

Abstract

Coronary artery calcification (CAC) is a measure of atherosclerosis and a well-established predictor of coronary artery disease (CAD) events. Here we describe a genome-wide association study (GWAS) of CAC in 22,400 participants from multiple ancestral groups. We confirmed associations with four known loci and identified two additional loci associated with CAC (ARSE and MMP16), with evidence of significant associations in replication analyses for both novel loci. Functional assays of ARSE and MMP16 in human vascular smooth muscle cells (VSMCs) demonstrate that ARSE is a promoter of VSMC calcification and VSMC phenotype switching from a contractile to a calcifying or osteogenic phenotype. Furthermore, we show that the association of variants near ARSE with reduced CAC is likely explained by reduced ARSE expression with the G allele of enhancer variant rs5982944. Our study highlights ARSE as an important contributor to atherosclerotic vascular calcification, and a potential drug target for vascular calcific disease.

PubMed Disclaimer

Conflict of interest statement

Bruce M. Psaty serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. Leslie S. Emery is now an employee of Celgene/Bristol Myers Squibb. Celgene/Bristol Myers Squibb had no role in the funding, design, conduct, or interpretation of this study. Nathan O. Stitziel has received research funding from Regeneron Pharmaceuticals, unrelated to this work. Karine A. Viaud-Martinez is an employee at Illumina Inc. Ryan W. Kim is an employee at Psomagen Inc. Roxona Mehran reports institutional research grants from Abbott Laboratories, Abiomed, Applied Therapeutics, AstraZeneca, Bayer, Beth Israel Deaconess, Bristol-Myers Squibb, CERC, Chiesi, Concept Medical, CSL Behring, DSI, Medtronic, Novartis Pharmaceuticals, OrbusNeich; consultant fees from Abbott Laboratories, Boston Scientific, CardiaWave, Chiesi, Janssen Scientific Affairs, Medscape/WebMD, Medtelligence (Janssen Scientific Affairs), Roivant Sciences, Sanofi, Siemens Medical Solutions; consultant fees paid to the institution from Abbott Laboratories, Bristol-Myers Squibb; advisory board, funding paid to the institution from Spectranetics/Philips/Volcano Corp; consultant (spouse) from Abiomed, The Medicines Company, Merck; Equity <1% from Claret Medical, Elixir Medical; DSMB Membership fees paid to the institution from Watermark Research Partners; consulting (no fee) from Idorsia Pharmaceuticals Ltd., Regeneron Pharmaceuticals; Associate Editor for ACC, AMA. Rajeev Malhotra is a consultant for MyoKardia (now owned by BMS), Epizon Pharma, Renovacor, and Third Pole, a co-founder of Patch and Angea Biotherapeutics, and has received research funding from Angea Biotherapeutics, Bayer Pharmaceuticals, and Amgen. Adrienne M. Stilp receives funding from Seven Bridges Genomics to develop tools for the NHLBI BioData Catalyst consortium. Pradeep Natarajan reports grants from Amgen, Apple, Boston Scientific, AstraZeneca, Allelica, Novartis, and Genentech, consulting income from GV, Blackstone Life Sciences, Foresite Labs, Apple, AstraZeneca, Allelica, Novartis, HeartFlow, and Genentech, is a scientific advisor to Esperion Therapeutics, Preciseli, and TenSixteen Bio, is a scientific co-founder of TenSixteen Bio, and spousal employment at Vertex, all unrelated to the present work. Clint L. Miller received a research grant from AstraZeneca for an unrelated project. The remaining authors declare no competing interests.

Figures

**Extended Data Fig. 1:. Coronary artery calcification levels across *ARSE* index variant genotypes suggest a recessive mode of inheritance.**
Mean log (coronary artery calcification + 1) across genotypes for index variants at ARSE. Error bars indicate the 95% confidence interval for the mean (n=22,400).

**Extended Data Fig. 2:. Co-localization of genetic associations with coronary artery calcification and genetic associations with *ARSE* expression in a) cultured fibroblasts and b) aorta.**
These plots were created with Locuscomparer (https://github.com/boxiangliu/locuscomparer) using the African 1000G ph3 reference population to calculate the linkage disequilibrium r. Unadjusted two-sided P values are provided. The posterior probability for causal variant sharing was 99.9% in cultured fibroblasts and 8.9% in aorta.

**Extended Data Fig. 3:. Co-localization of genetic associations with coronary artery calcification and genetic associations with *MMP16* expression in aorta.**
This plot was created with Locuscomparer (https://github.com/boxiangliu/locuscomparer) using the European 1000G ph3 reference population to calculate the linkage disequilibrium r. Unadjusted two-sided P values are provided. The posterior probability for causal variant sharing was 81.9%.

**Extended Data Fig. 4:. Cell type-specific gene expression of *ARSE* and *MMP16* in an integrated human atherosclerosis reference dataset.**
**(a-b)** Uniform Manifold Approximation and Projection (UMAP) embeddings from an integrated human carotid and coronary artery atherosclerosis single-cell RNA-seq reference dataset (Methods), showing **(a)** *ARSE* and **(b)** *MMP16*, normalized gene expression depicted by the heatmap from SCTransform normalized read counts. Individual sequencing libraries across four studies were harmonized after QC and batch correction with reciprocal PCA (rPCA). Clusters were annotated with level 1 cell type labels using transfer learning with cell labels from the Tabula Sapiens vasculature subset. Level 2 cell type label for endothelial-mesenchymal transition (EndoMT) endothelial cells expressing ARSE and MMP16 are also highlighted. **(c-d)** Scatter plots showing the normalized expression level of **(c)** *ARSE* and **(d)** *MMP16*, across the level 1 cell types. EC: Endothelial cells; SMC: Smooth muscle cells; T/NK: T cells and Natural Killer cells; pDC: plasmacytoid dendritic cells.

**Extended Data Fig. 5:. Silencing *MMP16* expression has no effect on osteogenic phenotypic switching in human coronary artery vascular smooth muscle cells.**
a) Treatment of human coronary artery vascular smooth muscle cells (n = 6 biologically independent samples in each group) with osteogenic media decreased *MMP16* mRNA expression by ~74% (left panel). Treatment of cells grown in osteogenic media with siMMP16 (resulting in >90% knockdown of *MMP16* mRNA) had no effect on *RUNX2* (middle panel) or *CNN1* (right panel) mRNA levels. Statistical comparisons were made using a two-tailed one-way ANOVA with Sidak’s post-hoc comparison testing. The mean ± SEM is depicted in plots. b) Treatment of human coronary artery vascular smooth muscle cells grown in osteogenic media with siMMP16 had no effect on calcification, as evidenced by decreased Alizarin Red S staining.

**Extended Data Fig. 6:. Silencing *ARSE* expression increases contractile gene expression in human aortic vascular smooth muscle cells.**
Silencing ARSE in cells (n = 12 biologically independent samples in each group) grown in normal media increased a) *ACTA2* and b) *TAGLN* mRNA levels by ~ 56% and 35%, respectively. Statistical comparisons were made using a two-tailed Student t test. The mean is depicted in plots, with the error bars representing the standard error of the mean.

**Extended Data Fig. 7:. Human aortic vascular smooth muscle cell calcification, bone and contractile marker expression, and contractility are affected by changes in *ARSE* expression.**
a) Treatment of human aortic vascular smooth muscle cells (n = 12 biologically independent samples in each group) with osteogenic media increased *ARSE* mRNA expression > 2-fold. b) Treatment of cells grown in osteogenic media with siARSE (resulting in >90% knockdown of *ARSE* mRNA) decreased *RUNX2 (*left panel), and *BGLAP (*middle panel) mRNA levels by ~20% and ~43% respectively, and increased CNN1 mRNA levels by > 150% (right panel). Silencing ARSE in cells grown in normal media increased CNN1 mRNA levels by > 2.5-fold. c) Treatment of cells grown in osteogenic media with siARSE reduced calcification, as evidenced by decreased Alizarin Red S staining (n=5 biologically independent samples in each group). d) Reduced ARSE expression in cells grown in collagen discs (left panel) resulted in a >3-fold increase in contraction (right panel, n=6 biologically independent samples in each group). e) Protein expression of ARSE, RUNX2 and CNN1 were confirmed by Western blot using antibodies directed against ARSE, RUNX2, CNN1 and GAPDH (for a loading control). Adenoviral expression of the 70-kDa isoform of ARSE in human aortic vascular smooth muscle cells was associated with a >15-fold increase in RUNX2 protein levels and an approximately 34% decrease in CNN1 protein levels, when cells were harvested 5 days after viral transduction (n=3 biologically independent samples in each group). f) As shown by Alizarin Red staining, increased ARSE expression resulted in augmented calcification in human aortic vascular smooth muscle cells (n=3 biologically independent samples in each group). g) Increased ARSE expression also caused a >70% decrease (right panel, n=6 biologically independent samples in each group) in contraction of human aortic vascular smooth muscle cells grown in collagen discs (left panel). Statistical comparisons were made using either a two-tailed one-way ANOVA with Sidak’s post-hoc comparison testing or a two-tailed Student t test. The mean is depicted in plots, with the error bars representing the standard error of the mean.

**Extended Data Fig. 8:. ARSE expression and calcification in normal and ischemic human coronary arteries.**
a) Cross sections of human coronary arteries from control subjects and patients with ischemic coronary artery disease (n=3 individuals in each group with 2 sections stained for each individual) were stained for ARSE (red), α-smooth muscle actin (green) and DNA (blue, DAPI). Immunofluorescence analysis shows a higher expression of ARSE in diseased arteries. Alizarin red staining for calcification was high in the coronary arteries of diseased patients with no significant stain observed in the control group. Scale bars, 200 µm for each immunofluorescence image; 500 µm for each Alizarin red staining image. Statistical comparisons were made using a two-tailed Student’s t test. The mean is depicted in plots, with the error bars representing the standard error of the mean. b) Cross sections of human coronary arteries (n=1 each for control and ischemic patient) were stained for ARSE (red), RUNX2 (green, VSMC calcification marker) and DNA (blue, DAPI). Immunofluorescence analysis shows a higher expression of ARSE in calcified diseased arteries that colocalized with increased RUNX2 expression. Scale bar 500 µm.

**Extended Data Fig. 9:. Luciferase reporter assay to analyze the functional impact of SNP rs5982944 (A/G).**
The rs5982944-A allele and rs5982944-G allele firefly luciferase constructs were co-transfected with renilla luciferase plasmid into human coronary smooth muscle cells (HCSMCs), human aortic smooth muscle cells (HASMCs) and HEK-293 cells (n=6 biologically independent samples for HCSMCs and HASMCs and n=5 biologically independent samples for HEK-293). Firefly luciferase activity and renilla luciferase activity (internal control reporter vector) were measured sequentially in cell lysates. Firefly luciferase activity in cell lysates transfected with either the rs5982944-A construct or the rs5982944-G construct was normalized to renilla luciferase activity. The mean is depicted in plots, with the error bars representing the standard error of the mean. Statistical comparisons were made using the two-tailed unpaired t-test.

**Extended Data Fig. 10:. Model of ARSE-induced phenotype switch from contractile to osteogenic vascular smooth muscle cells.**
Atherosclerotic vascular calcification is characterized by the phenotype switch of vascular smooth muscle cells (VSMCs) from a contractile phenotype to a proliferative, osteogenic phenotype. The osteogenic phenotype of VSMCs is characterized by decreased expression of contractile proteins such as calponin (CNN1), but increased expression of Runt-related transcription factor 2 (RUNX2), a master regulator of the phenotype switch, in addition to other markers of calcification such as bone gamma-carboxyglutamate protein (BGLAP) and alkaline phosphatase (ALPL). We identified ARSE as a major regulator of the phenotype switch.

**Fig. 1:. Manhattan plot for the genome-wide association study of log(CAC+1).**
In the Manhattan plot, each genetic variant is inluded as a dot, with the position on the x axis corresponding to their genomic position and the position on the y axis corresponding to the significance the association, denoted by –log₁₀ transformed two-sided P-values. The plot shows 6 genetic loci (including 2 novel and 4 known) associated with coronary artery calcification score at a significance level of P <5×10⁻ (dotted line) in the pooled analysis of 22,400 individuals from 10 studies.

**Fig. 2:. Silencing *ARSE* expression inhibits osteogenic phenotype switch in human coronary artery vascular smooth muscle cells.**
a) Treatment of human coronary artery vascular smooth muscle cells (n = 6 biologically independent samples in each group) with osteogenic media for 3 days increased *ARSE* mRNA expression approximately 5-fold. Treatment of cells grown in osteogenic media with siARSE resulted in >90% knockdown of *ARSE* mRNA. b) Protein expression of ARSE was measured by immunoblot (left panel) using antibodies directed against ARSE and GAPDH (for a loading control). Treatment of cells with osteogenic media increased ARSE protein levels by 1.5-fold (right panel). Treatment of cells grown in osteogenic media with siARSE resulted in >70% reduction of *ARSE* protein (n=4 biologically independent samples in each group). c) Treatment of cells grown in osteogenic media with siARSE ameliorated osteogenic phenotype switch as evidenced by decreased *RUNX2*, *BGLAP*, and *ALPL* mRNA levels, and increased *CNN1* mRNA levels ~2-fold. Of note, silencing *ARSE* in cells grown in normal media increased *CNN1* mRNA levels by > 5-fold (n=6 biologically independent samples in each group except n=5 for siARSE CNN1 data). d) Reduced *ARSE* expression was also associated with an approximately 50% decrease in RUNX2 and >30% increase in CNN1 protein levels assessed by immunoblot using antibodies directed against RUNX2, CNN1 and VCL (for a loading control) (n=6 biologically independent samples in each group). e) Treatment of cells grown in osteogenic media with siARSE reduced calcification by approximately 60% (right panel, n = 3 biologically independent samples in each group), as evidenced by decreased Alizarin Red staining (left panel). f) Reduced ARSE expression with siARSE treatment in human coronary artery vascular smooth muscle cells grown in collagen discs (left panel) resulted in a >3-fold increase in contraction (right panel, n=6 biologically independent samples in each group). Statistical comparisons were made using either a two-tailed one-way ANOVA with Sidak’s post-hoc comparison testing (for more than two groups) or a two-tailed Student t test (for two groups). The mean is depicted in plots, with the error bars representing the mean ± the standard error of the mean.

**Fig. 3:. Overexpression of *ARSE* induces calcification in human coronary artery vascular smooth muscle cells.**
a) Adenoviral expression of ARSE in human coronary artery vascular smooth muscle cells was associated with an 8-fold increase in RUNX2 protein levels and an approximately 70% decrease in CNN1 protein levels, when cells were harvested 5 days after viral transduction (n=3 biologically independent samples in each group). Protein expression was determined by immunoblot (left panel) using antibodies directed against ARSE, RUNX2, CNN1 and GAPDH (for a loading control) with quantification shown in the right panel. b) As shown by Alizarin Red staining (left panel), increased ARSE expression resulted in augmented calcification in human coronary artery vascular smooth muscle cells (right panel, n = 3 biologically independent samples in each group). Two independent experiments were performed with representative images shown. c) Increased ARSE expression also caused a >70% decrease (right panel, n=6 biologically independent samples in each group) in contraction of human coronary artery vascular smooth muscle cells grown in collagen discs (left panel). Statistical comparisons were made using a two-tailed Student t test. The mean is depicted in plots, with the error bars representing the mean ± the standard error of the mean.

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Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification

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Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification

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