Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma


Autoři: Yosuke Tanigawa aff001;  Michael Wainberg aff001;  Juha Karjalainen aff002;  Tuomo Kiiskinen aff004;  Guhan Venkataraman aff001;  Susanna Lemmelä aff004;  Joni A. Turunen aff006;  Robert R. Graham aff008;  Aki S. Havulinna aff004;  Markus Perola aff005;  Aarno Palotie aff002;  ;  Mark J. Daly aff002;  Manuel A. Rivas aff001
Působiště autorů: Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California, United States of America aff001;  Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America aff002;  Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America aff003;  Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland aff004;  Finnish Institute for Health and Welfare, Helsinki, Finland aff005;  Department of Ophthalmology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland aff006;  Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland aff007;  Maze Therapeutics, South San Francisco, California, United States of America aff008
Vyšlo v časopise: Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma. PLoS Genet 16(5): e32767. doi:10.1371/journal.pgen.1008682
Kategorie: Research Article
doi: 10.1371/journal.pgen.1008682

Souhrn

Protein-altering variants that are protective against human disease provide in vivo validation of therapeutic targets. Here we use genotyping data from UK Biobank (n = 337,151 unrelated White British individuals) and FinnGen (n = 176,899) to conduct a search for protein-altering variants conferring lower intraocular pressure (IOP) and protection against glaucoma. Through rare protein-altering variant association analysis, we find a missense variant in ANGPTL7 in UK Biobank (rs28991009, p.Gln175His, MAF = 0.8%, genotyped in 82,253 individuals with measured IOP and an independent set of 4,238 glaucoma patients and 250,660 controls) that significantly lowers IOP (β = -0.53 and -0.67 mmHg for heterozygotes, -3.40 and -2.37 mmHg for homozygotes, P = 5.96 x 10−9 and 1.07 x 10−13 for corneal compensated and Goldman-correlated IOP, respectively) and is associated with 34% reduced risk of glaucoma (P = 0.0062). In FinnGen, we identify an ANGPTL7 missense variant at a greater than 50-fold increased frequency in Finland compared with other populations (rs147660927, p.Arg220Cys, MAF Finland = 4.3%), which was genotyped in 6,537 glaucoma patients and 170,362 controls and is associated with a 29% lower glaucoma risk (P = 1.9 x 10−12 for all glaucoma types and also protection against its subtypes including exfoliation, primary open-angle, and primary angle-closure). We further find three rarer variants in UK Biobank, including a protein-truncating variant, which confer a strong composite lowering of IOP (P = 0.0012 and 0.24 for Goldman-correlated and corneal compensated IOP, respectively), suggesting the protective mechanism likely resides in the loss of interaction or function. Our results support inhibition or down-regulation of ANGPTL7 as a therapeutic strategy for glaucoma.

Klíčová slova:

Alleles – Cornea – Eyes – Genome-wide association studies – Genotyping – Glaucoma – Intraocular pressure – Variant genotypes


Zdroje

1. Cantor LB. Brimonidine in the treatment of glaucoma and ocular hypertension. Therapeutics and Clinical Risk Management. 2006. pp. 337–346. doi: 10.2147/tcrm.2006.2.4.337 18360646

2. Kass MA, Heuer DK, Higginbotham EJ, Johnson CA, Keltner JL, Miller JP, et al. The Ocular Hypertension Treatment Study: a randomized trial determines that topical ocular hypotensive medication delays or prevents the onset of primary open-angle glaucoma. Arch Ophthalmol. 2002;120: 701–13; discussion 829–30. doi: 10.1001/archopht.120.6.701 12049574

3. Kazemian P, Lavieri MS, Van Oyen MP, Andrews C, Stein JD. Personalized Prediction of Glaucoma Progression Under Different Target Intraocular Pressure Levels Using Filtered Forecasting Methods. Ophthalmology. 2018;125: 569–577. doi: 10.1016/j.ophtha.2017.10.033 29203067

4. The Japanese Archive of Multicentral Database in Glaucoma (JAMDIG) construction group. A novel method to predict visual field progression more accurately, using intraocular pressure measurements in glaucoma patients. Scientific Reports. 2016. doi: 10.1038/srep31728 27562553

5. MacGregor S, Ong J-S, An J, Han X, Zhou T, Siggs OM, et al. Genome-wide association study of intraocular pressure uncovers new pathways to glaucoma. Nat Genet. 2018;50: 1067–1071. doi: 10.1038/s41588-018-0176-y 30054594

6. Khawaja AP, Cooke Bailey JN, Wareham NJ, Scott RA, Simcoe M, Igo RP Jr, et al. Genome-wide analyses identify 68 new loci associated with intraocular pressure and improve risk prediction for primary open-angle glaucoma. Nat Genet. 2018;50: 778–782. doi: 10.1038/s41588-018-0126-8 29785010

7. Choquet H, Thai KK, Yin J, Hoffmann TJ, Kvale MN, Banda Y, et al. A large multi-ethnic genome-wide association study identifies novel genetic loci for intraocular pressure. Nat Commun. 2017;8: 2108. doi: 10.1038/s41467-017-01913-6 29235454

8. Hysi PG, Cheng C-Y, Springelkamp H, Macgregor S, Bailey JNC, Wojciechowski R, et al. Genome-wide analysis of multi-ancestry cohorts identifies new loci influencing intraocular pressure and susceptibility to glaucoma. Nat Genet. 2014;46: 1126–1130. doi: 10.1038/ng.3087 25173106

9. Leshchiner ES, Rush JS, Durney MA, Cao Z, Dančík V, Chittick B, et al. Small-molecule inhibitors directly target CARD9 and mimic its protective variant in inflammatory bowel disease. Proc Natl Acad Sci U S A. 2017;114: 11392–11397. doi: 10.1073/pnas.1705748114 29073062

10. Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562: 203–209. doi: 10.1038/s41586-018-0579-z 30305743

11. DeBoever C, Tanigawa Y, Lindholm ME, McInnes G, Lavertu A, Ingelsson E, et al. Medical relevance of protein-truncating variants across 337,205 individuals in the UK Biobank study. Nat Commun. 2018;9: 1612. doi: 10.1038/s41467-018-03910-9 29691392

12. DeBoever C, Tanigawa Y, Aguirre M, McInnes G. Assessing digital phenotyping to enhance genetic studies of human diseases. Am J Hum Genet. 2020; 106: 1–12. doi: 10.1016/j.ajhg.2020.03.007 32275883

13. Lim ET, Würtz P, Havulinna AS, Palta P, Tukiainen T, Rehnström K, et al. Distribution and medical impact of loss-of-function variants in the Finnish founder population. PLoS Genet. 2014;10: e1004494. doi: 10.1371/journal.pgen.1004494 25078778

14. Chan MPY, Grossi CM, Khawaja AP, Yip JLY, Khaw K-T, Patel PJ, et al. Associations with Intraocular Pressure in a Large Cohort: Results from the UK Biobank. Ophthalmology. 2016;123: 771–782. doi: 10.1016/j.ophtha.2015.11.031 26795295

15. Purcell S, Cherny SS, Sham PC. Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits. Bioinformatics. 2003;19: 149–150. doi: 10.1093/bioinformatics/19.1.149 12499305

16. Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016;536: 285–291. doi: 10.1038/nature19057 27535533

17. Cheng J-W, Cheng S-W, Ma X-Y, Cai J-P, Li Y, Lu G-C, et al. Myocilin polymorphisms and primary open-angle glaucoma: a systematic review and meta-analysis. PLoS One. 2012;7: e46632. doi: 10.1371/journal.pone.0046632 23029558

18. Comes N, Buie LK, Borrás T. Evidence for a role of angiopoietin-like 7 (ANGPTL7) in extracellular matrix formation of the human trabecular meshwork: implications for glaucoma. Genes Cells. 2011;16: 243–259. doi: 10.1111/j.1365-2443.2010.01483.x 21199193

19. Santulli G. Angiopoietin-like proteins: a comprehensive look. Front Endocrinol. 2014;5: 4. doi: 10.3389/fendo.2014.00004 24478758

20. Kuchtey J, Källberg ME, Gelatt KN, Rinkoski T, Komàromy AM, Kuchtey RW. Angiopoietin-like 7 secretion is induced by glaucoma stimuli and its concentration is elevated in glaucomatous aqueous humor. Invest Ophthalmol Vis Sci. 2008;49: 3438–3448. doi: 10.1167/iovs.07-1347 18421092

21. Kolker E, Higdon R, Haynes W, Welch D, Broomall W, Lancet D, et al. MOPED: Model Organism Protein Expression Database. Nucleic Acids Res. 2012;40: D1093–9. doi: 10.1093/nar/gkr1177 22139914

22. Schmidt T, Samaras P, Frejno M, Gessulat S, Barnert M, Kienegger H, et al. ProteomicsDB. Nucleic Acids Res. 2018;46: D1271–D1281. doi: 10.1093/nar/gkx1029 29106664

23. Tarkkanen A, Reunanen A, Kivelä T. Frequency of systemic vascular diseases in patients with primary open-angle glaucoma and exfoliation glaucoma. Acta Ophthalmol. 2008;86: 598–602. doi: 10.1111/j.1600-0420.2007.01122.x 18435818

24. Hirvelä H, Tuulonen A, Laatikainen L. Intraocular pressure and prevalence of glaucoma in elderly people in Finland: a population-based study. Int Ophthalmol. 1994;18: 299–307. doi: 10.1007/bf00917834 7607812

25. Tham Y-C, Li X, Wong TY, Quigley HA, Aung T, Cheng C-Y. Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis. Ophthalmology. 2014;121: 2081–2090. doi: 10.1016/j.ophtha.2014.05.013 24974815

26. Musunuru K, Kathiresan S. Cardiovascular endocrinology: Is ANGPTL3 the next PCSK9? Nat Rev Endocrinol. 2017;13: 503–504. doi: 10.1038/nrendo.2017.88 28707678

27. Musunuru K, Pirruccello JP, Do R, Peloso GM, Guiducci C, Sougnez C, et al. Exome sequencing, ANGPTL3 mutations, and familial combined hypolipidemia. N Engl J Med. 2010;363: 2220–2227. doi: 10.1056/NEJMoa1002926 20942659

28. Gusarova V, O’Dushlaine C, Teslovich TM, Benotti PN, Mirshahi T, Gottesman O, et al. Genetic inactivation of ANGPTL4 improves glucose homeostasis and is associated with reduced risk of diabetes. Nat Commun. 2018;9: 2252. doi: 10.1038/s41467-018-04611-z 29899519

29. Clapham KR, Chu AY, Wessel J, Natarajan P, Flannick J, Rivas MA, et al. A null mutation in ANGPTL8 does not associate with either plasma glucose or type 2 diabetes in humans. BMC Endocr Disord. 2016;16: 7. doi: 10.1186/s12902-016-0088-8 26822414

30. Peloso GM, Auer PL, Bis JC, Voorman A, Morrison AC, Stitziel NO, et al. Association of low-frequency and rare coding-sequence variants with blood lipids and coronary heart disease in 56,000 whites and blacks. Am J Hum Genet. 2014;94: 223–232. doi: 10.1016/j.ajhg.2014.01.009 24507774

31. Abu-Farha M, Cherian P, Al-Khairi I, Madhu D, Tiss A, Warsam S, et al. Plasma and adipose tissue level of angiopoietin-like 7 (ANGPTL7) are increased in obesity and reduced after physical exercise. PLoS One. 2017;12: e0173024. doi: 10.1371/journal.pone.0173024 28264047

32. Springelkamp H, Iglesias AI, Mishra A, Höhn R, Wojciechowski R, Khawaja AP, et al. New insights into the genetics of primary open-angle glaucoma based on meta-analyses of intraocular pressure and optic disc characteristics. Hum Mol Genet. 2017;26: 438–453. doi: 10.1093/hmg/ddw399 28073927

33. Rivas MA, Pirinen M, Conrad DF, Lek M, Tsang EK, Karczewski KJ, et al. Human genomics. Effect of predicted protein-truncating genetic variants on the human transcriptome. Science. 2015;348: 666–669. doi: 10.1126/science.1261877 25954003

34. Carnes MU, Allingham RR, Ashley-Koch A, Hauser MA. Transcriptome analysis of adult and fetal trabecular meshwork, cornea, and ciliary body tissues by RNA sequencing. Exp Eye Res. 2018;167: 91–99. doi: 10.1016/j.exer.2016.11.021 27914989

35. Jørgensen AB, Frikke-Schmidt R, Nordestgaard BG, Tybjærg-Hansen A. Loss-of-function mutations in APOC3 and risk of ischemic vascular disease. N Engl J Med. 2014;371: 32–41. doi: 10.1056/NEJMoa1308027 24941082

36. TG and HDL Working Group of the Exome Sequencing Project, National Heart, Lung, and Blood Institute, Crosby J, Peloso GM, Auer PL, Crosslin DR, Stitziel NO, et al. Loss-of-function mutations in APOC3, triglycerides, and coronary disease. N Engl J Med. 2014;371: 22–31. doi: 10.1056/NEJMoa1307095 24941081

37. Cohen JC, Boerwinkle E, Mosley TH Jr, Hobbs HH. Sequence variations in PCSK9, low LDL, and protection against coronary heart disease. N Engl J Med. 2006;354: 1264–1272. doi: 10.1056/NEJMoa054013 16554528

38. Tanigawa Y, Li J, Justesen JM, Horn H, Aguirre M, DeBoever C, et al. Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology. Nat Commun. 2019;10: 4064. doi: 10.1038/s41467-019-11953-9 31492854

39. Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4: 7. doi: 10.1186/s13742-015-0047-8 25722852

40. Conway JR, Lex A, Gehlenborg N. UpSetR: an R package for the visualization of intersecting sets and their properties. Bioinformatics. 2017;33: 2938–2940. doi: 10.1093/bioinformatics/btx364 28645171

41. Genome-wide summary statistics used for the analysis described in “Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma.” National Institutes of Health; 14 Dec 2019 [cited 17 Dec 2019]. https://doi.org/10.35092/yhjc.11368022.v1

42. McCarthy M, O’Brien E. McCarthy Group Front page. In: McCarthy Group [Internet]. 8 Oct 2018 [cited 20 May 2019]. http://mccarthy.well.ox.ac.uk/

43. Van Hout CV, Tachmazidou I, Backman JD, Hoffman JX, Ye B, Pandey AK, et al. Whole exome sequencing and characterization of coding variation in 49,960 individuals in the UK Biobank. bioRxiv. 2019. p. 572347. doi: 10.1101/572347

44. DeBoever C, Aguirre M, Tanigawa Y, Spencer CCA, Poterba T, Bustamante CD, et al. Bayesian model comparison for rare variant association studies of multiple phenotypes. bioRxiv. 2018; 257162. doi: 10.1101/257162

45. Moutsianas L, Agarwala V, Fuchsberger C, Flannick J, Rivas MA, Gaulton KJ, et al. The power of gene-based rare variant methods to detect disease-associated variation and test hypotheses about complex disease. PLoS Genet. 2015;11: e1005165. doi: 10.1371/journal.pgen.1005165 25906071

46. Band G, Le QS, Jostins L, Pirinen M, Kivinen K, Jallow M, et al. Imputation-based meta-analysis of severe malaria in three African populations. PLoS Genet. 2013;9: e1003509. doi: 10.1371/journal.pgen.1003509 23717212

47. Gene-based test results used for the analysis described in “Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma.” National Institutes of Health; 15 Dec 2019 [cited 17 Dec 2019]. https://doi.org/10.35092/yhjc.11369166.v1

48. Yang J, Zeng J, Goddard ME, Wray NR, Visscher PM. Concepts, estimation and interpretation of SNP-based heritability. Nat Genet. 2017;49: 1304–1310. doi: 10.1038/ng.3941 28854176

49. Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet. 2011;88: 76–82. doi: 10.1016/j.ajhg.2010.11.011 21167468

50. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, et al. Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 2010;42: 565–569. doi: 10.1038/ng.608 20562875

51. McInnes G, Tanigawa Y, DeBoever C, Lavertu A, Olivieri JE, Aguirre M, et al. Global Biobank Engine: enabling genotype-phenotype browsing for biobank summary statistics. Bioinformatics. 2019;35: 2495–2497. doi: 10.1093/bioinformatics/bty999 30520965

52. Manichaikul A, Mychaleckyj JC, Rich SS, Daly K, Sale M, Chen W-M. Robust relationship inference in genome-wide association studies. Bioinformatics. 2010;26: 2867–2873. doi: 10.1093/bioinformatics/btq559 20926424

53. Zhou W, Nielsen JB, Fritsche LG, Dey R, Gabrielsen ME, Wolford BN, et al. Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies. Nat Genet. 2018;50: 1335–1341. doi: 10.1038/s41588-018-0184-y 30104761

54. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25: 2078–2079. doi: 10.1093/bioinformatics/btp352 19505943

55. Choquet H, Paylakhi S, Kneeland SC, Thai KK, Hoffmann TJ, Yin J, et al. A multiethnic genome-wide association study of primary open-angle glaucoma identifies novel risk loci. Nat Commun. 2018;9: 2278. doi: 10.1038/s41467-018-04555-4 29891935

56. Shiga Y, Akiyama M, Nishiguchi KM, Sato K, Shimozawa N, Takahashi A, et al. Genome-wide association study identifies seven novel susceptibility loci for primary open-angle glaucoma. Hum Mol Genet. 2018;27: 1486–1496. doi: 10.1093/hmg/ddy053 29452408

Štítky
Genetika Reprodukční medicína

Článek vyšel v časopise

PLOS Genetics


2020 Číslo 5

Nejčtenější v tomto čísle

Tomuto tématu se dále věnují…


Kurzy Doporučená témata Časopisy
Přihlášení
Zapomenuté heslo

Nemáte účet?  Registrujte se

Zapomenuté heslo

Zadejte e-mailovou adresu se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se

VIRTUÁLNÍ ČEKÁRNA ČR Jste praktický lékař nebo pediatr? Zapojte se! Jste praktik nebo pediatr? Zapojte se!

×