#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network


Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype–phenotype associations, 26 represented phenotypes closely related to previously known genotype–phenotype associations, and 33 represented potentially novel genotype–phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits.


Vyšlo v časopise: Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network. PLoS Genet 9(1): e32767. doi:10.1371/journal.pgen.1003087
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1003087

Souhrn

Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype–phenotype associations, 26 represented phenotypes closely related to previously known genotype–phenotype associations, and 33 represented potentially novel genotype–phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits.


Zdroje

1. PendergrassSA, Brown-GentryK, DudekSM, TorstensonES, AmbiteJL, et al. (2011) The use of phenome-wide association studies (PheWAS) for exploration of novel genotype-phenotype relationships and pleiotropy discovery. Genetic epidemiology 35: 410–422.

2. McCartyCA, ChisholmRL, ChuteCG, KulloIJ, JarvikGP, et al. (2011) The eMERGE Network: a consortium of biorepositories linked to electronic medical records data for conducting genomic studies. BMC medical genomics 4: 13.

3. DennyJC, RitchieMD, BasfordMA, PulleyJM, BastaracheL, et al. (2010) PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations. Bioinformatics 26: 1205–1210.

4. CollinsFS (2004) The case for a US prospective cohort study of genes and environment. Nature 429: 475–477.

5. CollinsFS, ManolioTA (2007) Merging and emerging cohorts: necessary but not sufficient. Nature 445: 259.

6. WillettWC, BlotWJ, ColditzGA, FolsomAR, HendersonBE, et al. (2007) Merging and emerging cohorts: not worth the wait. Nature 445: 257–258.

7. MatiseTC, AmbiteJL, BuyskeS, CarlsonCS, ColeSA, et al. (2011) The Next PAGE in Understanding Complex Traits: Design for the Analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study. American journal of epidemiology 174: 849–859.

8. KathiresanS, MelanderO, GuiducciC, SurtiA, BurttNP, et al. (2008) Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans. Nature genetics 40: 189–197.

9. TeslovichTM, MusunuruK, SmithAV, EdmondsonAC, StylianouIM, et al. (2010) Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466: 707–713.

10. PatelRS, SuS, NeelandIJ, AhujaA, VeledarE, et al. (2010) The chromosome 9p21 risk locus is associated with angiographic severity and progression of coronary artery disease. Eur Heart J 31: 3017–3023.

11. HelgadottirA, ThorleifssonG, ManolescuA, GretarsdottirS, BlondalT, et al. (2007) A common variant on chromosome 9p21 affects the risk of myocardial infarction. Science 316: 1491–1493.

12. SandhuMS, WaterworthDM, DebenhamSL, WheelerE, PapadakisK, et al. (2008) LDL-cholesterol concentrations: a genome-wide association study. Lancet 371: 483–491.

13. WillerCJ, SannaS, JacksonAU, ScuteriA, BonnycastleLL, et al. (2008) Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nature genetics 40: 161–169.

14. WallaceC, NewhouseSJ, BraundP, ZhangF, TobinM, et al. (2008) Genome-wide association study identifies genes for biomarkers of cardiovascular disease: serum urate and dyslipidemia. American journal of human genetics 82: 139–149.

15. SamaniNJ, ErdmannJ, HallAS, HengstenbergC, ManginoM, et al. (2007) Genomewide association analysis of coronary artery disease. N Engl J Med 357: 443–453.

16. ZegginiE, ScottLJ, SaxenaR, VoightBF, MarchiniJL, et al. (2008) Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nature genetics 40: 638–645.

17. JiangCQ, LamTH, LiuB, LinJM, YueXJ, et al. (2010) Interleukin-6 receptor gene polymorphism modulates interleukin-6 levels and the metabolic syndrome: GBCS-CVD. Obesity (Silver Spring) 18: 1969–1974.

18. ZegginiE, WeedonMN, LindgrenCM, FraylingTM, ElliottKS, et al. (2007) Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 316: 1336–1341.

19. SaxenaR, VoightBF, LyssenkoV, BurttNP, de BakkerPI, et al. (2007) Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316: 1331–1336.

20. SalonenJT, UimariP, AaltoJM, PirskanenM, KaikkonenJ, et al. (2007) Type 2 diabetes whole-genome association study in four populations: the DiaGen consortium. American journal of human genetics 81: 338–345.

21. ReinerAP, LettreG, NallsMA, GaneshSK, MathiasR, et al. (2011) Genome-wide association study of white blood cell count in 16,388 African Americans: the continental origins and genetic epidemiology network (COGENT). PLoS Genet 7: e1002108 doi:10.1371/journal.pgen.1002108.

22. CrosslinDR, McDavidA, WestonN, NelsonSC, ZhengX, et al. (2011) Genetic variants associated with the white blood cell count in 13,923 subjects in the eMERGE Network. Hum Genet

23. Wellcome Trust Case Control Consortium (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447: 661–678.

24. LettreG, PalmerCD, YoungT, EjebeKG, AllayeeH, et al. (2011) Genome-wide association study of coronary heart disease and its risk factors in 8,090 African Americans: the NHLBI CARe Project. PLoS Genet 7: e1001300 doi:10.1371/journal.pgen.1001300.

25. IsomaaB, AlmgrenP, TuomiT, ForsenB, LahtiK, et al. (2001) Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes care 24: 683–689.

26. MatiseTC, AmbiteJL, BuyskeS, CarlsonCS, ColeSA, et al. (2011) The Next PAGE in Understanding Complex Traits: Design for the Analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study. American journal of epidemiology 174: 849–859.

27. DumitrescuL, CartyCL, TaylorK, SchumacherFR, HindorffLA, et al. (2011) Genetic Determinants of Lipid Traits in Diverse Populations from the Population Architecture using Genomics and Epidemiology (PAGE) Study. PLoS Genet 7: e1002138 doi:10.1371/journal.pgen.1002138.

28. FesinmeyerMD, NorthKE, RitchieMD, LimU, FranceschiniN, et al. (2012) Genetic Risk Factors for BMI and Obesity in an Ethnically Diverse Population: Results From the Population Architecture Using Genomics and Epidemiology (PAGE) Study. Obesity (Silver Spring).

29. HaimanCA, FesinmeyerMD, SpencerKL, BuzkovaP, VorugantiVS, et al. (2012) Consistent Directions of Effect for Established Type 2 Diabetes Risk Variants Across Populations: The Population Architecture using Genomics and Epidemiology (PAGE) Consortium. Diabetes 61: 1642–1647.

30. HindorffLA, SethupathyP, JunkinsHA, RamosEM, MehtaJP, et al. (2009) Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci U S A 106: 9362–9367.

31. JohnsonAD, O'DonnellCJ (2009) An open access database of genome-wide association results. BMC Med Genet 10: 6.

32. Team TRDC (2009) R: A Language and Environment for Statistical Computing.

33. PendergrassSA, DudekS, CrawfordDC, RitchieMD (2012) Visually integrating and exploring high throughput Phenome-Wide Association (PheWAS) results using PheWAS-View. BioData Min 5: 5.

34. PendergrassSA, DudekSM, CrawfordDC, RitchieMD (2010) Synthesis-View: visualization and interpretation of SNP association results for multi-cohort, multi-phenotype data and meta-analysis. BioData Min 3: 10.

35. PendergrassS, DudekSM, RodenDM, CrawfordDC, RitchieMD (2011) Visual integration of results from a large DNA biobank (biovu) using synthesis-view. Pac Symp Biocomput 265–275.

36. The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC Investigators. American journal of epidemiology 129: 687–702.

37. FriedLP, BorhaniNO, EnrightP, FurbergCD, GardinJM, et al. (1991) The Cardiovascular Health Study: design and rationale. Ann Epidemiol 1: 263–276.

38. Centers for Disease Control and Prevention NCfHS (1994) Plan and operation of the Third National Health and Nutrition Examination Survey, 1988–94. Series 1: programs and collection procedures. Vital Health Stat 1: 1–407.

39. KolonelLN, HendersonBE, HankinJH, NomuraAM, WilkensLR, et al. (2000) A multiethnic cohort in Hawaii and Los Angeles: baseline characteristics. American journal of epidemiology 151: 346–357.

40. Design of the Women's Health Initiative clinical trial and observational study. The Women's Health Initiative Study Group. Control Clin Trials 19: 61–109.

Štítky
Genetika Reprodukčná medicína

Článok vyšiel v časopise

PLOS Genetics


2013 Číslo 1
Najčítanejšie tento týždeň
Najčítanejšie v tomto čísle
Kurzy

Zvýšte si kvalifikáciu online z pohodlia domova

Získaná hemofilie - Povědomí o nemoci a její diagnostika
nový kurz

Eozinofilní granulomatóza s polyangiitidou
Autori: doc. MUDr. Martina Doubková, Ph.D.

Všetky kurzy
Prihlásenie
Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.

Prihlásenie

Nemáte účet?  Registrujte sa

#ADS_BOTTOM_SCRIPTS#