#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

A Meta-analysis of Gene Expression Signatures of Blood Pressure and Hypertension


The focus of blood pressure (BP) GWAS has been the identification of common DNA sequence variants associated with the phenotype; this approach provides only one dimension of molecular information about BP. While it is a critical dimension, analyzing DNA variation alone is not sufficient for achieving an understanding of the multidimensional complexity of BP physiology. The top loci identified by GWAS explain only about 1 percent of inter-individual BP variability. In this study, we performed a meta-analysis of gene expression profiles in relation to BP and hypertension in 7017 individuals from six studies. We identified 34 differentially expressed genes for BP, and discovered that the top BP signature genes explain 5%–9% of BP variability. We further linked BP gene expression signature genes with BP GWAS results by integrating expression associated SNPs (eSNPs) and discovered that one of the top BP loci from GWAS, rs3184504 in SH2B3, is a trans regulator of expression of 6 of the top 34 BP signature genes. Our study, in conjunction with prior GWAS, provides a deeper understanding of the molecular and genetic basis of BP regulation, and identifies several potential targets and pathways for the treatment and prevention of hypertension and its sequelae.


Vyšlo v časopise: A Meta-analysis of Gene Expression Signatures of Blood Pressure and Hypertension. PLoS Genet 11(3): e32767. doi:10.1371/journal.pgen.1005035
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1005035

Souhrn

The focus of blood pressure (BP) GWAS has been the identification of common DNA sequence variants associated with the phenotype; this approach provides only one dimension of molecular information about BP. While it is a critical dimension, analyzing DNA variation alone is not sufficient for achieving an understanding of the multidimensional complexity of BP physiology. The top loci identified by GWAS explain only about 1 percent of inter-individual BP variability. In this study, we performed a meta-analysis of gene expression profiles in relation to BP and hypertension in 7017 individuals from six studies. We identified 34 differentially expressed genes for BP, and discovered that the top BP signature genes explain 5%–9% of BP variability. We further linked BP gene expression signature genes with BP GWAS results by integrating expression associated SNPs (eSNPs) and discovered that one of the top BP loci from GWAS, rs3184504 in SH2B3, is a trans regulator of expression of 6 of the top 34 BP signature genes. Our study, in conjunction with prior GWAS, provides a deeper understanding of the molecular and genetic basis of BP regulation, and identifies several potential targets and pathways for the treatment and prevention of hypertension and its sequelae.


Zdroje

1. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, et al. (2003) Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Hypertension 42: 1206–1252. 14656957

2. Levy D, Ehret GB, Rice K, Verwoert GC, Launer LJ, et al. (2009) Genome-wide association study of blood pressure and hypertension. Nat Genet 41: 677–687. doi: 10.1038/ng.384 19430479

3. Ehret GB, Munroe PB, Rice KM, Bochud M, Johnson AD, et al. (2011) Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature 478: 103–109. doi: 10.1038/nature10405 21909115

4. Leonardson AS, Zhu J, Chen Y, Wang K, Lamb JR, et al. (2010) The effect of food intake on gene expression in human peripheral blood. Hum Mol Genet 19: 159–169. doi: 10.1093/hmg/ddp476 19837700

5. Zeller T, Wild P, Szymczak S, Rotival M, Schillert A, et al. (2010) Genetics and beyond—the transcriptome of human monocytes and disease susceptibility. PLoS One 5: e10693. doi: 10.1371/journal.pone.0010693 20502693

6. Bull TM, Coldren CD, Moore M, Sotto-Santiago SM, Pham DV, et al. (2004) Gene microarray analysis of peripheral blood cells in pulmonary arterial hypertension. Am J Respir Crit Care Med 170: 911–919. 15215156

7. Korkor MT, Meng FB, Xing SY, Zhang MC, Guo JR, et al. (2011) Microarray analysis of differential gene expression profile in peripheral blood cells of patients with human essential hypertension. Int J Med Sci 8: 168–179. 21369372

8. Hofman A, van Duijn CM, Franco OH, Ikram MA, Janssen HL, et al. (2011) The Rotterdam Study: 2012 objectives and design update. Eur J Epidemiol 26: 657–686. doi: 10.1007/s10654-011-9610-5 21877163

9. Schurmann C, Heim K, Schillert A, Blankenberg S, Carstensen M, et al. (2012) Analyzing illumina gene expression microarray data from different tissues: methodological aspects of data analysis in the metaxpress consortium. PloS one 7: e50938. doi: 10.1371/journal.pone.0050938 23236413

10. Volzke H, Alte D, Schmidt CO, Radke D, Lorbeer R, et al. (2011) Cohort profile: the study of health in Pomerania. Int J Epidemiol 40: 294–307. doi: 10.1093/ije/dyp394 20167617

11. Storey JD, Tibshirani R (2003) Statistical significance for genomewide studies. Proceedings of the National Academy of Sciences 100: 9440–9445. 12883005

12. Westra H-J, Peters MJ, Esko T, Yaghootkar H, Schurmann C, et al. (2013) Systematic identification of trans eQTLs as putative drivers of known disease associations. Nature genetics 45: 1238–1243. doi: 10.1038/ng.2756 24013639

13. Joehanes R., Huan T., C Yao, X Zhang, S Ying, et al. (2013) Genome-wide Expression Quantitative Trait Loci: Results from the NHLBI’s SABRe CVD Initiative. the American Society of Human Genetics (ASHG) conference. Boston Convention Ctr. Boston, MA.

14. Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, 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. doi: 10.1073/pnas.0903103106 19474294

15. Rowland NE, Li BH, Fregly MJ, Smith GC (1995) Fos induced in brain of spontaneously hypertensive rats by angiotensin II and co-localization with AT-1 receptors. Brain Res 675: 127–134. 7796121

16. Beetz N, Harrison MD, Brede M, Zong X, Urbanski MJ, et al. (2009) Phosducin influences sympathetic activity and prevents stress-induced hypertension in humans and mice. J Clin Invest 119: 3597–3612. doi: 10.1172/JCI38433 19959875

17. Hibino H, Inanobe A, Furutani K, Murakami S, Findlay I, et al. (2010) Inwardly rectifying potassium channels: their structure, function, and physiological roles. Physiol Rev 90: 291–366. doi: 10.1152/physrev.00021.2009 20086079

18. Felix JP, Priest BT, Solly K, Bailey T, Brochu RM, et al. (2012) The inwardly rectifying potassium channel Kir1.1: development of functional assays to identify and characterize channel inhibitors. Assay Drug Dev Technol 10: 417–431. doi: 10.1089/adt.2012.462 22881347

19. Fang L, Li D, Welling PA (2010) Hypertension resistance polymorphisms in ROMK (Kir1.1) alter channel function by different mechanisms. Am J Physiol Renal Physiol 299: F1359–1364. doi: 10.1152/ajprenal.00257.2010 20926634

20. Cappuccio FP, MacGregor GA (1991) Does potassium supplementation lower blood pressure? A meta-analysis of published trials. J Hypertens 9: 465–473. 1649867

21. Geleijnse JM, Kok FJ, Grobbee DE (2003) Blood pressure response to changes in sodium and potassium intake: a metaregression analysis of randomised trials. J Hum Hypertens 17: 471–480. 12821954

22. Fulgoni VL 3rd (2007) Limitations of data on fluid intake. J Am Coll Nutr 26: 588S−591S. 17921470

23. Koliaki C, Katsilambros N (2013) Dietary sodium, potassium, and alcohol: key players in the pathophysiology, prevention, and treatment of human hypertension. Nutr Rev 71: 402–411. doi: 10.1111/nure.12036 23731449

24. Morton J, Coles B, Wright K, Gallimore A, Morrow JD, et al. (2008) Circulating neutrophils maintain physiological blood pressure by suppressing bacteria and IFNgamma-dependent iNOS expression in the vasculature of healthy mice. Blood 111: 5187–5194. doi: 10.1182/blood-2007-10-117283 18281503

25. Harrison DG, Guzik TJ, Lob HE, Madhur MS, Marvar PJ, et al. (2011) Inflammation, immunity, and hypertension. Hypertension 57: 132–140. doi: 10.1161/HYPERTENSIONAHA.110.163576 21149826

26. Harrison DG, Marvar PJ, Titze JM (2012) Vascular inflammatory cells in hypertension. Front Physiol 3: 128. doi: 10.3389/fphys.2012.00128 22586409

27. Harrison DG, Vinh A, Lob H, Madhur MS (2010) Role of the adaptive immune system in hypertension. Curr Opin Pharmacol 10: 203–207. doi: 10.1016/j.coph.2010.01.006 20167535

28. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B (Methodological): 289–300.

29. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, et al. (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 102: 15545–15550. 16199517

30. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, et al. (2000) Gene Ontology: tool for the unification of biology. Nature genetics 25: 25–29. 10802651

31. Kanehisa M, Goto S (2000) KEGG: kyoto encyclopedia of genes and genomes. Nucleic acids research 28: 27–30. 10592173

32. Pruim RJ, Welch RP, Sanna S, Teslovich TM, Chines PS, et al. (2010) LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics 26: 2336–2337. doi: 10.1093/bioinformatics/btq419 20634204

Štítky
Genetika Reprodukčná medicína

Článok vyšiel v časopise

PLOS Genetics


2015 Číslo 3
Najčítanejšie tento týždeň
Najčítanejšie v tomto čísle
Kurzy

Zvýšte si kvalifikáciu online z pohodlia domova

Aktuální možnosti diagnostiky a léčby litiáz
nový kurz
Autori: MUDr. Tomáš Ürge, PhD.

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#