Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Genetic variants in microRNA genes and targets associated with cardiovascular disease risk factors in the African-American population

Abstract

The purpose of this study is to identify microRNA (miRNA) related polymorphism, including single nucleotide variants (SNVs) in mature miRNA-encoding sequences or in miRNA-target sites, and their association with cardiovascular disease (CVD) risk factors in African-American population. To achieve our objective, we examined 1900 African-Americans from the Atherosclerosis Risk in Communities study using SNVs identified from whole-genome sequencing data. A total of 971 SNVs found in 726 different mature miRNA-encoding sequences and 16,057 SNVs found in the three prime untranslated region (3′UTR) of 3647 protein-coding genes were identified and interrogated their associations with 17 CVD risk factors. Using single-variant-based approach, we found 5 SNVs in miRNA-encoding sequences to be associated with serum Lipoprotein(a) [Lp(a)], high-density lipoprotein (HDL) or triglycerides, and 2 SNVs in miRNA-target sites to be associated with Lp(a) and HDL, all with false discovery rates of 5%. Using a gene-based approach, we identified 3 pairs of associations between gene NSD1 and platelet count, gene HSPA4L and cardiac troponin T, and gene AHSA2 and magnesium. We successfully validated the association between a variant specific to African-American population, NR_039880.1:n.18A>C, in mature hsa-miR-4727-5p encoding sequence and serum HDL level in an independent sample of 2135 African-Americans. Our study provided candidate miRNAs and their targets for further investigation of their potential contribution to ethnic disparities in CVD risk factors.

This is a preview of subscription content, log in to check access.

Fig. 1

References

  1. Agarwal V, Bell GW, Nam JW, Bartel DP (2015) Predicting effective microRNA target sites in mammalian mRNAs. eLife 4:1–38. https://doi.org/10.7554/elife.05005

  2. Austin MA, King MC, Bawol RD, Hulley SB, Friedman GD (1987) Risk factors for coronary heart disease in adult female twins. Genetic heritability and shared environmental influences. Am J Epidemiol 125:308–318

  3. Barter P, Gotto AM, LaRosa JC, Maroni J, Szarek M, Grundy SM, Kastelein JJ, Bittner V, Fruchart J-C (2007) HDL cholesterol, very low levels of LDL cholesterol, and cardiovascular events. N Engl J Med 357:1301–1310

  4. Benjamin EJ, Blaha MJ, Chiuve SE, Cushman M, Das SR, Deo R, de Ferranti SD, Floyd J, Fornage M, Gillespie C, Isasi CR, Jimenez MC, Jordan LC, Judd SE, Lackland D, Lichtman JH, Lisabeth L, Liu SM, Longenecker CT, Mackey RH, Matsushita K, Mozaffarian D, Mussolino ME, Nasir K, Neumar RW, Palaniappan L, Pandey DK, Thiagarajan RR, Reeves MJ, Ritchey M, Rodriguez CJ, Roth GA, Rosamond WD, Sasson C, Towfighi A, Tsao CW, Turner MB, Virani SS, Voeks JH, Willey JZ, Wilkins JT, Wu JHY, Alger HM, Wong SS, Muntner P, Amer Heart Assoc Stat C, Stroke Stat S (2017) Heart disease and stroke statistics-2017 Update A Report From the American Heart Association. Circulation 135:E146–E603. https://doi.org/10.1161/cir.0000000000000485

  5. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B 57:289–300

  6. Bracken CP, Scott HS, Goodall GJ (2016) A network-biology perspective of microRNA function and dysfunction in cancer. Nat Rev Genet 17:719–732. https://doi.org/10.1038/nrg.2016.134

  7. Chatterjee S, Bedja D, Mishra S, Amuzie C, Avolio A, Kass DA, Berkowitz D, Renehan M (2014) Inhibition of glycosphingolipid synthesis ameliorates atherosclerosis and arterial stiffness in apolipoprotein E-/-Mice and rabbits fed a high-fat and -cholesterol diet. Circulation 129:2403–2413. https://doi.org/10.1161/CIRCULATIONAHA.113.007559

  8. Ding SL, Wang JX, Jiao JQ, Tu X, Wang Q, Liu F, Li Q, Gao J, Zhou QY, Gu DF, Li PF (2013) A Pre-microRNA-149 (miR-149) genetic variation affects miR-149 maturation and its ability to regulate the puma protein in apoptosis. J Biol Chem 288:26865–26877. https://doi.org/10.1074/jbc.M112.440453

  9. Do R, Willer CJ, Schmidt EM, Sengupta S, Gao C, Peloso GM, Gustafsson S, Kanoni S, Ganna A, Chen J, Buchkovich ML, Mora S, Beckmann JS, Bragg-Gresham JL, Chang HY, Demirkan A, Den Hertog HM, Donnelly LA, Ehret GB, Esko T, Feitosa MF, Ferreira T, Fischer K, Fontanillas P, Fraser RM, Freitag DF, Gurdasani D, Heikkila K, Hypponen E, Isaacs A, Jackson AU, Johansson A, Johnson T, Kaakinen M, Kettunen J, Kleber ME, Li X, Luan J, Lyytikainen LP, Magnusson PK, Mangino M, Mihailov E, Montasser ME, Muller-Nurasyid M, Nolte IM, O’Connell JR, Palmer CD, Perola M, Petersen AK, Sanna S, Saxena R, Service SK, Shah S, Shungin D, Sidore C, Song C, Strawbridge RJ, Surakka I, Tanaka T, Teslovich TM, Thorleifsson G, Van den Herik EG, Voight BF, Volcik KA, Waite LL, Wong A, Wu Y, Zhang W, Absher D, Asiki G, Barroso I, Been LF, Bolton JL, Bonnycastle LL, Brambilla P, Burnett MS, Cesana G, Dimitriou M, Doney AS, Doring A, Elliott P, Epstein SE, Eyjolfsson GI, Gigante B, Goodarzi MO, Grallert H, Gravito ML, Groves CJ, Hallmans G, Hartikainen AL, Hayward C, Hernandez D, Hicks AA, Holm H, Hung YJ, Illig T, Jones MR, Kaleebu P, Kastelein JJ, Khaw KT et al (2013) Common variants associated with plasma triglycerides and risk for coronary artery disease. Nat Genet 45:1345–1352. https://doi.org/10.1038/ng.2795

  10. Duan R, Pak CH, Jin P (2007) Single nucleotide polymorphism associated with mature miR-125a alters the processing of pri-miRNA. Hum Mol Genet 16:1124–1131. https://doi.org/10.1093/hmg/ddm062

  11. Dubois PCA, Trynka G, Franke L, Hunt KA, Romanos J, Curtotti A, Zhernakova A, Heap GAR, Adány R, Aromaa A, Bardella MT, van den Berg LH, Bockett NA, de la Concha EG, Dema B, Fehrmann RSN, Fernández-Arquero M, Fiatal S, Grandone E, Green PM, Groen HJM, Gwilliam R, Houwen RHJ, Hunt SE, Kaukinen K, Kelleher D, Korponay-Szabo I, Kurppa K, MacMathuna P, Mäki M, Mazzilli MC, McCann OT, Mearin ML, Mein CA, Mirza MM, Mistry V, Mora B, Morley KI, Mulder CJ, Murray JA, Núñez C, Oosterom E, Ophoff RA, Polanco I, Peltonen L, Platteel M, Rybak A, Salomaa V, Schweizer JJ, Sperandeo MP, Tack GJ, Turner G, Veldink JH, Verbeek WHM, Weersma RK, Wolters VM, Urcelay E, Cukrowska B, Greco L, Neuhausen SL, McManus R, Barisani D, Deloukas P, Barrett JC, Saavalainen P, Wijmenga C, van Heel DA (2010) Multiple common variants for celiac disease influencing immune gene expression. Nat Genet 42:295–302. https://doi.org/10.1038/ng.543

  12. Graham G (2015) Disparities in cardiovascular disease risk in the United States. Curr Cardiol Rev 11:238–245

  13. Huang RS, Gamazon ER, Ziliak D, Wen Y, Im HK, Zhang W, Wing C, Duan S, Bleibel WK, Cox NJ, Dolan ME (2011) Population differences in microRNA expression and biological implications. RNA Biol 8:692–701. https://doi.org/10.4161/rna.8.4.16029

  14. Huang S, Zhou S, Zhang Y, Lv Z, Li S, Xie C, Ke Y, Deng P, Geng Y, Zhang Q, Chu X, Yi Z, Zhang Y, Wu T, Cheng J (2015) Association of the genetic polymorphisms in pre-microRNAs with risk of ischemic stroke in a Chinese population. PLoS One 10:e0117007. https://doi.org/10.1371/journal.pone.0117007

  15. Jostins L, Ripke S, Weersma RK, Duerr RH, McGovern DP, Hui KY, Lee JC, Schumm LP, Sharma Y, Anderson CA, Essers J, Mitrovic M, Ning K, Cleynen I, Theatre E, Spain SL, Raychaudhuri S, Goyette P, Wei Z, Abraham C, Achkar J-P, Ahmad T, Amininejad L, Ananthakrishnan AN, Andersen V, Andrews JM, Baidoo L, Balschun T, Bampton PA, Bitton A, Boucher G, Brand S, Büning C, Cohain A, Cichon S, D’Amato M, De Jong D, Devaney KL, Dubinsky M, Edwards C, Ellinghaus D, Ferguson LR, Franchimont D, Fransen K, Gearry R, Georges M, Gieger C, Glas J, Haritunians T, Hart A, Hawkey C, Hedl M, Hu X, Karlsen TH, Kupcinskas L, Kugathasan S, Latiano A, Laukens D, Lawrance IC, Lees CW, Louis E, Mahy G, Mansfield J, Morgan AR, Mowat C, Newman W, Palmieri O, Ponsioen CY, Potocnik U, Prescott NJ, Regueiro M, Rotter JI, Russell RK, Sanderson JD, Sans M, Satsangi J, Schreiber S, Simms LA, Sventoraityte J, Targan SR, Taylor KD, Tremelling M, Verspaget HW, De Vos M, Wijmenga C, Wilson DC, Winkelmann J, Xavier RJ, Zeissig S, Zhang B, Zhang CK, Zhao H, Silverberg MS, Annese V, Hakonarson H, Brant SR, Radford-Smith G, Mathew CG, Rioux JD, Schadt EE et al (2012) Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491:119–124. https://doi.org/10.1038/nature11582

  16. Kannel WB, McGee DL (1979) Diabetes and cardiovascular disease: the Framingham study. JAMA 241:2035–2038

  17. Kurian AK, Cardarelli KM (2007) Racial and ethnic differences in cardiovascular disease risk factors: a systematic review. Ethn Dis 17:143–152

  18. Li D, Lewinger JP, Gauderman WJ, Murcray CE, Conti D (2011) Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies. Genet Epidemiol 35:790–799. https://doi.org/10.1002/gepi.20628

  19. Liu DJ, Leal SM (2010) Replication strategies for rare variant complex trait association studies via next-generation sequencing. Am J Hum Genet 87:790–801. https://doi.org/10.1016/j.ajhg.2010.10.025

  20. Magnani JW, Norby FL, Agarwal SK, Soliman EZ, Chen LY, Loehr LR, Alonso A (2016) Racial differences in atrial fibrillation-related cardiovascular disease and mortality: the Atherosclerosis Risk in Communities (ARIC) Study. JAMA Cardiol 1:433–441. https://doi.org/10.1001/jamacardio.2016.1025

  21. Malhotra A, Wolford JK, American Diabetes Association GSG (2005) Analysis of quantitative lipid traits in the genetics of NIDDM (GENNID) study. Diabetes 54:3007–3014

  22. Meyer TE, Verwoert GC, Hwang SJ, Glazer NL, Smith AV, van Rooij FJ, Ehret GB, Boerwinkle E, Felix JF, Leak TS, Harris TB, Yang Q, Dehghan A, Aspelund T, Katz R, Homuth G, Kocher T, Rettig R, Ried JS, Gieger C, Prucha H, Pfeufer A, Meitinger T, Coresh J, Hofman A, Sarnak MJ, Chen YD, Uitterlinden AG, Chakravarti A, Psaty BM, van Duijn CM, Kao WH, Witteman JC, Gudnason V, Siscovick DS, Fox CS, Kottgen A, Factors Genetic, Genetic Factors for Osteoporosis C, Meta Analysis of G, Insulin Related Traits C (2010) Genome-wide association studies of serum magnesium, potassium, and sodium concentrations identify six Loci influencing serum magnesium levels. PLoS Genet. https://doi.org/10.1371/journal.pgen.1001045

  23. Middelberg RPS, Ferreira MAR, Henders AK, Heath AC, Madden PAF, Montgomery GW, Martin NG, Whitfield JB (2011) Genetic variants in LPL, OASL and TOMM40/APOE-C1-C2-C4 genes are associated with multiple cardiovascular-related traits. BMC Med Genet 12:123. https://doi.org/10.1186/1471-2350-12-123

  24. Mitchell BD, Kammerer CM, Blangero J, Mahaney MC, Rainwater DL, Dyke B, Hixson JE, Henkel RD, Sharp RM, Comuzzie AG, VandeBerg JL, Stern MP, MacCluer JW (1996) Genetic and environmental contributions to cardiovascular risk factors in Mexican Americans. The San Antonio Family Heart Study. Circulation 94:2159–2170

  25. Morrison AC, Voorman A, Johnson AD, Liu X, Yu J, Li A, Muzny D, Yu F, Rice K, Zhu C, Bis J, Heiss G, O’Donnell CJ, Psaty BM, Cupples LA, Gibbs R, Boerwinkle E (2013) Whole-genome sequence-based analysis of high-density lipoprotein cholesterol. Nat Genet 45:899–901. https://doi.org/10.1038/ng.2671

  26. Nelson CP, Goel A, Butterworth AS, Kanoni S, Webb TR, Marouli E, Zeng L, Ntalla I, Lai FY, Hopewell JC, Giannakopoulou O, Jiang T, Hamby SE, Di Angelantonio E, Assimes TL, Bottinger EP, Chambers JC, Clarke R, Palmer CNA, Cubbon RM, Ellinor P, Ermel R, Evangelou E, Franks PW, Grace C, Gu D, Hingorani AD, Howson JMM, Ingelsson E, Kastrati A, Kessler T, Kyriakou T, Lehtimaki T, Lu X, Lu Y, Marz W, McPherson R, Metspalu A, Pujades-Rodriguez M, Ruusalepp A, Schadt EE, Schmidt AF, Sweeting MJ, Zalloua PA, AlGhalayini K, Keavney BD, Kooner JS, Loos RJF, Patel RS, Rutter MK, Tomaszewski M, Tzoulaki I, Zeggini E, Erdmann J, Dedoussis G, Bjorkegren JLM, Consortium E-C, CardioGramplusC4D, group UKBCCCw, Schunkert H, Farrall M, Danesh J, Samani NJ, Watkins H, Deloukas P (2017) Association analyses based on false discovery rate implicate new loci for coronary artery disease. Nat Genet 49:1385–1391. https://doi.org/10.1038/ng.3913

  27. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ, Sham PC (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81:559–575. https://doi.org/10.1086/519795

  28. R Development Core Team R (2011) R: a language and environment for statistical computing. R Foundation for Statistical Computing 1:409. https://doi.org/10.1007/978-3-540-74686-7

  29. Shih PA, O’Connor DT (2008) Hereditary determinants of human hypertension: strategies in the setting of genetic complexity. Hypertension 51:1456–1464. https://doi.org/10.1161/HYPERTENSIONAHA.107.090480

  30. Vasan RS, Larson MG, Leip EP, Evans JC, O’Donnell CJ, Kannel WB, Levy D (2001) Impact of high-normal blood pressure on the risk of cardiovascular disease. N Engl J Med 345:1291–1297. https://doi.org/10.1056/NEJMoa003417

  31. Vlachos IS, Zagganas K, Paraskevopoulou MD, Georgakilas G, Karagkouni D, Vergoulis T, Dalamagas T, Hatzigeorgiou AG (2015) DIANA-miRPath v3.0: deciphering microRNA function with experimental support. Nucl Acids Res 43:W460–W466. https://doi.org/10.1093/nar/gkv403

  32. Voorman AA, Brody J, Chen H, Lumley T, Davis B, Briandavisgmailcom MBD (2017) Package ‘seqMeta’

  33. Wang L, Zhi H, Li Y, Ma G, Ye X, Yu X, Yang T, Jin H, Lu Z, Wei P (2014) Polymorphism in miRNA-1 target site and circulating miRNA-1 phenotype are associated with the decreased risk and prognosis of coronary artery disease. Int J Clin Exp Pathol 7:5093–5102

  34. Weissglas-Volkov D, Pajukanta P (2010) Genetic causes of high and low serum HDL-cholesterol. J Lipid Res 51:2032–2057. https://doi.org/10.1194/jlr.R004739

  35. Whitfield JB (2014) Genetic insights into cardiometabolic risk factors. Clin Biochem Rev 35:15–36

  36. Willer CJ, Schmidt EM, Sengupta S, Peloso GM, Gustafsson S, Kanoni S, Ganna A, Chen J, Buchkovich ML, Mora S, Beckmann JS, Bragg-Gresham JL, Chang H-Y, Demirkan A, Den Hertog HM, Do R, Donnelly LA, Ehret GB, Esko T, Feitosa MF, Ferreira T, Fischer K, Fontanillas P, Fraser RM, Freitag DF, Gurdasani D, Heikkilä K, Hyppönen E, Isaacs A, Jackson AU, Johansson A, Johnson T, Kaakinen M, Kettunen J, Kleber ME, Li X, Luan Ja, Lyytikäinen L-P, Magnusson PKE, Mangino M, Mihailov E, Montasser ME, Müller-Nurasyid M, Nolte IM, O’Connell JR, Palmer CDCNA, Perola M, Petersen A-K, Sanna S, Saxena R, Service SK, Shah S, Shungin D, Sidore C, Song C, Strawbridge RJ, Surakka I, Tanaka T, Teslovich TM, Thorleifsson G, Van den Herik EG, Voight BF, Volcik KA, Waite LL, Wong A, Wu Y, Zhang W, Absher D, Asiki G, Barroso I, Been LF, Bolton JL, Bonnycastle LL, Brambilla P, Burnett MS, Cesana G, Dimitriou M, Doney ASF, Döring A, Elliott P, Epstein SE, Eyjolfsson GI, Gigante B, Goodarzi MO, Grallert H, Gravito ML, Groves CJ, Hallmans G, Hartikainen A-L, Hayward C, Hernandez D, Hicks AA, Holm H, Hung Y-J, Illig T, Jones MR, Kaleebu P, Kastelein JJP, Khaw K-T, Kim E et al (2013) Discovery and refinement of loci associated with lipid levels. Nat Genet 45:1274–1283. https://doi.org/10.1038/ng.2797

  37. Xu J, Murphy SL, Kochanek KD, Bastian BA (2016) National vital statistics reports deaths: final data for 2013. Natl Center Health Stat 64:1–118

  38. Yu B, de Vries PS, Metcalf GA, Wang Z, Feofanova EV, Liu X, Muzny DM, Wagenknecht LE, Gibbs RA, Morrison AC, Boerwinkle E (2016) Whole genome sequence analysis of serum amino acid levels. Genome Biol 17:237. https://doi.org/10.1186/s13059-016-1106-x

  39. Zuker M (2003) Mfold web server for nucleic acid folding and hybridization prediction. Nucl Acids Res 31:3406–3415. https://doi.org/10.1093/nar/gkg595

Download references

Acknowledgements

The Atherosclerosis Risk in Communities study has been funded in whole or in part with federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services (Contract Numbers HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I, and HHSN268201700005I). The authors thank the staff and participants of the ARIC study for their important contributions. Funding support for “Building on GWAS for NHLBI diseases: the U.S. CHARGE consortium” was provided by the NIH through the American Recovery and Reinvestment Act of 2009 (ARRA) (5RC2HL102419). Sequencing was carried out at the Baylor College of Medicine Human Genome Sequencing Center and supported by the National Human Genome Research Institute Grants U54 HG003273 and UM1 HG008898.

Author information

Correspondence to Eric Boerwinkle or Xiaoming Liu.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Electronic supplementary material

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Li, C., Grove, M.L., Yu, B. et al. Genetic variants in microRNA genes and targets associated with cardiovascular disease risk factors in the African-American population. Hum Genet 137, 85–94 (2018). https://doi.org/10.1007/s00439-017-1858-8

Download citation