Combined linkage and association analysis identifies rare and low frequency variants for blood pressure at 1q31


High blood pressure (BP) is a major risk factor for cardiovascular disease (CVD) and is more prevalent in African Americans as compared to other US groups. Although large, population-based genome-wide association studies (GWAS) have identified over 300 common polymorphisms modulating inter-individual BP variation, largely in European ancestry subjects, most of them do not localize to regions previously identified through family-based linkage studies. This discrepancy has remained unexplained despite the statistical power differences between current GWAS and prior linkage studies. To address this issue, we performed genome-wide linkage analysis of BP traits in African-American families from the Family Blood Pressure Program (FBPP) and genotyped on the Illumina Human Exome BeadChip v1.1. We identified a genomic region on chromosome 1q31 with LOD score 3.8 for pulse pressure (PP), a region we previously implicated in DBP studies of European ancestry families. Although no reported GWAS variants map to this region, combined linkage and association analysis of PP identified 81 rare and low frequency exonic variants accounting for the linkage evidence. Replication analysis in eight independent African ancestry cohorts (N = 16,968) supports this specific association with PP (P = 0.0509). Additional association and network analyses identified multiple potential candidate genes in this region expressed in multiple tissues and with a strong biological support for a role in BP. In conclusion, multiple genes and rare variants on 1q31 contribute to PP variation. Beyond producing new insights into PP, we demonstrate how family-based linkage and association studies can implicate specific rare and low frequency variants for complex traits.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1
Fig. 2


  1. 1.

    Berry JD, Dyer A, Cai X, Garside DB, Ning H, Thomas A, et al. Lifetime risks of cardiovascular disease. New Engl J Med. 2012;366:321–9.

  2. 2.

    Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2224–60.

  3. 3.

    Ehret GB, Caulfield MJ. Genes for blood pressure: an opportunity to understand hypertension. Eur Heart J. 2013;34:951–61.

  4. 4.

    Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr., et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003;289:2560–72.

  5. 5.

    Cooper RS, Luke A, Zhu X, Kan D, Adeyemo A, Rorimi C, et al. Genome scan among Nigerians linking blood pressure to chromosomes 2, 3, and 19. Hypertension. 2002;40:629–33.

  6. 6.

    Ehret GB. Genome-wide association studies: contribution of genomics to understanding blood pressure and essential hypertension. Curr Hypertens Rep. 2010;12:17–25.

  7. 7.

    Lifton RP, Gharavi AG, Geller DS. Molecular mechanisms of human hypertension. Cell. 2001;104:545–56.

  8. 8.

    Ehret GB, Ferreira T, Chasman DI, Jackson AU, Schmidt EM, Johnson T, et al. The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals. Nat Genet. 2016;48:1171–84.

  9. 9.

    Surendran P, Drenos F, Young R, Warren H, Cook JP, Manning AK, et al. Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension. Nat Genet. 2016;48:1151–1161.

  10. 10.

    Liu C, Kraja AT, Smith JA, Brody JA, Franceschini N, Bis JC, et al. Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. Nat Genet. 2016;48:1162–70.

  11. 11.

    Hoffmann TJ, Ehret GB, Nandakumar P, Ranatunga D, Schaefer C, Kwok PY, et al. Genome-wide association analyses using electronic health records identify new loci influencing blood pressure variation. Nat Genet. 2017;49:54–64.

  12. 12.

    Lee S, Wu MC, Lin X. Optimal tests for rare variant effects in sequencing association studies. Biostatistics. 2012;13:762–75.

  13. 13.

    Madsen BE, Browning SR. A groupwise association test for rare mutations using a weighted sum statistic. PLoS Genet. 2009;5:e1000384.

  14. 14.

    Li B, Leal SM. Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data. Am J Hum Genet. 2008;83:311–21.

  15. 15.

    Price AL, Kryukov GV, de Bakker PI, Purcell SM, Staples J, Wei LJ, et al. Pooled association tests for rare variants in exon-resequencing studies. Am J Hum Genet. 2010;86:832–8.

  16. 16.

    Lin DY, Tang ZZ. A general framework for detecting disease associations with rare variants in sequencing studies. Am J Hum Genet. 2011;89:354–67.

  17. 17.

    Zhu X, Feng T, Li Y, Lu Q, Elston RC. Detecting rare variants for complex traits using family and unrelated data. Genet Epidemiol. 2010;34:171–87.

  18. 18.

    Feng T, Elston RC, Zhu X. Detecting rare and common variants for complex traits: sibpair and odds ratio weighted sum statistics (SPWSS, ORWSS). Genet Epidemiol. 2011;35:398–409.

  19. 19.

    Epstein MP, Duncan R, Ware EB, Jhun MA, Bielak LF, Zhao W, et al. A statistical approach for rare-variant association testing in affected sibships. Am J Hum Genet. 2015;96:543–54.

  20. 20.

    Wang H, Cade BE, Chen H, Gleason KJ, Saxena R, Feng T, et al. Variants in angiopoietin-2 (ANGPT2) contribute to variation in nocturnal oxyhaemoglobin saturation level. Hum Mol Genet. 2016;25:5244–53.

  21. 21.

    Province MA, Kardia SL, Ranade K, Rao DC, Thiel BA, Cooper RS, et al. A meta-analysis of genome-wide linkage scans for hypertension: the National Heart, Lung and Blood Institute Family Blood Pressure Program. Am J Hypertens. 2003;16:144–7.

  22. 22.

    Caulfield M, Munroe P, Pembroke J, Samani N, Dominiczak A, Brown M, et al. Genome-wide mapping of human loci for essential hypertension. Lancet. 2003;361:2118–23.

  23. 23.

    Wu X, Kan D, Province M, Quertermous T, Rao DC, Chang C, et al. An updated meta-analysis of genome scans for hypertension and blood pressure in the NHLBI Family Blood Pressure Program (FBPP). Am J Hypertens. 2006;19:122–7.

  24. 24.

    Abecasis GR, Cherny SS, Cookson WO, Cardon LR. Merlin--rapid analysis of dense genetic maps using sparse gene flow trees. Nat Genet. 2002;30:97–101.

  25. 25.

    Morton NE. Sequential tests for the detection of linkage. Am J Human Genet. 1955;7:277–318.

  26. 26.

    Ott J. Analysis of human genetic linkage. Rev. edn. Baltimore: Johns Hopkins University Press; 1991.

  27. 27.

    Elston RC, Gray-McGuire C. A review of the ‘Statistical Analysis for. Genet Epidemiology’ (S A G E) Softw Package Human Genom. 2004;1:456–9.

  28. 28.

    Chen H, Meigs JB, Dupuis J. Sequence kernel association test for quantitative traits in family samples. Genet Epidemiol. 2013;37:196–204.

  29. 29.

    Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, et al. STRINGv10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 2015;43:D447–52.

  30. 30.

    Chang YP, Liu X, Kim JD, Ikeda MA, Layton MR, Weder AB, et al. Multiple genes for essential-hypertension susceptibility on chromosome 1q. Am J Hum Genet. 2007;80:253–64.

  31. 31.

    Perola M, Sammalisto S, Hiekkalinna T, Martin NG, Visscher PM, Montgomery GW, et al. Combined genome scans for body stature in 6,602 European twins: evidence for common Caucasian loci. PLoS Genet. 2007;3:e97.

  32. 32.

    Hunt SC, Ellison RC, Atwood LD, Pankow JS, Province MA, Leppert MF. Genome scans for blood pressure and hypertension: the National Heart, Lung, and Blood Institute Family Heart Study. Hypertension. 2002;40:1–6.

  33. 33.

    James K, Weitzel LR, Engelman CD, Zerbe G, Norris JM. Framingham Heart S: Genome scan linkage results for longitudinal systolic blood pressure phenotypes in subjects from the Framingham Heart Study. BMC Genet. 2003;4(Suppl 1):S83.

  34. 34.

    Consortium GT. Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science. 2015;348:648–60.

  35. 35.

    Levy D, Ehret GB, Rice K, Verwoert GC, Launer LJ, Dehghan A, et al. Genome-wide association study of blood pressure and hypertension. Nat Genet. 2009;41:677–87.

  36. 36.

    Ehret GB, Munroe PB, Rice KM, Bochud M, Johnson AD, Chasman DI, et al. Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature. 2011;478:103–9.

  37. 37.

    Franceschini N, Fox E, Zhang Z, Edwards TL, Nalls MA, Sung YJ, et al. Genome-wide association analysis of blood-pressure traits in African-ancestry individuals reveals common associated genes in African and non-African populations. Am J Hum Genet. 2013;93:545–54.

  38. 38.

    Zhu X, Feng T, Tayo BO, Liang J, Young JH, Franceschini N, et al. Meta-analysis of correlated traits via summary statistics from GWASs with an application in hypertension. Am J Human Genet. 2015;96:21–36.

  39. 39.

    Perola M, Kainulainen K, Pajukanta P, Terwilliger JD, Hiekkalinna T, Ellonen P, et al. Genome-wide scan of predisposing loci for increased diastolic blood pressure in Finnish siblings. J Hypertens. 2000;18:1579–85.

  40. 40.

    Newton-Cheh C, Johnson T, Gateva V, Tobin MD, Bochud M, Coin L, et al. Genome-wide association study identifies eight loci associated with blood pressure. Nat Genet. 2009;41:666–76.

  41. 41.

    Kato N, Takeuchi F, Tabara Y, Kelly TN, Go MJ, Sim X, et al. Meta-analysis of genome-wide association studies identifies common variants associated with blood pressure variation in east Asians. Nat Genet. 2011;43:531–8.

  42. 42.

    Marouli E, Graff M, Medina-Gomez C, Lo KS, Wood AR, Kjaer TR, et al. Rare and low-frequency coding variants alter human adult height. Nature. 2017;542:186–90.

  43. 43.

    Cowley AW Jr., Moreno C, Jacob HJ, Peterson CB, Stingo FC, Ahn KW, et al. Characterization of biological pathways associated with a 1.37 Mbp genomic region protective of hypertension in Dahl S rats. Physiol Genom. 2014;46:398–410.

  44. 44.

    Cowley AW Jr, Yang C, Kumar V, Lazar J, Jacob H, Geurts AM, et al. Pappa2 is linked to salt-sensitive hypertension in Dahl S rats. Physiol Genom. 2016;48:62–72.

  45. 45.

    Cashman JR, Camp K, Fakharzadeh SS, Fennessey PV, Hines RN, Mamer OA, et al. Biochemical and clinical aspects of the human flavin-containing monooxygenase form 3 (FMO3) related to trimethylaminuria. Curr Drug Metab. 2003;4:151–70.

  46. 46.

    Lifton RP. Molecular genetics of human blood pressure variation. Science. 1996;272:676–80.

  47. 47.

    Treacy EP, Akerman BR, Chow LM, Youil R, Lin CB, Bruce AG, et al. Mutations of the flavin-containing monooxygenase gene (FMO3) cause trimethylaminuria, a defect in detoxication. Hum Mol Genet. 1998;7:839–45.

  48. 48.

    Ford D, Easton DF, Stratton M, Narod S, Goldgar D, Devilee P, et al. Genetic heterogeneity and penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families. The Breast Cancer Linkage Consortium. Am J Human Genet. 1998;62:676–89.

  49. 49.

    He KY, Wang H, Cade BE, Nandakumar P, Giri A, Ware EB, et al. Rare variants in fox-1 homolog A (RBFOX1) are associated with lower blood pressure. PLoS Genet. 2017;13:e1006678.

  50. 50.

    Lander E, Kruglyak L. Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results. Nat Genet. 1995;11:241–7.

Download references


This work was supported in part by NIH grants HL086694 to AC and HG003054 to XZ. TLE was supported by NIH/NHLBI grant HL121429, JNH was supported by T32CA160056,  RJFL was support by NIH grants DK107786, DK110113, and U01HG007417. The GenNet study is funded by NIH grants HL086694. The Genetic Epidemiology Network of Arteriopathy (GENOA) was supported by the National Heart, Lung and Blood Institute (HL054464, HL054457, HL054481, HL087660, HL086694, HL119443) of the National Institutes of Health. Genotyping was performed at the Center for Inherited Disease Research (CIDR). The HyperGEN cohort study is funded by cooperative agreements (U10) with NHLBI: HL54471, HL54472, HL54473, HL54495, HL54496, HL54497, HL54509, HL54515, and 2 R01 HL55673-12. The study involves: University of Utah (Network Coordinating Center, Field Center, and Molecular Genetics Lab); University of Alabama at Birmingham (Field Center and Echo Coordinating and Analysis Center); Medical College of Wisconsin (Echo Genotyping Lab); Boston University (Field Center); University of Minnesota (Field Center and Biochemistry Lab); University of North Carolina (Field Center); Washington University (Data Coordinating Center); Weil Cornell Medical College (Echo Reading Center); National Heart, Lung, & Blood Institute. For a complete list of HyperGEN Investigators: The Supports for replication cohorts are shown in Supplementary.

Author information

Correspondence to Aravinda Chakravarti or Xiaofeng Zhu.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Electronic supplementary material

Combined linkage and association analysis identifies rare and low frequency variants for blood pressure at 1q31

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Further reading