Skip to main content
Log in

Genetic dissection of gene expression observed in whole blood samples of elderly Danish twins

  • Original Investigation
  • Published:
Human Genetics Aims and scope Submit manuscript

Abstract

The microarray technique is an important tool in gene expression analysis to study the activities of thousands of genes measured by their transcript levels under disease or laboratory controlled experimental conditions. Recent studies have suggested a genetic component in the variations of gene expression thus indicating the important role of genetic control over gene activities. In this study, we analyze and report the twin correlation on gene expression in whole blood samples of six female Danish twin pairs aged from 81 to 85 years. We studied the expression phenotype by treating the measured gene expression as a quantitative trait and introducing analytical approaches including the traditional twin methods in population genetics and the multivariate statistical methods. Using this combinatory approach, we were able to estimate and compare the twin correlation on the expression phenotype while accounting for systematic influence in microarray experiments. Analyses on our twin data detected a significant correlation on the expression levels of the actively regulated genes in both monozygotic and dizygotic twins, which is more pronounced in monozygotic twins. Gene ontology analysis has shown that these actively regulated genes are predominantly involved in defense and immune responses against antigenic stimulus. In conclusion, the correlation patterns revealed in our twin data provide evidence of the existence of a heritable mechanism in gene expression regulation persistently functioning even in aged subjects.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Brem RB, Yvert G, Clinton R, Kruglyak L (2002) Genetic dissection of transcriptional regulation in budding yeast. Science 296:752–755

    Article  CAS  PubMed  Google Scholar 

  • Buckland PR (2004) Allele-specific gene expression differences in humans. Hum Mol Genet 13:R255–R260

    Article  CAS  PubMed  Google Scholar 

  • Cheung VG, Spielman RS (2002) The genetics of variation in gene expression. Nat Genet 32(Suppl):S522–S525

    Article  Google Scholar 

  • Cheung VG, Conlin LK, Weber TM, Arcaro M, Jen KY, Morley M, Spielman RS (2003) Natural variation in human gene expression assessed in lymphoblastoid cells. Nat Genet 33:422–425

    Article  CAS  PubMed  Google Scholar 

  • Correa CR, Cheung VG (2004) Genetic variation in radiation-induced expression phenotypes. Am J Hum Genet 75:885–890

    Article  CAS  PubMed  Google Scholar 

  • Dohoo IR, Ducrot C, Fourichon C, Donald A, Hurnik D (1996) An overview of techniques for dealing with large numbers of independent variables in epidemiologic studies. Prev Veter Med 29:221–239

    Article  Google Scholar 

  • Dudoit S, Yang YH, Callow MJ, Speed TP (2002) Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments. Statistica Sinica 12:111–139

    MathSciNet  Google Scholar 

  • Fortin MJ, Jacquez GM, Shipley B (2002) Computer-intensive methods. In: El-Shaarawi AH, Piegorsch WW (eds) Encyclopedia of environmetrics. Wiley, Chichester

    Google Scholar 

  • Li C, Wong WH (2001a) Model-based analysis of oligonucleotide arrays: model validation, design issues and standard error application. Genome Biol Res 2:0032.1–0032.11

    Google Scholar 

  • Li C, Wong WH (2001b) Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection. Proc Natl Acad Sci USA 98:31–36

    Article  CAS  PubMed  Google Scholar 

  • Mak YT, Hampson G, Beresford JN, Spector TD (2004) Variations in genome-wide gene expression in identical twins—a study of primary osteoblast-like culture from female twins discordant for osteoporosis. BMC Genet 5:14

    Article  PubMed  Google Scholar 

  • McGraw KO, Wong SP (1996) Forming inferences about some intraclass correlation coefficients. Psychol Methods 1:30–46

    Article  Google Scholar 

  • McGue M, Bouchard TJ (1984) Adjustment of twin data for the effects of age and sex. Behav Genet 14:325–343

    Article  CAS  PubMed  Google Scholar 

  • Monks SA, Leonardson A, Zhu H, Cundiff P, Pietrusiak P, Edwards S, Phillips JW, Sachs A, Schadt EE (2004) Genetic inheritance of gene expression in human cell lines. Am J Hum Genet 75:1094–1105

    Article  CAS  PubMed  Google Scholar 

  • Morley M, Molony CM, Weber TM, Devlin JL, Ewens KG, Spielman RS, Cheung VG (2004) Genetic analysis of genome-wide variation in human gene expression. Nature 430:743–747

    Article  CAS  PubMed  Google Scholar 

  • Naderi A, Ahmed AA, Barbosa-Morais NL, Aparicio S, Brenton JD, Caldas C (2004) Expression microarray reproducibility is improved by optimising purification steps in RNA amplification and labelling. BMC Genomics 5:9

    Article  PubMed  Google Scholar 

  • Schadt EE, Monks SA, Drake TA, Lusis AJ, Che N, Colinayo V, Ruff TG, Milligan SB, Lamb JR, Cavet G, Linsley PS, Mao M, Stoughton RB, Friend SH (2003) Genetics of gene expression surveyed in maize, mouse and man. Nature 422:297–302

    Article  CAS  PubMed  Google Scholar 

  • Sham P (1998) Statistics in human genetics, Arnold applications of statistics. Edward Arnold, London

    Google Scholar 

  • Skytthe A, Kyvik K, Holm NV, Vaupel JW, Christensen K (2002) The Danish twin registry: 127 birth cohorts of twins. Twin Res 5:352–357

    Article  PubMed  Google Scholar 

  • Spector TD, MacGregor AJ, Snieder H (2000) Uses of twins in studying the genetics of complex traits. GeneScreen 1:93–95

    Article  Google Scholar 

  • Tan Q, Brusgaard K, Kruse TA, Oakeley E, Hemmings B, Beck-Nielsen H, Hansen L, Gaster M (2004a) Correspondence analysis of microarray time-course data in case–control design. J Biomed Inform 37:358–365

    Article  CAS  PubMed  Google Scholar 

  • Tan Q, Yashin AI, Christensen K, Jeune B, De Benedictis G, Kruse TA, Vaupel JW (2004b) Multidisciplinary approaches in genetic studies of human aging and longevity. Curr Genomics 5:409–416

    Article  CAS  Google Scholar 

  • Tavazoie S, Hughes JD, Campbell MJ, Cho RJ, Church GM (1999) Systematic determination of genetic network architecture. Nat Genet 22:281–285

    Article  CAS  PubMed  Google Scholar 

  • Yan H, Yuan W, Velculescu VE, Vogelstein B, Kinzler KW (2002) Allelic variation in human gene expression. Science 297:1143

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The study was jointly supported by the US National Institute on Aging (NIA) research grant NIA-PO1-AG08761, the GENOMEUTWIN Project (European Union Contract No. QLG2-CT-2002-01254), the Danish Medical Research Council and the Danish Biotechnology Instrument Center (DABIC) under the biotechnological research program of the Danish Research Agency. We are thankful to Rehannah Borup, Susanne Smed and Finn Cilius at the National Hospital in Copenhagen and to Fiona Brew at Affymetrix UK.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Qihua Tan.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Tan, Q., Christensen, K., Christiansen, L. et al. Genetic dissection of gene expression observed in whole blood samples of elderly Danish twins. Hum Genet 117, 267–274 (2005). https://doi.org/10.1007/s00439-005-1308-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00439-005-1308-x

Keywords

Navigation