Skip to main content
SpringerLink
Log in

Partial correlation network analyses to detect altered gene interactions in human disease: using preeclampsia as a model

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

Abstract

Differences in gene expression between cases and controls have been identified for a number of human diseases. However, the underlying mechanisms of transcriptional regulation remain largely unknown. Beyond comparisons of absolute or relative expression levels, disease states may be associated with alterations in the observed correlational patterns among sets of genes. Here we use partial correlation networks aiming to compare the transcriptional co-regulation for 222 genes that are differentially expressed in decidual tissues between preeclampsia (PE) cases and non-PE controls. Partial correlation coefficients (PCCs) have been calculated in cases (N = 37) and controls (N = 58) separately. For all PCCs, we tested if they were significant non-zero in the cases and controls separately. In addition, to examine if a given PCC is different between the cases and controls, we tested if the difference between two PCCs were significant non-zero. In the group with PE cases, only five PCCs were significant (FDR p value ≤ 0.05), of which none were significantly different from the PCCs in the controls. However, in the controls we identified a total of 56 statistically significant PCCs (FDR p value ≤ 0.05), of which 31 were also significantly different (FDR p value ≤ 0.05) from the PCCs in the PE cases. The identified partial correlation networks included genes that are potentially relevant for developing PE, including both known susceptibility genes (EGFL7, HES1) and novel candidate genes (CFH, NADSYN1, DBP, FIGLA). Our results might suggest that disturbed interactions, or higher order relationships between these genes play an important role in developing the disease.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Ahn J, Yu K, Stolzenberg-Solomon R, Simon KC, McCullough ML, Gallicchio L, Jacobs EJ, Ascherio A, Helzlsouer K, Jacobs KB, Li Q, Weinstein SJ, Purdue M, Virtamo J, Horst R, Wheeler W, Chanock S, Hunter DJ, Hayes RB, Kraft P, Albanes D (2010) Genome-wide association study of circulating vitamin D levels. Hum Mol Genet 19:2739–2745. doi:10.1093/hmg/ddq155

    Article  CAS  PubMed  Google Scholar 

  • Bayne RA, Martins da Silva SJ, Anderson RA (2004) Increased expression of the FIGLA transcription factor is associated with primordial follicle formation in the human fetal ovary. Mol Hum Reprod 10:373–381

    Article  CAS  PubMed  Google Scholar 

  • Boccia LM, Lillicrap D, Newcombe K, Mueller CR (1996) Binding of the Ets factor GA-binding protein to an upstream site in the factor IX promoter is a critical event in transactivation. Mol Cell Biol 16:1929–1935

    CAS  PubMed  Google Scholar 

  • Bodnar LM, Catov JM, Simhan HN, Holick MF, Powers RW, Roberts JM (2007) Maternal vitamin D deficiency increases the risk of preeclampsia. J Clin Endocrinol Metab 92:3517–3522. doi:10.1210/jc.2007-0718

    Article  CAS  PubMed  Google Scholar 

  • Cobellis L, Mastrogiacomo A, Federico E, Schettino MT, De Falco M, Manente L, Coppola G, Torella M, Colacurci N, De Luca A (2007) Distribution of Notch protein members in normal and preeclampsia-complicated placentas. Cell Tissue Res 330:527–534. doi:10.1007/s00441-007-0511-6

    Article  CAS  PubMed  Google Scholar 

  • Cooper ML, Adami HO, Gronberg H, Wiklund F, Green FR, Rayman MP (2008) Interaction between single nucleotide polymorphisms in selenoprotein P and mitochondrial superoxide dismutase determines prostate cancer risk. Cancer Res 68:10171–10177

    Article  CAS  PubMed  Google Scholar 

  • de la Fuente A, Bing N, Hoeschele I, Mendes P (2004) Discovery of meaningful associations in genomic data using partial correlation coefficients. Bioinformatics 20:3565–3574

    Article  Google Scholar 

  • Edwards AO, Ritter R 3rd, Abel KJ, Manning A, Panhuysen C, Farrer LA (2005) Complement factor H polymorphism and age-related macular degeneration. Science 308:421–424. doi:10.1126/science.1110189

    Article  CAS  PubMed  Google Scholar 

  • Enquobahrie DA, Meller M, Rice K, Psaty BM, Siscovick DS, Williams MA (2008) Differential placental gene expression in preeclampsia. Am J Obstet Gynecol 199:566 e1–e11

    Google Scholar 

  • Eyster KM, Mark CJ, Gayle R, Martin DS (2007) The effects of estrogen and testosterone on gene expression in the rat mesenteric arteries. Vascul Pharmacol 47:238–247

    Article  CAS  PubMed  Google Scholar 

  • Fenstad MH, Johnson MP, Loset M, Mundal SB, Roten LT, Eide IP, Bjorge L, Sande RK, Johansson AK, Dyer TD, Forsmo S, Blangero J, Moses EK, Austgulen R (2010) STOX2 but not STOX1 is differentially expressed in decidua from preeclamptic women. Mol Hum Reprod. doi:10.1093/molehr/gaq064

  • Fujita A, Sato JR, Garay-Malpartida HM, Yamaguchi R, Miyano S, Sogayar MC, Ferreira CE (2007) Modeling gene expression regulatory networks with the sparse vector autoregressive model. BMC Syst Biol 1:39

    Article  PubMed  Google Scholar 

  • Gifford RW, August PA, Cunningham G, Green LA, Lindheimer MD, McNellis D, Roberts JM, Sibai BM, Taler SJ (2000) Report of the National High Blood Pressure Education Program Working Group on high blood pressure in pregnancy. Am J Obstet Gynecol 183:S1–S22

    Article  Google Scholar 

  • Goldenberg RL, Rouse DJ (1998) Prevention of premature birth. N Engl J Med 339:313–320

    Article  CAS  PubMed  Google Scholar 

  • Goring HH, Curran JE, Johnson MP, Dyer TD, Charlesworth J, Cole SA, Jowett JB, Abraham LJ, Rainwater DL, Comuzzie AG, Mahaney MC, Almasy L, MacCluer JW, Kissebah AH, Collier GR, Moses EK, Blangero J (2007) Discovery of expression QTLs using large-scale transcriptional profiling in human lymphocytes. Nat Genet 39:1208–1216

    Article  PubMed  Google Scholar 

  • Grant WB (2010) Low vitamin D may explain the link between preeclampsia and cardiovascular disease. Am Heart J 159:e19. doi:10.1016/j.ahj.2009.12.007

    Article  PubMed  Google Scholar 

  • Haines JL, Hauser MA, Schmidt S, Scott WK, Olson LM, Gallins P, Spencer KL, Kwan SY, Noureddine M, Gilbert JR, Schnetz-Boutaud N, Agarwal A, Postel EA, Pericak-Vance MA (2005) Complement factor H variant increases the risk of age-related macular degeneration. Science 308:419–421. doi:10.1126/science.1110359

    Article  CAS  PubMed  Google Scholar 

  • Han L, Zhu J (2008) Using matrix of thresholding partial correlation coefficients to infer regulatory network. Biosystems 91:158–165

    Article  CAS  PubMed  Google Scholar 

  • Hochberg Y, Benjamini Y (1990) More powerful procedures for multiple significance testing. Stat Med 9:811–818

    Article  CAS  PubMed  Google Scholar 

  • Huntriss J, Gosden R, Hinkins M, Oliver B, Miller D, Rutherford AJ, Picton HM (2002) Isolation, characterization and expression of the human factor in the germline alpha (FIGLA) gene in ovarian follicles and oocytes. Mol Hum Reprod 8:1087–1095

    Article  CAS  PubMed  Google Scholar 

  • Infante J, Rodriguez-Rodriguez E, Mateo I, Llorca J, Vazquez-Higuera JL, Berciano J, Combarros O (2010) Gene-gene interaction between heme oxygenase-1 and liver X receptor-beta and Alzheimer’s disease risk. Neurobiol Aging 31:710–714. doi:10.1016/j.neurobiolaging.2008.05.025

    Article  CAS  PubMed  Google Scholar 

  • Kaare M, Seitsonen S, Jarvela I, Meri S, Laivuori H (2008) Complement factor H variant Y402H is not a risk factor for preeclampsia in the Finnish population. Hypertens Pregnancy 27:328–336. doi:10.1080/10641950801955691

    Article  CAS  PubMed  Google Scholar 

  • Klein RJ, Zeiss C, Chew EY, Tsai JY, Sackler RS, Haynes C, Henning AK, SanGiovanni JP, Mane SM, Mayne ST, Bracken MB, Ferris FL, Ott J, Barnstable C, Hoh J (2005) Complement factor H polymorphism in age-related macular degeneration. Science 308:385–389. doi:10.1126/science.1109557

    Article  CAS  PubMed  Google Scholar 

  • Kriegeskorte N, Simmons WK, Bellgowan PS, Baker CI (2009) Circular analysis in systems neuroscience: the dangers of double dipping. Nat Neurosci 12:535–540. doi:10.1038/nn.2303

    Article  CAS  PubMed  Google Scholar 

  • Kriegeskorte N, Lindquist MA, Nichols TE, Poldrack RA, Vul E (2010) Everything you never wanted to know about circular analysis, but were afraid to ask. J Cereb Blood Flow Metab 30:1551–1557. doi:10.1038/jcbfm.2010.86

    Article  PubMed  Google Scholar 

  • Lain KY, Roberts JM (2002) Contemporary concepts of the pathogenesis and management of preeclampsia. JAMA 287:3183–3186

    Article  PubMed  Google Scholar 

  • Liang L, Soyal SM, Dean J (1997) FIGalpha, a germ cell specific transcription factor involved in the coordinate expression of the zona pellucida genes. Development 124:4939–4947

    CAS  PubMed  Google Scholar 

  • Løset M, Mundal SB, Johnson MP, Fenstad MH, Freed KA, L. B, Blangero J, Moses EK, Austgulen R (2010) A transcriptional profile of the decidua in preeclampsia. AJOG. doi:10.1016/j.ajog.2010.08.043

  • Ma S, Gong Q, Bohnert HJ (2007) An Arabidopsis gene network based on the graphical Gaussian model. Genome Res 17:1614–1625

    Article  CAS  PubMed  Google Scholar 

  • Oksjoki R, Kovanen PT, Pentikainen MO (2003) Role of complement activation in atherosclerosis. Curr Opin Lipidol 14:477–482. doi:10.1097/01.mol.0000092627.86399.7b

    Article  CAS  PubMed  Google Scholar 

  • Opgen-Rhein R, Strimmer K (2007) From correlation to causation networks: a simple approximate learning algorithm and its application to high-dimensional plant gene expression data. BMC Syst Biol 1:37

    Article  PubMed  Google Scholar 

  • Redman CW, Sargent IL (2003) Pre-eclampsia, the placenta and the maternal systemic inflammatory response—a review. Placenta 24(Suppl A):S21–S27

    Article  PubMed  Google Scholar 

  • Roberts JM, Gammill HS (2005) Preeclampsia: recent insights. Hypertension 46:1243–1249

    Article  CAS  PubMed  Google Scholar 

  • Roberts JM, Pearson G, Cutler J, Lindheimer M (2003) Summary of the NHLBI Working Group on Research on hypertension during pregnancy. Hypertension 41:437–445

    Article  CAS  PubMed  Google Scholar 

  • Salonen Ros H, Lichtenstein P, Lipworth L, Cnattingius S (2000) Genetic effects on the liability of developing pre-eclampsia and gestational hypertension. Am J Med Genet 91:256–260

    Article  CAS  PubMed  Google Scholar 

  • Schafer J, Strimmer K (2005a) An empirical Bayes approach to inferring large-scale gene association networks. Bioinformatics 21:754–764

    Article  PubMed  Google Scholar 

  • Schafer J, Strimmer K (2005b) A shrinkage approach to large-scale covariance matrix estimation and implications for functional genomics. Stat Appl Genet Mol Biol 4: Article32

  • Seitsonen S, Lemmela S, Holopainen J, Tommila P, Ranta P, Kotamies A, Moilanen J, Palosaari T, Kaarniranta K, Meri S, Immonen I, Jarvela I (2006) Analysis of variants in the complement factor H, the elongation of very long chain fatty acids-like 4 and the hemicentin 1 genes of age-related macular degeneration in the Finnish population. Mol Vis 12:796–801

    CAS  PubMed  Google Scholar 

  • Seitsonen SP, Onkamo P, Peng G, Xiong M, Tommila PV, Ranta PH, Holopainen JM, Moilanen JA, Palosaari T, Kaarniranta K, Meri S, Immonen IR, Jarvela IE (2008) Multifactor effects and evidence of potential interaction between complement factor H Y402H and LOC387715 A69S in age-related macular degeneration. PLoS ONE 3:e3833

    Article  PubMed  Google Scholar 

  • Strimmer K (2008) A unified approach to false discovery rate estimation. BMC Bioinformatics 9:303. doi:10.1186/1471-2105-9-303

    Article  PubMed  Google Scholar 

  • Szolnoki Z, Maasz A, Magyari L, Horvatovich K, Farago B, Kondacs A, Bodor A, Hadarits F, Orosz P, Ille A, Melegh B (2009) Galectin-2 3279TT variant protects against the lymphotoxin-alpha 252GG genotype associated ischaemic stroke. Clin Neurol Neurosurg 111:227–230. doi:10.1016/j.clineuro.2008.09.027

    Article  PubMed  Google Scholar 

  • Winn VD, Haimov-Kochman R, Paquet AC, Yang YJ, Madhusudhan MS, Gormley M, Feng KT, Bernlohr DA, McDonagh S, Pereira L, Sali A, Fisher SJ (2007) Gene expression profiling of the human maternal-fetal interface reveals dramatic changes between midgestation and term. Endocrinology 148:1059–1079. doi:en.2006-0683[pii]10.1210/en.2006-0683

    Article  CAS  PubMed  Google Scholar 

  • Winn VD, Gormley M, Paquet AC, Kjaer-Sorensen K, Kramer A, Rumer KK, Haimov-Kochman R, Yeh RF, Overgaard MT, Varki A, Oxvig C, Fisher SJ (2009) Severe preeclampsia-related changes in gene expression at the maternal-fetal interface include sialic acid-binding immunoglobulin-like lectin-6 and pappalysin-2. Endocrinology 150:452–462

    Article  CAS  PubMed  Google Scholar 

  • Witlin AG, Sibai BM (1997) Hypertension in pregnancy: current concepts of preeclampsia. Annu Rev Med 48:115–127

    Article  CAS  PubMed  Google Scholar 

  • Zhao H, Chen ZJ, Qin Y, Shi Y, Wang S, Choi Y, Simpson JL, Rajkovic A (2008) Transcription factor FIGLA is mutated in patients with premature ovarian failure. Am J Hum Genet 82:1342–1348

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This study was supported by grants from FUGE—Functional genomics in Norway within the Research Council of Norway (Åsa Johnasson) and motility grants from NTNU—The Norwegian University of Science and Technology (Åsa Johansson) and Sven och Dagmar Saléns stiftelse (Åsa Johansson). Statistical analysis was supported in part by NIH grant MH59490 (Blangero).

Author information

Authors and Affiliations

  1. Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Kvinne-barn senteret, 1.etg. Øst, 7006, Trondheim, Norway

    Åsa Johansson, Mari Løset, Siv B. Mundal, Mona H. Fenstad & Rigmor Austgulen

  2. Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, TX, USA

    Åsa Johansson, Matthew P. Johnson, Katy A. Freed, Eric K. Moses & John Blangero

Authors
  1. Åsa Johansson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mari Løset
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Siv B. Mundal
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Matthew P. Johnson
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Katy A. Freed
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Mona H. Fenstad
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Eric K. Moses
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Rigmor Austgulen
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. John Blangero
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Åsa Johansson.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOC 377 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Johansson, Å., Løset, M., Mundal, S.B. et al. Partial correlation network analyses to detect altered gene interactions in human disease: using preeclampsia as a model. Hum Genet 129, 25–34 (2011). https://doi.org/10.1007/s00439-010-0893-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00439-010-0893-5

Keywords

Search

Navigation