Skip to main content
SpringerLink
Log in

Heterogeneity-based genome search meta-analysis for preeclampsia

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

Abstract

Preeclampsia is a pregnancy-related disorder that causes maternal and fetal morbidity and mortality. Its exact inheritance pattern is still unknown, and genome searches for identifying susceptibility loci for preeclampsia have thus far produced inconclusive or inconsistent results. We performed a heterogeneity-based genome search meta-analysis (HEGESMA) that synthesized the available genome scan data on preeclampsia. HEGESMA identifies genetic regions (bins) that rank highly on average in terms of linkage statistics across genome scans (searches). The significance of each bin’s average rank and heterogeneity across scans was calculated using Monte Carlo tests. The meta-analysis involved four genome-scans on general preeclampsia and five scans on severe preeclampsia. In general preeclampsia, 13 bins had significantly high average rank (P rank < 0.05) by either unweighted or weighted analyses, while four of them (2p11.2–2q21.1, 9q21.32–9q31.2, 2p15–2p11.2, 2q32.1–2q35) were formally significant by both analyses. Heterogeneity of bin 2.8 (2q32.1–2q35) was significantly low in both unweighted and weighted analysis (P Q  < 0.01). In severe preeclampsia, 10 bins had significantly high average rank by either unweighted or weighted analyses and five of them (3q11.1–3q21.2, 2q37.1–2q37.3, 18p11.32–18p11.22, 2p15–2p11.2, 7q34–7q36.3) were significant by both analyses. Bin 2q37.1–2q37.3 showed marginal low heterogeneity in unweighted and weighted analysis (P Q  = 0.06). Results should be interpreted with caution as the p values were modest. Further investigation of these regions by genotyping with additional markers and families may help to direct the identification of candidate genes for preeclampsia.

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

Similar content being viewed by others

References

  • Also-Rallo E, Lopez-Quesada E, Urreizti R, Vilaseca MA, Lailla JM, Balcells S, Grinberg D (2005) Polymorphisms of genes involved in homocysteine metabolism in preeclampsia and in uncomplicated pregnancies. Eur J Obstet Gynecol Reprod Biol 120:45–52

    Article  PubMed  CAS  Google Scholar 

  • Arngrımsson R, Sigurdardottir S, Frigge ML, Bjarnadttir RI, Jonsson T, Stefansson H, Baldursdottir A, Einarsdottir AS, Palsson B, Snorradottir S Lachmeijer AM, Nicolae D, Kong A, Bragason BT, Gulcher JR, Geirsson RT, Stefansson K (1998) A genome-wide scan reveals a maternal susceptibility locus for pre-eclampsia on chromosome 2p13. Hum Mol Genet 8:1799–1805

    Article  Google Scholar 

  • Bashford MT, Hefler LA, Vertrees TW, Roa BB, Gregg AR (2001) Angiotensinogen and endothelial nitric oxide synthase gene polymorphisms among hispanic patients with preeclampsia. Am J Obstet Gynecol 184:1345–1350

    Article  PubMed  CAS  Google Scholar 

  • Bouba I, Makrydimas G, Kalaitzidis R, Lolis DE, Siamopoulos KC, Georgiou I (2003) Interaction between the polymorphisms of the renin-angiotensin system in preeclampsia. Eur J Obstet Gynecol Reprod Biol 110:8–11

    Article  PubMed  CAS  Google Scholar 

  • Ciarmela P, Florio P, Battistini S, Grasso D, Amato T, Boschi S, Marozio L, Benedetto C, Petraglia F (2005) Mutational analysis of the inhibin alpha gene in preeclamptic women. J Endocrinol Invest 28:30–33

    PubMed  CAS  Google Scholar 

  • Chiodini BD, Lewis CM (2003) Meta-analysis of 4 coronary heart disease genome-wide linkage studies confirms a susceptibility locus on chromosome 3q. Arterioscler Thromb Vasc Biol 23:1863–1868

    Article  PubMed  CAS  Google Scholar 

  • DemenaisF, Kanninen T, Lindgren CM, Wiltshire S, Gaget S, Dandrieux C, Almgren P, Sjogren M, Hattersley A, Dina C Tuomi T, McCarthy MI, Froguel P, Groop LC (2003) A meta-analysis of four European genome screens (GIFT Consortium) shows evidence for a novel region on chromosome 17p11.2-q22 linked to type 2 diabetes. Hum Mol Genet 12:1865–1873

    Article  CAS  Google Scholar 

  • Dempfle A, Loesgen S (2004) Meta-analysis of linkage studies for complex diseases: an overview of methods and a simulation study. Ann Hum Genet 68:69–83

    Article  PubMed  CAS  Google Scholar 

  • Engels EA, Schmid CH, Terrin N, Olkin I, Lau J (2000) Heterogeneity and statistical significance in meta-analysis: an empirical study of 125 meta-analyses. Stat Med 19:1707–1728

    Article  PubMed  CAS  Google Scholar 

  • Fisher SA, Lanchbury JS, Lewis CM (2003) Meta-analysis of four rheumatoid arthritis genome-wide linkage studies: confirmation of a susceptibility locus on chromosome 16. Arthritis Rheum 48:1200–1206

    Article  PubMed  CAS  Google Scholar 

  • Fitzpatrick E, Goring HH, Liu H, Borg A, Forrest S, Cooper DW, Brennecke SP, Moses EK (2004) Fine mapping and SNP analysis of positional candidates at the preeclampsia susceptibility locus (PREG1) on chromosome 2. Hum Biol 76:849–862

    Article  PubMed  CAS  Google Scholar 

  • GOPEC Consortium (2005) Disentangling fetal and maternal susceptibility for pre-eclampsia: a British multicenter candidate-gene study. Am J Hum Genet 77:127–131

    Article  Google Scholar 

  • Harrison GA, Humphrey KE, JonesN, Badenhop R, Guo G, Elakis G, Kaye JA, Turner RJ, Grehan M, Wilton AN, Brennecke SP, Cooper DW (1997) A genomewide linkage study of preeclampsia/eclampsia reveals evidence for a candidate region on 4q. Am J Hum Genet 60:1158–1167

    PubMed  CAS  Google Scholar 

  • Ioannidis JP, Gwinn M, Little J, Higgins JP, Bernstein JL, Boffetta P, Bondy M, Bray MS, Brenchley PE, Buffler PA, Casas JP, Chokkalingam A, Danesh J, Smith GD, Dolan S, Duncan R, Gruis NA, Hartge P, Hashibe M, Hunter DJ, Jarvelin MR, Malmer B, Maraganore DM, Newton-Bishop JA, O’Brien TR, Petersen G, Riboli E, Salanti G, Seminara D, Smeeth L, Taioli E, Timpson N, Uitterlinden AG, Vineis P, Wareham N, Winn DM, Zimmern R, Khoury MJ, Human Genome Epidemiology Network, the Network of Investigator Networks (2006) A road map for efficient and reliable human genome epidemiology. Nat Genet 38:3–5

  • Kavvoura FK, Ioannidis JP (2005) CTLA-4 gene polymorphisms and susceptibility to type 1 diabetes mellitus: a HuGE Review and meta-analysis. Am J Epidemiol 162:3–16

    Article  PubMed  Google Scholar 

  • Koivukoski L, Fisher SA, Kanninen T, Lewis CM, von Wowern F, Hunt S, Kardia SLR, Levy D, Perola M, Rankinen T, Rao DC, Rice T, Thiel B, Melander O (2004) Meta-analysis of genome-wide scans for hypertension and blood pressure in Caucasians shows evidence of susceptibility regions on chromosomes 2 and 3. Hum Mol Genet 13:2325–2332

    Article  PubMed  CAS  Google Scholar 

  • Kosmas IP, Tatsioni A, Ioannidis JP (2003) Association of Leiden mutation in factor V gene with hypertension in pregnancy and pre-eclampsia: a meta-analysis. J Hypertens 21:1221–1228

    Article  PubMed  CAS  Google Scholar 

  • Kosmas IP, Tatsioni A, Ioannidis JP (2004) Association of C677T polymorphism in the methylenetetrahydrofolate reductase gene with hypertension in pregnancy and pre-eclampsia: a meta-analysis. J Hypertens 22:1655–1662

    Article  PubMed  CAS  Google Scholar 

  • Laasanen J, Hiltunen M, Punnonen K, Mannermaa A, Heinonen S (2002) Fibrinogen and factor VII promoter polymorphisms in women with preeclampsia. Obstet Gynecol 100:317–320

    Article  PubMed  CAS  Google Scholar 

  • Lachmeijer A, Arngrımsson R, Bastiaans EJ, Frigge ML, Pals G, Sigurdardottir S, Stefansson H, Palsson B, Nicolae D, Kong A, Aarnoudse JG, Gulcher JR, Dekker GA, ten Kate LP, Stefansson K (2001) A genome-wide scan for preeclampsia in The Netherlands. Eur J Hum Genet 9:758–764

    Article  PubMed  CAS  Google Scholar 

  • Lachmeijer A, Dekker G, Pals G, Aarnoudse JG, ten Katea LP, Arngrımsson R (2002a) Searching for preeclampsia genes: the current position. Eur J Obstet Gynecol Reprod Biol 105:94–113

    CAS  Google Scholar 

  • Lachmeijer A, Nosti-Escanilla MP, Bastiaans EB, Pals G, Sandkuijl LA, Kostense PJ, Aarnoudse JG, Crusius JB, Pena AS, Dekker GA, Arngrimsson R, ten Kate LP (2002b) Linkage and association studies of IL1B and IL1RN gene polymorphisms in preeclampsia. Hypertens Pregnancy 21:23–38

    Article  CAS  Google Scholar 

  • Laivuori H, Lahermo P, Ollikainen V, Widen E, Haiva-Mallinen L, Sundstrom H, Laitinen T, Kaaja R, Ylikorkala O, Kere J (2003) Susceptibility Loci for Preeclampsia on Chromosomes 2p25 and 9p13 in Finnish Families. Am J Hum Genet 72:168–177

    Article  PubMed  CAS  Google Scholar 

  • Lau J, Ioannidis JP, Schmid CH (1998) Summing up evidence: one answer is not always enough. Lancet 351:123–127

    Article  PubMed  CAS  Google Scholar 

  • Levinson DF, Levinson MD, SeguradoR, Lewis CM (2003) Genome scan meta-analysis of schizophrenia and bipolar disorder, part I: Methods and power analysis. Am J Hum Genet 73:17–33

    Article  PubMed  CAS  Google Scholar 

  • Lewis CM, Levinson DF (2006) Testing for genetic heterogeneity in the genome search meta-analysis method. Genet Epidemiol 30:348–355

    Article  PubMed  Google Scholar 

  • Lewis CM, Levinson DF, Wise LH, DeLisi LE, Straub RE, Hovatta I, Williams NM, Schwab SG, Pulver AE, Faraone SV Brzustowicz LM, Kaufmann CA, Garver DL, Gurling HM, Lindholm E, Coon H, Moises HW, Byerley W, Shaw SH, Mesen A, Sherrington R, O’Neill FA, Walsh D, Kendler KS, Ekelund J, Paunio T, Lonnqvist J, Peltonen L, O’Donovan MC, Owen MJ, Wildenauer DB, Maier W, Nestadt G, Blouin JL, Antonarakis SE, Mowry BJ, Silverman JM, Crowe RR, Cloninger CR, Tsuang MT, Malaspina D, Harkavy-Friedman JM, Svrakic DM, Bassett AS, Holcomb J, Kalsi G, McQuillin A, Brynjolfson J, Sigmundsson T, Petursson H, Jazin E, Zoega T, Helgason T (2003) Genome scan meta-analysis of schizophrenia and bipolar disorder, part II: Schizophrenia. Am J Hum Genet 73:34–48

    Article  PubMed  CAS  Google Scholar 

  • Moses EK, Lade JA, Guo G, Wilton AN, Grehan M, Freed K, Borg A, Terwilliger JD, North R, Cooper DW, Brennecke SP (2000) A genome scan in families from Australia and New Zealand confirms the presence of a maternal susceptibility locus for pre-eclampsia, on chromosome 2. Am J Hum Genet 67:1581–1585

    Article  PubMed  CAS  Google Scholar 

  • Pawitan Y, Reilly M, Nilsson E, Cnattingius S, Lichtenstein P (2004) Estimation of genetic and environmental factors for binary traits using family data. Stat Med 23:449–465

    Article  PubMed  CAS  Google Scholar 

  • Risch N (1990) Linkage strategies for genetically complex traits. III. The effect of marker polymorphism on analysis of affected relative pairs. Am J Hum Genet 46:242–253

    PubMed  CAS  Google Scholar 

  • Rothman KJ (1990) No adjustments are needed for multiple comparisons. Epidemiology 1:43–46

    Article  PubMed  CAS  Google Scholar 

  • Samsami Dehaghani A, Doroudchi M, Kalantari T, Pezeshki AM, Ghaderi A (2005) Heterozygosity in CTLA-4 gene and severe preeclampsia. Int J Gynaecol Obstet 88:19–24

    Article  PubMed  CAS  Google Scholar 

  • Segurado R, Detera-Wadleigh SD, Levinson DF, Lewis CM, Gill M, Nurnberger JI, Craddock N, DePaulo JR, Baron M, Gershon ES Ekholm J, Cichon S, Turecki G, Claes S, Kelsoe JR, Schofield PR, Badenhop RF, Morissette J, Coon H, Blackwood D, McInnes LA, Foroud T, Edenberg HJ, Reich T, Rice JP, Goate A, McInnis MG, McMahon FJ, Badner JA, Goldin LR, Bennett P, Willour VL, Zandi PP, Liu J, Gilliam C, Juo SH, Berrettini WH, Yoshikawa T, Peltonen L, Lonnqvist J, Nothen MM, Schumacher J, Windemuth C, Rietschel M, Propping P, Maier W, Alda M, Grof P, Rouleau GA, Del-Favero J, Van Broeckhoven C, Mendlewicz J, Adolfsson R, Spence MA, Luebbert H, Adams LJ, Donald JA, Mitchell PB, Barden N, Shink E, Byerley W, Muir W, Visscher PM, Macgregor S, Gurling H, Kalsi G, McQuillin A, Escamilla MA, Reus VI, Leon P, Freimer NB, Ewald H, Kruse TA, Mors O, Radhakrishna U, Blouin JL, Antonarakis SE, Akarsu N (2003) Genome scan meta-analysis of schizophrenia and bipolar disorder, part III Bipolar disorder. Am J Hum Genet 73:49–62

    Article  PubMed  CAS  Google Scholar 

  • Trikalinos T, Karvouni A, Zintzaras E, Ylisaukko-Oja T, Peltonen L, Jarvela I, Ioannidis JP (2005) A heterogeneity-based genome search meta-analysis for autism-spectrum disorders. Mol Psych 11:29–36

    Article  CAS  Google Scholar 

  • Ueda H, Howson JM, Esposito L, Heward J, Snook H, Chamberlain G, Rainbow DB, Hunter KM, Smith AN, Di Genova G, Herr MH, Dahlman I, Payne F, Smyth D, Lowe C, Twells RC, Howlett S, Healy B, Nutland S, Rance HE, Everett V, Smink LJ, Lam AC, Cordell HJ, Walker NM, Bordin C, Hulme J, Motzo C, Cucca F, Hess JF, Metzker ML, Rogers J, Gregory S, Allahabadia A, Nithiyananthan R, Tuomilehto-Wolf E, Tuomilehto J, Bingley P, Gillespie KM, Undlien DE, Ronningen KS, Guja C, Ionescu-Tirgoviste C, Savage DA, Maxwell AP, Carson DJ, Patterson CC, FranklynJA, Clayton DG, Peterson LB, Wicker LS, Todd JA, Gough SC (2003) Association of the T-cell regulatory gene CTLA4 with susceptibility to autoimmune disease. Nature 423:506–511

    Article  PubMed  CAS  Google Scholar 

  • van Heel DA, Fisher SA, Kirby A, Daly MJ, Rioux JD, Lewis CM (2004) Genome Scan Meta-Analysis Group of the IBD International Genetics Consortium. Inflammatory bowel disease susceptibility loci defined by genome scan meta-analysis of 1952 affected relative pairs. Hum Mol Genet 13:763–770

    Article  PubMed  CAS  Google Scholar 

  • Wise LH, Lanchbury JS, LewisCM (1999) Meta-analysis of genome searches. Ann Hum Genet 63:263–272

    Article  PubMed  CAS  Google Scholar 

  • Zintzaras E, Ioannidis JP (2005a) Heterogeneity testing in meta-analysis of genome searches. Genet Epidemiol 28:123–137

    Article  Google Scholar 

  • Zintzaras E, Ioannidis JP (2005b) HEGESMA: genome search meta-analysis and heterogeneity testing. Bioinformatics 21:3672–3673

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Biomathematics, University of Thessaly School of Medicine, Papakyriazi 22, Larissa, 41222, Greece

    Elias Zintzaras & Georgios Kitsios

  2. Division of Environmental and Life Sciences, Macquarie University, NSW, 2109, Macquarie, Australia

    Gavan A. Harrison

  3. Department of Medical Genetics, University of Helsinki, 00014, Helsinki, Finland

    Hannele Laivuori & Juha Kere

  4. Department of Clinical Genetics, HUSLAB, University of Helsinki, 00014, Helsinki, Finland

    Hannele Laivuori

  5. Department of Biosciences at Novum, Karolinska Institute, Huddinge, 14157, Sweden

    Katja Kivinen & Juha Kere

  6. Department of Obstetrics and Gynaecology, University of Thessaly School of Medicine, Larissa, 41222, Greece

    Ioannis Messinis

  7. Department of Nephrology, University of Thessaly School of Medicine, Larissa, 41222, Greece

    Ioannis Stefanidis

  8. Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, 45110, Greece

    John P. A. Ioannidis

  9. Department of Medicine, Tufts University School of Medicine, Boston, 02111, USA

    John P. A. Ioannidis

Authors
  1. Elias Zintzaras
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Georgios Kitsios
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gavan A. Harrison
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hannele Laivuori
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Katja Kivinen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Juha Kere
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ioannis Messinis
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ioannis Stefanidis
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. John P. A. Ioannidis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Elias Zintzaras.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zintzaras, E., Kitsios, G., Harrison, G.A. et al. Heterogeneity-based genome search meta-analysis for preeclampsia. Hum Genet 120, 360–370 (2006). https://doi.org/10.1007/s00439-006-0214-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00439-006-0214-1

Keywords

Search

Navigation