Advertisement

Human Genetics

, Volume 120, Issue 3, pp 360–370 | Cite as

Heterogeneity-based genome search meta-analysis for preeclampsia

  • Elias Zintzaras
  • Georgios Kitsios
  • Gavan A. Harrison
  • Hannele Laivuori
  • Katja Kivinen
  • Juha Kere
  • Ioannis Messinis
  • Ioannis Stefanidis
  • John P. A. Ioannidis
Original Investigation

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.

Keywords

Preeclampsia Average Rank Weighted Analysis Genome Scan HELLP Syndrome 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 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 120:45–52PubMedCrossRefGoogle Scholar
  2. 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 8:1799–1805CrossRefGoogle Scholar
  3. 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 184:1345–1350PubMedCrossRefGoogle Scholar
  4. 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 110:8–11PubMedCrossRefGoogle Scholar
  5. 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 28:30–33PubMedGoogle Scholar
  6. 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 23:1863–1868PubMedCrossRefGoogle Scholar
  7. 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 12:1865–1873CrossRefGoogle Scholar
  8. Dempfle A, Loesgen S (2004) Meta-analysis of linkage studies for complex diseases: an overview of methods and a simulation study. Ann Hum Genet 68:69–83PubMedCrossRefGoogle Scholar
  9. 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 19:1707–1728PubMedCrossRefGoogle Scholar
  10. 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 48:1200–1206PubMedCrossRefGoogle Scholar
  11. 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 76:849–862PubMedCrossRefGoogle Scholar
  12. GOPEC Consortium (2005) Disentangling fetal and maternal susceptibility for pre-eclampsia: a British multicenter candidate-gene study. Am J Hum Genet 77:127–131CrossRefGoogle Scholar
  13. 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 60:1158–1167PubMedGoogle Scholar
  14. 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 38:3–5Google Scholar
  15. 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 162:3–16PubMedCrossRefGoogle Scholar
  16. 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 13:2325–2332PubMedCrossRefGoogle Scholar
  17. 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 21:1221–1228PubMedCrossRefGoogle Scholar
  18. 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 22:1655–1662PubMedCrossRefGoogle Scholar
  19. Laasanen J, Hiltunen M, Punnonen K, Mannermaa A, Heinonen S (2002) Fibrinogen and factor VII promoter polymorphisms in women with preeclampsia. Obstet Gynecol 100:317–320PubMedCrossRefGoogle Scholar
  20. 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 9:758–764PubMedCrossRefGoogle Scholar
  21. 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 105:94–113Google Scholar
  22. 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 21:23–38CrossRefGoogle Scholar
  23. 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 72:168–177PubMedCrossRefGoogle Scholar
  24. Lau J, Ioannidis JP, Schmid CH (1998) Summing up evidence: one answer is not always enough. Lancet 351:123–127PubMedCrossRefGoogle Scholar
  25. 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 73:17–33PubMedCrossRefGoogle Scholar
  26. Lewis CM, Levinson DF (2006) Testing for genetic heterogeneity in the genome search meta-analysis method. Genet Epidemiol 30:348–355PubMedCrossRefGoogle Scholar
  27. 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 73:34–48PubMedCrossRefGoogle Scholar
  28. 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 67:1581–1585PubMedCrossRefGoogle Scholar
  29. 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 23:449–465PubMedCrossRefGoogle Scholar
  30. 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 46:242–253PubMedGoogle Scholar
  31. Rothman KJ (1990) No adjustments are needed for multiple comparisons. Epidemiology 1:43–46PubMedCrossRefGoogle Scholar
  32. Samsami Dehaghani A, Doroudchi M, Kalantari T, Pezeshki AM, Ghaderi A (2005) Heterozygosity in CTLA-4 gene and severe preeclampsia. Int J Gynaecol Obstet 88:19–24PubMedCrossRefGoogle Scholar
  33. 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 73:49–62PubMedCrossRefGoogle Scholar
  34. 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 11:29–36CrossRefGoogle Scholar
  35. 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 423:506–511PubMedCrossRefGoogle Scholar
  36. 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 13:763–770PubMedCrossRefGoogle Scholar
  37. Wise LH, Lanchbury JS, LewisCM (1999) Meta-analysis of genome searches. Ann Hum Genet 63:263–272PubMedCrossRefGoogle Scholar
  38. Zintzaras E, Ioannidis JP (2005a) Heterogeneity testing in meta-analysis of genome searches. Genet Epidemiol 28:123–137CrossRefGoogle Scholar
  39. Zintzaras E, Ioannidis JP (2005b) HEGESMA: genome search meta-analysis and heterogeneity testing. Bioinformatics 21:3672–3673CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Elias Zintzaras
    • 1
  • Georgios Kitsios
    • 1
  • Gavan A. Harrison
    • 2
  • Hannele Laivuori
    • 3
    • 4
  • Katja Kivinen
    • 5
  • Juha Kere
    • 5
    • 3
  • Ioannis Messinis
    • 6
  • Ioannis Stefanidis
    • 7
  • John P. A. Ioannidis
    • 8
    • 9
  1. 1.Department of BiomathematicsUniversity of Thessaly School of MedicineLarissaGreece
  2. 2.Division of Environmental and Life SciencesMacquarie UniversityMacquarieAustralia
  3. 3.Department of Medical GeneticsUniversity of HelsinkiHelsinkiFinland
  4. 4.Department of Clinical Genetics, HUSLABUniversity of HelsinkiHelsinkiFinland
  5. 5.Department of Biosciences at NovumKarolinska InstituteHuddingeSweden
  6. 6.Department of Obstetrics and GynaecologyUniversity of Thessaly School of MedicineLarissaGreece
  7. 7.Department of NephrologyUniversity of Thessaly School of Medicine LarissaGreece
  8. 8.Department of Hygiene and EpidemiologyUniversity of Ioannina School of MedicineIoanninaGreece
  9. 9.Department of MedicineTufts University School of MedicineBostonUSA

Personalised recommendations