IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0008347.html
   My bibliography  Save this article

Investigating the Role of Mitochondrial Haplogroups in Genetic Predisposition to Meningococcal Disease

Author

Listed:
  • Antonio Salas
  • Laura Fachal
  • Sonia Marcos-Alonso
  • Ana Vega
  • Federico Martinón-Torres
  • Grupo de investigación ESIGEM (Estudio Sobre la Influencia Genética en la Enfermedad Meningocócica) ¶

Abstract

Background and Aims: Meningococcal disease remains one of the most important infectious causes of death in industrialized countries. The highly diverse clinical presentation and prognosis of Neisseria meningitidis infections are the result of complex host genetics and environmental interactions. We investigated whether mitochondrial genetic background contributes to meningococcal disease (MD) susceptibility. Methodology/Principal Findings: Prospective controlled study was performed through a national research network on MD that includes 41 Spanish hospitals. Cases were 307 paediatric patients with confirmed MD, representing the largest series of MD patients analysed to date. Two independent sets of ethnicity-matched control samples (CG1 [N = 917]), and CG2 [N = 616]) were used for comparison. Cases and controls underwent mtDNA haplotyping of a selected set of 25 mtDNA SNPs (mtSNPs), some of them defining major European branches of the mtDNA phylogeny. In addition, 34 ancestry informative markers (AIMs) were genotyped in cases and CG2 in order to monitor potential hidden population stratification. Samples of known African, Native American and European ancestry (N = 711) were used as classification sets for the determination of ancestral membership of our MD patients. A total of 39 individuals were eliminated from the main statistical analyses (including fourteen gypsies) on the basis of either non-Spanish self-reported ancestry or the results of AIMs indicating a European membership lower than 95%. Association analysis of the remaining 268 cases against CG1 suggested an overrepresentation of the synonym mtSNP G11719A variant (Pearson's chi-square test; adjusted P-value = 0.0188; OR [95% CI] = 1.63 [1.22–2.18]). When cases were compared with CG2, the positive association could not be replicated. No positive association has been observed between haplogroup (hg) status of cases and CG1/CG2 and hg status of cases and several clinical variants. Conclusions: We did not find evidence of association between mtSNPs and mtDNA hgs with MD after carefully monitoring the confounding effect of population sub-structure. MtDNA variability is particularly stratified in human populations owing to its low effective population size in comparison with autosomal markers and therefore, special care should be taken in the interpretation of seeming signals of positive associations in mtDNA case-control association studies.

Suggested Citation

  • Antonio Salas & Laura Fachal & Sonia Marcos-Alonso & Ana Vega & Federico Martinón-Torres & Grupo de investigación ESIGEM (Estudio Sobre la Influencia Genética en la Enfermedad Meningocócica) ¶, 2009. "Investigating the Role of Mitochondrial Haplogroups in Genetic Predisposition to Meningococcal Disease," PLOS ONE, Public Library of Science, vol. 4(12), pages 1-8, December.
    • Handle: RePEc:plo:pone00:0008347
    DOI: 10.1371/journal.pone.0008347
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0008347
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0008347&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0008347?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. John P A Ioannidis, 2005. "Why Most Published Research Findings Are False," PLOS Medicine, Public Library of Science, vol. 2(8), pages 1-1, August.
    2. B. Devlin & Kathryn Roeder, 1999. "Genomic Control for Association Studies," Biometrics, The International Biometric Society, vol. 55(4), pages 997-1004, December.
    3. John P A Ioannidis, 2007. "Why Most Published Research Findings Are False: Author's Reply to Goodman and Greenland," PLOS Medicine, Public Library of Science, vol. 4(6), pages 1-2, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hastie, Nicholas D. & van der Loos, Matthijs J. H. M. & Vitart, Veronique & Völzke, Henry & Wellmann, Jürgen & Yu, Lei & Zhao, Wei & Allik, Jüri & Attia, John R. & Bandinelli, Stefania & Bastardot,, 2013. "GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment," Scholarly Articles 13383543, Harvard University Department of Economics.
    2. Matthijs J H M van der Loos & Cornelius A Rietveld & Niina Eklund & Philipp D Koellinger & Fernando Rivadeneira & Gonçalo R Abecasis & Georgina A Ankra-Badu & Sebastian E Baumeister & Daniel J Benjami, 2013. "The Molecular Genetic Architecture of Self-Employment," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-15, April.
    3. Lei Zhang & Yu-Fang Pei & Jian Li & Christopher J Papasian & Hong-Wen Deng, 2009. "Univariate/Multivariate Genome-Wide Association Scans Using Data from Families and Unrelated Samples," PLOS ONE, Public Library of Science, vol. 4(8), pages 1-12, August.
    4. Dominic Holland & Oleksandr Frei & Rahul Desikan & Chun-Chieh Fan & Alexey A Shadrin & Olav B Smeland & V S Sundar & Paul Thompson & Ole A Andreassen & Anders M Dale, 2020. "Beyond SNP heritability: Polygenicity and discoverability of phenotypes estimated with a univariate Gaussian mixture model," PLOS Genetics, Public Library of Science, vol. 16(5), pages 1-30, May.
    5. Vincent Michaud & Eulalie Lasseaux & David J. Green & Dave T. Gerrard & Claudio Plaisant & Tomas Fitzgerald & Ewan Birney & Benoît Arveiler & Graeme C. Black & Panagiotis I. Sergouniotis, 2022. "The contribution of common regulatory and protein-coding TYR variants to the genetic architecture of albinism," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    6. Alexander Frankel & Maximilian Kasy, 2022. "Which Findings Should Be Published?," American Economic Journal: Microeconomics, American Economic Association, vol. 14(1), pages 1-38, February.
    7. Jyotirmoy Sarkar, 2018. "Will P†Value Triumph over Abuses and Attacks?," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 7(4), pages 66-71, July.
    8. Parsa Akbari & Dragana Vuckovic & Luca Stefanucci & Tao Jiang & Kousik Kundu & Roman Kreuzhuber & Erik L. Bao & Janine H. Collins & Kate Downes & Luigi Grassi & Jose A. Guerrero & Stephen Kaptoge & Ju, 2023. "A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    9. Stanley, T. D. & Doucouliagos, Chris, 2019. "Practical Significance, Meta-Analysis and the Credibility of Economics," IZA Discussion Papers 12458, Institute of Labor Economics (IZA).
    10. Karin Langenkamp & Bodo Rödel & Kerstin Taufenbach & Meike Weiland, 2018. "Open Access in Vocational Education and Training Research," Publications, MDPI, vol. 6(3), pages 1-12, July.
    11. Kevin J. Boyle & Mark Morrison & Darla Hatton MacDonald & Roderick Duncan & John Rose, 2016. "Investigating Internet and Mail Implementation of Stated-Preference Surveys While Controlling for Differences in Sample Frames," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 64(3), pages 401-419, July.
    12. Gang Zheng & Zhaohai Li & Mitchell H. Gail & Joseph L. Gastwirth, 2010. "Impact of Population Substructure on Trend Tests for Genetic Case–Control Association Studies," Biometrics, The International Biometric Society, vol. 66(1), pages 196-204, March.
    13. Jelte M Wicherts & Marjan Bakker & Dylan Molenaar, 2011. "Willingness to Share Research Data Is Related to the Strength of the Evidence and the Quality of Reporting of Statistical Results," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-7, November.
    14. Valentine, Kathrene D & Buchanan, Erin Michelle & Scofield, John E. & Beauchamp, Marshall T., 2017. "Beyond p-values: Utilizing Multiple Estimates to Evaluate Evidence," OSF Preprints 9hp7y, Center for Open Science.
    15. Anton, Roman, 2014. "Sustainable Intrapreneurship - The GSI Concept and Strategy - Unfolding Competitive Advantage via Fair Entrepreneurship," MPRA Paper 69713, University Library of Munich, Germany, revised 01 Feb 2015.
    16. Sandosh Padmanabhan & Olle Melander & Toby Johnson & Anna Maria Di Blasio & Wai K Lee & Davide Gentilini & Claire E Hastie & Cristina Menni & Maria Cristina Monti & Christian Delles & Stewart Laing & , 2010. "Genome-Wide Association Study of Blood Pressure Extremes Identifies Variant near UMOD Associated with Hypertension," PLOS Genetics, Public Library of Science, vol. 6(10), pages 1-11, October.
    17. Dudek, Thomas & Brenøe, Anne Ardila & Feld, Jan & Rohrer, Julia, 2022. "No Evidence That Siblings' Gender Affects Personality across Nine Countries," IZA Discussion Papers 15137, Institute of Labor Economics (IZA).
    18. Uwe Hassler & Marc‐Oliver Pohle, 2022. "Unlucky Number 13? Manipulating Evidence Subject to Snooping," International Statistical Review, International Statistical Institute, vol. 90(2), pages 397-410, August.
    19. Jakris Eu-ahsunthornwattana & E Nancy Miller & Michaela Fakiola & Wellcome Trust Case Control Consortium 2 & Selma M B Jeronimo & Jenefer M Blackwell & Heather J Cordell, 2014. "Comparison of Methods to Account for Relatedness in Genome-Wide Association Studies with Family-Based Data," PLOS Genetics, Public Library of Science, vol. 10(7), pages 1-20, July.
    20. Frederique Bordignon, 2020. "Self-correction of science: a comparative study of negative citations and post-publication peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1225-1239, August.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0008347. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.