Edinburgh Research Explorer

Combining Meta- and mega-analytic approaches for multi-site diffusion imaging based genetic studies: From the enigma-DTI working group

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Neda Jahanshad
  • Peter Kochunov
  • Thomas E. Nichols
  • Emma Sprooten
  • René C. Mandl
  • Laura Almasy
  • Rachel M. Brouwer
  • Joanne E. Curran
  • Greig I. De Zubicaray
  • Rali Dimitrova
  • Peter T. Fox
  • L. Elliot Hong
  • Bennett A. Landman
  • Hervé Lemaitre
  • Lorna Lopez
  • Katie L. McMahon
  • Braxton D. Mitchell
  • Rene L. Olvera
  • Charles P. Peterson
  • Jessika E. Sussmann
  • Arthur W. Toga
  • Margaret J. Wright
  • Susan N. Wright
  • Dorret I. Boomsma
  • René S. Kahn
  • Anouk Den Braber
  • Hilleke E.Hulshoff Pol
  • Douglas Williamson
  • John Blangero
  • Dennis Van't Ent
  • David C. Glahn
  • Paul M. Thompson

Related Edinburgh Organisations

Original languageEnglish
Title of host publication2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Electronic)9781467319591
Publication statusPublished - 1 Jan 2014
Event2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 - Beijing, China
Duration: 29 Apr 20142 May 2014


Conference2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014


Meta-analyses estimate a statistical effect size for a test or an analysis by combining results from multiple studies without necessarily having access to each individual study's raw data. Multi-site meta-analysis is crucial for imaging genetics, as single sites rarely have a sample size large enough to pick up effects of single genetic variants associated with brain measures. However, if raw data can be shared, combining data in a "mega-analysis" is thought to improve power and precision in estimating global effects. As part of an ENIGMA-DTI investigation, we use fractional anisotropy (FA) maps from 5 studies (total N=2, 203 subjects, aged 9-85) to estimate heritability. We combine the studies through meta-and mega-analyses as well as a mixture of the two - combining some cohorts with mega-analysis and meta-analyzing the results with those of the remaining sites. A combination of mega-and meta-approaches may boost power compared to meta-analysis alone.

    Research areas

  • DTI, ENIGMA, Heritability, Imaging genetics, Mega-analysis, Meta-analysis, Multi-site


2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014


Beijing, China

Event: Conference

ID: 109401754