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Do Candidate Genes Affect the Brain's White Matter Microstructure? Large-Scale Evaluation of 6,165 Diffusion MRI Scans
By
Neda Jahanshad,
Habib Ganjgahi,
Janita Bralten,
Anouk den Braber,
Joshua Faskowitz,
Annchen R. Knodt,
Hervé Lemaitre,
Talia M. Nir,
Binish Patel,
Stuart Richie,
Emma Sprooten,
Martine Hoogman,
Kimm van Hulzen,
Artemis Zavaliangos-Petropulu,
Marcel P. Zwiers,
Laura Almasy,
Mark E Bastin,
Matt A Bernstein,
John Blangero,
Joanne Curran,
Ian J Deary,
Greig I de Zubicary,
Ravi Duggirala,
Simon E. Fisher,
Barbara Franke,
Peter Fox,
David Goldman,
Asta K. Haberg,
Ahmad Hariri,
L Elliot Hong,
Matt Huentelman,
Nicholas G Martin,
Jean-Luc Martinot,
Andrew McIntosh,
Katie L. McMahon,
Sarah E. Medland,
Braxton D Mitchell,
Susana Muñoz Maniega,
Rene L. Olvera,
Jaap Oosterlaan,
Charles Peterson,
Natalie Royle,
Andrew J. Saykin,
Gunter Schumann,
John Starr,
Elliot A Stein,
Jessika Sussmann,
Maria del. C Valdés Hernández,
Dennis van’t Ent,
Joanna M. Wardlaw,
Michael W. Weiner,
Douglas E. Williamson,
Anderson M. Winkler,
Margaret J Wright,
Yihong Yang,
Paul M. Thompson,
David C. Glahn,
Thomas E. Nichols,
Peter Kochunov
Posted 20 Feb 2017
bioRxiv DOI: 10.1101/107987
Susceptibility genes for psychiatric and neurological disorders - including APOE, BDNF, CLU, CNTNAP2, COMT, DISC1, DTNBP1, ErbB4, HFE, NRG1, NTKR3, and ZNF804A - have been reported to affect white matter (WM) microstructure in the healthy human brain, as assessed through diffusion tensor imaging (DTI). However, effects of single nucleotide polymorphisms (SNPs) in these genes explain only a small fraction of the overall variance and are challenging to detect reliably in single cohort studies. To date, few studies have evaluated the reproducibility of these results. As part of the ENIGMA-DTI consortium, we pooled regional fractional anisotropy (FA) measures for 6,165 subjects (CEU ancestry N=4,458) from 11 cohorts worldwide to evaluate effects of 15 candidate SNPs by examining their associations with WM microstructure. Additive association tests were conducted for each SNP. We used several meta-analytic and mega-analytic designs, and we evaluated regions of interest at multiple granularity levels. The ENIGMA-DTI protocol was able to detect single-cohort findings as originally reported. Even so, in this very large sample, no significant associations remained after multiple-testing correction for the 15 SNPs investigated. Suggestive associations (1.3x10-4 < p < 0.05, uncorrected) were found for BDNF, COMT, and ZNF804A in specific tracts. Meta- and mega-analyses revealed similar findings. Regardless of the approach, the previously reported candidate SNPs did not show significant associations with WM microstructure in this largest genetic study of DTI to date; the negative findings are likely not due to insufficient power. Genome-wide studies, involving large-scale meta-analyses, may help to discover SNPs robustly influencing WM microstructure.
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