White matter integrity as an intermediate phenotype: Exploratory genome-wide association analysis in individuals at high risk of bipolar disorder
Division of Psychiatry, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, UK. Electronic address: .
12/2012; 206(2-3). DOI: 10.1016/j.psychres.2012.11.002
White matter integrity, as measured using diffusion tensor imaging (DTI), is reduced in individuals with bipolar disorder (BD), their unaffected relatives and carriers of specific risk-alleles. Fractional anisotropy (FA), an index of white matter integrity, is highly heritable but the genetic architecture of this trait has received little investigation. In this study we performed a genome-wide association study with FA as quantitative phenotype, in unaffected relatives of patients with BD (N=70) and a matched control group (N=80). Amongst our top results were SNPs located in genes involved in cell adhesion, white matter development and neuronal plasticity. Pathway analysis of the top associated polymorphisms and genes confirmed the enrichment of processes relevant to BD and white matter development, including axon guidance, ErbB-signalling neurotrophin signalling, phosphatidylinositol signalling, and cell adhesion. The majority of genes implicated in these pathways were differentially associated with FA in individuals at high familial risk, suggesting interactions with genetic background or environmental factors secondary to familial risk for BD. Although the present findings require independent replication, the results encourage the use of global FA as a quantitative phenotype in future large-scale studies which may help to identify the biological processes underlying reduced FA in BD and other psychiatric disorders.
Available from: Bruno Etain
- "In BD, GWAS using other phenotypic aspects than classical categorical case/control classifications, are beginning to emerge (Craddock and Sklar, 2013). Published studies focused on several quantitative traits in BD, such as personality traits (Alliey-Rodriguez et al., 2011), negative mood delusions dimension (Meier et al., 2012), temperament (Greenwood et al., 2012) or white matter integrity (Sprooten et al., 2013). This is again consistent with the notion that quantitative traits may be relevant for detecting the involvement of genes of moderate effect. "
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Emotional reactivity has been proposed as a relevant intermediate phenotype of bipolar disorder (BD). Our goal was to identify genetic factors underlying emotional reactivity in a sample of bipolar patients.
Affect intensity (a proxy measure of emotional reactivity) was measured in a sample of 281 euthymic patients meeting DSM-IV criteria for BD. We use a validated dimensional tool, the 40-item self-report Affect Intensity Measure scale developed by Larsen and Diener. Patients with BD were genotyped for 475. 740 SNPs (using Illumina HumanHap550 Beadchips or HumanHap610 Quad chip). Association was investigated with a general mixed regression model of the continuous trait against genotypes, including gender as covariate.
Four regions (1p31.3, 3q13.11, 11p15.1 and 11q14.4) with a p-value lower or equal to 5×10(-6) were identified. In these regions, the joint effect of the four variants accounted for 24.5% of the variance of AIM score. Epistasis analysis did not detect interaction between these variants. In the 11p15.1 region, the rs10766743 located in the intron of the NELL1 gene remained significant after correction for multiple testing (p=2×10(-7)).
These findings illustrate that focusing on quantitative intermediate phenotypes can facilitate the identification of genetic susceptibility variants in BD.
Journal of Affective Disorders 09/2015; 188:101-106. DOI:10.1016/j.jad.2015.08.037 · 3.38 Impact Factor
Available from: Sean N Hatton
- "Lopez et al. (2012) conducted a GWAS on this general white matter integrity factor on 535 subjects of the LBC1936 study and found suggestive genome-wide association with SNPs in ADAMTS18 and LOC388630. Initial studies suggest that a proportion of the variance in fiber integrity can be predicted from common variants (Kohannim et al. 2012; Jahanshad et al. 2012, 2013c; Thompson and Jahanshad 2012; Braskie et al. 2012; Sprooten et al. 2013). "
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ABSTRACT: This article reviews work published by the ENIGMA Consortium and its Working Groups (http://enigma.ini.usc.edu). It was written collaboratively; P.T. wrote the first draft and all listed authors revised and edited the document for important intellectual content, using Google Docs for parallel editing, and approved it. Some ENIGMA investigators contributed to the design and implementation of ENIGMA or provided data but did not participate in the analysis or writing of this report. A complete listing of ENIGMA investigators is available at http://enigma.ini.usc.edu/publications/the-enigma-consortium-in-review/ For ADNI, some investigators contributed to the design and implementation of ADNI or provided data but did not participate in the analysis or writing of this report. A complete listing of ADNI investigators is available at http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ ADNI_Acknowledgement_List.pdf The work reviewed here was funded by a large number of federal and private agencies worldwide, listed in Stein et al. (2012); the funding for listed consortia is also itemized in Stein et al. (2012).
Brain Imaging and Behavior 01/2014; 8(2). DOI:10.1007/s11682-013-9269-5 · 4.60 Impact Factor
Available from: Joanne E Curran
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ABSTRACT: The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).
NeuroImage 04/2013; 81. DOI:10.1016/j.neuroimage.2013.04.061 · 6.36 Impact Factor
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