Reduced fractional anisotropy in the uncinate fasciculus in patients with major depression carrying the met-allele of the Val66Met brain-derived neurotrophic factor genotype.

Department of Psychiatry, Institute of Neuroscience, University of Dublin, Trinity College Dublin, Dublin, Ireland.
American Journal of Medical Genetics Part B Neuropsychiatric Genetics (Impact Factor: 3.23). 05/2012; 159B(5):537-48. DOI: 10.1002/ajmg.b.32060
Source: PubMed

ABSTRACT Experimental studies support a neurotrophic hypothesis of major depressive disorder (MDD). The aim of this study was to determine the effect of Val66Met brain-derived neurotrophic factor (BDNF) polymorphism on the white matter fiber tracts connecting hippocampus and amygdala with the prefrontal lobe in a sample of patients with MDD and healthy controls. Thirty-seven patients with MDD and 42 healthy volunteers were recruited. Diffusion tensor imaging (DTI) data with 61 diffusion directions were obtained with MRI 3 Tesla scanner. Deterministic tractography was applied with ExploreDTI and Val66Met BDNF SNP (rs6265) was genotyped. Fiber tracts connecting the hippocampus and amygdala with the prefrontal lobe, namely uncinate fasciculus (UF), fornix, and cingulum were analyzed. A significant interaction was found in the UF between BDNF alleles and diagnosis. Patients carrying the BDNF met-allele had smaller fractional anisotropy (FA) in the UF compared to those patients homozygous for val-allele and compared to healthy subjects carrying the met-allele. A significant three-way interaction was detected between region of the cingulum (dorsal, rostral, and parahippocampal regions), brain hemisphere and BDNF genotype. Larger FA was detectable in the left rostral cingulum for met-allele carriers when compared to val/val alelle carriers. We provide evidence for the importance of the neurotrophic involvement in limbic and prefrontal connections. The met-allele of the BDNF polymorphism seems to render subjects more vulnerable for dysfunctions associated with the UF, a tract known to be related to negative emotional-cognitive processing bias, declarative memory problems, and autonoetic self awareness.

  • [Show abstract] [Hide abstract]
    ABSTRACT: Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.
    NeuroImage 03/2014; · 6.25 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Recent literature shows that diffusion tensor properties can be estimated more accurately with diffusion kurtosis imaging (DKI) than with diffusion tensor imaging (DTI). Furthermore, the additional non-Gaussian diffusion features from DKI can be sensitive markers for tissue characterization. Despite these benefits, DKI is more susceptible to data artifacts than DTI due to its increased model complexity, higher acquisition demands, and longer scanning times. To increase the reliability of diffusion tensor and kurtosis estimates, we propose a robust estimation procedure for DKI. We have developed a robust and linear estimation framework, coined REKINDLE (Robust Extraction of Kurtosis INDices with Linear Estimation), consisting of an iteratively reweighted linear least squares approach. Simulations are performed, in which REKINDLE is evaluated and compared with the widely used RESTORE (Robust EStimation of Tensors by Outlier REjection) method. Simulations demonstrate that in the presence of outliers, REKINDLE can estimate diffusion and kurtosis indices reliably and with a 10-fold reduction in computation time compared with RESTORE. We have presented and evaluated REKINDLE, a linear and robust estimation framework for DKI. While REKINDLE has been developed for DKI, it is by design also applicable to DTI and other diffusion models that can be linearized. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.
    Magnetic Resonance in Medicine 03/2014; · 3.27 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Purpose: Low back pain is a global health problem in which more than 40% is caused by lumbar intervertebral disc degeneration (LDD). ADAMTS-5 (A disintegrin and metalloproteinase with thrombospondin motifs-5) was shown to be involved in LDD by functional analyses. To identify whether there is an association between ADAMTS-5 and LDD, and what is the contribution of ADAMTS-5 genetic polymorphisms to MD (Mean diffusivity) changes in lumbar IVD (Intervertebral disc). We firstly genotyped selected ADAMTS-5 SNPs (Single nucleotide polymorphisms) in a Chinese Han population. After the primary analyses of allelic, genotypic, and haplotypic association, we performed SNP-SNP interaction analysis. We subsequently genotyped another 50 participants and acquired the corresponding MD values from individual lumbar IVDs. The association analysis between the genotypic groups divided by the above positive SNPs and the corresponding MD values were also performed. Significant associations were identified in rs151058, rs229052, and rs162502. None of the 2-SNP haplotypic analysis survived the 10,000 permutation test. The following interaction analysis demonstrated that rs151058 was strong associated with LDD when conditioning on rs162502. Significant difference of MD values between AA and G+ carriers was identified in rs162502. This is the first study indicating that the SNPs of ADAMTS-5 may contribute to predisposition of LDD. An interaction between rs151058 and rs229052 may exist in ADAMTS-5 with LDD. The rs162502 might be associated with altered MD values. © 2014 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res.
    Journal of Orthopaedic Research 01/2014; · 2.88 Impact Factor


1 Download
Available from
Sep 15, 2014