In this paper, we mapped the influences of the BDNF Val66Met polymorphism on brain white matter architecture, extending genetic association analyses to 3D images. The Val allele was found to be associated with up to 15% reduction in FA in major fiber tracts, especially in the splenium of the corpus callosum and the optic radiation on the left, the left IFO/ILF, and superior corona radiata
. Moreover, associations between BDNF and FA were consistent in the two sub-groups of the subjects in the splenium of the corpus callosum and the optic radiation on the left. Although these two sub-groups were not truly independent of each other as all subjects were recruited from the same twin registry and their brain images acquired using the same MR scanner, testing BDNF-FA associations in these two sub-groups might still help to support the consistency and robustness of the associations, assuming that the genetic determinants for white matter architecture are independent across families (Van Steen et al., 2005
). In other words, the results are robust to subsampling within the same cohort, but further analysis of new cohorts that were independently assessed from the outset will be valuable as more large DTI datasets become available. Findings in this paper are consistent with those in our previous study, where genetic influences accounted for around 80% of the variance in FA in these regions (Chiang et al., 2009
). This suggests that BDNF is a key candidate gene that influences white matter integrity.
In all brain regions affected by the BDNF polymorphism, the additive effect of the Val allele was associated with a lower
FA. Supporting the direction and validity of this effect, a recent conference abstract (Alam et al., 2010
) reported significant BDNF genotype-dependent differences in FA, largely restricted to the body of the corpus callosum, where the Val allele was associated with a lower FA. In that study, DTI scans were collected from 85 young healthy volunteers (mean age: 33.5±9.6 years; 46 men/39 women) – a sample of around one fifth the size of that analyzed here. FA is usually considered as a measure of fiber myelination and organization (Beaulieu, 2002
). Higher FA reflects greater myelination, and a directional coherence in the myelinated fiber tracts (Beaulieu, 2002
), and has generally been linked with better functional performance (Chiang et al., 2009
). Even so, lower FA does not necessarily always imply lower white matter integrity, and may reflect (1) larger axonal diameter, which results in increased intracellular water content (Takahashi et al., 2002
), (2) greater fiber branching, or (3) higher intravoxel fiber crossing in, e.g., where the optic radiation and corpus callosum fibers intermix (see ) (Tuch et al., 2005
). The above hypotheses may be tested by comparing the T1-weighted and DT images in the same subjects using voxel-based morphometry (Ashburner and Friston, 2000
), where larger axonal diameter or more extensive fiber branching reflected by lower FA may also be detectable as reduced white matter density. Tuch et al. (2005)
showed that lower
FA, at the junction of the optic radiation and corpus callosum, was associated with a faster reaction time to visual stimuli. Schmithorst and Wilke (2002)
found that FA in the corona radiata
and internal capsule was lower in musicians than non-musicians. They attributed this to the rearrangement of neural representations for motor control after intensive musical training. The association between lower FA and the Val BDNF allele in this study may provide another exception to the “higher FA is always better” hypothesis.
We found that BDNF variants significantly modulated the association between FA and the OBJ sub-scale in the splenium of the corpus callosum, where the Val allele was associated with a positive FA-OBJ correlation, whereas the Met allele was associated with no correlation or with a negative correlation. The callosal splenium interconnects bilateral primary visual and visual association areas of the parietal and occipital cortex, and is relevant for visuospatial memory (Rudge and Warrington, 1991
). Positive correlation between FA and IQ may support the theory that optimal intellectual performance typically requires high processing speed and short reaction times, which are influenced by axonal myelination levels (Arbuthnott et al., 1980
). Furthermore, the myelination of white matter fibers may itself be enhanced by neuronal activity (Fields, 2005
). On the other hand, negative correlation between FA and IQ may reflect greater fiber crossing or branching that lowers FA, as in a broadly connected cognitive network (Tuch et al., 2005
). Reduced FA in one brain region may also indicate that during the maturation or improvement of cognitive function, myelination may be greater in other brain regions to optimize processing efficiency (Schmithorst and Wilke, 2002
). All these mechanisms may contribute to the association between white matter architecture and intellectual performance, and the causal pathways are influenced by genetic factors, including the BDNF gene. The interaction of the BDNF gene with FA and OBJ provides an example that the cross-trait correlation between FA and OBJ in major white matter regions is genetically mediated (Chiang et al., 2009
Given that the Val-BDNF allele was previously associated with superior cognitive performance compared to the Met allele (Hansell et al., 2007
), and that in our previous study FA was found to be in positive genetic correlation with IQ, especially with the OBJ subscale (Chiang et al., 2009
), the association between the Val allele and a lower FA we discovered here may appear somewhat counterintuitive. The surprising direction of the relationship may be explainable by considering the empirical plots of the modulatory effect of the BDNF gene on FA and IQ. For example, in the splenium of the corpus callosum where the modulatory effect of the BDNF gene on FA and IQ was significant (the right column
in ), the score for OBJ at the intersection of the two FA-OBJ regression lines for the Val (blue line
) and the Met (red line
) allele was higher than the average OBJ score across all the subjects (21.3 vs. 18.0). This may explain why the Val allele mediated a positive correlation between FA and OBJ in that region, but was associated with a lower FA than the Met allele. Genetic influences on FA and IQ may result from an overall combination of effects of positive and negative modulations on FA-IQ correlation by many cognition-related genes, including the BDNF gene here. Based on the currently available data, it seems like the net effect of all these genes results in a positive genetic correlation between FA and IQ, as found in our previous study. Nonetheless a genome-wide association study (GWAS) that examines the modulatory effects of all SNPs across the genome will be warranted to test this hypothesis. We have begun to examine GWAS in DTI (Hibar et al., 2010
), but the sheer number of tests across the genome makes it relatively underpowered without a meta-analytic approach of many large samples, or without a restricted set of prior hypotheses. Currently, the number of available large samples with both DTI and GWAS is limited. This will change in the future, perhaps facilitated by the Enigma consortium (http://enigma.loni.ucla.edu
) and by other meta-analytic approaches to imaging genetics.
Our findings need to be interpreted with caution, because: (1) We did not find significant BDNF interactions with FA and FIQ, VIQ, or PIQ. This may be due to a much higher genetic correlation between FA and OBJ in most white matter regions (Chiang et al., 2009
), so that with the current sample size, the modulatory effect of the BDNF gene for FA and OBJ may be easier to detect than the other IQ scales. (2) Given that interaction effects tend to be much weaker than direct associations, even larger samples may be required to replicate the modulatory effect of the BDNF gene for FA and OBJ, which was detected here in the pooled sample of 455 subjects, but not when the samples were split. (3) The subjects were scanned on average 7 years after their intellectual performance was evaluated, so we cannot rule out that some environmental factors, e.g., school education or work experiences, may confound the associations between gene effects, IQ, and white matter integrity, or that changes in IQ may have occurred between the time of the cognitive evaluation and the scan.
The BDNF allelic effects we detected here (up to 15%) are larger than those reported in genome-wide association studies (GWAS) of other complex traits (Visscher, 2008
). Nevertheless, there has been a strong hypothesis for many years that as we dissect complex traits into more and more basic endophenotypes, gene effects will become larger, and some recent work supports this (Benyamin et al., 2009
). We suggest that the phenotypes we report here are just such fundamental elements and that our findings of relatively large gene effects are not surprising. Even so, the BDNF gene affects cortical gray matter and intellectual performance (Egan et al., 2003
; Hariri et al., 2003
; Pezawas et al., 2004
), so it unquestionably plays a critical role in aspects of white matter microstructure that are relevant for intellectual performance.