BDNF gene effects on brain circuitry replicated in 455 twins

Brain-derived neurotrophic factor (BDNF) plays a key role in learning and memory, but its effects on the fiber architecture of the living brain are unknown. We genotyped 455 healthy adult twins and their non-twin siblings (188 males/267 females; age: 23.7±2.1 years, mean±SD) and scanned them with high angular resolution diffusion tensor imaging (DTI), to assess how the BDNF Val66Met polymorphism affects white matter microstructure. By applying genetic association analysis to every 3D point in the brain images, we found that the Val-BDNF genetic variant was associated with lower white matter integrity in the splenium of the corpus callosum, left optic radiation, inferior fronto-occipital fasciculus, and superior corona radiata. Normal BDNF variation influenced the association between subjects' performance intellectual ability (as measured by Object Assembly subtest) and fiber integrity (as measured by fractional anisotropy; FA) in the callosal splenium, and pons. BDNF gene may affect the intellectual performance by modulating the white matter development. This combination of genetic association analysis and large-scale diffusion imaging directly relates a specific gene to the fiber microstructure of the living brain and to human intelligence.

[1]  Karl J. Friston,et al.  Assessing the significance of focal activations using their spatial extent , 1994, Human brain mapping.

[2]  A. Meyer-Lindenberg,et al.  The Brain-derived Neurotrophic Factor Val66met Polymorphism and Variation in Human Cortical Morphology , 2022 .

[3]  M. Egan,et al.  Brain-Derived Neurotrophic Factor val66met Polymorphism Affects Human Memory-Related Hippocampal Activity and Predicts Memory Performance , 2003, The Journal of Neuroscience.

[4]  I. A. Boyd,et al.  Ultrastructural dimensions of myelinated peripheral nerve fibres in the cat and their relation to conduction velocity , 1980, The Journal of physiology.

[5]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[6]  Daniel Rueckert,et al.  Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data , 2006, NeuroImage.

[7]  Karl J. Friston,et al.  False discovery rate revisited: FDR and topological inference using Gaussian random fields , 2009, NeuroImage.

[8]  V. Schmithorst,et al.  Differences in white matter architecture between musicians and non-musicians: a diffusion tensor imaging study , 2002, Neuroscience Letters.

[9]  Peter M Visscher,et al.  Sizing up human height variation , 2008, Nature Genetics.

[10]  Mu-ming Poo,et al.  Neurotrophins as synaptic modulators , 2001, Nature Reviews Neuroscience.

[11]  Stephen M Smith,et al.  Fast robust automated brain extraction , 2002, Human brain mapping.

[12]  D. Salat,et al.  Choice reaction time performance correlates with diffusion anisotropy in white matter pathways supporting visuospatial attention. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[13]  C. Beaulieu,et al.  The basis of anisotropic water diffusion in the nervous system – a technical review , 2002, NMR in biomedicine.

[14]  Karl J. Friston,et al.  Topological FDR for neuroimaging , 2010, NeuroImage.

[15]  R. Fields,et al.  Myelination: An Overlooked Mechanism of Synaptic Plasticity? , 2005, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[16]  Leena Peltonen,et al.  Variants in TF and HFE explain approximately 40% of genetic variation in serum-transferrin levels. , 2009, American journal of human genetics.

[17]  Alan C. Evans,et al.  Enhancement of MR Images Using Registration for Signal Averaging , 1998, Journal of Computer Assisted Tomography.

[18]  C. Siao,et al.  Genetic Variant BDNF (Val66Met) Polymorphism Alters Anxiety-Related Behavior , 2006, Science.

[19]  Christoph Lange,et al.  Genomic screening and replication using the same data set in family-based association testing , 2005, Nature Genetics.

[20]  G. Abecasis,et al.  A general test of association for quantitative traits in nuclear families. , 2000, American journal of human genetics.

[21]  Chunshui Yu,et al.  COMT val158met modulates association between brain white matter architecture and IQ , 2009, American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics.

[22]  Paul M. Thompson,et al.  3 D pattern of brain atrophy in HIV / AIDS visualized using tensor-based morphometry , 2006 .

[23]  E K Warrington,et al.  Selective impairment of memory and visual perception in splenial tumours. , 1991, Brain : a journal of neurology.

[24]  R. Elston,et al.  The investigation of linkage between a quantitative trait and a marker locus , 1972, Behavior genetics.

[25]  R. Straub,et al.  Effect of COMT Val108/158 Met genotype on frontal lobe function and risk for schizophrenia , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[26]  Kenji Hashimoto,et al.  Ethnic difference of the BDNF 196G/A (val66met) polymorphism frequencies: The possibility to explain ethnic mental traits , 2004, American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics.

[27]  M. Egan,et al.  The BDNF val66met Polymorphism Affects Activity-Dependent Secretion of BDNF and Human Memory and Hippocampal Function , 2003, Cell.

[28]  Stephen M. Smith,et al.  A global optimisation method for robust affine registration of brain images , 2001, Medical Image Anal..

[29]  E. Vonesh,et al.  Mixed-effects nonlinear regression for unbalanced repeated measures. , 1992, Biometrics.

[30]  Agatha D. Lee,et al.  Genetics of Brain Fiber Architecture and Intellectual Performance , 2009, The Journal of Neuroscience.

[31]  Mark W. Woolrich,et al.  Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? , 2007, NeuroImage.

[32]  P. Basser,et al.  Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. , 1996, Journal of magnetic resonance. Series B.

[33]  A. Wright,et al.  Magnetic resonance microimaging of intraaxonal water diffusion in live excised lamprey spinal cord , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[34]  Karl J. Friston,et al.  Voxel-Based Morphometry—The Methods , 2000, NeuroImage.

[35]  S A Glantz,et al.  Multiple regression for physiological data analysis: the problem of multicollinearity. , 1985, The American journal of physiology.

[36]  Nicholas Ayache,et al.  Fast and Simple Calculus on Tensors in the Log-Euclidean Framework , 2005, MICCAI.

[37]  James C. Gee,et al.  Spatial transformations of diffusion tensor magnetic resonance images , 2001, IEEE Transactions on Medical Imaging.

[38]  M J Wright,et al.  Effect of the BDNF V166M polymorphism on working memory in healthy adolescents , 2007, Genes, brain, and behavior.