Brain volumes and Val66Met polymorphism of the BDNF gene: local or global effects?

Abstract

A common Single-Nucleotide Polymorphism in the Brain-Derived Neurotrophic Factor (BDNF) gene coding the Val66Met substitution in the pro-BDNF protein has been associated with a number of behavioural and neuroanatomical phenotypes; the latter include, for example, regional differences in volumes of the hippocampus and prefrontal grey matter. Here, we show that the observed regional differences may not stem from a localised effect of this gene. Our analysis of regional brain volume in a cohort of 331 adolescents indicates that the Val66Met substitution has a global effect on brain volume, and that the observed local differences are to be expected if brain allometry-the covariance pattern of regional brain volumes-is taken into account.

A systematic review of the effect of genes mediating neurodevelopment and neurotransmission on brain morphology: Focus on schizophrenia

“…Thus, the above studies clearly demonstrate that the polymorphism rs6265 is associated with frontal GMV reductions in healthy subjects 51 and patients with schizophrenia. 52 However, in another study (48) healthy subjects with the SNP rs6265 were shown to have an increase in frontal WMV.…”

“…46 The polymorphism rs6265 (Val166Met) of BDNF gene has been implicated in schizophrenia (P < 0.005). 47 Healthy subjects (N = 331) with Val/Val genotype (n = 217) were shown to have larger whole brain volume (F = 6.51; P < 0.0112) 48 as well as larger volumes of left inferior temporal gyrus (P < 0.000), prefrontal cortex (P < 0.001) and lateral occipital cortex (P < 0.001) (N = 144; n = 95), while patients with schizophrenia (N = 293) having the Val/Val genotype (n = 182) were shown to have increased left parahippocampal (P < 0.000) and left supramarginal gyral volumes (P < 0.001) 49 and decreased hippocampal volumes [N = 68; n = 44 (total: F = 5.102, P < 0.025; left: F = 4.031, P < 0.046; right: F = 5.171, P < 0.024)]. 50 Yang et al 51 observed that healthy subjects (N = 81) with Met/Met genotype (n = 17) were associated with less GM mainly in the frontal, temporal, cingulate and insular cortices (TFCE corrected, P < 0.05).…”

Studying neuroanatomy using MRI

“…From a statistical perspective, this observation raises the question about how to best "account for" total brain size when analyzing a region of interest (ROI) -which has traditionally been addressed by either proportionalizing ROI measures, or including total brain volume as a linear covariate when modelling variation in ROI anatomy. However, a number of recent studies 165,166 have underlined that relationships between ROI size and overall brain size are often profoundly non-linear, and shown how the inability of traditional methods to control for these non-linearities can lead to false inferences regarding the presence and location of regional brain changes. The importance of using an allometric framework in analysis of morphometric data is especially pronounced when studying groups that differ markedly in overall brain size due to demographic (e.g males vs. females) or clinical (e.g.…”

Imaging genomics

“…Curiously, different measures of the same structure – such as cortical thickness and cortical surface area – can both be highly heritable but determined by different sets of genes [24–26]. Conversely, the diffuse effects of single genes on the brain, such as brain-derived neurotrophic factor ( BDNF ), are not necessarily localized, and may be detected across many structures at once, due to the observed covariance among brain volumes [27–29]. These genetic modeling efforts have been greatly accelerated by software packages for efficient computational analysis, such as Mx [30] and SOLAR [31] – which now has 4000 registered users, and has spurred the widespread use of quantitative genetic analysis.…”