Altered brain-derived neurotrophic factor blood levels and gene variability are associated with anorexia and bulimia

Murine models and association studies in eating disorder (ED) patients have shown a role for the brain-derived neurotrophic factor (BDNF) in eating behavior. Some studies have shown association of BDNF -270C/T single-nucleotide polymorphism (SNP) with bulimia nervosa (BN), while BDNF Val66Met variant has been shown to be associated with both BN and anorexia nervosa (AN). To further test the role of this neurotrophin in humans, we screened 36 SNPs in the BDNF gene and tested for their association with ED and plasma BDNF levels as a quantitative trait. We performed a family-based association study in 106 ED nuclear families and analyzed BDNF blood levels in 110 ED patients and in 50 sib pairs discordant for ED. The rs7124442T/rs11030102C/rs11030119G haplotype was found associated with high BDNF levels (mean BDNF TCG haplotype carriers = 43.6 ng/ml vs. mean others 23.0 ng/ml, P = 0.016) and BN (Z = 2.64; P recessive = 0.008), and the rs7934165A/270T haplotype was associated with AN (Z =-2.64; P additive = 0.008). The comparison of BDNF levels in 50 ED discordant sib pairs showed elevated plasma BDNF levels for the ED group (mean controls = 41.0 vs. mean ED = 52.7; P = 0.004). Our data strongly suggest that altered BDNF levels modulated by BDNF gene variability are associated with the susceptibility to ED, providing physiological evidence that BDNF plays a role in the development of AN and BN, and strongly arguing for its involvement in eating behavior and body weight regulation.

Transcription factor map alignment of promoter regions

We address the problem of comparing and characterizing the promoter regions of genes with similar expression patterns. This remains a challenging problem in sequence analysis, because often the promoter regions of co-expressed genes do not show discernible sequence conservation. In our approach, thus, we have not directly compared the nucleotide sequence of promoters. Instead, we have obtained predictions of transcription factor binding sites, annotated the predicted sites with the labels of the corresponding binding factors, and aligned the resulting sequences of labels—to which we refer here as transcription factor maps (TF-maps). To obtain the global pairwise alignment of two TF-maps, we have adapted an algorithm initially developed to align restriction enzyme maps. We have optimized the parameters of the algorithm in a small, but well-curated, collection of human–mouse orthologous gene pairs. Results in this dataset, as well as in an independent much larger dataset from the CISRED database, indicate that TF-map alignments are able to uncover conserved regulatory elements, which cannot be detected by the typical sequence alignments.