Evaluating the role of a Galanin Enhancer Genotype on a range of metabolic, depressive and addictive phenotypes
Publication year
2014Author(s)
Number of pages
11 p.
Source
American Journal of Medical Genetics. Part B : Neuropsychiatric Genetics, 165, 8, (2014), pp. 654-664ISSN
Publication type
Article / Letter to editor

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Organization
SW OZ BSI OGG
Journal title
American Journal of Medical Genetics. Part B : Neuropsychiatric Genetics
Volume
vol. 165
Issue
iss. 8
Languages used
English (eng)
Page start
p. 654
Page end
p. 664
Subject
Developmental PsychopathologyAbstract
There is a large body of pre-clinical and some clinical data to link the neuropeptide galanin to a range of physiological and pathological functions that include metabolism, depression, and addiction. An enhancer region upstream of the human GAL transcriptional start site has previously been characterised. In-vitro transfection studies in rat hypothalamic neurons demonstrated that the CA allele was 40% less active than the GG allele in driving galanin expression. Our hypothesis was to investigate the effect of this galanin enhancer genotype on a range of variables that relate to the known functions of the galaninergic system in the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort of young adults (N=169-6,078). Initial findings showed a positive relationship of cannabis usage (OR=2.070, P=0.007, N=406 (individuals who had used cannabis at least once within the last 12 months, total sample size 2731) with the GG haplotype, consistent with the previous published data linking galanin with an increased release of dopamine. As our sample size was relatively small we replicated the analysis in a larger cohort of 2,224 African Americans and 1,840 European Americans, but no discernible trend across genotypes was observed for the relationship with cannabis usage. Further, we found no association of the galanin enhancer genotype with any of the other pathophysiological parameters measured. These findings emphasise that preclinical data does not always predict clinical outcomes in cohort studies, noting that association studies are subject to multiple confounders.
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