This region of chromosome 2 is home to GAD1 glutamate decarboxylase 1 gene map

This region of chromosome 2 is home to gad1 glutamate

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This region of chromosome 2 is home to GAD1 (glutamate decarboxylase 1, gene map locus 2q31), which catalyzes the conversion of glutamic acid to gamma-aminobutyric acid (GABA), the major inhibitory neurotransmitter in the verte- bral central nervous system. It has been associated with alco- hol dependence in Han Taiwanese males (Loh et al., 2006). In the IASPSAD sample, no association was found with depen- dence, but significant associations were found with initial sen- sitivity to alcohol and to age at onset of dependence (Kuo et al., 2008). Kuo and colleagues (2008) proposed that the underlying pathophysiology regulated by GAD1 may be more directly related to the component processes of dependence, than to the disorder itself. A small linkage peak (LOD 1.6) on chromosome 3 was located in the same region as linkage found previously in the same sample for alcohol consumption (LOD 2.7) (Hansell et al., 2009). In addition, a minor peak (LOD 1.0) was observed in the region encompassing the gamma-aminobutyric acid receptor A subunit 2 ( GABRA2 ) gene. This gene and others in its cluster on chromosome 4 ( GABRA4 , GABRB1 , GABRAG1 ) have been found to be associated with alcohol dependence (as well as other substance use disorders and psychopathology) across several independent studies (Covault et al., 2004; Edenberg et al., 2004; Fehr et al., 2006; Lappalainen et al., 2005; Lind et al., 2008; Matthews et al., 2007; Soyka et al., 2008). Some limitations need to be considered. First, these results were not genomewide significant. However, the likeli- hood that these are false positives is somewhat diminished as the results replicate linkage found in these regions by pre- vious studies. Further, quantitative trait loci of small effect are to be expected given that an alcohol dependence symp- tom score is likely to be influenced by many genes of small effect, as has been found for numerous traits in genomewide association studies (Wray et al., 2007). Larger linkage sig- nals, as have been reported previously, may simply reflect the high variance of effect size estimates found with smaller samples. Linkage differences related to sample variation were found in the current study, but are not sufficiently large for meaningful interpretation. A further limitation is that the component samples were collected for heteroge- neous purposes and may not be entirely representative of the adult Australian population. Notwithstanding these limi- tations, our analyses demonstrate the utility of a community sample, results of which are easily generalizable, for linkage analyses. The chromosomal regions identified provide a focus for future gene-mapping efforts. ACKNOWLEDGMENTS We thank all participating families, the project coordina- tors and interviewers under the supervision of Dixie Statham, the data managers under the supervision of John Pearson and David Smyth, and laboratory personnel under the supervision of Megan Campbell and Anjali Henders. For genome scans of twins and siblings, we acknowledge and thank the Mam- malian Genotyping Service, Marshfield WI (Director: Dr.
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