The primary aim of the current study was to conduct a genome-wide linkage scan of nicotine dependence in the UCSF Family Alcoholism Study sample to support and extend the findings of previous studies. A linkage peak was observed on chromosome 2 at 184 cM that achieved genome-wide significance when a variance components approach was used based on criteria described by Lander and Kruglyak (1995)
. This region continued to yield strong evidence for linkage when the Kong and Cox (1997)
statistic was used to test for linkage, but failed to reach genome-wide significance. This divergence in the results limits claims of genome-wide significance, though the consistency in LOD scores across analytic methods provides strong evidence of linkage to this region. Additional peaks of interest were found on a second region of chromosome 2 at 123 cM, chromosome 4 at 27 cM, chromosome 11 at 135 cM, and chromosome 12 at 50 cM, though these should be interpreted tentatively given the weaker evidence for linkage.
The linkage region on chromosome 2 at 184 cM has been previously identified as harboring a susceptibility locus for nicotine dependence (Loukola et al., 2008
; Straub et al., 1999
). The first study reported a linkage signal approximately 35 megabases centromeric, and the second study reported a linkage signal approximately 32 megabases telomeric of the peak reported in this study. In addition, a locus on the short arm of chromosome 2 at 85 cM, which contains NRXN1
, has been previously linked to both nicotine and alcohol dependence (Bierut et al., 2007
; Nussbaum et al., 2008
; Yang et al., 2005
), but this locus is approximately 100 megabases from the locus identified in the present study.
There are potential candidate genes within the support interval of the locus reported here. For example, the nicotinic acetylcholine α1 gene (CHRNA1
) is located near the center of the reported linkage peak. Although originally thought to be found only in muscle tissue, recent gene expression studies have found this gene to be expressed in brain as well (Su et al., 2004
) suggesting a potential role in nicotine addiction. Evidence for an association between this gene and smoking behavior has been previously reported (Faraone et al., 2004
), but negative findings have also been described (Sherva et al., 2008
). In addition, SNPs located in the nearby growth factor receptor-bound protein 14 (GRB14
) and grancalcin (GCA
) genes were recently associated with nicotine dependence in a genome-wide association study (GWAS) (Vink et al., 2009
). Potential mechanisms through which one or both of these genes might confer risk to nicotine dependence are not clear. GRB14
is thought to be involved in insulin receptor signaling and may influence signaling pathways that regulate growth and metabolism (Carre et al., 2008
may be involved in the migration and adherence of neutrophils (Jia et al., 2000
). Thus, further studies are necessary to determine whether a causal variant is located in GRB14
or whether the associated SNPs are in linkage disequilibrium with a causal variant located in a nearby gene such as CHRNA1
Follow-up analyses of the chromosome 2 linkage peak showed that SSAGA symptoms encompassing a broad range of DSM-IV nicotine dependence symptom clusters, including evidence of tolerance, inability to quit smoking, escalating pattern of use, and persistent use despite negative health consequences, provided modest contributions to the linkage signal. This suggests the chromosome 2 locus at 184 cM confers risk for nicotine dependence in general rather than a specific facet of this disorder. As further evidence of this conclusion, it is notable that the linkage analysis of the nicotine dependence diagnosis yielded a higher LOD score than any of the individual nicotine dependence symptoms (LOD = 3.54 vs. max LOD = 2.66). These results are consistent with a previous study demonstrating that a single genetic factor can explain a predominant proportion of the common variation between DSM-IV nicotine dependence symptoms (Lessov et al., 2004
A further aim of this study was to determine whether the reported genomic regions contributed to nicotine dependence specifically or to addiction more generally by showing evidence of linkage to both alcohol and nicotine dependence. The former conclusion was supported as no overlap between linkage signals reported in the present study were observed with those reported in a previous linkage study of alcohol dependence to chromosomes 1 at 11cM, 2 at 287 cM, 8 at 163 cM, and 18 at 48 cM (Gizer et al., unpublished observation). Further, supplementary genome-wide linkage scans of nicotine dependence utilizing alcohol dependence diagnoses alternatively as a covariate and as an additional predictor in a bivariate analysis showed little evidence of linkage between alcohol dependence and the regions reported herein. This suggests that the susceptibility loci identified in the present study are specifically involved in the etiology of nicotine dependence and are unrelated to alcohol dependence.
This result was somewhat surprising given the strong correlations between drinking and smoking behaviors (Miller and Gold, 1998
). Twin studies suggest that common genetic influences are partially responsible for the observed correlation (Swan et al., 1997
; True et al., 1999
), though disorder-specific genetic influences have been identified as well (Kendler et al., 2007
; Volk et al., 2007
). Nonetheless, previous family-based samples selected for alcohol dependence have identified genetic loci that confer risk to alcohol and tobacco use phenotypes. For example, loci on chromosomes 2 (Bierut et al., 2004
), 4 (Ehlers and Wilhelmsen, 2006
), 7 (Loukola et al., 2008
; Sullivan et al., 2008
), and 18 (Sullivan et al., 2008
) have been shown to contribute jointly to alcohol and nicotine dependence The lack of such findings in the present study suggest that unique genetic influences contributed to nicotine and alcohol dependence in the UCSF Family Alcoholism Study.
The reported findings have important implications for molecular genetic studies of nicotine dependence, but there are limitations that should be noted. For example, the UCSF Family sample was originally selected for alcohol dependence. Thus, it is not clear how the reported findings will generalize to populations without this bias, though a previous study reporting evidence of linkage to the chromosome 2 region used a sample selected for nicotine rather than alcohol dependence (Loukola et al., 2008
). Additionally, categorizing ‘never smokers’ and ‘not nicotine dependent’ participants as unaffected individuals may have influenced study results (Munafo et al., 2004). Given that unique genetic influences contribute to the initiation and persistent use of tobacco (Madden & Heath, 1995), combining these participants into a single unaffected category likely limited our ability to detect these unique genetic influences. Nonetheless, there is substantial overlap in the genetic influences contributing to these stages of tobacco use (Sullivan and Kendler, 1999), providing justification for this approach. The statistical power of the present study is another possible limitation. Linkage studies lack sufficient statistical power for identifying loci with small effects, and this may explain the lack of support for loci such as chromosomes 9q and 10q that have been previously linked to nicotine dependence.
In summary, the current study adds to the literature by supporting evidence of genetic linkage of chromosome 2q to nicotine dependence. This study extends this finding by showing that this region confers risk to the full nicotine dependence diagnosis rather than a specific facet of the disorder. Finally, the present study suggests this locus, as well as the additional loci identified, confers risk to nicotine but not alcohol dependence, thus providing evidence that this genomic region may harbor a gene specifically involved in the physiological effects and/or metabolism of nicotine.