Classification Tree Analysis as a Method for Uncovering Relations Between CHRNA5A3B4 and CHRNB3A6 in Predicting Smoking Progression in Adolescent Smokers

<span class=”paragraphSection”><div class=”boxTitle”>Abstract</div><div class=”boxTitle”>Introduction:</div>Prior research suggests the <span style=”font-style:italic;”>CHRNA5A3B4</span> and <span style=”font-style:italic;”>CHRNB3A6</span> gene clusters have independent effects on smoking progression in young smokers. Here classification tree analysis uncovers conditional relations between these genes.<div class=”boxTitle”>Methods:</div>Conditional classification tree and random forest analyses were employed to predict daily smoking at 6-year follow-up in a longitudinal sample of young smokers (<span style=”font-style:italic;”>N</span> = 480) who had smoked at least one puff at baseline and were of European ancestry. Potential predictors included gender, lifetime smoking, Nicotine Dependence Syndrome Scale (NDSS), and five single nucleotide polymorphisms (SNPs) tagging <span style=”font-style:italic;”>CHRNB3A6</span> and <span style=”font-style:italic;”>CHRNA5A3B4</span> Haplotypes A, B, and C. Conditional random forest analysis was used to calculate variable importance.<div class=”boxTitle”>Results:</div>The classification tree identified NDSS, the <span style=”font-style:italic;”>CHRNB3A6</span> SNP rs2304297, and the <span style=”font-style:italic;”>CHRNA5A3B4</span> Haplotype C SNP rs6495308 as predictive of year 6 daily smoking with the baseline NDSS identified as the strongest predictor. The <span style=”font-style:italic;”>CHRNB3A6</span> protective effect was contingent on a lower level of baseline NDSS, whereas the <span style=”font-style:italic;”>CHRNA5A3B4</span> Haplotype C protective effect was seen at a higher level of baseline NDSS. A <span style=”font-style:italic;”>CHRNA5A3B4</span> Haplotype C protective effect also was observed in participants with low baseline NDSS who had no <span style=”font-style:italic;”>CHRNB3A6</span> rs2304297 minor allele.<div class=”boxTitle”>Conclusions:</div>The protective effects of <span style=”font-style:italic;”>CHRNA5A3B4</span> Haplotype C and <span style=”font-style:italic;”>CHRNB3A6</span> on smoking progression are conditional on different levels of baseline cigarette use. Also, duplicate dominant epistasis between SNPs indicated the minor allele of either SNP afforded comparable protective effects in the absence of a minor allele at the other locus. Possible mechanisms underlying these conditional relations are discussed.<div class=”boxTitle”>Implications:</div>The substantive contributions of this paper are the demonstration of a difference in the protective effects of <span style=”font-style:italic;”>CHRNB3A6</span> and <span style=”font-style:italic;”>CHRNA5A3B4</span> Haplotype C in young smokers attributable to level of cigarette use, as well as observation of duplicate dominant epistasis between the two markers. The methodological contribution is demonstrating that classification tree and random forest statistical methods can uncover conditional relations among genetic effects not detected with more common regression methods.</span>

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