The proportion of the at-risk sample who become regular users of alcohol increased from 15 to 43 % between the two age ranges. Biological factors are significant in both the onset of regular alcohol use and of alcohol dependence in the youngest age range. The prevalence of regular drinking in the oldest age range has eliminated the effect of the biological factors in its onset; only the onset of alcohol dependence is affected by biological factors. In the older age range, since it is likely that much of the onset of alcohol dependence is driven by past drinking, particularly since relatively few of those who become alcohol dependent in the oldest age range have been drinking for a short time, those factors which are significant for regular alcohol use in the youngest age range are significant for alcohol dependence. Furthermore, it is likely that a biologically specific sub-population of the youngest group particularly sensitive to the effects of alcohol has been effectively eliminated from the at-risk group in the oldest age range . In the illicit drug use sub-sample in the youngest age range, CHRM2 is a greater factor for the onset of alcohol dependence than in the entire sample. However, EROs are not a factor in the onset of alcohol dependence in this group. The range of ERO values in the illicit drug use sub-sample does not differentiate those who become alcohol dependent from those who do not, although ERO values differentiate the illicit drug sub-sample from their complement in the entire sample. The illicit drug use sample shows greater and more extensive genetic effects than the entire sample, since the result of selecting the illicit drug use sub-sample is to remove those subjects whose alcohol dependence is unlikely to be genetically affected from the analysis. In examining the results of the logistic regression analysis of the transition from regular alcohol use to alcohol dependence in the youngest age range, the U-shaped effect of the duration of drinking suggests the presence of two distinct factors,cannabis grow system one a susceptibility to rapidly become dependent subsequent to the onset of regular alcohol use and the other a gradual effect of continued alcohol consumption.
The masking of the ERO effect by the rising component of the duration factor suggests that ERO is associated with a long term behavior pattern involving substance abuse. The absence of a genotypic effect is the result of including all those who become alcohol dependent in the analysis, not just those in the genetically more vulnerable, as can be observed by comparing the under 16 results between the regular alcohol user group and the illicit drug user group. In summary, for the youngest age range the pattern of significance of the ERO and SNP phenotypes for the onset of regular alcohol use and of alcohol dependence, as well as the pattern of significance in the transition from alcohol use to alcohol dependence suggests that delta ERO value indexes an element of propensity to use drugs to excess, while the CHRM2 SNPs index an age related effect of alcohol consumption on the brain with the behavioral outcome of dependence, as we explain below. We view the age-varying genotypic effect of the CHRM2 SNPs as an instance of a gene–environment interaction. In our case the immediate genotypic effects are upon the activation level of the type 2 muscarinic receptors and the environment is the neuroanatomic and neurophysiological context in which the action of the muscarinic receptors is taking place. This environment undergoes significant changes as the brain develops from the early teens into the early twenties, as we have noted above. In the transition from alcohol non-use to regular use of alcohol to alcohol dependence, we note that alcohol consumption has significant effects on the development of addiction in adolescent animals and humans . The cholinergic M2 receptor gene belongs to a family of muscarinic acetylcholine G-protein coupled receptors with five known subtypes . The M2 receptors in the mesolimbic dopaminergic system play a significant role in modulating the level of dopamine release . This has a important effect in governing the reward system , including modulating the effects of alcohol on it .It is not possible to determine the precise nature of the interaction between the genotypic effect on the cholinergic M2 receptors and the age-varying neuroanatomic/neurophysiologcial environment given the data at our disposal.
Given the age-related patterns of genotypic action we have described above, it is possible that the effect of alcohol consumption on the brain varies with the genotype of the cholinergic M2 receptors and the age of onset of regular drinking. specifically, when alcohol is consumed regularly in the youngest age range, perhaps better described as a particular stage in brain maturation centered in this age range, the addiction producing effects on those who have two copies of the major allele are accelerated compared to those who do not, leading to rapid transition from regular alcohol use to alcohol dependence. [This may be in part responsible for the ‘‘telescoping of trajectory’’ effects reported in Hussong et al. .] Those without two copies of the major allele may take longer to manifest the effects of alcohol use. As the age of the initiation of alcohol use increases, it appears that the cumulative risk for alcohol dependence when carried into the adult years is greater in those without two copies of the major allele than in those with two copies. We draw this last conclusion on the basis of the trend tests on our own data and the results of the studies of Wang et al.and Dick et al. . In those who become regular users of alcohol under the age of 16, a majority of those who became alcohol dependent within two years had the risk genotype; the majority of those who become alcohol dependent four years or more after their onset of regular drinking did not have the initial risk genotype.The frailty effect would play a role if there were relatively easy access to alcohol in the youngest age range, at least for those most at risk. Among those who have the major alleles, those who are genetically most vulnerable become alcohol dependent rapidly, leaving only those who have some protective factor. Thus risk for those with the major alleles will decrease with age, since those without the protective factors will have become alcohol dependent, leaving primarily those with protective factors at potential risk. We also note that if the illicit drug user population had easier access to alcohol than the entire population as a whole, the greater genetic effects seen in the illicit drug user sub-sample might in part be the result of a gene– environment interaction, akin to those described in Dick and Kendler , in which looser social controls over behavior accentuate genetic effects.
Since 80 % of the illicit drug use sub-sample are from COGA rather than community families, this is a plausible hypothesis. The specific environment of the most vulnerable group is more likely to accentuate genetic effects,cannabis grow lights rather than to diminish them.We found that SNPs reported to be significant in adults were significant in adolescents in this sample, particularly for those in the youngest age ranges, and for those who had ever used an illicit drug. However, in our results, the major allele was the risk allele, while in the results of Wang et al.and consequently of Dick et al. , the minor allele was the risk allele. Our results do not contradict those of Wang et al.and Dick et al. ; the results are mutually consistent. Instead, they reveal a novel age-specific risk factor undetectable by solely examining the condition of alcohol dependence rather than its age of onset. In view of the age differences between the sample studied in this paper, and the sample used in the studies of Wang et al.and Dick et al.it is not possible that they should contradict one another. In the Wang et al.study, about 5 % of the alcohol dependent subjects had ages of onset of less than 16 years of age. This is too small a fraction to have an effect on the results. As we noted in our discussion of the trend tests, in our study the genotypic distributions of the alcohol dependent subjects change with age of onset. While we do not observe a significant SNP effect in the oldest age range with DTSA, the fraction of subjects with the minor allele in those who become alcohol dependent is greater than the fraction of subjects with the minor allele in those who do not become alcohol dependent . This trend acts to produce a similar genotypic distributions for alcohol dependent and non alcohol dependent subjects when considered regardless of age of onset. In terms of the methodology, DTSA requires that there be differences in genotypic distributions between alcohol dependent and non alcohol dependent subjects to give a statistically significant results for a SNP; this is not true for the family based method used by Wang et al. .Our interpretation is that family based studies are more powerful than the type of association study employed here; the absence of a distributional difference does not mean that there is no genetic effect.In the age ranges and samples in which we found that ERO was significant for the onset of alcohol use or alcohol dependence, it was the lower values which characterize the risk factor, which is consistent with the results in adolescents and young adults in the studies by Rangaswamy et al. , Kamarajan et al. , and Gilmore et al. .
That no effects of regular alcohol use on ERO values were found is consistent with similar results obtained by Perlman et al. .It is important to note that the objectives of the twin studies considered here and of this study are quite different. The twin studies investigate the presence of a ‘‘disease’’ condition, although exactly which condition varies considerably among studies.The objective of this study, as a survival analysis, is to analyze the factors contributing to an event, the onset of a condition. Once the condition has come to pass, it is not of further interest in survival analysis. The genetic effects which produce the condition are only significant at the onset of the condition, and their effects persist only if the subsequent onset of the condition in other subjects is attributable to them.That is, in the longitudinal studies using multistage models, the affected subjects are retained throughout the study subsequent to their becoming affected, while in the survival analysis method used in this study, the affected subjects are removed from consideration in the study once they have become affected, and no longer influence the results. Therefore, although the use of a longitudinal multi-stage model in van Beek et al.and Baker et al.enables genetic influences to have age-specific characteristics, these effects are modeled as persisting through time as a result of an effect at a single age range. If early onset alcohol use is associated with the more genetically determined form of alcoholism then it would be expected that genetic factors leading to early drinking and dependence would be manifest. Our results are consistent with this hypothesis. The pattern of genetic results obtained here, albeit from a single gene, is weighted towards the strongest effects manifesting.Originally formulated over twenty years ago, and recently updated, the neural diathesis-stress model proposes that the hypothalamic-pituitary-adrenalaxis is the central physiological mechanism linking psychosocial stress to the onset and exacerbation of schizophrenia and related psychotic disorders . A central tenet to this model is that individuals with increased vulnerability for psychosis are more sensitive to the effects of psychosocial stressors due to abnormalities within the HPA axis which in turn contribute to dopaminergic and glutamatergic abnormalities that eventually trigger expression of psychotic illness . In support of the model, accumulated evidence indicates that patients with psychosis exhibit elevated basal cortisol relative to healthy controls , but a blunted cortisol awakening response [CAR ], the latter thought to represent a distinct HPA axis component, independent of stress-induced cortisol secretion .