Individuals with prior ARBs are more likely to demonstrate similar phenomena when administered alcohol in a laboratory , and ARBs are more common in individuals with alcoholic relatives, with estimated heritabilities of ~50% . The genetic component of ARBs may operate through several intermediate characteristics including the genetically influenced phenotype of a low level of response to alcohol , which is associated with higher drinking quantities per occasion. The low LR, a genetically influenced characteristic that predates heavy drinking and associated ARBs, has been noted to potentially relate to blackouts , but has not been extensively evaluated as a predictor of future alcohol-related memory lapses. Additional characteristics potentially correlated with ARBs include: male sex , externalizing behaviors , and having friends who engage in heavy drinking and drug use . Thus, a person’s demography, externalizing personality characteristics, and substance use among peers are also characteristics to consider when studying the onset and course of blackouts. Relatively few prospective studies have evaluated predictors of the pattern of occurrence of ARBs over time. We reported a 10-year follow-up of 230 drinking 20-year-old nonalcoholic males, noting that those who subsequently developed ARBs drank more heavily and frequently at baseline and were more likely to develop AUDs during the follow-up . Jennison and Johnson evaluated data at 2 points over 4 years for drinking 19- to 26-year-old men and women, reporting that ARBs were related to earlier onsets of drinking, higher alcohol quantities, alcoholic relatives, and smoking. Subjects who had blackouts at baseline had a 68% chance of experiencing ARBs during the follow-up,grow table with chronicity related to male sex and higher baseline alcohol intake and problems. A third longitudinal study of heavy drinkers reported that a history of 6+ lifetime ARBs was related to a 2-fold higher future risk of seeking treatment in emergency rooms .
While there are plentiful data regarding the high prevalence and retrospective correlates of blackouts, few studies have followed the course of these problems over multiple time points or have used latent trajectory analyses to search for predictors of patterns of ARBs over time. Also, few studies have focused on ARBs during a period of rapidly increasing heavy drinking and problems, the mid- to late-teens. The current study prospectively evaluated patterns of ARBs and their predictors from age 15 to 19 to test 4 hypotheses: the proportion of subjects reporting alcohol-related memory lapses will increase with age; there will be multiple trajectories of the occurrence of blackouts over time; characteristics from multiple domains will predict different latent ARB trajectories; and reflecting how a low LR relates to heavier drinking, a low LR will predict a greater likelihood of reporting ARBs.These evaluations focused on prospective latent trajectory analyses of patterns and predictors of ARBs over time beginning at age 15. Here, 75% of the drinkers reported blackouts at age 19, a prevalence higher than the 50% lifetime rate in U.S. general population and college samples . This high ARB prevalence in ALSPAC is consistent with a report that the United Kingdom ranks high regarding the proportion of adolescents who have been intoxicated 20+ times . Results may also reflect our requirement that subjects drank alcohol by age 15, as earlier onset drinking is associated with higher rates oflater alcohol problems ; although by age 14, 70% of U.K. students reported drinking . Our current results support Hypothesis 1 . As shown in Table 2, the proportions with ARBs increased over the 4 years for both subjects with and without ARBs at baseline. Such increases parallel the rapid increase in consumption levels likely to begin in mid-adolescence reported in most epidemiological studies . The current report and prior studies indicate a close link between higher quantities and ARBs, with some moderation through genetic influences and other characteristics .
Hypothesis 2, predicting heterogeneous patterns of blackouts over time, was supported by the LCGA. This procedure yielded 4 classes, including subjects with close to no ARBs; those with blackouts at every evaluation; those, who despite no ARBs at 15, were likely to experience blackouts at all follow-ups; and subjects with few members who reported early alcohol-related memory impairments, for whom the proportion gradually increased to 60%. This heterogeneity is similar to what has been reported for alcohol use and problems across mid- to late-adolescence and early adulthood , but the application of this pattern to blackouts has not been previously well studied in mid-adolescence. As projected in Hypothesis 3, the prediction of these latent trajectory classes required information from multiple domains. Among the age-15 items relevant to 5 potential domains of predictors , 14 differentiated across the latent classes. The data in Table 1 indicated that members of Class 2 and Class 3 demonstrated 14 baseline characteristics midway between Class 1 and Class 4 regarding age-15 domains. When these 14 items were entered in the multi-nomial logistic regression analysis predicting latent class membership, a pseudo R2 of 0.22 was generated, with separate contributions from at least 1 characteristic from each of these predictor domains. These represent the types of items highlighted in the Introduction as reflected in prior cross-sectional analyses . While Classes 2 and 3 had age-15 characteristics that distinguished them from the extreme high and low classes, few items differentiated between Class 2 and 3. However, the LCGA fit statistics supported a 4-class solution over a 3-class result. The data in Tables 1 and 3 point to higher Extroversion and estimated peer substance use at age 15 that may have contributed to the more rapid increase in the proportion of members with blackouts in Class 2.
The combination of being outgoing and sociable with having many drinking friends may have made subjects in Class 2 especially vulnerable to heavy drinking episodes that contributed to the high BACs associated with ARB by age 16. However, the few items that contributed to Class 3 versus 2 membership, along with the modest pseudo R2 for the multinomial logistic regression analyses, highlight the fact that there may be other important age-15 predictors of the trajectories of blackouts that were not available through the ALSPAC protocol. These might include family histories of alcohol problems and/or ARBs, low levels of parental supervision, and/or the absence of positive feelings toward parents, high life stresses, and using alcohol to cope with stress, each of which might characterize Class 2. Of special note was the high proportion of females in Class 4 . Contrary to most prior studies ,vertical rack the current data may reflect a secular trend for increasing alcohol use and problems in females compared to males, as well as reports that with similar alcohol intake females have higher BACs and potentially greater alcohol-related complications . Hypothesis 4 predicted that a low LR would relate to a pattern of higher ARBs, perhaps although the link between a low LR and heavier drinking per occasion . Support for this hypothesis is seen in the univariate analyses in Table 1 where the highest number of drinks needed for effects on the SRE was observed for Class 4 and the lowest drinks needed for effects for Class 1 . However, in Table 3, LR did not add to the prediction of latent trajectory classes when considered in the presence of alcohol quantity measures. Prior studies indicated that the relationship between low LR and alcohol-related problems operates primarily through an effect of LR on drinking quantities, as observed in subjects as young as age 12 . In the absence of age-15 quantity measures, LR entered the regression equation without any change from the pseudo R2 reported in Table 3. Thus, it is likely that the impact of a low LR on future blackouts overlapped with drinking quantities.First, clinicians and parents should be aware that in the large majority of these young subjects, ARBs were not isolated events. Thus, caregivers and parents, as well as young drinkers themselves need to learn that ARBs indicate relatively high BACs that are in turn related to dangers of escalating alcohol problems. Because alcohol-related memory lapses can be seen so early in the drinking history, there may be potential benefits of using brief motivational interviewing to attempt to decrease future alcohol related problems. The link between ARBs and the low LR to alcohol in Table 1 may indicate that the LR-based prevention program recently described for 18-year-olds may be worth testing in young drinkers who demonstrate ARBs . Also, information about the high BACs associated with ARBs, the potential risks for embarrassing behaviors, and possible poor judgment regarding unsafe sex and alcohol-related accidents with intense intoxication should become prominent components of all alcohol education–prevention programs with young drinkers.
While the current sample is relatively large, the data prospective and latent trajectory classes for ARBs have not been previously studied in this age group, the results must be considered in light of relevant caveats. First, the data were gathered through a prospective study that was not originally structured to focus on ARBs. As a result, the ALSPAC blackout question was not consistently coded as the actual number of ARBs experienced, and there was no distinction between fragmentary and en bloc phenomena. Related problems include that only a limited number of predictors were available from the age-15 evaluation, and a family history of AUDs was not consistently recorded in ALSPAC. Second, while data were evaluated as standard drinks, these are only estimates, as the grams of EtOH per drink can differ in different beverages and settings. Third, the subjects were almost exclusively of European origin and came from a single region in the United Kingdom. Fourth, to be eligible for consideration of ARBs in these prospective analyses, participants had to have consumed alcohol by age 15, raising questions of whether similar results would be seen in other populations or if baseline nondrinkers are included in the follow-up. Fifth, LCGA was used because it is appropriate for binary outcomes, relatively easy to interpret, can be applied to modest sized populations and has relatively few problems with convergence and model stability, but this approach might unrealistically constrain variance within classes. In addition, questions have been raised regarding whether latent trajectory analyses can do more than just describe patterns of variation over time and they may not be able to identify groups that reflect inherent fundamental attributes . Furthermore, reflecting our desire to help clinicians better predict future patterns of alcohol problems in 15-year-olds, baseline characteristics that are often handled as covariates in LCGA were used as predictors of trajectories in the current analyses. Thus, the trajectories reported here may look different than those seen with the typical approach to LCGA. Finally, the pseudo R2 reported from the multinomial regression was modest, and pseudo R2 s are not historically as meaningful as R2 s generated from continuous outcomes.Despite the success of antiretroviral therapy, approximately 20–50% of HIV-infected individuals have HIV associated neurocognitive disorder. HIV infection and stimulation of monocytes and lymphocytes promotes trafficking into the central nervous system, triggering a neuroinflammatory response. Within the CNS, inflammation leads to activation of microglia, the resident immune cells in the brain, which induces chemokines and cytokines that drive a chemotactic gradient along the blood -brain barrier and allows further infiltration of infected and uninfected peripheral immune cells. Chemokines and cytokines function as immunomodulatory proteins that influence HIV neuropathogenesis with both positive and negative effects that may contribute to the ongoing prevalence of HAND. The chemokine C-C motif ligand 2 , alternatively known as monocyte chemoattractant protein-1 , is a b-chemokine that is expressed during inflammation and that, upon activation of its receptor , can induce chemotaxis of monocytes to inflammatory sites generated by injury and infectious events. CCL2 is expressed by monocytes, macrophages, dendritic cells, neurons, astrocytes, microglia and endothelial cells, while CCR2 is expressed by monocytes, microglia, astrocytes, epithelial cells, activated T cells and dendritic cells. CCL2 has been identified as the most potent activator of macrophages in comparison to other monocyte chemoattractants, including RANTES, macrophage inflammatory protein-1a , MIP- 1 b, MCP-2 b and MCP-3. CCL2 levels in the brain and cerebrospinal fluid are elevated in HIV patients with encephalitis, AIDS patients with cytomegalovirus, AIDS dementia and HIV-positive patients with cerebral inflammation.