This is important because a better understanding of the underpinnings for phenotypes that contribute to an enhanced vulnerability to heavy drinking and alcohol problems can lead to prevention approaches that diminish that vulnerability . The concept of tolerance is broad and has several components. These include pharmacodynamic, or functional, tolerance where the body develops less response, or more resistance, to a given level of the drug . Functional tolerance can be further characterized based on the duration and intervals between alcohol exposure. Acute tolerance, which develops during a single exposure to alcohol and is sometimes labeled as within-session tolerance or the Mellanby effect , refers to the phenomenon whereby in a single drinking session one experiences less alcohol effect at a given blood level at falling alcohol concentrations as compared to an identical alcohol concentration at rising levels . Repeated bouts of alcohol exposure can also produce chronic, or intersession, tolerance to the drug which might reflect both the pharmacodynamic and pharmacokinetic effects and is the usual tolerance definition that applies to the AUD criterion item in the recent versions of the Diagnostic and Statistical Manuals of the American Psychiatric Association.Acute tolerance in humans can be measured in a research laboratory by either having subjects ingest alcohol-containing beverages or by infusing ethanol intravenously . While each method of administration has its strengths and limitations for a critical review, systematic reviews of the acute tolerance literature find that 60% to 80% of these alcohol challenge studies yield evidence for acute tolerance to at least some of alcohol’s effects. The reviews also find more consistent evidence of acute tolerance when subjective measures of intoxication are assessed at rising and falling alcohol concentrations as opposed to more objective measurements such as performance on neuropsychological tests or driving simulation.

In summary,trimming weed plants some studies have used alcohol challenges to document acute tolerance and, and others have used alcohol challenges to evaluate the type and intensity of reaction to alcohol in individuals at higher risk for AUDs before repeated binge drinking or multiple alcohol problems develop. However, few, if any, studies have evaluated both acute tolerance and LR in the same population. When the relatively lower intensity of response to alcohol was first identified in young adult light-to-moderate drinking non-AUD offspring of individuals with AUDs, the phenomenon was labeled as a “low LR” because it was not possible to determine if the measure related to innate sensitivity or was the consequence of the development of some form of tolerance. Thus, there is a need to add evaluations of acute tolerance to alcohol challenge studies focusing on the low LR phenotype.This paper presents the results of secondary data analyses from one of our prior alcohol challenge studies to directly test whether moderate drinking low and high LR individuals differ in the development of acute tolerance. The data compare alcohol challenge scores at similar breath alcohol concentrations along the ascending and descending limbs of the BrAC curve. Data are available on changes in scores for subjective responses to alcohol and alterations in the amount of body sway. Our Hypothesis 1 is that low LR individuals, who have been shown to demonstrate less intense subjective feelings and body sway during the alcohol challenge, will also demonstrate greater levels of acute tolerance than their sex- and age-matched high LR counterparts. In addition, Hypothesis 2 predicts that, the relationship of LR to acute tolerance will be similar across the sexes .As described in detail in our prior work , participants in the present secondary data analysis were 18- to 25-yearold Anglo and white Hispanic students enrolled at the University of California, San Diego who took part in a multistage experiment examining fMRI differences in subjects with low and high responses to alcohol. Following approval by the UCSD Human Research Protection Program, a random cohort of students was first asked to respond to an email survey requesting information on demography, physical health, drinking and other drug use characteristics, as well as their family history of alcohol and other drug related problems.

Their survey responses were used to identify an initial cohort of healthy, right-handed students who had experience with alcohol but who never met criteria for an alcohol use or illicit substance use disorder; were not pregnant; and to be eligible for this functional Magnetic Resonance Imaging study, had no irremovable body metal and no history of traumatic brain injury.The survey also included the Self-Report of the Effects of Alcohol questionnaire, a retrospective measure of LR, as a preliminary screen for the low LR phenotype . The SRE uses 12-items that ask individuals to recall the number of standard drinks it took to feel four effects of alcohol across three time frames. The effects are: first feeling any effect; feeling as if speech was slurred; feeling unsteady walking; and unwanted falling asleep . The three time periods included the first five times one ever consumed at least a full drink, most recent three months where drinking at least once a month, and during one’s period of heaviest drinking. The score for each period was the sum of the number of drinks for the effects actually experienced with alcohol for that time frame, divided by the number of the up to four experiences reported to generate the average drinks needed per effect. In the present analysis, the First-5 metric was used to preliminarily categorize participants into low and high LR subgroups . Each low LR individual was matched to a high LR subject on other characteristics that might affect LR including age, sex, recent six-month pattern of intake of alcohol, nicotine use and their use of other drugs . Respondents who completed the survey, met the initial inclusion criteria, and who completed the SRE were contacted by phone to confirm their continued interest in participating in the laboratory portion of the protocol. Selected participants were invited to come to the laboratory where a trained interviewer administered the Semi-Structured Assessment for the Genetics of Alcoholism  interview to review their personal and family history of psychiatric and substance use disorders. Participants who still met the recruitment criteria were instructed to fast overnight before coming to the laboratory at 8AM and to refrain from using alcohol or other drugs for at least 48 hours prior to their first alcohol challenge session in our laboratory as part of the final screen for the subsequent fMRI placebo and alcohol challenges. The data reported here came from that laboratory-based alcohol challenge as the fMRI-based sessions did not include the full usual laboratory measures.Upon arrival at the laboratory, participants underwent a breathalyzer test to confirm a zero-breath alcohol concentration .

They were seated in a recliner, allowed to acclimate to the lab environment, and fed an isocaloric snack. After approximately one hour, they were given 10 minutes to imbibe an alcoholic beverage mixed as a 20% by volume solution in a carbonated, non-caffeinated sugar-free soda flavored to their choice. Male participants received 0.75 mL/kg ethanol while female participants ingested a drink containing 0.70 mL/kg to adjust for sex differences in body water . The average resulting BrAC peak was approximately 60 milligrams/dL at about 60 minutes postingestion as shown in Table 1 . As per the standard procedure performed in our lab over the years, the beverage was consumed through a straw extending from a thermos that obscured the actual beverage offered. At baseline prior to administering the drink, and at 30-minute intervals thereafter for up to 210 minutes, participants completed the Subjective High Assessment Scale . For these secondary analyses,vertical growing system to assess SHAS items most comparable to subjective measures used in other labs that perform human laboratory alcohol research , we focused on the SHAS-7 items of feeling High, Clumsy, Confused, Dizzy, Drunk, Alcohol’s Effects, and Difficulty Concentrating. Notably, the SHAS-7 score correlates highly with the complete 13-item measure that the Schuckit lab has used widely in their research and it uses the same visual analog marking scales to measure an individual’s subjective responses to alcohol . To compare our results more directly with reports from other human laboratories that measure subjective responses to alcohol and that use Biphasic Alcohol Effects Scale , we also analyzed the feeling Sleepy sub-scale of the SHAS which corresponds best with the Sedation sub-scale of the BAES. BrACs were also obtained every 30 minutes. Body sway, or standing ataxia, was recorded using a harness attached to the participant at the level of the axilla, from which ropes extended to the front and side at an approximate 90- degree angle from one another. Each rope passed over a pulley and anterior-posterior and lateral sway were recorded as the total number of centimeters of back-and-forth movement of the rope. Subjects completed three 1-minute trials at each time point with eyes open, feet together, and hands at their sides, with scores recorded as the mean values of the three trials. This is the same approach that has been used in our laboratory since about 1980. Body sway scores were adjusted for baseline differences before analyses were conducted. In keeping with NIAAA guidelines, participants were released from the laboratory when their BrAC fell below 0.01 g %. Following the completion of the laboratory-based alcohol challenge individuals went on to participate in the fMRI portion of the study the results of which have been reported previously .The following paradigm was used to compare low and high LR participants on their patterns of within-session acute tolerance. Using the methods of Plawecki et al. , the half-peaks on the ascending and descending BrAC arms, as well as the peak of the individual’s BrAC curve, were calculated.

Specifically, we used the Spline function in MATLAB® to determine the latencies corresponding to a session’s peak BrAC and to the same half-peak BrAC on the ascending and descending arms of the BrAC curve. We then computed corresponding subjective responses on the SHAS-7, Sleepy sub-scale, and Body Sway measures at those latencies, using linear interpolation between the nearest data collection time points. In keeping with procedures used in our lab for decades, participants were instructed to rate their subjective feelings on the SHAS visual analog scale as “none” prior to consuming the beverage. Thus, the baseline SHAS value was always a score of zero. The combined SHAS-7 total of scores were calculated by summing the scores for the seven individual items that comprise the scale that included the feeling High, Clumsy, Confused, Dizzy, Drunk, Alcohol’s Effects, and Difficulty Concentrating sub-scales. SHAS-7 total and individual item scores, the Sleepy sub-scale score, and baseline-corrected anterior-posterior and lateral body sway data were analyzed using a series of two-way, 3 within-subjects factors-by-2 groups mixed effects analysis of covariance , with Greenhouse-Geisser corrections for sphericity violations. The 3-level within-subjects factor was Timeand the 2-level between-subjects factor was either LR group or Sex . Separate analyses examining acute tolerance were performed utilizing one-way ANCOVAs between LR and Sex groups. Here, we defined the dependent variable, acute tolerance, as the difference score for each SHAS item at half-peak BrACs. In both sets of analyses, we covaried for the usual number of drinks per typical drinking occasion for the prior 6 months given that the low- and high-LR groups differed on this measure of recent drinking history prior to the alcohol challenge. The covariate was centered around the population mean before entry into the ANCOVA models as a main effect and as an interaction term with Time . All analyses were done in SPSS version 26 .Table 1 displays the demographic and physical characteristics as well as the drinking and other drug use patterns of the 60 pairs of low and high LR participants categorized based on their scores on the SRE-5. Consistent with prior reports on subsets of this sample , the two groups were well matched on demographic and physical characteristics and most measures of drinking and other drug use frequency occurring in the past six months.