Increased alcohol drinking and seizure susceptibility in female humanized ApoE4 knockin rats.

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Published in final edited form as: Physiol Behav. 2026 Mar 13;310:115308. doi: 10.1016/j.physbeh.2026.115308 Increased alcohol drinking and seizure susceptibility in female humanized ApoE4 knockin rats Chan Young Choi a , Jassmyn J Venegas a , Sarah M Rauch a , Francis A Walter b , Joel N Ryan c , Mythili Machireddy c , Jacob M Weisz a , Gregory C Tracy d, * , Annie J Baker d , Stan B Floresco e , Hee Jung Chung d , Nu-Chu Liang a Author information Article notes Copyright and License information a Department of Psychology, University of Illinois Urbana Champaign, USA b Neuroscience Program, University of Illinois Urbana Champaign, USA c School of Molecular and Cellular Biology, University of Illinois Urbana Champaign, USA d Department of Molecular and Integrative Physiology, University of Illinois Urbana Champaign, USA e Department of Psychology, University of British Columbia, Canada * Current affiliation: Center for Psychiatric Genetics, Endeavor Health Research Institute, Evanston, IL, USA ✉ Correspondence: Nu-Chu Liang, Department of Psychology, University of Illinois Urbana-Champaign, 513 Psychology Bldg., 603 E. Daniel Street, M/C 716, Champaign, IL 61820, USA, ncliang8@illinois.edu , Fax: 217-244-5876 Issue date 2026 Jun 1. PMC Copyright notice PMCID: PMC13123892  NIHMSID: NIHMS2164366  PMID: 41833783 The publisher's version of this article is available at Physiol Behav Abstract Epidemiological analyses suggest that the Ɛ4 allele of apolipoprotein E ( ApoE ) genes may influence the effects of alcohol on cognitive and executive function and dementia risk compared to the Ɛ3 allele. Here, we investigated this question in female rats given that women are more vulnerable than men to the Ɛ4 genotype effects on various diseases. Experiment 1 examined the effects of alcohol drinking on performance in a Barnes maze and an operant strategy set-shifting (OSS) task during abstinence in wildtype (WT) and homozygous ApoE4 knock-in (E4) rats. Experiment 2 repeated the behavioral assessments to assess the effects of heavy alcohol exposure and explored seizure susceptibility in E4 and homozygous ApoE3 knock-in (E3) rats. The experiments revealed that E4 rats drank significantly higher doses of alcohol than did the WT and E3 rats. However, there was no genotype or alcohol effect on performance in the Barnes maze and the OSS task. Notably, E4 rats had a shorter latency to kainate-induced seizures and maintained worse seizures compared to age-matched E3 rats. These findings suggest that the Ɛ4 allele may confer a higher risk for increased alcohol drinking without significantly exacerbating alcohol-associated decline in cognitive and executive function in females. Given the scarcity and discrepant reports regarding the role of ApoE polymorphism on seizure disorders among human and rodent studies, results of this study also underscore the need for more rigorous clinical and preclinical studies to determine the role of ApoE in sporadic and alcohol withdrawal seizures. Keywords: ApoE , alcohol, executive function, Barnes maze, strategy set-shifting, seizure, gene-environment interaction 1. Introduction Alcohol consumption is causally related to many categories of internationally classified diseases including cancer, cognitive dysfunction, and dementia ( Rehm et al., 2017 ). Human and animal studies both indisputably reveal that long-term, repeated heavy alcohol exposure has a detrimental impact on the decline in cognitive and executive function, leading to subsequent development of dementia ( Nunes et al., 2019 ). However, whether a light to moderate level of alcohol exposure is protective on some health conditions is controversial. Previous systemic reviews revealed that mild-to-moderate alcohol consumption plays a protective role against cognitive decline and dementia ( Di Marco et al., 2014 ; Rehm et al., 2019 ) and suggested that moderate alcohol exposure promotes cellular survival pathways in the heart, vasculature, and brain ( Collins et al., 2009 ). By contrast, a retrospective cohort study in France revealed that moderate levels of drinking are associated with structural brain damage and increased burden of dementia ( Schwarzinger et al., 2018 ). Recent epidemiological analyses concluded that health-related harms outweigh the marginal beneficial effects of alcohol and that no level of alcohol exposure is safe for health ( Burton and Sheron, 2018 ). One key factor that may contribute to previous discrepancy on the relationships among alcohol, health, and diseases is the genetic influence on health risk resulting from different levels of alcohol exposure ( Chen et al., 2022 ). Given the increasing prevalence of global alcohol use ( Manthey et al., 2019 ) and the knowledge gap regarding the interaction between alcohol and genetic influences, better understanding of genetic mechanisms that may underlie the extent to which alcohol increases the risk on cognitive and other health issues is essential to develop optimal guidelines on safe drinking and prevention on alcohol-related diseases. Highly expressed in the liver and brain, apolipoprotein E ( ApoE ) plays an important role in transporting cholesterol in and out of the brain ( Theendakara et al., 2018 ). In humans, there are three ApoE alleles, Ɛ2, Ɛ3, and Ɛ4, which produce three protein isoforms that differ by amino acid at positions 112 and 158. The E2 isoform has cysteine at both positions; the E3 isoform has cysteine and arginine, respectively, at position 112 and 158, whereas the E4 isoform has arginine at both positions ( Belloy et al., 2019 ). The Ɛ4 genotype is highly associated with increased risks of neurodegenerative diseases such as late-onset Alzheimer’s disease (AD) and dementia with Lewy bodies and cardiovascular diseases ( Belloy et al., 2019 ). Notably, epidemiological analyses of how the Ɛ4 genotype may influence how light-to-moderate levels of alcohol exposure impacts brain structural abnormalities and cognitive dysfunction are inconclusive. One study found a potential reduced risk of developing dementia in light alcohol drinkers carrying the Ɛ4 allele ( Ruitenberg et al., 2002 ), but another found that the beneficial effect of drinking is confined to the Ɛ4 non-carriers ( Luchsinger et al., 2004 ). Importantly, other analyses reported that the risk of dementia is significantly higher in alcohol users expressing Ɛ4 than Ɛ4 non-carriers ( Anttila et al., 2004 ; Dufouil et al., 2000 ; Panza et al., 2009 ). The challenges of accurately estimating the level of alcohol exposure and identifying causal mechanisms in human studies underscore the strengths of using animal models to elucidate whether and how the Ɛ4 genotype may interact with alcohol exposure to influence cognitive decline and the development of dementia ( Matloff et al., 2019 ). In light of the need to understand the potential interactive effects of the Ɛ4 gene and alcohol exposure on the development of dementia, this study explored the effects of alcohol exposure on cognitive and executive function in Sprague-Dawley (SD) rats in which humanized ApoE ( hApoE ) gene was knockin to replace endogenous rat ApoE gene. This commencing exploratory study included only female rats because women are more vulnerable than men to the Ɛ4 genotype effects on AD ( Altmann et al., 2014 ) and their alcohol use have significantly increased over the past 2 decades ( Fama et al., 2019 ). Women are significantly more vulnerable to neurotoxic effects of alcohol, which can lead to reduced brain volume and cognitive dysfunction ( Crawford and Ryder, 1986 ). Many rodent studies with different exposure procedures in wildtype and selectively bred high alcohol drinking rats have shown higher alcohol intakes in females than males ( Mittal et al., 2020 ). The higher alcohol intake in female rats may render greater detrimental effects on the brain and associated function. However, the effects of alcohol exposure in female subjects remain insufficiently studied, warranting the focus on female wildtype and hApoE rats in the current study. The rat ApoE genotype displays functional features that resemble the Ɛ3 genotype ( Tran et al., 2013 ), which is the most common ApoE genotype in humans ( Theendakara et al., 2018 ). Thus, experiment 1 compared the effects of long-term alcohol drinking on behaviors in the wildtype (WT) and hApoE Ɛ4 knockin (E4) SD rats. The results of experiment 1 revealed that E4 rats consumed more alcohol than their WT counterparts, but their long-term moderate alcohol consumption did not lead to poorer outcomes on cognitive and executive function. To confirm the increased alcohol intake in carriers of the ԑ4 genotype and to further explore the impact of heavy alcohol exposure on behavioral function, experiment 2 compared alcohol intake and the effects of heavy alcohol exposure in E4 versus hApoE Ɛ3 knockin (E3) female rats. In both experiments, alcohol drinking started around adolescence to resemble the human condition where most drinking begins with moderate levels of alcohol in periadolescence and then escalates to episodic binge and/or heavy drinking ( Chung et al., 2018 ; Windle, 2016 ). Lastly, experiment 2 also examined behavioral seizures induced by kainate to determine whether like humanized E4 transgenic mice ( Hunter et al., 2012 ), E4 rats also show increased seizure propensity compared to their E3 counterparts. 2. Materials and Methods 2.1. Subjects All female SD rats were purchased and shipped from Envigo (Indianapolis, IN). Experiment 1 utilized 20 wildtype (WT, # 38701F) and 20 homozygous ApoE4 knock-in (E4, # 35901F), whereas Experiment 2 included six homozygous ApoE3 knock-in (E3, #39501F) and six E4 rats. Genotypes were confirmed by PCR and gel electrophoresis according to the vendor’s instruction. They arrived at the animal facility at approximately 1 month old and were pair-housed in clear plastic cages with a dimension of 35 cm × 45.5 cm × 17.8 cm in a temperature- controlled room. The housing room was maintained on a 12:12 light/dark cycle with the light onset at 10:30 AM and 1:00 PM for experiments 1 and 2 , respectively. Rats had ad libitum access to Tekkad global 18% protein diet (3.1 kcal/g, 2918 Irradiated, Envigo, Madison, WI) and water except during experimental procedures described below. Daily rat care and weighing started within one hour after the light onset and lasted for approximately one hour. All experimental procedures are approved by the Institutional Animal Care and Use Committee (Protocol # 20175) of the University of Illinois Urbana–Champaign and are in accordance with the Guide for the Care and Use of Laboratory Animals. Figure 1 summarizes the timeline for each experiment. Figure 1. Open in a new tab Experimental timelines. (A) In Experiment 1 , daily ethanol (EtOH) drinking occurred Monday to Friday during the last two hours of the dark and the first hour of the light cycle, which is indicated by the grey bar in the diagram. The 2% sucrose preference test occurred on the 3rd and 4th day of abstinence. Training and testing for learning and memory using a Barnes maze (BM), sensorimotor gating using pre-pulse inhibition (PPI) and executive function using operant strategy set-shifting (OSS) started after two weeks of abstinence from the 13-week alcohol drinking. (B) In Experiment 2 , EtOH drinking was measured at both 2 and 6 months of age and followed the same schedule as in Experiment 1 , except that the entire drinking period occurred only in the dark cycle. Following voluntary drinking during the 2nd month of age, heavy EtOH exposure was done via oral gavage on Mondays (M), Wednesdays (W), and Fridays (F) during the 3rd month of age. PPI, elevated plus maze (EPM) and open field test (OF) were conducted after the alcohol abstinence period began. Training and testing for the OSS started one week after abstinence from alcohol exposure. Marble burying test (MB) occurred before kainate seizure induction. The results of behavioral tests aside from BM, OSS, and kainate-induced seizure were mostly negative and beyond the scope of this report, so they are described in the supplementary document . 2.2. Alcohol Exposure Experiment 1. The experimental design included 10 rats per group for WT with exposure to only water throughout the study (WT-W), WT to alcohol (WT-EtOH), E4 to saccharin (E4-S), and E4 to alcohol (E4-EtOH). This sample size was selected based on our previous studies with similar intake and behavioral measures that rendered a > 0.8 observed power with alpha = 0.05. WT-W served as a naïve control and because saccharin was applied to encourage alcohol drinking, E4-S served as the saccharin control. The group design served to compare rats without (WT-W and E4-S) and with alcohol exposure (WT-EtOH and E4-EtOH) between genotypes. The four groups were within the scope of our primary hypothesis that there may be potential interactive effects between the Ɛ4 gene and alcohol exposure on behavior. Furthermore, to apply the three Rs principle of animal research, the WT-S and E4-W control groups were not included in this inaugural experiment. Before drinking exposure started, the WT groups were assigned such that they had similar average body weights. To accurately measure individual fluid intake, a transparent divider with holes of 0.5 cm diameter was inserted in each home cage to separate the two rats while allowing interactions and measurement of individual fluid intakes. Drinking training started on the fourth day after arrival and habituation to the facility. Drinking exposure occurred from 8:00 to 11:30 AM in home cages. Water bottles were replaced with bottles of 0.1% saccharin for the WT-EtOH, E4-S, and E4-EtOH groups of rats during the ~ 3 hours period. For the E4 rats, daily intakes during the 3 days training were averaged for assigning groups with similar baseline saccharin intake and body weight. After group assignment for each genotype and drinking training were completed, water, saccharin, versus alcohol (10% in 0.1% saccharin) daily drinking occurred from Monday to Friday every week for 13 weeks. Thus, rats drank respective fluids from two to four months of age, i.e., from adolescence to early adulthood. Our previous measure in adolescent rats that underwent this drinking regimen indicated that they reached a moderate blood alcohol concentration (BAC) level of ~ 50 mg/dl at the 1- and 3-h sampling time points ( Nelson et al., 2018 , 2016 ). To determine whether the long-term alcohol drinking rendered an acute withdrawal symptom, rats received a sucrose preference test where a bottle of water and a bottle of 2% sucrose solution were provided on the 3rd and 4th day of abstinence. Other behavioral assessments began after 2 weeks of withdrawal and the abstinence continued throughout the behavioral procedures ( Figure 1A ). Experiment 2. This was a pilot experiment to determine the influence of hApoE genotype on alcohol drinking and the effects of alcohol exposure. Experiment 1 revealed that alcohol naïve WT, which resembles the Ɛ3 genotype in humans ( Tran et al., 2013 ), and E4 rats performed similarly in behavioral tests (see below). Given such negative finding in Experiment 1 and considering that this experiment aimed to explore whether there is a genotype influence on the effects of heavy alcohol exposure, an alcohol naïve group was not included in each genotype. Both E3 and E4 rats received the same alcohol drinking schedule as described above in Experiment 1 , except that their weekday drinking exposure occurred from 9:00 AM to 1:00 PM for five consecutive weeks. This exposure period was one hour longer than in Experiment 1 and was done to include the last four hours of the dark cycle as well as promoting a higher level of alcohol drinking. Since Experiment 1 did not reveal robust behavioral impairments following 13 weeks of moderate drinking, alcohol was administered via oral gavage on Monday, Wednesday, and Friday with the weekly incrementing dose from 2, 3, 4, to 5 g/kg during the four weeks immediately following the alcohol drinking exposure. Previously, we demonstrated that 3 g/kg alcohol administration via oral gavage rendered BAC levels above the 80 mg/dl criterion for excessive binge drinking ( Crabbe et al., 2011 ; Sangiamo et al., 2023 ). After this early life alcohol exposure, rats underwent a series of behavioral assessments during abstinence ( Figure 1B ). Finally, to determine whether genotype difference in alcohol intake persists to adulthood, daily alcohol drinking was measured again for five weekdays when the rats were at 6-month-old and before undergoing kainate-induced seizure as described below. 2.3. Barnes maze The Barnes maze is an elevated round platform of 122 cm in diameter with 20 evenly spaced holes that were 10 cm in diameter and 2 cm away from the edge. The maze was set up in the middle of an illuminated testing room with several visuospatial cues in place, and a concealed overhead-mounted camera aimed directly at the center of the maze was used to record each trial. The camera was wired to display real-time images and store captured videos in a computer in the adjacent room. The round platform was mounted on a rotatable cart that enabled rotation at 360°. Underneath one of the holes attached an escape box (30 × 12.5 × 14.5 cm) with a 20° incline ramp. The procedures involved 8 days of training followed by 2 days of memory and reversal learning. The rats performed two trials on each day to locate the escape box for a reward of entering the box and staying in the dark for 30 seconds. During training, the rats were placed on the maze to locate the escape box and were guided to and placed in the box after the 90 seconds allowance of exploration had elapsed. There were four starting positions on the maze, and the rats started at each position over four trials across two days. This way rats performed two trials on each day to reach four training trials per starting position during the eight training days. The next day after the last training trial was completed, e.g., the 9th day, rats performed a probe trial where they were placed in the center of the maze to evaluate their memory. Following the probe trial, the location of the escape box was rotated 180° to the opposite side of the maze for reversal learning. There were three reversal learning trials with different starting position, the first trial followed the probe trial on the 9th day and the remaining two trials occurred on the 10th day. The exploration time during trials of reversal learning was increased to 150 seconds. Spatial learning and memory on the maze were assessed via scoring the number of errors made before locating the escape box and latency to enter the escape box in the recorded videos by two experimenters who did not know the group assignment. Additionally, an open-sourced deep neural network (DNN) architecture for pose estimation, DeepLabCut (DLC), was utilized to measure escape latency and travel length during each trial from the recorded videos using our previously published procedures ( Sangiamo et al., 2023 ). 2.4. Strategy Set-Shifting Behavioral flexibility was assessed via an operant strategy set-shifting (OSS) task in operant chambers (Med Associates, Fairfax, VT) that was established by the Floresco laboratory ( Floresco et al., 2008 ; Tomm et al., 2018 ). Rats performed the OSS task under a food restriction schedule where they received allotted chow to maintain body weight at ~ 85 – 90% of their body weights prior to the food restriction schedule. Each operant chamber was equipped with two retractable levers and a cue light above each lever. The OSS program included several phases of operant response training. The initial phase involved training rats to press a lever for a 45 mg food pellet (#F0021, Bio-Serv, Flemington, NJ) on an FR1 schedule followed by determining their preferred lever, e.g., side-bias. This phase of training took 7 – 10 days. The next day after lever preference was determined, rats performed the visual-cue discrimination phase. During this phase, each trial began with illumination of one of the two cue lights for 3 seconds followed by presentation of both levers. Pressing the lever with the illuminated cue light led to a food reward, whereas pressing the lever without illuminated cue light rendered termination of the trial, which also occurred when the rats did not make any response within 10 seconds of lever presentation. A session ended when the rats made a streak of 10 correct responses after a minimum of 30 trials or after 180 trails have elapsed. Most rats achieved the streak of 10 correct responses within one session, and rats that did not meet this criterion on the first day received a daily session on the following days until they met the criterion. Thus, this cue discrimination phase was completed in one to three days. The last phase of the OSS program, shift to response discrimination, occurred immediately on the next day after a rat met the criterion in the visual-cue discrimination. The initial 20 trials in this testing session were reminders of the visual-cue discrimination. Starting on the 21st trial, the rats were required to press their less preferred lever, e.g., opposite to their side-bias, to receive the food reward. In other words, the rule switched such that cue light illumination became irrelevant and the rats had to respond based on an egocentric strategy. The session ended after the rats made a streak of 10 correct lever presses based on the egocentric response discrimination or when the rats completed 160 trials after the rule switched. Altogether, the rats completed all phases of the OSS task in 10 – 15 days. All lever responses were recorded during each phase of the OSS program. Proportion of correct response, errors made to reach criterion during visual-cue and response discrimination, and types of errors made in trials during the egocentric response discrimination are the primary variables to assess learning efficiency and behavioral flexibility. Two main types of errors during response discrimination trials were analyzed. Perseverative errors were defined as pressing the lever with the cue-light illumination and never-reinforced errors were defined as pressing the preferred lever when the cue-light above it did not illuminate. 2.5. Kainate-induced Seizure Previous studies have reported increased seizure susceptibility in hApoE4 transgenic mice ( Hunter et al., 2012 ). To determine whether increased seizure susceptibility also occurs in hApoE4 rats, in experiment 2 , rats received an intraperitoneal injection of 20 mg/kg kainic acid (#78050, Sapphire North America, Ann Arbor, MI) 5 – 7 days after their last day of alcohol drinking. Two experimenters performed real time behavioral scoring and recorded the highest stage of behavioral symptoms reached every 10 minutes. The behavioral symptoms were characterized using modified Racine scales ( Kim et al., 2020 ; Liang et al., 2007 ). Briefly, stages 0 – 2 were characterized as no response to tail stiffening and wet dog shakes; stage 3 included rearing, salivation, and unilateral forelimb clonus; stage 4 advanced to bilateral forelimb clonus; stage 5 revealed bilateral fore- and hindlimb clonus and loss of posture control. Symptoms expressed in stage 3 were considered seizure-like behaviors, so the latency to reach stage 3 was recorded. One E3 and one E4 rat were mostly resting after receiving the kainate injection, which indicated failed injections. Thus, data from these two rats were not included in the analysis. The recurrence of stages 3 to 5 seizures was monitored, and within 1 hour of completing the first cycle of stages 3 – 5 seizures, rats were anesthetized with isoflurane and sacrificed. Rats that never reached stage 5 seizure were sacrificed 2 hours after the kainic acid injection. 2.6. Data analyses Data were analyzed with Statistica 7.1 (Stat Soft, Tulsa, OK). When the assumption of normality and homogeneity was met, ANOVAs were used to determine main and interactive effects between genotype and alcohol treatment. Alcohol intakes were analyzed with repeated measures ANOVAs using genotype as a between-subject factor and time as a within-subject factor. Similarly, data obtained from behavioral performance during Barnes maze and OSS was analyzed with repeated measures ANOVAs using genotype and alcohol treatment as between-subject factor and trials as a within-subject factor. If normality and homogeneity was violated, the Kruskal-Wallis non-parametric test was applied. When the sphericity assumption was violated, a Greenhouse-Geisser correction was applied to reduce the risk of a false significant effect. Fisher’s LSD post hoc analysis with a B-H false discovery correction was applied for when the comparisons involved ≤ 3 groups and Tukey’s HSD for when comparisons involved > 3 groups. 3. Results 3.1. Saccharin and ethanol intake During baseline drinking training in Experiment 1 , WT rats consumed significantly more 0.1% saccharin solution than did the E4 rats as indicated by a Kruskal-Wallis test [H(1) = 10.08, p < 0.002; Figure 2A ]. Despite lower baseline saccharin intake, E4 rats consumed more of the 10% ethanol solution compared to WT rats, as revealed by a main effect of genotype in the repeated measures ANOVA comparing the average 3-h intake across the 13 weeks of drinking: [F(1, 18) = 7.09, p < 0.02; Figure 2B ]. Post-hoc tests revealed that E4 rats began to drink significantly more of the 10% ethanol solution starting from week 5 ( p < 0.02). The group difference persisted until the end of the exposure period, but the level of drinking declined over time for all ethanol drinking rats [main effect of time: F(3.07, 55.32) = 17.82, p < 0.001]. Despite the long-term alcohol drinking, the alcohol naïve and exposed rats had similar level of sucrose preference percentages during the 2-bottle preference test [H(1) = 1.53, p = 0.22; Figure S1 ]. Figure 2. Open in a new tab Baseline 0.1% saccharin intake and subsequent intake of 10% ethanol solution throughout the exposure period that began during adolescence. (A) Female hApoE4 KI (E4) rats had significantly lower saccharin intake than did the wildtype (WT) rats during the 3-day training period. (B) Female E4 rats had higher alcohol intake than did the WT rats. *: WT vs. E4, p < 0.026 (C) Female E4 rats had lower saccharin intake than did their E3 counterparts ( p = 0.08). (D) Female E4 rats had higher alcohol intake than their E3 counterparts. *: WT vs. E4 and E3 vs. E4, p < 0.025. In Experiment 2 , baseline 0.1% saccharin intakes in E4 rats were lower than the E3 rats, but the difference did not reach statistical significance [t(10) = 1.97, p = 0.08; Figure 2C ]. The higher alcohol intake in E4 rats was replicated in experiment 2 where we compared drinking to E3 rats. Here, we again observed a significant genotype effect [F(1, 10) = 9.81, p < 0.02]. Female E4 rats consumed significantly more alcohol than did their E3 counterparts starting in week 2 (post hoc, p < 0.02) of drinking throughout the 5-week of drinking period during adolescence, and this difference in alcohol drinking persisted when drinking was measured once the rats were at 6 months of age (post hoc, p < 0.004; Figure 2D ). Notably, E4 rats maintained their high level of alcohol drinking whereas E3 rats showed decline in drinking during adolescence, and both groups significantly lowered alcohol intake when ethanol solution was offered again at 6 months of age [time: F(5, 50) = 10.68, p < 0.001]. 3.2. Performance on the Barnes maze The results of escape latency scored manually by the experimenters were similar to those obtained using DLC, so the results reported here were obtained from DLC analyses. Errors made to escape presented were manually scored by the experimenters. In experiment 1 , one WT water consuming rat died unexpectedly during the fluid exposure period, leaving 9 rats in the WT-W group. For all variables measured, including errors, distance traveled, and latency to escape across eight training days that resulted in four trials per starting position, the averages from each starting position at each trial were used for the analyses (i.e., T1 to T4 in Figure 3 ). Figure 3. Open in a new tab Performance on the Barnes maze. (A – C) Regardless of alcohol exposure, all WT and E4 rats learned the task (T1 to T4). E4 rats made more errors and had longer distance than WT rats in the R1 trial. However, E4, but not WT, rats improved performance in subsequent reversal learning (R2 and R3) trials. *: WT vs. E4, post hoc, p < 0.05. (D – E) Alcohol exposed E3 and E4 rats performed comparably during the initial learning and memory trials, e.g., T1 to P trials. Similar to the WT versus E4 comparisons, E4 rats began with more errors, longer travel distance, and longer latency than E3 rats in R1 trial. However, E4 rats improved when E3 rats showed little evidence of improved performance in R2 and R3 trials. *: E3 vs. E4, post hoc, p < 0.05. Learning and memory. To compare genotype and alcohol treatment effects on learning and memory during Barnes maze, data from the training and probe trials (T1 to P in Figure 3 ), were included for repeated-measures ANOVAs. In Experiment 1 , all rats learned to perform the maze and reduced the number of errors [F(3.11, 108.71) = 78.58], travel distance [F(3.16, 110.55) = 31.79], and latency [F(2.90, 101.33) = 120.46] to locate the escape location (all p < 0.001; Figure 3 , A – C ). The only significant genotype effect [F(1, 35) = 36.13, p < 0.001] identified was that E4 rats were faster to locate and enter the escape box compared to their WT counterparts. Alcohol consumption had no effect on learning and memory on the Barnes maze as assessed by either variables (treatment effect, all p > 0.3). In Experiment 2 , analyses of all three variables revealed that both E3 and E4 rats who were exposed to alcohol improved their performance during the learning and memory trials [F(2.06, 20.57) = 11.40, F(4, 40) = 10.06 and 28.60 for respective measures, all p < 0.001; Figure 3 , D – E ). A significant genotype effect on distance traveled [F(1, 10) = 5.92, p < 0.04] indicated that E4 rats identified the escape location with a shorter traveling distance, especially during the probe trial, compared to their E3 counterparts (the P trial of Figure 3E ). Reversal learning. To compare genotype and alcohol treatment effects on reversal learning when the escape location was switch 180° on the Barnes maze, data during the three reversal trials, e.g., R1 to R3 in Figure 3 , were included for repeated measures ANOVAs. In Experiment 1 , E4 rats made more errors and longer travel distance to identify the new escape location on the first reversal learning trial compared to WT rats, as revealed by significant main effects of genotype for these measures [F(1, 35) = 8.92 and 4.35, both p < 0.05; Figure 3A and 3B ]. However, the genotype effect on latency to identify the escape location was not significant [F(1, 35) = 1.49, p > 0.2; Figure 3C ]. While there was no significant alcohol treatment effect, there were significant genotype by reversal trial interactions on all three variables [F(1.37, 47.9) = 9.71, F(1.37, 18.1)= 6.89, and F(1.33, 46.72)= 4.40, all p < 0.02], indicating that WT rats did not improve their performance within three trials during the reversal learning ( Figure 3 , A – C ). In Experiment 2 , repeated-measures ANOVAs of errors, distance traveled, and latency to locate and enter the new escape location revealed no significant trial effects in either measures [F(2, 20) = 2.83, 1.77, and 1.70 for respective measures, all p > 0.08], indicating that the E3 and E4 rats did not show significant improvement during the three reversal learning trials. It appeared that the lack of significant trial effects was driven by the E3 rats ( Figure 3 , D – E ). Such observation is supported by the significant interactions of genotype by trial in errors and latency [F(2, 20) = 5.90 and 5.12, respectively, both p < 0.02] to enter the new escape location. E4 rats made significantly more errors and had longer latency compared to the E3 rats during the first reversal trial (post hoc, p < 0.03) and their performance on the third reversal trial significantly improved (post hoc R1 vs. R3 of E4, p < 0.03 for both measures, Figure 3D and 3F ). 3.3. Performance during operant strategy set-shifting In addition to the one WT-W rat, data from one rat in the WT-EtOH group was excluded due to malfunction of the operant chamber. All variables measured during the operant SS were analyzed using factorial ANOVAs with genotype and alcohol exposure as between group factors. In Experiment 1 , all rats performed similarly well regardless of genotype and alcohol exposure. During the visual cue discrimination, the number of errors made to reach the task criterion was similar between genotype and alcohol exposure [F(1, 34) = 2.12 and 3.18, respectively, both p > 0.08; Figure 4A ]. Likewise, the proportion of correct response during the 20 reminder trials of visual cue discrimination before the strategy-shift did not differ, indicating that rats in all groups retrieved this rule comparably [F(1, 34) = 2.58 and 0.69, respectively, both p > 0.1; Figure 4B ]. Once shifted to response discrimination, the number of errors made to reach the task criterion was similar in rats of both genotype and different alcohol exposures [F(1, 34) = 0.01 and 0.96, respectively, both p > 0.3; Figure 4C ]. During the response discrimination, there were no genotype or alcohol effect on the type of errors made. In other words, alcohol exposed and E4 rats did not make more preservative [F(1, 34) = 0.36 and 1.69 for genotype and alcohol exposure both p > 0.2; Figure 4D ] than their non-alcohol exposed and WT counterparts. Because of assumption violation, a non-parametric Kruskal-Wallis test was applied to determine group differences on never-reinforced errors ( Figure 4D ). Although the test identified a significant group effect [H(3) = 8.75, p < 0.04], post hoc Dunn’s tests did not reveal any specific between group difference. Figure 4. Open in a new tab Performance during the OSS in WT and E4 rats. Regardless of genotype and alcohol exposure (n = 9 – 10/group), performance during (A) visual cue discrimination, (B) the reminder trials of visual cue discrimination, and (C) response discrimination did not significantly differ. (D) The type of errors made after the response strategy shift did not differ across groups. Similar negative findings were revealed in Experiment 2 . Female E3 and E4 alcohol exposed rats made similar numbers of errors to reach the criterion of visual cue discrimination [H(1) = 0.23, p > 0.6; Figure 5A ] and had similar proportion of correct responses during the reminder trials [F(1, 10) = 0.10, p > 0.7; Figure 5B ]. They required similar number of errors to acquire the response discrimination strategy [F(1, 10) = 1.26, p > 0.2; Figure 5C ]. Notably, E3 rats made significantly more preservative errors than did the E4 rats [F(1, 10) = 6.02, p < 0.04; Figure 5D ], but they made similar number of never-reinforced errors [F(1, 10) = 3.38, p > 0.09; Figure 5D ] during the response discrimination trials. Figure 5. Open in a new tab Performance during OSS in E3 and E4 rats. Regardless of genotype (n = 6/genotype), performance during (A) visual cue discrimination, (B) the reminder trials of visual cue discrimination, and (C) response discrimination did not significantly differ. (D) After the response strategy shifted, E3 rats made more perseverative, but not never-reinforced, errors than did E4 rats. *: p < 0.04. 3.4. Kainate-induced seizure One-way factorial ANOVA revealed that the latency to reach stage 3 seizure was significantly shorter in E4 than E3 rats [F(1, 8) = 12.20, p < 0.009; Figure 6A ]. All E4 rats reached the most severe form of seizure, e.g., stage 5 seizure, whereas only one E3 rat did so. Mann-Whitney U tests were applied to compare the nonparametric seizure score recorded at each time point. The results revealed that compared to E3 rats, E4 rats maintained at a significantly more severe stage of seizure starting at 50 minutes after the kainate injection [Us = 0 – 4, p < 0.05; Figure 6B ]. Figure 6. Open in a new tab Kainate-induced seizure in E3 and E4 rats. (A) E4 rats reached stage 3 seizure significantly sooner than E3 rats. *: p < 0.01. (B) E4 rats maintained at a more severe stage of seizure throughout the observation period. *: Mann-Whitney U tests, p < 0.05. 4. Discussion Dementia is characterized by a significant decline in cognitive and executive function. The Ɛ4 allele is the most prevalent genetic risk ( Belloy et al., 2019 ), whereas alcohol is an emerging environmental risk of sporadic AD and its related dementia ( Matloff et al., 2019 ). This study explored the influence of early life alcohol exposure on cognitive and executive function assessed by a Barnes maze and an OSS task, respectively, in WT, E3, and E4 rats. The main finding of this study was that despite lower intake of the saccharin vehicle, female E4 rats drink significantly higher levels of alcohol than their WT and E3 counterparts. The higher level of alcohol drinking in E4 rats, however, did not exacerbate deficits in the Barnes maze and operant SS tasks. Notably, female E4 rats were more vulnerable than E3 rats to kainate-induced seizure. These findings reveal behavioral similarity as well as differences in hApoE knockin rats versus transgenic mice. The lack of learning and memory deficits on the Barnes maze in female E4 rats compared to the WT controls concurs with the finding from a previous study that also tested the E4 rats at ~ 6 month of age ( Kulkarni et al., 2020 ). This finding contrasts the findings that male and female mice with E4 target replacement show deficits in learning and memory in the Barnes maze or Morris water maze as early as 3 or 4 months of age compared to their E3 transgenic counterparts ( Liraz et al., 2013 ; Rodriguez et al., 2013 ). However, other studies with transgenic E4 mice did not find worse performance in a Morris water maze or a radial arm maze until the mice reach 16 and 12 months of age, respectively ( Andrews-Zwilling et al., 2010 ; Hartman et al., 2001 ). Similar to the finding of later onset of memory deficits in transgenic mice, a separate study found that female E4 rats had worse spatial working memory in a radial arm maze task than their WT counterparts when tested at 12 – 13 months of age ( Lee et al., 2024 ). Interestingly, a research group has shown that both female E4 rats and E4 transgenic mice begin to show impairment in a conditioned taste aversion learning, which is considered hippocampus-independent learning, compared to their WT or E3 counterparts as young as 3 – 4 months of age ( Har-Paz et al., 2021 , 2019 ). Despite the disparity in the onset of spatial learning and memory decline in rat and mouse hApoE models, the literature shows that Ɛ4 carriers begin to show cognitive decline earlier than WT and Ɛ3 carriers. Given that rats are closer to humans in physiology, genetics, and morphology ( Do Carmo and Cuello, 2013 ) and are the preferred species for assessment of cognition ( Ellenbroek and Youn, 2016 ), it will be worthwhile to thoroughly investigate the performance on the Barnes maze or other tasks that assess cognitive function in male and female hApoE knockin rats at different ages in future studies. One of the most notable findings in this study is the maintenance of a significantly higher level of voluntary alcohol drinking in female E4 than in WT and E3 rats. Such finding contrasts the finding that 3xTg-AD mice drank significantly more alcohol than the WT mice only during the initial 3 weeks of drinking and there was no genotype difference in total alcohol intake during the 11-week drinking period ( Hoffman et al., 2019 ). Similarly, previous studies found no differences in alcohol drinking between WT mice and other mouse models of familial AD and neurodegenerative disease, the APP/PS1 and P301S mice ( Catavero et al., 2022 ; Day et al., 2023 ). These findings suggest that the Ɛ4 genotype may be a risk factor for increasing alcohol intake, whereas other rare genetic risk factors of AD had no influence on voluntary drinking. Importantly, findings in the literature regarding whether alcohol exposure exacerbates decline in cognitive and executive function in rodent models of AD thus far are inconsistent. Whereas our and other studies did not find worse performance in alcohol exposed E4 rats, APP/PS1 mice, or P301S mice than in their WT counterparts ( Catavero et al., 2022 ; Day et al., 2023 ), alcohol exposure via drinking or vapor in male and female adult 3xTg-AD mice exacerbated impairments in Morris water maze compared to their WT counterparts ( Hoffman et al., 2019 ; Sanna et al., 2023 ). The 3xTg-AD mouse model used in the two studies includes three rare familial mutations for AD, Psen1 , APPSwe, and tauP301L . The findings in this and other studies suggest that certain genetic risk factors of AD such as Psen1 , APPSwe, and tauP301L may interact with alcohol to hasten the development from functional decline to dementia and underscore the need for more studies in various rodent models to elucidate the underlying mechanisms. Unlike previous studies that found significant impairments in Barnes maze ( Kuzmin et al., 2012 ; Stragier et al., 2015 ; Vetreno and Crews, 2012 ) and OSS ( Gass et al., 2014 ; Trantham-Davidson et al., 2014 ) in rodents that were repeatedly exposed to moderate to high levels of alcohol, this study did not find alcohol induced impairments in both tasks during abstinence. The moderate level of alcohol exposure in Experiment 1 did not render a withdrawal symptom measured via a sucrose preference test within the 4th day of abstinence. Thus, it is possible that the moderate level of consumption in Experiment 1 was not sufficient to produce long lasting cognitive and executive impairments assessed after 1 – 2 months of abstinence. Intriguingly, results from the reversal learning of the Barnes maze and the type of errors following strategy shift in the OSS task provide evidence of a genotype effect on behavioral flexibility, which is a measure of executive function. In both Experiments 1 and 2 , compared to WT and E3 rats, E4 rats made a greater number of errors and increased travel distance on the Barnes maze during the first trial when the escape location had changed. The behavioral patterns in E4 rats may be interpreted as that they had less behavioral flexibility than the WT and E3 rats. In subsequent reversal learning trials, however, E4 rats significantly improved their performance when WT and E3 rats showed little evidence of learning the change of escape location. WT and E4 rats performed similarly during the operant SS task in Experiment 1 , whereas E3 rats made significantly more perseverative errors than E4 rats in Experiment 2 . Hence, results from both experiments appear to corroborate better performance in E4 than in WT and E3 rats after the rule of a task has changed. This possibility will require confirmation via experiments with higher sample size because of the high variation of errors made in the OSS tasks and the small sample size, which rendered a limited study power in Experiment 2 . Furthermore, the significant genotype difference in saccharin intake suggests that ApoE4 may alter taste and related ingestive behaviors, reflecting a need of including the WT-S and E4-W groups in Experiment 1 and alcohol naïve controls in Experiment 2 . Given these limitations, a more comprehensive group design with a priori power analyses to determine appropriate sample size will be critical to elucidate the gene by environment interactions in follow up studies. Audiogenic and generalized tonic-clonic seizures are among the most severe form of alcohol withdrawal syndrome. Neuronal networks in the brainstem and compensatory upregulation of NMDA and kainate receptors and calcium channels are considered underlying mechanisms of alcohol withdrawal seizures, which typically occur 6 – 48 hours after the cessation of drinking ( Rogawski, 2005 ). Instead of examining audiogenic and generalized seizures within 48 hours after alcohol withdrawal, Experiment 2 assessed seizure susceptibility by a kainate injection > 5 days after the last alcohol consumption and the E3 and E4 rats had reached 6 months of age. The result that E4 alcohol exposed rats had shorter latency to clonic seizure and more severe seizure than their E3 counterparts is in line with findings in transgenic ApoE mice. One study found that transgenic E4 mice, particularly females, begin to show increased spontaneous tonic-clonic seizures following exposure to mild stress as early as 5 months of age compared to their E2 and E3 counterparts ( Hunter et al., 2012 ). Transgenic hApoE mice showed similar susceptibility to the convulsant, pentylenetetrazol (PTZ), at 6 months of age, but male transgenic E4 mice exhibited shorter latency and more severe forms of PTZ clonus compared to their E2 and E3 counterparts when tested at 17-month old ( Hunter et al., 2012 ). Using the 5xFAD mouse model of AD, another study demonstrated that expression of the Ɛ4 gene in male and female 5xFAD mice increased PTZ-induced seizures when tested after 8 months of age compared to expression of the Ɛ3 gene ( Lamoureux et al., 2021 ). These existing literatures are consistent with the increased seizure susceptibility observed in Experiment 2 , although the potentially stressful repeated behavioral testing and the lack of alcohol naïve controls confounded the interpretation. Mechanistically, a previous study used cultured embryonic hippocampal neurons from SD rats to demonstrate that compared to ApoE3, ApOE4 increased neuronal calcium response to NMDA via interactions between NMDA receptors and lipoprotein receptor-related proteins, which increased neurotoxicity ( Qiu et al., 2003 ). Another recent study found that compared to their hApoE3 counterparts, mice with hApoE4 targeted replacement have reduced hippocampal expression of Na+/K+-ATPase and glycolytic enzymes. The reduced Na+/K+-ATPase is associated with increased susceptibility to kainate-induced seizure in hApoE4 mice and in line with Na+/K+-ATPase related epilepsy in human cortices and animal models ( Singh et al., 2025 ). ApoE4 is also susceptible to proteolytic cleavage that produces neurotoxic fragments. These fragments are particularly harmful to GABAergic interneurons, which can lead to hyperexcitability and network dysregulation in the hippocampus and cortex ( Najm et al., 2019 ). The selective vulnerability of GABAergic interneuron is intriguing in the context of alcohol exposure and withdrawal related seizure, given that alcohol acts on GABA A receptor to produce its biological and psychoactive effects. Variation in the GABRA2 subunit of GABA A is associated with risk for increased alcohol intake and dependence ( Arias et al., 2013 ; Soyka et al., 2008 ). It is possible that ApoE4 also has an indirect interaction with GABA A receptors via its influence on the GABAergic neurotransmission, which in turn affects the level of drinking and severity of alcohol withdrawal. Although these mechanisms can support an increased risk for seizure and developing epilepsy in Ɛ4 carriers, especially when encountering challenges such as alcohol withdrawal, few human studies investigated whether the ApoE polymorphism is associated with risk for seizure disorders and the findings are inconclusive ( Briellmann et al., 2000 ; Sporis et al., 2005 ). Notably, one study with 194 alcohol dependent patients (38 women) found a positive and negative association between alcohol withdrawal seizures and the Ɛ3 and Ɛ2 allele, respectively; and the Ɛ4 allele had no association ( Wilhelm et al., 2007 ). The discrepancy among human studies and contrast findings between human and rodent studies underscore the need for more rigorous studies to determine the role of hApoE in sporadic as well as alcohol withdrawal seizures. As noted above, there are limitations in this study. While the alcohol drinking regimen can convey moderate levels of drinking, BAC was not measured to confirm the level of alcohol intoxication. Despite including the high dose alcohol oral gavage, E3 and E4 rats in Experiment 2 showed behavioral proficiency similar to rats in Experiment 1 . Thus, the lack of alcohol-induced impairments in both BM and OSS in this study may reflect insufficient alcohol exposure. Presumably, female E4 rats could have altered alcohol metabolism that renders a lower or similar BAC level to their WT and E3 counterparts despite high alcohol intake. Without a persistently higher BAC level in E4 than in WT and E3 rats during ethanol exposure, a lack of exacerbated behavioral deficits would be an expected outcome. It is also possible that functional assessment at young age prevented revelation of interactive effects between alcohol and ApoE4. The fact that ApoE4 is the top genetic risk factor for late onset sporadic AD underscores the importance of considering the age factor when determining the timing of functional assessment ( Lee et al., 2026 ). Additionally, despite a noted female vulnerability in the effects of ApoE4 on functional decline and AD ( Lee et al., 2026 ), previous studies with hApoE knockin rodents suggested increased male susceptibility of dysfunction associated with liver and metabolic problems ( Mattar et al., 2022 ; Wu et al., 2021 ). Given that alcohol has toxicity in multiple organs including the brain and liver, it will be worthwhile to include male rats in future investigations. Overall, our experiments demonstrated a higher voluntary ethanol drinking in female E4 rats compared to their WT and E3 counterparts and suggested a greater susceptibility to kainite-induced seizures in female E4 rats compared to E3 rats. While the results revealed possible increased alcohol drinking without exacerbating impairments in certain cognitive and executive function, the findings of increased saccharin intake and reduced startle magnitude during a sensory motor gating test in E4 rats ( Supplementary Figure S3B ) underscore the current insufficient investigation and understanding of biological and behavioral phenotypes of hApoE rats in the research field. The findings and limitations of our study also highlight the urgent need to elucidate mechanisms underlying the consequences of interactions among age, sex, ApoE genes, and alcohol exposure. Supplementary Material Supplementary materials NIHMS2164366-supplement-Supplementary_materials.docx (272.5KB, docx) Acknowledgements This study was supported by a Research Board Award RB21010 at UIUC to NCL and NIH R01 NS10019, RF1 AG083625, Alzheimer’s association AARG-NFT-644507 to HJC. 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