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. 2024 Nov 16;70:101478. doi: 10.1016/j.dcn.2024.101478

Associations between mesolimbic connectivity, and alcohol use from adolescence to adulthood

Angelica M Morales a,⁎, Scott A Jones a, Birgitta Carlson a, Dakota Kliamovich a, Joseph Dehoney b, Brooke L Simpson a, Kalene A Dominguez-Savage a, Kristina O Hernandez a, Daniel A Lopez a, Fiona C Baker c, Duncan B Clark d, David B Goldston e, Beatriz Luna d, Kate B Nooner f, Eva M Muller-Oehring c,g, Susan F Tapert h, Wesley K Thompson i, Bonnie J Nagel a,j
PMCID: PMC11617707  PMID: 39577156

Abstract

Dopaminergic projections from the ventral tegmental area (VTA) to limbic regions play a key role in the initiation and maintenance of substance use; however, the relationship between mesolimbic resting-state functional connectivity (RSFC) and alcohol use during development remains unclear. We examined the associations between alcohol use and VTA RSFC to subcortical structures in 796 participants (12–21 years old at baseline, 51 % female) across 9 waves of longitudinal data from the National Consortium on Alcohol and Neurodevelopment in Adolescence. Linear mixed effects models included interactions between age, sex, and alcohol use, and best fitting models were selected using log-likelihood ratio tests. Results demonstrated a positive association between alcohol use and VTA RSFC to the nucleus accumbens. Age was associated with VTA RSFC to the amygdala and hippocampus, and an age-by-alcohol use interaction on VTA-globus pallidus connectivity was driven by a positive association between alcohol and VTA-globus pallidus RSFC in adolescence, but not adulthood. On average, male participants exhibited greater VTA RSFC to the amygdala, nucleus accumbens, caudate, hippocampus, globus pallidus, and thalamus. Differences in VTA RSFC related to age, sex, and alcohol, may inform our understanding of neurobiological risk and resilience for alcohol use and other psychiatric disorders

Keywords: Ventral tegmental area, Alcohol, Sex differences, Longitudinal, Mesolimbic, MRI

1. Introduction

The mesolimbic pathway is comprised of dopaminergic projections from the ventral tegmental area (VTA) to the nucleus accumbens (NAcc), amygdala, and hippocampus (Lynd-Balta and Haber, 1994, Brinley-Reed and McDonald, 1999), which signal reward, aversion, salience, uncertainty, and novelty (Lammel et al., 2014). Alterations in the mesolimbic pathway are associated with changes in motivated behavior, cognitive functioning, and mood, which are believed to contribute to various psychiatric disorders, including substance use disorders, attention deficit/hyperactivity disorder (ADHD), schizophrenia, and mood disorders (for reviews see, Volkow et al., 2009, Del Campo et al., 2011, Grace, 2016). As many psychiatric disorders emerge during adolescence and young adulthood (Solmi et al., 2022), understanding the development of the mesolimbic system may be critical for identifying the neurobiological factors of risk and resilience for mental health conditions.

Resting-state functional connectivity (RSFC) produces indirect measures of coordinated neural activity by assessing the temporal correlations of low frequency oscillations in spontaneous blood-oxygen-level-dependent (BOLD) signal between distinct brain regions (Fox and Raichle, 2007). Using this technique, a large cross-sectional study demonstrated that patterns of VTA RSFC are consistent with the known dopaminergic projections from the VTA, but also extend to regions that play a role in limbic loops such as the globus pallidus and thalamus (Tomasi and Volkow, 2014). Results from studies examining the development of VTA RSFC to subcortical regions have varied, with evidence for age-related increases in VTA RSFC to the amygdala and caudate, decreases in VTA-globus pallidus connectivity, and no significant associations between VTA-NAcc RSFC from adolescence to adulthood (Tomasi and Volkow, 2014, Murty et al., 2018). These findings suggest that the development of VTA RSFC to subcortical regions is heterogenous, with both segregation and integration observed over time. Nonetheless, longitudinal studies that measure within-subject change are needed to determine whether age-related findings emerging from cross-sectional studies are reflective of developmental differences. VTA RSFC may also be related to sex, as a prior study found greater VTA-orbital gyrus RSFC in male as opposed to female participants (Peterson et al., 2017), indicating relevance for further study.

Adolescence and young adulthood are developmental periods during which alcohol use is prevalent (Johnston et al., 2022, Patrick et al., 2022), and prior studies suggest that individual differences in the severity of alcohol use are related to variation in mesolimbic circuitry. For example, levels of NAcc activation in response to nondrug rewards are correlated with greater current (Braams et al., 2016) and future (Morales et al., 2018, Swartz et al., 2020) self-reported alcohol use in adolescents. Consistent with preclinical studies demonstrating that repeated exposure to alcohol produces neuroadaptations in mesolimbic circuitry that promote alcohol-seeking behavior (Carrillo and Gonzales, 2011, Bassareo et al., 2017), individuals with heavy alcohol use exhibit greater mesolimbic activation to alcohol cues than comparison samples (Kareken et al., 2004, Schacht et al., 2013) and cue-induced NAcc activation is linked to craving and alcohol use problems (Filbey et al., 2008, Myrick et al., 2008). In addition to the effects of alcohol on mesolimbic circuitry in reward-related contexts, preclinical studies have demonstrated that exposure to alcohol decreases spontaneous firing of VTA neurons during withdrawal (Diana et al., 1993, Shen et al., 2007). In humans, studies examining RSFC of VTA targets (i.e., NAcc, amygdala) have produced mixed results, with greater levels of self-reported alcohol use linked to both increased and decreased RSFC to prefrontal regions (Muller-Oehring et al., 2015, Crane et al., 2018, Hu et al., 2018, Veer et al., 2019, Arienzo et al., 2020). Although prior research has demonstrated that acute alcohol administration impacts VTA-striatal RSFC (Morales et al., 2023), to our knowledge, no studies have measured VTA RSFC beyond the period of acute alcohol intoxication or explored its relationship with self-reported patterns of alcohol use. This may be particularly relevant for connectivity between the VTA and NAcc, given the evidence suggesting that long-term neuroadaptations in these regions are relevant for the escalation and maintenance of alcohol use.

In the current study, we assessed the effect of past month alcohol use and its interactions with age and sex on VTA RSFC to relevant subcortical areas, using 9 waves of longitudinal data from the National Consortium on Alcohol & Neurodevelopment (NCANDA). Based on prior literature, we expected age-related changes in VTA RSFC to vary across regions (Tomasi and Volkow, 2014) and for male participants to exhibit greater VTA RSFC than female participants (Peterson et al., 2017). We also expected that greater alcohol use would be associated with less VTA-NAcc RSFC, in line with preclinical findings noting alcohol-induced decreases in spontaneous VTA activity (Diana et al., 1993, Shen et al., 2007). Given the evidence that alcohol is associated with more pronounced longitudinal changes in brain structure in younger adolescents, as opposed to older adolescents and young adults (Sun et al., 2023), and sex differences in neurobiology of alcohol use disorder (Flores-Bonilla and Richardson, 2020), we expected interactions between alcohol, age, and sex on VTA RSFC. Although alcohol use was more prevalent in the NCANDA sample than other substance use, we conducted exploratory analyses to determine if similar effects were observed with cannabis and cigarettes, as acute reinforcing effects of Δ9-tetrahydrocannabinol and nicotine are linked to dopamine release in the mesolimbic pathway (Brody et al., 2009, Bossong et al., 2015) and long-term exposure to these drugs has also been associated with differences in mesolimbic function in response to drug-related stimuli (David et al., 2005, Zhou et al., 2019) and at rest (Zhou et al., 2018, Zhang et al., 2022).

2. Methods

2.1. Participants

The NCANDA study consists of five data collection sites: University of California San Diego (UCSD), SRI International, Duke University, University of Pittsburgh, and Oregon Health & Science University (OHSU). At each site, institutional review boards approved study procedures. Written informed consent was obtained from participating adults and from the legal guardians of participating minors, while written assent was obtained from minors. Detailed descriptions of recruitment and study procedures have been published elsewhere (Brown et al., 2015). Briefly, 831 participants between the ages of 12 and 21 were enrolled over the course of approximately 1 year at baseline, 692 of which met criteria for no/low drinking (see Supplemental Table 1 for low drinking cutoffs by age) and 139 who exceeded those drinking thresholds at the time of study entry. This study includes participants from the first 9 waves of data collection (2013–2021) and participants were on average 23.3 years-old (range: 19–29-years-old) at wave 9. Participants were fluent in English, resided in proximity to an assessment site, and were excluded at baseline for MRI contraindications; vision or hearing impairments that could not be corrected; use of medication impacting neurobiology or blood flow; serious medical, developmental, or learning disorders; or current Axis I psychiatric disorders including substance dependence. During the first 4 waves of data collection, all participants were scanned annually; however, in all subsequent waves of data collection, participants only completed annual scans until they turned 22 and then at ages 24, 27, 30 and 33. For this project, participants were excluded for neurobiological abnormalities (n = 23), and scans were excluded due to excessive motion or failed quality assurance for the resting state scan (n = 457) and missing (n = 35) or inconsistent (n = 29) self-report of alcohol use, as described below. After these additional exclusions, this project included 796 participants and a total of 4025 scans.

2.2. Self-reported substance use

The Customary Drinking and Drug Use Record (Brown et al., 1998), an interviewer-administered questionnaire, was used to assess recent alcohol, cannabis, and cigarette use. Recent alcohol use was defined as the total number of drinks in the past month and was calculated as the product of frequency (e.g., During the last 30 days, how many days did you drink alcohol?) and quantity (Over the last month, in the average 24-hour period you were drinking, how many alcoholic drinks did you have?) of use. In exploratory analyses, we also examined frequency of cannabis use (i.e., days used) and cigarette use (i.e., product of frequency and average number of cigarettes) over the past 30 days. Timepoints were excluded from statistical analyses where participants reported more substance use in the past month than in the last year, suggesting invalid reporting. Additional validity-based exclusions from relevant analyses included reporting an average of more than 30 drinks per day in the past month (n = 3), greater than 60 cigarettes per day in the past month (n = 1), and not reporting both frequency and quantity of alcohol or cigarette use. Due to zero inflation, a constant of one was added to all substance use values and they were log-transformed to improve normality and meet the assumption of linearity between substance use predictors and RSFC outcomes.

2.3. MRI acquisition

At UCSD, SRI and Duke, a 3 T GE Discovery MR750 scanner with an 8 channel-head coil was used to acquire high-resolution structural MRI (TR = 5.912 ms, TE = 1.932 ms, flip angle = 11°, and voxel size = 1.2 × 0.9375 × 0.9375 mm), resting-state functional magnetic resonance imaging (fMRI, TR = 2200 ms, TE = 30 ms, flip angle = 79°, and voxel size = 3.75 × 3.75 × 5 mm, acquisition time for 274 volumes = 10:03 min), and a field map for correction of spatial distortions in functional images (TR = 1000 ms, TE = 5/7 ms, and voxel size = 1.87 × 1.87 × 2.5 mm). OHSU and the University of Pittsburgh initially used 3 T Siemens Magnetom Tim Trio scanners with a 12-channel head coil but upgraded to 3 T Siemens PRISMA FIT with a 20-channel head coil during the study. Across both Siemens scanners, parameters for acquisition of structural MRI (TR = 1900 ms, TE = 2.92 ms, flip angle = 9°, and voxel size = 0.9375 × 0.9375 × 1.2 mm), resting-state fMRI (TR = 2200 ms, TE = 30 ms, flip angle = 79°, and voxel size = 3.75 × 3.75 × 5 mm, acquisition time for 275 volumes = 10:12 min), and gradient field maps (TR = 700 ms, TE = 4.92/7.38 ms, and voxel size = 2.5 × 2.5 × 2.5 mm) were comparable. During collection of the resting-state scans, participants were instructed to stare at a gray screen, keep their eyes open, and to not think about anything in particular.

2.4. MRI preprocessing

Functional data were processed using the publicly available NCANDA pipeline (Muller-Oehring et al., 2018, Zhao et al., 2019), which incorporates several software packages including FSL (Jenkinson et al., 2012), Numpy (www.numpy.org), Nipype (Gorgolewski et al., 2011) and CMTK (Rohlfing et al., 2003). Briefly, functional images underwent motion correction (Jenkinson et al., 2002), outlier-detection, detrending, physiological noise removal, temporal filtering (low pass frequency: 0.1, high pass frequency 0.01), and spatial smoothing (8 FWHM). To align the functional data to the SRI24 atlas (Rohlfing et al., 2010), transformation parameters were obtained by registering the mean BOLD image to the high-resolution structural MRI and nonlinear transformation of the high-resolution structural MRI to the SRI atlas were applied to the BOLD data. Volumes with framewise displacement > 0.3 mm/TR were censored to minimize effects of motion (Muller-Oehring et al., 2018, Zhao et al., 2019). Scans were excluded if they had <7.8 min of usable data after motion censoring, failed visual inspection for artifacts, or had registration errors (Muller-Oehring et al., 2018).

For seed-based RSFC analyses, bivariate Pearson correlations were used to assess the association between the average time course of the VTA (Pauli et al., 2018) and the average time course from every subcortical region in the Harvard-Oxford subcortical atlas (Frazier et al., 2005). For each subcortical structure, VTA RSFC values underwent Fisher’s r to z transformation to improve normality and resulting values from the left and right hemisphere of each subcortical structure were averaged. One-sample t-tests at baseline demonstrated significant VTA RSFC to the NAcc (mean RSFC: 0.12, p < 0.0001), amygdala (mean RSFC: 0.24, p < 0.0001), caudate (mean RSFC: 0.08, p < 0.0001), hippocampus (mean RSFC: 0.27, p < 0.0001), globus pallidus (mean RSFC: 0.21, p < 0.0001), putamen (mean RSFC: 0.08, p < 0.0001), and thalamus (mean RSFC: 0.28, p < 0.0001); therefore, all subcortical regions in the atlas were examined.

2.5. Statistical analyses

Analyses were conducted in R version 4.3.1 using the ‘nlme’ and ‘mgcv’ packages. Linear mixed effects models (LMEs), including random intercepts for subject, site, and sibling, were used to examine the effects of age, sex, and recent alcohol use on VTA RSFC. Inclusion of a random intercept for each participant models within-subject variability that is consistent across visits and addresses nonindependence of observations. Statistical models were fit with maximum likelihood estimation, and nested models were directly compared using likelihood ratio tests. During the initial phase of model comparison, for each VTA RSFC connection, we examined (1) main effects of age and sex and (2) the addition of an age-by-sex interaction. To the best model including age and sex, we added (3) the main effects of alcohol, (4) a sex-by-alcohol interaction, (5) an age-by-alcohol interaction, (6) both 2-way interaction terms, or a (7) 3-way interaction between age, sex, and alcohol. To address potential cohort effects and residual motion, baseline age and number of frames excluded due to excessive motion were included as covariates in all models (Zhao et al., 2021). For each VTA RSFC connection, final models were selected by examining all possible iterations of nested model comparisons. To determine the sensitivity and specificity of the results, effects of recent alcohol use were tested in a sample excluding participants who exceeded cutoffs for no/low drinking at baseline and recent alcohol use was replaced with other relevant alcohol use (i.e., quantity, frequency), cannabis, and cigarette use variables in models including the full sample. Prior studies examining development in the NCANDA sample have found nonlinear effects of age on neurobiology and personality (Pfefferbaum et al., 2016, Jones et al., 2022, Jones et al., 2023); however, generalized additive mixed models (GAMMs) only provided evidence for nonlinear effects of age (effective degrees of freedom for smoothed age term > 1) in VTA connectivity to the amygdala and hippocampus (Supplemental Table 2). GAMMs did not provide evidence of nonlinear effects of age in models where there were significant effects of alcohol, nor did they provide additional information about the association between alcohol use and VTA RSFC. Therefore, this project utilized linear mixed models, with only linear age effects, to describe the association between alcohol and VTA RSFC, as GAMMs limit the interpretability of our primary effects of interest. In primary LME and GAMM analyses on alcoholic drinks per month, fixed effects of age and sex were deemed significant at a threshold of p < 0.05 after correction for 7 comparisons using false discovery rate (Benjamini and Hochberg, 1997). The model building strategy ensures that fixed effects involving alcohol are only interpreted in models that best describe the underlying data structure for each RSFC value and effects were deemed significant at p < 0.05.

3. Results

3.1. Participant characteristics

Demographic information at baseline is provided in Table 1. As substance use data are zero inflated, average alcohol, cannabis, and cigarette use across 9 waves of data collection are provided for the entire sample and for participants reporting past month use (Table 2).

Table 1.

Sample Demographics at Baseline.

Female Male
N (%) 404 (50.7 %) 392 (49.2 %)
Age: Mean (SD) 16.30 (2.57) 16.11(2.47)
Parental Education: Median (years) 16 17
Household Income: N (%)*
Less than $25,000 22 (3.1 %) 17 (2.4 %)
$25,000 through $49,999 49 (6.9 %) 33 (4.6 %)
$50,000 through $74,999 44 (6.2 %) 47 (6.6 %)
$75,000 through $99,999 46 (6.5 %) 53 (7.4 %)
$100,000 through $199,999 126 (17.7 %) 121 (17.0 %)
$200,000 and greater 70 (9.8 %) 84 (11.8)
Race/Ethnicity: N (%)
Asian 30 (3.8 %) 33 (4.1 %)
African American / Black 61 (7.7 %) 35 (4.4 %)
Hispanic 38 (4.8 %) 44 (5.5 %)
Multiracial 17 (2.1 %) 15 (1.9 %)
Native American / American Indian 0 (0 %) 3 (0.4 %)
Pacific Islander 3 (0.4 %) 1 (0.1 %)
Caucasian / White 255 (32.0 %) 261 (32.8 %)
Site: N (%)
UPMC 66 (8.3 %) 50 (6.3 %)
SRI 77 (9.7 %) 79 (9.9 %)
Duke 92 (11.6 %) 79 (9.9 %)
OHSU 71 (8.9 %) 75 (9.4 %)
UCSD 98 (12.3 %) 109 (13.7 %)
Participant with Sibling Enrolled: N (%) 152 (19.1 %) 148 (18.6 %)
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Notes: OHSU = Oregon Health & Science University; SRI = SRI International; UPMC = University of Pittsburgh Medical Center; UCSD = University of California, San Diego

% calculated based on entire sample with available data at baseline

* n = 712 at baseline

Table 2.

Substance Use Over 9 Waves of Data Collection in NCANDA Sample.

Alcohol Drinks/Month Cannabis Days/Month Cigarettes/Month
Overall Use Nonzero Overall Use Nonzero Overall Use Nonzero
Wave M (SD)† % M (SD)† M (SD)† % M (SD)† M (SD)† % M (SD)†
Baseline 1.8 (8.0) 15.8 11.2 (17.2) 0.3 (1.9) 6.2 4.3 (6.7) 0.1 (0.8) 0.7 7.4 (5.7)
Year 1 3.2 (10.8) 26.9 11.9 (18.1) 0.9 (3.8) 14.9 5.9 (8.2) 0.5 (3.9) 2.9 14.8 (17.3)
Year 2 4.1 (9.7) 35.6 11.6 (13.3) 1.5 (5.0) 19.3 7.7 (9.2) 2.1 (27.0) 6.0 33.8 (105.6)
Year 3 5.8 (12.5) 44.2 13.2 (16.0) 2.2 (6.1) 24.2 9.0 (9.6) 1.9 (27.7) 5.7 30.5 (110.4)
Year 4 8.2 (16.0) 52.5 15.6 (19.3) 2.8 (7.2) 27.6 10.2 (10.5) 3.1 (22.9) 7.7 35.9 (71.1)
Year 5 10.8 (22.1) 62.7 17.2 (25.9) 3.9 (8.2) 36.3 10.8 (10.6) 6.1 (50.4) 6.7 82.0 (169.3)
Year 6 13.9 (21.1) 69.4 20.0 (22.9) 5.2 (9.5) 41.9 12.4 (11.2) 1.9 (13.9) 10.0 16.7 (38.5)
Year 7 11.3 (17.3) 71.7 15.7 (18.7) 5.7 (10.0) 43.0 13.4 (11.4) 5.1 (30.1) 9.3 47.8 (82.2)
Year 8 15.5 (24.9) 73.3 21.1 (27.0) 6.2 (10.5) 44.2 14.1 (11.8) 3.6 (23.5) 9.7 31.8 (64.6)
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† Mean and standard deviation

3.2. Sex Differences and developmental changes in VTA RSFC

Table 3 provides standardized estimates for the final best fitting linear mixed effects models for VTA RSFC to each subcortical structure. Main effects of sex were found in VTA RSFC to the NAcc (Fig. 1A), amygdala, caudate, hippocampus, globus pallidus (Fig. 2A), and thalamus (β’s > 0.11, p’s < 0.05 corrected). On average, male participants had greater VTA RSFC to subcortical regions than female participants. Nonlinear effects of age using GAMMs were only detected in the amygdala and hippocampus (F’s > 4.47, p’s < 0.05 corrected, Supplemental Table 2). Qualitatively describing the GAMMs, VTA RSFC to the amygdala and hippocampus decreased earlier in adolescence and increased from adolescence into adulthood (Supplemental Figure 1). None of the best fitting linear mixed effects models or GAMMs included age-by-sex interactions.

Table 3.

Final best-fitting linear mixed effects models.

Std Estimate Std Error t-value p-value
Accumbens ∼ age + sex + alcohol drinks per month
Intercept −0.1465 0.1092 −1.34 0.1798
Age −0.0059 0.0281 −0.21 0.8337
Sex (male) 0.2114 0.0414 5.11 <0.0001*
Alcohol (drinks/month) 0.0544 0.0187 2.90 0.0037*
Amygdala ∼ age + sex
Intercept −0.0324 0.1137 −0.28 0.7759
Age† 0.0094 0.0234 0.40 0.6883
Sex (male) 0.1338 0.0436 3.06 0.0026*
Caudate ∼ age + sex
Intercept −0.1086 0.1069 −1.02 0.3100
Age 0.0505 0.0247 2.04 0.0412
Sex (male) 0.1482 0.0406 3.65 0.0004*
Hippocampus ∼ age + sex
Intercept −0.0862 0.0650 −1.33 0.1851
Age† 0.0788 0.0236 3.33 0.0009*
Sex (male) 0.1141 0.0453 2.52 0.0129*
Globus Pallidus ∼ age * alcohol drinks per month + sex
Intercept −0.0875 0.1255 −0.70 0.4857
Age 0.0488 0.0275 1.77 0.0763
Alcohol 0.1234 0.0298 4.15 <0.0001*
Sex (male) 0.1251 0.0438 2.86 0.0049*
Alcohol (drinks/month):Age −0.0697 0.0241 −2.90 0.0038*
Putamen ∼ age + sex + alcohol drinks per month
Intercept −0.0535 0.1010 −0.53 0.5961
Age 0.0415 0.0252 −1.65 0.0988
Sex (male) 0.0611 0.0399 1.53 0.1280
Thalamus ∼ age + sex
Intercept −0.1060 0.0774 −1.37 0.1707
Age 0.0300 0.0238 1.26 0.2077
Sex (male) 0.1711 0.0454 3.77 0.0002*
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† See Supplemental Material for nonlinear age effects

* Significant effects (age and sex effects p < 0.05 FDR-corrected)

Note: Models also included random effects of subject, site, and sibling and fixed effects for baseline age and number of motion outliers.

Fig. 1.

Fig. 1

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Associations between recent alcohol use and ventral tegmental area – nucleus accumbens connectivity. Trend lines are predicted values with 95 % confidence intervals for main effects of age (A) and alcohol (B) on ventral tegmental area (VTA) – nucleus accumbens (NAcc) resting state functional connectivity (RSFC) extracted from the final best-fitting model. Male participants (blue) exhibited greater VTA –NAcc RSFC than female participants (red, β = 0.21, p < 0.0001); however, there were no significant effects of age (A, displays individual trajectories for 796 participants). Greater recent alcohol use was associated with greater VTA-NAcc RSFC (β = 0.05, p = 0.004; B). Confidence intervals reflect uncertainty in predicted values across all subjects and do not account for variation due to random effects.

Fig. 2.

Fig. 2

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Associations between recent alcohol use and ventral tegmental area – globus pallidus connectivity. Trend lines represent predicted values and 95 % confidence intervals for nonsignificant main effects of age extracted from the best-fitting model for ventral tegmental area (VTA) – globus pallidus (GP) resting state functional connectivity (RSFC, A, displays individual trajectories for 796 participants). Male participants (blue) exhibited greater VTA – GP RSFC than female participants (A, red, β = 0.13, p < 0.005). There was an age-by-recent alcohol use interaction on VTA – GP RSFC (β = −0.07, p = 0.004). The interaction was driven by stronger positive associations between alcohol use and VTA-GP RSFC at earlier as opposed to later ages (B). Confidence intervals reflect uncertainty in predicted values across all subjects and do not account for variation due to random effects.

3.3. Associations between VTA RSFC and alcohol use

Greater alcohol use was associated with greater VTA RSFC to the NAcc (β = 0.05, p = 0.004, Fig. 1B) across the entire age range of this sample. Meanwhile, an age-by-alcohol interaction was detected on VTA-globus pallidus RSFC (β = −0.07, p = 0.004), and post-hoc examination of this model at varying ages found that greater alcohol use was associated with greater VTA-globus pallidus RSFC at earlier (age 16.29 years, β = 0.12, p < 0.0001; age 18.23 years, β = 0.09, p < 0.0001; age 19.92 years, β = 0.06, p = 0.0005), but not at later ages (age 21.80 years, β = 0.03, p = 0.09; Fig. 2B). Frequency of alcohol use was associated with the same pattern of effects as total alcoholic drinks per month on VTA RSFC to the NAcc and globus pallidus. While average number of alcoholic drinks per day in the past month were significantly associated with VTA-NAcc RSFC, the age-by-alcoholic drinks per day interaction on VTA-globus pallidus connectivity was not significant (Supplemental Table 3).

3.4. Associations between VTA RSFC in participants with no/low alcohol use at baseline

When excluding participants exceeding criteria for no/low drinking at baseline (n = 137), associations between recent alcohol use and VTA RSFC to the NAcc (main effect of alcohol: β = 0.08, p = 0.0006) and globus pallidus (age-by-alcohol use interaction: β = −0.10, p = 0.0007) remained significant (n = 659; see Supplemental Table 4).

3.5. Associations between VTA RSFC and cannabis and cigarette use

An age-by-frequency of cannabis use interaction on VTA-globus pallidus RSFC was detected (β = −0.07, p = 0.009). Similar to the effects of alcohol, post-hoc examination of this model at varying ages found that greater cannabis use was associated with greater VTA-globus pallidus RSFC at younger (age 16.29 years, β = 0.08, p = 0.01; age 18.23 years, β = 0.05, p = 0.03) but not older ages (age 19.92 years, β = 0.02, p = 0.19; age 21.80 years, β = −0.006, p = 0.76). No other effects of cannabis or cigarettes were detected in VTA RSFC to the NAcc or globus pallidus (p’s > 0.29, Supplemental Table 5).

4. Discussion

This longitudinal study provides novel information about how age, sex, and alcohol use are related to VTA RSFC from adolescence to young adulthood. As anticipated, age effects varied by region, with nonlinear age-effects observed in the amygdala in hippocampus, and no significant age effects in VTA RSFC to the NAcc, caudate, globus pallidus, putamen, or thalamus. We extend prior findings showing greater RSFC between the VTA-orbital gyrus in male compared to female participants (Peterson et al., 2017), by identifying a similar pattern of sex-differences in VTA RSFC to the NAcc, amygdala, caudate, hippocampus, globus pallidus, and thalamus. Consistent with our hypothesis and prior work suggesting age-specific effects of alcohol (Sun et al., 2023), alcohol use was associated with VTA-globus pallidus RSFC in adolescence, but not adulthood. However, although we expected negative associations between alcohol use and VTA RSFC, positive associations were detected in VTA RSFC to the NAcc and globus pallidus.

The unexpected positive association between alcohol use and VTA-NAcc RSFC may be explained by findings from preclinical studies demonstrating that individual differences in alcohol-induced neuroadaptations in pre- and post-synaptic VTA-NAcc connections vary according to voluntary drinking patterns. Low-alcohol-drinking mice exhibit higher spontaneous activity in VTA dopaminergic cell bodies than alcohol-naïve or high-alcohol-drinking mice after 12 weeks of exposure to alcohol (Juarez et al., 2017). Differences between high- and low-alcohol-drinking mice have also been observed in post-synaptic dopamine release in the NAcc depending on the type of VTA stimulation (Liu et al., 2020). Importantly, neuroadaptations induced by long-term alcohol exposure may influence rewarding effects of acute alcohol thereby shaping behavior, as low- but not high-alcohol-drinking mice exhibit increases in VTA-NAcc firing that correspond with ethanol doses and optogenetic stimulation of VTA-NAcc dopamine neurons in high-alcohol-drinking mice decreased alcohol consumption (Juarez et al., 2017). High-alcohol-drinking rodents exhibit phenotypes observed in humans with alcohol use disorders (McBride et al., 2014); however, few participants in the NCANDA sample met DSM-IV criteria for alcohol abuse or dependence (n = 34 alcohol abuse; n = 3 alcohol dependence; assessed yearly during the first 4 waves of the study and at ages 24 and 27 in subsequent years), suggesting different results may be observed in samples enriched for alcohol use disorders. Additional research in samples with greater prevalence of alcohol use disorders may help explain the unexpected directionality of the association between alcohol use and VTA RSFC observed in this study, as the positive association between alcohol use and VTA-NAcc RSFC may confer resilience as opposed to risk for alcohol use disorders.

The globus pallidus is a key node linking striatal and frontal brain regions in pathways that influence not only motor function, but also cognitive functions relevant for substance use like inhibitory control and decision making, motivation, and habit formation (for a reviews see, Saga et al., 2017, Campbell and Lobo, 2023). Neuroimaging studies have demonstrated that acute administration of alcohol decreases activation in the globus pallidus during response inhibition (Nikolaou et al., 2013) and decreases globus pallidus-striatal RSFC in adults with greater levels of baseline alcohol use (Fede et al., 2020). Our findings extend this work, suggesting that alcohol and cannabis use are positively associated with VTA-globus pallidus RSFC beyond the period of acute intoxication. A preclinical study demonstrated that cocaine exposure increases the number of projections from the globus pallidus to the VTA and increases activity of VTA dopamine neurons, resulting in increased drug-seeking behavior (Beier et al., 2017). Mechanistic studies to determine if alcohol and cannabis induce similar neuroadaptations in VTA-globus pallidus connections would further elucidate the role of the globus pallidus in regulating drug-related behaviors. Additional evidence for the role of the globus pallidus in alcohol use comes from a study in adolescents, which demonstrated that heavy drinking adolescents have greater activation in the striatum/globus pallidus in response to alcohol cues compared with control participants (Brumback et al., 2015). Interestingly, a meta-analysis in adults did not detect significant effects of alcohol cues in the globus pallidus (Zeng et al., 2021). Future work might directly assess age differences in response to alcohol cues in the globus pallidus and their link to interactions between alcohol and age on VTA-globus pallidus RSFC observed in this study.

This study provides the first evidence of nonlinear developmental trajectories of VTA connectivity to amygdala and hippocampus, connections which have been linked to contextual learning and memory in preclinical (Tang et al., 2020, Titulaer et al., 2021, Sayegh et al., 2024, Sias et al., 2024) and clinical studies (Loh et al., 2016, Kramar et al., 2021). Although it remains unclear how connectivity between these regions influences the development of psychiatric disorders, studies in rodents have linked projections from the VTA to the amygdala to anxiety-like behavior (Morel et al., 2022). Lack of significant age-related effects on VTA-NAcc RSFC is consistent with prior research (Tomasi and Volkow, 2014, Murty et al., 2018) and suggests that VTA-NAcc RSFC develops relatively early and that the protracted development of context-dependent VTA-NAcc RSFC may explain developmental differences in motivated behavior (Murty et al., 2018). Male participants exhibited greater VTA RSFC to most subcortical regions examined compared to female participants, an effect that might contribute to sex differences in the risk for certain psychiatric disorders. For example, the prevalence of ADHD is higher in boys than girls (Mowlem et al., 2019), and a prior study demonstrated that children with ADHD had higher VTA RSFC to the amygdala, globus pallidus, and thalamus (Tomasi and Volkow, 2014). Studies in animals and in humans have elucidated sex differences in the complex neurochemical processes that shape mesolimbic function (Konradi et al., 1992, Munro et al., 2006, Manza et al., 2022). Conducting multimodal studies combining RSFC with noninvasive measures of neurochemistry suitable for use in children and adolescents may aid in identifying the neurochemical mechanisms that underlie individual differences in VTA RSFC throughout development (Larsen et al., 2020).

Although this study has many strengths including the large sample size and longitudinal design, it is not without limitations. Several fMRI studies using atlas-derived VTA seeds have identified patterns of RSFC that align with known anatomical connections, suggesting the validity of the approach used in this manuscript (Murty et al., 2014, Tomasi and Volkow, 2014), but the relatively low resolution in most fMRI studies and the blurring induced by various fMRI preprocessing steps limit the anatomical specificity the findings in small nuclei like the VTA. This issue may be addressed in the future by studies using 7 T scanners that can achieve greater spatial resolution (Morris et al., 2022). A variety of factors other than substance use may impact the development of the mesolimbic system. For instance, individual differences in exposure to adversity and/or resilience traits have distinct associations with mesocorticolimbic connectivity during reward-based decision-making (Richter et al., 2019) and at rest (Park et al., 2021). These findings highlight how relevant factors related to VTA RSFC (Park et al., 2021) or alcohol use (Nguyen-Louie et al., 2024) not accounted for in this analysis may alter the interpretation of our findings. The statistical modeling strategy employed allowed us to examine the effects of alcohol in a developmental context and retain the largest sample given the accelerated design; however, it does not provide evidence for a causal association between alcohol and VTA RSFC. Future studies may employ different approaches (i.e., cross-lagged panel models) which allow for examination of how alcohol use at earlier time points is related to future VTA RSFC. Although this study explored the association of VTA RSFC to cannabis and cigarette use, the proportion of scans occurring after past month cannabis (24.23 % at any time point) or cigarette use (5.54 % at any time point) was low compared with alcohol (43.50 % at any time point), resulting in less statistical power for these analyses and increasing the possibility of type 2 errors. Additionally, age-related associations of alcohol and cannabis with VTA-globus pallidus RSFC may be attributable to alcohol, cannabis, or their combined use, as the observational nature of this study made it difficult to dissociate their effects. Most scans occurred after past month use of alcohol alone (23.6 %) or both alcohol and cannabis use (19.9 %), with few scans occurring after cannabis use only (4.3 %). In addition to differences in prevalence, discrepancies across substances may reflect heaviness or severity of use. No information was available about doses of exposure to phytocannabinoids or recent e-cigarette use (i.e., past 30 days), which may also contribute to individual differences in VTA RSFC (Ertl et al., 2024, Sun et al., 2024). Lastly, VTA RSFC varied as a function of sex assigned at birth; however, sex differences may be driven by biological, social, and environmental influences related to the construct, as evidenced by prior work demonstrating sex-differences in the association between frontostriatal RSFC and pubertal maturation (Ojha et al., 2022).

In sum, these findings contribute to our understanding of the mesolimbic network and suggest that age, sex, and alcohol use may contribute to individual differences in mesolimbic functions such as motivated behavior, cognition, and mood. Furthermore, sex differences and the timing of fluctuations in VTA RSFC may relate to the prevalence and trajectory of psychiatric disorders, a possibility that could be explored by future studies. While associations between alcohol use and VTA connectivity observed in this study should be replicated and may reflect pre-existing differences, preclinical studies provide strong evidence that individual differences in alcohol-induced neuroadaptations promote risk and resilience to problem alcohol use and suggest that interventions that modulate VTA-NAcc connectivity could alter alcohol use.

CRediT authorship contribution statement

David B. Goldston: Writing – review & editing, Project administration, Funding acquisition. Duncan B. Clark: Writing – review & editing, Project administration, Funding acquisition. Fiona C. Baker: Writing – review & editing, Project administration, Funding acquisition. Daniel A. Lopez: Writing – review & editing. Wesley K. Thompson: Writing – review & editing. Kristina O. Hernandez: Writing – review & editing, Investigation. Joseph Dehoney: Data curation, Writing – review & editing. Kalene A. Dominguez-Savage: Writing – review & editing, Investigation. Bonnie Nagel: Writing – review & editing, Project administration, Funding acquisition, Conceptualization. Brooke L. Simpson: Writing – review & editing. Susan F. Tapert: Writing – review & editing, Project administration, Funding acquisition. Dakota Kliamovich: Writing – review & editing, Data curation. Eva M. Muller-Oehring: Writing – review & editing, Project administration, Funding acquisition. Birgitta Carlson: Writing – review & editing, Investigation, Data curation. Kate B. Nooner: Writing – review & editing, Project administration, Funding acquisition. Scott A. Jones: Writing – review & editing, Formal analysis, Data curation. Beatriz Luna: Writing – review & editing, Project administration, Funding acquisition. Angelica M. Morales: Writing – review & editing, Writing – original draft, Visualization, Formal analysis, Data curation, Conceptualization.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

The author is an Editorial Board Member/Editor-in-Chief/Associate Editor/Guest Editor for [Journal name] and was not involved in the editorial review or the decision to publish this article.

Acknowledgements

We would like to thank Kilian M. Pohl for the preprocessing of the MRI described in Section 2.4. and the past and present research staff at Duke University, Oregon Health & Science University, University of Pittsburgh, SRI International, and University of California San Diego for their instrumental role in participant scheduling and data collection. Collection and distribution of this work was funded by the National Institute on Alcohol Abuse and Alcoholism (AA021697, AA021695, AA021692, AA021696, AA021681, AA021690, AA021691). Additional support for this project came from the National Institute of Health for the 3 T Siemens Prisma MRI instrument and High-Performance Computing Cluster housed in OHSU’s Advanced Imaging Research Center (S10OD021701 and S10OD018224), and the Oregon Opportunity Partnership for advancing biomedical research. AMM received funding from the National Institute on Drug Abuse (K01DA046649) and the Silver Family Innovation Fund.

Data statement

Collection and distribution of the NCANDA data were supported by NIH funding AA021681, AA021690, AA021691, AA021692, AA021695, AA021696, AA021697. Access to NCANDA data is available via the NIAAA Data Archive, collection 4513 (https://nda.nih.gov/edit_collection.html?id=4513). The authors do not have permission to share data otherwise. All scripts are available on the Open Science Framework (OSF) at https://osf.io/4y8st/.

Footnotes

Appendix A

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.dcn.2024.101478.

Appendix A. Supplementary material

Supplementary material

mmc1.docx (957KB, docx)

Data availability

Link provided to NDA repository were data will be available in the future

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