Computational Mechanisms Underlying Multi-Step Planning Deficits in Methamphetamine Use Disorder.
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ABSTRACT:
SUBMITTER: Lavalley CA
PROVIDER: S-EPMC11230339 | biostudies-literature | 2024 Jun
REPOSITORIES: biostudies-literature
Publications
Computational Mechanisms Underlying Multi-Step Planning Deficits in Methamphetamine Use Disorder.
Lavalley Claire A CA Mehta Marishka M MM Taylor Samuel S Chuning Anne E AE Stewart Jennifer L JL Huys Quentin J M QJM Khalsa Sahib S SS Paulus Martin P MP Smith Ryan R
medRxiv : the preprint server for health sciences 20240628
Current theories suggest individuals with methamphetamine use disorder (iMUDs) have difficulty considering long-term outcomes in decision-making, which could contribute to risk of relapse. Aversive interoceptive states (e.g., stress, withdrawal) are also known to increase this risk. The present study analyzed computational mechanisms of planning in iMUDs, and examined the potential impact of an aversive interoceptive state induction. A group of 40 iMUDs and 49 healthy participants completed two ...[more]
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Project description:ObjectiveMethamphetamine and cannabis are two widely used, and frequently co-used, substances with possibly opposing effects on the central nervous system. Evidence of neurocognitive deficits related to use is robust for methamphetamine and mixed for cannabis. Findings regarding their combined use are inconclusive. We aimed to compare neurocognitive performance in people with lifetime cannabis or methamphetamine use disorder diagnoses, or both, relative to people without substance use disorders.Method423 (71.9% male, aged 44.6 ± 14.2 years) participants, stratified by presence or absence of lifetime methamphetamine (M-/M+) and/or cannabis (C-/C+) DSM-IV abuse/dependence, completed a comprehensive neuropsychological, substance use, and psychiatric assessment. Neurocognitive domain T-scores and impairment rates were examined using multiple linear and binomial regression, respectively, controlling for covariates that may impact cognition.ResultsGlobally, M+C+ performed worse than M-C- but better than M+C-. M+C+ outperformed M+C- on measures of verbal fluency, information processing speed, learning, memory, and working memory. M-C+ did not display lower performance than M-C- globally or on any domain measures, and M-C+ even performed better than M-C- on measures of learning, memory, and working memory.ConclusionsOur findings are consistent with prior work showing that methamphetamine use confers risk for worse neurocognitive outcomes, and that cannabis use does not appear to exacerbate and may even reduce this risk. People with a history of cannabis use disorders performed similarly to our nonsubstance using comparison group and outperformed them in some domains. These findings warrant further investigation as to whether cannabis use may ameliorate methamphetamine neurotoxicity.
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Project description:People with methamphetamine use disorder (MUD) struggle to shift their behaviour from methamphetamine-orientated habits to goal-oriented choices. The model-based/model-free framework is well suited to understand this difficulty by unpacking the computational mechanisms that support experienced-based (model-free) and goal-directed (model-based) choices. We aimed to examine whether 1) participants with MUD differed from controls on behavioural proxies and/or computational mechanisms of model-based/model-free choices; 2) model-based/model-free decision-making correlated with MUD symptoms; and 3) model-based/model-free deficits improved over six weeks in the group with MUD. Participants with MUD and controls with similar age, IQ and socioeconomic status completed the Two-Step Task at treatment commencement (MUD n = 30, Controls n = 31) and six weeks later (MUD n = 23, Controls n = 26). We examined behavioural proxies of model-based/model-free decisions using mixed logistic regression, and their underlying mechanisms using computational modelling. At a behavioural level, participants with MUD were more likely to switch their choices following rewarded actions, although this pattern improved at follow up. At a computational level, groups were similar in their use of model-based mechanisms, but participants with MUD were less likely to apply model-free mechanisms and less likely to repeat rewarded actions. We did not find evidence that individual differences in model-based or model-free parameters were associated with greater severity of methamphetamine dependence, nor did we find that group differences in computational parameters changed between baseline and follow-up assessment. Decision-making challenges in people with MUD are likely related to difficulties in pursuing choices previously associated with positive outcomes.
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Project description:ImportanceMortality associated with methamphetamine use has increased markedly in the US. Understanding patterns of methamphetamine use may help inform related prevention and treatment.ObjectiveTo assess the national trends in and correlates of past-year methamphetamine use, methamphetamine use disorder (MUD), injection, frequent use, and associated overdose mortality from 2015 to 2019.Design, setting, and participantsThis cross-sectional study analyzed methamphetamine use, MUD, injection, and frequent use data from participants in the 2015 to 2019 National Surveys on Drug Use and Health (NSDUH). Mortality data were obtained from the 2015 to 2019 National Vital Statistics System Multiple Cause of Death files.ExposuresMethamphetamine use.Main outcomes and measuresMethamphetamine use, MUD, injection, frequent use, and overdose deaths.ResultsOf 195 711 NSDUH respondents aged 18 to 64 years, 104 408 were women (weighted percentage, 50.9%), 35 686 were Hispanic individuals (weighted percentage, 18.0%), 25 389 were non-Hispanic Black (hereafter, Black) individuals (weighted percentage, 12.6%), and 114 248 were non-Hispanic White (hereafter, White) individuals (weighted percentage, 60.6%). From 2015 to 2019, overdose deaths involving psychostimulants other than cocaine (largely methamphetamine) increased 180% (from 5526 to 15 489; P for trend <.001); methamphetamine use increased 43% (from 1.4 million [95% CI, 1.2-1.6 million] to 2.0 million [95% CI, 1.7-2.3 million]; P for trend = .002); frequent methamphetamine use increased 66% (from 615 000 [95% CI, 512 000-717 000] to 1 021 000 [95% CI, 860 000-1 183 000]; P for trend = .002); methamphetamine and cocaine use increased 60% (from 402 000 [95% CI, 306 000-499 000] to 645 000 [95% CI, 477 000-813 000]; P for trend = .001); and MUD without injection increased 105% (from 397 000 [95% CI, 299 000-496 000] to 815 000 [95% CI, 598 000-1 033 000]; P for trend = .006). The prevalence of MUD or injection surpassed the prevalence of methamphetamine use without MUD or injection in each year from 2017 to 2019 (60% to 67% vs 37% to 40%; P for trend ≤.001). Adults with MUD or using injection were more likely to use methamphetamine frequently (52.68%-53.84% vs 32.59%; adjusted risk ratio, 1.62-1.65; 95% CI, 1.35-1.94). From 2015 to 2019, the adjusted prevalence of MUD without injection more than tripled among heterosexual women (from 0.24% to 0.74%; P < .001) and lesbian or bisexual women (from 0.21% to 0.71%; P < .001) and more than doubled among heterosexual men (from 0.29% to 0.79%; P < .001) and homosexual or bisexual men (from 0.29% to 0.80%; P = .007). It increased over 10-fold among Black individuals (from 0.06% to 0.64%; P < .001), nearly tripled among White individuals (from 0.28% to 0.78%; P < .001), and more than doubled among Hispanic individuals (from 0.39% to 0.82%; P < .001). Risk factors for methamphetamine use, MUD, injection, and frequent use included lower educational attainment, lower annual household income, lack of insurance, housing instability, criminal justice involvement, comorbidities (eg, HIV/AIDS, hepatitis B or C virus, depression), suicidal ideation, and polysubstance use.Conclusions and relevanceThis cross-sectional study found consistent upward trends in overdose mortality, greater risk patterns of methamphetamine use, and populations at higher risk for MUD diversifying rapidly, particularly those with socioeconomic risk factors and comorbidities. Evidence-based prevention and treatment interventions are needed to address surges in methamphetamine use and MUD.
| S-EPMC8459304 | biostudies-literature
Project description:People with Methamphetamine Use Disorder (PwMUD) spend substantial time and resources on substance use, which hinders their ability to explore alternate reinforcers. Gold-standard behavioural treatments attempt to remedy this by encouraging action towards non-drug reinforcers, but substance use often persists. We aimed to unravel the mechanistic drivers of this behaviour by applying a computational model of explore/exploit behaviour to decision-making data (Iowa Gambling Task) from 106 PwMUD and 48 controls. We then examined the longitudinal link between explore/exploit mechanisms and changes in methamphetamine use 6 weeks later. Exploitation parameters included reinforcement sensitivity and inverse decay (i.e., number of past outcomes used to guide choices). Exploration parameters included maximum directed exploration value (i.e., value of trying novel actions). The Timeline Follow Back measured changes in methamphetamine use. Compared to controls, PwMUD showed deficits in exploitative decision-making, characterised by reduced reinforcement sensitivity, U = 3065, p = 0.009, and less use of previous choice outcomes, U = 3062, p = 0.010. This was accompanied by a behavioural pattern of frequent shifting between choices, which appeared consistent with random exploration. Furthermore, PwMUD with greater reductions of methamphetamine use at 6 weeks had increased directed exploration (β = 0.22, p = 0.045); greater use of past choice outcomes (β = -0.39, p = 0.002) and greater choice consistency (β = -0.39, p = 0.002). Therefore, limited computational exploitation and increased behavioural exploration characterise PwMUD's presentation to treatment, while increased directed exploration, use of past choice outcomes and choice consistency predict greater reductions of methamphetamine use.
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Project description:Lithium has been the first-line treatment for bipolar disorder (BD) for more than six decades. Although the molecular effects of lithium have been studied extensively and gene expression changes are generally believed to be involved, the specific mechanisms of action that mediate mood regulation are still not known. In this study, a multi-step approach was used to explore the transcriptional changes that may underlie lithium's therapeutic efficacy. First, we identified genes that are associated both with lithium exposure and with BD, and second, we performed differential expression analysis of these genes in brain tissue samples from BD patients (n = 42) and healthy controls (n = 42). To identify genes that are regulated by lithium exposure, we used high-sensitivity RNA-sequencing of corpus callosum (CC) tissue samples from lithium-treated (n = 8) and non-treated (n = 9) rats. We found that lithium exposure significantly affected 1108 genes (FDR < 0.05), 702 up-regulated and 406 down-regulated. These genes were mostly enriched for molecular functions related to signal transduction, including well-established lithium-related pathways such as mTOR and Wnt signaling. To identify genes with differential expression in BD, we performed expression quantitative trait loci (eQTL) analysis on BD-associated genetic variants from the most recent genome-wide association study (GWAS) using three different gene expression databases. We found 307 unique eQTL genes regulated by BD-associated variants, of which 12 were also significantly modulated by lithium treatment in rats. Two of these showed differential expression in the CC of BD cases: RPS23 was significantly down-regulated (p = 0.0036, fc = 0.80), while GRIN2A showed suggestive evidence of down-regulation in BD (p = 0.056, fc = 0.65). Crucially, GRIN2A was also significantly up-regulated by lithium in the rat brains (p = 2.2e-5, fc = 1.6), which suggests that modulation of GRIN2A expression may be a part of the therapeutic effect of the drug. These results indicate that the recent upsurge in research on this central component of the glutamatergic system, as a target of novel therapeutic agents for affective disorders, is warranted and should be intensified.
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Project description:BackgroundAlcohol use disorder is characterized by perseverative alcohol use despite negative consequences. This hallmark feature of addiction potentially relates to impairments in behavioral flexibility, which can be measured by probabilistic reversal learning (PRL) paradigms. We here aimed to examine the cognitive mechanisms underlying impaired PRL task performance in patients with alcohol use disorder (AUDP) using computational models of reinforcement learning.MethodsTwenty-eight early abstinent AUDP and 27 healthy controls (HC) performed an extensive PRL paradigm. We compared conventional behavioral variables of choices (perseveration; correct responses) between groups. Moreover, we fitted Bayesian computational models to the task data to compare differences in latent cognitive variables including reward and punishment learning and choice consistency between groups.ResultsAUDP and HC did not significantly differ with regard to direct perseveration rates after reversals. However, AUDP made overall less correct responses and specifically showed decreased win-stay behavior compared to HC. Interestingly, AUDP showed premature switching after no or little negative feedback but elevated proneness to stay when accumulation of negative feedback would make switching a more optimal option. Computational modeling revealed that AUDP compared to HC showed enhanced learning from punishment, a tendency to learn less from positive feedback and lower choice consistency.ConclusionOur data do not support the assumption that AUDP are characterized by increased perseveration behavior. Instead our findings provide evidence that enhanced negative reinforcement and decreased non-drug-related reward learning as well as diminished choice consistency underlie dysfunctional choice behavior in AUDP.
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Project description:Apolipoprotein E4 (APOE4), the main susceptibly gene for Alzheimer’s disease1–5, exerts cerebrovascular toxicity6 leading to blood-brain barrier (BBB) breakdown in humans7–9 and APOE4 transgenic mice10–13. Moreover, an early BBB dysfunction predicts cognitive decline in humans7. However, the comprehensive large-scale analysis of cell-specific mechanisms underlying APOE4 cerebrovascular disorder and how it relates to neuronal disorder is lacking. Using single-nucleus RNA-sequencing, phosphoproteome and proteome analysis14–17 here we show that APOE4 compared to APOE3 leads to early disruption of the BBB transcriptome in 2-3-month old APOE4 knock-in mice18 followed by dysregulation in protein signaling networks. This includes proteins regulating cell junctions, cytoskeleton, clathrin-mediated transport, and translation in brain endothelium, and transcription and RNA-splicing suggestive of DNA damage in pericytes. Changes in the BBB signaling mechanisms paralleled an early, progressive BBB breakdown and loss of pericytes starting at 2-3 months of age. The BBB breakdown preceded loss of neurites, post-synaptic interactome dysregulation, and behavioral deficits that developed 2-5 months later, and was associated with astrocyte and microglia response protecting BBB integrity. Thus, disruption of the BBB cell-specific signaling mechanisms could be an initial central contributor to APOE4-mediated neuronal disorder, and possibly a major target to correct APOE4-related cognitive deficits.
2022-08-23 | PXD029230 | Pride
Project description:BackgroundThe use of naltrexone plus bupropion to treat methamphetamine use disorder has not been well studied.MethodsWe conducted this multisite, double-blind, two-stage, placebo-controlled trial with the use of a sequential parallel comparison design to evaluate the efficacy and safety of extended-release injectable naltrexone (380 mg every 3 weeks) plus oral extended-release bupropion (450 mg per day) in adults with moderate or severe methamphetamine use disorder. In the first stage of the trial, participants were randomly assigned in a 0.26:0.74 ratio to receive naltrexone-bupropion or matching injectable and oral placebo for 6 weeks. Those in the placebo group who did not have a response in stage 1 underwent rerandomization in stage 2 and were assigned in a 1:1 ratio to receive naltrexone-bupropion or placebo for an additional 6 weeks. Urine samples were obtained from participants twice weekly. The primary outcome was a response, defined as at least three methamphetamine-negative urine samples out of four samples obtained at the end of stage 1 or stage 2, and the weighted average of the responses in the two stages is reported. The treatment effect was defined as the between-group difference in the overall weighted responses.ResultsA total of 403 participants were enrolled in stage 1, and 225 in stage 2. In the first stage, 18 of 109 participants (16.5%) in the naltrexone-bupropion group and 10 of 294 (3.4%) in the placebo group had a response. In the second stage, 13 of 114 (11.4%) in the naltrexone-bupropion group and 2 of 111 (1.8%) in the placebo group had a response. The weighted average response across the two stages was 13.6% with naltrexone-bupropion and 2.5% with placebo, for an overall treatment effect of 11.1 percentage points (Wald z-test statistic, 4.53; P<0.001). Adverse events with naltrexone-bupropion included gastrointestinal disorders, tremor, malaise, hyperhidrosis, and anorexia. Serious adverse events occurred in 8 of 223 participants (3.6%) who received naltrexone-bupropion during the trial.ConclusionsAmong adults with methamphetamine use disorder, the response over a period of 12 weeks among participants who received extended-release injectable naltrexone plus oral extended-release bupropion was low but was higher than that among participants who received placebo. (Funded by the National Institute on Drug Abuse and others; ADAPT-2 ClinicalTrials.gov number, NCT03078075.).
| S-EPMC8111570 | biostudies-literature
Project description:We performed single-nucleus RNA-sequencing of the cortex of APOE3 and APOE4 knock-in (KI)flox/flox mice to investigate the effects of human APOE4 gene on cell-specific signaling mechanisms at the BBB and in the brain.
2022-08-22 | GSE185063 | GEO
Project description:The ability to switch between multiple tasks is central to flexible behavior. Although switching between tasks is readily accomplished, a well established consequence of task switching (TS) is behavioral slowing. The source of this switch cost and the contribution of cognitive control to its resolution remain highly controversial. Here, we tested whether proactive interference arising from memory places fundamental constraints on flexible performance, and whether prefrontal control processes contribute to overcoming these constraints. Event-related functional MRI indexed neural responses during TS. The contributions of cognitive control and interference were made theoretically explicit in a computational model of task performance. Model estimates of two levels of proactive interference, "conceptual conflict" and "response conflict," produced distinct preparation-related profiles. Left ventrolateral prefrontal cortical activation paralleled model estimates of conceptual conflict, dissociating from that in left inferior parietal cortex, which paralleled model estimates of response conflict. These computationally informed neural measures specify retrieved conceptual representations as a source of conflict during TS and suggest that left ventrolateral prefrontal cortex resolves this conflict to facilitate flexible performance.
| S-EPMC1459038 | biostudies-literature