Social Determinants of Health Associated with How Cannabis is Obtained and Used in Patients with Cancer Receiving Care at a Cancer Treatment Center in Pennsylvania.

Despite increased rates of cannabis use among patients with cancer, there are gaps in our understanding of barriers to accessing cannabis. Social determinants of health (SDoH) are associated with access to healthcare, but few studies have evaluated how SDoH relate to cannabis access and use among cancer patients. We examined whether access to and modes of cannabis use differed across indicators of SDoH among patients receiving treatment from a large National Cancer Institute (NCI) designated cancer center. This anonymous cross-sectional survey was developed in collaboration with the NCI Cannabis Supplement consortium, which funded 12 supplements to NCI Center Core Grants across the United States. We evaluated the association of race, gender, income, and age with mode of cannabis use, source of obtaining cannabis, what influences their purchase, and medical cannabis certification status. Overall, 1,053 patients receiving treatment for cancer in Pennsylvania completed the survey and 352 (33.4%) reported using cannabis since their cancer diagnosis. Patients who identified as Black/African-American were less likely to have medical cannabis certifications (p=0.04). Males and Black/African-Americans were more likely to report smoking cannabis (vs other forms, ps<0.01) and to purchase cannabis from an unlicensed dealer/seller (p<0.01). Lower-income patients were more likely to be influenced by price and ease of access (ps<0.05). Although cannabis users were younger than non-users, age was not associated with any outcomes. The current data shed light on how critical drivers of health disparities (such as race, gender, and income) are associated with where patients with cancer obtain cannabis, what forms they use, and what may influence their purchase decisions.

Molecular Imaging of Pulmonary Inflammation in Users of Electronic and Combustible Cigarettes: A Pilot Study.

Electronic cigarette (EC) use has increased dramatically, particularly among adolescents and young adults, and, like cigarette use, can cause pulmonary inflammation and increase the risk of lung disease. Methods: This preliminary study used PET with 18F-6-(1/2)(2-fluoro-propyl)-4-methylpyridin-2-amine (18F-NOS) to quantify inducible nitric oxide synthase expression to characterize oxidative stress and inflammation in the lungs in vivo in 3 age- and sex-matched groups: 5 EC users, 5 cigarette smokers, and 5 controls who had never smoked or vaped. Results: EC users showed greater 18F-NOS nondisplaceable binding potential (BPND) than cigarette smokers (P = 0.03) and controls (P = 0.01), whereas BPND in cigarette smokers did not differ from that in controls (P > 0.1). 18F-NOS lung tissue delivery and inducible nitric oxide synthase distribution volume did not significantly differ among groups. Although there were no group differences in peripheral inflammatory biomarker concentrations, 18F-NOS BPND correlated with the proinflammatory cytokine tumor necrosis factor-α concentrations (rs = 0.87, P = 0.05) in EC users. Additionally, when EC users and cigarette smokers were pooled together, number of vaping episodes or cigarettes per day correlated with interleukin-6 levels (rs = 0.86, P = 0.006). Conclusion: This is the first PET imaging study to compare lung inflammation between EC and cigarette users in vivo. We found preliminary evidence that EC users have greater pulmonary inflammation than cigarette smokers and controls, with a positive association between pulmonary and peripheral measures of inflammation.

Positron Emission Tomography of Neuroimmune Responses in Humans: Insights and Intricacies.

The brain's immune system plays a critical role in responding to immune challenges and maintaining homeostasis. However, dysregulated neuroimmune function contributes to neurodegenerative disease and neuropsychiatric conditions. In vivo positron emission tomography (PET) imaging of the neuroimmune system has facilitated a greater understanding of its physiology and the pathology of some neuropsychiatric conditions. This review presents an in-depth look at PET findings from human neuroimmune function studies, highlighting their importance in current neuropsychiatric research. Although the majority of human PET studies feature radiotracers targeting the translocator protein 18 kDa (TSPO), this review also considers studies with other neuroimmune targets, including monoamine oxidase B, cyclooxygenase-1 and cyclooxygenase-2, nitric oxide synthase, and the purinergic P2X7 receptor. Promising new targets, such as colony-stimulating factor 1, Sphingosine-1-phosphate receptor 1, and the purinergic P2Y12 receptor, are also discussed. The significance of validating neuroimmune targets and understanding their function and expression is emphasized in this review to better identify and interpret PET results.

Reward and inhibition in obesity and cigarette smoking: Neurobiological overlaps and clinical implications.

Cigarette smoking and obesity are the leading causes of premature morbidity and mortality and increase the risk of all-cause mortality four-fold when comorbid. Individuals with these conditions demonstrate neurobiological and behavioral differences regarding how they respond to rewarding stimuli or engage in inhibitory control. This narrative review examines the role of reward and inhibition in cigarette smoking and obesity independently, as well as recent research demonstrating an effect of increased body mass index (BMI) on neurocognitive function in individuals who smoke. It is possible that chronic smoking and overeating of highly palatable food, contributing to obesity, dysregulates reward neurocircuitry, subsequently leading to hypofunction of brain networks associated with inhibitory control. These brain changes do not appear to be specific to food or nicotine and, as a result, can potentiate continued cross-use. Changes to reward and inhibitory function due to increased BMI may also make cessation more difficult for those comorbid for obesity and smoking.

[18F]NOS PET Brain Imaging Suggests Elevated Neuroinflammation in Idiopathic Parkinson's Disease.

Neuroinflammation is implicated as a key pathologic mechanism in many neurodegenerative diseases and is thought to be mediated in large part by microglia, native phagocytic immune cells of the CNS. Abnormal aggregation of the protein α-synuclein after phagocytosis by microglia is one possible neuropathophysiological mechanism driving Parkinson's disease (PD). We conducted a human pilot study to evaluate the feasibility of targeting the inducible isoform of nitric oxide synthase using the [18F]NOS radiotracer to measure neuroinflammation in idiopathic PD. Ten adults consisting of 6 PD patients and 4 healthy controls (HC) underwent one hour of dynamic [18F]NOS positron emission tomography (PET) brain imaging with arterial blood sampling. We observed increased [18F]NOS whole brain distribution volume (VT) in PD patients compared to age-matched healthy controls (p < 0.008) via a 1-tissue compartment (TC) model. The rate constant K1 for transport from blood into tissue did not differ between groups (p = 0.72). These findings suggest elevated oxidative stress, a surrogate marker of inflammation, is present in early-stage idiopathic PD and indicate that [18F]NOS PET imaging is a promising, non-invasive method to measure neuroinflammation.

Associations between alcohol consumption and gray and white matter volumes in the UK Biobank.

Heavy alcohol consumption has been associated with brain atrophy, neuronal loss, and poorer white matter fiber integrity. However, there is conflicting evidence on whether light-to-moderate alcohol consumption shows similar negative associations with brain structure. To address this, we examine the associations between alcohol intake and brain structure using multimodal imaging data from 36,678 generally healthy middle-aged and older adults from the UK Biobank, controlling for numerous potential confounds. Consistent with prior literature, we find negative associations between alcohol intake and brain macrostructure and microstructure. Specifically, alcohol intake is negatively associated with global brain volume measures, regional gray matter volumes, and white matter microstructure. Here, we show that the negative associations between alcohol intake and brain macrostructure and microstructure are already apparent in individuals consuming an average of only one to two daily alcohol units, and become stronger as alcohol intake increases.

Trauma exposure among cannabis use disorder individuals was associated with a craving-correlated non-habituating amygdala response to aversive cues.

The relationship of cannabis-use disorder and trauma exposure at the level of the brain is not well-understood. Cue-reactivity paradigms have largely focused on characterizing aberrant subcortical function by averaging across the entire task. However, changes across the task, including a non-habituating amygdala response (NHAR), may be a useful biomarker for relapse vulnerability and other pathology. This secondary analysis utilized existing fMRI data from a CUD population with (TR-Y, n = 18) or without trauma (TR-N, n = 15). Amygdala reactivity to novel and repeated aversive cues was examined between TR-Y vs. TR-N groups, using a repeated measures ANOVA. Analysis revealed a significant interaction between TR-Y vs. TR-N and amygdala response to novel vs. repeated cues in the amygdala (right: F (1,31) = 5.31, p = 0.028; left: F (1,31) = 7.42, p = 0.011). In the TR-Y group, a NHAR was evident, while the TR-N group exhibited amygdala habituation, resulting in a significant difference between groups of amygdala reactivity to repeated cues (right: p = 0.002; left: p < 0.001). The NHAR in the TR-Y (but not TR-N) group was significantly correlated with higher cannabis craving scores, yielding a significant group difference (z = 2.1, p = 0.018). Results suggest trauma interacts with the brain's sensitivity to aversive cues, offering a neural explanation for the relationship between trauma and CUD vulnerability. These findings suggest the importance of considering the temporal dynamics of cue reactivity and trauma history in future studies and treatment planning, as this distinction may help decrease relapse vulnerability.

Impact of the natural hormonal milieu on ventral striatal responses to appetitive cigarette smoking cues: A prospective longitudinal study.

Background: The female sex hormones estradiol (E) and progesterone (P) galvanize the ventral striatal reward pathway. E elevates ventral striatal dopamine and accelerates drug-cued reinstatement, while P has opposing 'protective' effects on drug-related behavior. We hypothesize that women may exhibit greater ventral striatal responses to smoking cues (SCs) during the late follicular phase of the menstrual cycle (MC) when E is high and unimpeded by P, and reduced responses during the late luteal phase when P is high. Methods: To test our hypothesis, 24 naturally cycling cigarette-dependent women completed functional magnetic resonance (fMRI) sessions over the course of 3 MCs at select time points to reflect the early follicular (low E and P; LEP, control condition), late follicular (high E, low P; HE) and mid-luteal (high E, high P; HEP) MC phases. During fMRI sessions (counterbalanced by phase), women were exposed to a SC versus nonSC audio-visual clip. Ovulation was verified for each MC, and hormone levels were acquired prior to sessions. Results: Contrasts within conditions showed that ventral striatal brain responses to SCs versus nonSCs were negligible during LEP and greater during HE (p=0.009) and HP (p=0.016). Contrasts across conditions showed that HE and HEP had greater responses than LEP (p=0.005), and HE had greater responses than HEP (p=0.049). Conclusions: Results support and extend our retrospective cross-sectional study of the influence of the hormonal milieu on SC reactivity. Results are clinically relevant as they may guide novel, hormonally-informed and immediately translatable treatment strategies that can potentially reduce relapse in naturally cycling women.

Exploration of the influence of body mass index on intra-network resting-state connectivity in chronic cigarette smokers.

BACKGROUND: Obesity and cigarette smoking are two leading preventable causes of death. Previous research suggests that comorbid smoking and obesity likely share neurobehavioral underpinnings; however, the influence of body mass index (BMI) on resting-state functional connectivity (rsFC) in smokers remains unknown. In this study, we explore how BMI affects rsFC and associations between rsFC and smoking-related behavior. METHODS: Treatment-seeking cigarette smokers (N = 87; 54 % men) completed a BOLD resting-state fMRI scan session. We grouped smokers into BMI groups (N = 23 with obesity, N = 33 with overweight, N = 31 lean) and used independent components analysis (ICA) to identify the resting state networks commonly associated with cigarette smoking: salience network (SN), right and left executive control networks (ECN) and default mode network (DMN). Average rsFC values were extracted (p < 0.001, k = 100) to determine group differences in rsFC and relationship to self-reported smoking and dependence. RESULTS: Analyses revealed a significant relationship between BMI and connectivity in the SN and a significant quadratic effect of BMI on DMN connectivity. Heavier smoking was related to greater rsFC in the SN among lean and obese groups but reduced rsFC in the overweight group. CONCLUSIONS: Findings build on research suggesting an influence of BMI on the neurobiology of smokers. In particular, dysfunction of SN-DMN-ECN circuitry in smokers with overweight may lead to a failure to modulate attention and behavior and subsequent difficulty quitting smoking. Future research is needed to elucidate the mechanism underlying the interaction of BMI and smoking and its impact on treatment.

Influence of the natural hormonal milieu on brain and behavior in women who smoke cigarettes: Rationale and methodology.

Women experience more severe health consequences from smoking, have greater difficulty quitting, and respond less favorably to nicotine replacement therapy than men. The influence of fluctuating ovarian hormones, specifically estradiol (E) and progesterone (P), on brain and behavioral responses during exposure to smoking reminders (i.e., cues) may be a contributing factor. Results from our laboratory suggest that women in the late follicular phase of their menstrual cycle (MC) have enhanced smoking cue (SC) vulnerabilities and reduced functional connectivity in neurocircuitry underlying cognitive control, potentially placing them at greater risk for continued smoking and relapse. The primary aim of this study is to examine and link hormonal status with brain and behavioral responses to SCs over the course of three monthly MCs in naturally cycling women who are chronic cigarette smokers. This longitudinal, counterbalanced study collects brain and behavioral responses to SCs at three time points during a woman's MC. Participants complete psychological and physical examinations, biochemical hormonal verification visits, and at least three laboratory/neuroimaging scan visits. The scan visits include a 10-min SC task during blood oxygen level-dependent (BOLD) data acquisition and are timed to occur during the early follicular phase (low E and P), late follicular phase (high E, unopposed by P), and mid-luteal phase (high P, high E). The primary outcomes include brain responses to SCs (compared to non-SCs), subjective craving, E and P hormone levels, and behavioral responses to SCs. This study addresses a critical gap in our knowledge: namely, the impact of the natural hormonal milieu on brain and behavioral responses to SCs, a powerful relapse trigger. Additionally, this study will provide a roadmap for human sex differences researchers who are obliged to consider the often confounding cyclic hormonal fluctuations of women.

Sustained brain response to repeated drug cues is associated with poor drug-use outcomes.

A threefold increase in fatal cocaine overdoses during the past decade highlights the critical lack of medications for cocaine use disorders. The brain response to drug cues can predict future drug use; however, results have been mixed. We present preliminary evidence that a sustained response to repeated cocaine cues within a single task is a significant predictor of drug-use outcomes. Seventy-three cocaine inpatients were administered a passive-viewing fMRI task, featuring 500 ms novel evocative (cocaine, sexual, aversive) and neutral comparator cues in the first half (Half1), which were then repeated in the second half (Half2). After the baseline scan, patients received eight outpatient treatment weeks with twice-weekly drug screens. Drug-use outcome groups were empirically defined based on cocaine-positive or missing urines averaged across the outpatient phase: GOOD (<40%), POOR (>85%), and Intermediate (INT, between 40% and 85%) outcomes. Differences of response to initial (Half1) and repeated (Half2) cues in a priori (cue-reactive) regions were tested between outcome groups (3 [Group] × 2 [Halves] ANOVA). An interaction was found in the brain response to drug (but not sex or aversive) cues, with a significant difference between the GOOD and POOR outcome groups in Half2, driven by a significant decrease in brain response by the GOOD outcome group and a sustained brain response by the POOR outcome group, to repeated cocaine cues. The brain response to repeated drug cues may be a useful predictor of future drug use, encouraging future intervention studies to restore a "healthy" (decreasing) response to the repeated presentation of drug cues.

Smoking-induced craving relief relates to increased DLPFC-striatal coupling in nicotine-dependent women.

BACKGROUND: Craving is a major contributor to drug-seeking and relapse. Although the ventral striatum (VS) is a primary neural correlate of craving, strategies aimed at manipulating VS function have not resulted in efficacious treatments. This incongruity may be because the VS does not influence craving in isolation. Instead, craving is likely mediated by communication between the VS and other neural substrates. Thus, we examined how striatal functional connectivity (FC) with key nodes of networks involved in addiction affects relief of craving, which is an important step in identifying viable treatment targets. METHODS: Twenty-four nicotine-dependent non-abstinent women completed two resting-state (rs) fMRI scans, one before and one following smoking a cigarette in the scanner, and provided craving ratings before and after smoking the cigarette. A seed-based approach was used to examine rsFC between the VS, putamen and germane craving-related brain regions; the dorsolateral prefrontal cortex (dlPFC), the posterior cingulate cortex, and the anterior ventral insula. RESULTS: Smoking a cigarette was associated with a decrease in craving. Relief of craving correlated with increases in right dlPFC- bilateral VS (r = 0.57, p = 0.003, corrected) as did increased right dlPFC-left putamen coupling (r = 0.62, p = 0.001, corrected). CONCLUSIONS: Smoking-induced relief of craving is associated with enhanced rsFC between the dlPFC, a region that plays a pivotal role in decision making, and the striatum, the neural structure underlying motivated behavior. These findings are highly consistent with a burgeoning literature implicating dlPFC-striatal interactions as a neurobiological substrate of craving.

Effects of topiramate on neural responses to alcohol cues in treatment-seeking individuals with alcohol use disorder: preliminary findings from a randomized, placebo-controlled trial.

Topiramate, a GABA/glutamate modulator, is efficacious in reducing alcohol consumption, though the mechanisms underlying this effect are not well characterized. This study analyzed functional magnetic resonance imaging (fMRI) data from 22 heavy drinkers enrolled in a 12-week placebo-controlled, randomized clinical trial of topiramate to examine the effects of topiramate on alcohol cue-elicited brain responses, craving, and heavy drinking in individuals with DSM-5 alcohol use disorder. Patients were randomized to receive either topiramate (maximal daily dosage of 200 mg/day) or placebo and were administered an fMRI alcohol cue-reactivity task at baseline (before starting medication) and after 6 weeks of double-blind treatment. Analyses compared the topiramate (n = 12) and placebo (n = 8) groups on (1) the change in brain responses during alcohol cue exposure (vs non-alcohol cues) within five a priori regions of interest related to reward-the bilateral and medial orbitofrontal cortex (OFC) and bilateral ventral striatum (VS) and (2) change in craving and heavy drinking days (HDDs) from baseline and scan 2. Topiramate, relative to placebo, reduced alcohol cue-elicited activation of the left VS, bilateral OFC, and medial OFC, alcohol cue-elicited craving, and HDDs between baseline and 6 weeks of treatment. The reduction in alcohol cue-elicited activation in the medial OFC correlated with reductions in craving, and reduced activation in the right VS, right OFC, and medial OFC correlated with the reduction in HDD. This preliminary study provides evidence that topiramate's attenuation of alcohol cue-elicited brain activation and craving are key elements of the drug's neurobiological mechanism of action in reducing heavy drinking.

Genetic underpinnings of risky behaviour relate to altered neuroanatomy.

Previous research points to the heritability of risk-taking behaviour. However, evidence on how genetic dispositions are translated into risky behaviour is scarce. Here, we report a genetically informed neuroimaging study of real-world risky behaviour across the domains of drinking, smoking, driving and sexual behaviour in a European sample from the UK Biobank (N = 12,675). We find negative associations between risky behaviour and grey-matter volume in distinct brain regions, including amygdala, ventral striatum, hypothalamus and dorsolateral prefrontal cortex (dlPFC). These effects are replicated in an independent sample recruited from the same population (N = 13,004). Polygenic risk scores for risky behaviour, derived from a genome-wide association study in an independent sample (N = 297,025), are inversely associated with grey-matter volume in dlPFC, putamen and hypothalamus. This relation mediates roughly 2.2% of the association between genes and behaviour. Our results highlight distinct heritable neuroanatomical features as manifestations of the genetic propensity for risk taking.

An exploration of associations between smoking motives and behavior as a function of body mass index.

Objective: Cigarette smoking and obesity are the leading causes of premature morbidity and mortality and increase the risk of all-cause mortality four-fold when comorbid. Although research suggests that smoking motives may differ based on body mass index (BMI), it is unclear how these differences translate to smoking behavior. Method: Three groups of adults who smoke cigarettes (N = 79; obese n = 25, overweight n = 30, and lean n = 24) completed measures of smoking and the Smoking Motivations Questionnaire. Groups did not differ on age, education, cigarettes per day (CPD), pack-years, or nicotine dependence, as measured by the Fagerström Test for Cigarette Dependence (FTCD). Results: Analyses revealed different associations between reasons for smoking and smoking behavior depending on lean, overweight, or obesity status. Participants (N = 37 female, average age 39.8 years) self-reported smoking was positively associated with Addictive, and Automatic subscale scores among lean participants, with only the Addictive subscale score among those with overweight, and only the Automatic subscale score among those with obesity. Post hoc MANCOVA analysis revealed a significant interaction effect of Group x Automatic Smoking on Pack-years (F(2, 79)=3.34, p = 0.04). Conclusion: Findings suggest smoking motives are differentially associated with smoking behavior in adults who smoke depending on weight status. The daily smoking rate of participants with obesity may be less related to the addictive quality of smoking, and automaticity may be less associated with smoking history in those with overweight. Additional research on the influence of BMI on cigarette smoking is necessary to fully elucidate how obesity may impact treatment outcomes to optimize smoking cessation treatment among those with excess body weight.

Double jeopardy: Comorbid obesity and cigarette smoking are linked to neurobiological alterations in inhibitory control during smoking cue exposure.

Obesity and cigarette smoking are two of the leading preventable causes of death in the United States. Research suggests that overlapping pathophysiology may contribute to obesity and nicotine use disorder (NUD), yet no studies have investigated the effect of obesity on neural response to reward stimuli in NUD. This study used arterial spin-labeled perfusion functional magnetic resonance imaging (fMRI) to examine neural responses during exposure to smoking versus nonsmoking cues in 79 treatment-seeking participants with NUD, 26 with normal weight, 28 with overweight, and 25 with obesity. Given that deficits in behavioral inhibitory control have been associated with both obesity and NUD, participants completed an affect-congruent Go/NoGo task to assess the effect of body mass index (BMI) on this construct in NUD. Analyses revealed that BMI was negatively associated with activation in the right dorsolateral prefrontal cortex (dlPFC) in response to smoking cues, with significantly reduced response in smokers with overweight and smokers with obesity compared with normal-weight smokers. In addition, greater commission errors on the Go/NoGo task were correlated with reduced neural response to smoking cues in the right dlPFC only among those with obesity. Together, these findings provide evidence that obesity in treatment-seeking NUDs is related to neurobiological alterations in inhibitory control over cue-potentiated behaviors, suggesting that smoking cessation may be more difficult in individuals with comorbid NUD and obesity than in those without, requiring treatment strategies tailored to meet their unique needs.

Menstrual cycle phase modulates responses to smoking cues in the putamen: Preliminary evidence for a novel target.

BACKGROUND: The preclinical literature identifies the ventral striatum (VS) as a key player in drug-conditioned responses, guiding hypotheses examining neural substrates involved in human drug cue reactivity, including the study of sex differences. Men show a replicable response that includes the VS, while women's responses have been weaker and variable. New evidence suggests that the hormonal milieu modulates women's responses to drug cues in the dorsal striatum (DS), specifically, in the putamen. Here we tested the hypothesis that the hormonal milieu affects neural responses to smoking cues (SCs) in the putamen in women cigarette smokers. METHODS: We re-examined our three previous neuroimaging studies of the influence of sex and menstrual cycle (MC) phase effects on SC neuroactivity, incorporating the DS as a region of interest. RESULTS: As previously shown, men exhibited increased ventral medial prefrontal cortex (vmPFC) and VS/V pallidum responses, and women showed increased vmPFC responses that were greater in women during the follicular phase (high estradiol), compared to the luteal phase (high progesterone). Reducing the statistical threshold within luteal phase women revealed select deactivation of the putamen. CONCLUSIONS: These preliminary findings shed light upon factors that may modulate drug cue reactivity in women, specifically the influence of hormones on DS responses. Emerging literature suggests that manipulating the hormonal milieu may open a fundamental window into sex-specific treatment targets. More rigorous study of the brain substrates involved in drug cue reactivity and other reward-related behavior that may be influenced by sex and the hormonal milieu is imperative.

Oral Contraceptives and Cigarette Smoking: A Review of the Literature and Future Directions.

INTRODUCTION: Evidence continues to mount indicating that endogenous sex hormones (eg, progesterone and estradiol) play a significant role in smoking-related outcomes. Although approximately one out of four premenopausal smokers use oral contraceptives (OCs), which significantly alter progesterone and estradiol levels, relatively little is known about how OCs may influence smoking-related outcomes. Thus, the goal of this review article is to describe the state of the literature and offer recommendations for future directions. METHODS: In March 2017, we searched seven databases, with a restriction to articles written in English, using the following keywords: nicotine, smoker(s), smoking, tobacco, cigarettes, abstinence, withdrawal, and craving(s). We did not restrict on the publication date, type, or study design. RESULTS: A total of 13 studies were identified. Three studies indicated faster nicotine metabolism in OC users compared to nonusers. Five of six laboratory studies that examined physiological stress response noted heightened response in OC users compared to nonusers. Three studies examined cessation-related symptomatology (eg, craving) with mixed results. One cross-sectional study observed greater odds of current smoking among OC users, and no studies have explored the relationship between OC use and cessation outcomes. CONCLUSIONS: Relatively few studies were identified on the role of OCs in smoking-related outcomes. Future work could explore the relationship between OC use and mood, stress, weight gain, and brain function/connectivity, as well as cessation outcomes. Understanding the role of OC use in these areas may lead to the development of novel smoking cessation interventions for premenopausal women. IMPLICATIONS: This is the first review of the relationship between oral contraceptives (OCs) and smoking-related outcomes. The existing literature suggests that the use of OCs is related to increased nicotine metabolism and physiological stress response. However, the relationship between OC use and smoking-related symptoms (eg, craving) is mixed. Further, no published data were available on OC use and smoking cessation outcomes. Therefore, we recommend additional research be conducted to characterize the relationship between OC use and smoking cessation outcomes, perhaps as a function of the effect of OC use on mood, stress, weight gain, and brain function/connectivity.

Classifying and characterizing nicotine use disorder with high accuracy using machine learning and resting-state fMRI.

Cigarette smoking continues to be a leading cause of preventable morbidity and mortality. Although the majority of smokers report making a quit attempt in the past year, smoking cessation rates remain modest. Thus, developing accurate, data-driven methods that can classify and characterize the neural features of nicotine use disorder (NUD) would be a powerful clinical tool that could aid in optimizing treatment development and guide treatment modifications. This investigation applied support vector machine-based classification to resting-state functional connectivity (rsFC) data from individuals diagnosed with NUD (n = 108; 63 male) and matched nonsmoking controls (n = 108; 63 male) and multi-dimensional scaling to visualize the heterogeneity of NUD in individual smokers based on rsFC measures. Machine-based learning models identified five resting-state networks that played a role in distinguishing smokers from controls: the posterior and anterior default mode networks, the sensorimotor network, the salience network and the right executive control network. The classification method constructed classifiers with an average correct classification rate of 88.1 percent and an average area under the curve of 0.93. Compared with controls, individuals with NUD had weaker functional connectivity measures within these networks (P < 0.05, false discovery rate corrected). Further, multi-dimensional scaling visualization demonstrated that controls were similar to each other whereas individuals with NUD had less similarity to controls and to other individuals with NUD. Our findings build upon previous literature demonstrating that machine learning-based approaches to classifying rsFC data offer a valuable technique to understanding network-level differences in nicotine-related neurobiology and extend previous findings by improving classification accuracy and demonstrating the heterogeneity in resting-state networks of individuals with NUD.