Publications

BACKGROUND AND AIMS: Cognitive control and reward-related abnormalities are centrally implicated in addiction. However, findings from longitudinal studies addressing neurocognitive predictors of addictive behaviors are mixed. Further, little work has been conducted predicting non-substance-related addictive behaviors. Our study aimed to assess predictors of substance and non-substance addictive behaviors in a community sample, systematically evaluating each neurocognitive function's independent influence on addictive behavior.

METHODS: Australians (N = 294; 51.7% female; M[SD] age = 24.8[4.7] years) completed online neurocognitive tasks and surveys at baseline and 3-month follow-up. Self-report scales assessed problematic alcohol use, addictive eating (AE), problematic pornography use (PPU), and problematic internet use (PUI) at 3- and 6-month follow-ups. Linear regressions with bootstrapping assessed neurocognitive predictors for each addictive behavior across a 6-month period.

RESULTS: Neurocognition at baseline did not predict AE or PUI severity at 6-month follow-up. Less delay discounting at baseline predicted higher PPU at 6-month follow-up (β = -0.16, p = 0.005). Poorer performance monitoring at baseline predicted higher AE at 3-month follow-up (β = -0.16, p = 0.004), and more reward-related attentional capture at 3-months predicted higher AE at 6-month follow-up (β = 0.14, p = 0.033). Less reward-related attentional capture (β = -0.14, p = 0.003) and less risk-taking under ambiguity (β = -0.11, p = 0.029) at baseline predicted higher PUI at 3-month follow-up. All findings were of small effect size. None of the neurocognitive variables predicted problematic alcohol use.

DISCUSSION AND CONCLUSIONS: We were unable to identify a core set of specific neurocognitive functions that reliably predict multiple addictive behavior types. However, our findings indicate both cognitive control and reward-related functions predict non-substance addictive behaviors in different ways. Findings suggest that there may be partially distinct neurocognitive mechanisms contributing to addiction depending on the specific addictive behavior.

The behaviors that characterize sleep have been observed across a broad range of different species. While much attention has been placed on vertebrates (mostly mammals and birds), the grand diversity of invertebrates has gone largely unexplored. Here, we introduce the intrigue and special value in the study of sleeping platyhelminth flatworms. Flatworms are closely related to annelids and mollusks, and yet are comparatively simple. They lack a circulatory system, respiratory system, endocrine glands, a coelom, and an anus. They retain a central and peripheral nervous system, various sensory systems, and an ability to learn. Flatworms sleep, like other animals, a state which is regulated by prior sleep/wake history and by the neurotransmitter GABA. Furthermore, they possess a remarkable ability to regenerate from a mere fragment of the original animal. The regenerative capabilities of flatworms make them a unique bilaterally symmetric animal to study a link between sleep and neurodevelopment. Lastly, the recent applications of tools for probing the flatworm genome, metabolism, and brain activity make their entrance into the field of sleep research all the more timely.

Flatworms are among the best studied animal models for regeneration; however, they also represent an emerging opportunity to investigate other biological processes as well. For instance, flatworms are nocturnal and sleep during the day, a state that is regulated by sleep/wake history and the action of the sleep-promoting neurotransmitter gamma-aminobutyric acid (or GABA). Sleep is widespread across the animal kingdom, where it serves many nonexclusive functions. Notably, sleep saves energy by reducing metabolic rate and by not doing something more energetically taxing. Whether the conservation of energy is apparent in sleeping flatworms is unclear. We measured the oxygen consumption rate (OCR) of flatworms dosed with either (1) GABA (n = 29) which makes flatworms inactive or (2) dopamine (n = 20) which stimulates flatworms to move, or (3) day and night neurotransmitter-free controls (n = 28 and 27, respectively). While OCR did not differ between the day and night, flatworms treated with GABA used less oxygen than those treated with dopamine, and less than the day-time control. Thus, GABA affected flatworm physiology, ostensibly by enforcing energy-conserving sleep. Evidence that dopamine increased metabolism was less strong. This work broadens our understanding of flatworm physiology and expands the phylogenetic applicability of energy conservation as a function of sleep.

OBJECTIVE: Distinguishing arginine vasopressin deficiency (AVP-D; central diabetes insipidus) from primary polydipsia (PP), commonly referred to as psychogenic polydipsia, is challenging. Psychopathologic findings, commonly used for PP diagnosis in clinical practice, are rarely evaluated in AVP-D patients, and no comparative data between the two conditions currently exist.

DESIGN: Data from two studies involving 82 participants [39 AVP-D, 28 PP, and 15 healthy controls (HC)].

METHODS: Psychological evaluations were conducted using standardized questionnaires measuring anxiety [State-Trait Anxiety Inventory (STAI)], alexithymia [Toronto Alexithymia Scale (TAS-20)], depressive symptoms (Beck's Depression Inventory-II (BDI-II), and overall mental health [Short Form-36 Health Survey (SF-36)]. Higher STAI, TAS-20, and BDI-II scores suggest elevated anxiety, alexithymia, and depression, while higher SF-36 scores signify better overall mental health.

RESULTS: Compared to HC, patients with AVP-D and PP showed higher levels of anxiety (HC 28 points [24-31] vs AVP-D 36 points [31-45]; vs PP 38 points [33-46], P < .01), alexithymia (HC 30 points [29-37] vs AVP-D 43 points [35-54]; vs PP 46 points [37-55], P < .01), and depression (HC 1 point [0-2] vs AVP-D 7 points [4-14]; vs PP 7 points [3-13], P < .01). Levels of anxiety, alexithymia, and depression showed no difference between both patient groups (P = .58, P = .90, P = .50, respectively). Compared to HC, patients with AVP-D and PP reported similarly reduced self-reported overall mental health scores (HC 84 [68-88] vs AVP-D 60 [52-80], P = .05; vs PP 60 [47-74], P < .01).

CONCLUSION: This study reveals heightened anxiety, alexithymia, depression, and diminished overall mental health in patients with AVP-D and PP. The results emphasize the need for careful interpretation of psychopathological characteristics to differentiate between AVP-D and PP.

The potential risk for mental health conditions over the menopause transition shapes women's expectations and informs putative physiological mechanisms regulating women's mental health. We review evidence from prospective studies reporting on associations between mental health conditions and the menopause transition. Major depressive disorder and the more prevalent subthreshold depressive symptoms are the most common conditions studied. We reviewed 12 prospective studies reporting depressive symptoms, major depressive disorder, or both over the menopause transition and found no compelling evidence for a universal increased risk for either condition. However, specific subgroups of participants, primarily defined by menopause-related risk factors (ie, vasomotor symptoms that are severe or disturb sleep, a long duration of the transition, or reproductive hormone dynamics) and psychosocial risk factors (eg, stressful life events), were vulnerable to depressive symptoms. The increased risk of major depressive disorder over the menopause transition appears predominantly in individuals with previous major depressive disorder. Greater focus on recognising risk factors in primary care is warranted. On the basis of scarce data, we found no compelling evidence that risk of anxiety, bipolar disorder, or psychosis is universally elevated over the menopause transition. Potential misattribution of psychological distress and psychiatric disorders to menopause could harm women by delaying accurate diagnosis and the initiation of effective psychotropic treatments, and by creating negative expectations for people approaching menopause. A paradigm shift is needed. We conclude with recommendations for the detection and treatment of depressive symptoms or major depressive disorder and strategies to promote good mental health over the menopause transition, while responsibly preparing and supporting those at risk.

IMPORTANCE: Safe and effective nonhormonal treatments for menopausal vasomotor symptoms (VMS) are needed.

OBJECTIVE: To evaluate the efficacy and safety of elinzanetant, a selective neurokinin-1,3 receptor antagonist, for the treatment of moderate to severe menopausal vasomotor symptoms.

DESIGN, SETTING, AND PARTICIPANTS: Two randomized double-blind phase 3 trials (OASIS 1 and 2) included postmenopausal participants aged 40 to 65 years experiencing moderate to severe vasomotor symptoms (OASIS 1: 77 sites in the US, Europe, and Israel from August 27, 2021, to November 27, 2023, and OASIS 2: 77 sites in the US, Canada, and Europe from October 29, 2021, to October 10, 2023).

INTERVENTION: Once daily oral elinzanetant, 120 mg, for 26 weeks or matching placebo for 12 weeks followed by elinzanetant, 120 mg, for 14 weeks.

MAIN OUTCOMES AND MEASURES: Primary end points included mean change in frequency and severity of moderate to severe vasomotor symptoms from baseline to weeks 4 and 12, measured by the electronic hot flash daily diary. Secondary end points included Patient-Reported Outcomes Measurement Information System Sleep Disturbance Short Form 8b total T score and Menopause-Specific Quality of Life questionnaire total score from baseline to week 12.

RESULTS: Eligible participants (mean [SD] age, OASIS 1: 54.6 [4.9] years; OASIS 2: 54.6 [4.8] years) were randomized to elinzanetant (OASIS 1: n = 199; OASIS 2: n = 200) or placebo (OASIS 1: n = 197; OASIS 2: n = 200). A total of 309 (78.0%) and 324 (81.0%) completed OASIS 1 and 2, respectively. For the elinzanetant and placebo groups, the baseline mean (SD) VMS per 24 hours were 13.4 (6.6) vs 14.3 (13.9) (OASIS 1) and 14.7 (11.1) v 16.2 (11.2) (OASIS 2). Baseline VMS severity was 2.6 (0.2) vs 2.5 (0.2) (OASIS 1) and 2.5 (0.2) vs 2.5 (0.2) (OASIS 2). Elinzanetant significantly reduced VMS frequency at week 4 (OASIS 1: -3.3 [95% CI, -4.5 to -2.1], P < .001; OASIS 2: -3.0 [95% CI, -4.4 to -1.7], P < .001) and at week 12 (OASIS 1: -3.2 [95% CI, -4.8 to -1.6], P < .001; OASIS 2: -3.2 [95% CI, -4.6 to -1.9], P < .001). Elinzanetant also improved VMS severity at week 4 (OASIS 1: -0.3 [95% CI, -0.4 to -0.2], P < .001; OASIS 2: -0.2 [95 CI, -0.3 to -0.1], P < .001) and week 12 (OASIS 1: -0.4 [95% CI, -0.5 to -0.3], P < .001; OASIS 2: -0.3 [95% CI, -0.4 to -0.1], P < .001). Elinzanetant improved sleep disturbances and menopause-related quality of life at week 12, and the safety profile was favorable.

CONCLUSIONS AND RELEVANCE: Elinzanetant was well tolerated and efficacious for moderate to severe menopausal VMS.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: OASIS 1: NCT05042362, OASIS 2: NCT05099159.

IMPORTANCE: Safe and effective nonhormonal treatments for menopausal vasomotor symptoms (VMS) are needed.

OBJECTIVE: To evaluate the efficacy and safety of elinzanetant, a selective neurokinin-1,3 receptor antagonist, for the treatment of moderate to severe menopausal vasomotor symptoms.

DESIGN, SETTING, AND PARTICIPANTS: Two randomized double-blind phase 3 trials (OASIS 1 and 2) included postmenopausal participants aged 40 to 65 years experiencing moderate to severe vasomotor symptoms (OASIS 1: 77 sites in the US, Europe, and Israel from August 27, 2021, to November 27, 2023, and OASIS 2: 77 sites in the US, Canada, and Europe from October 29, 2021, to October 10, 2023).

INTERVENTION: Once daily oral elinzanetant, 120 mg, for 26 weeks or matching placebo for 12 weeks followed by elinzanetant, 120 mg, for 14 weeks.

MAIN OUTCOMES AND MEASURES: Primary end points included mean change in frequency and severity of moderate to severe vasomotor symptoms from baseline to weeks 4 and 12, measured by the electronic hot flash daily diary. Secondary end points included Patient-Reported Outcomes Measurement Information System Sleep Disturbance Short Form 8b total T score and Menopause-Specific Quality of Life questionnaire total score from baseline to week 12.

RESULTS: Eligible participants (mean [SD] age, OASIS 1: 54.6 [4.9] years; OASIS 2: 54.6 [4.8] years) were randomized to elinzanetant (OASIS 1: n = 199; OASIS 2: n = 200) or placebo (OASIS 1: n = 197; OASIS 2: n = 200). A total of 309 (78.0%) and 324 (81.0%) completed OASIS 1 and 2, respectively. For the elinzanetant and placebo groups, the baseline mean (SD) VMS per 24 hours were 13.4 (6.6) vs 14.3 (13.9) (OASIS 1) and 14.7 (11.1) v 16.2 (11.2) (OASIS 2). Baseline VMS severity was 2.6 (0.2) vs 2.5 (0.2) (OASIS 1) and 2.5 (0.2) vs 2.5 (0.2) (OASIS 2). Elinzanetant significantly reduced VMS frequency at week 4 (OASIS 1: -3.3 [95% CI, -4.5 to -2.1], P < .001; OASIS 2: -3.0 [95% CI, -4.4 to -1.7], P < .001) and at week 12 (OASIS 1: -3.2 [95% CI, -4.8 to -1.6], P < .001; OASIS 2: -3.2 [95% CI, -4.6 to -1.9], P < .001). Elinzanetant also improved VMS severity at week 4 (OASIS 1: -0.3 [95% CI, -0.4 to -0.2], P < .001; OASIS 2: -0.2 [95 CI, -0.3 to -0.1], P < .001) and week 12 (OASIS 1: -0.4 [95% CI, -0.5 to -0.3], P < .001; OASIS 2: -0.3 [95% CI, -0.4 to -0.1], P < .001). Elinzanetant improved sleep disturbances and menopause-related quality of life at week 12, and the safety profile was favorable.

CONCLUSIONS AND RELEVANCE: Elinzanetant was well tolerated and efficacious for moderate to severe menopausal VMS.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: OASIS 1: NCT05042362, OASIS 2: NCT05099159.

OBJECTIVE: To examine effects of menstrual phase and nighttime light exposure on subjective sleepiness and auditory Psychomotor Vigilance Task performance.

METHODS: Twenty-nine premenopausal women (12 =Follicular; 17 =Luteal) completed a 6.5-hour nighttime monochromatic light exposure with varying wavelengths (420-620 nm) and irradiances (1.03-14.12 µW/cm2). Subjective sleepiness, reaction time, and attentional lapses were compared between menstrual phases in women with minimal (<33%) or substantial (≥33%) light-induced melatonin suppression.

RESULTS: When melatonin was not suppressed, women in the follicular phase had significantly worse reaction time (mean difference=145.1 ms, 95% CI 51.8-238.3, p < .001, Cohen's D=1.9) and lapses (mean difference=12.9 lapses, 95% CI 4.37-21.41, p < .001, Cohen's D=1.7) compared to women in the luteal phase. When melatonin was suppressed, women in the follicular phase had significantly better reaction time (mean difference=152.1 ms, 95% CI 43.88-260.3, p < .001, Cohen's D=1.7) and lapses (mean difference=12.3 lapses, 95% CI 1.14-25.6, p < .01, Cohen's D=1.6) compared to when melatonin was not suppressed, such that their performance was not different (p > .9) from women in the luteal phase. Subjective sleepiness did not differ by menstrual phase (mean difference=0.6, p > .08) or melatonin suppression (mean difference=0.2, p > .4).

CONCLUSIONS: Nighttime light exposure sufficient to suppress melatonin can also mitigate neurobehavioral performance deficits associated with the follicular phase. Despite the relatively small sample size, these data suggest that nighttime light may be a valuable strategy to help reduce errors and accidents in female shift workers.

OBJECTIVES: Mathematical models of human neurobehavioral performance that include the effects of acute and chronic sleep restriction can be key tools in assessment and comparison of work schedules, allowing quantitative predictions of performance when empirical assessment is impractical.

METHODS: Using such a model, we tested the hypothesis that resident physicians working an extended duration work roster, including 24-28 hours of continuous duty and up to 88 hours per week averaged over 4weeks, would have worse predicted performance than resident physicians working a rapidly cycling work roster intervention designed to reduce the duration of extended shifts. The performance metric used was attentional failures (ie, Psychomotor Vigilance Task lapses). Model input was 169 actual work and sleep schedules. Outcomes were predicted hours per week during work hours spent at moderate (equivalent to 16-20 hours of continuous wakefulness) or high (equivalent to ≥20 hours of continuous wakefulness) performance impairment.

RESULTS: The model predicted that resident physicians working an extended duration work roster would spend significantly more time at moderate impairment (p = .02, effect size=0.2) than those working a rapidly cycling work roster; this difference was most pronounced during the circadian night (p < .001). On both schedules, performance was predicted to decline from weeks 1 + 2 to weeks 3 + 4 (p < .001), but the rate of decline was significantly greater on extended duration work roster (p < .01). Predicted performance impairment was inversely related to prior sleep duration (p < .001).

CONCLUSIONS: These findings demonstrate the utility of a mathematical model to evaluate the predicted performance profile of schedules for resident physicians and others who experience chronic sleep restriction and circadian misalignment.

OBJECTIVES: The Pathways to Wellness randomized controlled trial found that 2 behavioral interventions, mindfulness awareness practices and survivorship education, reduced depressive symptoms in younger breast cancer survivors (BCSs) compared with wait-list control. This secondary analysis examines whether the interventions led to reduced loss of work productivity among younger BCSs and whether such reductions were mediated by reductions in depressive symptoms.

METHODS: The Work Productivity and Activity Impairment scale was used to measure work productivity loss at 4 assessment time points. Correlates of productivity loss at enrollment were examined using multivariable linear regression. Differences in change over time in productivity loss between each intervention group and control were assessed using linear mixed models. Reduced depressive symptoms were tested as a mediator of reduced productivity loss.

RESULTS: Of 247 trial participants, 199 were employed and included in the analyses. At enrollment, higher productivity loss was associated with chemotherapy receipt (P = .003), younger age (P = .021), more severe cognitive problems (P = .002), higher musculoskeletal pain severity (P = .002), more depressive symptoms (P = .016), and higher fatigue severity (P = .033). The mindfulness intervention led to significantly less productivity loss compared with control at all 3 postintervention assessment points (all P < .05), with about 54% of the effect mediated by reduction in depressive symptoms. Survivorship education was not associated with reduced loss of productivity.

CONCLUSIONS: These findings suggest that addressing depressive symptoms through behavioral interventions, such as mindfulness, may mitigate impacts on work productivity in younger BCSs.