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An accumulating body of evidence indicates that peripheral physiological rhythms help regulate and organize large-scale brain activity. Given that schizophrenia (SZ) is characterized by marked abnormalities in oscillatory cortical activity as well as changes in autonomic function, the present study aimed to identify mechanisms by which central and autonomic nervous system deficits may be related. We evaluated phase-amplitude coupling (PAC) as a physiological mechanism through which autonomic nervous system (ANS) and central nervous system (CNS) activity are integrated and that may be disrupted in SZ.
PAC was measured between high-frequency heart rate variability (HF-HRV) as an index of parasympathetic activity and electroencephalography (EEG) oscillations in 36 individuals with first-episode SZ and 38 healthy comparison participants at rest.
HRV-EEG coupling was lower in SZ in the alpha and theta bands, and HRV-EEG coupling uniquely predicted group membership, whereas HRV and EEG power alone did not. HRV-EEG coupling in the alpha band correlated with measures of sustained attention in SZ. Granger causality analyses indicated a stronger heart-to-brain effect than brain-to-heart effect, consistent across groups.
Lower HRV-EEG coupling provides evidence of deficient autonomic regulation of cortical activity in SZ, suggesting that patterns of dysconnectivity observed in brain networks extend to brain–body interactions. Deficient ANS–CNS integration in SZ may foster a breakdown in the spatiotemporal organization of cortical activity, which may contribute to core cognitive impairments in SZ such as dysregulated attention. These findings encourage pursuit of therapies targeting autonomic function for the treatment of SZ.
Little is known about the dose and pattern of moderate-to-vigorous physical activity (MVPA) to prevent depression. We aimed to assess the prospective association of dose and pattern of accelerometer-derived MVPA with the risk of diagnosed depression.
We included 74,715 adults aged 40–69 years from the UK Biobank cohort who were free of severe disease at baseline and participated in accelerometer measurements (mean age 55.2 years [SD 7.8]; 58% women). MVPA at baseline was derived through 1-week wrist-worn accelerometry. Diagnosed depression was defined by hospitalization with ICD-10 codes F32.0-F32.A. Restricted cubic splines and Cox regression determined the prospective association of dose and pattern of MVPA with the risk of incident depression.
Over a median 7.9-year follow-up, there were 3,089 (4.1%) incident cases of depression. Higher doses of MVPA were curvilinearly associated with lower depression risk, with the largest minute-per-minute added benefits occurring between 5 (HR 0.99 [95% CI 0.96–0.99]) and 280 (HR 0.67 [95% CI 0.60–0.74]) minutes per week (reference: 0 MVPA minutes).
Regardless of pattern, higher doses of MVPA were associated with lower depression risk in a curvilinear manner, with the greatest incremental benefit per minute occurring during the first 4–5 h per week. Optimal benefits occurred around 15 h/week.
Early pubertal timing is associated with depressive symptoms in girls, but studies in boys are limited and have yielded conflicting results.
N = 4,664 male participants from a UK birth cohort (Avon Longitudinal Study of Parents and Children – ALSPAC). Seven indicators of pubertal timing were measured repeatedly from 7 to 17 years (age at: peak height velocity, peak weight velocity, peak bone mineral content velocity, Tanner stage 3 pubic hair, Tanner stage 3 genitalia, axillary hair, and voice break), categorised into ‘early’, ‘on-time,’ and ‘late’ (mean ± 1 SD). Depressive symptoms (binary variable indicating higher versus lower levels) were assessed at 14 and 18 years, and depression (ICD-10 diagnosis) was assessed at 18 years. Multivariable logistic regression was used to examine associations between each indicator of pubertal timing and depressive symptoms/depression, adjusted for socioeconomic status (SES) and prepubertal body mass index (BMI).
Compared to males with normative pubertal development, the odds of depression at age 18 were higher in those with early age at peak height velocity (OR: 2.06; 95% CI 1.27–3.34), early age at peak weight velocity (OR: 2.10; 95% CI 1.16–3.79), and early age at Tanner genitalia stage 3 (OR: 1.81; 95% CI 1.01–3.26). There was no evidence for associations between pubertal timing and depressive symptoms at age 14 or 18.
We found evidence that males with an earlier pubertal timing had increased odds of depression at age 18. Early maturing boys could be targeted for interventions aimed at preventing depression.
Previous studies (various designs) present contradicting insights on the potential causal effects of diet/physical activity on depression/anxiety (and vice versa). To clarify this, we employed a triangulation framework including three methods with unique strengths/limitations/potential biases to examine possible bidirectional causal effects of diet/physical activity on depression/anxiety.
Study 1: 3-wave longitudinal study (n = 9,276 Dutch University students). Using random intercept cross-lagged panel models to study temporal associations. Study 2: cross-sectional study (n = 341 monozygotic and n = 415 dizygotic Australian adult twin pairs). Using a co-twin control design to separate genetic/environmental confounding. Study 3: Mendelian randomization utilizing data (European ancestry) from genome-wide association studies (n varied between 17,310 and 447,401). Using genetic variants as instrumental variables to study causal inference.
Study 1 did not provide support for bidirectional causal effects between diet/physical activity and symptoms of depression/anxiety. Study 2 did provide support for causal effects between fruit/vegetable intake and symptoms of depression/anxiety, mixed support for causal effects between physical activity and symptoms of depression/anxiety, and no support for causal effects between sweet/savoury snack intake and symptoms of depression/anxiety. Study 3 provides support for a causal effect from increased fruit intake to the increased likelihood of anxiety. No support was found for other pathways. Adjusting the analyses including diet for physical activity (and vice versa) did not change the conclusions in any study.
Triangulating the evidence across the studies did not provide compelling support for causal effects of diet/physical activity on depression/anxiety or vice versa.
The structure of psychopathology can be organized hierarchically into a set of transdiagnostic dimensional phenotypes. No studies have examined whether these phenotypes are associated with brain structure or dementia in older adults.
Data were drawn from a longitudinal study of older adults aged 70–90 years at baseline (N = 1072; 44.8% male). Confirmatory factor models were fit to baseline psychiatric symptoms, with model fit assessed via traditional fit indices, model-based reliability estimates, and evaluation of model parameters. Bayesian plausible values were generated from the best-fitting model for use in subsequent analyses. Linear mixed models examined intraindividual change in global and regional gray matter volume (GMV) and cortical thickness over 6 years. Logistic regression examined whether symptom dimensions predicted incident dementia over 12 years.
A higher-order model showed a good fit to the data (BIC = 28,691.85; ssaBIC = 28,396.47; CFI = 0.926; TLI = 0.92; RMSEA = 0.047), including a general factor and lower-order dimensions of internalizing, disinhibited externalizing, and substance use. Baseline symptom dimensions did not predict change over time in total cortical and subcortical GMV or average cortical thickness; regional GMV or cortical thickness in the frontal, parietal, temporal, or occipital lobes; or regional GMV in the hippocampus and cerebellum (all p-values >0.5). Finally, baseline symptom dimensions did not predict incident dementia across follow-ups (all p-values >0.5).
We found no evidence that transdiagnostic dimensions are associated with gray matter structure or dementia in older adults. Future research should examine these relationships using psychiatric indicators capturing past history of chronic mental illness rather than current symptoms.
Negative symptoms are a key feature of several psychiatric disorders. Difficulty identifying common neurobiological mechanisms that cut across diagnostic boundaries might result from equifinality (i.e., multiple mechanistic pathways to the same clinical profile), both within and across disorders. This study used a data-driven approach to identify unique subgroups of participants with distinct reward processing profiles to determine which profiles predicted negative symptoms.
Participants were a transdiagnostic sample of youth from a multisite study of psychosis risk, including 110 individuals at clinical high-risk for psychosis (CHR; meeting psychosis-risk syndrome criteria), 88 help-seeking participants who failed to meet CHR criteria and/or who presented with other psychiatric diagnoses, and a reference group of 66 healthy controls. Participants completed clinical interviews and behavioral tasks assessing four reward processing constructs indexed by the RDoC Positive Valence Systems: hedonic reactivity, reinforcement learning, value representation, and effort–cost computation.
k-means cluster analysis of clinical participants identified three subgroups with distinct reward processing profiles, primarily characterized by: a value representation deficit (54%), a generalized reward processing deficit (17%), and a hedonic reactivity deficit (29%). Clusters did not differ in rates of clinical group membership or psychiatric diagnoses. Elevated negative symptoms were only present in the generalized deficit cluster, which also displayed greater functional impairment and higher psychosis conversion probability scores.
Contrary to the equifinality hypothesis, results suggested one global reward processing deficit pathway to negative symptoms independent of diagnostic classification. Assessment of reward processing profiles may have utility for individualized clinical prediction and treatment.
The prevalence of youth anxiety and depression has increased globally, with limited causal explanations. Long-term physical health conditions (LTCs) affect 20–40% of youth, with rates also rising. LTCs are associated with higher rates of youth depression and anxiety; however, it is uncertain whether observed associations are causal or explained by unmeasured confounding or reverse causation.
Using data from the Norwegian Mother, Father, and Child Cohort Study (MoBa) and Norwegian National Patient Registry, we investigated phenotypic associations between childhood LTCs, and depression and anxiety diagnoses in youth (<19 years), defined using ICD-10 diagnoses and self-rated measures. We then conducted two-sample Mendelian Randomization (MR) analyses using SNPs associated with childhood LTCs from existing genome-wide association studies (GWAS) as instrumental variables. Outcomes were: (i) diagnoses of major depressive disorder (MDD) and anxiety disorders or elevated symptoms in MoBa, and (ii) youth-onset MDD using summary statistics from a GWAS in iPSYCH2015 cohort.
Having any childhood LTC phenotype was associated with elevated youth MDD (OR = 1.48 [95% CIs 1.19, 1.85], p = 4.2×10−4) and anxiety disorder risk (OR = 1.44 [1.20, 1.73], p = 7.9×10−5). Observational and MR analyses in MoBa were consistent with a causal relationship between migraine and depression (IVW OR = 1.38 [1.19, 1.60], pFDR = 1.8x10−4). MR analyses using iPSYCH2015 did not support a causal link between LTC genetic liabilities and youth-onset depression or in the reverse direction.
Childhood LTCs are associated with depression and anxiety in youth, however, little evidence of causation between LTCs genetic liability and youth depression/anxiety was identified from MR analyses, except for migraine.
Relatively little is known about mental healthcare-related harm, with patient safety incidents (PSIs) in community-based services particularly poorly understood. We aimed to characterize PSIs, contributory factors, and reporter-identified solutions within community-based mental health services for working-age adults.
We obtained data on PSIs reported within English services from the National Reporting and Learning System. Of retrieved reports, we sampled all incidents reportedly involving ‘Death’, ‘Severe harm’, or ‘Moderate harm’, and random samples of a proportion of ‘Low harm’ or ‘No harm’ incidents. PSIs and contributory factors were classified through qualitative content analysis using existing frameworks. Frequencies and proportions of incident types were computed, and reporter-identified solutions were inductively categorized.
Of 1825 sampled reports, 1443 were eligible and classified into nine categories. Harmful outcomes, wherein service influence was unclear, were widely observed, with self-harm the modal concern amongst ‘No harm’ (15.0%), ‘Low harm’ (62.8%), and ‘Moderate harm’ (37.6%) categories. Attempted suicides (51.7%) and suicides (52.1%) were the most frequently reported events under ‘Severe harm’ or ‘Death’ outcomes, respectively. Incidents common to most healthcare settings were identified (e.g. medication errors), alongside specialty-specific incidents (e.g. Mental Health Act administration errors). Contributory factors were wide-ranging, with situational failures (e.g. team function failures) and local working conditions (e.g. unmanageable workload) widely reported. Solution categories included service user-directed actions and policy introduction or reinforcement.
Study findings provide novel insights into incidents, contributory factors, and reported solutions within community-based mental healthcare. Targets for safety improvement are outlined, aimed at strengthening system-based prevention of incidents.
Late-life depression (LLD) is characterized by medial temporal lobe (MTL) abnormalities. Although gray matter (GM) and white matter (WM) differences in LLD have been reported, few studies have investigated them concurrently. Moreover, the impact of aetiological factors, such as neurodegenerative and cerebrovascular burden, on tissue differences remains elusive.
This prospective cross-sectional study involved 72 participants, including 33 patients with LLD (mean age 72.2 years, 23 female) and 39 healthy controls (HCs) (mean age 70.6 years, 24 female), who underwent clinical and positron emission tomography (PET)-magnetic resonance imaging (MRI) assessments. High-resolution 3D T1-weighted and T2-weighted FLAIR images were used to assess MTL GM volumes and white matter hyperintensities (WMHs), a proxy for cerebrovascular burden. Diffusion kurtosis imaging metrics derived from multishell diffusion MRI data were analyzed to assess WM microstructure in the following MTL bundles reconstructed using constrained spherical deconvolution tractography: uncinate fasciculus, fornix, and cingulum. Standardized uptake value ratio of 18F-MK-6240 in the MTL was used to assess Alzheimer’s disease (AD) type tau accumulation as a proxy for neurodegenerative burden.
Compared to HCs, patients with LLD showed significantly lower bilateral MTL volumes and WM microstructural differences primarily in the uncinate fasciculi bilaterally and right fornix. In patients with LLD, higher vascular burden, but not tau, was associated with lower MTL volume and more pronounced WM differences.
LLD was associated with both GM and WM differences in the MTL. Cerebrovascular disease, rather than AD type tau-mediated neurodegenerative processes, may contribute to brain tissue differences in LLD.
The hypothesized cognitive model of negative symptoms, proposed nearly twenty years ago, is the most prevalent psychological framework for conceptualizing negative symptoms in schizophrenia spectrum disorders (SSDs). The aim of this study was to comprehensively validate the model for the first time, specifically by quantifying the relationships between negative symptom severity and all related dysfunctional beliefs.
A systematic search was conducted using MEDLINE and PsychINFO, supplemented by manual reviews of reference lists and Google Scholar. Eligible studies were peer-reviewed with data on the direct cross-sectional association between negative symptoms and at least one relevant dysfunctional belief in SSD patients. Screening and data extraction were completed by independent reviewers. Random-effects meta-analyses were performed to pool effect size estimates of z-transformed Pearson’s r correlations. Moderators of these relationships, as well as subset analyses for negative symptom domains and measurement instruments, were also assessed.
Significant effects emerged for the relationships between negative symptoms and defeatist performance beliefs (k = 38, n = 2808), r = 0.23 (95% CI, 0.18–0.27), asocial beliefs (k = 8, n = 578), r = 0.21 (95% CI, 0.12–0.28), low expectancies for success (k = 55, n = 5664), r = −0.21 (95% CI, −0.15 – −0.26), low expectancies for pleasure (k = 5, n = 249), r = −0.19 (95% CI, −0.06 – −0.31), and internalized stigma (k = 81, n = 9766), r = 0.17 (95% CI, 0.12–0.22), but not perception of limited resources (k = 10, n = 463), r = 0.08 (95% CI, −0.13 – 0.27).
This meta-analysis provides support for the cognitive model of negative symptoms. The identification of specific dysfunctional beliefs associated with negative symptoms is essential for the development of precision-based cognitive-behavioral interventions.
Previous studies identified clusters of first-episode psychosis (FEP) patients based on cognition and premorbid adjustment. This study examined a range of socio-environmental risk factors associated with clusters of FEP, aiming a) to compare clusters of FEP and community controls using the Maudsley Environmental Risk Score for psychosis (ERS), a weighted sum of the following risks: paternal age, childhood adversities, cannabis use, and ethnic minority membership; b) to explore the putative differences in specific environmental risk factors in distinguishing within patient clusters and from controls.
A univariable general linear model (GLS) compared the ERS between 1,263 community controls and clusters derived from 802 FEP patients, namely, low (n = 223) and high-cognitive-functioning (n = 205), intermediate (n = 224) and deteriorating (n = 150), from the EU-GEI study. A multivariable GLS compared clusters and controls by different exposures included in the ERS.
The ERS was higher in all clusters compared to controls, mostly in the deteriorating (β=2.8, 95% CI 2.3 3.4, η2 = 0.049) and the low-cognitive-functioning cluster (β=2.4, 95% CI 1.9 2.8, η2 = 0.049) and distinguished them from the cluster with high-cognitive-functioning. The deteriorating cluster had higher cannabis exposure (meandifference = 0.48, 95% CI 0.49 0.91) than the intermediate having identical IQ, and more people from an ethnic minority (meandifference = 0.77, 95% CI 0.24 1.29) compared to the high-cognitive-functioning cluster.
High exposure to environmental risk factors might result in cognitive impairment and lower-than-expected functioning in individuals at the onset of psychosis. Some patients’ trajectories involved risk factors that could be modified by tailored interventions.
Depressive disorders are the most common diagnosis among individuals who die by suicide, and intermittent theta-burst stimulation (iTBS) is a noninvasive treatment for those with difficult-to-treat depression who are at higher risk for suicide. Previous data suggests that pairing iTBS with D-cycloserine, a partial N-methyl-D-aspartate (NMDA) receptor agonist, improves antidepressant outcomes. However, its impact on suicide risk is not known.
We examine suicidal ideation and implicit suicide risk after iTBS+D-cycloserine in two clinical trials (open-label trial [n = 12] and randomized placebo-controlled trial [RCT, n = 50]) involving adults with major depressive disorder and the acute effects of D-cycloserine on implicit suicide risk in a crossover trial (n = 18). Implicit suicide risk was assessed using the computerized death/suicide implicit association test (IAT), and depressive symptoms and suicidal ideation were assessed using the clinician-rated Montgomery–Asberg Depression Rating Scale (MADRS).
Open-label iTBS+D-cycloserine was associated with a rapid reduction in suicidal ideation, and iTBS+D-cycloserine was superior to iTBS+placebo in reducing suicidal ideation. Similarly, open-label iTBS+D-cycloserine was associated with decreased implicit suicide risk as measured by the death/suicide IAT, and iTBS+D-cycloserine was associated with greater decreases in death/suicide IAT scores compared to iTBS+placebo. A single acute dose of D-cycloserine in the absence of iTBS had no effect on implicit suicide risk.
Adjunctive D-cycloserine with iTBS is a promising strategy to reduce suicidal ideation and implicit suicide risk in depression.
Psychotic disorders are known to be associated with elevated dopamine synthesis; yet, nondopamine factors may underlie the manifestation of some psychotic symptoms that are nonresponsive to dopamine-blocking agents. One under-explored nondopamine mechanism is neuroplasticity. We propose an account of the course of psychotic symptoms based on the extensive evidence for dopamine facilitation of Hebbian synaptic plasticity in cortical and subcortical memory systems. The encoding of psychotic experiences in autobiographical memory (AM) is expected to be facilitated in the hyperdopaminergic state associated with acute psychosis. However, once such ‘spurious AM of psychosis’ (SAMP) is encoded, its persistence may become dependent more on synaptic factors than dopamine factors. Under this framework, the involuntary retrieval of residual SAMP is postulated to play a key role in mediating the reactivation of symptoms with similar contents, as often observed in patients during relapse. In contrast, with active new learning of normalizing experiences across diverse real-life contexts, supported by intact dopamine-mediated salience, well-integrated SAMP may undergo ‘extinction’, leading to remission. The key steps to the integration of SAMP across psychotic and nonpsychotic memories may correspond to one’s ‘recovery style’, involving processes similar to the formation of ‘non-believed memory’ in nonclinical populations. The oversuppression of dopamine can compromise such processes. We synthesize this line of evidence into an updated dopamine-gated memory framework where neuroplasticity processes offer a parsimonious account for the recurrence, persistence, and progression of psychotic symptoms. This framework generates testable hypotheses relevant to clinical interventions.
Maternal depression is associated with difficulties in understanding and adequately responding to children’s emotional signals. Consequently, the interaction between mother and child is often disturbed. However, little is known about the neural correlates of these parenting difficulties. Motivated by increasing evidence of the amygdala’s important role in mediating maternal behavior, we investigated amygdala responses to child sad and happy faces in mothers with remitted major depression disorder (rMDD) relative to healthy controls.
We used the sensitivity subscale of the emotional availability scales and functional magnetic resonance imaging in 61 rMDD and 27 healthy mothers to examine the effect of maternal sensitivity on mothers’ amygdala responses to their children’s affective facial expressions.
For mothers with rMDD relative to controls, we observed decreased maternal sensitivity when interacting with their child. They also showed reduced amygdala responses to child affective faces that were associated with lower maternal sensitivity. Connectivity analysis revealed that this blunted amygdala response in rMDD mothers was functionally correlated with reduced activation in higher-order medial prefrontal areas.
Our results contribute toward a better understanding of the detrimental effects of lifetime depression on maternal sensitivity and associated brain responses. By targeting region-specific neural activation patterns, these results are a first step toward improving the prediction, prevention, and treatment of depression-related negative effects on mother–child interaction.
Dissecting the exposome linked to mental health outcomes can help identify potentially modifiable targets to improve mental well-being. However, the multiplicity of exposures and the complexity of mental health phenotypes pose a challenge that requires data-driven approaches.
Guided by our previous systematic approach, we conducted hypothesis-free exposome-wide analyses to identify factors associated with 7 psychiatric diagnostic domains and 19 symptom dimensions in 157,298 participants from the UK Biobank Mental Health Survey. After quality control, 294 environmental, lifestyle, behavioral, and economic variables were included. An Exposome-Wide Association Study was conducted per outcome in two equally split datasets. Variables associated with each outcome were then tested in a multivariable model.
Across all diagnostic domains and symptom dimensions, the top three exposures were childhood adversities and traumatic events. Cannabis use was associated with common psychiatric disorders (depressive, anxiety, psychotic, and bipolar manic disorders), with ORs ranging from 1.10 to 1.79 in the multivariable models. Additionally, differential associations were identified between specific outcomes—such as neurodevelopmental disorders, eating disorders, and self-harm behaviors—and exposures, including early life experiences (being adopted), lifestyle (time spent using computers), and dietary habits (vegetarian diet).
This comprehensive mapping of the exposome revealed that several factors, particularly in the domains of those previously well-studied were shared across mental health phenotypes, providing further support for transdiagnostic pathoetiology. Our findings also showed that distinct relations might exist. Continued exposome research through multimodal mechanistic studies guided by the transdiagnostic mental health framework is required to better inform public health policies.
Genetically informative twin studies have consistently found that individual differences in anxiety and depression symptoms are stable and primarily attributable to time-invariant genetic influences, with non-shared environmental influences accounting for transient effects.
We explored the etiology of psychological and somatic distress in 2279 Australian twins assessed up to six times between ages 12–35. We evaluated autoregressive, latent growth, dual-change, common, and independent pathway models to identify which, if any, best describes the observed longitudinal covariance and accounts for genetic and environmental influences over time.
An autoregression model best explained both psychological and somatic distress. Familial aggregation was entirely explained by additive genetic influences, which were largely stable from ages 12 to 35. However, small but significant age-dependent genetic influences were observed at ages 20–27 and 32–35 for psychological distress and at ages 16–19 and 24–27 for somatic distress. In contrast, environmental influences were predominantly transient and age-specific.
The longitudinal trajectory of psychological distress from ages 12 to 35 can thus be largely explained by forward transmission of a stable additive genetic influence, alongside smaller age-specific genetic innovations. This study addresses the limitation of previous research by exhaustively exploring alternative theoretical explanations for the observed patterns in distress symptoms over time, providing a more comprehensive understanding of the genetic and environmental factors influencing psychological and somatic distress across this age range.
Artificial intelligence (AI) has been recently applied to different mental health illnesses and healthcare domains. This systematic review presents the application of AI in mental health in the domains of diagnosis, monitoring, and intervention. A database search (CCTR, CINAHL, PsycINFO, PubMed, and Scopus) was conducted from inception to February 2024, and a total of 85 relevant studies were included according to preestablished inclusion criteria. The AI methods most frequently used were support vector machine and random forest for diagnosis, machine learning for monitoring, and AI chatbot for intervention. AI tools appeared to be accurate in detecting, classifying, and predicting the risk of mental health conditions as well as predicting treatment response and monitoring the ongoing prognosis of mental health disorders. Future directions should focus on developing more diverse and robust datasets and on enhancing the transparency and interpretability of AI models to improve clinical practice.
We aimed to study how hormonal status (oral contraceptive [OC] users vs naturally cycling [NC]) affects different dimensions and variability of psychological well-being, and how they relate to sex hormone levels (estradiol, progesterone, and testosterone).
Twenty-two NC participants and 18 OC users reported daily affective and physical symptoms and collected daily salivary samples across 28 days. Groups were compared using psychological well-being averages (linear mixed models), day-to-day variability (Levene’s test), and network models. Within NC participants, cycle phase effects and time-varying associations between hormones and psychological well-being were assessed using both person-centered mean and change (subtracting mean from daily score) scores.
Lowered variability was found for OC users’ agitation, risk-taking, attractiveness, and energy levels. They showed lower overall ratings of happiness, attractiveness, risk-taking, and energy levels (range R2m = .004: .019) but also reported more relaxation, sexual desire, and better sleep quality (range R2m = .005; .01) compared to the NC group. The impact of sex hormones on psychological well-being varied significantly across cycle phases, with the largest effects for progesterone levels.
Our results confirm that hormonal status is associated with a range of psychological well-being domains beyond mood and sexual desire, including energy levels, feelings of attractiveness, risk taking, and agitation. Lowered variability in OC users versus NC participants fit with ‘emotional blunting’ as a possible mechanism behind OC’s side effects. Our findings that show the menstrual cycle and sex hormones differentially influenced markers of psychological well-being emphasize the need to adequately account for the menstrual cycle.
Major depressive disorder (MDD) is characterized by changes in appetite and body weight as well as blunted reward sensitivity (‘anhedonia’). However, it is not well understood which mechanisms are driving changes in reward sensitivity, specifically regarding food. Here, we used a sample of 117 participants (54 patients with MDD and 63 healthy control participants [HCPs]) who completed a food cue reactivity task with ratings of wanting and liking for 60 food and 20 non-food items. To evaluate which components of the food may contribute to altered ratings in depression, we tested for associations with macronutrients of the depicted items. In line with previous studies, we found reduced ratings of food wanting (p = .003) but not liking (p = .23) in patients with MDD compared to matched HCPs. Adding macronutrient composition to the models of wanting and liking substantially improved their fit (ps < .001). Compared to carbohydrate-rich foods, patients with MDD reported lower liking and wanting ratings for high-fat and high-protein foods. Moreover, patients with MDD showed weaker correlations in their preferences for carbohydrate- versus fat- or protein-rich foods (ps < .001), pointing to potential disturbances in metabolic signaling. To conclude, our results suggest that depression-related alterations in food reward ratings are more specific to the macronutrient composition of the food than previously anticipated, hinting at disturbances in gut–brain signaling. These findings raise the intriguing question of whether interventions targeting the gut could help normalize aberrant reward signals for foods rich in fat or protein.