Psychological Medicine最新文献

{"title":"Mapping the exposome of mental health: exposome-wide association study of mental health outcomes among UK Biobank participants.","authors":"Angelo Arias-Magnasco, Bochao Danae Lin, Lotta-Katrin Pries, Sinan Guloksuz","doi":"10.1017/S0033291724003015","DOIUrl":"10.1017/S0033291724003015","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":20891,"journal":{"name":"Psychological Medicine","volume":"55 ","pages":"e16"},"PeriodicalIF":5.9,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11968124/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143365796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"28 days later: A prospective daily study on psychological well-being across the menstrual cycle and the effects of hormones and oral contraceptives.","authors":"Anne Marieke Doornweerd, Lotte Gerritsen","doi":"10.1017/S003329172400357X","DOIUrl":"https://doi.org/10.1017/S003329172400357X","url":null,"abstract":"<p><strong>Background: </strong>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).</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 <i>R²_m =</i> .004: .019) but also reported more relaxation, sexual desire, and better sleep quality (range <i>R²_m =</i> .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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":20891,"journal":{"name":"Psychological Medicine","volume":"55 ","pages":"e19"},"PeriodicalIF":5.9,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143365790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of genes and environment assessed longitudinally on psychological and somatic distress in twins from ages 15 to 35 years.","authors":"Nathan A Gillespie, Baptiste Couvy-Duchesne, Michael C Neale, Ian B Hickie, Nicholas G Martin","doi":"10.1017/S0033291724003222","DOIUrl":"10.1017/S0033291724003222","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":20891,"journal":{"name":"Psychological Medicine","volume":"55 ","pages":"e17"},"PeriodicalIF":5.9,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11968121/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143256145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between the functional brain network and antidepressant responsiveness in patients with major depressive disorders: a resting-state EEG study.","authors":"Kang-Min Choi, Hyeon-Ho Hwang, Chaeyeon Yang, Bori Jung, Chang-Hwan Im, Seung-Hwan Lee","doi":"10.1017/S0033291724003477","DOIUrl":"https://doi.org/10.1017/S0033291724003477","url":null,"abstract":"<p><strong>Background: </strong>Recent neuroimaging studies have demonstrated that the heterogeneous antidepressant responsiveness in patients with major depressive disorder (MDD) is associated with diverse resting-state functional brain network (rsFBN) topology; however, only limited studies have explored the rsFBN using electroencephalography (EEG). In this study, we aimed to identify EEG-derived rsFBN-based biomarkers to predict pharmacotherapeutic responsiveness.</p><p><strong>Methods: </strong>The resting-state EEG signals were acquired for demography-matched three groups: 98 patients with treatment-refractory MDD (trMDD), 269 those with good-responding MDD (grMDD), and 131 healthy controls (HCs). The source-level rsFBN was constructed using 31 sources as nodes and beta-band power envelope correlation (PEC) as edges. The degree centrality (DC) and clustering coefficients (CCs) were calculated for various sparsity levels. Network-based statistic and one-way analysis of variance models were employed for comparing PECs and network indices, respectively. The multiple comparisons were controlled by the false discovery rate.</p><p><strong>Results: </strong>Patients with trMDD were characterized by the altered dorsal attention network and salience network. Specifically, they exhibited hypoconnection between eye fields and right parietal regions (<i>p</i> = 0.0088), decreased DC in the right supramarginal gyrus (<i>q</i> = 0.0057), and decreased CC in the reward circuit (<i>q</i>s < 0.05). On the other hand, both MDD groups shared increased DC but decreased CC in the posterior cingulate cortex.</p><p><strong>Conclusions: </strong>We confirmed that network topology was more severely deteriorated in patients with trMDD, particularly for the attention-regulatory networks. Our findings suggested that the altered rsFBN topologies could serve as potential pathologically interpretable biomarkers for predicting antidepressant responsiveness.</p>","PeriodicalId":20891,"journal":{"name":"Psychological Medicine","volume":"55 ","pages":"e25"},"PeriodicalIF":5.9,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143255917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New diagnosis in psychiatry: beyond heuristics.","authors":"Patrick D McGorry, Ian B Hickie, Roman Kotov, Lianne Schmaal, Stephen J Wood, Sophie M Allan, Kürşat Altınbaş, Niall Boyce, Laura F Bringmann, Avshalom Caspi, Bruce Cuthbert, Łukasz Gawęda, Robin N Groen, Sinan Guloksuz, Jessica A Hartmann, Robert F Krueger, Cristina Mei, Dorien Nieman, Dost Öngür, Andrea Raballo, Marten Scheffer, Marieke J Schreuder, Jai L Shah, Johanna T W Wigman, Hok Pan Yuen, Barnaby Nelson","doi":"10.1017/S003329172400223X","DOIUrl":"https://doi.org/10.1017/S003329172400223X","url":null,"abstract":"<p><strong>Background: </strong>Diagnosis in psychiatry faces familiar challenges. Validity and utility remain elusive, and confusion regarding the fluid and arbitrary border between mental health and illness is increasing. The mainstream strategy has been conservative and iterative, retaining current nosology until something better emerges. However, this has led to stagnation. New conceptual frameworks are urgently required to catalyze a genuine paradigm shift.</p><p><strong>Methods: </strong>We outline candidate strategies that could pave the way for such a paradigm shift. These include the Research Domain Criteria (RDoC), the Hierarchical Taxonomy of Psychopathology (HiTOP), and Clinical Staging, which all promote a blend of dimensional and categorical approaches.</p><p><strong>Results: </strong>These alternative still heuristic transdiagnostic models provide varying levels of clinical and research utility. RDoC was intended to provide a framework to reorient research beyond the constraints of DSM. HiTOP began as a nosology derived from statistical methods and is now pursuing clinical utility. Clinical Staging aims to both expand the scope and refine the utility of diagnosis by the inclusion of the dimension of timing. None is yet fit for purpose. Yet they are relatively complementary, and it may be possible for them to operate as an ecosystem. Time will tell whether they have the capacity singly or jointly to deliver a paradigm shift.</p><p><strong>Conclusions: </strong>Several heuristic models have been developed that separately or synergistically build infrastructure to enable new transdiagnostic research to define the structure, development, and mechanisms of mental disorders, to guide treatment and better meet the needs of patients, policymakers, and society.</p>","PeriodicalId":20891,"journal":{"name":"Psychological Medicine","volume":"55 ","pages":"e26"},"PeriodicalIF":5.9,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143256056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probabalistic reinforcement learning impairments predict negative symptom severity and risk for conversion in youth at clinical high-risk for psychosis.","authors":"Lauren Luther, Ian M Raugh, Gregory P Strauss","doi":"10.1017/S0033291724003416","DOIUrl":"https://doi.org/10.1017/S0033291724003416","url":null,"abstract":"<p><strong>Background: </strong>Elucidation of transphasic mechanisms (i.e., mechanisms that occur across illness phases) underlying negative symptoms could inform early intervention and prevention efforts and additionally identify treatment targets that could be effective regardless of illness stage. This study examined whether a key reinforcement learning behavioral pattern characterized by reduced difficulty learning from rewards that have been found to underlie negative symptoms in those with a schizophrenia diagnosis also contributes to negative symptoms in those at clinical high-risk (CHR) for psychosis.</p><p><strong>Methods: </strong>CHR youth (<i>n</i> = 46) and 51 healthy controls (CN) completed an explicit reinforcement learning task with two phases. During the acquisition phase, participants learned to select between pairs of stimuli probabilistically reinforced with feedback indicating receipt of monetary gains or avoidance of losses. Following training, the transfer phase required participants to select between pairs of previously presented stimuli during the acquisition phase and novel stimuli without receiving feedback. These test phase pairings allowed for inferences about the contributions of prediction error and value representation mechanisms to reinforcement learning deficits.</p><p><strong>Results: </strong>In acquisition, CHR participants displayed impaired learning from gains specifically that were associated with greater negative symptom severity. Transfer performance indicated these acquisition deficits were largely driven by value representation deficits. In addition to negative symptoms, this profile of deficits was associated with a greater risk of conversion to psychosis and lower functioning.</p><p><strong>Conclusions: </strong>Impairments in positive reinforcement learning, specifically effectively representing reward value, may be an important transphasic mechanism of negative symptoms and a marker of psychosis liability.</p>","PeriodicalId":20891,"journal":{"name":"Psychological Medicine","volume":"55 ","pages":"e28"},"PeriodicalIF":5.9,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143256024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What works for whom in pediatric OCD: description of causally interpretable meta-analysis methods and report on trial data harmonization.","authors":"Lesley A Norris, David H Barker, Ariella R Rosen, Joshua Kemp, Jennifer Freeman, Kristen G Benito","doi":"10.1017/S0033291724003301","DOIUrl":"https://doi.org/10.1017/S0033291724003301","url":null,"abstract":"<p><strong>Background: </strong>Improving patient outcomes will be enhanced by understanding \"what works, for whom?\" enabling better matching of patients to available treatments. However, answering this \"what works, for whom?\" question requires sample sizes that exceed those of most individual trials. Conventional methods for combining data across trials, including aggregate-data meta-analysis, suffer from key limitations including difficulty accounting for differences across trials (e.g., comparing \"apples to oranges\"). Causally interpretable meta-analysis (CI-MA) addresses these limitations by pairing individual-participant-data (IPD) across trials using advancements in transportability methods to extend causal inferences to clinical \"target\" populations of interest. Combining IPD across trials also requires careful acquisition and harmonization of data, a challenging process for which practical guidance is not well-described in the literature.</p><p><strong>Methods: </strong>We describe methods and work to date for a large harmonization project in pediatric obsessive-compulsive disorder (OCD) that employs CI-MA.</p><p><strong>Results: </strong>We review the data acquisition, harmonization, meta-data coding, and IPD analysis processes for Project Harmony, a study that (1) harmonizes 28 randomized controlled trials, along with target data from a clinical sample of treatment-seeking youth ages 4-20 with OCD, and (2) applies CI-MA to examine \"what works, for whom?\" We also detail dissemination strategies and partner involvement planned throughout the project to enhance the future clinical utility of CI-MA findings. Data harmonization took approximately 125 hours per trial (3,000 hours total), which was considerably higher than preliminary projections.</p><p><strong>Conclusions: </strong>Applying CI-MA to harmonize data has the potential to answer \"what works for whom?\" in pediatric OCD.</p>","PeriodicalId":20891,"journal":{"name":"Psychological Medicine","volume":"55 ","pages":"e27"},"PeriodicalIF":5.9,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143256372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence in mental health care: a systematic review of diagnosis, monitoring, and intervention applications.","authors":"Pablo Cruz-Gonzalez, Aaron Wan-Jia He, Elly PoPo Lam, Ingrid Man Ching Ng, Mandy Wingman Li, Rangchun Hou, Jackie Ngai-Man Chan, Yuvraj Sahni, Nestor Vinas Guasch, Tiev Miller, Benson Wui-Man Lau, Dalinda Isabel Sánchez Vidaña","doi":"10.1017/S0033291724003295","DOIUrl":"https://doi.org/10.1017/S0033291724003295","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":20891,"journal":{"name":"Psychological Medicine","volume":"55 ","pages":"e18"},"PeriodicalIF":5.9,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143255282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multidimensional outcome of first-episode psychosis: a network analysis.","authors":"Manuel J Cuesta, Gustavo J Gil-Berrozpe, Ana M Sánchez-Torres, Lucía Moreno-Izco, Elena García de Jalón, Víctor Peralta","doi":"10.1017/S0033291724003465","DOIUrl":"https://doi.org/10.1017/S0033291724003465","url":null,"abstract":"<p><strong>Background: </strong>Few studies have examined the long-term outcomes of first-episode psychosis (FEP) among patients beyond symptomatic and functional remission. This study aimed to broaden the scope of outcome indicators by examining the relationships between 12 outcomes of FEP patients at 20.9 years after their initial diagnosis.</p><p><strong>Methods: </strong>At follow-up, 220 out of 550 original patients underwent a new assessment. Twelve outcomes were assessed via semistructured interviews and complementary scales: symptom severity, functional impairment, personal recovery, social disadvantage, physical health, number of suicide attempts, number of episodes, current drug use, dose-years of antipsychotics (DYAps), cognitive impairment, motor abnormalities, and DSM-5 final diagnosis. The relationships between these outcome measures were investigated using Spearman's correlation analysis and exploratory factor analysis, while the specific connections between outcomes were ascertained using network analysis.</p><p><strong>Results: </strong>The outcomes were significantly correlated; specifically, symptom severity, functioning, and personal recovery showed the strongest correlations. Exploratory factor analysis of the 12 outcomes revealed two factors, with 11 of the 12 outcomes loading on the first factor. Network analysis revealed that symptom severity, functioning, social disadvantage, diagnosis, cognitive impairment, DYAps, and number of episodes were the most interconnected outcomes.</p><p><strong>Conclusion: </strong>Network analysis provided new insights into the heterogeneity between outcomes among patients with FEP. By considering outcomes beyond symptom severity, the rich net of interconnections elucidated herein can facilitate the development of interventions that target potentially modifiable outcomes and generalize their impact on the most interconnected outcomes.</p>","PeriodicalId":20891,"journal":{"name":"Psychological Medicine","volume":"55 ","pages":"e29"},"PeriodicalIF":5.9,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143255937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Altered food liking in depression is driven by macronutrient composition.","authors":"Lilly Thurn, Corinna Schulz, Diba Borgmann, Johannes Klaus, Sabine Ellinger, Martin Walter, Nils B Kroemer","doi":"10.1017/S0033291724003581","DOIUrl":"https://doi.org/10.1017/S0033291724003581","url":null,"abstract":"<p><p>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 (<i>p</i> = .003) but not liking (<i>p</i> = .23) in patients with MDD compared to matched HCPs. Adding macronutrient composition to the models of wanting and liking substantially improved their fit (<i>p</i>s < .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 (<i>p</i>s < .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.</p>","PeriodicalId":20891,"journal":{"name":"Psychological Medicine","volume":"55 ","pages":"e20"},"PeriodicalIF":5.9,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143190346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}