Objectives To compare receipt of guideline-informed myocardial infarction (MI) care by mental disorder and assess how the COVID-19 pandemic affected associations. Design A population-based cohort study using linked electronic health records. Setting England, November 2019 to February 2023. Participants 131 075 adults with non-ST-elevation MI (NSTEMI) and 79 045 adults with ST-elevation MI (STEMI) were identified from the Myocardial Ischaemia National Audit Project, and their prior diagnoses of mental disorder were ascertained from linked hospitalisation and primary care records. Outcome measures We compared guideline-informed care standards for each of NSTEMI and STEMI between people with schizophrenia, bipolar disorder or depression versus those without any of these disorders. We used logistic regression to adjust for confounders and investigate differences over time. Results Mental disorder disparities were more evident for NSTEMI than STEMI. Following NSTEMI, people with a mental disorder had lower odds of angiography eligibility and receipt, cardiac ward admission and cardiac rehabilitation referral. ORs (95% CIs) ranged from 0.25 (0.20 to 0.31) for angiography receipt for schizophrenia to 0.92 (0.89 to 0.96) for cardiac ward admission for depression. Following STEMI, people with bipolar disorder were less likely to meet the 150 min call-to-balloon target (OR 0.72; 95% CI 0.55 to 0.93), and people with schizophrenia were less likely to receive rehabilitation referral (OR 0.38; 95% CI 0.23 to 0.61) or indicated secondary prevention medication (OR 0.46, 95% CI 0.27 to 0.77). There was no clear evidence that the COVID-19 pandemic affected disparities. Conclusions People with a mental disorder are less likely to receive guideline-informed MI care, with disparities greatest following NSTEMI and for people with schizophrenia.

Twin studies reveal high genetic overlap between anxiety disorders and depression, contributing to the internalising spectrum. Some genetic specificity for fear-based anxiety disorders (fear), distinct from general anxiety and depression (distress), has also emerged. Limited datasets with detailed phenotyping across anxiety disorders have restricted most genome-wide association studies (GWAS) to "any anxiety diagnosis". Additional genome-wide evidence to discern genetic differences between fear and distress is required. We conducted GWAS meta-analyses of fear (panic, agoraphobia, specific phobia, social anxiety disorder) and generalised anxiety disorder (GAD), measured using brief single-item and detailed symptom-based diagnoses from three datasets. We explored two control group criteria: phenotype-specific (fear/GAD) or broader anxiety/depression screening. We identified one independent genome-wide significant locus and three gene-level associations with fear (up to 35,523 Ncases; 157,447 Ncontrols). Four genome-wide significant loci and three gene-level associations were identified for GAD (up to 60,879 Ncases; 117,064 Ncontrols). The genetic correlation between fear and GAD was significantly different from unity only when excluding a depression-enriched dataset and using phenotype-specific control screening (rg = 0.87; P = 9.32 × 10-3). Most complex traits had statistically similar genetic correlations with fear and GAD, including depression. Exceptions included general cognitive ability, educational attainment, and coronary artery disease, showing statistically stronger genetic correlations with fear than GAD, while bipolar disorder type I, anorexia nervosa, and neuroticism displayed the opposite pattern. Our findings partially support a distress-fear genetic distinction, but show stronger evidence for an overarching genetic liability to internalising psychopathology driving comorbidity across anxiety disorders and depression.

AIMS:People with schizophrenia experience poorer cardiovascular disease (CVD) outcomes, but other mental disorders have been little studied. We compared post-myocardial infarction (MI) mortality by mental disorder, explored whether differences in care contributed to mortality disparities, and investigated whether disparities worsened during the COVID-19 pandemic. METHODS AND RESULTS:We identified people with MI in England (November 2019-February 2023) from the Myocardial Ischaemia National Audit Programme, ascertaining mental disorder diagnoses from linked electronic health records and mortality from national death records. We used logistic regression to compare 30-day and one-year mortality between people with each of schizophrenia, bipolar disorder, or depression (of any severity) vs. those without these disorders for ST-elevation MI (STEMI) and non-STEMI (NSTEMI), adjusting for confounders and investigating differences by calendar time period. For one-year mortality, we additionally adjusted for receipt of guideline-informed care. We included 131 075 patients with NSTEMI and 79 045 with STEMI. For NSTEMI, schizophrenia [odds ratio (OR) 1.73, 95% CI 1.20-2.49] and depression (1.17, 1.08-1.26) were associated with higher 30-day mortality. For STEMI, 30-day mortality was higher in people with schizophrenia (1.61, 1.09-2.37), bipolar disorder (1.68, 1.08-2.59), and depression (1.10, 1.01-1.20). All disorders were associated with higher one-year mortality following NSTEMI and STEMI, with adjustment for care attenuating estimates. Relative mortality disparities were generally unaffected by the COVID-19 pandemic. CONCLUSION:Our findings highlight the increased risk of post-MI mortality in people with mental disorders. Improved implementation of acute cardiac care standards may help to close the gap.

Background Undisturbed circadian rhythms of rest/activity are crucial to health and well-being. There is growing evidence to suggest that circadian rhythm disruptions are also associated with adverse mental health outcomes (and vice versa), but important questions about the relationship between circadian rhythms and mental health remain unanswered.Objective To determine future priorities for research in the area of mental health and circadian rhythms, a James Lind Alliance Priority Setting Partnership exercise in collaboration with a steering group comprising individuals with lived experience, carers and clinicians was undertaken.Methods An initial survey among UK residents provided a set of 964 questions supplied by 247 respondents (227 lived experience, 44 carers (including 40 carers with lived experience), 41 clinicians (including 37 clinicians with lived experience)). Responses were processed into 171 summary questions by the steering group. Reviews of published research and existing clinical guidelines reduced this to 63 unanswered summary questions. A ranking survey of these 63 questions asked respondents to select their 10 most important research questions, from which the most highly ranked would be taken to the final stage. This was completed by 222 respondents (200 lived experience, 33 carers (including 29 carers with lived experience), 38 clinicians (including 30 clinicians with lived experience)).Findings In a final face-to-face workshop, 19 individuals, including individuals with lived experience, carers and clinicians, discussed and ranked a list of questions to produce a ranking of the top 25 research questions/priorities, with a particular focus on the Top 10.Discussion The final research questions are presented to inform researchers and funding bodies when setting future research priorities across the fields of mental health and circadian rhythms.Clinical implications Addressing the priorities identified here should lead to greater understanding of the relationships between mental health and circadian rhythms and will have longer-term impacts on research, healthcare innovation and public health policy.

Background Multiple sclerosis (MS) is an autoimmune disease with complex aetiology involving genetic, environmental and lifestyle factors. Shift work disrupts circadian rhythms and is a potential occupational risk factor for MS, with exposure before age 20 thought to be of additional risk.Objective To investigate associations between retrospective lifetime shift work exposure and MS diagnosis and between prospective shift work exposure and incident MS over 13 years of follow-up in the UK Biobank cohort.Methods Participants that were in work and free of MS at baseline were followed up for 13 years, and lifetime exposure to night, day and mixed shift work was assessed in a subset of participants. Logistic regression and Cox proportional hazard models were applied to test associations between shift work and MS diagnosis, controlling for demographic and lifestyle confounders.Results Lifetime exposure to mixed, day or night shift work was not associated with an increased risk of MS diagnosis. No significant associations were observed for early-life shift work exposure or in prospective analysis of those reporting shift work at baseline. Factors such as female sex, smoking, childhood obesity and reduced sunlight exposure were consistently associated with higher MS risk.Conclusions There was no evidence for an association between shift work and the risk of MS diagnosis in this cohort, in retrospective analysis of lifetime exposure or in prospective studies of shift work at baseline following 13 years of follow-up. Further research is needed to elucidate mechanisms and latitudinal variations in shift work-related MS risk.

Abstract Background Bipolar disorder and depression are associated with structural and functional changes in the retina, including a thinner retinal nerve fibre layer (RNFL). Lithium is widely considered the most effective treatment for bipolar disorder, but its mechanism of action is not fully understood. We assessed research looking at the effect of lithium on structural or functional retinal outcomes in humans. Methods Searches using the terms ‘Lithium’ AND ‘retina’ were carried out to identify peer reviewed studies assessing the impact of lithium on retinal structure or function. These included those with or without a control group comparison, pre- and post- lithium comparisons and observational studies. There were no exclusions based on the quantity or preparation of lithium administered, or the length of administration. Risk of bias was assessed using the Joanna Briggs Institute (JBI) critical appraisal tool for Analytical Cross Sectional Studies, and a narrative synthesis and tabulated summary of the included studies was completed. Results Seven studies assessing structural outcomes and 10 reporting functional ones were identified, all highly heterogenous and with multiple limitations. Structural outcomes were derived exclusively from optical coherence tomography (OCT) with retinal nerve fibre layer (RNFL) being the most common measurement. There was no evidence of differences in the RNFL between participants with bipolar disorder taking lithium and healthy controls in two larger studies. In six studies looking at differences in those with bipolar disorder taking lithium and those taking valproate, two showed no signs of difference and four showed evidence of thicker RNFL in the lithium group. Studies reporting functional outcomes reported a statistically significant effect of lithium on at least one functional measure, derived from electrooculography, electroretinography, and dark adaptation thresholds. Conclusions Current evidence suggests that lithium is likely to have an effect on the retina but limitations in all studies mean better designed and adequately powered prospective studies are required. Registration PROSPERO database (Number-CRD42024516635).

Ketogenic interventions, including ketogenic diets, are increasingly being explored as potential treatments for severe mental illnesses. Ketosis – the metabolic state characterised by high circulating levels of ketone bodies – is thought to be central to the beneficial effects of these diets. Hence, it is plausible that other interventions that induce ketosis may similarly improve mental health outcomes. Here, we critically appraise the evidence surrounding the use of ketosis-inducing interventions for the treatment of severe mental illness. Several uncontrolled trials suggest beneficial mental and metabolic health effects of ketogenic diets in depression, bipolar disorder and schizophrenia, but are limited by confounders and expectation bias. The only reported randomised controlled clinical trial so far suggested a small, greater between-group difference in antidepressive effect of a modified ketogenic diet over a phytochemical control diet in treatment-resistant depression, that did not reach statistical significance. Additionally, ketone levels did not correlate with psychiatric outcomes. Preclinical studies suggest a beneficial effect of ketogenic diets on psychiatric symptom correlates but largely did not explore ketone-outcome correlations. Exogenous ketone and oral medium-chain triglyceride supplements induce nutritional ketosis, however, they have not been tested in patients with severe mental illness. Fasting and time-restricted eating produce ketosis but it is unclear if this explains their reported mental health and metabolic effects. Large, randomised controlled clinical trials are needed to examine and compare the effects of different ketogenic interventions in severe mental illness. Trials should be designed to isolate the role of ketosis, investigate the mechanistic basis of beneficial effects observed, assess dose-response relationships, examine treatment adherence in routine clinical settings, ascertain the duration of treatment effects following discontinuation, and clarify the impact of ketosis-inducing interventions on the need for psychiatric medications and standard care.

BACKGROUND:Circadian rhythm disturbances represent a core feature of bipolar disorder (BD), with evening chronotype as a marker for poorer outcomes. We hypothesized that BD psychopathology combined with evening chronotype would be associated with structural alterations in circadian-related hypothalamic regions, particularly the suprachiasmatic nucleus (SCN), specific to BD relative to other psychiatric diagnoses. METHODS:We investigated structural neuroimaging data from the UK Biobank (113 BD, 205 major depressive disorder, 91 psychotic disorders, 199 healthy control). The SCN-containing anterior-inferior hypothalamic subunit was segmented, central to circadian functional neuroanatomy. For each group, the effect of diagnosis × chronotype interactions on its volume were tested using analysis of variance, with post hoc estimated marginal means and correction for multiple comparisons. Covariates included age, sex, handedness, and psychiatric medication use. Specificity was examined across 4 additional hypothalamic subunits. RESULTS:There was a diagnosis × chronotype interaction in the SCN-containing anterior-inferior hypothalamic subunit volume (F6,586 = 2.84, p = .010). This was driven by larger volumes in individuals with BD with evening versus morning chronotype (t586 = 3.24, familywise error rate-corrected p = .004). No comparable results were found in other hypothalamic regions or diagnoses. CONCLUSIONS:Hypothalamic structure differs by chronotype in BD, with chronotype-related associations localized to an anterior-inferior hypothalamic region implicated in circadian regulation. These findings support chronotype as a biologically meaningful dimension of variation in BD and provide neuroanatomical evidence linking circadian preference to circadian-relevant brain structure. Longitudinal and interventional studies will be important to clarify the temporal dynamics, underlying mechanisms, and potential clinical significance of these associations.

Abstract Background Chronic pain and depression are prevalent and burdensome conditions that frequently co-occur. Separate neuroimaging studies of each disorder suggest overlapping brain-structure alterations, however, relatively few studies have examined their comorbidity directly, and the neuroanatomical profile of co-occurring chronic pain and depression remains unclear. Methods Using UK Biobank data (n = 71,214), we conducted cross-sectional pairwise association analyses of brain structure (cortical measures, subcortical volumes, and white matter microstructure) comparing participants with current comorbid chronic pain and depression, current chronic pain only, current depression only, and controls. Results Compared with controls, the comorbidity group showed regional differences in cortical surface area and thickness (β range = −0.096 to 0.098, p FDR < 0.05), widespread lower cortical volume (β range = −0.096 to −0.050, p FDR < 0.05), lower thalamic (left: β = −0.048, p FDR = 0.038; right: β = −0.060, p FDR = 0.007), hippocampal (left: β = −0.062, p FDR = 0.035; right: β = −0.088, p FDR = 0.002) and left accumbens volume (β = −0.073, p FDR = 0.011), and evidence of widespread white matter microstructure alterations (fractional anisotropy: β range = −0.116 to −0.080, p FDR < 0.05; mean diffusivity: β range = 0.063 to 0.137, p FDR < 0.05). Pairwise comparisons with the disorder-specific groups also identified several alterations unique to the comorbidity group. Compared to controls, those with chronic pain only had widespread lower cortical surface area and volume (β range = −0.043 to −0.015, pFDR < 0.05), whereas non-comorbid depression showed more regionally specific lower cortical thickness and volume (β range = −0.140 to −0.062, pFDR < 0.05) and lower thalamic volume (left: β = −0.067, p FDR = 0.016; right: β = −0.066, p FDR = 0.015), alongside widespread white matter microstructure deficits (fractional anisotropy: β range = −0.104 to −0.083, p FDR < 0.05; mean diffusivity: β range = 0.079 to 0.149, p FDR < 0.05). Conclusion These results provide a robust characterisation of brain structure alterations in comorbid chronic pain and depression, highlighting a distinct neuroanatomical profile and advancing understanding of underlying neurobiology.

Abstract Background Chronic pain and depression are common disorders and leading causes of disability worldwide. They frequently co-occur and show substantial genetic correlation, indicating a shared genetic basis. However, the locus-specific architecture of this overlap remains poorly characterised and may yield important insights into the pathophysiology of their comorbidity. Methods Using the largest currently available European-ancestry genome-wide association studies of major depressive disorder (MDD) (n = 1,639,572) and multisite chronic pain (MCP) (n = 387,649), we estimated the polygenic overlap between traits using the bivariate causal mixture model (MiXeR), identified shared loci via conjunctional false discovery rate (conjFDR), and tested colocalisation with each trait and genetically regulated gene expression in 13 brain tissues. Results MiXeR analysis demonstrated a high degree of directionally consistent polygenic overlap between MDD and MCP. Subsequent conjFDR analysis identified 375 shared loci, 22 of which showed cross-trait colocalisation between the MDD and MCP signals. Gene mapping and enrichment of shared loci implicated several biological processes, including cadherin-mediated cell-cell adhesion and translational initiation. Gene expression colocalisation in brain tissue highlighted protein phosphatase 6 catalytic subunit ( PPP6C ) and suppressor of cancer cell invasion ( SCAI ) in both disorders. Conclusion Overall, these findings have enhanced our understanding of the complex relationship between chronic pain and depression by identifying potential shared molecular mechanisms that warrant further study as targets for prevention and treatment.

INTRODUCTION:Circadian dysfunction is involved in the pathophysiology of bipolar disorders (BD), and circadian-based interventions are gaining recognition in their management. Moreover, basic and epidemiologic research has generated findings inspiring circadian-informed self- and clinician-management strategies. Despite these gains, many Clinical Practice Guidelines and clinical training programs have not incorporated this evidence in their recommendations and curricula. This International Society for Bipolar Disorders (ISBD) Chronobiology and Chronotherapy Task Force position paper reports a Delphi-based expert consensus on what is essential for mental health clinicians to know about the chronobiology and chronotherapy of BD. METHODS:An initial pool of statements was extracted from academic and grey literature, and experts could suggest additional statements. Statements were rated on a 5-point scale ('essential'; 'important'; 'don't know/depends'; 'unimportant'; 'should not be included'). Consensus was reached when statements were rated as essential or important by ≥ 80% of experts. RESULTS:Thirty experts from 15 countries in Europe, North and South America, and the Asia Pacific participated (mean age of 55.3 years [SD = 11.8]; 40% female; 83% psychiatrists; mean clinical experience of 26 years [SD = 10.8]). Eight-hundred-and-thirty-seven statements were rated across three rounds. Consensus was reached on 342 statements spanning four major themes: basic circadian science; circadian health and disruption; chronobiology of BD; and six chronotherapies (e.g., protocols, outcomes, risks/contraindications). CONCLUSIONS:An expert consensus was obtained on the essential information about the chronobiology and chronotherapy of BD, intended to help clinicians optimise their management of BD. Dissemination of this knowledge is expected to enhance the training and efficacy of clinicians.

Antipsychotic treatment is associated with higher risk of major adverse cardiovascular events (MACEs), and risk may vary by multimorbidity and concomitant medications. Using Hong Kong electronic health records, we followed 26,274 MACE-free adults (18-65 years) with multimorbidity who initiated antipsychotics, capturing demographics, chronic conditions, and prior medication use. We applied a conditional inference survival tree to define clinically interpretable risk profiles and compared ten time-to-event machine learning models using time-dependent ROC, calibration, and decision curve analyses. The highest-risk profile was age >48 years with chronic kidney disease, antibacterial/antiplatelet use, no antidepressant use, and no metastatic cancer (171.3 per 1,000 person-years). A random survival forest model showed the best discrimination (C-statistics 0.841, 0.835, and 0.824 at 1, 3, and 5 years, respectively), with age, antidepressant use, and chronic kidney disease as key predictors. These results support practical cardiovascular risk stratification for antipsychotic initiators with multimorbidity.

Bipolar disorder is defined by extreme variability in mood, activity and sleep/wake patterns. To date, studies of sleep and circadian parameters in bipolar disorder have predominantly relied on short term monitoring over 1–2 weeks, leaving a need for approaches that can assess individual-level changes in sleep, activity and mood with high levels of temporal granularity. In the AMBIENT-BD study, we will optimise low intensity ambient and passive data collection techniques. These methods will allow us to infer sleep and circadian timing patterns over extended time periods while developing novel data collection, sharing and analytical methods. In parallel, we will develop data management systems to streamline and optimise data sharing. At its core, our project involves an 18-month prospective study focused on the assessment of sleep/wake patterns and clinical and functional outcomes in individuals with bipolar disorder. Furthermore, in collaboration with Bipolar Scotland, we will deliver a knowledge exchange programme on the theme of ‘Sleep, circadian rhythms and bipolar disorder’. AMBIENT-BD will advance our understanding of symptom trajectories and mechanisms contributing to relapse in bipolar disorder, providing new insights for innovations in clinical management.

Abstract Background Chronic pain and depression are leading causes of disability and frequently co-occur. Depression presents with diverse symptoms, but despite this variability, the prevalence of individual depressive symptoms in chronic pain and the genetic and causal associations linking these traits remain poorly characterised. Methods Using data from 142,688 age- and sex-matched UK Biobank participants, we compared depressive symptom severity levels and item-level Patient Health Questionnaire-9 (PHQ-9) prevalences, spanning affective, cognitive and somatic domains, between participants with and without chronic pain. Using genome-wide association study (GWAS) summary statistics of multisite chronic pain (MCP), major depressive disorder (MDD), and individual symptoms of depression, genetic correlations and bidirectional causal effects between MCP and depressive phenotypes (MDD and individual symptoms) were estimated via linkage disequilibrium score regression (LDSC) and two-sample Mendelian randomisation (MR), respectively. Results Depression (at every severity level) was more common in the chronic pain group compared to controls, with the largest between-group difference for severe symptoms (7.50-fold increase). All individual depressive symptoms were at least 2.79 times as prevalent in chronic pain. Additionally, chronic pain had a significant and positive genetic correlation with MDD (r g = 0.59) and all depressive symptoms (r g = [0.24, 0.55]). MR supported a bidirectional causal association between MCP and MDD (MCP→MDD: OR = 1.85, p FDR < 0.001, MDD→MCP: β = 0.17, p FDR < 0.001). At the symptom level, MR indicated bidirectional effects between MCP and anhedonia (MCP→anhedonia: OR = 1.60, p FDR < 0.001, anhedonia→MCP: β = 0.08, p FDR = 0.005), and unidirectional effects of MCP on appetite/weight gain (OR = 1.90, p FDR = 0.022) and appetite/weight loss (OR = 1.63, p FDR = 0.005), concentration problems (OR = 1.63, p FDR = 0.044), and suicidal thoughts (OR = 1.46, p FDR = 0.021). Additionally, genetic liability to concentration problems was associated with a lower risk of MCP (β = -0.04, p FDR = 0.022). Conclusion Chronic pain is associated with a marked depressive burden spanning all symptom domains. Shared genetic architecture and symptom-specific causal pathways, particularly involving anhedonia, highlight potential targets for improved treatment of comorbid chronic pain and depression.

Importance: Major depressive disorder (MDD) is a complex psychiatric disorder influenced by genetic, social, and environmental factors. Family history, genome-wide polygenic scores, and childhood trauma are key predictors of MDD onset with distinct contributions. Objective: This study modelled the combined effects of family history of multiple psychiatric disorders, polygenic scores of multiple traits, and childhood trauma, alongside sociodemographic factors on MDD diagnosis and number of episodes. We aimed to build and externally validate predictive models for MDD risk and severity. Participants: We used data from the Genetic Links to Anxiety and Depression Study and other NIHR BioResource studies (GLAD+) and UK Biobank (UKB) collected between 2016 and 2023. Outcomes and measurements: MDD diagnosis followed DSM-5 criteria using online questionnaire data. Family history (Yes/No) was reported for up to 22 psychiatric disorders. Polygenic scores were calculated based on genome-wide association studies (n=22). Participants answered the five-item childhood trauma screener. We used elastic net regression with nested cross-validation to select the best predictors. Results: In GLAD+ (9,927 MDD cases, 4,452 controls), family history explained 17% of the MDD variance, followed by childhood trauma (11%), sociodemographics (10%), and polygenic scores (7%), resulting in 33% of the MDD variance (AUC-ROC=0.84). In UKB (40,667 MDD cases, 70,755 controls), family history explained 13% of the MDD variance, childhood trauma (7%), sociodemographics (6%), and polygenic scores (4%). Combined together, the predictors explained 23% of the variance (AUC-ROC=0.74). The top five individual predictors were family history of depression, childhood trauma, female sex, family history of anxiety, and the MDD polygenic score in both cohorts. The predictive models were externally well-validated across GLAD+ and UKB obtaining comparable predictive performance. Finally, when combined, the predictors explained 26% and 12% of the variance in the number of MDD episodes in GLAD+ and UKB respectively. Conclusions: Integrating family history, PRSs, ChT, and sociodemographic factors can predict risk of an MDD diagnosis and its recurrent course. This model may help identify individuals at high risk for depression in clinical settings, assess its severity, enable early diagnosis and potentially personalize treatment. ### Competing Interest Statement Prof Breen has received honoraria, research or conference grants and consulting fees from Illumina, Otsuka, and COMPASS Pathfinder Ltd. Prof Hotopf is the principal investigator of the RADAR-CNS consortium, an IMI public private partnership, and as such receives research funding from Janssen, UCB, Biogen, Lundbeck and MSD. Prof McIntosh has received research support from Eli Lilly, Janssen, and the Sackler Foundation, and has also received speaker fees from Illumina and Janssen. Prof Cleare has received honoraria for presentations from Janssen, Otsuka, COMPASS Pathways Plc., Viatris and Medscape, honoraria for consulting from Janssen, Otsuka and COMPASS Pathways Plc, research grant support from ADM Protexin Ltd and Beckley Psytech Ltd, and is President of the International Society for Affective Disorders (unpaid). Prof Zahn is a private psychiatrist service provider at The London Depression Institute, has collaborated with EMOTRA, EMIS PLC, Depsee Ltd, and Alloc Modulo Ltd. He has received honoraria from pharmaceutical companies (Lundbeck, Janssen) for scientific presentations and is a co-investigator on a Livanova-funded observational study of Vagus Nerve Stimulation for Depression. RZ is affiliated with the DOr Institute of Research and Education, Rio de Janeiro and advises the Scients Institute, USA. ### Funding Statement This work was supported by the National Institute for Health and Care Research (NIHR) BioResource [RG94028, RG85445], NIHR Biomedical Research Centre [IS-BRC-1215-20018], HSC R&D Division, Public Health Agency [COM/5516/18], MRC Mental Health Data Pathfinder Award (MC\_PC\_17,217), and the National Centre for Mental Health funding through Health and Care Research Wales. Johan Zvrskovec acknowledges funding from the National Institute for Health and Care Research (NIHR) Biomedical Research Centre and Guys and St Thomas NHS Foundation Trust. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The GLAD Study was approved by the London - Fulham Research Ethics Committee on 21st August 2018 (REC reference: 18/LO/1218) following a full review by the committee. The NIHR BioResource has been approved as a Research Tissue Bank by the East of England - Cambridge Central Committee (REC reference: 17/EE/0025). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors