The genetics of severe depression.

Genome-wide association studies (GWASs) of major depressive disorder (MDD) have recently achieved extremely large sample sizes and yielded substantial numbers of genome-wide significant loci. Because of the approach to ascertainment and assessment in many of these studies, some of these loci appear to be associated with dysphoria rather than with MDD, potentially decreasing the clinical relevance of the findings. An alternative approach to MDD GWAS is to focus on the most severe forms of MDD, with the hope that this will enrich for loci of larger effect, rendering their identification plausible, and providing potentially more clinically actionable findings. Here we review the genetics of severe depression by using clinical markers of severity including: age of onset, recurrence, degree of impairment, and treatment with ECT. There is evidence for increased family-based and Single Nucleotide Polymorphism (SNP)-based estimates of heritability in recurrent and early-onset illness as well as severe functional impariment. GWAS have been performed looking at severe forms of MDD and a few genome-wide loci have been identified. Several whole exome sequencing studies have also been performed, identifying associated rare variants. Although these findings have not yet been rigorously replicated, the elevated heritability seen in severe MDD phenotypes suggests the value of pursuing additional genome-wide interrogation of samples from this population. The challenge now is generating a cohort of adequate size with consistent phenotyping that will allow for careful and robust classifications and distinctions to be made. We are currently pursuing such a strategy in our 50-site worldwide Gen-ECT-ics consortium.

Artificial intelligence and increasing misinformation.

With the recent advances in artificial intelligence (AI), patients are increasingly exposed to misleading medical information. Generative AI models, including large language models such as ChatGPT, create and modify text, images, audio and video information based on training data. Commercial use of generative AI is expanding rapidly and the public will routinely receive messages created by generative AI. However, generative AI models may be unreliable, routinely make errors and widely spread misinformation. Misinformation created by generative AI about mental illness may include factual errors, nonsense, fabricated sources and dangerous advice. Psychiatrists need to recognise that patients may receive misinformation online, including about medicine and psychiatry.

Artificial intelligence and cybercrime: implications for individuals and the healthcare sector.

The malicious use of artificial intelligence is growing rapidly, creating major security threats for individuals and the healthcare sector. Individuals with mental illness may be especially vulnerable. Healthcare provider data are a prime target for cybercriminals. There is a need to improve cybersecurity to detect and prevent cyberattacks against individuals and the healthcare sector, including the use of artificial intelligence predictive tools.

Dysregulated placental expression of kynurenine pathway enzymes is associated with inflammation and depression in pregnancy.

BACKGROUND: Perinatal depression (including antenatal-, postnatal-, and depression that spans both timepoints) is a prevalent disorder with high morbidity that affects both mother and child. Even though the full biological blueprints of perinatal depression remain incomplete, multiple studies indicate that, at least for antenatal depression, the disorder has an inflammatory component likely linked to a dysregulation of the enzymatic kynurenine pathway. The production of neuroactive metabolites in this pathway, including quinolinic acid (QUIN), is upregulated in the placenta due to the multiple immunological roles of the metabolites during pregnancy. Since neuroactive metabolites produced by the pathway also may affect mood by directly affecting glutamate neurotransmission, we sought to investigate whether the placental expression of kynurenine pathway enzymes controlling QUIN production was associated with both peripheral inflammation and depressive symptoms during pregnancy. METHODS: 68 placentas obtained at birth were analyzed using qPCR to determine the expression of kynurenine pathway enzymes. Cytokines and metabolites were quantified in plasma using high-sensitivity electroluminescence and ultra-performance liquid chromatography, respectively. Maternal depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS) throughout pregnancy and the post-partum. Associations between these factors were assessed using robust linear regression with ranked enzymes. RESULTS: Low placental quinolinate phosphoribosyl transferase (QPRT), the enzyme responsible for degrading QUIN, was associated with higher IL-6 and higher QUIN/kynurenic acid ratios at the 3rd trimester. Moreover, women with severe depressive symptoms in the 3rd trimester had significantly lower placental expression of both QPRT and 2-amino-3-carboxymuconate-6-semialdehyde decarboxylase (ACMSD); impaired activity of these two enzymes leads to QUIN accumulation. CONCLUSION: Overall, our data support that a compromised placental environment, featuring low expression of critical kynurenine pathway enzymes is associated with increased levels of plasma cytokines and the dysregulated kynurenine metabolite pattern observed in depressed women during pregnancy.

Integrative transcriptome- and DNA methylation analysis of brain tissue from the temporal pole in suicide decedents and their controls.

Suicide rates have increased steadily world-wide over the past two decades, constituting a serious public health crisis that creates a significant burden to affected families and the society as a whole. Suicidal behavior involves a multi-factorial etiology, including psychological, social and biological factors. Since the molecular neural mechanisms of suicide remain vastly uncharacterized, we examined transcriptional- and methylation profiles of postmortem brain tissue from subjects who died from suicide as well as their neurotypical healthy controls. We analyzed temporal pole tissue from 61 subjects, largely free from antidepressant and antipsychotic medication, using RNA-sequencing and DNA-methylation profiling using an array that targets over 850,000 CpG sites. Expression of NPAS4, a key regulator of inflammation and neuroprotection, was significantly downregulated in the suicide decedent group. Moreover, we identified a total of 40 differentially methylated regions in the suicide decedent group, mapping to seven genes with inflammatory function. There was a significant association between NPAS4 DNA methylation and NPAS4 expression in the control group that was absent in the suicide decedent group, confirming its dysregulation. NPAS4 expression was significantly associated with the expression of multiple inflammatory factors in the brain tissue. Overall, gene sets and pathways closely linked to inflammation were significantly upregulated, while specific pathways linked to neuronal development were suppressed in the suicide decedent group. Excitotoxicity as well as suppressed oligodendrocyte function were also implicated in the suicide decedents. In summary, we have identified central nervous system inflammatory mechanisms that may be active during suicidal behavior, along with oligodendrocyte dysfunction and altered glutamate neurotransmission. In these processes, NPAS4 might be a master regulator, warranting further studies to validate its role as a potential biomarker or therapeutic target in suicidality.

Implications of Online Self-Diagnosis in Psychiatry.

Online self-diagnosis of psychiatric disorders by the general public is increasing. The reasons for the increase include the expansion of Internet technologies and the use of social media, the rapid growth of direct-to-consumer e-commerce in healthcare, and the increased emphasis on patient involvement in decision making. The publicity given to artificial intelligence (AI) has also contributed to the increased use of online screening tools by the general public. This paper aims to review factors contributing to the expansion of online self-diagnosis by the general public, and discuss both the risks and benefits of online self-diagnosis of psychiatric disorders. A narrative review was performed with examples obtained from the scientific literature and commercial articles written for the general public. Online self-diagnosis of psychiatric disorders is growing rapidly. Some people with a positive result on a screening tool will seek professional help. However, there are many potential risks for patients who self-diagnose, including an incorrect or dangerous diagnosis, increased patient anxiety about the diagnosis, obtaining unfiltered advice on social media, using the self-diagnosis to self-treat, including online purchase of medications without a prescription, and technical issues including the loss of privacy. Physicians need to be aware of the increase in self-diagnosis by the general public and the potential risks, both medical and technical. Psychiatrists must recognize that the general public is often unaware of the challenging medical and technical issues involved in the diagnosis of a mental disorder, and be ready to treat patients who have already obtained an online self-diagnosis.

Perceived Barriers to Using Neurostimulation: A National Survey of Psychiatrists, Patients, Caregivers, and the General Public.

OBJECTIVES: Neurostimulation interventions often face heightened barriers limiting patient access. The objective of this study is to examine different stakeholders' perceived barriers to using different neurostimulation interventions for depression. METHODS: We administered national surveys with an embedded experiment to 4 nationwide samples of psychiatrists (n = 505), people diagnosed with depression (n = 1050), caregivers of people with depression (n = 1026), and members of the general public (n = 1022). We randomly assigned respondents to 1 of 8 conditions using a full factorial experimental design: 4 neurostimulation modalities (electroconvulsive therapy [ECT], repetitive transcranial magnetic stimulation [rTMS], deep brain stimulation [DBS], or adaptive brain implants [ABIs]) by 2 depression severity levels (moderate or severe). We asked participants to rank from a list what they perceived as the top 3 barriers to using their assigned intervention. We analyzed the data with analysis of variance and logistic regression. RESULTS: Nonclinicians most frequently reported "limited evidence of the treatment's effectiveness" and "lack of understanding of intervention" as their top 2 most important practical barriers to using ECT and TMS, respectively. Compared with nonclinicians, psychiatrists were more likely to identify "stigma about treatment" for ECT and "lack of insurance coverage" for TMS as the most important barriers. CONCLUSIONS: Overall, psychiatrists' perceptions of the most important barriers to using neurostimulation interventions were significantly different than those of nonclinicians. Perceived barriers were significantly different for implantable DBS and ABI) versus nonimplantable (rTMS and ECT) neurostimulation interventions. Better understanding of how these barriers vary by neurostimulation and stakeholder group could help us address structural and attitudinal barriers to effective use of these interventions.

Relapse prevention through health technology program reduces hospitalization in schizophrenia.

BACKGROUND: Psychiatric hospitalization is a major driver of cost in the treatment of schizophrenia. Here, we asked whether a technology-enhanced approach to relapse prevention could reduce days spent in a hospital after discharge. METHODS: The Improving Care and Reducing Cost (ICRC) study was a quasi-experimental clinical trial in outpatients with schizophrenia conducted between 26 February 2013 and 17 April 2015 at 10 different sites in the USA in an outpatient setting. Patients were between 18 and 60 years old with a diagnosis of schizophrenia, schizoaffective disorder, or psychotic disorder not otherwise specified. Patients received usual care or a technology-enhanced relapse prevention program during a 6-month period after discharge. The health technology program included in-person, individualized relapse prevention planning with treatments delivered via smartphones and computers, as well as a web-based prescriber decision support program. The main outcome measure was days spent in a psychiatric hospital during 6 months after discharge. RESULTS: The study included 462 patients, of which 438 had complete baseline data and were thus used for propensity matching and analysis. Control participants (N = 89; 37 females) were enrolled first and received usual care for relapse prevention followed by 349 participants (128 females) who received technology-enhanced relapse prevention. During 6-month follow-up, 43% of control and 24% of intervention participants were hospitalized (χ2 = 11.76, p<0.001). Days of hospitalization were reduced by 5 days (mean days: b = -4.58, 95% CI -9.03 to -0.13, p = 0.044) in the intervention condition compared to control. CONCLUSIONS: These results suggest that technology-enhanced relapse prevention is an effective and feasible way to reduce rehospitalization days among patients with schizophrenia.

Blood-based biomarkers of antidepressant response to ketamine and esketamine: A systematic review and meta-analysis.

(R,S)-ketamine (ketamine) and its enantiomer (S)-ketamine (esketamine) can produce rapid and substantial antidepressant effects. However, individual response to ketamine/esketamine is variable, and there are no well-accepted methods to differentiate persons who are more likely to benefit. Numerous potential peripheral biomarkers have been reported, but their current utility is unclear. We conducted a systematic review/meta-analysis examining the association between baseline levels and longitudinal changes in blood-based biomarkers, and response to ketamine/esketamine. Of the 5611 citations identified, 56 manuscripts were included (N = 2801 participants), and 26 were compatible with meta-analytical calculations. Random-effect models were used, and effect sizes were reported as standardized mean differences (SMD). Our assessments revealed that more than 460 individual biomarkers were examined. Frequently studied groups included neurotrophic factors (n = 15), levels of ketamine and ketamine metabolites (n = 13), and inflammatory markers (n = 12). There were no consistent associations between baseline levels of blood-based biomarkers, and response to ketamine. However, in a longitudinal analysis, ketamine responders had statistically significant increases in brain-derived neurotrophic factor (BDNF) when compared to pre-treatment levels (SMD [95% CI] = 0.26 [0.03, 0.48], p = 0.02), whereas non-responders showed no significant changes in BDNF levels (SMD [95% CI] = 0.05 [-0.19, 0.28], p = 0.70). There was no consistent evidence to support any additional longitudinal biomarkers. Findings were inconclusive for esketamine due to the small number of studies (n = 2). Despite a diverse and substantial literature, there is limited evidence that blood-based biomarkers are associated with response to ketamine, and no current evidence of clinical utility.

Telepsychiatry in an Era of Digital Mental Health Startups.

PURPOSE OF REVIEW: Telepsychiatry practiced by psychiatrists is evidence-based, regulated, private, and effective in diverse settings. The use of telemedicine has grown since the COVID-19 pandemic as people routinely obtain more healthcare services online. At the same time, there has been a rapid increase in the number of digital mental health startups that offer various services including online therapy and access to prescription medications. These digital mental health firms advertise directly to the consumer primarily through digital advertising. The purpose of this narrative review is to contrast traditional telepsychiatry and the digital mental health market related to online therapy. RECENT FINDINGS: In contrast to standard telepsychiatry, most of the digital mental health startups are unregulated, have unproven efficacy, and raise concerns related to self-diagnosis, self-medicating, and inappropriate prescribing. The role of digital mental health firms for people with serious mental illness has not been determined. There are inadequate privacy controls for the digital mental health firms, including for online therapy. We live in an age where there is widespread admiration for technology entrepreneurs and increasing emphasis on the role of the patient as a consumer. Yet, the business practices of digital mental health startups may compromise patient safety for profits. There is a need to address issues with the digital mental health startups and to educate patients about the differences between standard medical care and digital mental health products.

Ulotaront: review of preliminary evidence for the efficacy and safety of a TAAR1 agonist in schizophrenia.

Ulotaront is a trace amine-associated receptor 1 (TAAR1) agonist in Phase 3 clinical development for the treatment of schizophrenia. Ulotaront was discovered through a unique, target-agnostic approach optimized to identify drug candidates lacking D2 and 5-HT2A receptor antagonism, while demonstrating an antipsychotic-like phenotypic profile in vivo. The mechanism of action (MOA) of ulotaront is thought to be mediated by agonism at TAAR1 and serotonin 5-HT1A receptors. Ulotaront has completed two Phase 2 trials (4-week acute study and 26-week open-label extension) which led to Breakthrough Therapy Designation from the US Food and Drug Administration for the treatment of schizophrenia. In the double-blind, placebo-controlled, acute study, ulotaront was associated with significant (p < 0.001) improvement in Positive and Negative Syndrome Scale (PANSS) total score (effect size [ES]: 0.45), with improvements vs. placebo also observed across secondary endpoints. Post-hoc analyses of the acute trial revealed additional evidence to support the effect of ulotaront on negative symptoms. In the 4-week study, ulotaront was well-tolerated, with an incidence of adverse events (AEs) numerically lower compared to placebo (45.8% vs. 50.4%; with a number needed to harm [NNH] for individual ulotaront AEs all > 40). The open-label extension demonstrated further improvement across schizophrenia symptoms and confirmed the tolerability of ulotaront, with a 6-month completion rate of 67%. Based on current data, ulotaront shows potential to be a first-in-class TAAR1 agonist for the treatment of schizophrenia with a safety and efficacy profile distinct from current antipsychotics.

Challenges and Ethical Considerations to Successfully Implement Artificial Intelligence in Clinical Medicine and Neuroscience: a Narrative Review.

This narrative review discusses how the safe and effective use of clinical artificial intelligence (AI) prediction tools requires recognition of the importance of human intelligence. Human intelligence, creativity, situational awareness, and professional knowledge, are required for successful implementation. The implementation of clinical AI prediction tools may change the workflow in medical practice resulting in new challenges and safety implications. Human understanding of how a clinical AI prediction tool performs in routine and exceptional situations is fundamental to successful implementation. Physicians must be involved in all aspects of the selection, implementation, and ongoing product monitoring of clinical AI prediction tools.

Expectations for Artificial Intelligence (AI) in Psychiatry.

PURPOSE OF REVIEW: Artificial intelligence (AI) is often presented as a transformative technology for clinical medicine even though the current technology maturity of AI is low. The purpose of this narrative review is to describe the complex reasons for the low technology maturity and set realistic expectations for the safe, routine use of AI in clinical medicine. RECENT FINDINGS: For AI to be productive in clinical medicine, many diverse factors that contribute to the low maturity level need to be addressed. These include technical problems such as data quality, dataset shift, black-box opacity, validation and regulatory challenges, and human factors such as a lack of education in AI, workflow changes, automation bias, and deskilling. There will also be new and unanticipated safety risks with the introduction of AI. The solutions to these issues are complex and will take time to discover, develop, validate, and implement. However, addressing the many problems in a methodical manner will expedite the safe and beneficial use of AI to augment medical decision making in psychiatry.

National Network of Depression Centers' Recommendations on Harmonizing Clinical Documentation of Electroconvulsive Therapy.

ABSTRACT: Electroconvulsive therapy (ECT) is a highly therapeutic and cost-effective treatment for severe and/or treatment-resistant major depression. However, because of the varied clinical practices, there is a great deal of heterogeneity in how ECT is delivered and documented. This represents both an opportunity to study how differences in implementation influence clinical outcomes and a challenge for carrying out coordinated quality improvement and research efforts across multiple ECT centers. The National Network of Depression Centers, a consortium of 26+ US academic medical centers of excellence providing care for patients with mood disorders, formed a task group with the goals of promoting best clinical practices for the delivery of ECT and to facilitate large-scale, multisite quality improvement and research to advance more effective and safe use of this treatment modality. The National Network of Depression Centers Task Group on ECT set out to define best practices for harmonizing the clinical documentation of ECT across treatment centers to promote clinical interoperability and facilitate a nationwide collaboration that would enable multisite quality improvement and longitudinal research in real-world settings. This article reports on the work of this effort. It focuses on the use of ECT for major depressive disorder, which accounts for the majority of ECT referrals in most countries. However, most of the recommendations on clinical documentation proposed herein will be applicable to the use of ECT for any of its indications.

Technology-Facilitated Depression Self-Management Linked with Lay Supporters and Primary Care Clinics: Randomized Controlled Trial in a Low-Income Sample.

Purpose: To test whether technology-facilitated self-management support improves depression in primary care settings. Methods: We randomized 204 low-income primary care patients who had at least moderate depressive symptoms to intervention or control. Intervention participants received 12 months of weekly automated interactive voice response telephone calls that assessed their symptom severity and provided self-management strategies. Their patient-nominated supporter (CarePartner) received corresponding guidance on self-management support, and their primary care team received urgent notifications. Those randomized to enhanced usual care received printed generic self-management instructions. Results: One-year attrition rate was 14%. By month 6, symptom severity on the Patient Health Questionnaire-9 (PHQ-9) decreased 2.5 points more in the intervention arm than in the control arm (95% CI -4.2 to -0.8, p = 0.003). This benefit was similar at month 12 (p = 0.004). Intervention was also over twice as likely to lead to ≥50% reduction in symptom severity by month 6 (OR = 2.2 (1.1, 4.7)) and a decrease of ≥5 PHQ-9 points by month 12 (OR = 2.3 (1.2, 4.4)). Conclusions: Technology-facilitated self-management guidance with lay support and clinician notifications improves depression for primary care patients. Subsequent research should examine implementation and generalization to other chronic conditions. clinicaltrials.gov, identifier NCT01834534.

Contributions of common genetic variants to risk of schizophrenia among individuals of African and Latino ancestry.

Schizophrenia is a common, chronic and debilitating neuropsychiatric syndrome affecting tens of millions of individuals worldwide. While rare genetic variants play a role in the etiology of schizophrenia, most of the currently explained liability is within common variation, suggesting that variation predating the human diaspora out of Africa harbors a large fraction of the common variant attributable heritability. However, common variant association studies in schizophrenia have concentrated mainly on cohorts of European descent. We describe genome-wide association studies of 6152 cases and 3918 controls of admixed African ancestry, and of 1234 cases and 3090 controls of Latino ancestry, representing the largest such study in these populations to date. Combining results from the samples with African ancestry with summary statistics from the Psychiatric Genomics Consortium (PGC) study of schizophrenia yielded seven newly genome-wide significant loci, and we identified an additional eight loci by incorporating the results from samples with Latino ancestry. Leveraging population differences in patterns of linkage disequilibrium, we achieve improved fine-mapping resolution at 22 previously reported and 4 newly significant loci. Polygenic risk score profiling revealed improved prediction based on trans-ancestry meta-analysis results for admixed African (Nagelkerke's R2 = 0.032; liability R2 = 0.017; P < 10-52), Latino (Nagelkerke's R2 = 0.089; liability R2 = 0.021; P < 10-58), and European individuals (Nagelkerke's R2 = 0.089; liability R2 = 0.037; P < 10-113), further highlighting the advantages of incorporating data from diverse human populations.

They Affect the Person, but for Better or Worse? Perceptions of Electroceutical Interventions for Depression Among Psychiatrists, Patients, and the Public.

Responding to reports of cases of personality change following deep brain stimulation, neuroethicists have debated the nature and ethical implications of these changes. Recently, this literature has been challenged as being overblown and therefore potentially an impediment to patients accessing needed treatment. We interviewed 16 psychiatrists, 16 patients with depression, and 16 members of the public without depression, all from the Midwestern United States, about their views on how three electroceutical interventions (deep brain stimulation, electroconvulsive therapy, and transcranial magnetic stimulation) used to treat depression might affect the self. Participants were also asked to compare the electroceuticals' effects on the self with the effects of commonly used depression treatments (psychotherapy and pharmaceuticals). Using qualitative content analysis, we found that participants' views on electroceuticals' potential effects on the self mainly focused on treatment effectiveness and side effects. Our results have implications for both theoretical discussions in neuroethics and clinical practice in psychiatry.

Beyond the Cuckoo's Nest: Patient and Public Attitudes about Psychiatric Electroceutical Interventions.

Recent research emphasizes the role of psychiatric electroceutical interventions (PEIs), bioelectronic treatments that employ electrical stimulation to affect and modify brain function, to effectively treat psychiatric disorders. We sought to examine attitudes about three PEIs-electroconvulsive therapy, transcranial magnetic stimulation, and deep brain stimulation-among patients with depression and members of the general public. As part of a larger study to assess different stakeholders' attitudes about PEIs, we conducted semi-structured key informant interviews with 16 individuals living with depression and 16 non-depressive members of the general public. We used a purposive sampling approach to recruit potential participants based on eligibility criteria. We performed qualitative content analysis of interview transcripts. Participants from both groups expressed an overall cautionary attitude towards PEIs, yet there were mixed attitudes in both groups. Patients commonly described electroconvulsive therapy as scary, traumatic, or intense, while members of the general public often referenced the treatment's negative portrayal in One Flew over the Cuckoo's Nest. Patients and the general public saw transcranial magnetic stimulation as a potentially viable option, but in most cases only if medication was not effective. Deep brain stimulation attitudes were predominantly negative among patients and cautionary among public. The overall cautionary attitudes towards PEIs, together with the technological features and social aspects underlying those attitudes, highlight the need for unbiased education to fill the gaps in knowledge and inform perceptions of those who may benefit from these treatments.

Inflammation and kynurenine pathway dysregulation in post-partum women with severe and suicidal depression.

Depression during pregnancy and the post-partum is common, with severe cases resulting in suicidal behavior. Despite the urgent and unmet medical need, the biological underpinnings of peri-partum depression remain unclear. It has been suggested that it is triggered by dynamic changes of the immune system during pregnancy and at delivery. Therefore, we investigated whether a pro-inflammatory status in plasma, together with changes in the kynurenine pathway activity, is associated with the development of severe depression and suicidal behavior in the post-partum. Our cross-sectional study targets a unique, understudied population in which the pronounced severity of symptoms required hospitalization. We analyzed plasma IL-1ß, IL-2, IL-6, IL-8, TNF-α, tryptophan, serotonin, kynurenine, nicotinamide, quinolinic- and kynurenic acids in post-partum women diagnosed with peripartum onset depression (PPD) and healthy controls (n = 165). We assessed depression severity using the Edinburgh Postnatal Depression Scale and suicidality using the Columbia-Suicide Severity Rating Scale. We found that increased plasma IL-6 and IL-8 and reductions of serotonin, IL-2 and quinolinic acid were associated with the severity of depressive symptoms and increased the risk for PPD. Moreover, women with lower serotonin levels were at an increased risk for suicidal behavior, even when adjusting for depression severity, psychosocial factors, age BMI, and medication. Our results indicate that severe depression in the post-partum involves dysregulation of the immune response and the kynurenine pathway, with a concomitant reduction in serotonin levels. We propose that inflammatory cytokines and the kynurenine pathway are potential treatment targets in PPD, opening up the possibility of novel therapeutic strategies targeting the peripartum.

International Consortium on the Genetics of Electroconvulsive Therapy and Severe Depressive Disorders (Gen-ECT-ic).

Recent genome-wide association studies have demonstrated that the genetic burden associated with depression correlates with depression severity. Therefore, conducting genetic studies of patients at the most severe end of the depressive disorder spectrum, those with treatment-resistant depression and who are prescribed electroconvulsive therapy (ECT), could lead to a better understanding of the genetic underpinnings of depression. Despite ECT being one of the most effective forms of treatment for severe depressive disorders, it is usually placed at the end of treatment algorithms of current guidelines. This is perhaps because ECT has controlled risk and logistical demands including use of general anaesthesia and muscle relaxants and side-effects such as short-term memory impairment. Better understanding of the genetics and biology of ECT response and of cognitive side-effects could lead to more personalized treatment decisions. To enhance the understanding of the genomics of severe depression and ECT response, researchers and ECT providers from around the world and from various depression or ECT networks, but not limited to, such as the Psychiatric Genomics Consortium, the Clinical Alliance and Research in ECT, and the National Network of Depression Centers have formed the Genetics of ECT International Consortium (Gen-ECT-ic). Gen-ECT-ic will organize the largest clinical and genetic collection to date to study the genomics of severe depressive disorders and response to ECT, aiming for 30,000 patients worldwide using a GWAS approach. At this stage it will be the largest genomic study on treatment response in depression. Retrospective data abstraction and prospective data collection will be facilitated by a uniform data collection approach that is flexible and will incorporate data from many clinical practices. Gen-ECT-ic invites all ECT providers and researchers to join its efforts.