Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).

We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.

Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.

Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.

We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BPD and, importantly, BPD-D from MDD.

Metabolic and bariatric surgery (MBS) is safe and efficacious for adolescents with severe obesity. Pairing MBS with behavioral lifestyle interventions may be effective for optimizing treatment outcomes. However, no standardized program exists. Adolescent perspectives are critical to understanding how to design interventions to enhance engagement, sustain motivation, and meet informational needs for pre- and post-MBS self-management behaviors. The aim of this study was to develop an MBS lifestyle support intervention built on evidence-based content with input from adolescents and their families.

A mixed-methods design identified adolescent preferences for MBS lifestyle support. Data were collected from a racially and ethnically diverse sample of adolescents (N = 17, 76% females, 24% males 41.2% non-Hispanic Black, 41.2% Hispanic/Latino, 11.8% non-Hispanic White, 5.8% Other) and their mothers (N = 13, 38.4% Hispanic) recruited from an MBS clinic. Quantitative surveys and qualitative interviews assessed preferred types of pre-post MBS content, modality, frequency, and delivery platforms to inform the design of the intervention. Mixed methods data were triangulated to provide a comprehensive understanding of adolescent/parent preferences.

Adolescents prioritized eating well, managing stress, and maintaining motivation as desired support strategies. Parents identified parental support groups and nutrition guidance as priorities. Peer support and social media platforms were identified as key approaches for boosting motivation and engagement.

The patient voice is an important first step in understanding how, and whether behavioral lifestyle programs combined with MBS for weight management can be optimized. Adolescent preferences may enhance program fit and identify health behavior supports needed to sustain behavior change.

Develop and implement a system in the Veterans Health Administration (VA) to alert local medical center personnel in real time when an acute- or long-term care patient/resident is admitted to their facility with a history of colonization or infection with a multidrug-resistant organism (MDRO) previously identified at any VA facility across the nation.

An algorithm was developed to extract clinical microbiology and local facility census data from the VA Corporate Data Warehouse initially targeting carbapenem-resistant Enterobacterales (CRE) and methicillin-resistant Staphylococcus aureus (MRSA). The algorithm was validated with chart review of CRE cases from 2010-2018, trialed and refined in 24 VA healthcare systems over two years, expanded to other MDROs and implemented nationwide on 4/2022 as “VA Bug Alert” (VABA). Use through 8/2023 was assessed.

VABA performed well for CRE with recall of 96.3%, precision of 99.8%, and F1 score of 98.0%. At the 24 trial sites, feedback was recorded for 1,011 admissions with a history of CRE (130), MRSA (814), or both (67). Among Infection Preventionists and MDRO Prevention Coordinators, 338 (33%) reported being previously unaware of the information, and of these, 271 (80%) reported they would not have otherwise known this information. By fourteen months after nationwide implementation, 113/130 (87%) VA healthcare systems had at least one VABA subscriber.

A national system for alerting facilities in real-time of patients admitted with an MDRO history was successfully developed and implemented in VA. Next steps include understanding facilitators and barriers to use and coordination with non-VA facilities nationwide.

There is emerging evidence of heterogeneity within treatment-resistance schizophrenia (TRS), with some people not responding to antipsychotic treatment from illness onset and a smaller group becoming treatment-resistant after an initial response period. It has been suggested that these groups have different aetiologies. Few studies have investigated socio-demographic and clinical differences between early and late onset of TRS.

This study aims to investigate socio-demographic and clinical correlates of late-onset of TRS.

Using data from the electronic health records of the South London and Maudsley, we identified a cohort of people with TRS. Regression analyses were conducted to identify correlates of the length of treatment to TRS. Analysed predictors include gender, age, ethnicity, positive symptoms severity, problems with activities of daily living, psychiatric comorbidities, involuntary hospitalisation and treatment with long-acting injectable antipsychotics.

We observed a continuum of the length of treatment until TRS presentation. Having severe hallucinations and delusions at treatment start was associated shorter duration of treatment until the presentation of TRS.

Our findings do not support a clear cut categorisation between early and late TRS, based on length of treatment until treatment resistance onset. More severe positive symptoms predict earlier onset of treatment resistance.

DFdF, GKS, EF and IR have received research funding from Janssen and H. Lundbeck A/S. RDH and HS have received research funding from Roche, Pfizer, Janssen and Lundbeck. SES is employed on a grant held by Cardiff University from Takeda Pharmaceutical Comp

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Major depressive disorder (MDD) is a leading cause of disease burden worldwide, with lifetime prevalence in the United States of 17%. Here we present the results of the first prospective, large-scale, patient- and rater-blind, randomized controlled trial evaluating the clinical importance of achieving congruence between combinatorial pharmacogenomic (PGx) testing and medication selection for MDD.

1,167 outpatients diagnosed with MDD and an inadequate response to ≥1 psychotropic medications were enrolled and randomized 1:1 to a Treatment as Usual (TAU) arm or PGx-guided care arm. Combinatorial PGx testing categorized medications in three groups based on the level of gene-drug interactions: use as directed, use with caution, or use with increased caution and more frequent monitoring. Patient assessments were performed at weeks 0 (baseline), 4, 8, 12 and 24. Patients, site raters, and central raters were blinded in both arms until after week 8. In the guided-care arm, physicians had access to the combinatorial PGx test result to guide medication selection. Primary outcomes utilized the Hamilton Depression Rating Scale (HAM-D17) and included symptom improvement (percent change in HAM-D17 from baseline), response (50% decrease in HAM-D17 from baseline), and remission (HAM-D17<7) at the fully blinded week 8 time point. The durability of patient outcomes was assessed at week 24. Medications were considered congruent with PGx test results if they were in the ‘use as directed’ or ‘use with caution’ report categories while medications in the ‘use with increased caution and more frequent monitoring’ were considered incongruent. Patients who started on incongruent medications were analyzed separately according to whether they changed to congruent medications by week8.

At week 8, symptom improvement for individuals in the guided-care arm was not significantly different than TAU (27.2% versus 24.4%, p=0.11). However, individuals in the guided-care arm were more likely than those in TAU to achieve remission (15% versus 10%; p<0.01) and response (26% versus 20%; p=0.01). Remission rates, response rates, and symptom reductions continued to improve in the guided-treatment arm until the 24week time point. Congruent prescribing increased to 91% in the guided-care arm by week 8. Among patients who were taking one or more incongruent medication at baseline, those who changed to congruent medications by week 8 demonstrated significantly greater symptom improvement (p<0.01), response (p=0.04), and remission rates (p<0.01) compared to those who persisted on incongruent medications.

Combinatorial PGx testing improves short- and long-term response and remission rates for MDD compared to standard of care. In addition, prescribing congruency with PGx-guided medication recommendations is important for achieving symptom improvement, response, and remission for MDD patients.

Funding Acknowledgements: This study was supported by Assurex Health, Inc.

To identify ways that the built environment may support or disrupt safe doffing of personal protective equipment (PPE) in biocontainment units (BCU).

We observed interactions between healthcare workers (HCWs) and the built environment during 41 simulated PPE donning and doffing exercises.

The BCUs of 4 Ebola treatment facilities and 1 high-fidelity BCU mockup.

A total of 64 HCWs (41 doffing HCWs and 15 trained observers) participated in this study.

In each facility, we observed how the physical environment influences risky behaviors by the HCW. The environmental design impeded communication between trained observers (TOs) and HCWs because of limited window size or visual obstructions with louvers, which allowed unobserved errors. The size and configuration of the doffing area impacted HCW adherence to protocol, and lack of clear demarcation of zones resulted in HCWs inadvertently leaving the doffing area and stepping back into the contaminated areas. Lack of standard location for items resulted in equipment and supplies frequently shifting positions. Finally, different solutions for maintaining balance while removing shoe covers (ie, chair, hand grips, and step stool) had variable success. We identified the 5 key requirements that doffing areas must achieve to support safe doffing of PPE, and we developed a matrix of proposed design strategies that can be implemented to meet those requirements.

Simple, low-cost environmental design interventions can provide structure to support and improve HCW safety in BCUs. These interventions should be implemented in both current and future BCUs.