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.

Previous research has found that measures of premorbid intellectual functioning may be predictive of performance on memory tasks among older adults (Duff, 2010). Intellectual functioning itself is correlated with education. The purpose of this study was to investigate the incremental validity of a measure of premorbid intellectual functioning over education levels to predict performance on the Virtual Environment Grocery Store (VEGS), which involves a simulated shopping experience assessing learning, memory, and executive functioning.

Older adults (N = 118, 60.2% female, age 60-90, M = 73.51, SD = 7.46) completed the Wechsler Test of Adult Reading and the VEGS.

WTAR and education level explained 9.4% of the variance in VEGS long delay free recall, F = 5.97, p = 0.003). WTAR was a significant predictor (ß = 0.25, p = 0.006), while level of education was not.

These results suggest that crystalized intelligence may benefit recall on a virtual reality shopping task.

Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians.

In total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance.

Three trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12.

Our findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies.

We aimed to describe the clinical characteristics of female patients presenting with premenstrual disorders to a tertiary service in the UK. We conducted a retrospective case-note review of referrals to the National Female Hormone Clinic from April 2014 to August 2020. Based on clinical assessment, we determined whether the patient met criteria for premenstrual dysphoric disorder or premenstrual exacerbation of an underlying psychiatric disorder.

Of 146 patients seen in clinic for premenstrual disorders, an ICD-10 psychiatric diagnosis was made in 130 (89.0%); a minority 16 (11.0%) did not have a psychiatric diagnosis. Following assessment, 94 patients (64.4%) met criteria for premenstrual dysphoric disorder and 67 (45.6%) had exacerbation of a psychiatric disorder.

Patients presenting to this specialist service had complex psychiatric comorbidity; almost half presented with exacerbation of a psychiatric disorder.

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.

To develop a pediatric research agenda focused on pediatric healthcare-associated infections and antimicrobial stewardship topics that will yield the highest impact on child health.

The study included 26 geographically diverse adult and pediatric infectious diseases clinicians with expertise in healthcare-associated infection prevention and/or antimicrobial stewardship (topic identification and ranking of priorities), as well as members of the Division of Healthcare Quality and Promotion at the Centers for Disease Control and Prevention (topic identification).

Using a modified Delphi approach, expert recommendations were generated through an iterative process for identifying pediatric research priorities in healthcare associated infection prevention and antimicrobial stewardship. The multistep, 7-month process included a literature review, interactive teleconferences, web-based surveys, and 2 in-person meetings.

A final list of 12 high-priority research topics were generated in the 2 domains. High-priority healthcare-associated infection topics included judicious testing for Clostridioides difficile infection, chlorhexidine (CHG) bathing, measuring and preventing hospital-onset bloodstream infection rates, surgical site infection prevention, surveillance and prevention of multidrug resistant gram-negative rod infections. Antimicrobial stewardship topics included β-lactam allergy de-labeling, judicious use of perioperative antibiotics, intravenous to oral conversion of antimicrobial therapy, developing a patient-level “harm index” for antibiotic exposure, and benchmarking and or peer comparison of antibiotic use for common inpatient conditions.

We identified 6 healthcare-associated infection topics and 6 antimicrobial stewardship topics as potentially high-impact targets for pediatric research.

Emergency Medical Services (EMS) systems have developed protocols for prehospital activation of the cardiac catheterization laboratory for patients with suspected ST-elevation myocardial infarction (STEMI) to decrease first-medical-contact-to-balloon time (FMC2B). The rate of “false positive” prehospital activations is high. In order to decrease this rate and expedite care for patients with true STEMI, the American Heart Association (AHA; Dallas, Texas USA) developed the Mission Lifeline PreAct STEMI algorithm, which was implemented in Los Angeles County (LAC; California USA) in 2015. The hypothesis of this study was that implementation of the PreAct algorithm would increase the positive predictive value (PPV) of prehospital activation.

This is an observational pre-/post-study of the effect of the implementation of the PreAct algorithm for patients with suspected STEMI transported to one of five STEMI Receiving Centers (SRCs) within the LAC Regional System. The primary outcome was the PPV of cardiac catheterization laboratory activation for percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG). The secondary outcome was FMC2B.

A total of 1,877 patients were analyzed for the primary outcome in the pre-intervention period and 405 patients in the post-intervention period. There was an overall decrease in cardiac catheterization laboratory activations, from 67% in the pre-intervention period to 49% in the post-intervention period (95% CI for the difference, -14% to -22%). The overall rate of cardiac catheterization declined in post-intervention period as compared the pre-intervention period, from 34% to 30% (95% CI, for the difference -7.6% to 0.4%), but actually increased for subjects who had activation (48% versus 58%; 95% CI, 4.6%-15.0%). Implementation of the PreAct algorithm was associated with an increase in the PPV of activation for PCI or CABG from 37.9% to 48.6%. The overall odds ratio (OR) associated with the intervention was 1.4 (95% CI, 1.1-1.8). The effect of the intervention was to decrease variability between medical centers. There was no associated change in average FMC2B.

The implementation of the PreAct algorithm in the LAC EMS system was associated with an overall increase in the PPV of cardiac catheterization laboratory activation.