METHODS: An international working group (WG) of 37 experts and patients, and a steering group (SG) of 18 experts were convened from 14 countries. The project team (PT) identified outcomes by conducting a literature review, screening 1979 articles and reviewing the full texts of 547 of these articles. Semi-structured interviews and advisory groups were performed with the WG, SG and people living with HIV to add to the list of potentially relevant outcomes. The WG voted via a modified Delphi process - informed by six Zoom calls - to establish a core set of outcomes for use in clinical practice.
RESULTS: From 156 identified outcomes, consensus was reached to include three patient-reported outcomes, four clinician-reported measures and one administratively reported outcome; standardized measures were included. The WG also reached agreement to measure 22 risk-adjustment variables. This outcome set can be applied to any person living with HIV aged > 18 years.
CONCLUSIONS: Adoption of the HIV360 outcome set will enable healthcare providers to record, compare and integrate standardized metrics across treatment sites to drive quality improvement in HIV care.
METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors.
RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged.
CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.