Patient-specific severity of von Willebrand factor degradation identifies patients with a left ventricular assist device at high risk for bleeding.

BACKGROUND: Continuous-flow left ventricular assist devices (LVADs) cause an acquired von Willebrand factor (VWF) deficiency and bleeding. Models to risk-stratify for bleeding are urgently needed. We developed a model of continuous-flow LVAD bleeding risk from patient-specific severity of VWF degradation. METHODS: In a prospective, longitudinal cohort study, paired blood samples were obtained from patients (n = 67) with a continuous-flow LVAD before and during support. After 640 ± 395 days, patients were categorized as all-cause bleeders, gastrointestinal (GI) bleeders, or nonbleeders. VWF multimers and VWF clotting function were evaluated to determine bleeding risk. RESULTS: Of 67 patients, 34 (51%) experienced bleeding, 26 (39%) experienced GI bleeding, and 33 (49%) did not bleed. In all patients, LVAD support significantly reduced high-molecular-weight VWF multimers (P < .001). Bleeders exhibited greater loss of high-molecular-weight VWF multimers (mean ± standard deviation, -10 ± 5% vs -7 ± 4%, P = .008) and reduced VWF clotting function versus nonbleeders (median [interquartile range], -12% [-31% to 4%] vs 0% [-9 to 26%], P = .01). A combined metric of VWF multimers and VWF function generated the All-Cause Bleeding Risk Score, which stratified bleeders versus nonbleeders (86 ± 56% vs 41 ± 48%, P < .001) with a positive predictive value of 86% (95% confidence interval, 66%-95%) and diagnostic odds ratio of 11 (95% confidence interval, 2.9-44). A separate GI Bleeding Risk Score stratified GI bleeders versus nonbleeders (202 ± 114 vs 120 ± 86, P = .003) with a positive predictive value of 88% (64%-97%) and diagnostic odds ratio of 18 (3.1-140). CONCLUSIONS: The severity of loss of VWF multimers and VWF clotting function generated Bleeding Risk Scores with high predictive value for LVAD-associated bleeding. This model may guide personalized antithrombotic therapy and patient surveillance.

Genome-Wide Association Study of Treatment-Resistant Depression: Shared Biology With Metabolic Traits.

OBJECTIVE: Treatment-resistant depression (TRD) occurs in roughly one-third of all individuals with major depressive disorder (MDD). Although research has suggested a significant common variant genetic component of liability to TRD, with heritability estimated at 8% when compared with non-treatment-resistant MDD, no replicated genetic loci have been identified, and the genetic architecture of TRD remains unclear. A key barrier to this work has been the paucity of adequately powered cohorts for investigation, largely because of the challenge in prospectively investigating this phenotype. The objective of this study was to perform a well-powered genetic study of TRD. METHODS: Using receipt of electroconvulsive therapy (ECT) as a surrogate for TRD, the authors applied standard machine learning methods to electronic health record data to derive predicted probabilities of receiving ECT. These probabilities were then applied as a quantitative trait in a genome-wide association study of 154,433 genotyped patients across four large biobanks. RESULTS: Heritability estimates ranged from 2% to 4.2%, and significant genetic overlap was observed with cognition, attention deficit hyperactivity disorder, schizophrenia, alcohol and smoking traits, and body mass index. Two genome-wide significant loci were identified, both previously implicated in metabolic traits, suggesting shared biology and potential pharmacological implications. CONCLUSIONS: This work provides support for the utility of estimation of disease probability for genomic investigation and provides insights into the genetic architecture and biology of TRD.