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e23510 Background: There is minimal data comparing the prognostic models (PM) developed to predict recurrence of Gastrointestinal stromal tumors (GIST). Current PM include tumor size, location, and mitotic index (MI) but lack genotypic data. This analysis compares the performance of the National Institute of Health, Armed Forces Institute of Pathology, and Memorial Sloan Kettering Cancer Center models for predicting tumor recurrence with and without adjustment for c-kit Exon 11 mutation status (MS). Methods: This is an IRB-approved single-institution retrospective analysis. Adults with GIST mentioned in their medical records from 2014 – 2025 at the authors’ institution were identified. 330 patients with documented biopsy-proven GIST were included. Data was collected by manual review. PM were evaluated using multivariate analysis, adjusting for surgical resection, systemic therapy, and c-Kit exon 11 MS. Predictive performance was measured by area under the curve (AUC) and receiver operating characteristics (ROC) analysis. Results: Mean age at diagnosis was 64.6 years (SD =13.1 years). 46.7 % of patients were male. Primary GIST was most common in the stomach (63.9%) and small bowel (23.6%). Primary tumors were an average of 6.5 cm (SD 5.6 cm) with a MI of 6.6/50 HFU (SD = 13.4 50/HFU). Patients received resection (80.9%) and first-line systemic therapy with imatinib (43.3%). Recurrence occurred in 17.9% of patients. 19.4% of patients completed genetic testing, of which 51.6% were c-Kit exon 11 mutation positive. The predictive performance of all PM was not statistically different with (p value = 0.16) or without (p value = 0.18) adjustment for c-Kit exon 11 MS (Table 1). However, adjusting for c-Kit exon 11 MS improved AUC for all PM. Conclusions: Adjusting PM for c-KIT exon 11 status improved the predictive performance of all PM, although the results were not significant. This study found no significant difference in the performance of PM that predict GIST recurrence, which aligns with the one other study on this topic. Lack of significance may be due to a small sample size, which also limited the multivariate analysis. Including genotypes in PM that predict GIST recurrence should be further explored with larger multi-center datasets that can adjust for multiple mutations. Multivariate analysis comparing prognostic models for gastrointestinal stromal tumors at predicting recurrence with and without adjustment for c-KIT exon 11 genotypes using receiver operating characteristic. Without c-Kit exon 11 AUC (95% Confidence Interval) P value NIH 0.86 (0.81,0.90) 0.18 AFIP 0.87 (0.82,0.91) MSKCC 0.89 (0.84,0.94) With c-Kit exon 11 genotype NIH 0.80 (0.67,0.93) 0.16 AFIP 0.84 (0.73,0.95) MSKCC 0.90 (0.80,0.99) NIH: National Institute of Health, AFIP: Armed Forces Institute of Pathology, MSKCC: Memorial Sloan Kettering Cancer Centre. AUC: Area under the curve.

ABSTRACT Bipolar disorder’s (BD) clinical heterogeneity has an unresolved genetic basis. We meta-analyzed genome-wide association studies (GWAS) of 16 BD subphenotypes in 226,032 individuals from 57 cohorts (38,022 cases); 10 advanced to multivariate and multi-trait analyses. Four factors (compulsive, psychotic, dysregulated, internalizing) explained 82.8% of shared genetic variance. BD1 and BD2 loaded on distinct factors despite a high genetic correlation; 87.0% of common-factor loci were significant in neither subtype. Unipolar mania aligned with psychosis over internalizing, and was distinguishable from BD1, and rapid cycling showed heritable cross-domain liability. We identified 356 risk loci, 158 novel, including the first univariate-GWAS associations for psychosis, unipolar mania, rapid cycling and schizoaffective disorder—and 249 credible genes (89 high-confidence), 12 with approved-drug or clinical-phase annotations. Cell-type association showed a midbrain dopaminergic–GABAergic gradient along the psychotic factor. BD’s genetic architecture appears hierarchical—a general liability resolving into dimensions of course and comorbidity beyond diagnostic subtypes.