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PURPOSE This study assessed the joint association of pathogenic variants (PVs) in breast cancer (BC) predisposition genes and polygenic risk scores (PRS) with BC in the general population. METHODS A total of 26,798 non-Hispanic white BC cases and 26,127 controls from predominately population-based studies in the Cancer Risk Estimates Related to Susceptibility consortium were evaluated for PVs in BRCA1, BRCA2, ATM, CHEK2, PALB2, BARD1, BRIP1, CDH1, and NF1. PRS based on 105 common variants were created using effect estimates from BC genome-wide association studies; the performance of an overall BC PRS and estrogen receptor–specific PRS were evaluated. The odds of BC based on the PVs and PRS were estimated using penalized logistic regression. The results were combined with age-specific incidence rates to estimate 5-year and lifetime absolute risks of BC across percentiles of PRS by PV status and first-degree family history of BC. RESULTS The estimated lifetime risks of BC among general-population noncarriers, based on 10th and 90th percentiles of PRS, were 9.1%-23.9% and 6.7%-18.2% for women with or without first-degree relatives with BC, respectively. Taking PRS into account, more than 95% of BRCA1, BRCA2, and PALB2 carriers had > 20% lifetime risks of BC, whereas, respectively, 52.5% and 69.7% of ATM and CHEK2 carriers without first-degree relatives with BC, and 78.8% and 89.9% of those with a first-degree relative with BC had > 20% risk. CONCLUSION PRS facilitates personalization of BC risk among carriers of PVs in predisposition genes. Incorporating PRS into BC risk estimation may help identify > 30% of CHEK2 and nearly half of ATM carriers below the 20% lifetime risk threshold, suggesting the addition of PRS may prevent overscreening and enable more personalized risk management approaches.

AbstractIn the last two decades, the development of culture‐independent genomic techniques has facilitated an increased appreciation of the microbiota‐immunity interactions and their role in a multitude of chronic inflammatory diseases such as chronic rhinosinusitis (CRS), asthma, inflammatory bowel disease and dermatitis. While the pathologic role of bacteria in chronic inflammatory diseases is generally accepted, the understanding of the role of fungi remains controversial. Chronic rhinosinusitis, specifically the phenotype linked to nasal polyps, represents a spectrum of chronic inflammatory diseases typically characterized by a type 2 immune response. Studies on the microbiota within sinus cavities from healthy and diseased patients have focused on the bacterial community, mainly highlighting the loss of diversity associated with sinus inflammation. Within the various CRS with nasal polyps (CRSwNP) phenotypes, allergic fungal rhinosinusitis presents an opportunity to investigate the role of fungi in chronic type 2 immune responses as well as the antifungal immune pathways designed to prevent invasive fungal diseases. In this review, we examine the spectrum of fungi‐associated sinus diseases highlighting the interaction between fungal species and host immune status on disease presentation. With a focus on fungi and type 2 immune response, we highlight the current knowledge and its limitations of the sinus mycobiota along with cellular interactions and activated molecular pathways linked to fungi.

Abstract Background Filgotinib (FIL) is an oral preferential Janus kinase (JAK) 1 inhibitor in development for the treatment of inflammatory diseases. FIL for the treatment of moderately to severely active ulcerative colitis (UC) was evaluated in the phase 2b/3, double-blind, placebo (PBO)-controlled SELECTION study (NCT02914522) and its long-term extension (LTE) study (NCT02914535). Here we report safety results from the FIL UC program. Methods Patients received FIL 100 mg, FIL 200 mg or PBO (2:2:1) once daily orally for up to 11 weeks for induction (cohort 1). At week 11, FIL induction responders were rerandomized 2:1 to continue FIL or receive PBO maintenance for 47 weeks (cohort 2). Week 10 non-responders and patients with worsening disease during the maintenance study were eligible for open-label FIL in the LTE. Patients completing the maintenance study could continue blinded dosing in the LTE. Cohort 3 comprised cohorts 1 and 2 and the LTE. Exposure-adjusted incidence rates (EAIRs) and exposure-adjusted event rates (EAERs) per 100 patient-years (PYs) were calculated for treatment-emergent adverse events (AEs) by treatment group in cohorts 1 and 2 (EAIR) and cohort 3 (EAER). Results In cohort 1, 1069 patients received FIL and 279 patients received PBO; baseline characteristics were generally similar across treatment groups (overall mean age, 43 years; mean UC duration, 8.4 years; mean Mayo Clinic Score, 9.0). EAIRs for AEs of interest were similar across treatment groups in cohorts 1 and 2 (Table 1). Treatment exposure for PBO, FIL 100 mg or FIL 200 mg in cohort 3 (i.e. cohorts 1 + 2 + the LTE) was 318, 360 and 1207 PYs, and median treatment duration was 12, 11 and 67 weeks, respectively. One case of pulmonary embolism occurred with FIL 200 mg induction and three venous thrombosis cases occurred with PBO maintenance/LTE (cohort 3) (Table 2). EAERs for all infections were similar across treatment groups, the most common being nasopharyngitis (Table 2). Opportunistic infections were rare. EAERs for serious infections were low across treatment groups (2.2 [PBO], 3.5 [FIL 100 mg], 2.2 [FIL 200 mg]), the most common being appendicitis (Table 2). EAERs for herpes zoster (HZ) were low in all treatment groups (0.3 [PBO], 0.3 [FIL 100 mg], 1.8 [FIL 200 mg]) (Table 2). HZ infections were cutaneous only and only one was serious. EAIRs for all infections in cohorts 1 and 2 were generally numerically higher for both PBO and FIL in patients over (vs under) 65 years old and in those with (vs without) biologic treatment failure (Figure 1). Conclusion FIL was well tolerated in patients with UC. Aggregation of AEs typical for pan-JAK inhibition was not observed, consistent with preferential JAK-1 inhibition with FIL.

Introduction: Recent studies showed post-operative atrial fibrillation (POAF) is associated with increased stroke risk - even approaching that of unprovoked AF. This raises the question of whether patients with POAF should receive anticoagulation. We aim to compare different anticoagulation strategies in patients with POAF after cardiac and non-cardiac surgeries. Methods: Using a large national administrative database (OptumLabs Data Warehouse), we identified 33,981 patients with POAF between 1/1/2013-9/30/2019. Patients were divided to four groups based on the initial treatment within 30 days of POAF: (1) no anticoagulation (N=28,807) (2) apixaban (N=2178) (3) rivaroxaban (N=1320) (4) warfarin (N=1676). Follow up started at the 30 th day after POAF to exclude patients who died shortly after surgery and minimize immortal time bias. The follow up continued until patients changed treatment strategies, insurance, or died. 1:1 propensity score matching was performed between each anticoagulant to no treatment to balance on 86 baseline characteristics. Results: The mean age was 71.1±11.2 yr; mean CHA 2 DS 2 -VASc was 4.1±1.8; 29.1% received cardiac surgeries; 15.2% received anticoagulation within 30 days of POAF. The event rate per 100 person years was 1.58 for stroke in no-anticoagulation group, and 1.29 for anticoagulation group; 2.86 for major bleeding in no-anticoagulation group and 4.50 for anticoagulation group. After matching, apixaban and rivaroxaban were associated with a lower risk of stroke, but a higher risk of major bleeding; warfarin was not associated with a lower risk of stroke, but a higher risk of major bleeding (Figure). The effect was consistent across subgroups, e.g., age and surgery type. Conclusions: In patients with POAF, the stroke rate was lower than what was typically observed in clinical AF. Treatment with apixaban and rivaroxaban immediately after POAF was associated with a reduced risk of stroke but an increased risk of major bleeding.

Introduction: Watchman has been increasingly used in AF patients who have difficulties taking anticoagulation, but the RCTs only compared Watchman to warfarin. There was also a signal of increased ischemic stroke with Watchman in comparison to warfarin in RCTs, which made some clinicians question the fundamental premise that Watchman can reduce stroke. We aimed to compare Watchman to no anticoagulation in a large national cohort of patients in the US. Methods: We identified AF patients treated with Watchman (N=7,309) or no anticoagulation (N=1,234,543) between 2015-2017 from the OptumLabs Data Warehouse, which is the first to link private insurance, Medicare Advantage, and Medicare Fee-for-Service records at patient level longitudinally. One-to-one propensity score matching was used to balance patients on demographics and medical history. The primary outcomes were ischemic stroke or systemic embolism (hereafter referred to as stroke) and major bleeding. Secondary outcomes included all-cause mortality and intracranial bleeding. Results: In the unmatched cohort, the mean age was 76.6±6.4 yr in the Watchman group and 76.6 ±8.5 yr in the no anticoagulation group, but Watchman patients were more likely to have a history of bleeding (44.9% vs 13.7%) and intracranial bleeding (9.5% vs 2.6%). After matching, the two groups were similar on 18 baseline characteristics. Watchman was associated with a lower risk of stroke and mortality, but a higher risk of major bleeding and a similar risk of intracranial bleeding. The associations were largely consistent across subgroups, including those with relative contraindications to anticoagulation (Figure). Conclusions: In AF patients who had difficulties taking anticoagulation, Watchman offers an alternative approach to reduce stroke and mortality. The results provide important evidence to inform clinical decision making in the absence of RCTs, since 40% of AF patients in routine practice are not on anticoagulation.

Introduction: An artificial intelligence (AI) algorithm applied to electrocardiography (ECG) during normal sinus rhythm (NSR) has been shown to predict concomitant atrial fibrillation (AF). We sought to characterize the value of AI-ECG as a predictor of future AF and assess its performance compared to other clinical prediction scores in a population-based sample. Methods: We calculated the AI-ECG probability during NSR in patients who enrolled in the population-based Mayo Clinic Study of Aging with at least one ECG in NSR within two years prior and no history of AF at the time of the baseline study visit. The cumulative incidence of AF was estimated for strata defined by AI-ECG probability and CHARGE-AF score. Cox proportional hazards were fit to assess the independent prognostic value and interaction of AI-ECG probability and CHARGE-AF score. Concordance (c) statistics were calculated for AI-ECG probability, CHARGE-AF score and combined AI-ECG and CHARGE-AF score. Results: A total of 1,936 patients with a median age 75.8 (quartile range [QR] 70.4, 81.8) years, median CHARGE-AF score 14.0 (QR 13.2, 14.7) and median CHADS2VASC score 3 (QR 2, 4) were included in the analysis. The cumulative incidence of AF increased in a stepwise fashion across quartiles of AI-ECG probability and CHARGE-AF score (Figure 1). When compared in the same model, both AI-ECG probability (hazard ratio [HR] 1.76, 95% confidence interval [CI] 1.51-2.04) and CHARGE-AF score (HR 1.90, 95% CI 1.58-2.28) independently predicted AF without significant interaction (p=0.54). C statistics were 0.69 (95% CI 0.66-0.72) for AI-ECG probability, 0.69 (95% CI 0.66-0.71) for CHARGE-AF and 0.72 (95% CI 0.69-0.75) for combined AI-ECG and CHARGE-AF score. Conclusions: In the Mayo Clinic Study of Aging, both the AI-ECG probability and CHARGE-AF score independently predicted time to AF. The AI-ECG may offer a means to assess risk with a single test without requiring manual or automated clinical data abstraction.