Citations

Progress in development of prognostic and therapeutic options for the rare cholestatic liver diseases, primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC), is hampered by limited knowledge of their pathogeneses. In particular, the potential role of hepatotoxic and/or metabolism‐altering environmental chemicals in the pathogenesis of these diseases remains relatively unstudied. Moreover, the extent to which metabolic pathways are altered due to ongoing cholestasis and subsequent liver damage or possibly influenced by hepatotoxic chemicals is poorly understood. In this study, we applied a comprehensive exposomics‐metabolomics approach to uncover potential pathogenic contributors to PSC and PBC. We used untargeted high‐resolution mass spectrometry to characterize a wide range of exogenous chemicals and endogenous metabolites in plasma and tested them for association with disease. Exposome‐wide association studies (EWAS) identified environmental chemicals, including pesticides, additives and persistent pollutants, that were associated with PSC and/or PBC, suggesting potential roles for these compounds in disease pathogenesis. Metabolome‐wide association studies (MWAS) found disease‐associated alterations to amino acid, eicosanoid, lipid, co‐factor, nucleotide, mitochondrial and microbial metabolic pathways, many of which were shared between PSC and PBC. Notably, this analysis implicates a potential role of the 5‐lipoxygenase pathway in the pathogenesis of these diseases. Finally, EWAS × MWAS network analysis uncovered linkages between environmental agents and disrupted metabolic pathways that provide insight into potential mechanisms for PSC and PBC. Conclusion: This study establishes combined exposomics‐metabolomics as a generalizable approach to identify potentially pathogenic environmental agents and enumerate metabolic alterations that may impact PSC and PBC, providing a foundation for diagnostic and therapeutic strategies.

Abstract Introduction: Multiple Myeloma (MM) is an incurable plasma cell malignancy commonly preceded by the asymptomatic stage smoldering multiple myeloma (SMM). MM is characterized with significant genomic heterogeneity of chromosomal gains and losses (CNVs), translocations, and point mutations (SNVs); alterations that are also observed in SMM patients. However, current SMM risk models rely solely on clinical markers and do not accurately capture progression risk. While incorporating some genomic biomarkers improves prediction, using all MM genomic features to comprehensively stratify patients may increase risk stratification precision in SMM. Methods: We obtained a total of 214 patient samples at SMM diagnosis. We performed whole-exome sequencing on 166 tumors; of these, RNA sequencing was performed on 100. Targeted capture was done on 48 additional tumors. Upon binarization of DNA features, we performed consensus non-negative matrix factorization to identify distinct molecular clusters. We then trained a random forest classifier on translocations, SNVs, and CNVs. The predicted clinical outcomes for the molecular subtypes were further validated in an independent SMM cohort of 74 patients. Results: We identified six genomic subtypes, four with hyperdiploidy (>48 chromosomes, HMC, HKR, HNT, HNF) and two with IgH translocations (FMD, CND) (Table 1). In multivariate analysis accounting for IMWG (20-2-20) clinical risk stages, high-risk (HMC, FMD, HKR) and intermediate-risk (HNT, HNF) genetic subtypes were independent predictors of progression (Hazards ratio [HR]: 3.8 and 5.5, P = 0.016 and 0.001, respectively). The low-risk, CND subtype harboring translocation (11;14) was enriched for the previously defined CD-2 MM signature defined by the B cell markers CD20 and CD79A (FDR = 0.003 ), showed upregulation of CCND1, E2F1, and E2F7 (FDR = 0.01, 0.0004, 0.08), and was enriched for G2M checkpoint, heme metabolism, and monocyte cell signature (FDR = 0.003, 0.003, 0.003, respectively). The FMD subtype with IgH translocations (4;14) and (14;16) was enriched for P53, mTORC1, unfolded protein signaling pathways and plasmacytoid dendritic cell signatures (FDR = 0.01, 0.005, 0.008, respectively). The HKR tumors were enriched for inflammatory cytokine signaling, MYC target genes, T regulatory cell signature, and the MM proliferative (PR) signatures (FDR = 0.02, 0.03, 0.007, 0.02, respectively). The APOBEC mutational signature was enriched in HMC and FMD tumors (P = 0.005), while there was no statistical difference across subtypes in the AID signature. The median follow-up for the primary cohort is 7.1 years. Median TTP for patients in HMC, FMD, and HKR was 3.8, 2.6, and 2.2 years, respectively; TTP for HNT and HNF was 4.3 and 5.2, respectively, while it was 11 years in CND patients (P = 0.007). Moreover, by analyzing the changes in MM clinical biomarkers over time, we found that patients from high-risk subgroups had higher odds of developing evolving hemoglobin and monoclonal protein levels over time (P = 0.01 and 0.002, respectively); Moreover, the absolute increase in M-protein was significantly higher in patients from the high-risk genetic subtypes at one, two, and five years from diagnosis (P = 0.001, 0.03, and 0,01, respectively). Applying the classifier to the external cohort replicated our findings where intermediate and high-risk genetic subgroups conferred increased risk of progression to MM in multivariate analysis after accounting for IMWG staging (HR: 5.5 and 9.8, P = 0.04 and 0.005, respectively). Interestingly, within the intermediate-risk clinical group in the primary cohort, patients in the high-risk genetic subgroups had increased risk of progression (HR: 5.2, 95% CI 1.5 - 17.3, P = 0.007). In the validation cohort, these patients also had an increased risk of progression to MM (HR: 6.7, 95% CI 1.2 - 38.3, P = 0.03), indicating that molecular classification improves the clinical risk-stratification models. Conclusion: We identified and validated in an independent dataset six SMM molecular subgroups with distinct DNA alterations, transcriptional profiles, dysregulated pathways, and risks of progression to active MM. Our results underscore the importance of molecular classification in addition to clinical evaluation in better identifying high-risk SMM patients. Moreover, these subgroups may be used to identify tumor vulnerabilities and target them with precision medicine efforts. Figure 1 Figure 1. Disclosures Bustoros: Janssen, Bristol Myers Squibb: Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria. Casneuf: Janssen: Current Employment. Kastritis: Amgen: Consultancy, Honoraria, Research Funding; Takeda: Honoraria; Pfizer: Consultancy, Honoraria, Research Funding; Genesis Pharma: Honoraria; Janssen: Consultancy, Honoraria, Research Funding. Walker: Bristol Myers Squibb: Research Funding; Sanofi: Speakers Bureau. Davies: Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Dimopoulos: Amgen: Honoraria; BMS: Honoraria; Takeda: Honoraria; Beigene: Honoraria; Janssen: Honoraria. Bergsagel: Genetech: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; GSK: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Yong: BMS: Research Funding; Autolus: Research Funding; Takeda: Honoraria; Janssen: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; GSK: Honoraria; Amgen: Honoraria. Morgan: BMS: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees. Getz: IBM, Pharmacyclics: Research Funding; Scorpion Therapeutics: Consultancy, Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy.

Abstract Background: Protein production and homeostasis are critical to life and death decisions of malignant plasma cells in multiple myeloma (MM). While protein homeostasis has been targeted effectively with proteasome inhibitors in this disease, inhibition of protein production has not been clinically tested. Protein translation inhibition represents an immediately available avenue, with the agent omacetaxine mepesuccinate (Oma). Recent in vivo and ex vivo work illustrates the broad sensitivity MM cells have to Oma, irrespective of proteasome inhibitor (PI) or immunomodulatory (IMiD) drug treatment exposure (Walker et al. Clinical Cancer Research, 2021). High levels of baseline protein translation, compared to other cells in the bone marrow, serves as a biomarker of high Oma sensitivity in MM patient samples. Based on this, we hypothesized that Oma treatment in MM may lead to eventual drug resistance through the downregulation of protein synthesis. To test this, we evaluated the effects of long-term Oma treatment on MM cells, by establishing resistance in two human MM cell lines and comparing them to their isogenic parental lines. Methods: Omacetaxine resistance was established by dose escalation in MM cell lines NCI-H929 and MM1S, with concentrations gradually increased over 80 weeks to 84 nM and 52 nM, respectively. Resistance was confirmed via CellTiter-Glo after 96 h incubations. Translation rates were measured by incorporation of OP-Puromycin. Flow cytometry was used for cell cycle analysis. Mass cytometry (CyTOF) was performed on a Fluidigm Helios system with a 35-marker panel. Cell morphology was examined by confocal microscopy using a Zeiss LSM780 spectral microscope with DAPI and Mitotracker stains. Cell line xenograft studies were performed using NSG mice engrafted via IV tail injection. Results: Resistant cell lines H929-R and MM1S-R displayed decreased cytotoxicity to Oma, with EC50 >100 nM after 96 h treatment, compared to parental line sensitivity of 24 nM for MM1S and 54 nM for H929 (Fig 1A and 1B). Next, we evaluated baseline translation rates for both parental and resistant lines. As hypothesized, H929 cells significantly downregulated translation after acquiring Oma resistance, but MM1S cells actually significantly upregulated protein synthesis (n = 3, p < 0.001 for both lines, Fig 1C). Interestingly, MM1S-R cells showed global phenotypic changes from the parental line based on UMAP analysis of CyTOF results, whereas H929-R appeared similar to its isogenic line (Fig 1D). The most altered protein was the transcription factor XBP1s, which was elevated in MM1S-R cells compared to parental (Fig 1E). An increased percentage of aneuploidy cells was observed in both resistant lines compared to the parental lines, indicating genomic pressure on both (Fig 1F). Consistent with this, confocal microscopy showed the emergence of multi-nucleated and pleomorphic cells in the Oma resistant lines compared to parental (Fig 1G). Finally, both resistant lines showed a surprising extended survival in an untreated MM NSG xenograft model. Mice engrafted with either H929-R or MM1S-R had a significant survival advantage over their parental cell lines (p = 0.0019, p = 0.0014, Fig 1G and 1H). Median survival was 119 days for H929-P and unreached for H929-R mice, MM1S was 47 and 68 days respectively. Conclusion: After prolonged exposure to Oma, cell lines H929 and MM1S displayed unique characteristics compared to their parental lines, including changes in protein translation rates, drug sensitivities, aneuploidy, and in vivo growth characteristics. Once resistant to Oma, H929 cells downregulated translation, similar to published patient sample data. Conversely, MM1S cells upregulated translation and displayed a more complex phenotypic shift, including an upregulation of XPB1s, an indication of increased unfolded protein response. Much like PIs, we believe Oma disrupts the delicate proteostasis intrinsic to MM cells, putting them on the defensive. Both Oma resistant cell lines exhibited a stressed cell state evident through their decline of in vivo fitness and an increase in poly-aneuploidy. Ongoing research with these cell lines will evaluate transcriptional changes, continuing to advance our understanding of Oma sensitivity and resistance in multiple myeloma. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Abstract Background: Advances in supportive care and novel therapies have driven improved outcomes for patients with Multiple myeloma (MM) and Light Chain Amyloidosis (AL). Unfortunately, this progress demands a heavy toll - higher patient costs. Financial toxicity (FT) is the adverse impact of cancer on a patient's financial well-being, contributing to increased distress, lower medication compliance, and even reduced survival. We aimed to evaluate MM and AL patients for financial toxicity over time to better understand its impact on various quality of life (QOL) domains. Methods: Adult patients with MM or AL that receive care at Mayo Clinic, Rochester MN, were recruited for a prospective study between December 2019 and March 2021. FT was measured using the validated COmprehensive Score for financial Toxicity (COST) questionnaire at the time of enrollment, 3 months, and 6 months follow-up. COST scores range from 0-44, with higher scores indicating lower FT. We defined patients with a COST score of ≤ 23 as having substantial FT. Domains of QOL were assessed via the Patient Reported Outcome Measurement Information System (PROMIS)-29 survey. Patient demographics and clinical information were abstracted from the electronic medical record. Statistical analysis included a comparison of COST scores among groups through Wilcoxon rank-sum, Kruskal-Wallis, and Jonckheere-Terpestra tests for binary, unordered, and ordered categorical variables, respectively. Results: One hundred and sixteen patients (96 MM, 83%; AL 20, 17%) enrolled in this study. The cohort is characterized as follows: 49% age 65+ (51% age 35-64), 54% male, 93% White, 4.3% Black, 3.5% Hispanic, 44% with incomes > USD 75k/yr (26% < USD 50k/yr), 77% with at least some college education (32% graduate or doctoral degree), 52% insured through Medicare (4.3% through Medicaid), 36% employed (53% retired), and 71% married (16% divorced). Forty-three percent of patients enrolled in the study were newly diagnosed (56% relapsed), and 72% had received an autologous stem cell transplant. Baseline mean COST score was25.9 (N=116; SD 10.2), with 37% reporting FT. A total of 101 patients (85 MM; 16 AL) completed a baseline and either 3- or 6-month COST survey. Thirty-eight of these patients (38%) reported FT at the time of enrollment. Among those reporting baseline FT, 71% continued to report FT at 3 or 6 months; 29% showed reduced FT. Of the 62% of patients who reported low FT at baseline, 78% showed continued low FT at 3 or 6 months; 22% showed increased FT. Results of longitudinal follow-up are outlined in Figure 1. FT was significantly associated with increased anxiety, depression, and pain intensity domains on the PROMIS-29. Substantial FT was associated with: women, Medicaid as primary insurance, and being divorced. FT was also greater in unemployed/disabled vs retired individuals. Conversely, low FT was associated with: males, earning > USD 75k/yr, Medicare as primary insurance, having at least some college education, being retired, and traveling 300+ miles for care. Financial toxicity did not differ significantly by age, race, ethnicity, disease status (newly diagnosed vs relapsed), or transplant status. Discussion : Financial toxicity was present in more than one-third of AL and MM patients in this high-earning and well-educated cohort. Financial toxicity was associated with increased anxiety, depression, and pain intensity, contributing to lower patient quality of life. Longitudinal follow-up has shown financial toxicity to be dynamic, necessitating routine evaluation of patient financial burdens. Future work will focus on automating FT assessment with incorporation into routine care and developing care processes to support patients. Figure 1 Figure 1. Disclosures Dispenzieri: Alnylam: Research Funding; Takeda: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding.

Abstract Background It is unclear how acute coronavirus disease 2019 (COVID-19)-directed therapies are used in children with life-threatening COVID-19 in US hospitals. We described characteristics of children hospitalized in the intensive care unit or step-down unit (ICU/SDU) who received COVID-19-directed therapies and the specific therapies administered. Methods Between March 15, 2020 and December 27, 2020, children <18 years of age in the ICU/SDU with acute COVID-19 at 48 pediatric hospitals in the United States were identified. Demographics, laboratory values, and clinical course were compared in children who did and did not receive COVID-19-directed therapies. Trends in COVID-19-directed therapies over time were evaluated. Results Of 424 children in the ICU/SDU, 235 (55%) received COVID-19-directed therapies. Children who received COVID-19-directed therapies were older than those who did not receive COVID-19-directed therapies (13.3 [5.6-16.2] vs 9.8 [0.65-15.9] years), more had underlying medical conditions (188 [80%] vs 104 [55%]; difference = 25% [95% CI: 16% to 34%]), more received respiratory support (206 [88%] vs 71 [38%]; difference = 50% [95% CI: 34% to 56%]), and more died (8 [3.4%] vs 0). Of the 235 children receiving COVID-19-directed therapies, 172 (73%) received systemic steroids and 150 (64%) received remdesivir, with rising remdesivir use over the study period (14% in March/April to 57% November/December). Conclusion Despite the lack of pediatric data evaluating treatments for COVID-19 in critically ill children, more than half of children requiring intensive or high acuity care received COVID-19-directed therapies.

AbstractIntroductionMotoric cognitive risk (MCR), a clinical syndrome characterized by slow gait speed and subjective cognitive complaints, has been associated with dementia risk. The neuropathological features underlying MCR remain poorly understood.MethodsThe Atherosclerosis Risk in Communities (ARIC) community‐based cohort study classified participants using standardized criteria as MCR+/– and mild cognitive impairment (MCI)+/– at study baseline (2011–2013). We examined the 5‐year dementia risk and baseline brain structural/molecular abnormalities associated with MCR+ and MCI+ status.ResultsOf 5023 nondemented participants included, 204 were MCR+ and 1030 were MCI+. Both MCR+ and MCI+ participants demonstrated increased dementia risk. The pattern of structural brain abnormalities associated with MCR+ differed from that of MCI+. Whereas MCI+ was associated with comparatively smaller volumes in brain regions vulnerable to Alzheimer's disease pathology, MCR+ status was associated with smaller volumes in frontoparietal regions and greater white matter abnormalities.DiscussionMCR may represent a predementia syndrome characterized by prominent white matter abnormalities and frontoparietal atrophy.

Background Goals of care (GOC) conversations in the emergency department (ED) are often a brief discussion of code status rather than a patient-oriented dialogue. We aimed to develop a guide to facilitate conversations between ED clinicians and patients to elicit patient values and establish goals for end-of-life care, while maintaining ED efficiency. Paths of ED Care, a conversation guide, is the product of this work. Design A multidisciplinary/multispecialty group used recommended practices to adapt a GOC conversation guide for ED patients. ED clinicians used the guide and provided feedback on content, design, and usability. Patient-clinician interactions were recorded for discussion analysis, and both were surveyed to inform iterative refinement. A series of discussions with patient representatives, multidisciplinary clinicians, bioethicists, and health care designers yielded feedback. We used a process similar to the International Patient Decision Aid Standards and provide comparison to these. Results A conversation guide, eight pages with each page 6 by 6 inches in dimension, uses patient-oriented prompts and includes seven sections: 1) evaluation of patient/family understanding of disease, 2) explanation of possible trajectories, 3) introduction to different pathways of care, 4) explanation of pathways, 5) assessment of understanding and concerns, 6) code status, and 7) personalized summary. Limitations Recruitment of sufficient number of patients/providers to the project was the primary limitation. Methods are limited to qualitative analysis of guide creation and feasibility without quantitative analysis. Conclusions Paths of ED Care is a guide to facilitate patient-centered shared decision making for ED patients, families, and clinicians regarding GOC. This may ensure care concordant with patients’ values and preferences. Use of the guide was well-received and facilitated meaningful conversations between patients and providers.

Abstract Background Consolidation of healthcare in the US has resulted in integrated organizations encompassing large geographic areas, with varying services and complex patient flows. Profound changes in patient volumes and behavior have occurred during the SARS Cov2 pandemic, but understanding these changes across organizations is challenging. Network analysis provides a novel approach to address this. Methods We retrospectively evaluated hospital-based encounters with an index emergency department visit in a healthcare system comprising 18 hospitals, using patient transfer as a marker of unmet clinical need. We developed quantitative models of transfers using network analysis incorporating the level of care provided (ward, progressive care, intensive care) during pre-pandemic (May 25, 2018 to March 16, 2020) and mid-pandemic (March 17, 2020 to March 8, 2021) time periods. Results 829,455 encounters were evaluated. The system functioned as a non-small-world, non-scale-free, dissociative network. Our models reflected transfer destination diversification and variations in volume between the two time points – results of intentional efforts during the pandemic. Known hub-spoke architecture correlated with quantitative analysis. Conclusion Applying network analysis in an integrated US healthcare organization demonstrates changing patterns of care and the emergence of bottlenecks in response to the SARS Cov2 pandemic, consistent with clinical experience, providing a degree of face validity. The modeling of multiple influences can identify susceptibility to stress and opportunities to strengthen the system where patient movement is common and voluminous. The technique provides a mechanism to analyze the effects of intentional and contextual changes on system behavior.

SummaryBackgroundRumination syndrome is a functional gastroduodenal disorder characterised by effortless regurgitation of recently ingested food. Emerging evidence reports duodenal eosinophilic inflammation in a subset, suggesting a shared pathophysiology with functional dyspepsia (FD).AimTo assess the clinical features of rumination syndrome and FD in a community‐based study.MethodsWe mailed a survey assessing gastrointestinal symptoms, diet and psychological symptoms to 9835 residents of Olmsted County, MN, USA in 2017‐2018; diagnostic codes were obtained from linked clinical records. The two disorders were assessed as mutually exclusive in ‘pure’ forms with a separate overlap group, all compared to a control group not meeting criteria for either. Prevalence of associations, and univariate and independent associations with predictors were assessed by logistic regression.ResultsPrevalence of rumination syndrome and FD were 5.8% and 7.1%, respectively; the overlap was 3.83‐times more likely than expected by chance. Independent predictors for rumination (odds ratio (OR), 95% confidence interval (CI)) were female gender (1.79, 1.21‐2.63), smoking (1.89, 1.28‐2.78), gluten‐free diet (1.58, 1.14‐2.19), allergic rhinitis (1.45, 1.01‐2.08) and depression (1.10, 1.05‐1.16). FD was independently associated with female gender, depression, non‐coeliac wheat sensitivity, migraine, irritable bowel syndrome and somatic symptoms. A similar reported efficacy (≥54%) of low fat or dairy‐free diets was found with both disorders (P = 0.53 andP = 1.00, respectively). The strongest independent associations with overlapping FD and rumination syndrome were a history of rheumatoid arthritis (3.93, 1.28‐12.06) and asthma (3.02, 1.44‐6.34).ConclusionRumination syndrome overlaps with FD with a shared risk factor profile, suggesting a common pathophysiology.