Bone marrow adipocytes (BMAd) have recently been implicated in accelerating bone metastatic cancers, such as acute myelogenous leukemia and breast cancer. Importantly, bone marrow adipose tissue (BMAT) expands with aging and obesity, two key risk factors in multiple myeloma disease prevalence, suggesting that BMAds may influence and be influenced by myeloma cells in the marrow. Here, we provide evidence that reciprocal interactions and cross-regulation of myeloma cells and BMAds play a role in multiple myeloma pathogenesis and treatment response. Bone marrow biopsies from patients with multiple myeloma revealed significant loss of BMAT with myeloma cell infiltration of the marrow, whereas BMAT was restored after treatment for multiple myeloma. Myeloma cells reduced BMAT in different preclinical murine models of multiple myeloma and in vitro using myeloma cell-adipocyte cocultures. In addition, multiple myeloma cells altered adipocyte gene expression and cytokine secretory profiles, which were also associated with bioenergetic changes and induction of a senescent-like phenotype. In vivo, senescence markers were also increased in the bone marrow of tumor-burdened mice. BMAds, in turn, provided resistance to dexamethasone-induced cell-cycle arrest and apoptosis, illuminating a new possible driver of myeloma cell evolution in a drug-resistant clone. Our findings reveal that bidirectional interactions between BMAds and myeloma cells have significant implications for the pathogenesis and treatment of multiple myeloma. Targeting senescence in the BMAd or other bone marrow cells may represent a novel therapeutic approach for treatment of multiple myeloma. Significance: This study changes the foundational understanding of how cancer cells hijack the bone marrow microenvironment and demonstrates that tumor cells induce senescence and metabolic changes in adipocytes, potentially driving new therapeutic directions.
Atypical antipsychotic (AA) medications including risperidone (RIS) and olanzapine (OLAN) are FDA approved for the treatment of psychiatric disorders including schizophrenia, bipolar disorder and depression. Clinical side effects of AA medications include obesity, insulin resistance, dyslipidemia, hypertension and increased cardiovascular disease risk. Despite the known pharmacology of these AA medications, however, the mechanisms contributing to adverse metabolic side-effects are not well understood. To evaluate drug-associated effects on the heart, we assessed changes in the cardiac proteomic signature in mice administered for 4 weeks with clinically relevant exposure of RIS or OLAN. Using proteomic and gene enrichment analysis, we identified differentially expressed (DE) proteins in both RIS-and OLAN-treated mouse hearts (p <0.05), including proteins comprising mitochondrial respiratory complex I and pathways involved
Objective Fasting plasma glucose (FPG), 2-hour plasma glucose (2hPG) from a 75-g oral glucose tolerance test (OGTT) and glycated hemoglobin (HbA1c) can lead to different results when diagnosing prediabetes and diabetes. The Hemoglobin Glycation Index (HGI) quantifies the interindividual variation in glycation resulting in discrepancies between FPG and HbA1c. We used data from the Vitamin D and Type 2 Diabetes (D2d) study to calculate HGI, to identify HGI-associated variables, and to determine how HGI affects prediabetes and diabetes diagnosis. Measurements A linear regression equation [HbA1c (%) = 0.0164 × FPG (mg/dL) + 4.2] was derived using the screening cohort (n = 6829) and applied to calculate predicted HbA1c. This was subtracted from the observed HbA1c to determine HGI in the baseline cohort with 2hPG data (n = 3945). Baseline variables plus prediabetes and diabetes diagnosis by FPG, HbA1c, and 2hPG were compared among low, moderate, and high HGI subgroups. Results The proportion of women and Black/African American individuals increased from low to high HGI subgroups. Mean FPG decreased and mean HbA1c increased from low to high HGI subgroups, consistent with the HGI calculation; however, mean 2hPG was not significantly different among HGI subgroups. Conclusions High HGI was associated with Black race and female sex as reported previously. The observation that 2hPG was not different across HGI subgroups suggests that variation in postprandial glucose is not a significant source of population variation in HGI. Exclusive use of HbA1c for diagnosis will classify more Black individuals and women as having prediabetes compared with using FPG or 2hPG.
Background Communicating scientific uncertainty about public health threats such as COVID-19 is an ethically desirable task endorsed by expert guidelines on crisis communication. However, the communication of scientific uncertainty is challenging because of its potential to promote ambiguity aversion—a well-described syndrome of negative psychological responses consisting of heightened risk perceptions, emotional distress, and decision avoidance. Communication strategies that can inform the public about scientific uncertainty while mitigating ambiguity aversion are a critical unmet need. Objective This study aimed to evaluate whether an “uncertainty-normalizing” communication strategy—aimed at reinforcing the expected nature of scientific uncertainty about the COVID-19 pandemic—can reduce ambiguity aversion, and to compare its effectiveness to conventional public communication strategies aimed at promoting hope and prosocial values. Methods In an online factorial experiment conducted from May to June 2020, a national sample of 1497 US adults read one of five versions of an informational message describing the nature, transmission, prevention, and treatment of COVID-19; the versions varied in level of expressed scientific uncertainty and supplemental focus (ie, uncertainty-normalizing, hope-promoting, and prosocial). Participants then completed measures of cognitive, emotional, and behavioral manifestations of ambiguity aversion (ie, perceived likelihood of getting COVID-19, COVID-19 worry, and intentions for COVID-19 risk-reducing behaviors and vaccination). Analyses assessed (1) the extent to which communicating uncertainty produced ambiguity-averse psychological responses; (2) the comparative effectiveness of uncertainty-normalizing, hope-promoting, and prosocial communication strategies in reducing ambiguity-averse responses; and (3) potential moderators of the effects of alternative uncertainty communication strategies. Results The communication of scientific uncertainty about the COVID-19 pandemic increased perceived likelihood of getting COVID-19 and worry about COVID-19, consistent with ambiguity aversion. However, it did not affect intentions for risk-reducing behaviors or vaccination. The uncertainty-normalizing strategy reduced these aversive effects of communicating scientific uncertainty, resulting in levels of both perceived likelihood of getting COVID-19 and worry about COVID-19 that did not differ from the control message that did not communicate uncertainty. In contrast, the hope-promoting and prosocial strategies did not decrease ambiguity-averse responses to scientific uncertainty. Age and political affiliation, respectively, moderated the effects of uncertainty communication strategies on intentions for COVID-19 risk-reducing behaviors and worry about COVID-19. Conclusions Communicating scientific uncertainty about the COVID-19 pandemic produces ambiguity-averse cognitive and emotional, but not behavioral, responses among the general public, and an uncertainty-normalizing communication strategy reduces these responses. Normalizing uncertainty may be an effective strategy for mitigating ambiguity aversion in crisis communication efforts. More research is needed to test uncertainty-normalizing communication strategies and to elucidate the factors that moderate their effectiveness.
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