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  • 1
    In: Nature Computational Science, Springer Science and Business Media LLC, Vol. 2, No. 9 ( 2022-09-08), p. 605-616
    Abstract: The clinical presentation of amyotrophic lateral sclerosis (ALS), a fatal neurodegenerative disease, varies widely across patients, making it challenging to determine if potential therapeutics slow progression. We sought to determine whether there were common patterns of disease progression that could aid in the design and analysis of clinical trials. We developed an approach based on a mixture of Gaussian processes to identify clusters of patients sharing similar disease progression patterns, modeling their average trajectories and the variability in each cluster. We show that ALS progression is frequently nonlinear, with periods of stable disease preceded or followed by rapid decline. We also show that our approach can be extended to Alzheimer’s and Parkinson’s diseases. Our results advance the characterization of disease progression of ALS and provide a flexible modeling approach that can be applied to other progressive diseases.
    Type of Medium: Online Resource
    ISSN: 2662-8457
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 3029424-1
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  • 2
    In: The Lancet Neurology, Elsevier BV, Vol. 19, No. 11 ( 2020-11), p. 899-907
    Type of Medium: Online Resource
    ISSN: 1474-4422
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2020
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  • 3
    In: Diabetes Care, American Diabetes Association, Vol. 45, No. 6 ( 2022-06-02), p. 1306-1314
    Abstract: Patients with type 2 diabetes are encouraged to lose weight, but excessive weight loss in older adults may be a marker of poor health and subsequent mortality. We examined weight change during the postintervention period of Look AHEAD, a randomized trial comparing intensive lifestyle intervention (ILI) with diabetes support and education (DSE) (control) in overweight/obese individuals with type 2 diabetes and sought to identify predictors of excessive postintervention weight loss and its association with mortality. RESEARCH DESIGN AND METHODS These secondary analyses compared postintervention weight change (year 8 to final visit; median 16 years) in ILI and DSE in 3,999 Look AHEAD participants. Using empirically derived trajectory categories, we compared four subgroups: weight gainers (n = 307), weight stable (n = 1,561), steady losers (n = 1,731), and steep losers (n = 380), on postintervention mortality, demographic variables, and health status at randomization and year 8. RESULTS Postintervention weight change averaged −3.7 ± 9.5%, with greater weight loss in the DSE than the ILI group. The steep weight loss trajectory subgroup lost on average 17.7 ± 6.6%; 30% of steep losers died during postintervention follow-up versus 10–18% in other trajectories (P & lt; 0001). The following variables distinguished steep losers from weight stable: baseline, older, longer diabetes duration, higher BMI, and greater multimorbidity; intervention, randomization to control group and less weight loss in years 1–8; and year 8, higher prevalence of frailty, multimorbidity, and depressive symptoms and lower use of weight control strategies. CONCLUSIONS Steep weight loss postintervention was associated with increased risk of mortality. Older individuals with longer duration of diabetes and multimorbidity should be monitored for excessive unintentional weight loss.
    Type of Medium: Online Resource
    ISSN: 0149-5992
    Language: English
    Publisher: American Diabetes Association
    Publication Date: 2022
    detail.hit.zdb_id: 1490520-6
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  • 4
    In: JAMA Oncology, American Medical Association (AMA), Vol. 9, No. 1 ( 2023-01-01), p. 128-
    Abstract: Cytokine storm due to COVID-19 can cause high morbidity and mortality and may be more common in patients with cancer treated with immunotherapy (IO) due to immune system activation. Objective To determine the association of baseline immunosuppression and/or IO-based therapies with COVID-19 severity and cytokine storm in patients with cancer. Design, Setting, and Participants This registry-based retrospective cohort study included 12 046 patients reported to the COVID-19 and Cancer Consortium (CCC19) registry from March 2020 to May 2022. The CCC19 registry is a centralized international multi-institutional registry of patients with COVID-19 with a current or past diagnosis of cancer. Records analyzed included patients with active or previous cancer who had a laboratory-confirmed infection with SARS-CoV-2 by polymerase chain reaction and/or serologic findings. Exposures Immunosuppression due to therapy; systemic anticancer therapy (IO or non-IO). Main Outcomes and Measures The primary outcome was a 5-level ordinal scale of COVID-19 severity: no complications; hospitalized without requiring oxygen; hospitalized and required oxygen; intensive care unit admission and/or mechanical ventilation; death. The secondary outcome was the occurrence of cytokine storm. Results The median age of the entire cohort was 65 years (interquartile range [IQR], 54-74) years and 6359 patients were female (52.8%) and 6598 (54.8%) were non-Hispanic White. A total of 599 (5.0%) patients received IO, whereas 4327 (35.9%) received non-IO systemic anticancer therapies, and 7120 (59.1%) did not receive any antineoplastic regimen within 3 months prior to COVID-19 diagnosis. Although no difference in COVID-19 severity and cytokine storm was found in the IO group compared with the untreated group in the total cohort (adjusted odds ratio [aOR] , 0.80; 95% CI, 0.56-1.13, and aOR, 0.89; 95% CI, 0.41-1.93, respectively), patients with baseline immunosuppression treated with IO (vs untreated) had worse COVID-19 severity and cytokine storm (aOR, 3.33; 95% CI, 1.38-8.01, and aOR, 4.41; 95% CI, 1.71-11.38, respectively). Patients with immunosuppression receiving non-IO therapies (vs untreated) also had worse COVID-19 severity (aOR, 1.79; 95% CI, 1.36-2.35) and cytokine storm (aOR, 2.32; 95% CI, 1.42-3.79). Conclusions and Relevance This cohort study found that in patients with cancer and COVID-19, administration of systemic anticancer therapies, especially IO, in the context of baseline immunosuppression was associated with severe clinical outcomes and the development of cytokine storm. Trial Registration ClinicalTrials.gov Identifier: NCT04354701
    Type of Medium: Online Resource
    ISSN: 2374-2437
    Language: English
    Publisher: American Medical Association (AMA)
    Publication Date: 2023
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  • 5
    In: JAMA Network Open, American Medical Association (AMA), Vol. 4, No. 11 ( 2021-11-12), p. e2134330-
    Type of Medium: Online Resource
    ISSN: 2574-3805
    Language: English
    Publisher: American Medical Association (AMA)
    Publication Date: 2021
    detail.hit.zdb_id: 2931249-8
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  • 6
    In: JAMA Oncology, American Medical Association (AMA)
    Abstract: Systematic data on the association between anticancer therapies and thromboembolic events (TEEs) in patients with COVID-19 are lacking. Objective To assess the association between anticancer therapy exposure within 3 months prior to COVID-19 and TEEs following COVID-19 diagnosis in patients with cancer. Design, Setting, and Participants This registry-based retrospective cohort study included patients who were hospitalized and had active cancer and laboratory-confirmed SARS-CoV-2 infection. Data were accrued from March 2020 to December 2021 and analyzed from December 2021 to October 2022. Exposure Treatments of interest (TOIs) (endocrine therapy, vascular endothelial growth factor inhibitors/tyrosine kinase inhibitors [VEGFis/TKIs], immunomodulators [IMiDs] , immune checkpoint inhibitors [ICIs], chemotherapy) vs reference (no systemic therapy) in 3 months prior to COVID-19. Main Outcomes and Measures Main outcomes were (1) venous thromboembolism (VTE) and (2) arterial thromboembolism (ATE). Secondary outcome was severity of COVID-19 (rates of intensive care unit admission, mechanical ventilation, 30-day all-cause mortality following TEEs in TOI vs reference group) at 30-day follow-up. Results Of 4988 hospitalized patients with cancer (median [IQR] age, 69 [59-78] years; 2608 [52%] male), 1869 had received 1 or more TOIs. Incidence of VTE was higher in all TOI groups: endocrine therapy, 7%; VEGFis/TKIs, 10%; IMiDs, 8%; ICIs, 12%; and chemotherapy, 10%, compared with patients not receiving systemic therapies (6%). In multivariable log-binomial regression analyses, relative risk of VTE (adjusted risk ratio [aRR] , 1.33; 95% CI, 1.04-1.69) but not ATE (aRR, 0.81; 95% CI, 0.56-1.16) was significantly higher in those exposed to all TOIs pooled together vs those with no exposure. Among individual drugs, ICIs were significantly associated with VTE (aRR, 1.45; 95% CI, 1.01-2.07). Also noted were significant associations between VTE and active and progressing cancer (aRR, 1.43; 95% CI, 1.01-2.03), history of VTE (aRR, 3.10; 95% CI, 2.38-4.04), and high-risk site of cancer (aRR, 1.42; 95% CI, 1.14-1.75). Black patients had a higher risk of TEEs (aRR, 1.24; 95% CI, 1.03-1.50) than White patients. Patients with TEEs had high intensive care unit admission (46%) and mechanical ventilation (31%) rates. Relative risk of death in patients with TEEs was higher in those exposed to TOIs vs not (aRR, 1.12; 95% CI, 0.91-1.38) and was significantly associated with poor performance status (aRR, 1.77; 95% CI, 1.30-2.40) and active/progressing cancer (aRR, 1.55; 95% CI, 1.13-2.13). Conclusions and Relevance In this cohort study, relative risk of developing VTE was high among patients receiving TOIs and varied by the type of therapy, underlying risk factors, and demographics, such as race and ethnicity. These findings highlight the need for close monitoring and perhaps personalized thromboprophylaxis to prevent morbidity and mortality associated with COVID-19–related thromboembolism in patients with cancer.
    Type of Medium: Online Resource
    ISSN: 2374-2437
    Language: English
    Publisher: American Medical Association (AMA)
    Publication Date: 2023
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  • 7
    In: JAMA Network Open, American Medical Association (AMA), Vol. 5, No. 1 ( 2022-01-04), p. e2142046-
    Type of Medium: Online Resource
    ISSN: 2574-3805
    Language: English
    Publisher: American Medical Association (AMA)
    Publication Date: 2022
    detail.hit.zdb_id: 2931249-8
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  • 8
    In: Schizophrenia Bulletin, Oxford University Press (OUP), Vol. 46, No. 2 ( 2020-02-26), p. 432-441
    Abstract: In the last 2 decades, several neuroimaging studies investigated brain abnormalities associated with the early stages of psychosis in the hope that these could aid the prediction of onset and clinical outcome. Despite advancements in the field, neuroimaging has yet to deliver. This is in part explained by the use of univariate analytical techniques, small samples and lack of statistical power, lack of external validation of potential biomarkers, and lack of integration of nonimaging measures (eg, genetic, clinical, cognitive data). PSYSCAN is an international, longitudinal, multicenter study on the early stages of psychosis which uses machine learning techniques to analyze imaging, clinical, cognitive, and biological data with the aim of facilitating the prediction of psychosis onset and outcome. In this article, we provide an overview of the PSYSCAN protocol and we discuss benefits and methodological challenges of large multicenter studies that employ neuroimaging measures.
    Type of Medium: Online Resource
    ISSN: 0586-7614 , 1745-1701
    RVK:
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2180196-4
    SSG: 15,3
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  • 9
    In: Blood, American Society of Hematology, Vol. 116, No. 21 ( 2010-11-19), p. 3160-3160
    Abstract: Abstract 3160 While oncogene addiction is a well-documented phenomenon, the molecular mechanisms by which oncogene withdrawal triggers cell death are poorly understood. Interrogation of this phenomenon in a manipulatable murine model, coupled to concomitant analysis of human AML samples, could elucidate this phenomenon for therapeutic applications. In order to decipher these molecular mechanisms, we employ a murine model harboring a tetracycline repressible, activated NRAS (NRASG12V) transgene along with an MLL/AF9 transgene to induce AML development. Primary leukemia cells are then transplanted into SCID mice and, upon development of full-blown leukemia, NRASG12V transgene expression is repressed with doxycycline. Previous work has shown that repression of NRASG12V in this model leads to widespread apoptosis of the leukemia cells (Kim et al. Blood 2009). To analyze the kinetics of this response, we found that the tumor burden, as assayed by the white blood cell (WBC) count, declines by 60 hours of doxycycline treatment. NRASG12V message levels are undetectable by 12 hours while protein expression begins to decline after 48 hours. To dissect the signaling network directing the apoptotic response, the phosphorylation status of critical signaling intermediates was analyzed by flow cytometry at time points from 48–96 hours post-doxycycline treatment. This analysis revealed numerous modifications in known NRAS effectors including loss of phosphoErk1/2, phosphoSTAT3, and phosphop38. These alterations correlate with immunophenotypic cell surfaces markers. Whereas leukemia cells expressing mature myeloid markers (Mac1+) do not exhibit alterations in any of the phosphoproteins tested, only Mac1- leukemia cells show meaningful changes in RAS-activated signaling molecules. Whether mouse leukemic stem cells reside in the Mac1+ fraction or in the less differentiated subpopulation remains unclear. These findings suggest that subpopulations of leukemia cells exhibit differential vulnerabilities to oncogene addiction. Furthermore, these studies also reveal that oncogene withdrawal leads to a reduction of the Mac1+Gr1- population and an enrichment of the Mac1-Gr1- and Mac1+Gr1+ populations. Therefore, in addition to effecting apoptosis, oncogene withdrawal leads to alterations in the differentiation status of the leukemia, which could alter the self-renewal capacity of these cells. Using these results, we have designed an extensive antibody panel and are currently using a CyTOF mass spectrometer, a new technology that allows us to perform 30 dimensional measurements to profile immunophenotypic markers and phosphoprotein states with single cell resolution. Simultaneous, high-dimensional single cell profiling of signaling states enables integrative network analysis of these data and as such will allow us to discern pathway dependencies and regulatory relationships that traditional low dimensional flow cytometry cannot (Sachs et al. Science 2005, Sachs et al. IEEE Eng Med Biol Soc 2009). This approach will provide a novel and powerful method to elucidate the critical pathways and leukemic subpopulations that define the response to oncogene withdrawal. Furthermore, these findings will be compared to a concomitant study of 30-dimensional measurements of human AML samples which could facilitate harnessing the oncogene addiction phenomenon in therapeutic applications. Disclosures: No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2010
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  • 10
    In: Blood, American Society of Hematology, Vol. 132, No. Supplement 1 ( 2018-11-29), p. 2626-2626
    Abstract: In acute myeloid leukemia (AML) standard therapies often induce complete remission, but patients frequently relapse and die of the disease. Leukemia stem cells (LSCs) have self-renewal potential and ability to recapitulate the disease. Our goal is to define the molecular mechanisms that allow AML to relapse. We have previously shown that activated NRAS (NRASG12V) facilitates self-renewal in the LSC-enriched subpopulation in a mouse model of AML (Mll-AF9/NRASG12V, Sachs et al. Blood 2014). We subsequently utilized single-cell RNA sequencing of the LSCs from this model to define and validate the only subset of the LSC-enriched population that can efficiently transplant leukemia in mice. We hypothesize that NRASG12V exerts a unique signaling profile that directs self-renewal in this subset of LSCs. Understanding these pathways at the single-cell level would enable us to design rational therapeutics that would prevent relapse in AML. We used mass cytometry (CyTOF2) to define the signaling activation state of LSC subsets in our AML model. Similar to flow cytometry, mass cytometry provides quantitative measurements of cell-surface and intracellular proteins at the single-cell level. In addition, it can simultaneously and accurately measure over 40 proteins, allowing us to quantitate a panel of intracellular signaling molecules in well-defined immunophenotypic leukemia subpopulations. We previously reported that the LSC-enriched population in this leukemia model is Mac1LowKit+Sca1+ (MKS) and subsequently showed that the self-renewing subset within the MKS population is MKSCD36LowCD69High. In contrast, the MKSCD36HighCD69Low population is incapable of transplanting leukemia in mice. The MKS cells displayed elevated levels of activated signaling molecules relative to the non-MKS population. Comparing the MKS subsets to each other, we found that the self-renewing MKSCD36LowCD69High population displayed significantly higher levels of several signaling molecules including Myc, NF-kB, and β-catenin relative to MKSCD36HighCD69Low cells (which lack self-renewal capacity). We reasoned that self-renewal might be mediated through these signaling molecules uniquely elevated in MKSCD36LowCD69High cells. Next, we sought to define the global signaling activation network within individual MKS subsets to determine if the signaling cascades and dependencies vary between these populations. We used Bayesian network modeling (Sachs K et al. Science 2005) to compare the statistical relationships between these signaling molecules, at the single-cell level. Signaling molecules that impact the levels of downstream effectors can be inferred using this approach. Using this method, we found that the signaling activation network does not significantly vary between MKS subsets. These observations suggest that self-renewal may be driven by alteration in the levels of signaling intermediates rather than alternate signal transduction architecture. We previously found that NRASG12V-mediated signals drive self-renewal in this AML model (Sachs Z. et al. Blood 2014). We used this model to ask which of these self-renewal-associated signaling molecules might be NRASG12V-regulated. We abolished NRASG12V transgene expression in these mice and harvested leukemia cells 72 hours later (per our standard lab protocol). Using this approach, found that self-renewal-associated signaling molecules, including NF-kB and β-catenin, are significantly reduced after NRASG12V-withdrawal indicating that NRASG12V -dependent signaling likely leads to the increase in these signaling molecules. In conclusion, we used mass cytometry analysis to identify the LSC self-renewal-associated signaling state in a murine model of AML and show that NRASG12V activates this signaling program. These data can be used to rationally design therapeutics such as small molecule inhibitors to target self-renewal-specific signaling and prevent relapse in AML. Disclosures No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2018
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    detail.hit.zdb_id: 80069-7
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