multivariate analysis
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Mechanisms and consequences of cerebrovascular dysfunction in preeclampsia
PROJECT SUMMARY/ABSTRACT Preeclampsia (PE) is a common hypertensive disorder of pregnancy that causes significant maternal and fetal morbidity and mortality worldwide. PE women are at a high risk of stroke, including intracerebral hemorrhage, during the peripartum period, suggesting the sequelae of PE adversely impacts the cerebral circulation to promote hemorrhage. In addition, women with severe early-onset PE are at an 85-fold increased risk of death from intracerebral hemorrhage, importantly suggesting severity of disease promotes greater vulnerability of the cerebral circulation to degradation and rupture. However, the consequences of PE extend far beyond pregnancy and are associated with excessive cardiovascular and cerebrovascular disease risk later in life. Women with previous pregnancy complicated by PE can develop cognitive impairment as early as in their 30’s and 40’s, suggesting PE predisposes the brain to early-onset cognitive impairment. Studies have shown that formerly PE women have changes in gray matter volume and increased white matter lesion burden that occurs as a function of time from pregnancy, suggesting that PE continues to progressively damage the brain long after the affected pregnancy. Thus, our overall goal is to elucidate mechanisms by which women with PE are at risk of intracerebral hemorrhage in pregnancy and cognitive decline later in life. Our preliminary studies found greater vascular degradation, hematoma and cerebral edema in a model of severe PE that was associated with vascular inflammation and microglia activation (neuroinflammation). In addition, we found endothelial dysfunction and diminished neurovascular coupling in PE rats that persisted 5 months postpartum. Impaired neurovascular coupling is well-recognized as an underlying contributor to cognitive decline. These effects in postpartum animals with previous exposure to PE were associated with memory impairment that was not present in the pregnant state, suggesting neurovascular dysfunction precedes cognitive decline. Our central hypothesis is that the sequela of PE accelerates hypertension-induced cerebrovascular dysfunction that predisposes to intracerebral hemorrhage during pregnancy and its persistence postpartum results in early-onset cognitive decline. We will therefore elucidate mechanisms by which PE accelerates vascular degradation and worsens outcome from hemorrhagic stroke, probing pathways involved in oxidative degradative processes using multi-omics and multivariate analysis (Aim 1). We will also determine underlying molecular mechanisms that cause persistent cerebral microvascular dysfunction and cognitive decline postpartum, including oxidative stress-induced BBB leakage and persistent neuroinflammation that drives potassium channel dysfunction, reduced neurovascular coupling and neurovascular uncoupling (Aim 2). We will also use machine learning approaches together with multi-omics and outcome measures to identify factors and cellular pathways that are most impactful for prediction of intracerebral hemorrhage and cognitive impairment. The ability to predict and prevent devasting neurovascular disorders associated with PE has the potential to have long-lasting impacts on the lives of women with PE.
Targeting subtype specification as a driver of PDAC health disparities
PROJECT SUMMARY Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease that is refractory to current treatment strategies due in part to adaptive mechanisms of chemoresistance. Racial health disparities also confound the treatment and care of these patients. Blacks (people with African genetic ancestry) have significantly higher incidence rates of PDAC and decreased survival times compared to Caucasians (White genetic ancestry) even after socioeconomic status and tumor stages are controlled. Therefore, it is possible different racial groups exhibit unique molecular characteristics in PDAC tumors that contribute to these health disparities. The unique molecular characteristics that distinguish PDAC tumors between racial groups exhibiting disparities have the potential to identify new therapeutic targets. In a previous study, we identified 4 distinct subtypes of PDAC (Metabolic, Progenitor-like, Proliferative, and Inflammatory) that can be distinguished using multivariate analysis of quantitative proteomic data. While these PDAC subtypes are predictive of therapeutic response, this has not yet been analyzed in disparity factor balanced studies. We have examined the proteomes of primary PDAC tumors using quantitative mass spectrometry and identified unique protein signatures for Blacks and Whites. PDAC tumors from Black patients display features consistent with the Inflammatory subtype of PDAC, which is characterized by an inflamed microenvironment expressing complement proteins that can promote resistance to chemotherapy. Therefore, it is possible that race influences subtype and Blacks could preferentially develop the more aggressive and treatment refractory Inflammatory subtype. Strategies are needed to modulate subtype to improve response to chemotherapy. Toward this goal, our proteomic analysis identified polycomb repressor complex 1 (PRC1) protein RNF2 as being upregulated in PDACs from Blacks compared to Whites. We have also discovered that RNF2 regulates mRNA expression of the PDAC subtype specification factor GATA6 and inhibiting RNF2 promotes a molecular shift toward the more chemosensitive Classical subtype of PDAC. Therapeutic targeting can be achieved with Tazemetostat that inhibits the upstream PRC2 to prevent RNF2 binding the GATA6 promoter leading to its increased expression. Additionally, the Inflammatory subtype characterized by innate immune complement protein activation could be targeted with another FDA approved drug, Avacopan, which has not previously been studied in PDAC. Therefore, the Specific Aims of this proposal are designed to: 1) Evaluate the extent to which Tazemetostat treatment impacts chemotherapy-induced subtype plasticity in patient derived organoids; and 2) To determine the extent to which strategies targeting pathways associated with PDAC disparities affect progression and subtype characteristics in vivo. The successful completion of these aims has the potential to be moved quickly into phase I clinical trials since both Tazemetostat and Avacopan are FDA approved drugs. Furthermore, if successful, this project has the potential to mitigate health disparities in PDAC and broadly improve patient outcomes by implementing new precision interventions. The mouse models we propose faithfully recapitulate pancreatic cancer's clinical syndrome, histopathology and molecular properties, including the often-unique features of the stromal and immune responses that constitute the complex desmoplasia of this disease, which cannot be addressed using in vitro model systems
GED: A flexible family of versatile methods for hypothesis-driven multivariate decompositions
Does that title put you to sleep or pique your interest? The goal of my presentation is to introduce a powerful yet under-utilized mathematical equation that is surprisingly effective at uncovering spatiotemporal patterns that are embedded in data -- but that might be inaccessible in traditional analysis methods due to low SNR or sparse spatial distribution. If you flunked calculus, then don't worry: the math is really easy, and I'll spend most of the time discussing intuition, simulations, and applications in real data. I will also spend some time in the beginning of the talk providing a bird's-eye-view of the empirical research in my lab, which focuses on mesoscale brain dynamics associated with error monitoring and response competition.
Utilizing Random Forest for Multivariate Analysis: Exploring the Influence of Dopaminergic Neurons on Drosophila Larvae Locomotion
Bernstein Conference 2024
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