Person: Palmer, Nathan
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Palmer
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Nathan
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Palmer, Nathan
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Publication Early Detection of Poor Adherers to Statins: Applying Individualized Surveillance to Pay for Performance(Public Library of Science, 2013) Zimolzak, Andrew; Spettell, Claire M.; Fernandes, Joaquim; Fusaro, Vincent Alfred; Palmer, Nathan; Saria, Suchi; Kohane, Isaac; Jonikas, Magdalena Anna; Mandl, KennethBackground: Medication nonadherence costs $300 billion annually in the US. Medicare Advantage plans have a financial incentive to increase medication adherence among members because the Centers for Medicare and Medicaid Services (CMS) now awards substantive bonus payments to such plans, based in part on population adherence to chronic medications. We sought to build an individualized surveillance model that detects early which beneficiaries will fall below the CMS adherence threshold. Methods: This was a retrospective study of over 210,000 beneficiaries initiating statins, in a database of private insurance claims, from 2008-2011. A logistic regression model was constructed to use statin adherence from initiation to day 90 to predict beneficiaries who would not meet the CMS measure of proportion of days covered 0.8 or above, from day 91 to 365. The model controlled for 15 additional characteristics. In a sensitivity analysis, we varied the number of days of adherence data used for prediction. Results: Lower adherence in the first 90 days was the strongest predictor of one-year nonadherence, with an odds ratio of 25.0 (95% confidence interval 23.7-26.5) for poor adherence at one year. The model had an area under the receiver operating characteristic curve of 0.80. Sensitivity analysis revealed that predictions of comparable accuracy could be made only 40 days after statin initiation. When members with 30-day supplies for their first statin fill had predictions made at 40 days, and members with 90-day supplies for their first fill had predictions made at 100 days, poor adherence could be predicted with 86% positive predictive value. Conclusions: To preserve their Medicare Star ratings, plan managers should identify or develop effective programs to improve adherence. An individualized surveillance approach can be used to target members who would most benefit, recognizing the tradeoff between improved model performance over time and the advantage of earlier detection.Publication Gene expression analysis in Fmr1KO mice identifies an immunological signature in brain tissue and mGluR5-related signaling in primary neuronal cultures(BioMed Central, 2015) Prilutsky, Daria; Kho, Alvin T.; Palmer, Nathan; Bhakar, Asha L.; Smedemark-Margulies, Niklas; Margulies, David; Kong, Sek Won; Bear, Mark F.; Kohane, IsaacBackground: Fragile X syndrome (FXS) is a neurodevelopmental disorder whose biochemical manifestations involve dysregulation of mGluR5-dependent pathways, which are widely modeled using cultured neurons. In vitro phenotypes in cultured neurons using standard morphological, functional, and chemical approaches have demonstrated considerable variability. Here, we study transcriptomes obtained in situ in the intact brain tissues of a murine model of FXS to see how they reflect the in vitro state. Methods: We used genome-wide mRNA expression profiling as a robust characterization tool for studying differentially expressed pathways in fragile X mental retardation 1 (Fmr1) knockout (KO) and wild-type (WT) murine primary neuronal cultures and in embryonic hippocampal and cortical murine tissue. To study the developmental trajectory and to relate mouse model data to human data, we used an expression map of human development to plot murine differentially expressed genes in KO/WT cultures and brain. Results: We found that transcriptomes from cell cultures showed a stronger signature of Fmr1KO than whole tissue transcriptomes. We observed an over-representation of immunological signaling pathways in embryonic Fmr1KO cortical and hippocampal tissues and over-represented mGluR5-downstream signaling pathways in Fmr1KO cortical and hippocampal primary cultures. Genes whose expression was up-regulated in Fmr1KO murine cultures tended to peak early in human development, whereas differentially expressed genes in embryonic cortical and hippocampal tissues clustered with genes expressed later in human development. Conclusions: The transcriptional profile in brain tissues primarily centered on immunological mechanisms, whereas the profiles from cell cultures showed defects in neuronal activity. We speculate that the isolation and culturing of neurons caused a shift in neurological transcriptome towards a “juvenile” or “de-differentiated” state. Moreover, cultured neurons lack the close coupling with glia that might be responsible for the immunological phenotype in the intact brain. Our results suggest that cultured cells may recapitulate an early phase of the disease, which is also less obscured with a consequent “immunological” phenotype and in vivo compensatory mechanisms observed in the embryonic brain. Together, these results suggest that the transcriptome of cultured primary neuronal cells, in comparison to whole brain tissue, more robustly demonstrated the difference between Fmr1KO and WT mice and might reveal a molecular phenotype, which is typically hidden by compensatory mechanisms present in vivo. Moreover, cultures might be useful for investigating the perturbed pathways in early human brain development and genes previously implicated in autism. Electronic supplementary material The online version of this article (doi:10.1186/s13229-015-0061-9) contains supplementary material, which is available to authorized users.Publication The Drug Data to Knowledge Pipeline: Large-Scale Claims Data Classification for Pharmacologic Insight(American Medical Informatics Association, 2016) Homer, Mark L.; Palmer, Nathan; Bodenreider, Olivier; Cami, Aurel; Chadwick, Laura; Mandl, KennethIn biomedical informatics, assigning drug codes to categories is a common step in the analysis pipeline. Unfortunately, incomplete mappings are the norm rather than the exception with coverage values less than 85% not uncommon. Here, we perform this linking task on a nationwide insurance claims database with over 13 million members who were dispensed, according to National Drug Codes (NDCs), over 50,000 unique product forms of medication. The chosen approach employs Cerner Multum’s VantageRx and the U.S. National Library of Medicine’s RxMix. As a result, 94.0% of the NDCs were successfully mapped to categories used by common drug terminologies, e.g., Anatomical Therapeutic Chemical (ATC). Implemented as an SQL database and scripts, the approach is generic and can be setup for a new data set in a few hours. Thus, the method is a viable option for large-scale drug classification.Publication Integrative analysis of genetic data sets reveals a shared innate immune component in autism spectrum disorder and its co-morbidities(BioMed Central, 2016) Nazeen, Sumaiya; Palmer, Nathan; Berger, Bonnie; Kohane, IsaacBackground: Autism spectrum disorder (ASD) is a common neurodevelopmental disorder that tends to co-occur with other diseases, including asthma, inflammatory bowel disease, infections, cerebral palsy, dilated cardiomyopathy, muscular dystrophy, and schizophrenia. However, the molecular basis of this co-occurrence, and whether it is due to a shared component that influences both pathophysiology and environmental triggering of illness, has not been elucidated. To address this, we deploy a three-tiered transcriptomic meta-analysis that functions at the gene, pathway, and disease levels across ASD and its co-morbidities. Results: Our analysis reveals a novel shared innate immune component between ASD and all but three of its co-morbidities that were examined. In particular, we find that the Toll-like receptor signaling and the chemokine signaling pathways, which are key pathways in the innate immune response, have the highest shared statistical significance. Moreover, the disease genes that overlap these two innate immunity pathways can be used to classify the cases of ASD and its co-morbidities vs. controls with at least 70 % accuracy. Conclusions: This finding suggests that a neuropsychiatric condition and the majority of its non-brain-related co-morbidities share a dysregulated signal that serves as not only a common genetic basis for the diseases but also as a link to environmental triggers. It also raises the possibility that treatment and/or prophylaxis used for disorders of innate immunity may be successfully used for ASD patients with immune-related phenotypes. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1084-z) contains supplementary material, which is available to authorized users.Publication A Gene Expression Profile of Stem Cell Pluripotentiality and Differentiation Is Conserved across Diverse Solid and Hematopoietic Cancers(BioMed Central, 2012) Palmer, Nathan; Schmid, Patrick R; Berger, Bonnie; Kohane, IsaacBackground: Understanding the fundamental mechanisms of tumorigenesis remains one of the most pressing problems in modern biology. To this end, stem-like cells with tumor-initiating potential have become a central focus in cancer research. While the cancer stem cell hypothesis presents a compelling model of self-renewal and partial differentiation, the relationship between tumor cells and normal stem cells remains unclear. Results: We identify, in an unbiased fashion, mRNA transcription patterns associated with pluripotent stem cells. Using this profile, we derive a quantitative measure of stem cell-like gene expression activity. We show how this 189 gene signature stratifies a variety of stem cell, malignant and normal tissue samples by their relative plasticity and state of differentiation within Concordia, a diverse gene expression database consisting of 3,209 Affymetrix HGU133+ 2.0 microarray assays. Further, the orthologous murine signature correctly orders a time course of differentiating embryonic mouse stem cells. Finally, we demonstrate how this stem-like signature serves as a proxy for tumor grade in a variety of solid tumors, including brain, breast, lung and colon. Conclusions: This core stemness gene expression signature represents a quantitative measure of stem cell-associated transcriptional activity. Broadly, the intensity of this signature correlates to the relative level of plasticity and differentiation across all of the human tissues analyzed. The fact that the intensity of this signature is also capable of differentiating histological grade for a variety of human malignancies suggests potential therapeutic and diagnostic implications.