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Institution

National Jewish Health

HealthcareDenver, Colorado, United States
About: National Jewish Health is a healthcare organization based out in Denver, Colorado, United States. It is known for research contribution in the topics: T cell & Asthma. The organization has 883 authors who have published 833 publications receiving 79201 citations. The organization is also known as: National Jewish Medical and Research Center.
Topics: T cell, Asthma, Population, Lung, Antigen


Papers
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Posted ContentDOI
20 Aug 2018-bioRxiv
TL;DR: This paper proposes the variant-Set Mixed Model Association Tests (SMMAT) for continuous and binary traits using the generalized linear mixed model framework and shows that all the proposed SMMAT tests correctly control type I error rates for both continuous andbinary traits in the presence of population structure and relatedness.
Abstract: With advances in Whole Genome Sequencing (WGS) technology, more advanced statistical methods for testing genetic association with rare variants are being developed. Methods in which variants are grouped for analysis are also known as variant-set, gene-based, and aggregate unit tests. The burden test and Sequence Kernel Association Test (SKAT) are two widely used variant-set tests, which were originally developed for samples of unrelated individuals and later have been extended to family data with known pedigree structures. However, computationally-efficient and powerful variant-set tests are needed to make analyses tractable in large-scale WGS studies with complex study samples. In this paper, we propose the variant-Set Mixed Model Association Tests (SMMAT) for continuous and binary traits using the generalized linear mixed model framework. These tests can be applied to large-scale WGS studies involving samples with population structure and relatedness, such as in the National Heart, Lung, and Blood Institute9s Trans-Omics for Precision Medicine (TOPMed) program. SMMAT tests share the same null model for different variant sets, and a virtue of this null model, which includes covariates only, is that it needs to be only fit once for all tests in each genome-wide analysis. Simulation studies show that all the proposed SMMAT tests correctly control type I error rates for both continuous and binary traits in the presence of population structure and relatedness. We also illustrate our tests in a real data example of analysis of plasma fibrinogen levels in the TOPMed program (n = 23,763), using the Analysis Commons, a cloud-based computing platform.

3 citations

Journal ArticleDOI
TL;DR: Active engagement and monitoring of SDB and insomnia will often be necessary to achieve optimal outcomes, and aggressive treatment of insomnia prior to or in combination with SDB treatment may be particularly indicated in situations where insomnia is suspected to interfere with diagnosis or treatment.
Abstract: Sufficient evidence has accumulated to warrant conceptualization of comorbid insomnia and sleep disordered breathing (SDB) as a distinct clinical syndrome. As such, diagnostic and treatment approaches should be founded on an integrated and multidisciplinary approach with equivalent clinical attention and priority given to both insomnia and respiratory aspects of patients’ presenting complaints. Several well established and effective treatments exist for both insomnia and SDB. Although questions of optimal treatment combination and sequence remain to be examined, current evidence provides preliminary guidance regarding the sequential or concurrent management of insomnia and sleep disordered breathing when comorbid. Unsatisfactory response to pharmacotherapy or cognitive-behavioral therapy for chronic insomnia should trigger evaluation for comorbid sleep-related breathing disturbance prior to more aggressive or off label pharmacotherapy. Presence and course of insomnia symptoms should be monitored closely in SDB patients with persistence of insomnia symptoms following SDB treatment prompting targeted treatment of insomnia. Aggressive treatment of insomnia prior to or in combination with SDB treatment may be particularly indicated in situations where insomnia is suspected to interfere with diagnosis or treatment of SDB. Insomnia and sleep disordered breathing appear to uniquely contribute to the morbidity of patients with this comorbidity. With this in mind, active engagement and monitoring of SDB and insomnia will often be necessary to achieve optimal outcomes.

3 citations

Journal ArticleDOI
TL;DR: The differences between two methodologies for threshold detection of added resistive loads in children and adolescents using a servo-controlled cone that occluded an aperture to varying degrees are reported.
Abstract: This paper reports the differences between two methodologies for threshold detection of added resistive loads in children and adolescents. The first-generation apparatus utilized a series of laminar flow screens to present various total resistances, while in the second generation the apparatus utilized a servo-controlled cone that occluded an aperture to varying degrees. Protocol modifications in the second generation methodology included forced choice, attentional enhancements, and larger increments of added resistance. Two studies conducted 2 years apart provided data on the first and second generations of methodology. All participants in Study 1 (N = 33) and Study 2 (N = 33) were children with asthma. Subjects were matched for both age and asthma severity. Results showed the methodologic improvements in the second generation to be significant. Tracking and random thresholds were achieved by 85% and 82% of the subjects in Study 2 compared to 76% and 42% in Study 1, respectively. The correlation...

3 citations


Authors

Showing all 901 results

NameH-indexPapersCitations
Thomas V. Colby12650160130
John W. Kappler12246457541
Donald Y.M. Leung12161450873
Philippa Marrack12041654345
Jeffrey M. Drazen11769352493
Peter M. Henson11236954246
David A. Schwartz11095853533
David A. Lynch10871459678
Norman R. Pace10129750252
Kevin K. Brown10038747219
Stanley J. Szefler9955437481
Erwin W. Gelfand9967536059
James D. Crapo9847337510
Yang Xin Fu9739033526
Stephen D. Miller9443330499
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20233
202214
202113
202017
201917
201841