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A score test for genetic class-level association with nonlinear biomarker trajectories.
Qian, Jing; Nunez, Sara; Kim, Soohyun; Reilly, Muredach P; Foulkes, Andrea S.
Afiliação
  • Qian J; Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, MA, U.S.A.
  • Nunez S; Department of Mathematics and Statistics, Mount Holyoke College, South Hadley, MA, U.S.A.
  • Kim S; Department of Mathematics and Statistics, Mount Holyoke College, South Hadley, MA, U.S.A.
  • Reilly MP; Department of Medicine, Columbia University, New York, NY, U.S.A.
  • Foulkes AS; Department of Mathematics and Statistics, Mount Holyoke College, South Hadley, MA, U.S.A.
Stat Med ; 36(19): 3075-3091, 2017 Aug 30.
Article em En | MEDLINE | ID: mdl-28543585
ABSTRACT
Emerging data suggest that the genetic regulation of the biological response to inflammatory stress may be fundamentally different to the genetic underpinning of the homeostatic control (resting state) of the same biological measures. In this paper, we interrogate this hypothesis using a single-SNP score test and a novel class-level testing strategy to characterize protein-coding gene and regulatory element-level associations with longitudinal biomarker trajectories in response to stimulus. Using the proposed class-level association score statistic for longitudinal data, which accounts for correlations induced by linkage disequilibrium, the genetic underpinnings of evoked dynamic changes in repeatedly measured biomarkers are investigated. The proposed method is applied to data on two biomarkers arising from the Genetics of Evoked Responses to Niacin and Endotoxemia study, a National Institutes of Health-sponsored investigation of the genomics of inflammatory and metabolic responses during low-grade endotoxemia. Our results suggest that the genetic basis of evoked inflammatory response is different than the genetic contributors to resting state, and several potentially novel loci are identified. A simulation study demonstrates appropriate control of type-1 error rates, relative computational efficiency, and power. Copyright © 2017 John Wiley & Sons, Ltd.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biomarcadores / Estudos Longitudinais / Modelos Estatísticos / Polimorfismo de Nucleotídeo Único Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biomarcadores / Estudos Longitudinais / Modelos Estatísticos / Polimorfismo de Nucleotídeo Único Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article