Literature DB >> 20381257

Pathway genetic load allows simultaneous evaluation of multiple genetic associations.

Ryan M Huebinger1, Harold R Garner, Robert C Barber.   

Abstract

OBJECTIVE: Despite the general success of genome-wide association studies, much heritability remains unidentified in many disease states. Some of this 'missing' heritability may lie in epistatic interactions among multiple loci, which are typically ignored. We utilized a method for simultaneous evaluation of epistatic interactions between allelic variations within genes confined to a single pathway, which we have termed as pathway genetic load (PGL).
METHODS: In separate analyses, we evaluated the risk for sepsis and for death associated with alleles at six loci in the TLR4 signaling and response pathway previously known or suspected to be linked to the development of sepsis after traumatic injury. We evaluated 155 patients with > or =15% TBSA burns and without significant non-burn trauma [ISS < or =16], traumatic or anoxic brain injury or spinal cord injury, who survived > 48 h post-admission. Clinical data were collected prospectively and candidate genotypes were determined by TaqMan assay.
RESULTS: After adjustment for burn size, inhalation injury, age, gender and race, PGL was associated with increased probability for complicated sepsis (aOR=1.59; 95%CI=1.11-2.29; p=0.011) and death (aOR=1.75; 95%CI=1.11-2.76; p=0.017).
CONCLUSION: Relative size and variability of aORs indicate greater power to detect genetic associations with PGL compared to the analysis of loci individually by multivariate logistic regression. 2010 Elsevier Ltd and ISBI. All rights reserved.

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Year:  2010        PMID: 20381257     DOI: 10.1016/j.burns.2010.02.001

Source DB:  PubMed          Journal:  Burns        ISSN: 0305-4179            Impact factor:   2.744


  6 in total

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2.  Improving genetic risk prediction by leveraging pleiotropy.

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Review 3.  Using biological knowledge to uncover the mystery in the search for epistasis in genome-wide association studies.

Authors:  Marylyn D Ritchie
Journal:  Ann Hum Genet       Date:  2011-01       Impact factor: 1.670

4.  Beyond missing heritability: prediction of complex traits.

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Journal:  PLoS Genet       Date:  2011-04-28       Impact factor: 5.917

Review 5.  Association between CD14 promoter -159C/T polymorphism and the risk of sepsis and mortality: a systematic review and meta-analysis.

Authors:  An-Qiang Zhang; Cai-Li Yue; Wei Gu; Juan Du; Hai-Yan Wang; Jianxin Jiang
Journal:  PLoS One       Date:  2013-08-19       Impact factor: 3.240

6.  A Hypothesis for Using Pathway Genetic Load Analysis for Understanding Complex Outcomes in Bilirubin Encephalopathy.

Authors:  Sean M Riordan; Douglas C Bittel; Jean-Baptiste Le Pichon; Silvia Gazzin; Claudio Tiribelli; Jon F Watchko; Richard P Wennberg; Steven M Shapiro
Journal:  Front Neurosci       Date:  2016-08-18       Impact factor: 4.677

  6 in total

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