Literature DB >> 29417942

Full genetic analysis for genome-wide association study of Fangji: a powerful approach for effectively dissecting the molecular architecture of personalized traditional Chinese medicine.

Gang Chen1,2, Wen-da Xue1,2, Jun Zhu3.   

Abstract

Elucidation of the systems biology foundation underlying the effect of Fangji, which are multi-herbal traditional Chinese medicine (TCM) formulas, is one of the major aims in the field. The numerous bioactive ingredients of a Fangji deal with the multiple targets of a complex disease, which is influenced by a number of genes and their interactions with the environment. Genome-wide association study (GWAS) is an unbiased approach for dissecting the genetic variants underlying complex diseases and individual response to a given treatment. GWAS has great potential for the study of systems biology from the point of view of genomics, but the capacity using current analysis models is largely handicapped, as evidenced by missing heritability. Recent development of a full genetic model, in which gene-gene interactions (dominance and epistasis) and gene-environment interactions are all considered, has addressed these problems. This approach has been demonstrated to substantially increase model power, remarkably improving the detection of association of GWAS and the construction of the molecular architecture. This analysis does not require a very large sample size, which is often difficult to meet for a GWAS of treatment response. Furthermore, this analysis can integrate other omic information and allow for variations of Fangji, which is very promising for Fangjiomic study and detection of the sophisticated molecular architecture of the function of Fangji, as well as for the delineation of the systems biology of personalized medicine in TCM in an unbiased and comprehensive manner.

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Year:  2018        PMID: 29417942      PMCID: PMC6256273          DOI: 10.1038/aps.2017.137

Source DB:  PubMed          Journal:  Acta Pharmacol Sin        ISSN: 1671-4083            Impact factor:   6.150


  56 in total

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Journal:  Eur J Hum Genet       Date:  2011-03-30       Impact factor: 4.246

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Journal:  Gastroenterology       Date:  2016-12-30       Impact factor: 22.682

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Journal:  Genet Epidemiol       Date:  2017-07-10       Impact factor: 2.135

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10.  Mixed Linear Model Approaches of Association Mapping for Complex Traits Based on Omics Variants.

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  4 in total

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2.  Integrated Pharmacogenetics Analysis of the Three Fangjis Decoctions for Treating Arrhythmias Based on Molecular Network Patterns.

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4.  Pharmacokinetics of Active Ingredients of Salvia miltiorrhiza and Carthamus tinctorius in Compatibility in Normal and Cerebral Ischemia Rats: A Comparative Study.

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Journal:  Eur J Drug Metab Pharmacokinet       Date:  2020-04       Impact factor: 2.441

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