Literature DB >> 12730090

Genes, environment, and cardiovascular disease.

Charles F Sing1, Jari H Stengård, Sharon L R Kardia.   

Abstract

In this essay, we call to attention what every medical researcher knows about the etiology of cardiovascular disease but most deny, or choose to ignore, when designing, carrying out, and reporting genetic studies. Medical research is entering an era of synthesis that will take advantage of the successes of reductionism over the past decade in defining and describing human genome variations. Meaningful insights into the role of such variation requires a biological model of genome-phenotype relationships that incorporates interactions between subsets of possible genetic and environmental agents as causations in particular contexts indexed by time and space. We make recommendations for what needs to be done to cope with these complexities.

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Year:  2003        PMID: 12730090     DOI: 10.1161/01.ATV.0000075081.51227.86

Source DB:  PubMed          Journal:  Arterioscler Thromb Vasc Biol        ISSN: 1079-5642            Impact factor:   8.311


  75 in total

1.  Subgroups at high risk for ischaemic heart disease:identification and validation in 67 000 individuals from the general population.

Authors:  Ruth Frikke-Schmidt; Anne Tybjærg-Hansen; Greg Dyson; Christiane L Haase; Marianne Benn; Børge G Nordestgaard; Charles F Sing
Journal:  Int J Epidemiol       Date:  2014-10-30       Impact factor: 7.196

Review 2.  "Are we there yet?": Deciding when one has demonstrated specific genetic causation in complex diseases and quantitative traits.

Authors:  Grier P Page; Varghese George; Rodney C Go; Patricia Z Page; David B Allison
Journal:  Am J Hum Genet       Date:  2003-09-17       Impact factor: 11.025

3.  Public understanding of risks from gene-environment interaction in common diseases: implications for public communications.

Authors:  C M Condit; L Shen
Journal:  Public Health Genomics       Date:  2010-08-13       Impact factor: 2.000

4.  Buckley-James boosting for survival analysis with high-dimensional biomarker data.

Authors:  Zhu Wang; C Y Wang
Journal:  Stat Appl Genet Mol Biol       Date:  2010-06-08

5.  Common clinical practice versus new PRIM score in predicting coronary heart disease risk.

Authors:  Ruth Frikke-Schmidt; Anne Tybjærg-Hansen; Peter Schnohr; Gorm B Jensen; Børge G Nordestgaard
Journal:  Atherosclerosis       Date:  2010-07-27       Impact factor: 5.162

6.  Epistatic pleiotropy and the genetic architecture of covariation within early and late-developing skull trait complexes in mice.

Authors:  Jason B Wolf; Larry J Leamy; Eric J Routman; James M Cheverud
Journal:  Genetics       Date:  2005-07-14       Impact factor: 4.562

7.  The contribution of individual and pairwise combinations of SNPs in the APOA1 and APOC3 genes to interindividual HDL-C variability.

Authors:  C M Brown; T J Rea; S C Hamon; J E Hixson; E Boerwinkle; A G Clark; C F Sing
Journal:  J Mol Med (Berl)       Date:  2006-05-17       Impact factor: 4.599

8.  Machine learning for detecting gene-gene interactions: a review.

Authors:  Brett A McKinney; David M Reif; Marylyn D Ritchie; Jason H Moore
Journal:  Appl Bioinformatics       Date:  2006

9.  Heritability of carotid intima-media thickness: a twin study.

Authors:  Jinying Zhao; Faiz A Cheema; J Douglas Bremner; Jack Goldberg; Shaoyong Su; Harold Snieder; Carisa Maisano; Linda Jones; Farhan Javed; Nancy Murrah; Ngoc-Anh Le; Viola Vaccarino
Journal:  Atherosclerosis       Date:  2007-09-06       Impact factor: 5.162

Review 10.  Arguments for the sake of endophenotypes: examining common misconceptions about the use of endophenotypes in psychiatric genetics.

Authors:  David C Glahn; Emma E M Knowles; D Reese McKay; Emma Sprooten; Henriette Raventós; John Blangero; Irving I Gottesman; Laura Almasy
Journal:  Am J Med Genet B Neuropsychiatr Genet       Date:  2014-01-24       Impact factor: 3.568

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