Literature DB >> 15811251

Complex phenotypes and complex genetics: an introduction to genetic studies of complex traits.

John W Belmont1, Suzanne M Leal.   

Abstract

There is currently intense interest in the genetic factors contributing to many diseases with cardiovascular complications. Diseases like atherosclerosis, diabetes, and hypertension are referred to as complex traits because multiple genes contribute to the phenotype either individually or through interactions with each other or the environment. Enabled and energized by the striking successes over the past 20 years in identifying genes that are responsible for single gene traits, many geneticists have turned to the investigation of methods that will allow for the dissection of complex traits. There have already been some successes, so there is no reason to consider the problem as inherently intractable. However, it is important to reflect on what conditions are necessary for the identification of genes that operate in complex traits. A recurring theme in this research area has been difficulty in repeating and validating research findings, and this most often can be attributed to limitations in study design. It is also important to consider that any particular research strategy can only hope to describe a portion of factors that contribute to variation in the population; therefore, the genetic approach cannot be a panacea. New efficient technologies for genotyping and public databases describing the fine structure of genetic correlations in the genome should aid many aspects of the gene discovery process.

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Year:  2005        PMID: 15811251     DOI: 10.1007/s11883-005-0004-6

Source DB:  PubMed          Journal:  Curr Atheroscler Rep        ISSN: 1523-3804            Impact factor:   5.113


  81 in total

1.  Multiplex relative risk and estimation of the number of loci underlying an inherited disease.

Authors:  Paul Schliekelman; Montgomery Slatkin
Journal:  Am J Hum Genet       Date:  2002-11-21       Impact factor: 11.025

2.  Multiplexed genotyping with sequence-tagged molecular inversion probes.

Authors:  Paul Hardenbol; Johan Banér; Maneesh Jain; Mats Nilsson; Eugeni A Namsaraev; George A Karlin-Neumann; Hossein Fakhrai-Rad; Mostafa Ronaghi; Thomas D Willis; Ulf Landegren; Ronald W Davis
Journal:  Nat Biotechnol       Date:  2003-05-05       Impact factor: 54.908

Review 3.  Estimating recombination rates from population-genetic data.

Authors:  Michael P H Stumpf; Gilean A T McVean
Journal:  Nat Rev Genet       Date:  2003-12       Impact factor: 53.242

4.  Ignoring linkage disequilibrium among tightly linked markers induces false-positive evidence of linkage for affected sib pair analysis.

Authors:  Qiqing Huang; Sanjay Shete; Christopher I Amos
Journal:  Am J Hum Genet       Date:  2004-10-18       Impact factor: 11.025

Review 5.  The relative power of family-based and case-control designs for linkage disequilibrium studies of complex human diseases I. DNA pooling.

Authors:  N Risch; J Teng
Journal:  Genome Res       Date:  1998-12       Impact factor: 9.043

6.  Parametric and nonparametric linkage analysis: a unified multipoint approach.

Authors:  L Kruglyak; M J Daly; M P Reeve-Daly; E S Lander
Journal:  Am J Hum Genet       Date:  1996-06       Impact factor: 11.025

Review 7.  The TDT and other family-based tests for linkage disequilibrium and association.

Authors:  R S Spielman; W J Ewens
Journal:  Am J Hum Genet       Date:  1996-11       Impact factor: 11.025

8.  The family based association test method: strategies for studying general genotype--phenotype associations.

Authors:  S Horvath; X Xu; N M Laird
Journal:  Eur J Hum Genet       Date:  2001-04       Impact factor: 4.246

Review 9.  Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease.

Authors:  David Botstein; Neil Risch
Journal:  Nat Genet       Date:  2003-03       Impact factor: 38.330

10.  Organizational challenges in clinical genomic research.

Authors:  Jill S Altshuler; David Altshuler
Journal:  Nature       Date:  2004-05-27       Impact factor: 49.962

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  3 in total

1.  Curve-based multivariate distance matrix regression analysis: application to genetic association analyses involving repeated measures.

Authors:  Rany M Salem; Daniel T O'Connor; Nicholas J Schork
Journal:  Physiol Genomics       Date:  2010-04-27       Impact factor: 3.107

2.  Polymorphisms of glutathione S-transferase M1, T1 and P1 in patients with reflux esophagitis and Barrett's esophagus.

Authors:  Zdenek Kala; Jiří Dolina; Filip Marek; Lydie Izakovicova Holla
Journal:  J Hum Genet       Date:  2007-05-03       Impact factor: 3.172

3.  Allelic polymorphism within the TAS1R3 promoter is associated with human taste sensitivity to sucrose.

Authors:  Alexey A Fushan; Christopher T Simons; Jay P Slack; Ani Manichaikul; Dennis Drayna
Journal:  Curr Biol       Date:  2009-06-25       Impact factor: 10.834

  3 in total

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