Literature DB >> 15172664

Localization and identification of human quantitative trait loci: king harvest has surely come.

John Blangero1.   

Abstract

The scientific process of localization and subsequent identification of genes influencing risk of common diseases is still in its infancy. Initial localization of disease-related loci has traditionally been performed using family-based linkage methods to scan the genome. Early pronouncements of the failure of this approach for common diseases were premature and based on comparing suboptimal linkage designs with overly optimistic and empirically unproven association-based designs. On the contrary, substantial recent progress in the positional cloning of genes influencing such complex phenotypes suggests that modern approaches based around a family-based linkage paradigm will be successful. In particular, the rapidly growing emphasis on the analysis of the genetic basis of quantitative correlates of disease risk represents a novel and promising approach in which initial localization is performed using linkage and subsequent identification utilizes association approaches in positional candidate genes.

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Year:  2004        PMID: 15172664     DOI: 10.1016/j.gde.2004.04.009

Source DB:  PubMed          Journal:  Curr Opin Genet Dev        ISSN: 0959-437X            Impact factor:   5.578


  37 in total

1.  An application of the latent p value method to assess linkage in asthma pedigrees.

Authors:  Craig C Teerlink; Alun Thomas
Journal:  Hum Hered       Date:  2010-04-23       Impact factor: 0.444

2.  Increased level of linkage disequilibrium in rural compared with urban communities: a factor to consider in association-study design.

Authors:  Veronique Vitart; Andrew D Carothers; Caroline Hayward; Peter Teague; Nicholas D Hastie; Harry Campbell; Alan F Wright
Journal:  Am J Hum Genet       Date:  2005-03-24       Impact factor: 11.025

Review 3.  Neuroimaging endophenotypes: strategies for finding genes influencing brain structure and function.

Authors:  David C Glahn; Paul M Thompson; John Blangero
Journal:  Hum Brain Mapp       Date:  2007-06       Impact factor: 5.038

4.  Genomewide rapid association using mixed model and regression: a fast and simple method for genomewide pedigree-based quantitative trait loci association analysis.

Authors:  Yurii S Aulchenko; Dirk-Jan de Koning; Chris Haley
Journal:  Genetics       Date:  2007-07-29       Impact factor: 4.562

5.  GATTACA--are we there yet?

Authors:  Jeremy B M Jowett
Journal:  Nat Rev Endocrinol       Date:  2009-04       Impact factor: 43.330

Review 6.  Tilting at quixotic trait loci (QTL): an evolutionary perspective on genetic causation.

Authors:  Kenneth M Weiss
Journal:  Genetics       Date:  2008-08       Impact factor: 4.562

7.  Agreement among type 2 diabetes linkage studies but a poor correlation with results from genome-wide association studies.

Authors:  S Lillioja; A Wilton
Journal:  Diabetologia       Date:  2009-03-19       Impact factor: 10.122

8.  Association of genetic variation in ENPP1 with obesity-related phenotypes.

Authors:  Christopher P Jenkinson; Dawn K Coletta; Marion Flechtner-Mors; Shirley L Hu; Marcel J Fourcaudot; Lenore M Rodriguez; Jennifer Schneider; Rector Arya; Michael P Stern; John Blangero; Ravindranath Duggirala; Ralph A DeFronzo
Journal:  Obesity (Silver Spring)       Date:  2008-05-08       Impact factor: 5.002

Review 9.  Electrophysiological Endophenotypes for Schizophrenia.

Authors:  Emily M Owens; Peter Bachman; David C Glahn; Carrie E Bearden
Journal:  Harv Rev Psychiatry       Date:  2016 Mar-Apr       Impact factor: 3.732

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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