====== TFE 2011-2012 (final year project) ======
[[tfe2011-2012|Back to list]]

===== A study of family-based genome-wide association analyses to identify important genetic risk factors for asthma-related phenotypes =====

The Human Genome Project and its spin-offs such as the Allele Frequency/Genotype
Project or the HapMap Project (The International HapMap Consortium 2003) are making
it increasingly feasible to disentangle the genetic basis of a given complex trait using
genome-wide association studies. The goal of genetic association studies is to explain
the variation in the disease trait of interest using an individual's genotype at a genetic
marker. These studies take advantage of the fact that we can measure genotypes directly,
either via protein electrophoretic or molecular genetic methods. Association analyses are
used in many settings: looking at the effects of markers in candidate genes, fine mapping
under linkage peaks and even whole genome scans.

To date, the most popular design choice for testing association between phenotype and
genotype is the case-control design based on unrelated individuals. Such a design does
not a priori protect against a spurious finding of association due to population admixture
or stratification. Moreover, parental genotype effects or imprinting effects can only be
investigated in an association analysis when parental information is included.
The work of Falk and Rubinstein (1987) revolutionized genetic association tests by
noting that valid tests, immune from confounding due to admixture, could be constructed
using parental genotype and the genotype data from their affected offspring. Since
then, several methods have been proposed for using family data (e.g., Terwilliger and
Ott 1992, Spielman et al. 1993). The most commonly used method of family-based
association tests is Spielman’s Transmission Disequilibrium Test (TDT; Spielman et al.
1993) in which alleles transmitted to affected offspring are compared with the expected
distribution of alleles among offspring. Since its conception, many generalizations to
the affected child (trio) setting with biallelic markers and the assumption of an additive
genetic model have been proposed (e.g., Sham and Curti 1995, Bickeboller and Clerget-
Darpoux 1995, Schaid and Li 1997, Rabinowitz and Laird 2000, Laird et al. 2000,
Horvath et al. 2001).

The topic of this thesis is to compare the power of genome-wide association screening
methods using non-parametric FBAT methodologies <http://www.biostat.harvard.edu/~fbat/default.html), and parametric modeling approaches, such as those available in the
ABEL suite (http://www.genabel.org/).

In practice, first both viewpoints for genome-wide association screening in family-based
designs need to be understood (key references in Van Steen et al 2011).
Second, a simulation study is set up, similar to Aulchenko et al (2007).
Third, improved GRAMMAR-like approaches (http://www.genabel.org/) are compared
with improved PBAT screening approaches (Van Steen et al 2005, Ionita-Laza et al 2007,
Won et al 2009).
Fourth, a real-life application is performed on available genome-wide asthma data.
Fifth, the results of both simulation study and real-life data application are put into a
broader framework (Van Steen 2011) and the thesis is drafted.

Depending on the progress made in this project, the work may lead to a genuine scientific
publication.

== Références: ==
 
  * Abecasis GR, Cardon LR, Cookson WOC (2000). A general test of association for quantitative traits in nuclear families. Am J Hum Genet 66, 279-292.
  * Aulchenko et al (2007) Grammar: a fast and simple method for genome-wide pedigree-based quantitative trait loci association analysis - 10.1534/genetics.107.075614
  * DeMeo DL, Lange C, Silverman EK, Senter JM, Drazen JM, Barth MJ, Laird NM, Weiss ST (2002) Univariate and multivariate family-based association analysis of the IL-13 ARG130GLN polymorphism in the Childhood Asthma Management Program. Genet Epi 23, 335-348.
  * Falconer DS and Mackay TFC. Introduction to quantitative genetics. Fourth Edition, Longman, Edinburgh 1997.
  * Fulker DW, Cherny SS, Sham PC, Hewitt JK (1999). Combined linkage and association analysis for quantitative traits. Am. J. Hum. Genet 64: 259-267.
  * Horvath S, Xu X, Laird NM (2001). The family based association test method: strategies for studying general genotype-phenotype associations. Eu. J Hum Genet 9, 301-306.
  * Ionita-Laza I, McQueen M, Laird N, Lange C. Genomewide weighted hypothesis testing in family-based association studies, with an application to a 100K scan. Am J Hum Genet 2007; 81(3):607-614.
  * Laird N, Horvath S and Xu X (2000). Implementing a unified approach to family based tests of association. Genetic Epi 19(Suppl 1), S36-S42.
  * Laird N, Kraft P, Lange C, Van Steen K (2004). Statistical methods in genetic epidemiology. In: Respiratory Genetics, Eds EK Silverman, SD Shapiro and ST Weiss.
  * Van Steen K, Mcqueen MB, Herbert A, Raby B, Lyon H, Demeo DL, Murphy A, Su J, Datta S, Rosenow C, Christman M, Silverman Ek, Laird NM, Weiss St, Lange C (2005) Genomic screening and replication using the same data set in family-based association testing, Nature Genetics 37 (7) 683 – 691.
  * Van Steen K (2011) Perspectives on Large-Scale Multi-Stage Family-Based Association Studies (invited paper) Statistics in Medicine DOI: 10.1002/sim.4259.
  * Won S, Bertram L, Becker D, Tanzi RE, Lange C. Maximizing the power of genome-wide association studies: a novel class of powerful family-based association tests. Statistics in Biosciences 2009; 1(2):125-143.

== Renseignements: ==  

[[http://www.montefiore.ulg.ac.be/~kvansteen/|Kristel Van Steen]] (<kristel.vansteen@ulg.ac.be>)