Download Why haplotype analysis is not critical in genome wide association studies Derek Gordon

Why haplotype analysis is not
critical in genome wide
association studies
Derek Gordon
Department of Genetics
Rutgers University
Piscataway, NJ
[email protected]
Acknowledgements
• Conference organizers and participants
– Dr. Kui Zhang, Dr. David Allison, Dr. Hemant Tiwari,
Dr. Jung-Ying Tzeng, Mr. Richard Sarver
– Dr. Dan Schaid (The Pro)
– Dr. Mike Province (The Provocateur)
• Rutgers University
– Dr. Steve Buyske
• Rockefeller University
– Dr. Jürg Ott
Terminology
Locus
– Particular position, point, or place
– Specific identifiable location on a
chromosome
Allele
– Alternative forms of the same
gene
– Specific DNA sequence at a locus
Polymorphic/polymorphism
Genotype
gggatc
Allele 1
gggctc
Allele 2
P
M
Locus
1
A
or
Genotype:
2
C
– Specific alleles at each locus
Haplotype
– Specific alleles at many loci on
the same chromosome
Haplotype:
1 1 2
2 2 4
Terminology
Locus
– Particular position, point, or place
– Specific identifiable location on a
chromosome
gggatc
Allele 1
gggctc
Allele 2
P
M
Locus
Polymorphism consisting of single base
pair change is called a Single Nucleotide
Polymorphism (SNP).
Question
• What are reasons for not using haplotypes
in genetic association analysis?
Some answers
• Curse of dimensionality
– Temptation to simplify analysis.
• Determining correct haplotype?
• Biologically speaking, the SNP’s the thing!
Do haplotypes provide statistical power gain over
single marker tests for genetic association?
NOT NECESSARILY!
• Example -SNP that
has two alleles,
disease-causing (D)
and wild-type (+).
Frequencies in case
and control
populations are given
in table at right.
Allele
Case
Freq
Control
Freq
D
0.1
0.05
+
0.9
0.95
Haplotype frequencies
Haplotype
Case Freq
H1(containing
0.10
disease mutation)
h2 (Middle
p
haplotype freq)
h3
1 - p - 0.10
Control Freq
0.05
p + 0.025
1 - p - 0.075
Do haplotypes provide statistical power
gain over single marker tests for
genetic association?
Statistical tests – Chi-square test of association on
alleles (1 degree of freedom) or haplotypes (2
degrees of freedom).
Compute minimum sample size for each test to
detect association with 80% power at 10E-07
significance level.
Efficiency = (Minimum Sample Size for Haplotype
test)/(Minimum Sample Size for Allele Test).
Middle Haplotype Frequency in Cases (p )
0.
8
0.
84
0.
88
0.
64
0.
68
0.
72
0.
76
0.
6
0.
4
0.
44
0.
48
0.
52
0.
56
0.
2
0.
24
0.
28
0.
32
0.
36
0.
04
0.
08
0.
12
0.
16
0
Efficiency
1.2
1
0.8
0.6
0.4
0.2
0
Example – Alzheimer’s Disease
One of the most well-documented and
replicated results of a risk locus for late
onset Alzheimer’s Disease (AD) is the
APOE gene on Chromosome 19.
There are three alleles at this locus,
labeled ε2, ε3, and ε4. The last (ε4) is the
risk allele for the AD.
Fallin et al. (2001) Genome Res Vol.
11, Issue 1: 143-151 (Part of Table 3)
Likelihood ratio test using haplotypes that
flank (but do not include) SNPs in APOE
gene is 45.64.
Haplotype results less significant than
single locus tests
LRT value of 45.64 is smaller (and therefore,
less significant) than value of 50.45 for
SNP in APOE gene.
Martin et al. (2000) : Am J Hum
Genet. 67(2):383-94 (Figure 2).
• Curse of dimensionality
– Temptation to simplify analysis.
• Determining correct haplotype?
• Biologically speaking, the SNP’s the thing!
Hierarchical clustering to reduce
“curse of dimensionality”
Example – Hoehe et al. (Hum Mol Genet.
2000 Nov 22;9(19):2895-908) estimated
52 haplotypes in African American cases
and controls when testing for association
of substance dependence with mu-opioid
receptor gene.
Hoehe et al. table of haplotypes
Hierarchical clustering to reduce
“curse of dimensionality”
The large number of haplotypes made for
difficult interpretation and for power loss.
The authors proposed a hierarchical
clustering method to reduce degrees of
freedom by grouping similar haplotypes
together.
Clustering yielded a minimum p-value of
0.017 at 20th step (2 haplotype classes)
Correction for correlated tests
Levenstien et al. (BMC Bioinformatics. 2003
Dec 11;4:62) applied permutation methods
to the Hoehe et al. data, replicating the
clustering application in each permuted
data set.
The findings were that the minimum p-value
less than or equal to 0.017 occurred in
almost 70% of the permuted data sets.
Correction for correlated tests
In other words, the p-value of the minimum
p-value was 0.70, indicating no significant
association among haplotypes and
substance abuse.
This example points out risks of ad hoc (and
invalid) statistical analyses that are
necessarily developed to address the
dimensionality problem with haplotypes.
• Curse of dimensionality
– Temptation to simplify analysis.
• Determining correct haplotype?
• Biologically speaking, the SNP’s the thing!
Can we determine correct
haplotypes for individuals?
PLoS Genet. 2006 August; 2(8): e127.
Results of haplotype-pair
misclassification
• For genes with substantial amount of
recombination, some haplotype pairs had
100% misclassification rates for SNPHAP
program and nearly 100%
misclassification rates for PHASE
program.
• Curse of dimensionality
– Temptation to simplify analysis.
• Determining correct haplotype?
• Biologically speaking, the SNP’s the thing!
The SNP’s the thing!
Genotypes are the more biologically relevant
units of measurement for genetic
association of genetic traits.
Three base-pair code for
determining Amino Acids
Types of mutations
www.ucl.ac.uk/~ucbhjow/b241/images/mutation.gif
Types of mutations
(deletion of single
base pair)
www.ucl.ac.uk/~ucbhjow/b241/images/mutation.gif
If we type the SNP and only the SNP that
causes the change in phenotype (e.g.,
missense, nonsense, or frameshift
mutations), with sufficiently large sample
size, we can determine the location of the
mutation without haplotype analysis.
Science 2005 Apr 15;308(5720):385-9.
Only single locus SNP tests used to
map AMD in Klein et al. study (Figure
1A).
Nat Med (2008) Epub April 20.
Authors sequenced GRK2 and GRK5 genes
(no haplotyping) and found non-silent basepair change in GRK5 gene, resulting in two
alleles: GRK5-Q41 (non-protective against
heart failure) and GRK5-L41 (protective
against heart failure).
Survival curves for subjects with GRK5-Q41 allele using
beta-blockers and subjects with GRK5-L41 allele not using
beta-blockers (Figure 3c – Liggett et al).
To summarize
• Haplotype analysis increases the
complexity of the analysis, in terms of the
number of haplotypes introduced, the
assumptions required, and the
interpretation of the analysis.
• Determination of correct haplotype is
problematic.
• Biological relevance of haplotypes?
Finally…
Will we even need haplotype
analysis in the future?
Can we always type the
causative locus?
In the near future, YES!
Science
(2008), Vol
311, pg
1544.
Importance of typing causative
SNP (PAWE-3D Website)