Download Pharmacogenetics of response to antiresorptive therapy

Pharmacogenetics of response to
antiresorptive therapy:
Vitamin D receptor gene
Tuan V. Nguyen, Associate Professor
John A. Eisman, Professor and Director
Bone and Mineral Research Program
Garvan Institute of Medical Research
Sydney, Australia
Osteoporosis heterogenous pathophysiological mechanisms and
response to therapy
Variability in BMD = 0.12 x Mean
Variability in DBMD = 3 x Mean
Variability in response to therapy:
1-3 x Mean DBMD
5
450
Alendronate
Placebo
Probability of density (%)
400
No. of subjects
350
300
250
200
150
100
4
3
2
1
50
0
0
-14 -12 -10 -6
-4
-2
0
2
4
6
9
17
-40
Rate of change (%/year)
Nguyen et al, JBMR 1999
Average rate of BMD loss: -0.6  1.8 %/yr
-30
-20
-10
0
10
20
30
Percent change in lumbar spine BMD
Adapted from Cummings et al,
JAMA 1998
40
Individual vs average
Clinical
– efficacy and tolerance
– Duration
– new pharmacologic targets
Theoretical
– genetics of BMD
– genetics of BMD change
– environmental factors
Available data
genetic polymorphisms and response to antiresorptive
therapy
Genetics of BMD and body composition
rMZ
rDZ
H2 (%)
Lumar spine BMD
0.74 (0.06)
0.48 (0.10)
77.8
Femoral neck BMD
0.73 (0.06)
0.47 (0.11)
76.4
Total body BMD
0.80 (0.05)
0.48 (0.10)
78.6
Lean mass
0.72 (0.06)
0.32 (0.12)
83.5
Fat mass
0.62 (0.08)
0.30 (0.12)
64.8
Nguyen, et al, Am J Epidemiol 1998
VDR genotype and BMD
• VDR genotype and osteocalcin levels (PNAS, 1992)
• VDR genotype and BMD (Nature, 1994)
• Contentious association
• Meta-analysis: 15 cross-sectional, cohort studies
• Bayesian modelling
VDR genotype and lumbar spine BMD
Melhus H et al.
Melhus H et al.
Kroger H et al.
Kroger H et al.
Riggs BL et al.
Riggs BL et al.
Berg JP et al.
Berg JP et al.
Boschictsch et al.
Boschictsch et al.
Garneo P et al.
Garneo P et al.
Jorgensen HL et al.
Jorgensen HL et al.
Kiel et al.
Kiel et al.
McClure L et al.
McClure L et al.
Vandevyver C et al.
Vandevyver C et al.
Gennari L et al.
Gennari L et al.
Hansen TS et al.
Hansen TS et al.
Gornez C et al.
Gornez C et al.
Langdahl BL et al.
Langdahl BL et al.
Marc J et al.
Marc J et al.
Overall
Overall
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Effect size (bb vs BB)
1.5
2.0
-1.0
-0.5
0.0
0.5
Effect size (bb vs Bb)
1.0
1.5
Pooled effects of VDR genotype on BMD: Bayesian
analysis
bb - BB
bb - Bb
4.0
7
3.5
Probability of density (%)
Probability of density (%)
6
3.0
2.5
2.0
1.5
P |d >0| = 0.940
1.0
0.5
5
4
3
2
P |d > 0| = 0.80
1
0.0
-0.03 -0.02 -0.01
0.00
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0
-0.02
Absolute difference in lumbar spine BMD between bb and BB (g/cm2)
Overall difference: 14.7 (95% CI: 0.8 to 42.3) mg/cm2
-0.01
0.00
0.01
0.02
0.03
0.04
Absolute difference in lumbar spine BMD between bb and Bb (g/cm2)
Overall difference: 5.8 (95% CI: -6.5 to 18.0) mg/cm2
BsmI b allele associated with higher BMD
Model of drug response
Activity of other
biological systems
Drug effect
Target responsiveness
Drug concentration at
target
Drug
response
Adverse
reaction
Drug concentration at
other biological systems
Responsiveness at other
biological systems
Other predisposition
Adapted from Meisel, et al. J Mol Med 2003
Heritability of BMD change
• 21 MZ and 19 DZ twin pairs over 3 years
• Changes in lumbar spine BMD:
rMZ = 0.93 vs rDZ = 0.51
(Kelly et al. JBMR 1993; 8:11-7)
• 25 MZ and 21 DZ male twin pairs over 14 years
• Changes in distal radius BMD:
rMZ=0.61, rDZ=0.41 (NS)
(Christian, et al. 1989)
VDR genotype and BMD change
Significant association
No significant association
Rapuri, J Steroid Biochem & Mol Biol
2004
Gunnes, JCEM 1997
Garnero, JBMR 1996
Hansen, Bone 1998
Gomez, Osteoporosis Int 1999
Guardiola, Ann Int Med 1999
Gough, J Rheumatol 1998
Publication bias?
Deng, Hum Genet 1998
Zmuda, JBMR 1997
Ferrari, Lancet 1995
Krall, JBMR 1995
In “positive” studies, BsmI b allele associated with
lesser loss or greater increase in BMD
Inter-subject variability in response to
antiresorptive therapy
5
Alendronate
Probability of density (%)
Placebo
4
3
2
1
0
-40
-30
-20
-10
0
10
20
30
40
Percent change in lumbar spine BMD
Adapted from Cummings et al, JAMA 1998
Placebo: n=2218, mean change in LSBMD: 1.5 ± 8.1 %
Alendronate: n=2214, mean change in LSBMD: 8.3 ± 7.8 %
Pharmacogenetics of response to
antiresorptive treatments
• Few studies
• Candidate gene approach
VDR genotypes and response to Raloxifene Rx
BMD
Bone turnover markers
n=66 osteoporotic women; duration of Rx: 1 yr
Palomba et al. Human Reprod 2003; 18:192-8
VDR genotypes and response to Alendronate Rx
BMD
Bone
turnover
markers
n=68 osteoporotic women; duration of Rx: 1 yr
Palomba et al. Clin Endocrinol 2003; 58:365-71
VDR genotype and BMD response to treatment
ALN
RLX
HRT
9
9
8
8
7
7
ALN+RLX
ALN+HRT
9
9
8
8
7
7
6
6
5
5
4
4
3
3
2
2
6
6
5
5
4
4
3
3
2
2
1
1
0
0
BB
Bb
bb
BB
Bb
bb
1
1
BB
Bb
bb
Adapted from Palomba et al. Clin Endocrinol 2003; Hum
Reprod 2003; and Palomba et al, OI 2005 (Epub).
BB
Bb
bb
Genetic factors and response to
antiresorptive therapy
• Response to antiresorptive therapy is multifactorial
(VDR genotypes explained 5-10% of the variability)
• SNPs profile could allow individualization of
treatment
• Issues of study design and interpretation
Bayesian decision approach
SNP association studies:
Bayesian approach to decision
Alternatives
1. Abandon study
2. Continue data collection
3. Evidence strong enough for molecular exploration
Rationale for decision
True positive assoc. / False positive assoc. = 20/1
(NOT the same as p-value)
A hypothetical scenario
• 20 SNPs (out of 1000 SNPs) are actually
associated with BMD response to Rx
• Study power = 80% (i.e., type II error = 20%)
• Type I error = 5%
• Finding: Significant association for 1 SNP (P =
0.05)
• What is the probability that there is indeed an
association?
20 SNPs involved; Power = 80%; False +ve = 5%
1000 SNPs
Association (n=20)
a=5%
power=80%
Significant
N=16
No association (n=980)
Nonsignificant
Significant
(n=49)
Nonsignificant
True positive / False positive = 16/49
P(True association | Significant result) = 16/(16+49) = 25%
The need for lower P-value
About 25% of all findings with “p<0.05” should, if viewed in a scientifically
agnostic light, properly be regarded as nothing more than chance findings
(1).
• Proportion of significant associations depends on:
– p-value,
– overall proportion of hypotheses being tested are true
– statistical power
• For a ratio (true +ve) / (false +ve) association = 20:1, p-value should be
lowered by 400 times
• For a ratio (true +ve) / (false +ve) association = 50:1, p-value should be
lowered by 1000 times
(1) J Berger (1987); R Matthews (2001)
Bayesian resolution of conflicting finding
Change in LSBMD in response to ALN Rx: bb vs BB genotypes
Probability density
0.25
0.20
0.15
Current data
(D=-4.6%, Var=6.7)
0.10
Marc OI 1999
0.05
P(bb-BB>3%) = 0.01
0.00
0.25
0.20
Prior distribution
(D=4.1%, Var=0.4)
0.15
0.10
Palomba 2003, 2005
P(bb-BB>3%) = 0.91
0.05
0.00
0.25
0.20
Posterior distribution
(D=3.6%, Var=0.37)
0.15
0.10
P(bb-BB>3%) = 0.73
0.05
0.00
-20
-15
-10
-5
0
5
10
15
20
Genetic markers could allow identification of
those more or less likely to
– fracture
– respond to a specific treatment
– suffer side effects from a specific treatment
With cost-benefits in relation to intervention,
Bayesian method offers a powerful
approach to individualise inference
Acknowledgments
Nguyen D. Nguyen
Garvan Institute of Medical Research
Regia Congressi Organizing C’tee
Reserved slides
Misunderstanding of P-value
Bisphosphonate treatment was associated with a 5%
increase in BMD compared to placebo (p<0.05)
1. It has been proved that bisphosphonate is better
than placebo?
2. If the treatment has no effect, there is less than a
5% chance of obtaining such result
3. The observed effect is so large that there is less
than 5% chance that the treatment is no better
than placebo
4. I don’t know
60
52
50
Percent
40
30
20
19
15
15
10
0
1
2
Answer
3
4
1. Better treatment; 2. <5% chance of getting the result if there is no effect; 3. <5% due
to chance 4. I don’t know (Source: Wulff et al., Stat Med 1987; 6:3-10)
P value is NOT
• the likelihood that findings are due to chance
• the probability that the null hypothesis is true
given the data
• P-value is 0.05, so there is 95% chance that a real
difference exists
• With low p-value (p < 0.001) the finding must be
true
• The lower p-value, the stronger the evidence for
an effect
P-value
• Grew out of quality control during WWII
• Question: the true frequency of bad bullets is
1%, what is the chance of finding 4 or more bad
bullets if we test 100 bullets?
• Answer: With some maths (binomial theorem),
p=2%
So, p-value is the probability of getting a result as
extreme (or more extreme) than the observed value
given an hypothesis
Process of Reasoning
The current process of hypothesis testing is a “proof by
contradiction”
If the null hypothesis is true,
then the observations are
unlikely.
If Tuan has hypertension, then
he is unlikely to have
pheochromocytoma.
The observations occurred
Tuan has pheochromocytoma
______________________________________
______________________________________
Therefore, the null hypothesis
is unlikely
Therefore, Tuan is unlikely to
have hypertension
What do we want to know?
• Clinical
P(+ve | Diseased): probability of a +ve test given that the
patient has the disease
P(Diseased | +ve): probability of that the patient has the
disease given that he has a +ve test
• Research
P(Significant test | No association): probability that the test is
significant given that there is no association
P(Association | Significant test): probability that there is an
association given that the test statistic is significant
Diagnostic and statistical reasoning
Diagnosis
Research
Absence of disease
There is no real difference
Presence of disease
There is a difference
Positive test result
Statistical significance
Negative test result
Statistical non-significance
Sensitivity (true positive rate) Power (1-b)
False positive rate
P-value
Prior probability of disease
(prevalence)
Positive predictive value
Prior probability of research
hypothesis
Bayesian probability
For a given sample size, posterior
probability increases with p-value
1.0
Posterior Probability of Association
0.9
p = 0.0001
p = 0.001
0.8
0.7
0.6
0.5
p = 0.01
p = 0.05
0.4
0.3
0.2
0.1
0.0
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Prior Probability of Association
0.8
0.9
1.0
50
18
50
16
50
14
50
12
50
10
0
85
0
65
0
45
25
0
160
140
120
100
80
60
40
20
0
50
Number of studies
Distribution of sample sizes
Sample size
Ioannidis et al, Trends Mol Med 2003
Distribution of effect sizes
100
80
60
40
20
4
8
2.
2.
2
6
1.
8
0.
1.
2
5
0.
0
0
Number of studies
120
Effect size (OR)
Ioannidis et al, Trends Mol Med 2003
Correlation
between the odds
ratio in the first
studies and in
subsequent
studies
Ioannidis et al,
Nat Genet 2001
Evolution of
the strength of
an association
as more
information is
accumulated
Ioannidis et al,
Nat Genet 2001
Predictors of statistically significant discrepancies
between the first and subsequent studies of the same
genetic association
Odds ratio –
univariate
analysis
Predictor
Odds ratio –
multivariate
analysis
Total no. of studies (per
association)
1.17 (1.03, 1.33)
1.18 (1.02, 1.37)
Sample size of the first
study
0.42 (0.17, 0.98)
0.44 (0.19, 0.99)
Single first study with clear
genetic effect
9.33 (1.01, 86.3)
NS
Ioannidis et al, Nat Genet 2001